doctoral thesis 2
TRANSCRIPT
Doctoral Thesis
The Role of Innovation Policy and Science
Communication in Accepting New Food Technology
September 2020
Doctoral Program in Technology Management
Graduate School of Technology Management
Ritsumeikan University
Mohamed Farid
Doctoral Thesis Reviewed
by Ritsumeikan University
The Role of Innovation Policy and Science
Communication in Accepting New Food Technology
(食品に関する新技術受容のイノベーション政策と
科学コミュニケーションの役割)
September 2020 2020 年 9 月
Doctoral Program in Technology Management Graduate School of Technology Management
Ritsumeikan University
立命館大学大学院テクノロジー・マネジメント研究科
テクノロジー・マネジメント専攻博士課程後期課程
Mohamed Farid
モハメド ファリド
Supervisor: Associate Professor KODAMA Kota
研究指導教員: 児玉 耕太准教授
Declaration
I, Mohamed Farid, herby in this document, declare that my own research work stated in
this thesis has never been used to obtain any academic degree from any other university than
Ritsumeikan university. However, some parts of the research results stated in this thesis may have
been published before by me in scientific journals during the course of this doctoral program study
as part of the publication requirements of obtaining a doctoral degree from Ritsumeikan
University.
M. Farid
June 2020
Abstract
Innovation policy provides an integrated interface between academic research,
technological development, as well as the industrial policy in order to create an inclusive
contributory framework that promotes innovation and solves several societal challenges. Several
governmental entities in Japan, especially METI and MEXT, are thriving to provide innovation
policies that can help developing concrete solutions to several challenges that can be scaled
nationwide in Japan as well as globally. The approach of the respected entities above has moved
forward to influence also other governmental entities to take the same approach, such as MHLW,
MAFF, and CAA.
One of the most pressing challenges globally is hunger and undernourishment, where
nearly 26% of the global population suffer from different levels of food insecurity. In Japan,
although there is a low level of food insecurity, however, Japan is facing a different type of
challenges related to agriculture and food self-sufficiency. The food production in Japan has
dropped from 79% in 1960 to nearly 37% in 2018. With the existence of other social challenges
in Japan, such as the aging population, which followed by the rapid increase of the national medical
care expenditure, Japan has taken several measures and stated policies related to innovation in the
food technologies that can tackle the challenges mentioned above.
Therefore, this research has been formulated to explore further the ability of Japan to grow
in food-related technologies, especially functional food, and genetically edited food. The approach
to achieve the research aim is to study the regulations further and create a comparison between the
regulations in Japan and globally to spot the strong points that can help boost innovative food
industries in Japan. This research helps in providing an answer to three main research questions
namely; what are the key differences in terms of functional food regulations between Japan and
overseas, what are the key differences in terms of genetically edited food regulations between
Japan and overseas, and what are the factors affecting the genetically edited food acceptance. The
research has utilized a qualitative approach to answer the first and second research questions,
where the third was tackled by the quantitative approach represented in the structural equation
modeling technique.
In terms of function food, after analyzing the regulations in Japan in comparison with the
regulations in the USA, EU, China, Korea, Taiwan, and Singapore. It was found that regulations
in Japan, especially FFC regulation, is becoming the primary regulation in this field, and it is
promoting innovation and the inclusiveness of SMEs as well as the large corporations.
In terms of genetically edited food regulations, after comparing the regulations in Japan in
comparison with regulations in EU and USA, it was also found that the regulations in Japan are
the most encouraging for innovation in this field, since that it does not require further inspection
and labeling process, unlike GMOs. However, the dilemma remains to explore whether consumers
in Japan are willing to adopt genetically edited food products in the future. To tackle this part, an
SEM analysis was conducted by 180 responses examining six factors. The survey was conducted
twice with an intervention in the middle in the form of a presentation to increase the awareness of
genetically edited food. The analysis shows a significant difference in all the factors when
comparing the results before and after the intervention, which emphasizes the role of science
communication in enhancing awareness and increasing the acceptance level.
Overall, the research has emphasized the role of science communication and regulatory
science, in promoting the industry, as well as the role of innovation policy and the collaboration
between different parties to promote innovation in different fields.
Acknowledgment
I would like to express my sincere gratitude to my research supervisor, Prof. Dr. Kodama,
for his massive contribution and continued support to conduct this research. During the doctoral
program, Prof. Kodama has supported me in becoming a better scientific researcher and provided
guidance and support in every way possible.
I would like to sincerely thank the research committee, especially Prof. Natori and Prof.
Lim, for the constructive feedback and comments during which have massively increased the
quality of the work in this research.
My sincere appreciations to all Ritsumeikan University’s professors, especially for Prof.
Aoyama, Prof. Ishida, Prof. Oda, and Prof, Choi, who have contributed effectively in my
educational journey.
Also, I would like to thank all my colleagues from masters and doctoral degrees and the
members of the Life Innovation Design Laboratory for their continued support and collaboration
during this study, which has significantly raised my awareness about different scientific fields.
I would like to thank all the staff members of the technology management office, the
international students center as well as the research office for their continued support and endless
efforts spent in supporting the administrative matters of this study.
My sincere thanks go to the Japanese Ministry of Education MEXT as well as to the
Japanese Ministry of Foreign Affairs MOFA, for their continued support and for providing
excellent educational opportunities and funding for international researchers and for their
continued efforts in creating a strong connection between Japan and Africa.
Table of Abbreviations
MOT Technology Management
METI Ministry of Economy, Trade and Industry
MEXT Ministry of Education, Culture, Sports, Science and Technology
MHLW Ministry of Health, Labour and Welfare
MAFF Ministry of Agriculture, Forestry and Fisheries
CAA Consumer Affairs Agency
USA United States of America
EU European Union
FFC Food with Function Claim
SME Small and medium-sized enterprises
GMO Genetically Modified Organism
SEM Structural Equation Modeling
MOFA Ministry of Foreign Affairs
SDG Sustainable Development Goal
UN United Nations
FAO Food and Agriculture Organization
COVID-19 Novel Corona Virus Disease 2019
UN-DESA United Nations Department of Economic and Social Affairs
UNU-WIDER World Institute for Development Economics Research
GDP Gross Domestic Product
RQ Research Question
IBM International Business Machines “Corporation”
SPSS Statistical Package for Social Sciences “Software”
AMOS Analysis of Moment Structures “Software”
Ver. Version
FOSHU Food for Specified Health Uses
T. Trillion
M. Million
K. Thousand
FHC Food with health claims
FNFC Food with Nutrient Function Claims
Healthy-Do Hokkaido Government-Certified Functional Food
Ex. Example
TOKUHO Tokutei Hokenyo Shokuhin “Health Food”
mg Milligram
HACCP Hazard Analysis and Critical Control Points
GMP Good Manufacturing Practice
EC European Commission
FDA Food and Drug Administration
DSHEA Dietary Supplement Health and Education Act
MFDS Ministry of Food and Drug Safety
TFDA Taiwan Food and Drug Administration
CFDA China Food and Drug Administration
HAS Health Sciences Authority
SISPQC Safety, Identity, strength, purity and quality
USD United States Dollar
USDA United States Department of Agriculture
WHO World Health Organization
Bt-corn Bacillus Thuringiensis Corn
CRISPR Clustered Regularly Interspaced Short Palindromic Repeats
Cas9 CRISPR associated protein 9
RNA Ribonucleic Acid
DNA Deoxyribonucleic Acid
GM Genetically Modified
ZFN Zinc Finger Nucleases
TALENs Transcription Activator-like Effect Nucleases
ODM Oligonucleotide Directed Mutagenesis
KN Knowledge
ATT Attitude Towards Technology
TR Trust
PB Perceived Benefits
PR Perceived Risks
WTP Willingness to Purchase
TAM Technology Acceptance Model
UK United Kingdome
KMO Kaiser-Meyer-Olkain
C.R. Critical Ratio
S.E. Standard Error
SRMR Standardized Root Mean Square Residual
RMSEA Root Mean Square Error of Approximation
CFI Comparative Fit Index
Table of Contents
1. Introduction ............................................................................................................... 1
1.1. Background ........................................................................................................ 1
1.2. Research Aim and Objectives ............................................................................ 2
1.3. Research Questions ............................................................................................ 3
1.4. Research Methodology ....................................................................................... 5
2. Functional Food Regulations ................................................................................... 8
2.1. Background ........................................................................................................ 8
2.2. Introduction ........................................................................................................ 8
2.3. Regulations in Japan ....................................................................................... 13
2.3.1. Food for Specified Health Use (FOSHU) .................................................... 14
2.3.2. Food with Nutrient Function Claims (FNFC) ............................................. 18
2.3.3. Food with Function Claims FFC ................................................................. 20
2.3.4. Japanese Local Government Regulation System ......................................... 22
2.4. Functional Food Global Regulations ............................................................. 25
2.4.1. Regulators .................................................................................................... 25
2.4.2. Product Categorization ................................................................................ 25
2.4.3. Shape Description ........................................................................................ 26
2.4.4. Product Purpose .......................................................................................... 26
2.4.5. Positive List .................................................................................................. 27
2.4.6. GMP System – Good Manufacturing Practice ............................................ 27
2.5. Functional Food Regulations Conclusion ...................................................... 28
3. Genetically Edited Food Regulations ................................................................... 31
3.1. Background ...................................................................................................... 31
3.2. Genetically Modified Food .............................................................................. 31
3.3. Genetically Edited Food ................................................................................... 33
3.4. GMO and Gene-Edited Foods Regulations .................................................... 35
3.4.1. Japan's Regulations ..................................................................................... 36
3.5. Conclusion ........................................................................................................ 39
4. Genetically Edited Food Acceptance .................................................................... 42
4.1. Background ...................................................................................................... 42
4.2. Survey Design ................................................................................................... 42
4.3. Responses Collection ....................................................................................... 45
4.4. Survey Demographics ...................................................................................... 46
4.5. Theoretical Model and Literature Review ....................................................... 48
4.6. Analysis of the Data ......................................................................................... 66
4.6.1. Validity and Reliability of the Constructs .................................................... 67
4.7. Model Testing ................................................................................................... 71
4.8. Initial analysis for model’s constructs ............................................................ 73
4.9. Model’s Path Coefficient ................................................................................. 79
4.10. Model’s Goodness of Fit .............................................................................. 81
4.11. Willingness to Adopt .................................................................................... 85
4.12. Effect of knowledge and science communication ....................................... 87
4.13. Intervention Analysis ................................................................................... 97
5. Conclusion ............................................................................................................... 98
5.1. Research Summary and Conclusion ............................................................... 98
5.2. Research Significance and Implications ....................................................... 102
5.3. Limitations and Opportunities for Future Research .................................... 105
References ...................................................................................................................... 109
Appendix 1: How importance the food security in the SDG ..................................... 123
List of Tables
Table 1 | Summarized research methodology ................................................................................ 7
Table 2 | Estimates of National Medical Care Expenditures in Japan (Source: MHLW) ............ 10
Table 3 | Estimates of National Medical Care Expenditures in Japan (Source: World Bank) ..... 12
Table 4 | Sample of the approved FOSHU products ingredients (Source: MHLW) .................... 17
Table 5 | Specifications of the authorized claim for FNFC food products (Source: MHLW) ..... 19
Table 6 | Summarized description for functional food categories in Japan ................................. 24
Table 7 | Summarization for the global functional food regulations (Source: Farid, et al. 2019) 30
Table 8 | Genetically Modified and Genetically Edited Foods Regulations Comparison (Source: Farid, et al., 2020) ......................................................................................................................... 41
Table 9 | List of questions related to the Knowledge construct (Farid, et al., 2020) ................... 53
Table 10 | List of questions related to the “Attitude Towards Technology” construct (Farid, et al., 2020) ....................................................................................................................................... 57
Table 11 | List of questions related to the “trust” construct (Farid, et al., 2020) ......................... 60
Table 12 | List of questions related to the “perceived benefits” construct (Farid, et al., 2020) ... 62
Table 13 | List of questions related to the “perceived risks” construct (Farid, et al., 2020) ........ 64
Table 14 | List of questions related to the “willingness to purchase” construct (Farid, et al., 2020)....................................................................................................................................................... 66
Table 15 | Exploratory Factor Analysis ........................................................................................ 68
Table 16 | Kaiser-Meyer-Olkin KMO test, results guideline ....................................................... 69
Table 17 | KMO and Bartlett’s Test Results ................................................................................ 70
Table 18 | Reliability Values of Model’s Constructs ................................................................... 71
Table 19 | Model’s estimated regression weights (before intervention) ...................................... 72
Table 20 | Model’s estimated regression weights (after intervention) ......................................... 73
Table 21 | estimated regression weights for the “knowledge” construct (after intervention) ...... 74
Table 22 | estimated regression weights “attitude towards technology” (after intervention) ...... 75
Table 23 | estimated regression weights for the “trust” construct (after intervention) ................. 76
Table 24 | estimated regression weights for the “perceived benefits” construct (after intervention) .................................................................................................................................. 76
Table 25 | estimated regression weights for the “perceived risks” construct (after intervention) 77
Table 26 | estimated regression weights for the “willingness to purchase” construct (after intervention) .................................................................................................................................. 78
Table 27 | Acceptable fit rules for selected factors ...................................................................... 82
Table 28 | Model fit index ............................................................................................................ 84
Table 29 | Willingness to purchase binary question responses table ........................................... 85
Table 30 | Willingness to purchase binary question (chi-square test) .......................................... 86
Table 31 | Comparison for the intervention significance for the knowledge construct ............... 89
Table 32 | Comparison for the intervention significance for the attitude towards technology construct ........................................................................................................................................ 90
Table 33 | Comparison for the intervention significance for the trust construct .......................... 92
Table 34 | Comparison for the intervention significance for the perceived benefits construct .... 93
Table 35 | Comparison for the intervention significance for the perceived risks construct ......... 95
Table 36 | Comparison for the intervention significance for the willingness to purchase construct....................................................................................................................................................... 97
Table 37 | Poverty rate prediction post-COVID-19 ................................................................... 125
List of Figures
Figure 1 | Health and functional food categories in Japan chart (Source: MHLW, CAA) .......... 13
Figure 2 | FOSHU products approval flow chart (Source: MHLW, CAA) ................................. 15
Figure 3 | FOSHU regulations subcategories (Source: MHLW) ................................................. 17
Figure 4 | Accumulative number of FOSHU and FFC authorized products in Japan (Source: CAA, MHLW) .............................................................................................................................. 22
Figure 5 | How genome editing (CRISPR) works ........................................................................ 34
Figure 6 | Data collection session design ..................................................................................... 44
Figure 7 | Diagram explaining the number of survey respondents .............................................. 46
Figure 8 | Demographics of survey’s respondents ....................................................................... 47
Figure 9 | Conceptual model to be tested in this study ................................................................ 49
Figure 10 | Attitude model for genetically modified food (Christoph et al., 2008) ..................... 51
Figure 11 | Level of knowledge associated with certain hazards ................................................. 52
Figure 12 | Categorization of products adopters .......................................................................... 54
Figure 13 | Estimated attitude model towards GM food (Dane mark, Germany, UK) (Bredahl, 2001) ............................................................................................................................................. 62
Figure 14 | Path coefficient using benefits risk analysis model (China) (Zhang et al., 2018) ..... 64
Figure 15 | Path coefficient using benefits risk analysis model (Taiwan) (Chen & Li, 2007) ..... 65
Figure 16 | Model’s standardized estimates based on the data before the intervention ............... 80
Figure 17 | Model’s standardized estimates based on the data after the intervention .................. 81
Figure 18 | Willingness to purchase binary question chart .......................................................... 86
Figure 19 | Respondents mean-line before and after intervention (Knowledge) ......................... 88
Figure 20 | Respondents mean-line before and after intervention (Attitude towards technology)....................................................................................................................................................... 89
Figure 21 | Respondents mean-line before and after intervention (Trust) ................................... 91
Figure 22 | Respondents mean-line before and after intervention (Perceived benefits) .............. 92
Figure 23 | Respondents mean-line before and after intervention (Perceived risks) ................... 94
Figure 24 | Respondents mean-line before and after intervention (Willingness to purchase) ..... 96
Figure 25 | The Sustainable development goals map ................................................................. 123
Figure 26 | Distribution of food insecurity level in different regions (FAO, 2020) ................... 128
Figure 27 | Food insecurity level by percentage in different regions (2014 – 2018) ................. 129
Figure 28 | Expected increase in the number of undernourished people after COVID-19 (FAO, 2020) ........................................................................................................................................... 129
1
1. Introduction
1.1. Background
The world is facing tremendous population growth (Benna & Garba, 2016). Over the past
70 years, the World population has tripled. During the year 1950, the world population was about
2.5 billion people (Demeny & McNicoll, 2006). However, now in the year 2020, the world
population is estimated by 7.8 billion people (Jensen & Levin, 2020). The world population will
continue to grow by approximately 1% a year to reach 8.5 billion in the year 2030. Studies
expected the population to grow further to reach 9.7 billion by the year 2050 and will increase to
11.2 billion by the year 2100 (United Nations, 2013). The tremendous population growth will
continue to create a challenge, especially in providing enough supply of food to the future
population. Food security is one of the main challenges that the world is currently facing. Due to
the importance of the food-related challenges, the United Nations (UN), has allocated the “Zero
Hunger” goal as the second goal of the Sustainable Development Goals (SDGs) (Blesh et al.,
2019). According to the latest estimates from The Food and Agriculture Organization (FAO), over
700 million people around the world who represent nearly 9% of the world population, have
suffered from stringent levels of food insecurity in the year 2018 (Tacon, 2018). FAO has defined
the status of severe food insecurity as the people who did not have any access to any type of food
for a day or more. Another study from FAO shows that additional 1.3 billion people representing
another 17% of the world population have suffered from moderate levels of food insecurity,
represented in the lack of having continuous access to sufficient level of nutritional food. However,
the situation in Japan is different. Although Japan has a very low level of food insecurity yet, Japan
has a low level of food self-sufficiency when comparing the food imports to the exports where it
was dropped by nearly 55% during the past 60 years reaching an all-time low of 37% (Farina,
2
2017). Also, in Japan, the number of farming households has dropped by nearly 90% in the last 50
years from 11 million in the year 1965 to 1.3 million in 2015, where currently 60% of the farmers
in Japan are aged above 65 years old. Another challenge is also represented in the fact that the
percentage of arable land in Japan is minimal, specifically below 12%.
Based on the above challenges mentioned in the world in general and Japan in specific,
there is an urgent need to focus on solving food security and food self-sufficiency challenges,
which can be solved by utilizing different food technologies namely functional food and
biotechnology (Jamil, 2009) represented in genetically edited food.
Japan also has a very high level of R&D in different fields, which can be utilized in solving
such pressing challenges and boost Japan as an innovation hub in the area of food technologies
locally and globally.
1.2. Research Aim and Objectives
As we have discussed earlier in the background part, there is a continued need for food-
related technologies for providing food for everyone at a low cost. Also, although Japan is
currently facing several challenges related to agriculture, however, Japan has an opportunity to
excel further in the food-related technology field, such as functional food and genetically edited
food. Functional food in the United States, considered as a growing industry, where the industry
grows by nearly 10% yearly. However, the situation in Japan is quite different, where the industry
grows by almost 2% only yearly. This considered very challenging for the Japanese sector due to
the high cost associated with research and development.
Therefore, and in order to support tackling the above-mentioned challenges, this research
has been formulated with the explicit aim of exploring how Japan can grow in the field of
3
innovative food technologies with a focus on “Functional Food” and “Genetically Edited Food”
products.
The approach to achieve the research aim is to study the regulations further and create a
comparison between the regulations in Japan and globally to spot the strong points that can help
boost innovative food industries in Japan. Also, the regulation comparison can help the Japanese
food industry to expand globally with a clear understanding of the regulatory challenges in
different countries. In order to achieve the research aim, the following research objectives were
set:
• Compare the functional food regulations in Japan and globally.
• Discuss how different regulations in Japan can boost innovation.
• Compare the genetically edited food regulations in Japan and globally.
• Explore how to increase the acceptance of innovative food technologies-based
products “genetically edited food” among consumers in Japan.
1.3. Research Questions
Given in consideration the background of this study and the highlighted research problem,
there is a need to create a better understanding of different opportunities that can help the Japanese
companies grow in the field of food-related technologies. Therefore, formulating the research
questions have followed three stages.
The first stage is studying the functional food in Japan and globally since that functional
food is considered as very common in Japan with a considerably acceptable level of knowledge
among the manufacturers. Therefore, the first research question was formulated to investigate how
4
Japan can expand globally in the field of functional food by reviewing the global regulations in
this regard.
• RQ1: What are the key differences in terms of functional food regulations between
Japan and overseas?
The following stage after studying the functional food regelation is to target a more
innovative field of food technologies where the global market has excellent opportunities with low
competition as well. In this stage, the main focus was “genetically edited food” since it is a very
innovative industry and meets the requirements mentioned earlier. To explore the possibilities of
growing the Japanese sector locally and globally in the field of genetically edited food, the local
and global regulations for this regard have been the focus of this part. Therefore, the second
research question was stated as follows;
• RQ2: What are the key differences in terms of genetically edited food regulations
between Japan and overseas?
The third stage, after studying the genetically edited food regulations in Japan and globally,
aims to investigate the possibility of growing the genetically edited food industry, which needs to
improve the acceptance of the genetically edited food in the first place. Therefore, in this stage,
we wanted to discover further what are the factors that affect the acceptance and adoption rate of
the genetically edited food products, so the following research question was formulated.
• RQ3: What are the factors affecting genetically edited food acceptance?
5
Finding scientific answers for the three research questions mentioned above shall create
collective knowledge and set a basic understanding of the possibilities to grow the Japanese
innovative food industry locally and globally.
1.4. Research Methodology
In order to achieve the research aim and find an answer to the above-mentioned research
questions, a mixed methodology has been applied to this research combining the qualitative
approach along with the quantitative approach.
The first research question aims to create a better understanding of the difference between
the regulations in Japan and the regulations globally in terms of functional food. Therefore, the
qualitative approach has been used to tackle this question by conducting a literature review and
review for secondary data represented in the previous studies and governmental legislation reports.
In this part of the study, the Japanese regulations were studied based on the latest updates and
using four different types of regulations in Japan. The Japanese regulations were also compared
with the regulations in the United States, European Union, Korea, Taiwan, China, and Singapore.
The second research question aims to investigate a more innovative industry, which is the
genetically edited food industry, and to create a better understanding of the difference between the
regulations in Japan that govern genetically edited food and the regulations globally in this regard.
Therefore, the qualitative approach has been used in this segment as well, represented in literature
reviews and analysis for the official reports and legislation as well as the press releases of the
regulatory authorities in Japan, America, and the European Union.
The third research question aims to investigate more the willingness to accept genetically
edited food products in Japan. Therefore, in this part, a qualitative approach was utilized in the
6
form of a survey and experiment. For the survey part, the structural equation modeling method
was utilized in order to investigate further the different factors that affect the willingness to
consumer genetically edited food products in Japan. The main factors studied in this part were six
factors, namely; knowledge, attitude towards technology, perceived benefits, perceived risks, trust,
and willingness to purchase. Each factor of the six factors mentioned above was measured using
seven different questions.
Due to the fact that genetically edited food is considered a new term, and there is a lack of
knowledge about it among the general consumers including the survey respondents, an experiment
was designed in the form of intervention to increase the knowledge of the respondents about the
genetically edited food and how it is different than genetically modified food. Therefore, the survey
was conducted twice in the same session, with having an intervention in the form of a five-minute
informative presentation between each run of the survey. The questions before and after the
intervention were identical, since that the main focus in this step was to investigate the role of
knowledge and science communication in increasing the awareness and the acceptance rate by
comparing the willingness to adopt genetically edited food products data before and after the
intervention. The correct and complete samples of the respondents who answered both surveys
were 180 respondents, with an average age of 21 years old, who are bachelor’s degree students,
studying business administration at Ritsumeikan University, Japan. All the analyses for the surveys
have been conducted using IBM SPSS and IBM SPSS Amos (Ver. 26).
7
Table 1 | Summarized research methodology
RQ1 RQ2 RQ3
Question
What are the key
differences in terms of
functional food
regulations between
Japan and overseas?
What are the key
differences in terms of
genetically edited food
regulations between Japan
and overseas?
What are the factors
affecting genetically
edited food acceptance?
Focus Functional Food Genetically Edited Food Genetically Edited Food
Aim Regulation comparison Regulation comparison Explore factors affects the
acceptance
Approach Qualitative Qualitative Quantitative
Methodology Literature
review
Literature
review
Structural equation
modeling SEM
Data Source
Previous study and
governmental legislation
reports
Previous study and
governmental legislation
reports
Survey and
experiment
Data Points
Regulation of Japan,
USA, EU, Korea, Taiwan,
China, Singapore
Regulation of Japan,
USA, EU
SEM Factors:
Knowledge, Trust,
Perceived Benefits,
Perceived Risks, Attitude
Towards Technology,
Willingness to Purchase.
8
2. Functional Food Regulations1
2.1. Background
This chapter focuses mainly on the first research question (What are the key differences in
terms of functional food regulations between Japan and overseas?). The study focuses on this
chapter to identify the different regulations of the functional food in Japan, also the regulations for
the labeling of functional food globally, especially in the United States, European Union, China,
Korea, Taiwan, and Singapore. The study in this chapter comes as part of the main aim of this
research of exploring ways to expand the Japanese functional food products globally. To achieve
this aim, we have studied in this chapter the local and global functional food markets as well as
the regulations to point out the strengths and opportunities for the Japanese functional food systems
to expand abroad. This chapter focuses mainly on the literature review and the secondary sources
represented in the governmental regulation reports and press releases.
