adoption of iot in logistics & supply chain …

ADOPTION OF IOT IN LOGISTICS & SUPPLY

CHAIN MANAGEMENT: A SYSTEMATIC

LITERATURE REVIEW

Klayton Eduardo da Rocha (UFSCar)

[email protected]

Juliana Veiga Mendes (UFSCar)

[email protected]

Luis Antonio de Santa-Eulalia (USherbrooke)

[email protected]

virginia aparecida da silva moris (UFSCar)

[email protected]

The Fourth Industrial Revolution (Industry 4.0) has the potential to

dramatically change the way businesses and Supply Chain work. In this

context, one of the main emerging technologies is known as the Internet of

Things (IoT), which allows objects to communicate to one another and to

various platforms in real-time. This paper presents a Systematic Literature

Review focused on IoT and Logistics & Supply Chain Management (LSCM).

Down from more than 72 thousand documents around IoT on the ISI Web of

Science database, we found 39 articles (with SJR quality ranking) explicitly

combining IoT and LSCM. It was possible to identify a high quantity of articles

employing the single case-study methodology (85%), suggesting that the

research on this field may still be at its early developments. Most of these

case studies were technical papers around IoT platforms (46%) and the use of

RFID (Radio Frequency Identification) to improve systems operations. It was

also possible to notice that system’s complexity is a major concern in the

literature, including issues related to the lack of established standards for

data exchange and problems concerning data security and privacy. Besides

presenting different definitions and mapping how the top journals are

publishing these two topics together, this paper also recommends future

studies relating IoT and LSCM.

Palavras-chave: Systematic Literature Review, Internet of Things, Logistics &

Supply Chain Management, Industry 4.0

XXXVII ENCONTRO NACIONAL DE ENGENHARIA DE PRODUCAO “A Engenharia de Produção e as novas tecnologias produtivas: indústria 4.0, manufatura aditiva e outras abordagens

avançadas de produção”

Joinville, SC, Brasil, 10 a 13 de outubro de 2017.




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1. Introduction

The Fourth Industrial Revolution is “fundamentally changing the way we live, work, and

relate to one another” (SCHWAB, p. 1, 2016). The Industry 4.0 concerns the development

and the connection of emerging technologies in areas such as 3D printing, augmented virtual

reality, artificial intelligence, robotics, autonomous vehicles, big data, cloud computing,

biotechnology in a way to promote disruptions in businesses, but important changes may also

occur in the economy and in the society. Among these technologies, the Internet of Thing

(IoT) is reaching substantial attention (CHUNG; KIM, 2016). According to Weinberger,

Bilgeri & Fleisch (p. 700, 2016), the term IoT “was initially coined at the Auto-ID labs at the

Massachusetts Institute of Technology (MIT) and describes the vision that virtually all objects

become smart and connected”. Kafle, Fukushima & Harai (p.44, 2016) considers it as “an

object of the physical world (physical thing) or the information’ world (virtual thing), which

is capable of being identified and integrated into communication networks.”

IoT may contribute to addressing many of our global challenges, such as disease outbreaks,

climate change, pollution, resource scarcity (KAFLE; FUKUSHIMA; HARAI, 2016) and it

may impact our own life routine, such as home management and appliance maintenance

(WEINBERGER; BILGERI; FLEISCH, 2016, BABAMIR, 2012). In terms of the application

of IoT to the industrial world, the literature mention that it may help in “preventive

maintenance, remote control, manufacturing analytic tools and services, management of

process quality as well as smart retrofitting of machinery (…), and it will allow to integrate

whole supply chains, tracking and tracing inter and intra plant logistics” (WEINBERGER;

BILGERI; FLEISCH, p. 701, 2016). In addition, the advances in IoT may help to “monitor

and visualize various wireless sensor networks (WSN) applications in manufacturing

environments such as automated workcells, transportation systems, logistic, and storage

systems” (BI; WANG; DA XU, p. 377 2016). In this context, real-time data and delivery of

the product in the right place at the right time (SIVAMANI; KWAK; CHO, 2014) are

streamlined, even allowing the creation of new services and the improvement of business

processes (APPEL et al., 2014) and business models.




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Despite the importance of IoT in Logistics & Supply Chain Management (LSCM), a

Systematic Literature Review in the area is still lacking. Thus, this paper aims to contribute to

reducing this research gap by presenting and discussing what the scientific literature has

published in the area.

This paper is organized as following. After presenting this general introduction in Section 1,

Section 2 shows the employed methodology, while Section 3 presents the main research

results. Finally, Section 4 outlines some conclusions and final remarks.

2. Methodology

Inspired by Seuring & Muller (2008), Govindan, Soleimani & Kannan (2014), Conforto,

Amaral & Silva (2011) and Hallinger (2013), we followed the steps summarized in Figure

1for the data collection, and described next.

Figure 1 - Summary of the steps for the methodology

Source: Adapted from Conforto, Amaral & Silva (2011)

a) Problem definition: is the formulation of a question to be tested, which should be

susceptible to a solution (GIL, 2002). For this paper, we have developed the following

question: What is the state of the art in field of the Internet of Things employed in the

context of Logistics & Supply Chain Management?

b) Goals: should be aligned with a research project objective. We aim to identify indexed

peer-reviewed scientific publications related to IoT and LSCM;

c) Primary sources: represents the databases in which articles are available to the public.

For this first literature review effort, we opted for the “Web of Science (WoS)”, since it

is a large multi-disciplinary and human-curated database.

d) Strings: are the words related to the construct of the research as input to the search.

Conforto, Amaral & Silva (2011) indicate that a preliminary search or consultation to




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experts is necessary to define the correct strings. In order to better choose strings, we

performed a large search combined with a papers’ word count solution to identify the

most suitable terms in this context. This is explained in Section 3.1;

e) Acceptance: is the process in which we decide whether to keep or reject an article to

the review. In this article, we have considered only peer reviewed “articles” with

relationship with both topics of IoT and LSCM. We inspected first the titles, summaries

and key-words, before reading the entire manuscript;

f) Classification: is a way to rank the articles. We used the SJR classification - Scimago

Journal Ranking (SCIMAGO, 2007), since it´s a well-known international ranking;

g) Analysis and discussion: are the steps to explore the content of the papers addressing

the research goal. We have focused on identifying the main journals of publications

and their research methodology. After that, we have identified the need to explore the

categories under Case Study papers due to its larger amount of publications.

3. Results

3.1 Preliminary search

Following “item d” of the methodology, we have developed a preliminary search before

defining the complete list of strings. The starting point was a simple string: “Internet of

things”, resulting in 10.288 documents. In this scenario, it was possible to identify that IoT

publications have started in 1992, however the topic has risen its relevance only in the past

five years, as illustrated in Figure 2, growing exponentially.




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Figure 2 – Number of publications from the preliminary search

Source: Authors

Using an option from the WoS platform to extract information from the articles (3,021) and

proceeding papers (2,885), it was possible to download the “title”, “key-words” and “abstract”

from all the 5,906 documents. This information was uploaded to an online word count

website (https://wordcounter.net/), which gives the relevant words (e.g. excluding article,

pronoun, etc.) that repeat the most in the article. It was possible to start drafting a new set of

strings to the complete search list, including the acronym