2.2. Introduction
Food is a human necessity. It provides our daily lives with nutrients and energy. Cooking
has, however, become "functional food," which changes health benefits and nutritional benefits.
Functional foods have now advanced to the point where they can be designed to improve public
health and reduce the likelihood of having specific types of diseases. Functional foods can be
defined as foods or beverages that have boosted nutrients such as vitamins, fibers, proteins,
minerals, or other functional components. Functional foods can operate in two ways. The first way
is by enhancing existing ingredients, where the second way is by incorporating one or more new
ingredients to improve non-original food functions (Hasler, 2002). Functional food producers
1 This section may include an adaptation of Farid, et al., 2019
9
follow specific processes to ensure products with true values are produced. Most regulators around
the world are drafting rigorous and detailed regulations and standards to ensure food efficiency
and safety. Regulatory bodies may also study whether the goods offer real value to consumers.
Legislations vary from country to country, making exporting functional foods a challenging task,
especially if the regulations are not clear or if the goods have not been modified to fit the importing
country's regulations. Functional food has continued to deliver true added value for a wide
spectrum of customers, especially among senior citizens, since its inception in Japan. In the 1980s,
Japan introduced the term "functional foods," followed by legislation for it. In Japanese economics
and society, functional food has become important. With rising healthcare costs and the resulting
financial burdens facing Japan, including welfare programs for senior citizens and others with
chronic diseases, adopting healthy and functional foods at the earliest possible age can limit the
possibility of acquiring diet-related diseases, thereby reducing the cost of national health
expenditure (Bagchi, 2008).
The national health expenditure rate in Japan is on a continuous rise. In the year 1987, the
total national healthcare-related expenditure in Japan was valued with almost eighteen trillion
Japanese yen, with an approximated expenditure per capita of 147,000 Japanese yen per year.
However, thirty years later and specifically in the year 2017, the total expenditure has surpassed
the forty-three trillion Japanese yen a year, and reached to nearly 340,000 Japanese yen per capita.
Such a massive increase in the healthcare cost of nearly 130% over the past thirty years have
created economic consequences in Japan, as shown in the table below.
10
Table 2 | Estimates of National Medical Care Expenditures in Japan (Source: MHLW)
Total Expenditure (Trillion JPY)
Increase compared to the previous year (%)
Expenditure per capita (Thousand JPY)
1987 18.08 5.9 147.8
1988 18.76 3.8 152.8
1989 19.73 5.2 160.1
1990 20.61 4.5 166.7
1991 21.83 5.9 176
1992 23.48 7.6 188.7
1993 24.36 3.8 195.3
1994 25.79 5.9 206.3
1995 26.96 4.5 214.7
1996 28.45 5.6 226.1
1997 28.91 1.6 229.2
1998 29.58 2.3 233.9
1999 30.7 3.8 242.3
2000 30.14 1.8 237.5
2001 31.1 3.2 244.3
2002 30.95 0.5 242.9
2003 31.54 1.9 247.1
2004 32.11 1.8 251.5
2005 33.13 3.2 259.3
2006 33.13 0.0 259.3
2007 34.14 3.0 267.2
2008 34.81 2.0 272.6
2009 36.01 3.4 282.4
2010 37.42 3.9 292.2
2011 38.59 3.1 301.9
2012 39.21 1.6 307.5
2013 40.06 2.2 314.7
2014 40.81 1.9 321.1
2015 42.36 3.8 333.3
2016 42.14 (0.5) 332.0
2017 43.07 2.2 339.9
11
Japan’s Ministry of Health and Welfare has created the term Food for Specified Health Use
FOSHU in an effort to create appropriate legislation to accredit functional food products and verify
their commercialization. The share of functional foods on the global market is rapidly increasing.
The market recorded $300 billion in revenue in 2017 and is expected to grow to $440 B in 2022.
The Asia - Pacific region has a market share of 34%, followed by North America of 25%, Latin
America of 17%, Western Europe of 16%, Eastern Europe of 3%, Middle East and Africa of 3%,
and Australia and New Zealand of 2%. While the US has the highest country market share, the
Asia - Pacific region has more regional market share. Japan is currently leading the way, with a
market size ranging from $30B to $40B. The US market, however, is growing rapidly, with rates
exceeding 10 percent per year. In contrast, Japan's market shows a much lower level of growth of
less than 2 percent per annum.
We take the age-dependence ratio as an important measure when analyzing the key
demographics of potential markets for functional food. The age-dependence ratio is the ratio of the
older dependents (people over 64) to the working-age population (people between 15 and 64). It
measures the proportion of society's elderly portion as relative to those of working age. A high
ratio indicates that a large segment of the population depends on the workforce to meet the
healthcare and other needs of the senior population. In societies with high elderly population rates,
innovative measures need to be taken to minimize social service costs without reducing service
levels. To measure changes over the past fifty years, a comparison was created between the age
dependency ratio for the years 1967 and 2017. Generally speaking, the countries in our comparison
all display rises in the dependence of the elderly vary widely from country to country. The lowest
rise in the United States was up from 15.9% in 1967 to 23.4% in 2017, a 47% leap. By contrast,
Japan's highest growth was from 9.3 percent in 1967 to 45 percent in 2017, with a massive 383.9
12
percent increase. The EU increased by 78.4%, Korea increased by 193.8%, Taiwan by 170%,
China by 131.3%, and Singapore by 244.2%. While the EU has a ratio of 30.5 percent for 2017
(higher than the Asian countries excluding Japan), Europe has experienced a low level of growth
compared to Asian countries over the past 50 years. This implies that, generally, the Asian
countries have seen major demographic change over the last few decades.
We believe the Asian functional food markets must continue to grow to cope with the high
medical and social expenditures associated with these changes. In addition, markets such as China,
with a total population of 1.37 billion, already have tremendous opportunities in this area,
compounded by the rapid increase in the age dependency ratio (14.8 percent in 2017, with a 50-
year leap of 131.3 percent). There is no doubt that the growing elderly dependency ratio is partially
due to healthcare services that have increased the average life expectancy. In 2017, average life
expectancy in Japan reached close to 84 years.
Table 3 | Estimates of National Medical Care Expenditures in Japan (Source: World Bank)
Variable Japan US EU China Korea Taiwan Singapore
Population (M) 126.9 323.4 511.2 1,378.6 51.2 23.5 5.6
GDP ($. T.) 4.9 18.6 16.4 11.1 1.4 0.4 0.3
GDP per Capita ($. K.) 38.9 57.5 32.2 8.1 27.6 25.5 55.2
Life Expectancy (year) 83.9 78.6 80.6 76.2 82 80.4 82.7
Age dependency ratio, old* (%) Year 2018
46.17 24.14 30.86 15.33 19.85 18.9 15.03
Age dependency ratio, old* (%) Year 1967
9.3 15.9 17.1 6.4 6.5 7.0 (est.) 5.2
Increase in age dependency over 50 years (%)
383.9 47.2 78.4 131.3 193.8 170 244.2
13
2.3. Regulations in Japan
There is a clear distinction between the categories of health food and pharmaceutical.
While the health food category is specialized in providing modified or enhanced food to provide
healthier nutrition, the pharmaceutical category is specialized for products that can cure or prevent
diseases. The group of health foods is composed of two major subcategories. The first consists of
the so-called "health food," which is considered a grey zone with vague requirements for labeling
and descriptive definitions. The second category which is the subject of this study is "health and
functional food" or food with health claims (FHC) which is highly regulated by the Japanese
authorities and is further divided into three subdomains: Foods for Specified Health Use (FOSHU),
Food with Nutrient Function Claims (FNFC), and Food with Function Claims (FFC). Along with
the three categories mentioned above, there is another category related to the local government
system certification, where local governments can certify a product as a functional food
considering that it matches with certain standards. One of the well-known systems in this category
is Healthy-Do, which is the official local government certification system in the prefecture of
Hokkaido in Japan.
Figure 1 | Health and functional food categories in Japan chart (Source: MHLW, CAA)
Health Food
Health and functional food Pharmaceutical
So-called “Health food”
Gray Zone
FFC Food with
Function Claims
Notification system
FNFC Food with
Nutrient Function Claims
Self-
Authentication system
FOSHU Food for
Specified Health Use
Individual Permission restraints
Pharmaceutical
including quasi-drugs
Local Government System (local certification system)
14
2.3.1. Food for Specified Health Use (FOSHU)
FOSHU, "Foods for Specified Health Use," also which is known as TOKUHO, is a
Japanese abbreviation for "tokutei hokenyo shokuhin," or foods with special healthy qualities. The
Ministry of Health, Labour and Welfare (MHLW) in Japan introduced those laws in 1991. This
system requires that each product be given special testing procedures to obtain labels approval.
The research relating to food labeling was moved to the Consumer Affairs Agency (CAA) after 1st
of September 2009.
The approval procedure for this functional food category uses strict standards, and it
requires massive financial investment and a lengthy review period. It poses affordability and time-
to-market challenges for smaller companies or start-ups, which gives big companies a competitive
advantage. Such products have different labeling to reflect the product 's claim and functions, such
as identifying ingredients that affect body functions (e.g., stabilizing blood pressure, reducing
cholesterol). To get a product licensed, the applicant must submit the application forms for
approval to apply for review requests. Within the CAA, three entities review the request for
permission; the Consumer Commission, the Food Safety Committee, and the Health Ministry. A
sample of the food product to be tested by the National Institute of Health and Nutrition or another
approved and licensed inspection agency must be submitted by the applicant.
As shown in the figure below, the process for getting FOSHU approval is considered to be
lengthy with a high number of stakeholders involved. The figure shows a clear process for the
FOSHU applicant to follow in order to get the authorization needed for product commercialization.
As shown in the figure below, there are several other stakeholders involved in the process beside
the CAA and MHLW.
15
Figure 2 | FOSHU products approval flow chart (Source: MHLW, CAA)
Applicant
Display permission application form
Application form for examination
Sample of the product for testing
Public Health Office
Prefectural government Designated cities
Consumer Affairs Agency CAA
Consumer Committee
Food Safety Committee
Ministry of Health,
Labor and Welfare
National Institute of Health and Nutrition
or other registered entity
Apply
Send
Process Send the permission
Permission notice
Deliver
Apply
Request analysis
Analysis Results
Submit Analysis Results
Consult Report
Consult Report
Consult Report
16
As shown in the figure above, for a product to be approved as a FOSHU product, it has to
go through a lengthy process, and it has to match very strict requirements. The first requirement
that the product must demonstrate a high level of effectiveness on the human body. Also, the
product must have very high safety standards, which can be verified by toxicity tests on animals,
also by verifying the potential effect of any excessive intake cases. The product must have balanced
level ingredients with appropriate use of nutrition. Also, the product must maintain its capabilities
and specifications by the time the consumer expected to use it. Also, the product must follow
quality control and quality assurance strict systems in order to verify the ingredients and product
specifications to be at the authorized level.
The FOSHU category consists of 4 subcategories, as represented in the figure below. Along
with the regular category, there are three different categories, namely: qualified, standardized, and
reduction of disease risk. The qualified FOSHU, which represents food with health features that
are not based on scientific evidence that meets the FOSHU level or food with a certain efficacy
but without a proven mechanism of the successful functional item, will be accepted as an eligible
FOSHU product. The standardized FOSHU category represents when standards and specifications
for foods with sufficient FOSHU approvals are established, and scientific evidence is accumulated.
Standardized FOSHU is approved when it meets the specifications and standards. The last category
is the reduction of disease risk category, which was added to the FOSHU regulation by the MHLW
in accordance with the decision of the Codex Alimentarius Commission of the Food and
Agricultural Organization / World Health Organization. This category contains products that have
ingredients proven to reduce the risk of certain diseases such as calcium or folic acid, which can
be used with specific daily intake specifying the recommended minimum and maximum daily
intakes. The ingredients for this category in specific should be completely based on strong
17
scientific evidence in which the scientific community has consensus to approve it, as shown in the
table below.
Figure 3 | FOSHU regulations subcategories (Source: MHLW)
Table 4 | Sample of the approved FOSHU products ingredients (Source: MHLW)
Specified Health Uses Principal Ingredients (ingredients exhibiting health functions)
Foods to modify gastrointestinal conditions
Oligosaccharides, lactose, bifidobacteria, lactic acid bacteria, dietary fiber 8 ingestible dextrin, polydextrol, guar gum, psyllium seed coat, etc.)
Foods related to blood cholesterol level Chitosan, soybean protein, degraded sodium alginate
Foods related to blood sugar levels Indigestible dextrin, wheat albumin, guava tea polyphenol, L-arabiose, etc.
Foods related to blood pressure Lactotripeptide, casein dodecaneptide, tochu leaf glycoside (geniposidic acid), sardine peptide, etc.
Foods related to dental hygiene Paratinose, maltitiose, erythrytol, etc.
Cholesterol plus gastrointestinal conditions, triacylglycerol plus cholesterol Degraded sodium alginate, dietary fiber from psyllium seed husk, etc.
Foods related to mineral absorption Calcium citrated malate, casein phosphopeptide, hem iron, fracuto-oligosaccharide, etc.
Foods related to osteogenesis Soybeen isoflavone, MBP (Milk basic protein), etc.
Foods related to triacylglycerol Middle chain fatty acid, etc.
Source: Japanese Ministry of Health, Labour and Welfare of Japan (Website)
Regular Reduction of Disease Risk
Food for Specific Health Use (FOSHU)
Qualified Standardized
18
2.3.2. Food with Nutrient Function Claims (FNFC)
FNFC, "Food with Nutrient Function Claims," which was introduced by the MHLW in
April 2001, is another type of the Japanese national functional food regulations. The FNFC
contains all foods that have been labeled with nutrient role statements meeting the guidelines of
the MHLW. Yet again, after 2009, the procedure is regulated by the CAA. The FNFC standards
specify several ingredients that may be used, including thirteen vitamins, beta carotene, six
minerals, and n-3 fatty acids. The key difference between the FNFC and the FOSHU is that the
former does not need any approval from the CAA as long as the product manufacturer ensures that
the product meets the requirements and specifications, unlike the accreditation and certification
process under FOSHU. The FNFC regulations do not require getting a particular logo or credential
on the product. However, the nutrient function claims, as well as the warning indications, must be
clearly displayed on the product. It is not allowed to label the FNFC products as products useful
for a specified healthcare-related purpose. An example of the FNFC labeling is the identification
of the nutritional ingredient as "Vitamin C," with a specified range of 24 ~ 1000 mg of
recommendable daily intake. The functional claims would be "helps to maintain skin and healthy
mucosa, and has an antioxidant effect." A warning would be, "Increased intake of this product will
not result in disease cure or health promotion, please comply with the advisable daily intake."
The table below shows a list of the functional ingredient allowed to be used in the FNFC
category, with its advisable daily intake, as well as the translated meaning of the functional claim
of the labels, which were translated from Japanese to English.
19
Table 5 | Specifications of the authorized claim for FNFC food products (Source: MHLW)
Functional Ingredient
Advisable daily intake
Approximate “translated” meaning of the nutrient functional claim
Niacin 3.3 ~ 60 mg Niacin is a nutrient that helps maintain healthy skin and mucous membranes
Pantothenic acid 1.65 ~ 30 mg Niacin is a nutrient that helps maintain healthy skin and mucous membranes
Biotin 14 ~ 500 μg Biotin is a nutrient that helps maintain healthy skin and mucous membranes
Vitamin A 135 ~ 600 μg Vitamin A is a nutrient that helps maintain night vision. Vitamin A is a nutrient that helps maintain healthy skin and mucous membranes
Vitamin B1 0.30 ~ 25 mg Vitamin B1 is a nutrient that helps produce energy from carbohydrates and maintain healthy skin and mucous membrane
Vitamin B2 0.33 ~ 12 mg Vitamin B2 is a nutrient that helps maintain healthy skin and mucous membranes
Vitamin B6 0.3 ~ 25 mg Vitamin B6 is a nutrient that assists in energy production from proteins and helps in maintaining healthy skin and mucous membranes
Vitamin B12 0.60 ~ 60 μg Vitamin B 12 is a nutrient that assists the formation of red blood cells
Vitamin C 24 ~ 1000 mg Provides an anti-oxidizing effect, also assist in maintaining skin and mucosa healthily
Vitamin D 1.5 ~ 5.0 μg Vitamin D is a nutrient that promotes the absorption of calcium in the intestinal tract and helps bone formation.
Vitamin E 2.4 ~ 150 mg Vitamin E is a nutrient that protects the lipids in the body from oxidation and helps maintain the health of cells through its antioxidant effect.
Folic acid 60 ~ 200 μg Folic acid is a nutrient that helps the formation of red blood cells also it contributes to the normal development of the fetus.
Zinc 2.1 ~ 25 mg
Zinc is a nutrient needed to maintain a normal taste. Zinc is a nutrient that helps maintain healthy skin and mucous membranes. Zinc is a nutrient that is involved in the metabolism of proteins and nucleic acids and helps maintain good health.
Calcium 210 ~ 600 mg Calcium is a nutrient required for bone and tooth development
Iron 2.25 ~ 10 mg Essential for red blood cell formation process
Copper 0.18 ~ 6 mg helps to form red blood cells and helps maintaining several body enzymes in functioning properly, as well as in bone formation
Magnesium 75 ~ 300 mg Essential in the bone and teeth development Helps in keeping appropriate blood circulation helps proper function of many body enzymes
Source: Japanese Ministry of Health, Labour and Welfare of Japan (Translated from Japanese)
20
2.3.3. Food with Function Claims FFC
In April 2015, Japan also introduced a new form of legislation called the Food with
Function Claims (FFC). That category requires a company to mark the food if the company has
provided a report to the CAA stating that the goods meet national specifications, comply with
health and safety guidelines and provide medical evidence for the reported functions obtained from
clinical trials of humans to check their efficacy. The trials have to be carried out in systematic
studies by specialists and experts. The food business operator is expected to send this form of
notice to the CAA Secretary-General at least sixty days before the launch date or before any
marketing campaigns for the product are being conducted. The products must also have packages
labeled that comply with the Food Labeling Act and the Notification Guidelines for Products with
Function Claims. The labeling procedures include that the label has to be in the Japanese language
and include essential details such as the key ingredients, the process for using essential warnings,
suggested regular usage, and the manufacturer's contact information.
Category FFC may be used with all food products, including fresh vegetable products but
excluding products already registered under FOSHU or FNFC; this label also excludes all
alcoholic beverages and foods containing excessive amounts of fat, cholesterol, sugar, and sodium.
Keywords that could show or suggest medical benefits such as treatment, prevention, diagnosis,
and cure are banned in FFC labeling. Furthermore, FFC products may not target a specific segment
of consumers suffering from a particular disease. Such products are prohibited from being
provided to minors or pregnant women and do not show any claim specific for physical changes
such as hair growth, bodybuilding, or skin whitening.
21
Six key procedures are used to produce a product that has the FFC code. The first is to
determine the product's compatibility with FFC regulation within the main constraints described
above, in particular for the labeling process. Secondly, the assessment of public health by means
of safety checks, a compilation of data into databases, or a review of actual data on intake. The
third step is to build a manufacturing and product quality management and assurance program.
Hazard Analysis and Critical Control Points (HACCP) procedures or GMP systems are
recommended for manufacturers to implement. Fourthly, the creation of a reporting system for
collecting data on adverse health events. The fifth is assessing the effectiveness of the product by
conducting clinical trials or systematic literature reviews. Lastly, the manufacturer provides a
product label that meets the "Guidelines on Notification of Foods with Function Claims" standard.
The FFC category offers an easy way for small companies to reach the industry, as it does
not entail a lengthy and expensive process like FOSHU. It also does not require passing product
inspection. Unlike the FOSHU, it does give the manufacturer control over the evaluation of the
product. This new concept has caused a revolution in Japan's functional food industry. Despite the
much more recent start, the first year alone saw 172 FCC products registered. By March 2019, the
cumulative number of FFC products reached 1721, which exceeds by almost 40% the number of
FOSHU products registered in almost twenty-five years. Based on the information mentioned
above, it is predicted that the FOSHU system will decrease drastically over the coming years due
to the high cost and lengthy inspection procedures, and most manufacturers will then implement
the FFC system, making it the main system in this area. The chart below shows the development
of the FFC regulated products in comparison with the FOSHU regulated products, in terms of
accumulative number of products authorized.
22
Figure 4 | Accumulative number of FOSHU and FFC authorized products in Japan (Source: CAA, MHLW)
2.3.4. Japanese Local Government Regulation System
Japanese local governments, in addition to the national systems, can certify the
functionality of food based on scientific merits. A symbolic example of this is the Hokkaido
Functional Food Labeling Program (Healthy DO), the first local government accreditation
program in Japan. Healthy DO was introduced in 2013, two years before Food with Function
Claims Framework (FFC) was introduced. Healthy-DO's goal is to promote food-related industries
in Hokkaido by growing the value of food and providing appropriate information in response to
customer needs. A product that meets the three following conditions is eligible for Healthy DO
labeling. The first condition that it uses Hokkaido functional materials and main ingredients. The
second that it is a processed food product made in Hokkaido. The third that it has released a peer-
reviewed paper with the findings of a human intervention test for the ingredients of the products.
As of March 2020, 110 items were accredited as Healthy-DO Items.
0200400600800
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FOSHU FFC
23
A distinction between FFC and Healthy-DO products is that FFC products only need to be
reported to the CAA Consumers Affairs Department, while Healthy-DO products need to go
through a Hokkaido Local Government certification process. With functional materials, it may be
suggested that it is suitable for preserving and promoting safety, but these indications of efficacy
are not permitted in Healthy-DO, and only an indication of empirical evidence for functional
content is permitted. Studies of human intervention are needed on both systems. FFC products
include a clinical study that uses each final product. A peer-reviewed paper describing a human
intervention study would be required for Healthy-DO products, but it is not mandatory to perform
a human intervention study for each final product. In addition, foods that contribute to high levels
of blood sugar such as confectionery are not FFC approved, while Healthy-DO products do apply,
allowing for the certification of confectionery and luxury goods. If the product meets the criteria
for both systems, the Healthy-DO and FFC labels that appear on the same product. Based on the
comparison and the information mentioned above, it is highly anticipated that the local Healthy-
DO program will help small business goods to easily obtain certification, opening doors to growth
in this sector.
The table below summarizes all the functional food related regulations in Japan namely;
FOSHU, FNFC, FFC, and local systems in terms of complexity, history, labelling regulations,
characteristics, inspection regulations, regulatory authority and other aspects.
24
Table 6 | Summarized description for functional food categories in Japan
Category Characteristics
FOSHU | Food for
Specified Health Use
• The main regulation that governs functional food in Japan since 1991
• Can be labeled with specific effect (ex. cholesterol reduction)
• The process is lengthy, complicated and requires a substantial investment
• Every product must be examined individually by several governmental entities
• High barriers to entry which is difficult for startups or small business to apply
• Product samples must be inspected, and the effect must be proven
FNFC | Food with
Nutrient Function
Claims
• The second main regulation that governs functional food in Japan since 2001
• Specifies all food that is labeled with the nutrient function claims
• Utilized as a supplement for necessary daily intakes of nutrients (ex. vitamins)
• FNFC Nutrients must be fundamental for human activities
• Ingredients efficacy must be scientifically proven and well-studied
• Specified allowed ingredients (13 vitamins, six minerals, n-3 fatty acids)
• Must be labeled with the authorized dosage and warnings
• Doesn't require permissions of the producers guarantee that it meets standards
FFC | Food with
Function Claims
• The latest regulation issued by CAA in 2015 to govern functional food
• Allows business to label the food based on a notification system to CAA
• CAA must be notified by product details 60 days before the launch date
• Products must meet national requirements and conform with safety standards
• Products must have evidence for efficacy by clinical trials or systematic
reviews
• Products must be labeled with the main ingredients, daily usage, and warnings
• Products must not target specific segment who suffer from a certain disease
• It provides an affordable way for startups to enter the market because it doesn't
require lengthy and expensive procedures, unlike FOSHU.
Japanese Local
Government
Regulation System
• The first example for the local system is Healthy-Do, which is issued by the
Hokkaido local government in 2013.
• The products must have functional materials and manufactured in Hokkaido
• Must have a peer-reviewed article with results from a human intervention
study for the product's ingredients.
• Allows confectionery and luxury goods to be certified.
• The items can have Healthy-Do seal along with FFC if it meets requirements
• Number of products are 110 items (as of March 2020)
• Allows startups and local manufacturers to enter the industry
25
2.4. Functional Food Global Regulations
2.4.1. Regulators
Functional foods are governed in each country according to the rules and guidelines defined
by the regulator. The main regulator for functional foods in the EU is the European Commission
(EC), which has started to adopt food supplement regulations according to the European
Parliament and Council Directive 2002/46 / EC of 10 June 2002. In the United States, the Federal
Food and Drug Administration (FDA) is the regulator. The FDA started the functional food
labeling scheme in 1991, and also issued the 1994 Dietary Supplement Health and Education Act
(DSHEA). In Korea, the regulator is the Ministry of Food and Drug Safety (MFDS), which in May
2004 elaborated on the Health Function Food Act. The Taiwan Food and Drug Administration
(TFDA) exists in Taiwan. In China, the responsible entity is the Chinese Food and Drug
Administration, which issued the first functional food law in 1996, also finalized detailed rules for
the filing of health food applications, and in May 2017 began a new official process to accept the
application for health food filing. In Singapore, the Health Sciences Authority (HAS) is the
regulator. In Japan, the responsible entity is CAA.
2.4.2. Product Categorization
There is a major gap between the rules and regulations relating to functional food and
pharmaceutical development. As well as the validation and authorization process, the development
process is different. All the above-mentioned countries have created specific laws, regulations, and
standards for functional or health foods that are independent of pharmaceutical laws and
regulations. Countries consider functional foods as a particular category of food items, even though
there is no separate regulatory structure.
26
2.4.3. Shape Description
Functional food products can come in various forms, such as capsules or tablets. Each has
different characteristics of dissolution and different dosage types. When a capsule normally
contains powder or jelly, the substance is formed in solid shape by tablets. In terms of efficacy,
capsule content tends to enter the bloodstream much faster than tablet ingredients, especially if
tablets are covered with substances that slow bloodstream delivery. Capsules also appear to have
a shorter shelf life than tablets, thus making tablets a better long-term storage choice. In terms of
functional food packaging, it is important to understand the labeling regulations. The product type
(tablets, capsules) needs to be specified in the EU, Singapore, and the USA. Such a description in
Korea, Japan, and Taiwan is not required, though. In China, the product's shape is often displayed
on all the products, but not always. If a manufacturer produces functional food export packages to
the EU, Singapore, or the US, that manufacturer should meet the labeling requirements by
displaying the product's shape.
2.4.4. Product Purpose
There is a strong distinction between controlling healthy foods and pharmaceutical
products for use purposes and details relating to the market. Pharmaceuticals are often sold as
remedies or therapies for serious illnesses. Functional foods, on the other hand, tend to be marketed
as additives or as sources of boosted nutrients. Efficient food marketing strategies and labels can
only communicate the message of being dietary supplements or improved vitamins and nutrients
in the countries we've compared (EU, USA, Korea, Taiwan China, Singapore, and Japan). These
may not be marketed as products that treat any medical condition.
27
2.4.5. Positive List
A common approach by regulatory authorities to ensure the safety of functional food
ingredients is the creation of a “positive list.” Regulations call for clear identification of
permissible ingredients, and regulators provide a positive list containing the names of the vitamins,
minerals, and other substances approved for use in functional foods, along with their permissible
sources. Some countries also have a negative list containing possible ingredients not allowed in a
functional food product (FSAI, 2007). In the countries we've compared, we found that China, the
EU, Japan, Korea, Singapore, and Taiwan provide the permitted components with a specific
positive list, while the US does not provide such a list. While the existence of the positive list and
the negative list may create some limitations on the ingredients that can be used by manufacturers,
they provide clear support for manufacturers to gain certification or validation for their products
on global markets.
2.4.6. GMP System – Good Manufacturing Practice
Many manufacturers of functional food products prefer to follow the Good Manufacturing
Practice (GMP) framework to ensure the goods are produced with a high degree of health and
quality. The program ensures the manufacturing process meets the regulations necessary. The
GMP requirement is not limited to manufacturers alone; it may extend to include the packaging
and labeling facilities, as well as the distribution centers and storage facilities. This program offers
the customer the assurance that the product has the highest standard of protection, honesty, power,
purity, consistency, and composition (SISPQC). The GMP program is not limited to produced
goods only. It focuses on the entire production environment, covering all the premises required for
product marketing, the quality assurance of the personnel involved in creating the products, and
the various processes the manufacturer used (Bagchi, 2008). The GMP method is distinct from
28
country to country. We found that the United States, Korea, Taiwan, and China have dedicated
GMP systems for producing functional food products. According to the general food legislation,
the EU has HACCP and food GMP. According to the Food Sanitation Act, Japan has the HACCP
requirement, and GMP is for supplement type foods such as tablets and capsules. Singapore does
not require a particular GMP for functional foods, however there are several GMP systems used
in the country in general.
2.5. Functional Food Regulations Conclusion
The global market size of functional food is constantly increasing, particularly with the
increase of the elderly populations and the increase in life expectancy. Consumers in several
markets around the world began to learn more about the benefits of functional foods, fueled by a
rise in disposable income. The Asia-Pacific market is the world's leading regional market for
functional foods generating nearly 40 percent of global revenues in 2017, and a compound annual
growth of nearly 8 percent over the coming six years is also highly expected.
It is highly expected that the FFC to become Japan's key regulatory mechanism, in which
companies can sell their goods while planning to obtain the FOSHU licenses. The study has shown,
after observing the rules and regulations in different countries, that compliance with various
certifications and disclosure of product details are essential in the United States. The
implementation of these steps involves a very high expense that may present problems for Japanese
goods in American markets. There are less constraints on the Singaporean markets, and it is
considered an attractive economy and marketplace for the Japanese products.
29
China is seen as a vast and rising market. Due to many health risks and the rise of non-
communicable diseases such as obesity, the Chinese market is turning towards functional foods.
China has a large number of senior citizens too. The reasons set out above makes China an
attractive market for Japanese goods. It is strongly recommended to start promoting the products
listed in each country's positive list such as the list of China, since that it will have far lower
development costs, and to target countries with less entry barriers. We also suggest further
negotiations with each country's approved agencies to promote and accelerate product promotion
with a view to preventing uncertainties.
Another way to reach a crucial and diverse market like the United States is by marketing
the practical food commodity to targets. The American functional food market is rising by 10
percent annually, allowing the main ingredients to be constantly supplied. The global market for
functional food ingredients is close to USD 67 billion in 2017, and an annual compound growth
of 6.7 per cent is expected over the coming years (Data Bridge, 2017).
Small start-up companies that are shaping and revolutionizing the food's future might also
use the findings. The research provides the startups with important knowledge by partnering with
manufacturers in this area to create new products or solutions for the international markets.
The table below summarizes the findings of the global functional food regulations
comparison, which compares the regulations in Japan, US, EU, China, Korea, Taiwan and
Singapore. The table summarizes the comparison especially the points mentioned above, and it is
the product of the collaboration of several co-authors in a peer reviewed article that we have
published earlier in 2019.
30
Table 7 | Summarization for the global functional food regulations (Source: Farid, et al. 2019)
Item Japan US EU China Korea Taiwan Singapore
Regulatory Agency CAA/MHLW FDA EC CFDA MFDS TFDA HSA
Category Food Food Food Food Food Food Food
Shape description (tablet, etc.)
No Yes Yes Often No No Yes
Purpose: Supplement of meals
Yes/No Yes Yes Yes Yes Yes Yes
Purposes: Treatment of diseases
No No No No No No No
Approval System (Business · Item)
In parallel No Yes Yes Yes Yes No
Safety review system for the ingredients
Depends Yes Yes Yes Yes Yes Yes
Presence of positive list Yes No Yes Yes Yes Yes Yes
GMP system by country Yes Yes Yes Yes Yes Yes No
Clinical trials of individual products
Depends No For new ingredient New Ingredient Depends Depends No
Adverse reaction reporting system
Yes Yes Yes No Yes No No
Obligated to display the category name
Yes Yes Yes Yes Recommended Yes Recommended
Obligations to display the certification mark/approval number
Depends No No Yes Recommended Yes No
Obligated to display the usage and dosage
Recommended Yes Yes Yes Yes Yes Recommended
31
3. Genetically Edited Food Regulations 2
3.1. Background
After conducting the regulations review of the functional food in Japan and globally, and
identified the potential opportunities for Japan to expand abroad in this field, the study has started
to develop and cover a more innovative field which is genetically edited food. This chapter focuses
mainly on the second research question (What are the key differences in terms of genetically edited
food regulations between Japan and overseas?).
The study in this chapter aims to identify the major differences in the regulations between
Japan, the United States, and the European Union in the field of genetically edited food and
discover the potential of expanding this industry. This chapter focuses mainly on the literature
review and the secondary sources represented in the governmental regulation reports and press
releases.
3.2. Genetically Modified Food
Although there is a certain unified definition that defines genetically modified food, there
are numerous definitions that define GMOs. One of the most cited definitions for GMOs is the one
issued by the World Health Organization WHO, defining GMO food as food produced from or
using genetically modified organisms. Also, the WHO has another definition for GMOs in general
as "organisms in which genetic materials have been altered in a way that does not occur naturally".
While the United States Department of Agriculture USDA states that GMO is "An organism
produced through genetic modification", the European Union is in consensus with the same
definition as the WHO definition mentioned above.
2 This section may include an adaptation of Farid, et al., 2020
32
GM foods are typically food containing genetically modified organisms (GMOs). In other
words, the DNA of the species to be used as food, is altered or modified by means of biotechnology
or without natural recombination. This method is also often referred to as "DNA recombination"
or "genetic engineering." Genetic modification technology enables the selected gene to be
transferred from certain organism to another or between non-related species.
The key justification for the production of GMO food is to provide food with a higher
nutritional level as well as a greater tolerance to bacteria and herbicides. Bacillus thuringiensis
corn or Bt-corn is one of the most common examples of genetically modified food. Bt-Corn has
been developed to contain specific proteins that can work against insects or pests. Because of its
particular characteristics, Bt-corn needs fewer pesticides and has a high degree of herbicide
resistance. Bt-corn is now commonly used in the United States and has an acceptance rate of 83%.
The use of GMOs in food has led to significant controversy. To date, the majority of the
scientific community has concluded that there is no proof of substantial threats to humans from
the use of genetically modified food. A study published in 2014 by Critical Reviews in
Biotechnology found that researchers reviewed all health studies and scientific papers published
between 2002 and 2011 on the health of GMO food; on the basis of this analysis, there is a
scientific consensus that the use of genetically engineered or genetically modified food is popular
worldwide and there is no proof of any related hazards.
In addition, a major analysis of genetically modified crops carried out by the National
Academies of Science, Engineering, and Medicine in 2016 confirmed that there are solid scientific
grounds and facts to prove the safety of genetically modified crops.
33
Another research on sustainable agriculture has established a wider agreement that there
has been no adverse impact on health or the climate from the cultivation of genetically modified
foods. This was decided after 14 years of continuous cultivation of GMO crops and cumulatively
planting more than two billion acres. The report also states that the European Commission-related
research lab has concluded that there is no major difference in human health impacts between
genetically modified crops and conventionally grown crops.
3.3. Genetically Edited Food
Genetic editing is seen as one of the fairly modern developments in genome engineering.
It is significantly different from genetic modification, in which gene editing of a particular genome
directly edits genes. The gene modification method usually randomly integrates a foreign gene
into the genome to alter the characteristics of the organism. Gene editing, however, transfers the
updated gene to a specific location in the genome, which determines the ultimate outcome of the
process. Over the last few years, various types of genome editors have been used, but CRISPR-
Cas9 is considered to be the most accurate tool. The use of gene-editing technology, namely
CRISPR, in food and agriculture, presently requires comprehensive research efforts. It also has the
ability to create significant importance for both farmers and consumers by limiting any potential
risks associated with genetically modified food.
CRISPR is the abbreviation for "Clustered Regularly Interspaced Short Palindromic
Repeats". Scientists use this technique as molecular scissors in order to specifically target gene in
the genome to be edited with an extremely high degree of precision. The procedure begins when
scientists identify a specific gene in the genome that is responsible for some of the features that
need to be modified. Scientists are developing an RNA guide (short for ribonucleic acid) that
simulates the sequence of DNA that needs to be modified, as well as the Cas9 enzyme, which cuts
34
the actual sequence at the desired location. After the break, scientists can add or modify different
functions, and after the change, the cell can be repaired using its enzymes. After removal of the
guide RNA and Cas9 enzyme, the DNA editing protocol is deemed complete, and alterations are
implemented in relatively close to traditional organism breeding processes.
Figure 5 | How genome editing (CRISPR) works
Taking into consideration that genome editing technology is deemed scientifically safer
than genome modification technology, Japan's regulatory authorities find that food produced by
genome editing technology is close to that produced by traditional breeding. However, an online
survey study conducted by the University of Tokyo, involving more than 38,000 respondents,
found that 43% of respondents expressed a lack of willingness to eat agricultural products
1. identify the sequence to edit
2. Create guide RNA 3. Attach RNA to enzyme Cas9
4. Allocate and match to cut 5. Cut, modify, paste DNA editing
How CRISPR works
35
generated by genome editing technology while nearly 9 percent only of the respondents have
shown a clear sign of willingness to adopt the genetically edited food products in the future.
3.4. GMO and Gene-Edited Foods Regulations
Regulations for the classification and labeling of genetically modified food are perceived
to be well-formulated in contrast to the regulations regulating genetically edited food, provided
the context of the marketing of genetically modified food started since 1994. In several regions
around the world, GMO regulations are gradually being formulated to comply with the latest
guidelines on health and safety and to conform with consumer labeling requirements.
This segment summarizes the laws governing genetically modified food as opposed to
those controlling genetically edited food in three regions: Japan, Europe, and the United States.
Regulations differ by region in regard to the labeling of genetically modified food. In
particular, it can be categorized as compulsory labeling or voluntary labeling. In the voluntary
situations, the authorities shall give the producer the option of labeling a genetically modified food
product unless there are substantial variations in the composition or allergenic potential of the
traditional food product, at which point the labeling is mandatory. Compulsory or
mandatory labeling may also be divided into two main categories, the pan-labeling, and the
designated product labeling. Products must be branded in the pan-labeling category if they contain
genetically modified products that exceed a certain threshold standard set by the regulatory
authority or if the product has substantial variations from the conventional one. For the designated
products labeling, specific products identified as genetically modified by the regulatory authorities
must be classified in the genetic modification category.
36
In regard to genetically edited food, the regulations are still at the stage of development
where each nation establishes effective regulations on a domestic basis, as there are no
unified global regulations in this aspect. However, the regulatory authorities are divided based
on two main legislative strategies. The first strategy is to classify genetically edited foods as
genetically modified foods, which must have strict safety regulations and detailed safety inspection
for each product individually. The other approach is to deem genetically edited food products
similar to conventional products because, in many cases, there is no significant distinction between
genetically edited products and conventionally bred products.
3.4.1. Japan's Regulations
Regarding the genetically modified products, the designated Japanese authorities have
confirmed that all crops or processed food containing certain GM materials must be labeled.
Regulations for processed food products specify that if one of the top three ingredients in the
product weight ratio contains genetically modified material or if the genetically modified
ingredients account for more than five percent of the total weight ratio of the product, they must
be labeled genetically modified. However, compulsory labeling is not necessary in the case of
genetically modified materials, which cannot be detected in specific products such as oil or sauce
products.
As discussed earlier in the introduction section, the genetically edited foods are
significantly different from the genetically modified food in terms of characteristics, development
methodology, and process. As a result, the Japanese Ministry of Health, Labor, and Welfare
(MHLW) began discussing how to control food created by genome editing technology in
September 2018. On the 27th of March 2019, after studying 691 comments received from the
37
public on the subject, MHLW published its policy on the regulation of genetically edited food
products.
The MHLW designated committee of experts in this regard recommended that any food
created by genome editing technology containing transgenes should be subject to the same safety
standards as those established in the current genetically modified food regulations. If the food does
not contain transgenes, it will not be treated in the same way as the food produced by DNA
recombination technology. The Consumer Affairs Agency (CAA) is responsible for labeling and
consumer safety in Japan. At the end of 2019, the CAA announced that, apart from GMO products,
which are subject to strict labeling and safety controls, products created by genome editing
technology do not require specific labeling, and it will be treated as conventional food products.
3.4.2. EU's Regulations
Laws governing genetically modified food are considered to be the most strict labeling
regulations in the world, as all genetically modified food products in Europe must be labeled in
compliance with the 1998 European Commission ruling. In November 2003, the laws and policies
governing genetically modified food were amended to include genetically modified foods with
undetectable genetically modified DNA. The Regulations have specified that conventional food
products must have genetically modified labels if it has 0.9% or more of its ingredients consists of
genetically modified content.
On the 25th of July 2018, the Court of Justice of the European Union released press release
No 111/18 specifying that genetically edited food should be regarded as a subset of genetically
modified food because it is already based on a genetic engineering approach. Subsequently, all
food produced using genetic editing technology would have to comply with all labeling and safety
38
inspection rules and regulations governing genetically modified food. This judgment was contrary
to Japanese regulations, which make a full and clear distinction between genetically modified food
and genetically edited food products in terms of the technology used and the nature of the products.
This decision was seen by European research laboratories and biotechnology experts as a
setback to advancement in food technology in Europe as it will hinder the innovation in this regard.
This decision is considered to be an obstacle to scientific progress in the region because many
scientists in different countries around the world are suggesting using gene-editing technology to
help solving the food and agriculture-related economic challenges.
3.4.3. USA Regulations
The regulation of genetically edited food in the USA is still in the process of
conceptualization. Nevertheless, numerous drafts and official meetings have been held in this
regard. On the 11th of January 2017, the FDA released a proposal named “Genome Editing in New
Plant Varieties Used for Food,” which was intended to be a primary regulatory guideline and to
gain a general opinion on the procedure of regulating genetically edited food products. The Food
and Drug Administration has described genetically edited food as a food created by genetic editing
technology that enables scientists to make specific changes at a specific location of a genome.
Gene editing can be done using a number of methodologies, including CRISPR, Zinc Finger
Nucleases (ZFNs), Transcription Activator-like Effect Nucleases (TALENs) and Oligonucleotide
Directed Mutagenesis (ODM). In addition, the Food and Drug Administration has limited
genetically modified foods by requiring them to comply with the same food safety requirements
as traditional breeding foods. Although that there are no clear regulations for the genetically edited
food products yet, however, the American Department of Agriculture USDA is currently planning
to take the approach of classifying the genome edited crops as conventional crops, since that the
39
alteration caused by genome editing technology may also be conducted using the traditional
breeding methods. However, the Food and Drug Administration is taking a different approach in
terms of genetically edited livestock, as the FDA is conceptualizing the idea of regulating genome
edited livestock as strict as the pharmaceutical drug regulations.
3.5. Conclusion
Genetically modified food laws are radically different between Japan, Europe, and the
United States. Japanese and European systems abide by compulsory regulations, while the US, as
stated above, abides by voluntary regulations. Regulations governing the labeling of genetically
modified food tend to be tighter in the European Union, as all products containing genetically
modified food ingredients must be labeled, even though GMOs are not detectable in the finished
product. In addition, the regulations on genetically edited food products follow the same system
as those on genetically modified food in Europe, which has created a dilemma for biotechnology
laboratories in the region as the decision hinders innovation in the field of genetically edited food.
In addition, the European decision to label genetically edited food as genetically modified
food has created another obstacle for the food safety laboratory and inspection units, as inspectors
are now required to test if the food contains genetically modified substances; however, scientists
are still struggling to find an effective method, since genetically edited food is difficult to be
differentiated than the food produced by conventional breeding methods.
The table below shows the analysis of both genetically modified and genetically edited
food regulations. It was developed on the basis of the reports by the Food Safety Center of the
Hong Kong Government and based on the analysis of other governmental sources, such as the
United States Department of Agriculture (USDA), Food and Drug Administration (FDA), Ministry
40
of Health and Welfare (MHLW) in Japan, Consumer Affairs Agency (CAA) in Japan and
European Commission (E.C.).
On the basis of the above analysis, it is concluded that the Japanese system is opening the
doors to more progress in genetically edited food products and boosting innovation in this field.
Gene editing is a ground-breaking approach to addressing many food safety and security issues
and is radically different from the genome modification approach.
Japan has many agricultural challenges, and genetically editing food can be a major step
forward in crafting potential solutions to these challenges. In Japan, the regulations governing
genetically edited food are quite attractive for biotech companies to innovate in this field. Japan's
regulations allow companies to develop their products without further inspections compared to
genetically modified food.
The main question continues to be whether Japanese consumers are able to accept
genetically edited food products because they are a new form of product that also has the term
'genetics' in their name. In the earlier part of this research, several scientific articles have been
reviewed, which showed that the GMO or any genetics related term had been linked to a number
of consumer health concerns.
Therefore, and to continue exploring the main aim of this research, the upcoming chapters
shall explore more the level of acceptance of the genetically edited food among the potential
Japanese consumers, also exploring the factors that can affect or enhance the acceptance level for
similar products.
41
Table 8 | Genetically Modified and Genetically Edited Foods Regulations Comparison (Source: Farid, et al., 2020)
Comparison Aspect Japan Europe USA
GM Regulation Type Designated products labeling Pan-Labeling Voluntarily Labeling
GM Regulatory MHLW, CAA E.C. USDA, FDA
Advantages of GMO Regulations
Provides moderate notification for consumers
in case the food components contain GM ingredients higher than a
certain level
Provide clear identification for consumers regarding
the GM components
Provides explicit notification for customers with a specific allergy or
dietary need
Disadvantages of GMO Regulations
Does not meet the needs of the consumers who would like to ensure that the food does not contain any GM
materials at all
Difficult to ensure its full enforcement by the
government due to the limitation of the dedication
for GM components in many cases
Does not provide clear identification for GM
products for the customers sensitive to this matter
Gene-edited food regulation Yes No In the development stage
Gene-edited food commercialization No No Yes (Soy Oil)
How gene-edited food categorized As conventional food As genetically modified
food
In the development stage; however, USDA has a potential approach of
having gene-edited food as conventional, and animal products as genetically
modified
Gene-edited food requires safety testing
No, a voluntary notification system may
apply
Yes, require full testing as genetically modified food In the development stage.
Gene-edited food requires specific labeling No Yes, similar to GMO In the development stage.
42
4. Genetically Edited Food Acceptance 3
4.1. Background
In the previous chapter, the regulations of the genetically edited food were discussed, and
a comparison between the regulations in Japan, the United States, and the European Union has
been conducted. Based on the results of the comparison, it was found that the regulations in Japan
give the manufacturers of the genetically edited food the ability to innovate, since that the
genetically edited food products shall not require any further inspection or labeling, due to the fact
that it can be very hard to differentiate it from the conventional food products. However, although
that it these regulations in Japan gives the manufacturers an opportunity to expand in this market,
the real question would be if the Japanese society is willing to accept this type of genetically edited
food in the future or not, giving into consideration that genetically modified foods have been
associated with negative image among consumers, and many consumers often think that
genetically edited food and genetically modified food are the same types, due to the fact that both
have the term of “genetics”.
Therefore, in this chapter, the study will focus further on the potential acceptance of the
genetically edited food products among Japanese consumers, and more specifically, the youth
segment. Also, the study shall explore the factors that affect the acceptance level the most.
4.2. Survey Design
In order to measure the factors affecting the acceptance of genetically edited food, the
survey was designed to adopt the methodology of structural equation modeling SEM. In this study,
several factors have been selected as constructs with an aim to measure the main construct of
3 This section may include an adaptation of Farid, et al., 2020
43
willingness to purchase. Also, the study has put particular focus on the main factor, which is
knowledge, giving into consideration, the importance of science communication and knowledge
in affecting consumer behavior towards certain products or services. Also, the “attitude towards
technology” was considered a construct in this study, in order to measure how the people who
accept technology, in general, will perceive the genetically edited food products. The other three
constructs were studied as well, namely, trust, perceived benefits, and perceived risk in order to
measure how those factors affect the potential adoption of the genetically edited food products in
general. The constructs were selected based on several studies measuring the acceptance of
technology in general and biotechnology in specific. The studies have shown that perceived
benefits and trust have a positive effect on the willingness to purchase, while the perceived risk
has a negative effect on the willingness to purchase.
One of the critical challenges in this study is considered the lack of knowledge about
biotechnology in general among consumers, specifically the lack of knowledge regarding
genetically edited food. Usually, the general public cannot differentiate between genetically edited
food and genetically modified food, giving into consideration that genetically edited food is a
relatively new method, and also genetically modified food is often discussed in different media
sources. In order to tackle this challenge, and measure the effect caused by the lack of knowledge
as well as measuring the effect of science communication, the survey has been conducted two
times with intervention between them. The intervention has come in the form of a short
introductory presentation for less than 5 minutes between the two surveys, providing more
information about the genetically edited food and how it distinguished from genetically modified
food in terms of methodology and techniques. The intervention presentation has discussed the
issue of risk in terms of genetically engineered food in general, also the associated risk with natural
44
food products either in the case of organic food or non-GMO products. The presentation also has
shown scientific facts about GMO products and the level of its production in the American market,
especially in the case of soybeans or corn. The presentation has ended by a slide showing real
examples of genetically edited food products in the United States and Japan, in order to raise the
awareness about the potential possibilities of utilizing gene-editing technology in the food
industry.
As mentioned above, the survey was conducted twice, both in the same session with
intervention between them, as shown in the figure below. The reason behind that, is to extract the
immediate reaction of the respondents after getting the science communication intervention. The
surveys before and after the intervention were identical, with the exact same list of questions, in
order to clearly identify the effect of science communication on raising awareness and affecting
the attitude towards genetically edited food.
Figure 6 | Data collection session design
General Introduction
5 Minutes
Survey 1
15 Minutes
Intervention
5 Minutes
Survey 2
15 Minutes
Identical survey questions
45
4.3. Responses Collection
On the 24th of December 2019, the survey was conducted in the Osaka Ibaraki Campus of
the Ritsumeikan University in the City of Osaka, Japan. The survey took place at a main session
for the business administration school. The session was attended by nearly 240 participants whom
their age averaged 20 years old. Although the respondents were randomly selected in general,
however, selecting the business school students in particular to be the place of the study was
determined. The selection of the business school came due to the fact that the survey aims to study
the public perception in general, so schools related to technology, science, biotech, and life science
were generally avoided in order to remove the bias of previous knowledge and familiarity about
the topic. Therefore, the majority of the survey respondents didn’t have prior solid knowledge
about biotechnology or genetically edited food in specific. In order to avoid the awarding bias, and
maintain professional data collection standards and integrity, the study did not offer any type of
financial or non-financial award for the respondents by any level, and responding to the survey
questions was totally a voluntarily act from respondents who seek for developing the scientific
knowledge and participate in this study.
The survey respondents have participated in both surveys before and after the intervention
in the same session, where the whole process has been conducted in nearly 40 minutes, including
the answer of both surveys, attending the intervention presentation, and introduction. The
respondents have used their own electronic devices to respond instantly to the survey question.
The first survey was responded by 216 attendees, and after attending the short intervention
presentation, the second survey was responded by 207 attendees. After comparing the completed
samples and eliminate the respondents who participated in only one survey and did not participate
46
in the other, the number of completed samples was consolidated into 180 complete samples who
answered both surveys completely, as shown in the figure below.
Figure 7 | Diagram explaining the number of survey respondents
4.4. Survey Demographics
As mentioned above in the data collection subsection, the survey took place in the
Ritsumeikan University, Osaka Japan, which resulted in 180 completed samples. Apart from SEM
related questions, several demographic questions were asked as well. Based on the responses
received regarding the gender of the respondents that 84 respondents were female, representing
47% of the total number of respondents, while 96 respondents were male, representing 53%.
Regarding the nationality of the respondents, the majority of the respondents were Japanese
national with 166 respondents representing 92% of the total number of the respondents, followed
by the 11 Korean nationals who presented 6% of the respondents, followed by 3 Chinese nationals
who represented nearly 2% of the respondents.
The survey also questioned the type of hometown that the respondents are originally from
in order to investigate if there is any difference in terms of technology acceptance between the
Total number of attendees 240
Survey 1 respondents
216
Survey 2 respondents
207
Survey 1 & 2 respondents
180 Survey 1 Survey 2
47
respondents from rural hometown in comparison with the respondents from urban hometown. In
this regard, the majority of the respondents were from urban hometowns, with 130 respondents
representing 72% of the total completed responses, while 50 respondents have shown that they
have rural hometowns representing 28% of the survey respondents.
Also, the survey has explored further the living status of the respondents, asking them if
they are currently living alone, or with family or with friends. The majority of the respondents
have replied that they are living with their family, which are 128 respondents representing 71% of
the total respondents. In the second position came 49 respondents who have shown that they are
living alone, representing 27% of the respondents, and only three respondents have shown that
they are living with friends, representing nearly 2% of the respondents, as shown in the chart
below.
Figure 8 | Demographics of survey’s respondents
9684
166
11 3
130
50
128
49
30
20406080
100120140160180
Male
Female
Japan
Korea
China
Urban
Rural
Family
Alone
Friend
s
Number of Respondents
Gender Nationality Hometown Living with
48
4.5. Theoretical Model and Literature Review
Based on the extensive literature review conducted, there is a research gap in the area of
discussing the acceptance of genetically edited food products in comparison with the genetically
modified food products. This lack of literature might be caused by the fact that genetically edited
food is a relatively new term, and there is a lack of knowledge among the public about it,
nevertheless that there are very few products in the market. Therefore, there is a difficulty in
creating studies about the acceptance of the product, and that is where the uniqueness of this study
relies on. In this study, the construct and the literature review were generated by reviewing
previous researches related to genetically modified food acceptance and the acceptance of
technology in general.
The conceptual model proposed in this research, as shown in the figure below, aims to
measure the direct and indirect impact of five different variables on the willingness to purchase
genetically edited food products. Nevertheless, several other insights could be explored regarding
the relationship between the factors and the effect of other factors such as the demographics.
The model tests the potential effect of the knowledge about biotechnology and genetically
edited food in specific, on the level of the consumers’ attitude towards genetically edited food
represented in the level of trust, perceived benefits, and perceived risks. Also, it tests a unique
factor namely attitude towards technology, testing how the consumer’s positive acceptance to
technology, in general, can affect positively the level of their awareness about the biotechnology
in general and genetically edited food in specific, also testing the effect of the positive attitude
towards technology on the trust in the biotech stakeholders. The model also tests how the level of
trust, perceived benefits, and perceived risks directly affect the willingness to purchase genetically
edited food products.
49
Figure 9 | Conceptual model to be tested in this study
4.5.1. KN | Knowledge
Knowledge is one of the key factors that affect the attitude towards a certain subject. The
more knowledge the consumer has about a certain product, the more the consumer can make an
educated decision about it and take a well-studied action, which in this case, we call it attitude. A
paper published by the University of California Agriculture and National Resources has discussed
the role of knowledge in creating perception towards biotechnology-based agriculture. The paper
has stated that consumer survey results show some key findings on consumer attitudes towards
biotechnology in agriculture. Based on the survey conducted, there is no consensus among
consumers whether biotechnology-based agriculture is beneficial or not. However, there is a
limited group of consumers who strongly have a clear opposing opinion towards biotechnology in
agriculture. Although this opposing group is limited in terms of numbers, however, they create
active movements strongly opposing biotechnology. Unfortunately, this type of activists deemed
Knowledge KN
Perceived Benefits PB
Trust TR
Perceived Risks PR
Willingness to Purchase WTP
Attitude Towards Technology ATT
50
to be successful in affecting public opinion. This negative effect is mainly caused by the lack of
scientific knowledge among the potential consumers and the lack of trusted information from
governmental sources or scientific sources that promotes the scientific evidence about
biotechnology safety. Although there are several academic materials describing this fact, however,
the materials published by academic sources lack the ease of access nor understanding among
public consumers. Therefore, the study has shown the importance of scientific knowledge among
consumers and how it can shape the attitude towards biotechnology-based products. Also, the
study highlighted the significant role that universities and governments can play in terms of science
communication and raising the awareness of the consumers about biotechnology. The educational
sources about this topic should be easy to obtained by the public, also written in simple language
that can be understood by the general public from different educational and social backgrounds
(James, 2004).
A study published by the Appetite journal exploring main factors that affect the attitude
and acceptability of genetically modified food products in Germany has highlighted that
knowledge is one of the key aspects that affect the attitude towards genetic modification, thus
affect the acceptability of genetic modification in an indirect way, as shown in the figure below
(Christoph et al., 2008).
51
Figure 10 | Attitude model for genetically modified food (Christoph et al., 2008)
Another study published by the Journal of Risk Research has investigated the relationship
between the knowledge, acceptance, and trust of technologically based hazards. One of the main
goals of the study was to investigate how personal knowledge of certain hazards has influence and
relationship with perceived benefits, perceived risks, trust towards the topic, and acceptability in
general. The study has involved over 500 respondents. All the participants were university students
studying industrial engineering in particular. The mean of the respondents' age was nearly 22 years
old. The study has investigated several factors, such as social risks, social benefits, acceptability,
social trust, and personal knowledge. The study has measured the above-mentioned factors in
association with several perceived hazards by consumers, including food colorants, agricultural
pesticides, antibiotics, food preservatives, herbicides, chemical fertilizers, and genetic
engineering. The study has confirmed the model stating that there is a correlation between trust,
perceived risk, perceived benefits, and acceptability. The study has shown that the respondents
have a relatively high level of knowledge of environmental-related hazards with an average of 4.8
where all the other aspects are ranging from 3.3 to 5.4, especially regarding the atmospheric
Sociodemographic Characteristics Knowledge Perception of personal
health risks
Attitudes towards genetic modifications
Acceptability of genetic modification
52
pollution, which has scored 5.4. In the same survey, the respondents had a low level of knowledge
of genetic engineering, which has scored an average value of 3.8. Also, different aspects related to
agriculture have scored low in the knowledge index as well, such as herbicides that scored 3.3, and
pesticides which scored 3.5. Therefore, the study has implied that genetic engineering has a low
level of knowledge among the general public in general and needs more efforts in terms of science
communication and awareness, as shown in the figure below (Bronfman et al., 2008).
Figure 11 | Level of knowledge associated with certain hazards
Therefore, and based on the above-mentioned studies, in this study, the construct of
knowledge has deemed to be essential in measuring the factors that affect the acceptance of the
genetically edited food products. Therefore, in this construct, the study has focused on
investigating the potential effect of knowledge on trust, perceived benefits, and perceived risks. In
this regard, the study analyzed the level of information the respondents had on genetically modified
food and genetically edited food, as well as whether they could distinguish between them.
5.45.1
4.4
4.03.8
3.73.6
3.63.6
3.63.5
3.3
0.0 1.0 2.0 3.0 4.0 5.0 6.0
Air pollution
Ozone layer depletionClimate change
Nuclear powerGenetic engineering
Water fluoridationFood colorants
Chemical fertilizersChemical disinfectants
Food preservativesPesticides
Herbicides
Knowledge
53
Therefore, the study has explored whether the respondents understood the potential for the use of
genetic editing technology in food, as well as its impact on animals’ safety and wellbeing to gain
more knowledge of this technology. The questions asked in this construct are as following;
Table 9 | List of questions related to the Knowledge construct (Farid, et al., 2020)
Code Variable Measured (Questions)
KN1 I understand what genetically modified food is
KN2 I understand what genetically edited food is
KN3 I understand clearly the difference between genetically modified and genetically edited
KN4 I understand the potentials of utilizing gene editing technology on crops/food
KN5 I understand the potentials of utilizing gene editing technology on animals
KN6 I understand the potentials of utilizing gene editing technology on human health
KN7 I am willing to learn more about gene editing technology
4.5.2. ATT | Attitude Towards Technology
Attitude towards technology construct assumes that there are several consumers have a
positive attitude towards technology, and this attitude differ from consumer to another. One of the
most famous and well cited models in this domain is the technology adoption life cycle model or
as known as Rogers’ bell curve. This model was published back in the year 1957 by Bohlen, Beal
and Rogers from Iowa State University in the United Stated. The model aimed initially to create
further understanding to processes related to agriculture and home economics. The others have
continued their research efforts in developing a model named diffusion process (Rogers, 1957). In
a later stage one of the authors namely Everett Rogers has issued a book named “Diffusion of
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Innovations” in the year 1962 (Rogers, 1962), where he made a generalization out of the model to
be used in visualizing the technology adoption rate in general. The book was updated over the
years till it reached to its fifth edition published in the year 2003 (E.M. Rogers, 2003). The model
shows 5 levels of technology adoption, which clarify that consumer attitude towards technology
vary from a consumer to another, as well as its impact on the willingness to purchase. The
innovation adoption lifecycle clarifies that 2.5% of the consumers are considered innovators who
start adopting the products in very early stage. Followed by 13.5% of the consumers considered as
early adopters. Followed by 34% of the consumers considered as early majority. Followed by 34%
of the consumers considered as late majority. Ending with 16% of the consumers considered as
laggards as shown in the figure below.
Figure 12 | Categorization of products adopters
Innovators are enthusiastic to try new ideas, to the extent where they are almost intrigued
by their riskiness. The interest of innovators of new technologies takes them out of a small
community of peers and into more cosmopolitan than normal social ties. Early adoptions tend to
be more inclusive than innovators in the local social system. The early adopters, as opposed to the
cosmopolitan innovators, are considered localists. In most social environments, people in the early
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adoption group tend to have the highest degree of opinion leadership. Early-majority leaders will
accept new ideas well ahead of a traditional member of the social-system. They often interact with
peers but are not often found to hold positions of leadership. The late majority is a cynical crowd,
taking fresh ideas only after the traditional social network user. Their adoption can be supported
by economic necessity and an increase in social pressure. Laggards are traditionalists and the last
to take on board innovation. With almost no leadership of opinion, the laggards are local to the
point of being isolated from the other categories of adopters. (E.M. Rogers, 2003).
Several other studies have shown a clear relationship between the attitude towards
technology in general and the trust in technology. A paper published by emerald insight was
exploring how trust can fit in the technology acceptance model TAM in critical topics such as
mobile money among very financially sensitive consumers in India who live below the poverty
line. The study has conducted a survey by gathering data samples from 225 actual and potential
mobile money consumers and analyzed the results by utilizing the partial least square
methodology. The findings suggest that TAM's trust and core constructs, such as attitude towards
technology usage and perceived usefulness, contribute to the impact of mobile money acceptance
intention and increase the willingness to adopt. Although that this study aims to investigate the
willingness to acceptance of mobile money, which is not the topic of this research, however, this
study was found useful since that both mobile money and genetically edited food are considered
new technologies, and the audience often perceives both of them with risk mentality especially
that the willingness to adopt in this study was related to financial product examined in a very
financial sensitive environment among consumers below the poverty line (Chauhan, 2015).
Another study was published by the journal of computer and information systems in this
regard, exploring if the trust is important in technology adoption. The study has stated that trust
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study in the context of technology adoption is one of the initial building of trust and clarified that
a person must make a “leap of faith” when he is committed to new technology because of a lack
of complete information. This study uses institution-based trust theory to compare the features of
emerging technology with the confidence-building stance of potential players. This trustful attitude
is then correlated with the decision to implement the technology. The study model was evaluated
using policy capture. Policy capture is a simulation-based decision-making technique that enables
the researcher to experience a simulation of real decision-making. The questionnaire was provided
to nearly 180 undergraduate students. The results of this exploratory study suggest that trust is an
important component in the acceptance and adoption of technology and that this concept should
be incorporated into future technology-based research (Bahmanziari et al., 2003).
Another study also published by the journal of engineering and technology management
was investigating several factors related to increasing the acceptance of risk-related technology
such as autonomous driving. The research has found that trust is one of the main factors affecting
the attitude towards technology and the adoption rate towards new technologies as well (Kaur &
Rampersad, 2018).
Another study was published by the British Food Journal also in the year 2016 to
investigate the attitude towards GMO food. The study examined the attitudes towards GMOs that
have shown that the majority of respondents agree that science and technology are important to
human development and, in particular, to social growth and to the local economy. The study has
also found a positive correlation between attitudes towards technology in general and the belief
that genetically modified foods can boost agricultural production (López Montesinos et al., 2016).
Therefore, and based on the above-mentioned study, in this construct, we aim to explore
the relationship between the attitude towards technology and knowledge, as well as the attitude
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towards technology and trust. In this construct, it can be argued that consumers who have a positive
attitude towards technology, and in other words from the innovators or the early adopters of the
technology, will have a higher level of knowledge about biotechnology in general and might have
more knowledge about genetically edited food in specific. Also, consumers with a higher level of
positive attitude towards technology might have a higher level of trust in the biotechnology and
genetically edited food products. Therefore, the questions in the table below were formed to
investigate more the level of respondents' attitude towards technology, also the level of
understanding for technology related news, as well as the willingness to discuss and accept new
ideas.
Table 10 | List of questions related to the “Attitude Towards Technology” construct (Farid, et al., 2020)
Code Variable Measured (Questions)
ATT1 I am interested in science and technology in general
ATT2 I think that utilizing new technologies is essential for society development
ATT3 Generally, I understand science and technology news on Media (TV, Radio and Newspaper)
ATT4 I am usually interested to try new technological products such as new electronics
ATT5 I would like to purchase the electronic products once they arrive in the market
ATT6 I think that utilizing new technologies will continue to enhance Japan's economy
ATT7 I am willing to discuss new ideas even if it is against my beliefs
4.5.3. TR| Trust
Trust is a key component in the consumer behavior study. Several scientists have studied
the effect of trust on the willingness to purchase or increasing the adoption rate of certain products
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or services. More and above, scientists have made more efforts to study the factors that affect trust
and how to increase it. Moreover, despite the essence of the uncertain option situation involving
applications for biotechnology, trust emerges as a key variable that is often seen as a factor that
eases the decision-making process in the time uncertainty (Viklund, 2003). A paper published by
food quality and preference journal exploring the perceptions of risks and benefits related to GMO
food has argued that there is indeed a knowledge gap in the field of genetic engineering among
consumers. This knowledge gap was created due to the lack of trusted sources of information, and
that most information trending about this topic are coming from nonscientific sources (Costa-Font
& Mossialos, 2007). Therefore, more efforts needed in the area of science communication
especially related to the benefits and risks communication in order to boost the trust in genetically
engineered products.
Another study published by Moon and Balasubramanian has suggested a model examining
the public acceptance for GMOs. The study has utilized Fishbein multi-attribute model to develop
an empirical model to examine and explore the attribute of agriculture biotechnology as well as
the characteristics that encourage the public to accept utilizing biotechnology in food. The study
has shown that consumers in the UK and USA, consider that the government is the essential source
of information regarding genetic engineering technology. Therefore, trust in government
information is considered to be one of the essential drivers to enhance the awareness and
acceptance rate for biotechnology products, especially GMO food (Moon et al., 2001). This
research is examining the same factor of trusting the government in increasing the acceptance of
genetically edited food products.
Another study was conducted by a group of researchers at Colorado State University to
identify further how the general public trust different information sources about agriculture and
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biotechnology. The survey was conducted to explore the most trusted source of information among
Colorado residence, exploring different sources such as governmental sources, social media, media
reports, national government, local government, companies, universities, and other sources. The
survey has utilized four levels Likert scale survey, where if the respondents answered by 1, it
means that the information source is highly trusted, and four means the information sources are
not trusted. Based on the survey results of 403 respondents representing Colorado residence on a
proportional basis, it was found that in terms of agriculture, the residence considers universities,
research organizations, farmers, and the Colorado Department of Agriculture are the most trusted
source of information with an average mean value of 1.6. Where news reports in the media, as well
as food industry corporations, scored 2.5. Social media came at the bottom of the list of trusted
sources about agriculture with an average score of 2.9. Very similar results were obtained when
the respondents were asked about their most trusted source of information about food quality and
safety. Universities, research organizations, and the Colorado Department of Agriculture came on
the top of the most trusted sources with an average score of 1.7. Where Food industry corporations,
as well as the news reports in the media, came with very low result of 2.4, and social media has
scored the lowest score in the trusted sources with an average of 3.0. (Michael J. Martin, 2016).
Based on the above-mentioned results, the official government sources, as well as universities,
have a high level of credibility among consumers. Therefore, it would be effective if universities
and governments join together in created trusted information sources for the public educating more
about gene engineering technologies.
Also, based on the papers reviewed above, the trust construct has been created in the model
as one of the core drivers to increase the willingness to purchase genetically edited food products.
The model examines the relationship between trust and willingness to purchase and also examines
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the extent of trust the respondents have towards different information sources such as academic
researches, scientists, biotech companies, government, farmers, and media, as shown in the table
below.
Table 11 | List of questions related to the “trust” construct (Farid, et al., 2020)
Code Variable Measured (Questions)
TR1 I have trust in academic researchers working on biotechnology projects
TR2 I have trust in scientists working on gene editing technology
TR3 I have trust in biotech companies that aims to utilize gene editing technology
TR4 I have trust in the government regulations that govern food safety in Japan
TR5 I have trust that biotechnology is providing great value to the society
TR6 I have trust in the farmers in Japan who will utilize gene editing farming technique
TR7 I have trust in the news (TV, Radio, Newspaper) promoting gene editing technology in food
4.5.4. PB | Perceived Benefits
Perceived benefit refers to the perception of the positive consequences of a particular
action. In behavioral science, the term perceived benefits is also used to describe the motivations
of a person behaving and taking action or treatment. Researchers and theorists seek to quantify
positive perceptions and perceived benefits because they conclude that an individual's cognition
influences behavior in terms of acceptability, motivation, and attitudes towards certain products,
services, or actions in case if the consumer had a positive perceived benefits level (Leung, 2013).
In this regard, several related published papers were reviewed. A study published by Plos
One in 2014 has highlighted several factors related to the acceptance of genetically modified food.
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The purpose of this paper is to assess the behavior of Malaysian stakeholders towards genetically
modified (GM) salmon and to identify factors that affect their acceptance of GM salmon using the
structural equation modeling methodology. A survey was conducted on over 400 participants from
different stakeholder groups in the Klang Valley region of Malaysia. The public attitude towards
GM salmon was assessed using seven-point Likert scales using self-developed questionnaires. The
results of this study have reinforced the complexity of public attitudes towards GM salmon and
should be seen as a multi-faceted process. Relevant application-linked expectations of the religious
acceptability of GM salmon followed by perceived risks and benefits, familiarity, and the general
potential of modern biotechnology are the most important direct predictors for encouraging GM
salmon. The study has highlighted the importance of perceived benefits by the consumers in order
to enhance the attitude towards genetically modified food, thus increasing the willingness to
purchase and willingness to adopt genetically engineered food in general (Amin et al., 2014).
One of the most well-cited studies in this field is a study by Bredahl examining consumer
attitudes and purchase intentions towards GM food products. The paper presents the findings of a
survey conducted in Denmark, Germany, Italy, and the United Kingdom to explore the growth of
consumer attitudes towards genetic modification and buying decisions on genetically modified
yogurt and beer in food production. In total, more than 2,000 customers were interviewed in the
four countries. The study has examined several factors that affect the attitude towards GM food,
and it was found that perceived benefits and perceived risks have a significant direct effect on the
attitude to GM food, especially in the case of the perceived risk that had a strong positive effect
on the attitude towards GM food as shown in the figure below (Bredahl, 2001).
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Figure 13 | Estimated attitude model towards GM food (Dane mark, Germany, UK) (Bredahl, 2001)
Therefore, and based on the studies mentioned above, the perceived benefits construct was
added to the research model due to its importance in several related studies to genetically modified
food acceptance. This construct measures several factors related to how the consumers perceive
several benefits related to the consumption and adoption of genetically edited food products such
consumer health benefits, animal health benefits, benefits related to the reduction of hunger in
third countries, economic benefits for the society, and financial benefits for the consumers as
shown in the table below.
Table 12 | List of questions related to the “perceived benefits” construct (Farid, et al., 2020)
Code Variable Measured (Questions)
PB1 I think that genetically edited food shall bring more health benefits for its consumers
PB2 I think that editing animal genes is a good approach for better animal health and comfort for the animals
PB3 I think that genetically edited food will help reducing hunger in developing countries
PB4 I think that genetically edited food shall be financially suitable for the majority
PB5 Utilizing gene editing technology shall boost the farming and agriculture in Japan
PB6 Utilizing gene editing technology shall enhance the Japanese economy and society
PB7 I think even if gene editing technologies have risks, scientists will be able to fix it in the future
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4.5.5. PR | Perceived Risks
Several studies have focused on the perceived risks regarding the consumption of
genetically modified food products. One of the main studies in this regard is the study authored by
Lone Bredahl, which was mentioned in the perceived benefits construct above. The study has
examined several factors regarding the risk perception of the consumers in Europe, such as
environmental hazards and human health risks. The study has also found the perceived risks
construct has a significant negative effect on the attitude towards genetically modified food
(Bredahl, 2001).
Another study also published by the food quality and preference journal has suggested a
framework to examine the intention to purchase GM food products among food consumers. The
study has utilized several models related to this topic, namely the benefits risk analysis model and
the theory of planned behavior model to examine creating a full framework exploring the major
factors affecting the genetically modified food acceptance. The study has examined several
attributes related to the perceived risk, such as the negative effect on the environment, and whether
the consumption of GM food might cause an allergic reaction, as well as whether the consumption
of GM food can create health-related risks on the consumer. The study has found that perceived
risks have a significant negative effect on purchase intention, as shown in the figure below (Zhang
et al., 2018). As shown in the figure below, both the attitude towards GM and perceived risks
constructs had a significant effect on the purchase intentions. Also, the trust construct had a
significant effect on the perceived risk construct ask well.
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Figure 14 | Path coefficient using benefits risk analysis model (China) (Zhang et al., 2018)
Therefore, and based on the above-mentioned studies, the construct of perceived risks has
been added to the research. In this construct, the study examines the direct effect of the perceived
risks on the willingness to purchase genetically edited food products. To examine this construct,
the study has highlighted several questions where the respondents express the level of risks they
perceive towards genetically edited food such as the risk of environmental damage, health-related
risks, unknown risks in the future, and allergic reaction risks as shown in the table below.
Table 13 | List of questions related to the “perceived risks” construct (Farid, et al., 2020)
Code Variable Measured (Questions)
PR1 I think that If I eat genetically edited food, my genome might get affected
PR2 I think that if I eat genetically edited food, it will create a negative effect on my health
PR3 I think that planting genetically edited seeds is considered as a risk for the environment
PR4 I think that editing animal genes shall create risks on animal health in the future
PR5 I think that If I consume genetically edited products, it may negatively affect my descendants
PR6 I think that utilizing gene editing technology in food might create more allergies
PR7 I think of risk consequences of using gene editing technology are still unclear
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4.5.6. WTP| Willingness to Purchase
The main aim of this study in general, is to examine essential factors affecting the
willingness to purchase genetically edited food. The above-mentioned studies in the constructs
have examined similar factors related to genetically modified food. Another study published by
the food quality and preference journal has examined the attitude of Taiwanese consumers towards
genetically modified food products. The study has utilized the structural equation modeling
method in order to examine several factors related to genetically modified food acceptance by
conducting a survey with over 550 respondents in several areas in Taiwan. The study has found
that perceived risks construct has a significant negative effect on the attitude towards GM food.
Also, that perceived benefits construct has a significant positive effect on the attitude towards
genetically modified food, as shown in the figure below (Chen & Li, 2007).
Figure 15 | Path coefficient using benefits risk analysis model (Taiwan) (Chen & Li, 2007)
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Therefore, and based on the above-mentioned studies and cited models, in this construct,
the study examines how the willingness to purchase genetically edited food products is affected
by trust, perceived benefits and perceived risks. In this construct also, the study examines several
variables related to the purchase intention and consumer behavior such as health-related benefits,
related financial benefits as well as the willingness to purchase for self-consuming or for a family
member in general as shown in the table below.
Table 14 | List of questions related to the “willingness to purchase” construct (Farid, et al., 2020)
Code Variable Measured (Questions)
WTP1 I am willing to purchase genetically edited food in general
WTP2 I will buy gene-edited food if it has less fat than ordinary food
WTP3 I would buy genetically edited food if it were cheaper than ordinary food
WTP4 I will buy genetically edited food if it is grown in an environmentally friendly way
WTP5 I will buy genetically edited food if it has better nutrients than ordinary food
WTP6 I will buy genetically edited food if it provides better health benefits
WTP7 I would buy genetically edited food as a gift for family or friend
4.6. Analysis of the Data
In order to analyze the data with a high level of accuracy and data integrity, IBM SPSS
was used, along with its special edition Amos for analyzing the conceptualized model. In this
aspect, the latest edition of SPSS was utilized, namely (version 26).
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4.6.1. Validity and Reliability of the Constructs
To validate the reliability and validity of the construct, the exploratory factor analysis EFA
was utilized using the IBM SPSS, and it was implemented specifically on the survey results after
the intervention to remove the lack of knowledge bias and maintain data integrity. While
conducting the factor extraction process, the maximum likelihood method was utilized in order to
maintain the highest level of data compatibility when building the model using IBM AMOS, since
that Amos uses the same method in model building. During the factor extraction process, the
number of factors was set as six, and the maximum iterations for convergence variable was set to
25. To identify the correlated factors, the analysis has used the rotation method of Promax,
combined with the Kaiser normalization method. For ensuring a high effect of the variables on the
main constructs, all the variables with a small coefficient below 0.3 were surpassed.
Several rounds have been conducted of the EFA, and based on the parameters mentioned
above of surpasses coefficients below 0.3 or the variables that got loaded into multiple constructs
in the analysis process, ten variables out of the 42 total variables were deselected from the model,
namely; the seventh variable of the “knowledge”; the first, third, fourth, fifth and seventh variables
of the “attitude towards technology; the third, six, and seventh variables of the “trust”, as well as
the seventh variable of the “willingness to purchase”. This process has resulted an increase in the
overall model fit after focusing the analysis on 32 variables compared with the full 42 variables
listed in the main SEM survey, as shown in the EFA analysis in the table below.
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Table 15 | Exploratory Factor Analysis
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6
KN1 0.789
KN2 0.947
KN3 0.826
KN4 0.804
KN5 0.737
KN6 0.488
ATT2 0.801
ATT6 0.597
TR1 0.815
TR2 0.844
TR4 0.408
TR5 0.378
PB1 0.508
PB2 0.77
PB3 0.678
PB4 0.526
PB5 0.795
PB6 0.465
PB7 0.529
PR1 0.594
PR2 0.837
PR3 0.781
PR4 0.752
PR5 0.802
PR6 0.684
PR7 0.448
WTP1 0.67
WTP2 0.858
WTP3 0.862
WTP4 0.785
WTP5 0.878
WTP6 0.726
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In the process of sampling adequacy measuring, Kaiser-Meyer-Olkain (KMO) test was
conducted using the SPSS software. The KMO test aims to create an accurate measure of the level
of suitability of the data to the factor analysis. KMO measures each variable included in the model,
as well as the completed model for sampling adequacy. The results of the KMO are ranged from
zero to one, where the results close to one refers to a higher level of sampling adequacy, and results
close to zero refers to a lower level of sampling adequacy. Several previous studies about the KMO
method have indicated that the KMO scores with a value ranging from 0.8 to 1, reflects that the
sampling process was adequate, where the KMO scores ranging from 0.6 to 0.8 are considered to
be borderline accepted, and finally, the scores less than 0.6 are reflecting the inadequacy of the
sampling process. Where the KMO values, which are more close to zero, indicate that there is a
large level of partial correlations in comparison with the sum of correlations, which means that it
may create a challenge in conducting the factor analysis. In the original paper crafting the KMO
test by Kaiser, six levels of KMO results were established, as shown in the table below (Revelle,
2016).
Table 16 | Kaiser-Meyer-Olkin KMO test, results guideline
KMO Score Min. KMO Score Max. Indication
0.90 1.00 Marvelous
0.80 0.89 Meritorious
0.70 0.79 Middling
0.60 0.69 Mediocre
0.50 0.59 Miserable
0.00 0.49 Unacceptable
Another test also used for ensuring that the sample is suitable for the factor analysis is the
Bartlett’s test. Bartlett test was introduced in the year of 1951 to test the sample sphericity. It
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examines if the matrix has significant differentiation compared to the identity matrix or not. It also
tests the correlations between the variables in order to provide estimated probability statistically,
showing if the matrix has a correlation among some of the variably with a significant level. The
test returns P-value to indicate the significance level. In case if the P-value returned for a sample
is less than 0.05, it indicates that the data is suitable to be used in the factor analysis process.
Regarding the first test of the Kaiser-Meyer-Olkain, which was conducted using SPSS
version 26, the test has resulted in a KMO value of 0.904, which indicates that the sample is
“marvelous” according to KMO guideline, and the sample has a very high level of sampling
adequacy. Regarding the second test, namely Bartlett’s test of sphericity, the P-value resulted in a
value below 0.001, which indicates a high level of significance. Therefore, the data were deemed
suitable for factor analysis, as shown in the table below.
Table 17 | KMO and Bartlett’s Test Results
Test Measure Value
Kaiser Meyer Olkain KMO Measure of sampling adequacy 0.904
Bartlett’s test of sphericity
Chi-Square 3805.085
Degree of freedom 496
Significance 0.000*
* indicates p-value less than 0.001 (high level of significance)
In order to ensure the study and analysis reliability, Cronbach’s alpha was calculated for
all the items tested. After calculating the Cronbach alpha using the reliability calculation function
in SPSS, the values were all found to exceed the 0.7, which is the recommended value for Cronbach
alpha reliability analysis, as shown in the table below. The Cronbach alpha results were calculated
as 0.902 for the knowledge construct with six items included, 0.702 for the attitude towards
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technology construct with two items included, 0.823 for the trust construct with four items
included, 0.870 for the perceived benefits construct with seven items included, 0.877 for the
perceived risks with seven items included, and lastly with the highest Cronbach alpha value comes
the willingness to purchase construct with a value of 0.933 with six items included. Based on the
results mentioned, the validity and reliability of the model were confirmed.
Table 18 | Reliability Values of Model’s Constructs
Construct Cronbach’s Alpha Mean Variance Standard
Deviation Number of
Items
KN 0.902 20.31 19.959 4.467 6
ATT 0.702 7.45 2.092 1.447 2
TR 0.823 13.29 7.771 2.788 4
PB 0.870 23.99 22.76 4.771 7
PR 0.877 23.11 19.574 4.424 7
WTP 0.933 19.61 24.898 4.99 6
4.7. Model Testing
After testing all the aspects related to the validity, reliability, and fitness of the model was
analyzed further to investigate how knowledge affects trust, perceived benefits, perceived risks;
also how the attitude towards technology affects knowledge and trust; as well as how the
willingness to purchase is affected by trust, perceived benefits, perceived risks. By measuring all
the P-value for all the paths measured, it was found that all the paths have a high level of
significance in the survey before the intervention, except two paths representing the effect of
knowledge on trust which had a p-value of 0.232, and the effect of attitude towards technology on
knowledge, which had a p-value of 0.383, except that, all the paths had a p-value less than 0.05
which deemed as acceptable and significant. Regarding the survey after the intervention, all the
paths have deemed sufficient, since that all the p-values have resulted less than 0.05, which shows
a high level of significance, and also demonstrates that all the paths in the final model are
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confirmed, as shown in the two tables below representing the model analysis in both surveys before
and after the intervention.
Another way also to assess the significance is the critical ratio (C.R.). The critical ratio is
resulted by dividing an estimate on the standard error (S.E.). This type of test is often also named
by the Wald test in several statistical packages. In order to get an indication of two sides'
significance with 0.05 level, C.R. should be more than 1.96 or less than -1.96. As shown in the
tables below, all the paths have shown C.R. level of more than 1.96 or less than -1.96 in the case
of perceived risk on willingness to purchase; however two paths couldn't be confirmed under the
above-mentioned conditions namely knowledge on trust which scored 1.19, and attitude towards
technology on knowledge, which scored 0.872. The two unconfirmed paths in the C.R. test, are
the same two paths mentioned above in the p-value test part, which reflects the accuracy of the
results. Regarding the survey after the intervention, all the paths are deemed significant since they
fall outside the range of -1.96 to 1.96. Therefore, all the paths are deemed valid.
Table 19 | Model’s estimated regression weights (before intervention)
Estimate S.E. C.R. P-value Result
KN ➔ TR 0.114 0.063 1.196 0.232 ** Not Supported
KN ➔ PB 0.563 0.086 4.829 0.000 * Supported
KN ➔ PR 0.301 0.073 3.288 0.001 Supported
ATT ➔ KN 0.084 0.115 0.872 0.383 ** Not Supported
ATT ➔ TR 0.438 0.096 3.601 0.000 * Supported
TR ➔ WTP 0.479 0.145 4.555 0.000 * Supported
PB ➔ WTP 0.399 0.114 4.287 0.000 * Supported
PR ➔ WTP -0.319 0.095 -3.818 0.000 * Supported
* indicates p-value less than 0.001 (high level of significance) ** indicates p-value higher than 0.05 (not significant)
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Table 20 | Model’s estimated regression weights (after intervention)
Estimate S.E. C.R. P-value Result
KN ➔ TR 0.388 0.119 2.907 0.004 Supported
KN ➔ PB 0.773 0.101 7.632 0.000 * Supported
KN ➔ PR 0.369 0.076 4.06 0.000 * Supported
ATT ➔ KN 0.701 0.128 6.144 0.000 * Supported
ATT ➔ TR 0.331 0.143 2.319 0.02 Supported
TR ➔ WTP 0.527 0.108 6.141 0.000 * Supported
PB ➔ WTP 0.437 0.095 5.134 0.000 * Supported
PR ➔ WTP -0.194 0.085 -3.042 0.002 Supported
* indicates p-value less than 0.001 (high level of significance)
4.8. Initial analysis for model’s constructs
To further analyze the full model created after the intervention, the factor analysis data
were reviewed for each construct. Overall, the constructs vary in terms of the number of variables.
However, all of the constructs contain two variables or more as the minimum value. All the
standardized loadings for all the variables in all constructs have exceeded the minimum value of
0.40 stated by Lewis and Byrd in the year 2003. The minimum value of the loadings can be found
in the trust construct with a value of 0.51 for the fourth variable. However, this value is deemed
acceptable, as explained earlier.
The first construct in this analysis is the “knowledge” construct which has the abbreviation
of “KN”. This construct contains six variables and aims to measure different points related to
knowledge about biotechnology and genetically edited food in specific. All the standardized
loading variables are considered to be high, since that all the values exceed 0.70 except variable
KN1 with a value of 0.68 which aims to verify the knowledge of genetically modified food, and
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the variable KN6 with a value of 0.62, which aims to verify the knowledge about the potential
positive effect of gene editing on human health. Both values are considered to be accepted, and
above all, the acceptable values stated by other researches such as 0.40 and 0.50. The highest
variable in terms of estimates in this construct was KN4, with a value of 0.815, which aims to
verify the knowledge about the potential effect of genome editing on agriculture, as shown in the
table below.
Table 21 | estimated regression weights for the “knowledge” construct (after intervention)
Estimate P-Value Measure
Knowledge
KN
KN1 ➔ KN 0.683 0.000* Genetically modified food
KN2 ➔ KN 0.764 0.000* Genetically edited food
KN3 ➔ KN 0.762 0.000* Difference between genetically modified and genetically edited food
KN4 ➔ KN 0.815 0.000* Potential of genome editing in agriculture
KN5 ➔ KN 0.768 0.000* Potential of genome editing in animal health
KN6 ➔ KN 0.620 0.000* Potential of genome editing in human health
* indicates p-value less than 0.001 (high level of significance)
The second construct subject to this study is the “attitude towards technology” with an
abbreviation of “ATT”. Due to running several attempts of model analysis in order to synchronize
both models before and after the intervention, to have acceptable loading values, several variables
were eliminated from this construct, and only two variables remained, which have significant
values in both models. Although the construct has two items, however, both of the items have
scored a high level of estimate above 0.70. The ATT2 item, which aims to investigate the potential
positive effect of technology on society, has an estimate of 0.755 and ATT6 with a value of 0.716,
which aims to identify a potential positive effect of technology on Japan’s economy. Although that
the case of having two items per construct is considered to be borderline, however, it is allowed
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and proven for its efficiency, according to Yong and Pearce, in 2013, who issued a guide focusing
on factor analysis. The guide mentioned stated that a construct with two variables is considered
reliable in case if the two items are highly correlated and have standardized estimates of 0.70 or
higher, which is the case in this construct where both of the items scored 0.755 and 0.716
respectively as shown in the table below.
Table 22 | estimated regression weights “attitude towards technology” (after intervention)
Estimate P-Value Measure
Attitude Towards
Technology
ATT
ATT2 ➔ ATT 0.755 0.000* Positive effect of technologies on society development
ATT6 ➔ ATT 0.716 0.000* Positive effect of technologies on Japan’s economy
* indicates p-value less than 0.001 (high level of significance)
The third construct subject to this study is the “trust” construct with the abbreviation of
“TR”. This construct aims to measure to what extent the respondents believe and trust several
variables related to biotechnology in general and genetically edited food in specific. Although this
construct contains originally seven variables, however, three variables were eliminated based on
the results of the factor analysis, especially when synchronizing the data before and after the
intervention. All the remaining variables have a high level of correlation since that all the variables
exceed the value of 0.70, however only one variable namely TR4 that aims to evaluate the level of
trust in the governmental food safety regulations has scored an estimate of 0.518 which is deemed
acceptable as mentioned in the other constructs above. The highest variable in this construct was
TR5 that has an estimate of 0843, which aims to validate the trust in biotechnology in general and
its benefits on the society, as shown in the table below.
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Table 23 | estimated regression weights for the “trust” construct (after intervention)
Estimate P-Value Measure
Trust
TR
TR1 ➔ TR 0.741 0.000* Trust in academic researchers
TR2 ➔ TR 0.749 0.000* Trust in genome editing scientists
TR4 ➔ TR 0.518 0.000* Trust in Japan’s food safety regulations
TR5 ➔ TR 0.843 0.000* Positive effect of biotechnology in society
* indicates p-value less than 0.001 (high level of significance)
The fourth construct subject to this study is “perceived benefits,” which has the
abbreviation of “PB”. This construct has a complete set of seven variables without any elimination.
This construct aims to identify what type of benefits the consumer perceive regarding the adoption
of genetically edited food products. Four variables had high estimates of values higher than 0.7,
namely PB2, PB3, PB5, and PB6. Where two variables have scored estimates ranging from 0.60
to 0.69, namely PB1, and PB7. The variable named PB4 has scored the lowest estimate value of
0.583, which aims to identify the financial benefits of utilizing gene-editing technology in food.
However, it was deemed acceptable since that it surpassed the minimum value of 0.40.
Table 24 | estimated regression weights for the “perceived benefits” construct (after intervention)
Estimate P-Value Measure
Perceived Benefits
PB
PB1 ➔ PB 0.681 0.000* Positive effect of genetically edited food on human health
PB2 ➔ PB 0.754 0.000* Positive effect of genetically edited food on animal health and comfort
PB3 ➔ PB 0.705 0.000* Eliminate hunger in developing countries
PB4 ➔ PB 0.583 0.000* Lower food pricing and financial suitability
PB5 ➔ PB 0.700 0.000* Promote Japan’s agricultural production
PB6 ➔ PB 0.784 0.000* Enhance Japan’s economy and society
PB7 ➔ PB 0.624 0.000* Benefits are higher than the risks
* indicates p-value less than 0.001 (high level of significance)
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The fifth construct in the study is “perceived risks”, which is abbreviated by “PR”. Like
the perceived benefits construct, this construct was a complete one, with all the seven variables
stated. This construct aims to identify the several risks that the consumer perceives when adopting
genetically edited food products. All the variables had a relatively high level of estimates, where
three variables scored estimates with values higher than 0.60, namely PR1, PR6, PR7. Three other
variables have scored high estimated with values higher than 0.70, namely PR2, PR4, and PR5,
where the variable PR3 came with the highest estimate of 0.838 in this construct, as shown in the
table below.
Table 25 | estimated regression weights for the “perceived risks” construct (after intervention)
Estimate P-Value Measure
Perceived Risks
PR
PR1 ➔ PR 0.668 0.000* Risk of consumer genome affection
PR2 ➔ PR 0.754 0.000* Negative effect on human health
PR3 ➔ PR 0.838 0.000* Negative effect on environment
PR4 ➔ PR 0.783 0.000* Negative effect on animal health
PR5 ➔ PR 0.792 0.000* Potential negative effect on descendant’s health
PR6 ➔ PR 0.611 0.000* Risk of creating new allergies
PR7 ➔ PR 0.661 0.000* Risk uncertainty
* indicates p-value less than 0.001 (high level of significance)
The last and the most critical construct subject to this study is the “willingness to purchase”
construct, which is abbreviated by WTP. This construct measures the willingness to purchase
genetically edited food in general as well as the willingness to purchase with different conditions
such as better health, environment, price value, and other factors. This construct is where the model
ends since it is connected with trust, perceived benefits, and perceived risks. The construct
originally contains seven variables. However, one variable, namely WTP 7, was eliminated during
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the factor analysis to maintain a higher level of model fit and data adequacy. This construct by far
is the highest construct in terms of the estimated values for variables since that all variables have
scored above 0.8, except for one variable, namely WTP 6, that scored 0.742, which is considered
a high value as well.
Table 26 | estimated regression weights for the “willingness to purchase” construct (after intervention)
Estimate P-Value Measure
Willingness to Purchase
WTP
WTP1 ➔ WTP 0.867 0.000* Willingness to purchase in general
WTP2 ➔ WTP 0.823 0.000* Willingness to purchase conditioned with low fat ingredients
WTP3 ➔ WTP 0.828 0.000* Willingness to purchase conditioned with lower pricing values
WTP4 ➔ WTP 0.846 0.000* Willingness to purchase conditioned with environmentally sustainable agriculture
WTP5 ➔ WTP 0.861 0.000* Willingness to purchase conditioned with better nutrients levels
WTP6 ➔ WTP 0.742 0.000* Willingness to purchase conditioned with better health claims
* indicates p-value less than 0.001 (high level of significance)
As a summary of all the tested constructs, all the variables have scored a p-value of less
than 0.001, which indicates a very high level of significance. Six different constructs were
analyzed, with an original number of variables of 42 variables. However, ten variables were
eliminated, and 32 variables remained subject to this analysis. All the 32 variables have exceeded
the minimum value of 0.4, where the majority of the variables had a high level of estimates. Of
the total number of 32 variables, none of the variables have scored an estimate below 0.5, and only
two variables have scored estimates of 0.50 to 0.59. Seven variables had an estimated value of
0.60 to 0.69. The majority of the variables, specifically 15 variables, have obtained the estimated
values from 0.70 to 0.79, followed by eight variables that obtained the estimated value between
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0.80 to 0.89. Based on that analysis and as pointed earlier than more than 70% of the variables
have obtained estimate values of 0.70 or higher, which indicates the high level of correlation
between the variables in each construct.
4.9. Model’s Path Coefficient
As discussed earlier in the above subsection, the model has achieved all the significance
requirements represented in having all paths with a p-value less than 0.05, as well as having a C.R.
value outside the range of -1.96 to 1.96. Therefore, the model has deemed significant, especially
using the dataset after the intervention. Regarding the path coefficient, it was found that all paths
hold positive values which indicates a positive impact in all paths, except the path between
perceived risks and willingness to purchase, which had a negative value indicating on the negative
impact of perceived risk on the willingness to purchase genetically edited food products in general.
The model below shows the relations between different factors and how it affects the
willingness to purchase genetically edited food products. The estimates in the model below are
based on the dataset gathered before the intervention. Therefore, it shows a lack of knowledge of
the respondents regarding the topic. The model shows a non-significant effect from attitude to
technology on the knowledge construct with a value of 0.08 and a p-value of 0.383. Another
insignificant effect shown in this model is the effect of the knowledge on the trust construct with
a value of 0.11 and a p-value of 0.232. The all the remaining paths have a significant p-value of
0.001 or below. The attitude towards technology has an effect on trust with a value of 0.43. The
knowledge affects perceived benefits by 0.56, and affect perceived risks by 0.30. The willingness
to purchase is affected by the trust by the level of 0.47, and affected by perceived benefits by the
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level of 0.39, and affected by the perceived risks by the level of -0.31, as shown in the model
below.
Figure 16 | Model’s standardized estimates based on the data before the intervention
The figure below shows the standardized estimates of the model based on the data collected
after the intervention. The model below shows the relations between different factors and how it
affects the willingness to purchase genetically edited food products, and it was exactly a duplicate
of the same model used before the intervention, as well as the same survey questions. The estimates
in the model below are based on the dataset gathered after the intervention. Therefore, it shows a
higher level of knowledge about genetically edited food products in comparison with the survey
before the intervention. The model is considered a complete one since that all the paths in the
model are significant, with a p-value lower than 0.05. The model shows an effect of attitude
towards technology on knowledge by 0.70, and on trust by the level of 0.33. The model also shows
an effect of knowledge on trust by the level of 0.38, and on the perceived benefits by the level of
Knowledge KN
Perceived Benefits PB Trust TR Perceived
Risks PR
Willingness to Purchase WTP
Attitude Towards Technology ATT 0.08
0.11 0.43 0.56 0.30
0.47 0.39 - 0.31
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0.77, as well as on the perceived risks by the level of 0.36. Also, the model shows that the
willingness to purchase is affected by the trust by the level of 0.52, and by perceived benefits by
0.43, and by the perceived risks by the level of -0.19. The results of this model show the significant
difference compared to the results from the first model especially on the effect of attitude towards
technology on knowledge, as well as the effect of knowledge on trust, which are two significant
paths in the model after the intervention compared to insignificant values in the model before the
intervention.
Figure 17 | Model’s standardized estimates based on the data after the intervention
4.10. Model’s Goodness of Fit
Accepting or rejecting a certain model is considered to be a critical decision, especially for
models that have implications on policy or education (Bentler, 1990). Several scholars have
Knowledge KN
Perceived Benefits PB Trust TR Perceived
Risks PR
Willingness to Purchase WTP
Attitude Towards Technology ATT 0.70
0.38 0.33 0.77 0.36
0.52 0.43 - 0.19
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designed sets of indexes to validate the goodness of fit for the conceptual models and to verify
whether the model fits the data (Browne & Cudeck, 1992). Fit indices are mainly categorized into
two categories, namely, absolute and incremental fit. The study shall focus mainly on the absolute
fit indices due to being the most fundamental indications for the level of fitness of the data to the
theory (Hooper et al., 2007).
Table 27 | Acceptable fit rules for selected factors
Symbol Fit Index Acceptable Fit Source
χ 2 / df Relative Chi Square
< 2.00
< 2.00
< 2.00
Ullman, 2001
Schermelleh et al., 2003
Schreiber et al., 2006
SRMR Standardized Root Mean Square Residual
< 0.070
< 0.090
<0.080
Bagozzi and Yi, 2012
Hair et al., 2010
Schreiberet et al., 2006
RMSEA Root Mean Square Error of Approximation
≤ 0.070
< 0.080
≤ 0.060
Bagozzi and Yi, 2012
Hair et al., 2010
Hu and Bentler, 1999
CFI Comparative Fit Index > 0.920 Hair et al., 2010
One of the main absolute fit indices is the relative chi-square, which is also known as
normed chi-square. In order to reach the value of the relative chi-square, the calculated chi-square
index of the model is divided by the degree of freedom. This index is commonly used in structural
equation modeling studies since it has low sensitivity towards sample sizes. Several studies have
shown estimated values for the acceptance of the relative chi-square index of any value above 0
and less than 2, as shown in the table above.
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Another well-known fit index is the standardized root mean square residual or as known as
SRMR. Like the relative chi-square, SRMR is an absolute fit index as well. It shows the value of
the standardized difference when comparing the observed correlation with the predicted
correlation. The values for this index are ranging from 0 to 1, where the values closer to 0 are
considered to be more acceptable as a degree of model fit. Values below 0.9 are acceptable,
according to the study by Hair et al. in the year 2010. Also, another study by Schreiberet et al. in
the year 2006 has indicated that values below 0.08 are acceptable, as well as a study by Bagozzi
and Yi in the year 2012 who indicated that values below 0.07 are acceptable.
Another index for measuring the model fit is the root mean square error of approximation
or as known as RMSEA which currently very popular among all the papers published using the
methodology of structural equation modeling. Like the normed chi-square and SRMR, RMSEA is
an absolute measure as well, which avoids the bias of sample size. The values of RMSEA ranges
from 0 to 1, where values closer to 0 indicate better fitness level of the model. A study by Bagozzi
and Yi in the year 2012 has indicated that the acceptable value for RMSEA is equal or below
0.070, where Hair et al., in the year 2010, has indicated that the acceptable value is below 0.080.
One of the most renowned studies in this field is a study published by Hu and Bentler in the year
1999, where it indicated that fit value is equal or below 0.060, as shown in the table above.
The comparative fit index or as known as CFI, is an incremental measure for fit. It analyzes
the differences between the input data and the model subject to the hypotheses. The CFI values
are ranged from 0 to 1, where values closer to 1 indicate a better level of fitness. A study by Hair
et al. in the year 2010 has indicated that values above the 0.920 are considered to be acceptable,
as shown in the table above.
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Table 28 | Model fit index
Measure Value Acceptable Fit Source Status
χ 2 / df 1.639
< 2.00
< 2.00
< 2.00
Ullman, 2001
Schermelleh et al., 2003
Schreiber et al., 2006
Accepted
Accepted
Accepted
SRMR 0.065
< 0.070
< 0.090
<0.080
Bagozzi and Yi, 2012
Hair et al., 2010
Schreiberet et al., 2006
Accepted
Accepted
Accepted
RMSEA 0.060
≤ 0.070
< 0.080
≤ 0.060
Bagozzi and Yi, 2012
Hair et al., 2010
Hu and Bentler, 1999
Accepted
Accepted
Accepted
CFI 0.926 > 0.920 Hair et al., 2010 Accepted
By testing the model fitness value across all the measures listed above, the model has
passed all the acceptable values where it has scored 1.639 in χ 2 / df index, while the acceptable
value is below 2.0, according to Ullman, Schermelleh, and Schreiber. Regarding standardized root
mean square residual SRMR value, the model has scored 0.065, while the acceptable value below
0.070, according to Bagozzi and Yi, and below 0.080, according to Schreiberet, as well as below
0.090 according to Hair. Regarding root mean square error of approximation RMSEA, the model
has scored a value of 0.060 which is considered acceptable according to Bagozzi and Yi who stated
that the acceptable value is equal or less than 0.070, as well as to Hair who stated that the acceptable
value is below 0.080, and Hu and Bentler who stated that the acceptable value is equal to or below
0.060. Regarding the comparative fit index CFI, the model has scored 0.926, which is considered
an acceptable value according to Hair et al. in the year 2010, who stated that the acceptable value
should be higher than 0.920, as shown in the table above.
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4.11. Willingness to Adopt
In order to further verify the real effect of the knowledge and science communication on
the increase the level of the adoption of the genetically edited food product, the respondents were
asked a direct binary yes or no question asking them if they are willing to adopt the genetically
edited food products in the future. The respondents have answered the same question before the
intervention and after the intervention. By analyzing the results, it was found that in the first
survey, only 43 respondents have replied with yes, representing 24% of the total survey population,
where 137 respondents representing 76% of the survey respondents have replied with no, which
represents refusal for adoption genetically edited food product. After conducting the intervention,
which aims to increase the awareness of the respondents by the nature of genetically edited food
and the aspects differentiating it from the genetically modified food, significant differences were
found. In the second survey, the number of respondents who showed their willingness to adopt
genetically edited food and answered with yes in the survey has increased from 43 people in the
first survey to 73 people in the second survey, representing a massive increase of nearly 70% of
the acceptance level since that it has increased from 24% in the first survey to 41% in the second
survey after the intervention. Subsequently, the number of respondents who replied by no has
decreased from 137 in the first survey to 107 in the second survey, as shown in the table and figure
below.
Table 29 | Willingness to purchase binary question responses table
Yes No
Number % Number %
Before Intervention 43 24% 137 76%
After Intervention 73 41% 107 59%
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Figure 18 | Willingness to purchase binary question chart
In order to further validate the statistical significance of the differences in the values above,
SPSS was used to conduct the chi-square test. Based on the calculations, it was found that the two-
sided asymptotic significance was less than 0.001, which is an indication that the values are
significant, as shown in the table below.
Table 30 | Willingness to purchase binary question (chi-square test)
Value df Significance
Pearson Chi-Square 70.358 * 1 0.000
Number of Valid Cases 180
* The minimum expected count is 17.44.
24%
76%
Before Intervention Yes No
41%
59%
After Intervention Yes No70% increase
in acceptance rate
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Based on the values mentioned in the tables above, which has indicated a significant
difference between the acceptance rate of the genetically modified food before and after the
intervention, it can be concluded that there is a positive effect for increasing the knowledge by the
science communication on the level of acceptance of genetically edited food, and it highlights the
importance of increasing the awareness in this matter.
4.12. Effect of knowledge and science communication
In order to further identify the detailed effect of the intervention represented in the short
presentation conducted between the first and second surveys, the study has compared the mean
and level of significance between the respondents’ responses before and after the presentation.
The figures below show the box and whisker plot for each of the constructs. The values on
the left of the chart represent the responses before the intervention, while the values on the right
represent the responses after the intervention. The box and whisker plot or as known as box plot,
is considered to be a very convenient way to compare between two groups and provide a visual
representation for the data distribution.
The figure below shows the box plot for the knowledge construct where the full seven
items were assessed. Visually and before studying the data further, it is clear that the mean line of
the survey data after the intervention is higher than the mean line of the data before the
intervention, which shows the positive effect that the intervention created in terms of raising the
knowledge and awareness of biotechnology and genetically edited food in specific.
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Figure 19 | Respondents mean-line before and after intervention (Knowledge)
Discovering further the items that were affected by the intervention in the knowledge
construct, it was found that the intervention has created a significant positive effect on all the items
in the construct. Overall, the mean of the knowledge data has increased by 39% from 2.42 before
the intervention to reach 3.37 after the intervention. The most changed variable was KN3, which
its mean value has increased by 65% from 1.99 to 3.29 after the intervention. This item in specific
was the core item in the presentation, since that it investigates if the respondents understand the
difference between genetically edited food and genetically modified food or not. The answers
mentioned above show that the intervention was successful in increasing the awareness about this
part in particular. The lowest item changed based on the intervention was KN7, since that it has
changed by 8% only from 3.05 to 3.29, which investigates if the respondents became more
interested in learning more about genetically edited food. Although the change in this item was
low in terms of value, it had a significant level as well, as shown in the table below.
KN1 KN2 KN3 KN4 KN5 KN6 KN70
1
2
3
4
5
6
Before After
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Table 31 | Comparison for the intervention significance for the knowledge construct
Item Mean (Before)
Mean (After)
StdDev (Before)
StdDev (After) Change Change% P-value Significance
KN1 3.03 3.52 0.94 0.91 0.48 16% 0.000 significant
KN2 2.28 3.40 1.02 0.93 1.12 49% 0.000 significant
KN3 1.99 3.29 0.98 0.94 1.29 65% 0.000 significant
KN4 2.17 3.36 1.03 0.92 1.19 55% 0.000 significant
KN5 2.17 3.43 1.05 0.87 1.26 58% 0.000 significant
KN6 2.26 3.32 1.08 0.89 1.07 47% 0.000 significant
KN7 3.05 3.29 1.02 0.97 0.24 8% 0.001 significant
Mean 2.42 3.37 1.09 0.92 0.95 39%
Moving to the second construct, which is the attitude towards technology, aims to measure
the level of interest that the respondents have towards technology in general. From the visual
representation in the box plot below, it was observed that the values of the responses after the
intervention are slightly higher than the values before the intervention. However, both values are
correlated to some extend judging by the synchronization of the mean line movement between the
two segments before and after the intervention, as shown in the figure below.
Figure 20 | Respondents mean-line before and after intervention (Attitude towards technology)
ATT1 ATT2 ATT3 ATT4 ATT5 ATT6 ATT70
1
2
3
4
5
6
Before After
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As mentioned in the description of the box plot above, in general, there is a limited positive
change in this construct when comparing the mean of all the responses for all the questions before
and after the intervention, where the mean has increased by averagely 7% from 3.22 to 3.44. The
highest item positively increased was ATT5, which measures the level of interest among the
respondents to purchase technology in the early release stage, which has increased by 13% after
the intervention. However, the intervention had a non-significant low effect on the variable ATT6,
where it has increased by only 2% from 3.63 to 3.68, with a p-value of 0.467.
Table 32 | Comparison for the intervention significance for the attitude towards technology construct
Item Mean (Before)
Mean (After)
StdDev (Before)
StdDev (After) Change Change% P-value Significance
ATT1 3.00 3.26 1.03 0.97 0.26 9% 0.001 significant
ATT2 3.72 3.77 0.96 0.83 0.05 1% 0.000 significant
ATT3 2.92 3.24 0.89 0.83 0.33 11% 0.000 significant
ATT4 3.29 3.49 1.01 0.85 0.20 6% 0.010 significant
ATT5 2.80 3.17 0.92 0.96 0.37 13% 0.000 significant
ATT6 3.63 3.68 0.87 0.82 0.06 2% 0.467 non-significant
ATT7 3.16 3.46 0.90 0.89 0.29 9% 0.000 significant
Mean 3.22 3.44 0.99 0.90 0.22 7%
The third construct subject to this study is the trust construct, which aims to identify the
level of trust in several stakeholders related to genetically edited food such as scientists,
universities, research labs, government regulations, and other factors. Also like the previous
construct, the mean-line representing the data obtained after the intervention is higher than the line
created by the data before the intervention in all the points. However, the change is quite limited,
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and visually there is a correlation between the responses before and after the intervention, as shown
in the figure below.
Figure 21 | Respondents mean-line before and after intervention (Trust)
Overall, the intervention had a positive impact on increasing the trust level for different
stakeholders related to genetically edited food. The results have seen a statistically significant
increase from 3.00 to 3.22, which represents 7%. All the variables have been increased positively
and significantly except the TR7 which aims to test the trust of the respondents in the media
channels such as TV, radio or newspaper, which the increase has failed to achieve the minimum
significance level of 0.05, and resulted in a p-value of 0.178. The highest factor affected by the
intervention was TR3, which tests the trust in the biotech company and has achieved a significant
increase of 11% after the intervention in comparison with the data obtained before the intervention,
as shown in the table below.
TR1 TR2 TR3 TR4 TR5 TR6 TR70
1
2
3
4
5
6
Before After
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Table 33 | Comparison for the intervention significance for the trust construct
Item Mean (Before)
Mean (After)
StdDev (Before)
StdDev (After) Change Change% P-value Significance
TR1 3.04 3.27 0.80 0.80 0.23 7% 0.001 significant
TR2 3.00 3.26 0.81 0.84 0.26 9% 0.000 significant
TR3 2.87 3.19 0.78 0.84 0.33 11% 0.000 significant
TR4 3.04 3.26 0.89 0.97 0.22 7% 0.002 significant
TR5 3.29 3.49 0.79 0.83 0.21 6% 0.003 significant
TR6 3.04 3.22 0.78 0.82 0.18 6% 0.018 significant
TR7 2.75 2.85 0.79 0.91 0.10 4% 0.178 non-significant
Mean 3.00 3.22 0.82 0.88 0.22 7%
The fourth construct in this study was the perceived benefits construct, which aims to
explore the type of benefits that the consumers perceive from adopting genetically edited food. By
visually observing the box plot below, it was found that the mean-line representing the data
gathered after the intervention is higher than the mean line created by the data obtained before the
intervention, which shows a general increase across all the variables in the perceived benefits
construct after the intervention.
Figure 22 | Respondents mean-line before and after intervention (Perceived benefits)
PB1 PB2 PB3 PB4 PB5 PB6 PB70
1
2
3
4
5
6
Before After
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By reviewing the detailed mean analysis for each variable in the perceived benefits
construct, it was found that all the variables have increased positively and in a statistically
significant way. The overall mean has increased by 15% from 2.98 to 3.43, and all the variables
have registered an increase with a significant level of p-value below 0.001, which shows a high
level of statistical significance. In general, the respondents have perceived higher values in every
aspect after the intervention, which shows the importance of science communication in increasing
the perception of the benefits among consumers. The highest variable affected by the intervention
was PB2, which has achieved an increase of 21% after the intervention since that it has scored a
mean value of 2.76 in the first survey and 3.35 in the second survey. PB2 is the variable responsible
for testing the perceived benefits of animal health in case of utilizing genome editing technology.
Where the lowest variable changed were PB3 and PB7, which changed positively and equally by
nearly 10% after the intervention.
Table 34 | Comparison for the intervention significance for the perceived benefits construct
Item Mean (Before)
Mean (After)
StdDev (Before)
StdDev (After) Change Change% P-value Significance
PB1 2.79 3.32 0.98 1.00 0.53 19% 0.000 significant
PB2 2.76 3.35 0.99 0.94 0.59 21% 0.000 significant
PB3 3.27 3.59 0.99 0.91 0.32 10% 0.000 significant
PB4 2.78 3.28 0.81 0.90 0.50 18% 0.000 significant
PB5 3.02 3.46 0.91 0.89 0.44 15% 0.000 significant
PB6 3.07 3.51 0.84 0.83 0.44 14% 0.000 significant
PB7 3.18 3.49 0.95 0.89 0.31 10% 0.000 significant
Mean 2.98 3.43 0.95 0.91 0.45 15%
The fifth construct subject to this study is perceived risks, which aims to explore different
risks and hazards that the consumer perceives if adopted genetically edited food products. Based
on the visual representation in the box chart below, it was found that the mean line before and after
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the intervention are nearly identical and highly correlated, although that the mean-line after the
intervention is slightly higher than the line before the intervention.
Figure 23 | Respondents mean-line before and after intervention (Perceived risks)
By analyzing the perceived risks further, it was found that the mean after the intervention
has increased with a very limited level of only 4% since that it has increased from 3.18 to 3.30,
which indicates that the intervention did not have any significant effect on increasing or reducing
the risk perception among consumers towards genetically edited food products and its
stakeholders. Five out of the seven items had a very high p-value, which indicates non-significant
changes between the answers before and after the intervention. Only PR2 and PR6 variables have
scored a p-value below 0.05, which indicates a high level of significance. PR2 and PR6 are
variables related to human health risks and allergies creation, although that changes in those
variables were significant, it have very low values of 3% for the PR2 variable, and 6% of the PR6
variable.
PR1 PR2 PR3 PR4 PR5 PR6 PR70
1
2
3
4
5
6
Before After
95
Table 35 | Comparison for the intervention significance for the perceived risks construct
Item Mean (Before)
Mean (After)
StdDev (Before)
StdDev (After) Change Change% P-value Significance
PR1 3.11 3.27 0.99 0.84 0.16 5% 0.074 non-significant
PR2 3.12 3.21 0.91 0.78 0.09 3% 0.000 significant
PR3 3.16 3.21 0.92 0.84 0.06 2% 0.520 non-significant
PR4 3.33 3.38 0.98 0.79 0.05 1% 0.552 non-significant
PR5 3.15 3.27 0.97 0.80 0.12 4% 0.156 non-significant
PR6 3.06 3.24 0.93 0.88 0.19 6% 0.029 significant
PR7 3.37 3.52 0.99 0.90 0.16 5% 0.078 non-significant
Mean 3.18 3.30 0.96 0.84 0.12 4%
The last construct subject to this study is the willingness to purchase genetically edited
food products, which aims to investigate the extend where the consumer is willing to adopt
genetically edited food under certain conditions. From the visual representation of the box plot
below, it was found that the mean-line obtained from the data after the intervention, is higher than
the mean line obtained from the data before the intervention in all the aspects. It is also visually
observed that the two lines are highly correlated. It can be concluded that the intervention has
increased the willingness to purchase genetically edited food products. From the box plot below
also, it shows that the WTP1, which aims to identify the willingness to purchase genetically edited
food products in general, is experiencing substantial difference when the results before and after
the intervention were compared.
96
Figure 24 | Respondents mean-line before and after intervention (Willingness to purchase)
By analyzing the changes further that happened in the mean values before and after the
intervention, it was found that in general, the mean value for the willingness to purchase has
increased from 2.94 to 3.19 representing an 8% significant increase. By analyzing further the
different variables, it was found that all the variables had a statistically significant increase except
for one factor only, namely WTP4, which aims to analyze the level acceptance for genetically
edited food if it is grown in an environmentally friendly way. The highest variable that changed
after the intervention was WTP1, which changed from 2.76 to 3.13, with a significant change
percentage of 14%, which aims to examine the willingness to purchase genetically edited food in
general. Also, specifics related to the level of significance and means comparisons are stated in the
table below to explore the most factors that were affected by the intervention.
WTP1 WTP2 WTP3 WTP4 WTP5 WTP6 WTP70
1
2
3
4
5
6
Before After
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Table 36 | Comparison for the intervention significance for the willingness to purchase construct
Item Mean (Before)
Mean (After)
StdDev (Before)
StdDev (After) Change Change% P-value Significance
WTP1 2.76 3.13 0.89 0.99 0.38 14% 0.000 significant
WTP2 2.91 3.17 1.00 0.99 0.26 9% 0.000 significant
WTP3 2.99 3.32 0.98 0.98 0.32 11% 0.000 significant
WTP4 3.13 3.21 0.93 0.98 0.08 2% 0.278 non-significant
WTP5 3.11 3.36 1.01 0.91 0.25 8% 0.002 significant
WTP6 3.26 3.43 0.91 0.90 0.17 5% 0.041 significant
WTP7 2.44 2.69 0.93 0.99 0.25 10% 0.002 significant
Mean 2.94 3.19 0.98 0.99 0.24 8%
Based on the above-mentioned tables and descriptions, it was found that the intervention
had a positive effect on all the factors subject to the study. The most affected factor was the
knowledge, where the mean for all the responses was increased by 39% after the intervention,
followed by the increase of the perceived benefits, which was increased by 15% after the
intervention, followed by the willingness to purchase which was increased by 8% after the
intervention. The results found from this part puts further emphasis on the importance of science
communication in increasing the awareness and adoption rate.
4.13. Intervention Analysis
Based on the several studies and statistical analysis conducted in this section of the study,
it is concluded that the science communication represented in the intervention performed in this
study, has a positive effect in increasing the knowledge about genetically edited food products.
Overall, the intervention has created a significant difference and an increase in the willingness to
purchase a genetically edited food product among the survey respondents.
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5. Conclusion
5.1. Research Summary and Conclusion
This research puts a special emphasis on the role of regulations and innovation policies in
solving one of the most critical challenges that face the world. Hunger and undernourishment are
global challenges, where according to 2018 statistics, 26% of the world population have suffered
from different levels of food insecurity. In Japan, there the level of food insecurity is very low in
comparison with several other Asian countries, but Japan is facing another challenge related to
food insufficiency, especially that the number of farming households has decreased by nearly 90%
in the last 50 years. With Japan's aging challenges and the need for better health solutions, Japan
has created several policies and regulations to help in solving those challenges. Although the
functional food industry has started in Japan, however, the market in Japan is growing steadily by
nearly 2% a year, and the American market is growing by 10% a year. The research has examined
several factors that can allow Japan to explore foreign markets in food-related technologies. Based
on the global challenges and the local challenges in Japan, the research focused has been emerged
to explore further the Japanese health-food regulations in comparison with global regulations.
After studying the different regulations in Japan, it was found that there are three types of national
regulation, namely; FOSHU, FNFC, and FFC, as well as local government system regulation.
Based on the study result, the research has concluded that the FFC will continue to grow to become
the main regulation type used in Japan, since that it offers a more suitable process for SMEs to
grow in this field in comparison with FOSHU. The research also has studied different regulations
around the world in this field, especially in the United States, European Union, China, Singapore,
Korea, Taiwan. After studying the regulations in different countries, it was found that the
regulations in Japan especially FFC regulations are very accommodating for the innovation in this
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field, as a result of that, more than 2,000 FFC products have been authorized in Japan in just five
years, more than 1,500 of them are in the markets already, in comparison to the FOSHU regulations
which had an accumulative number of nearly 1,100 products in the span of over 25 years. In terms
of global regulations in this part, it was found that the regulations in the United States are
challenging for foreign companies since it requires various certifications and strict process.
However, the American market is considered an interesting market for supplying ingredients. The
study has also concluded that it can be feasible for Japanese companies to explore the foreign
markets that have a positive list such as China, which has a massive market size and acceptability
for the Japanese products. The results of this part of emphasize the role of innovation policy and
regulations in driving the innovation in food-related technologies such as FFC.
After concluding the functional food part, the study has explored furthermore innovative
field in terms of food technologies, which is the genetically edited food field. Utilizing genome
editing in food can solve several challenges related to agriculture, such as weather challenges, cost
reduction, food availability, insects, as well as to provide food with a higher level of nutrients.
Thus, it can help in solving the challenges faced by several developing countries, as well as the
challenges of the developed countries represented in the lack of agricultural workers. In this part,
the study has focused on the difference between the regulations in Japan, the United States, the
European Union in this regard. It was found that the regulations in Japan are the most scientific-
based, since that it provides the producers of the genetically edited food products the ability to
produce it without any further testing or inspection, unlike GMOs. The reason behind the Japanese
regulation that it might be difficult to detect the genetically edited food products since the edited
conducted may have been done by conventional breeding as well. This policy opens the door for
innovation in the field of genetically edited food and provides the biotech companies a golden
100
opportunity to grow in the Japanese market and globally as well. Also, the policy encourages
innovation and creates an opportunity for Japan to be the technology hub for genetically edited
food worldwide. The regulations of genetically edited food in the United States are still in the
development phase, and there might be a direction that USDA will take the same approach as
Japan for the crops. However, the FDA will strictly regulate animal genome editing. For the
European market, the court has issued a ruling that genetically edited food shall be considered as
a subcategory of the genetically modified food. Therefore, it must go through all the processes and
testing required for authorizing GMO products. After concluding that the regulations in Japan are
the most suitable for innovation in this field, and will open the door for more companies to
innovate, it was found that according to previous studies, the Japanese consumers may not accept
this type of regulations for the genetically edited food and demand further labeling and safety
testing. From this point, the third part of the research has emerged to test the acceptance rate of the
Japanese consumers for the genetically edited food products and the type of factors that affect the
willingness to purchase.
There is an evident lack of knowledge among the public for the genetically edited food and
the difference between it and the GMO. Therefore, a survey measuring the factors affecting the
acceptance of the youth in Japan for genetically edited food was conducted. The survey has been
conducted twice, where we have provided the survey the first time, following by short educational
presentation, then we provided the same survey again. The survey was conducted using the
structural equation modelling method where we have measured six factors, namely; Knowledge,
Attitude Towards Technology, Perceived Benefits, Perceived Risks, Trust, and the Willingness to
Purchase. Every factor was measured using seven different questions. Also, we have conducted
the second survey to measure the impact of the intervention, which is the science communication
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in enhancing the adoption rate for genetically edited food. The survey was conducted on the 24th
of December 2019, at Ritsumeikan University, Japan, among bachelor degree students studying
business and economics. The correct and complete respondents who answered both of the surveys
were 180 persons. The data were analyzed using a Windows-based IBM Statistics software and
IBM Amos. Also, reliability and validity were examined. The hypotheses that knowledge has a
direct impact on Perceived Benefits, Perceived Risks, and Trust and that the mentioned three
factors have a direct impact on Willingness to Purchase, also the Attitude Towards Technology
directly affects Trust and Knowledge was established. All the hypotheses were confirmed based
on the P-values for the paths for the model measured after the intervention based on the second
survey data. However, reviewing the first survey result, we have failed to verify the effect of
Knowledge on Trust, and The Attitude Towards Technology on Knowledge due to the lack of
significance in this test. The study has found a definite increase effect on the paths when comparing
the models before and after the intervention stating on the role of knowledge and science
communication in changing the perception and attitude towards genetically edited food, especially
in the path between Knowledge to Trust that was found significant only in the second survey. Also,
there was a final Yes or No question asking the respondents for their final willingness to purchase
for genetically edited food, and in the first survey only 23% have shown their willingness to
purchase, however in the second survey, the number had a major increase to reach 41%. This
question has shown us a sign of change in the consumer acceptance of genetically edited food after
having an introductory level knowledge about the technology and what it brings to the consumers,
which proves the high importance of the science communication in this field.
Also, at the end of this segment, the study has compared the respondent's responses for all
the variables before and after the intervention in order to identify further the validity of the effect
102
of science communication in raising the awareness and adoption rate of genetically edited food.
By conducting paired t-test for all the responses, we found that there is a significant increase in the
means of all the constructs after the intervention in comparison with the means before the
intervention. The most affected construct was the knowledge construct where it was increased by
39% after the intervention, followed by perceived benefits with an increase of 15%, followed by
the willingness to purchase with an increase of 8%. The results found from this part highlights
further the importance and efficiency of science communication in enhancing the consumer
awareness and acceptance rate.
As a conclusion, the regulations of food technologies in Japan are very accommodating
and encouraging for innovation in different fields, thanks for the innovation policies stated by the
Japanese government in the past five years. However, in order to create further success in food-
related technologies, science communication should be utilized. Concrete efforts in the area of
science communication are advised to be taken by the government, universities, and industry
together by providing clear and accessible trusted source of information for the general public.
5.2. Research Significance and Implications
This research focuses on three main parts, namely; functional food regulations, genetically
edited food regulations, and genetically edited food acceptance. The significance of this research
comes in several aspects. The first aspect that this research combines several fields in food-related
technologies, especially in Japan, comparing functional food, genetically modified food, and
genetically edited food, which makes it an integrated study for several types of food technologies.
This research also considered being one of the very few researches published by a Japanese
university in English language studying in detail the difference between several regulations related
to functional food in Japan. The research also has utilized updated sources in Japan and has
103
included updates in the legislation related to functional food in Japan according to the food
sanitation act's last amendment published in June 2018 as well as the latest standards from CAA.
Regarding the functional food regulations as well, the research has highlighted the local
regulations of the functional food that allows local municipalities in Japan to certify products
created in its prefecture, for example, the Healthy-Do system, which is the local system in
Hokkaido. Such local systems are usually not highlighted in similar research that focuses on the
national regulations only.
Regarding the genetically edited food regulations part, the research is considered
significant due to the fact that the term is quite updated, and there is a lack of research articles
reviewing the regulations for genetically edited food in comparison with the genetically modified
food regulations. Also, the regulations in this regard are still in the development stage, and there
is a lack of information sources discussing it. Therefore, this research highlights the differences
between the regulations of genetically edited food in Japan, the EU, and the USA. Although the
regulations in the USA still not finalized yet. However, the research has highlighted the potential
direction that the USDA and FDA might take in this regard in the near future.
One of the most unique points about this research that the research has highlighted the
factors that affect the acceptance of genetically edited food in Japan. Currently, most of the
published papers discussing consumer behavior and acceptance around the world are focusing
mainly on genetically modified food, since genetically edited food isn't fully commercialized yet.
The research has measured several factors affecting genetically edited food acceptance, such as
perceived benefits, perceived risks, and trust. With the lack of research work examining consumer
acceptance in this field, this research opens the door for more researchers to apply the same
methodology in examining several factors in other regions in Japan or worldwide.
104
The significance of the research also relays in the methodology of it, while most researches
focus on obtaining the data using one survey, this research has utilized the experimental approach
of conducting two surveys with an intervention between them to measure the difference between
the two data sets before and after the intervention. Via this intervention, the research has verified
the importance of knowledge and science communication in enhancing the awareness and
acceptance of genetically edited food products, which gave the study an empirical approach in
investigating this part.
Overall, the study also has the unique approach of examining the regulations and how the
innovation policy can support high technology industries, as well as the consumer behavior
towards those industries.
Regarding the academic implications, the study can be considered as a base study to
support more researchers to start navigating the consumer acceptance and perception of the new
food technologies such as genetically edited food in Japan and globally. The study provides a
reference in this field in particular, since that most of the similar studies conducted are focusing
more on the genetically modified food field.
Regarding the policy related implications, the study has provided empirical explanation for
the importance of knowledge and science communication, to support policy makers in this field.
It also creates the validity and the demand for more science communication policies due to its
importance. Also, the study advices a collaborative framework between the government,
universities and private sector to create trusted source of information for the consumers.
105
Regarding the industry implications, the study provides significant information about the
regulation comparison, which can be utilized by different companies in this field to grow locally
and globally.
5.3. Limitations and Opportunities for Future Research
Although that this research has put several spotlights on new research areas, and also has
created significant value for the scientific research as well as implications in terms of policy and
academia in general, however, the research also has some limitations that have been totally
acknowledged regarding this research. This subsection shall highlight several limitations, that can
be utilized for future enhancements, and future studies as well.
Regarding the first part of the research that aims to discover further how Japan can grow
internationally in the area of functional food. In this part, the study has highlighted clearly the
Japanese regulations, also investigated several countries' regulations to spot the strength points the
Japanese regulations have in this regard. Although the research in this part has focused mainly on
the regulations, however, more research work can be conducted in investigating further the
consumer acceptance in the foreign markets for the Japanese functional food products. Moreover,
future researches can also highlight the different importing restrictions or procedures for the
Japanese functional food products to the foreign markets and what is the level of complexity of
the procedures to register the Japanese products in the foreign markets to be traded legally among
consumers. This research has partially highlighted the procedures needed, such as labeling
requirements in different countries. However, more research work can be conducted on the
importing legislation itself. Also, future researches can put more emphasis on business-related
studies and statistics showing market sizes in each country, and the sales and market share of the
large enterprises in this field in each country, so we can understand further the level of competition
106
in each market. Also, future studies can create comparisons between the prices of Japanese
products and other global products, giving into consideration maintaining a similar level of
ingredients in order to understand the pricing level and competitiveness of the Japanese products
globally.
Regarding the second part of the research it examined the regulations of the genetically
edited food in Japan in comparison with the regulations in the United States and the European
Union. In this part the limitation is represented in the review methodology, since that in this part,
only legislation reports and press releases have been reviewed without citing comparisons from
other peer-reviewed papers, which came due to the lack of published literature reviewing the
regulations of the genetically edited food due to the uniqueness of the term. Most of the papers
reviewing the genetically edited food aim to discuss more the technicalities behind it and the
different methodologies for it such as CRISPR, TALEN or ZFN, however very few researches
focus on the regulations due to also that regulations around the world are still in the development
stage especially in the United States. Further studies also can be conducted in the future when the
legislation for genetically edited food is more clearly defined around the world. Future studies can
also focus on comparing the regulations of the genetically edited food in the countries that produce
genetically modified food such as Brazil, Argentina, India, Canada, China, Paraguay, Pakistan,
South Africa, Uruguay, and Bolivia. The reason for pointing out those countries that the countries
mentioned has cultivated more than 1 million hectares of genetically modified crops a year based
on the 2015 statistics. The countries mentioned above are supporting the cultivation of GMO crops,
and it would be a good opportunity to examine further if they are considering genetically edited
food as a conventional food or as genetically modified food.
107
Regarding the third part, it focuses on the potential level of acceptance of genetically edited
food products in Japan, as well as examining the different factors that may affect the level of
acceptance. The limitation in this part that all the literature review conducted to extract the factors
subject to the study are based on reviewing genetically modified food-related paper, due to the
uniqueness of the studies examining the acceptance of genetically edited food products in
comparison with the number of studies examining the genetically modified food products.
Therefore, one of the critical issues in this research that it assumes that consumers initially perceive
genetically edited food products and genetically modified food products in the same way and that
the factors affecting the acceptance level are the same in both categories. Therefore, it is truly an
open space for research efforts to be spent more on studying further the factors affecting
genetically edited food and verify the hypotheses above.
Another limitation also regarding the survey results examining the acceptance of
genetically edited food, that consumers are not fully aware of how genetically edited food is
different from genetically modified food, and there is a misconception among consumers that both
categories are the same due to the fact that both have the term "genetically" in their titles. The
genetically modified food products are often associated with health risks in the awareness of the
consumers. Although this study has created intervention between the first and second survey to
eliminate the bias represented in the lack of knowledge regarding genetically edited food, however,
the intervention presentation took place in 5 minutes only, which was not enough to increase the
level of awareness about the difference between the two categories from a technical point of view.
However, the intervention focused more on providing simple and clear information about this
regard without a detailed explanation. Therefore, the bias represented in the lack of knowledge
might still exist in this survey results. It is highly recommended for future studies to create longer
108
intervention presentation to provide more clear and detailed information about genetically edited
food in order to eliminate the lack of knowledge and test the impact of other factors such as
perceived benefits, perceived risks, and trust in a more clear way.
The most critical and the main concern related to the survey results about factors affecting
the acceptance of genetically edited food, that all the survey respondents were from Ritsumeikan
University and from a similar age group. Moreover, all the students are from the same college,
which means that they have a very similar social and educational background as well as interests.
Therefore, all the results from this survey shall be used as exploratory or introductory to examining
the factors affecting genetically edited food products acceptance further. The results came from a
very narrow sample in terms of demographics and did not represent the whole Japanese population
nationwide. Therefore, it is recommended for further studies to utilize the research work of this
study to conduct similar surveys nationwide in other cities of Japan, also expand the sample to
reach more respondents from different social backgrounds in order to verify the validity of the
model to be used to represent the whole population of Japan. Also, it is highly recommended to
conduct further studies in the future to investigate the willingness to purchase genetically edited
food products among the persons responsible for purchasing food products for the family.
Although several limitations regarding the research conducted in this study have been
acknowledged, the study is considered a pioneer in the studied fields, especially the part related to
genetically edited food acceptance in Japan. Therefore, the study is considered a gate for more
researches to implement several approaches and examine further points regarding functional food
and genetically edited food in specific as well as the role of science communication and innovation
policy in boosting innovation.
109
References
1. Farid, M., Kodama, K., Arato, T., Okazaki, T., Oda, T., Ikeda, H., & Sengoku, S. (2019).
Comparative Study of Functional Food Regulations in Japan and Globally. Global
Journal of Health Science, 11(6).
2. Farid, M., Cao, J., Lim, Y., Arato, T., & Kodama, K. (2020). Exploring Factors Affecting
the Acceptance of Genetically Edited Food Among Youth in Japan. International Journal
of Environmental Research and Public Health, 17(8), 2935.
3. Jamil, K. (2009). Biotechnology—A Solution to Hunger?. UN Chronicle, 46(3), 70.
4. A Guide to Food Labeling and Advertisements, A publication of the Agri-Food &
Veterinary Authority, Singapore, First published Feb 2010. Amendments Oct 2011, Oct
2013, Jul 2014, Jan 2015, Jul 2015, Mar 2016, Aug 2018, Feb 2019,
https://www.ava.gov.sg/docs/default-source/tools-and-resources/resources-for-
businesses/aguidetofoodlabelingandadvertisementsversionjuly2.pdf
5. Amin, L., Azad, M. A. K., Gausmian, M. H., & Zulkifli, F. (2014). Determinants of
Public Attitudes to Genetically Modified Salmon. PLOS ONE, 9(1), e86174.
https://doi.org/10.1371/journal.pone.0086174
6. Amin, L.; Jahi, J.M.; Nor, A.R.M.; Osman, M.; Mahadi, N.M. Public Acceptance of
Modern Biotechnology. Asia-Pac. J. Mol. Biol. Biotechnol. 2007, 15, 39–51.
7. Authinticated US Government Information, Department of Health and Human Services,
Food and Drug Administration, [Docket No. FDA–2016–N–4389], Genome Editing in
New Plant Varieties Used for Foods; Request for Comments, Leslie Kux. Available
online: https://www.govinfo.gov/content/pkg/FR-2017-01-19/pdf/2017-00840.pdf
(accessed on 11 January 2017).
8. Bagchi, D. (2008). Nutraceutical and Functional Food Regulations in the United States
and Around the World. Elsevier. https://doi.org/10.1016/B978-0-12-373901-8.X0001-7
9. Bahmanziari, T., Pearson, J. M., & Crosby, L. (2003). Is trust important in technology
adoption? A policy capturing approach. Journal of Computer Information Systems, 43(4),
46–54.
10. Bauer, M.W. Distinguishing Red and Green Biotechnology: Cultivation Effects of the
Elite Press. Int. J. Public Opin. Res. 2005, 17, 63–89, doi:10.1093/ijpor/edh057.
110
11. Beal, George M., Everett M. Rogers, and Joe M. Bohlen (1957) "Validity of the concept
of stages in the adoption process. (n.d.).
12. Benna, U. G., & Garba, S. B. (2016). Population growth and rapid urbanization in the
developing world. IGI Global.
13. Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological
Bulletin, 107(2), 238–246. https://doi.org/10.1037/0033-2909.107.2.238
14. Blandon, Jose & Cranfield, John & Henson, Spencer. (2007). Functional Food and
Natural Health Product Issues: The Canadian and International Context.
15. Blesh, J., Hoey, L., Jones, A. D., Friedmann, H., & Perfecto, I. (2019). Development
pathways toward “zero hunger.” World Development, 118, 1–14.
16. Botelho, D.; Kurtz, H. The introduction of genetically modified food in the United States
and the United Kingdom: A news analysis. Soc. Sci. J. 2008, 45, 13–27,
2008.doi:10.1016/j.soscij.2007.11.001.
17. Bredahl, L. (2001). Determinants of Consumer Attitudes and Purchase Intentions With
Regard to Genetically Modified Food – Results of a Cross-National Survey. Journal of
Consumer Policy, 24(1), 23–61. https://doi.org/10.1023/A:1010950406128
18. Bredahl, L.; Grunert, K.G.; Frewer, L.J. Consumer Attitudes and Decision-Making With
Regard to Genetically Engineered Food Products—A Review of the Literature and a
Presentation of Models for Future Research. J. Consum. Policy 1998, 21, 251–77,
doi:10.1023/A:1006940724167.
19. Bronfman, N. C., Vázquez, E. L., Gutiérrez, V. V., & Cifuentes, L. A. (2008). Trust,
acceptance and knowledge of technological and environmental hazards in Chile. Journal
of Risk Research, 11(6), 755–773. https://doi.org/10.1080/13669870801967184
20. Bröring, Stefanie & Khedkar, Sukhada. (2018). Regulatory Compliance and Company
Strategies: The Case of the Nutrition and Health Claims Regulation (EC) No. 1924/2006:
A Legal-Economic Perspective. DOI: https://doi.org/10.1007/978-3-319-77045-1_6
21. Browne, M. W., & Cudeck, R. (1992). Alternative Ways of Assessing Model Fit.
Sociological Methods & Research, 21(2), 230–258.
https://doi.org/10.1177/0049124192021002005
111
22. CAA Policies, FOSHU Database, 2019
https://www.caa.go.jp/policies/policy/food_labeling/health_promotion/pdf/health_promot
ion_190415_0001.xls
23. Center for Food Safety, The Government of the Hong Kong Special Administrative
Reion, International Development in Labelling of GM Foods, March 2019. Available
online:
https://www.cfs.gov.hk/english/programme/programme_gmf/programme_gmf_gi_info4.
html (accessed on 11 December 2019).
24. Cerny, C.A.; Kaiser, H.F. A study of a measure of sampling adequacy for factor-analytic
correlation matrices. Multivar. Behav. Res. 1977, 12, 43–47.
25. Chauhan, S. (2015). Acceptance of mobile money by poor citizens of India: Integrating
trust into the technology acceptance model. Info, 17(3), 58–68.
https://doi.org/10.1108/info-02-2015-0018
26. Chen, M.-F., & Li, H.-L. (2007). The consumer’s attitude toward genetically modified
foods in Taiwan. Food Quality and Preference, 18(4), 662–674.
https://doi.org/10.1016/j.foodqual.2006.10.002
27. Chong, L. K., Udell, L. J., & Downs, B. W. (2008). Intellectual Property, Branding,
Trademark and Regulatory Approvals in Nutraceuticals and Functional Foods. In
Nutraceutical and Functional Food Regulations in the United States and Around the
World (pp. 403–416). Elsevier. https://doi.org/10.1016/B978-012373901-8.00025-1
28. Chong, L. K., Udell, L. J., & Downs, B. W. (2008). Intellectual Property, Branding,
Trademark and Regulatory Approvals in Nutraceuticals and Functional Foods. In
Nutraceutical and Functional Food Regulations in the United States and Around the
World (pp. 403–416). Elsevier. https://doi.org/10.1016/B978-012373901-8.00025-1
29. Christoph, I. B., Bruhn, M., & Roosen, J. (2008). Knowledge, attitudes towards and
acceptability of genetic modification in Germany. Appetite, 51(1), 58–68.
https://doi.org/10.1016/j.appet.2007.12.001
30. Christoph, I.B.; Bruhn, M.; Roosen, J. Knowledge, attitudes towards and acceptability of
genetic modification in Germany. Appetite 2008, 51, 58–68,
doi:10.1016/j.appet.2007.12.001.
112
31. Clare M. Hasler, Functional Foods: Benefits, Concerns and Challenges—A Position
Paper from the American Council on Science and Health, The Journal of Nutrition,
Volume 132, Issue 12, December 2002, Pages 3772–3781,
https://doi.org/10.1093/jn/132.12.3772
32. Consumer Affair Agency, food labeling policy
https://www.caa.go.jp/policies/policy/food_labeling/health_promotion/
33. Costa-Font, J., & Mossialos, E. (2007). Are perceptions of ‘risks’ and ‘benefits’ of
genetically modified food (in)dependent? Food Quality and Preference, 18(2), 173–182.
https://doi.org/10.1016/j.foodqual.2005.09.013
34. Costa-Font, J.; Mossialos, E. Are Perceptions of ‘Risks’ and ‘Benefits’ of Genetically
Modified Food (in) Dependent? Food Qual. Prefer. 2007, 18, 173–82,
doi:10.1016/j.foodqual.2005.09.013.
35. Court of Justice of the European Union, Press Release No 111/18, Luxembourg,
Organisms obtained by mutagenesis are GMOs and are, in principle, subject to the
obligations laid down by the GMO Directive. Available online:
https://curia.europa.eu/jcms/upload/docs/application/pdf/2018-07/cp180111en.pdf
(accessed on 25 July 2018).
36. Daliri, Eric & Lee, Byong. (2015). Current Trends and Future Perspectives on Functional
Foods and Nutraceuticals. 10.1007/978-3-319-23177-8_10.
37. Dederer, H.G.; Hamburger, D. (Eds.) Regulation of Genome Editing in Plant
Biotechnology: A Comparative Analysis of Regulatory Frameworks of Selected
Countries and the EU; Springer International Publishing: Cham, UK, 2019.
38. Demeny, P., & McNicoll, G. (2006). World population 1950-2000: Perception and
response. Population and Development Review, 32, 1–51.
39. Díaz, Cristina & Gil-González, Diana & Alvarez-Dardet, Carlos. (2018). Scientific
Evidence on Functional Food and Its Commercial Communication: A Review of
Legislation in Europe and the USA: Functional food in Europe and in the USA….
Journal of Food Science. 83. 10.1111/1750-3841.14359.
40. Dries, L.; Heijman, W.; Jongeneel, R.; Purnhagen, K.; Wesseler, J. (Eds.) EU
Bioeconomy Economics and Policies: Volume II; Springer International Publishing:
Cham, UK, 2019.
113
41. Eriksson, D.; Kershen, D.; Nepomuceno, A.; Pogson, B.J.; Prieto, H.; Purnhagen, K.;
Whelan, A. A comparison of the EU regulatory approach to directed mutagenesis with
that of other jurisdictions, consequences for international trade and potential steps
forward. New Phytol. 2019, 222, 1673–1684, Jun. 2019, doi:10.1111/nph.15627.
42. EU Publications, Functional Food Report, 2010, Directorate-General for Research and
Innovation (European Commission), ISSN 1018-5593, DOI 10.2777/82512
43. Euro Monitor 2013 Report, Global Consumer Trends https://www.euromonitor.com
44. Evaluation of randomized controlled trials of foods with functional claims requests: The
learning outcomes from studies in Japan, Nanae Tanemura, Naobumi Hamadate, Hisashi
Urushihara, Journal of Functional Foods, Volume 42, 2018, Pages 248-253, ISSN 1756-
4646.
45. FAO, IFAD and WFP. 2015. The State of Food Insecurity in the World 2015. In Meeting
the 2015 International Hunger Targets: Taking Stock of Uneven Progress; FAO: Rome,
Italy, 2015. Available online: http://www.fao.org/3/a-i4646e.pdf (accessed on 10
February 2020).
46. FAO. (2020). Simulating rising undernourishment during the COVID-19 pandemic
economic downturn. FAO. https://doi.org/10.4060/ca8815en
47. Federal Register/Vol. 82, No. 12, Thursday, January 19, 2017, Proposed Rules,
Department of agriculture, Animal and Plant Health Inspection Service, 7 CFR Part 340
[Docket No. APHIS–2015–0057] RIN 0579–AE1. Available online:
https://www.govinfo.gov/content/pkg/FR-2017-01-19/pdf/2017-00858.pdf (accessed on
14 January 2020).
48. Fishbein, M. An Investigation of the Relationships between Beliefs about an Object and
the Attitude toward that Object. Hum. Relat. 1963, 16, 233–239,
doi:10.1177/001872676301600302.
49. Fornell, C.; Larcker, D.F. Evaluating Structural Equation Models with Unobservable
Variables and Measurement Error. J. Mark. Res. 1981, 18, 39, doi:10.2307/3151312.
50. Frewer, L.J.; Howard, C.; Shepherd, R. Public Concerns in the United Kingdom about
General and Specific Applications of Genetic Engineering: Risk, Benefit, and Ethics. Sci.
Technol. Hum. Values 1997, 22, 98–124, doi:10.1177/016224399702200105.
114
51. Functional Food Ingredients Market 2019 Synopsis, Market Surge, Future Scope, Top
Key Players and Forecast to 2025, https://wiseawareness.com/functional-food-
ingredients-market-2019-synopsis-market-surge-future-scope-top-key-players-and-
forecast-to-2025/
52. Functional Foods And Natural Health Products Regulations In Canada And Around The
World: Nutrition Labels And Health Claims, Stavroula Malla, Jill Hobbs, Eric Kofi
Sogah, Canadian Agricultural Innovation and Regulation Network, CAIRN research
network, April 2013
53. Functional Foods In The European Union: An Overview Of The Sector’s Main Issues,
Alessandra Castellini, Maurizio Canavari, and Carlo Pirazzoli, 2002, 8th Joint
Conference on Food, Agriculture and the Environment
54. Functional foods: the Food and Drug Administration perspective, Am J Clin Nutr. 2000
Jun;71(6 Suppl):1735S-8S; discussion 1739S-42S. doi: 10.1093/ajcn/71.6.1735S.
PMID:10837331 DOI: 10.1093/ajcn/71.6.1735S
55. Gaskell, G. Worlds Apart? The Reception of Genetically Modified Foods in Europe and
the U.S. Science 1999, 285, 384–87, doi:10.1126/science.285.5426.384.
56. Gaskell, G.; Stares, S.; Allansdottir, A.; Allum, N.; Castro, P.; Esmer, Y.; Hampel, J.
Europeans and Biotechnology in 2010 Winds of change? 2010. Available online:
https://ec.europa.eu/research/swafs/pdf/pub_archive/europeans-biotechnology-in-
2010_en.pdf (accessed on 21 February 2020).
57. Global Health Functional Food Market Insights, Forecast To 2025, Big Market Research,
2018, https://www.bigmarketresearch.com/global-health-functional-food-insights-
forecast-to-2025-market
58. Glossary of Agricultural Biotechnology Terms, United States Department of Agriculture.
February 2013. Available online:
https://www.usda.gov/topics/biotechnology/biotechnology-glossary (accessed on 13
January 2020).
59. Gur, Johanna & Mawuntu, Marselinny & Martirosyan, Danik. (2018). FFC’s
Advancement of Functional Food Definition. Functional Foods in Health and Disease. 8.
385. 10.31989/ffhd.v8i7.531. DOI: https://doi.org/10.31989/ffhd.v8i7.531
115
60. Hasler, C. M. (2002). Functional Foods: Benefits, Concerns and Challenges—A Position
Paper from the American Council on Science and Health. The Journal of Nutrition,
132(12), 3772–3781. https://doi.org/10.1093/jn/132.12.3772
61. Health claims regulations Comparison between USA, Japan, and European Union, Lalor
Fiona, Wall, Patrick, British Food Journal, Volume: 113, Issue: 2-3, Pages: 298-313,
Published: 2011, DOI: 10.1108/00070701111105358
62. Farina, F. (2017). Japan in the international food regimes: Understanding japanese food
self-sufficiency decline. In Feeding Japan (pp. 363-384). Palgrave Macmillan, Cham.
63. Health foods and foods with health claims in Japan, Ohama, Ikeda, Moriyama,
TOXICOLOGY, Volume: 221, Issue: 1, Pages: 95-111, DOI: 10.1016/j.tox.2006.01.015,
Published: 2006
64. Hibino, A.; Nagata, M. Biotechnology in the Japanese media: Comparative analysis of
newspaper articles on genetic engineering in Japan and Europe. Asian J. Soc. Psychol.
2006, 9, 12–23, 2006.
65. Hoban, T.J. Consumer acceptance of biotechnology: An international perspective. Nat.
Biotechnol. 1997, 15, 232–234, doi:10.1038/nbt0397-232.
66. Hooper, D., Coughlan, J., & Mullen, M. (2007). Structural Equation Modeling:
Guidelines for Determining Model Fit. The Electronic Journal of Business Research
Methods, 6.
67. Hu, L.-T.; Bentler, P.M. Cutoff criteria for fit indices in covariance structure analysis:
Conventional criteria versus new alternatives. Struct. Equ. Model. A Multidiscip. J. 1999,
6, 1–55.
68. Huffman, W.; Mccluskey, J. The economics of labeling GM foods. AgBioForum 2014,
17, 156–160.
69. International Service for the Acquisition of Agri-biotech Applications, ISAAA. Global
Status of Commercialized Biotech/GM Crops: ISAAA Brief No. 52; ISAAA: Ithaca, NY,
USA, 2016.
70. ISAAA Brief 54-2018: Executive Summary, ISAAA. 2016. Global Status of
Commercialized Biotech/GM Crops: 2018. ISAAA Brief No. 54. ISAAA. Available
online:
116
http://www.isaaa.org/resources/publications/briefs/54/executivesummary/default.asp
(accessed on 10 January 2020).
71. James, C.; Krattiger, A.F. Global Review of the Field Testing and Commercialization of
Transgenic Plants, 1986 to 1995: The First Decade of Crop Biotechnology. ISAAA
Briefs No. 1. ISAAA: Ithaca, NY. pp. 31. Available online:
https://www.isaaa.org/resources/publications/briefs/01/download/isaaa-brief-01-1996.pdf
(accessed on 17 January 2020).
72. James, J. (2004). Consumer knowledge and acceptance of agricultural biotechnology
vary. California Agriculture, 58(2), 99–105.
73. Japan’s falling food self-sufficiency, The Japan Times, August 2019. Available online:
https://www.japantimes.co.jp/opinion/2019/08/20/editorials/japans-falling-food-self-
sufficiency/#.XlwRMS2B1TY (accessed on 13 February 2020).
74. Japan’s New Health Claims Labeling System Creates Opportunities, 2015, GAIN Report
Number: JA5025, USDA Foreign Agricultural Service, Yuichi Hayashi,
https://gain.fas.usda.gov
75. Jensen, C. J., & Levin, B. H. (2020). The world of 2020: Demographic shifts, cultural
change, and social challenge. Exploring the Future of Crime, Communities, and Policing,
31.
76. Kaur, K., & Rampersad, G. (2018). Trust in driverless cars: Investigating key factors
influencing the adoption of driverless cars. Journal of Engineering and Technology
Management, 48, 87–96. https://doi.org/10.1016/j.jengtecman.2018.04.006
77. Kaur, K.; Rampersad, G. Trust in driverless cars: Investigating key factors influencing
the adoption of driverless cars. J. Eng. Technol. Manag. 2018, 48, 87–96,
doi:10.1016/j.jengtecman.2018.04.006.
78. Khedkar, Sukhada & Ciliberti, Stefano & Bröring, Stefanie. (2016). The EU health
claims regulation: implications for innovation in the EU food sector. British Food
Journal. 118. 2647-2665. 10.1108/BFJ-01-2016-0021.
79. Klümper, W.; Qaim, M. A Meta-Analysis of the Impacts of Genetically Modified Crops.”
Edited by emidio albertini. PLoS ONE 2014, 9, e111629,
doi:10.1371/journal.pone.0111629.
117
80. Komoto, K.; Okamoto, S.; Hamada, M.; Obana, N.; Samori, M.; Imamura, T. Japanese
Consumer Perceptions of Genetically Modified Food: Findings from an International
Comparative Study. Interact. J. Med. Res. 2016, 5, e23, doi:10.2196/ijmr.5850.
81. Labeling Guidance for Genome Edited Food Products (Japan), United States Department
of Agriculture USDA, Foreign Agricultural Service, Report Number: JA2019-0174, by
Daisuke Sasatani and Suguru Sato. Available online:
https://apps.fas.usda.gov/newgainapi/api/Report/DownloadReportByFileName?fileName
=Labeling%20Guidance%20for%20Genome%20Edited%20Food%20Products_Tokyo_J
apan_10-06-2019 (accessed on 8 October 2019).
82. Latifah Amin, M.; Azad, A.K.; Gausmian, M.H.; Zulkifli, F. Determinants of Public
Attitudes to Genetically Modified Salmon. PLoS ONE 2014, 9, e86174,
doi:10.1371/journal.pone.0086174.
83. Ledford, H. CRISPR Conundrum: Strict European Court Ruling Leaves Food-Testing
Labs without a Plan. Nature 2019, 572, 15–15, doi:10.1038/d41586-019-02162-x.
84. Leighton K. Chong, Lawrence J. Udell, Bernard W. Downs, Chapter 25 - Intellectual
Property, Branding, Trademark and Regulatory Approvals in Nutraceuticals and
Functional Foods, DOI: https://doi.org/10.1016/B978-012373901-8.00025-1.
85. Leung, Y. (2013). Perceived Benefits. In M. D. Gellman & J. R. Turner (Eds.),
Encyclopedia of Behavioral Medicine (pp. 1450–1451). Springer New York.
https://doi.org/10.1007/978-1-4419-1005-9_1165
86. López Montesinos, O. A., Pérez, E. F., Fuentes, E. E. S., Luna-Espinoza, I., & Cuevas, F.
A. (2016). Perceptions and attitudes of the Mexican urban population towards genetically
modified organisms. British Food Journal, 118(12), 2873–2892.
https://doi.org/10.1108/BFJ-06-2016-0247
87. Lucht, J.M. Public Acceptance of Plant Biotechnology and GM Crops. Viruses-Basel
2015, 7, 4254–4281, doi:10.3390/v7082819.
88. Maes, J.; Bourgonjon, J.; Gheysen, G.; Valcke, M. Variables Affecting Secondary School
Students’ Willingness to Eat Genetically Modified Food Crops. Res. Sci. Educ. 2018, 48,
597–618, doi:10.1007/s11165-016-9580-4.
118
89. Martin, M.J.; Hill, R.L.; Van Sandt, A.; Thilmany, D.D. Colorado Residents Trusted
Sources of Agricultural, Biotechnology, and Food Information; The Journal of
Agrobiotechnology Management & Economics, Volume 19, Article 4, 2016.
90. Martirosyan, Danik & Singharaj, Bryan. (2016). Health Claims and Functional Food: The
Future of Functional Foods under FDA and EFSA Regulation.
91. McCluskey, J.J.; Kalaitzandonakes, N.; Swinnen, J. Media Coverage, Public Perceptions,
and Consumer Behavior: Insights from New Food Technologies. Annu. Rev. Resour.
Econ. 2016, 8, 467–486, doi:10.1146/annurev-resource-100913-012630.
92. Michael J. Martin, R. L. H. (2016, September 16). Colorado Residents Trusted Sources of
Agricultural, Biotechnology, and Food Information. AgBioForum.
http://www.agbioforum.org/v19n1/v19n1a04-martin.htm
93. Mishra, Swati & Behera, Prafulla & Kar, Biswabandita & Ray, Ramesh. (2018).
Advances in Probiotics, Prebiotics and Nutraceuticals. 10.1007/978-3-319-74820-7_7.
94. Miura, T. (2017), “Food functional display system in Hokkaido: Current status of
Healthy DO”, Vol. 21 No.1, pp.1-4. (in Japanese)
95. Montesinos, O.A.L.; Pérez, E.F.; Fuentes, E.E.S.; Luna-Espinoza, I.; Cuevas, F.A.
Perceptions and Attitudes of the Mexican Urban Population towards Genetically
Modified Organisms. Br. Food J. 2016, 118, 2873–92, doi:10.1108/BFJ-06-2016-0247.
96. Moon, W., Balasubramanian, S. K., Moon, W., & Balasubramanian, S. K. (2001). A
MULTI-ATTRIBUTE MODEL OF PUBLIC ACCEPTANCE OF GENETICALLY
MODIFIED ORGANISMS. https://doi.org/10.22004/AG.ECON.20745
97. Moon, W.; Balasubramanian, S.K. A Multi-Attribute Model of Public Acceptance of
Genetically Modified Organisms. Sel. Pap. 2001, 20, doi:10.22004/ag.econ.20745.
98. Moors, Ellen. (2012). Functional Foods: Regulation and Innovations in the EU.
Innovation The European Journal of Social Science Research. 25. 424-440.
10.1080/13511610.2012.726407.
99. Moseley, B. The safety and social acceptance of novel foods. Int. J. Food Microbiol.
1999, 50, 25–31, Sep. 1999, doi:10.1016/S0168-1605(99)00074-4.
100. Mukhamedjanov, E. K. (2018). Fucoidan is the nutraceutic for support of
homeostasis of metabolic indicators and systems of their regulation. Journal of Probiotics
& Health, 06. https://doi.org/10.4172/2329-8901-C3-032
119
101. National Academies of Sciences Engineering and Medicine, Genetically
Engineered Crops: Experiences and Prospects. Washington, DC: The National
Academies Press, 2016. Available online:
https://www.nap.edu/catalog/23395/genetically-engineered-crops-experiences-and-
prospects (accessed on 7 February 2020).
102. Nicolia, A.; Manzo, A.; Veronesi, F.; Rosellini, D. An Overview of the Last 10
Years of Genetically Engineered Crop Safety Research. Crit. Rev. Biotechnol. 2014, 34,
77–88, doi:10.3109/07388551.2013.823595.
103. Nutraceutical and functional food regulations in the United States and around the
World, Second edition, Debasis Bagchi, Food science and technology international series,
Academic Press, DOI: 10.1016/B978-0-12-373901-8.X0001-7
104. Öz, B.; Unsal, F.; Movassaghi, H. Consumer attitudes toward genetically
modified food in the United States: Are Millennials different? J. Transnatl. Manag. 2018,
23, 3–21, doi:10.1080/15475778.2017.1373316.
105. Pardo, R.; Midden, C.; Miller, J.D. Attitudes toward Biotechnology in the
European Union. J. Biotechnol. 2002, 98, 9–24, doi:10.1016/S0168-1656(02)00082-2.
106. Patel, Darshika & Dufour, Yvon & Domigan, Neil. (2008). Functional Food and
Nutraceutical Registration Process in Japan and China: Similarities and Differences.
Journal of Pharmacy and Pharmaceutical Sciences. 11(4).
107. Pidgeon, N.F.; Poortinga, W.; Rowe, G.; Horlick‐Jones, T.; Walls, J.; O’Riordan,
T. Using Surveys in Public Participation Processes for Risk Decision Making: The Case
of the 2003 British GM Nation? Public Debate. Risk Anal. 2005, 25, 467–479,
doi:10.1111/j.1539-6924.2005.00603.x.
108. Recent Trends in GE Adoption, United States Department of Agriculture,
Economic Research Service, September 2019, Laura Dodson. Available online:
https://www.ers.usda.gov/data-products/adoption-of-genetically-engineered-crops-in-the-
us/recent-trends-in-ge-adoption.aspx (accessed on 12 January 2020).
109. Regulation of Functional Foods and Nutraceuticals A Global Perspective, Clare
M. Hasler, 2005, ISBN 0-8138-1177-5
120
110. Regulations on health/functional foods in Korea, Ji Yeon Kim, Dai Byung Kim,
Hyong Joo Lee, Toxicology, Volume 221, Issue 1, 2006, Pages 112-118, ISSN 0300-
483X
111. Revelle, W. (n.d.). KMO: Find the Kaiser, Meyer, Olkin Measure of Sampling
Adequacy.
112. Rogers, E.M. (2003). Diffusion of Innovations, 5th Edition. Free Press.
https://books.google.co.jp/books?id=9U1K5LjUOwEC
113. Rogers, Everett M. (1962). Diffusion of Innovations the Free Press of Glencoe.
NY, 32, 891–937.
114. Ronald, P. Plant Genetics, Sustainable Agriculture and Global Food Security.
Genetics 2011, 188, 11–20, doi:10.1534/genetics.111.128553.
115. Schimizu, T. (2003), “Health claims on functional foods: the Japanese regulations
and an international comparison”, Nutrition Research Reviews, Vol. 16, pp. 241-52.
116. SDGs, U. (2015). United Nations sustainable development goals. UN. Org.
117. Shimizu, Makoto. (2014). History and Current Status of Functional Food
Regulations in Japan. Nutraceutical and Functional Food Regulations in the United States
and Around the World: Second Edition. 257-263. 10.1016/B978-0-12-405870-5.00015-3.
118. Shimizu, Makoto. (2016). Multifunctions of dietary polyphenols in the regulation
of intestinal inflammation. Journal of Food and Drug Analysis. 25.
10.1016/j.jfda.2016.12.003.
119. Singh, Ram & Takahashi, Toru & Shastun, Sergey & Elkilany, Galal & Hristova,
Krasimira & Shehab, Abdulla & Onsaard, Ekasit & Phomkong, Wiriya & Chaves, Hilton
& Singh, Mukta & Srivastava, Ratan & Srivastav, Munushi & Singh, RG. (2016). The
Concept of Functional Foods and Functional Farming in the Prevention of Cardiovascular
Diseases A Review of Goals from 18th WCCN. DOI:
https://doi.org/10.17554/j.issn.2309-6861.2015.02.75
120. Stephanie. (2016, May 11). Kaiser-Meyer-Olkin (KMO) Test for Sampling
Adequacy. Statistics How To. https://www.statisticshowto.com/kaiser-meyer-olkin/
121. Sumner, A., Hoy, C., Ortiz-Juarez, E., & UNU-WIDER. (2020). Estimates of the
impact of COVID-19 on global poverty (4th ed., Vol. 2020). UNU-WIDER.
https://doi.org/10.35188/UNU-WIDER/2020/800-9
121
122. Tacon, A. G. (2018). Global trends in aquaculture and compound aquafeed
production. The Magazine of the World Aquaculture Society, 49, 33–46.
123. Tan, M.; Teo, T.S. Factors Influencing the Adoption of the Internet. Int. J.
Electron. Commer. 1998, 2, 5–18, doi:10.1080/10864415.1998.11518312.
124. Technology adoption life cycle. (2020b). In Wikipedia.
https://en.wikipedia.org/w/index.php?title=Technology_adoption_life_cycle&oldid=9346
04314
125. The 2017 Revision of World Population Prospects is the 25th round of official
UN population estimates and projections that have been prepared by the Population
Division of the United Nations Department of Economic and Social Affairs. Available
online: https://www.un.org/development/desa/en/news/population/world-population-
prospects-2017.html (accessed on 12 January 2020).
126. The World Bank Database, Age dependency ratio, age distributions of United
Nations Population Division's World Population,
https://data.worldbank.org/share/widget?indicators=SP.POP.DPND&view=chart
127. The World Population Prospects 2019: Highlights presents the main results of the
26th round of the UN’s global population estimates and projections. Available online:
https://www.un.org/development/desa/en/news/population/world-population-prospects-
2019.html (accessed on 10 January 2020).
128. UN General Assembly, Transforming our World: The 2030 Agenda for
Sustainable Development, 21 October 2015, A/RES/70/1. Available online:
https://www.refworld.org/docid/57b6e3e44.html (accessed on 9 January 2020).
129. United Nations, Department of Economic and Social Affairs, Population Division
(2019). World Population Prospects 2019: Highlights (ST/ESA/SER.A/423). ISBN: 978-
92-1-148316-1. Available online:
https://population.un.org/wpp/Publications/Files/WPP2019_Highlights.pdf (accessed on
23 December 2019).
130. United Nations. (2013). UN Projects World Population to Reach 8.5 Billion by
2030, Driven by Growth in Developing Countries.
122
131. US Food and Drug Administration FDA, Gene Editing, CBER’s Perspective,
FDA Science Board Meeting. Available online:
https://www.fda.gov/media/101146/download (accessed on 15 November 2016).
132. USDA Foreign Agricultural Service, Report Number: JA9050, Suguru Sato.
Available online:
https://apps.fas.usda.gov/newgainapi/api/report/downloadreportbyfilename?filename=Jap
anese%20Health%20Ministry%20Finalizes%20Genome%20Edited%20Food%20Policy_
Tokyo_Japan_4-12-2019.pdf (accessed on 4 December 2019).
133. Van Eenennaam, A.L.; Wells, K.D.; Murray, J.D. Proposed U.S. Regulation of
Gene-Edited Food Animals Is Not Fit for Purpose. NPJ Sci. Food 2019, 3, 3,
doi:10.1038/s41538-019-0035-y.
134. Viklund, M. J. (2003). Trust and risk perception in western Europe: A cross‐
national study. Risk Analysis: An International Journal, 23(4), 727–738.
135. Villaño, Débora & Gironés-Vilaplana, Amadeo & Cristina, Garcia-Viguera &
Moreno, Diego A.. (2016). Development of Functional Foods. DOI:
https://doi.org/10.1016/B978-0-12-803751-5.00010-6
136. World Health Organization. Frequently asked questions on genetically modified
foods. Available online: https://www.who.int/foodsafety/areas_work/food-
technology/faq-genetically-modified-food/en/ (accessed on 17 January 2020).
137. Worlds apart. Consumer acceptance of functional foods and beverages in
Germany and China, Siegrist, Michael, Shi, Jing, Giusto, Alice, Hartmann, Christina,
APPETITE, Volume: 92, Pages: 87-93, DOI: 10.1016/j.appet.2015.05.017, Published:
SEP 1, 2015
138. Yamada, K., Sato-Mito, N., Nagata, J. and Umegaki, K. (2008), “Health claim
evidence requirements in Japan”, Journal of Nutrition, Vol. 138 No. 6, pp. 1192S-19.
139. Zhang, Y., Jing, L., Bai, Q., Shao, W., Feng, Y., Yin, S., & Zhang, M. (2018).
Application of an integrated framework to examine Chinese consumers’ purchase
intention toward genetically modified food. Food Quality and Preference, 65, 118–128.
https://doi.org/10.1016/j.foodqual.2017.11.001
123
Appendix 1: How importance the food security in the SDG
The Sustainable Development Goals SDGs are sets of global goals that were stated and
adopted by all the United Nations member countries in the year 2015. It is a global blueprint that
aims to provide a sustainable future for all countries around the world. The Sustainable
Development Goals were announced in the United Nations General Assembly with the plan to
achieve all the stated goals by the year 2030. The primary foundation of the SDGs that it tackles
all the social and most pressing challenges that the world is facing. It focusses mainly on poverty,
health, education, environmental challenges as well as other pressing issues. The total number of
goals is 17 goals, and the goals have been set to be interconnected to achieve the great purpose of
global sustainability (SDGs, 2015).
The 1st goal of the SDGs is named “no poverty,” and it aims to eliminate all the forms of
poverty everywhere in the world. Poverty poses a real challenge in achieving SDGs, since that
more than 700 million persons around the world are living in extreme poverty conditions. The 2nd
goal is named “zero hunger,” which aims to eliminate hunger around the world and provide decent
sources of food.
Figure 25 | The Sustainable development goals map
124
First Goal: Zero Poverty
The first goal of the SDGs is to eliminate poverty everywhere around the world. During
the past three decades, the world has successfully reduced the number of people who live in
extreme poverty from 36% in the year 1990 to nearly 10% in the year 2015, which means that we
have over 700 million people around the world currently still living in extreme poverty conditions.
Poverty affects access to the most basic needs for daily life, such as healthcare, education, water,
and, most importantly, food. According to the United Nations studies, the majority of the sub-
Saharan Africa citizens live on less than $1.90 per day. Also, people in rural areas have more
severe conditions of poverty in comparison with the urban areas since that the average poverty rate
in rural areas is more than 17%, which more than three times the average rate in the urban areas in
this regard. Although poverty has a close connection with unemployment, however, in the year
2018, it was registered that nearly 8% of the working households around the world are living in
extreme poverty situations. Based on the statistics mentioned above, the world needs to provide
sustainable jobs and promote equality for more sustainable and inclusive economic development
in the future. Also, as we have noticed that food pricing is a critical issue that can be tackled in
order to coop with the high poverty rates, and provide decent living standards even for financially
sensitive families. There are other issues also associated with poverty, such as equality. Globally
there are 20% more women suffer from extreme poverty than men in the age 25 – 34 years old.
Also, eliminating poverty is essential for our future generations since nearly 20% of the children
around the world are suffering from poverty.
Although that the poverty situation around the world is gradually enhancing in comparison
with the year 1990, however due to the current COVID-19 crisis, the situation might get severely
worse, and might reverse the positive progress that happened in the past decades. According to the
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UN-DESA, COVID-19 will severely affect the no poverty SDG, since that the huge loss of
individual income, especially among the part-time workers, can lead to pushing a high number of
families around the world below the poverty line. The UNU-WIDER also has issued a study to
estimate the potential negative effect of the COVID-19 on the poverty rate globally with a special
focus on the per capita income. The study has calculated the several potential outcome scenarios
of global contractions with 5%, 10%, and 20% when applying the well-known poverty lines
standards of $1.9, $3.2 and $5.5 a day. The study has confirmed the above mentioned UN-DESA
assumption that COVID-19 will create an actual challenge in achieving the zero hunger SDG by
the year 2030. There is a very high probability that the poverty rate will increase for the first time
since 1990, and it may reverse a decade worth of work in the global fight against poverty. The
most extreme scenario in the study has predicted that some areas will register poverty levels similar
to the ones registered in 1990, also that the number of people suffering from poverty may increase
by 420 million people on the $1.9 line to 580 million people on the $5.5 poverty line. The study
has summarized the three different scenarios outcome in, as shown in the table below (Sumner et
al., 2020).
Table 37 | Poverty rate prediction post-COVID-19
$1.9 per day $3.2 per day $5.5 per day
Current (M Person) 759.2 1898.5 3275.8
5% Increase (M Person) 844.1 2033.8 3399.5
10% Increase (M Person) 940.8 2176.9 3524.4
20% Increase (M Person) 1178.1 2479.9 3799.3
Current (%) 10.1 25.2 43.5
5% Increase (%) 11.2 27.0 45.2
10% Increase (%) 12.5 28.9 46.8
20% Increase (%) 15.7 33.0 50.5
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As shown in the study cited above, the world is expected to have an increase in the poverty
rate after the COVID-19 crisis, which create a better urge for food-related technologies that can
help to provide enough nutrients with optimum financial value, in order to meet the expectations
and the need globally.
Second Goal: Zero Hunger
The second goal of the SDG is “Zero Hunger,” which aims to eliminate hunger and achieve
high level of food security for all as well as to improve the nutrition level worldwide. Globally,
hunger is back on the rise, and under-nutrition continues to affect millions of children. Globally,
public investment in agriculture is getting reduced, small-scale food producers and family farmers
need much more support, and increased investment in infrastructure and technology is desperately
needed for agriculture. Although the number of people suffering from hunger around the world
has been going down since 1990, however starting from 2015, the number is back again on the
rise. The number of people suffering from severe hunger has increased from 784 million in the
year 2015 to nearly 821 million in the year 2018. Nearly 70% of the undernourished citizens
worldwide are concentrated in two regions, where 277 million citizens are located in southern
Asia, and 237 million are located in sub-Saharan Africa. Overall, it is estimated that in developing
countries, nearly 13% of the total population is undernourished. This estimation is different in the
case of sub-Saharan Africa, where the percentage of undernourished people has increased from
20% in the year 2014 to more than 23% in the year 2017, making nearly 1 out of every four citizens
undenounced, which is a shocking fact. The undernourishment also can be considered the main
reason behind child mortality in several countries where 3.1 million children under five years old
die every year, representing 45% of the child mortality rate in the same areas. According to the
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latest estimates from FAO in the year 2018, nearly 22% of the total number of children under five
years old worldwide, are still suffering from undernourishment.
The level of food security is divided into three categorizations. The first one is “severe food
insecurity,” which represents the people who are suffering from extreme levels of food insecurity
and have suffered from not being able to reach any nutrition source for a complete day or more.
The second level is “moderate food insecurity,” and in this level, the people are suffering from a
medium level of food insecurity, which means that they have uncertainty on a daily basis whether
they will get food or not. Also, they might be obligated to reduce the amount of food that they
usually or need to consume in order to survive. In this category, people are eating from any source
of food they can reach to, despite its level of nutrients or hygiene. The third category is named
“food security,” which represents the people who have direct and regular access to food with
acceptable quantity and quality.
As shown in the figure below, around 700 million people worldwide representing nearly
10% of the global population are suffering from the worst level of food insecurity, where the total
number of people suffering from food insecurity in general including both severe and moderate
levels are above 2 billion person, representing 26% of the global population, which emphasize on
the importance of solving food security-related challenges.
The level of food insecurity is different from region to region, and it is highly correlated
with several other economic factors such as GDP per capita. Based on the figure below, the number
of people suffering from severe food insecurity in North America and Europe is nearly 11 million
people, who are representing slightly less than 1% of the population of this region that reached 1.1
billion people. On the other hand, we find that Africa is suffering from severe levels of food
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insecurity where the number of people suffering from that is nearly 277 million people who
represent more than 21% of the total population of 1.2 billion people.
Figure 26 | Distribution of food insecurity level in different regions (FAO, 2020)
The level of moderate food insecurity, including severe food insecurity as well, has reached
very high levels in Africa. According to the figure below, the percentage of undernourished people
in Africa has increased from 47.6 in the year 2014 to 52.5 in the year 2018, making more than half
of the African population unnourished. The level also is increasing globally since it has increased
from 23.2% in the year 2014 to 26.4 in the year 2018. The only regions that have a steady decrease
in the undernourishment rate are the northern America and Europe, where the percentage of
undernourished people has decreased from 9.6 in the year 2014 to 8.0 in the year 2018. Although
the numbers in Asia are increasing as well, however, the situation in Japan is completely different.
According to the data in 2018, nearly 0.6% are suffering from a severe level of food insecurity,
and 2.8% are suffering from moderate level including the severe level of food insecurity, where
the Average in Asia is about 7.8% for the severe levels, and 22.8% for the moderate and severe
level, which shows the strength of Japan in this field.
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Figure 27 | Food insecurity level by percentage in different regions (2014 – 2018)
Due to the COVID-19 situation, the world is expecting a wave of economic development
reduction in the upcoming few years. Scientists have created three scenarios for the GDP reduction
rate using several economic-related data. Although that the international monetary fund has created
a forecast last January that the world economy will witness a growth of 3% during this year,
however, the actual studies this April are showing contraction in the world economy by at least
3%. According to the three scenarios, it is highly expected that the number of people suffering
from undernourishment will increase by 14.4 to 80.3 million based on the economic scenarios, as
shown in the figure below (FAO, 2020).
Figure 28 | Expected increase in the number of undernourished people after COVID-19 (FAO, 2020)
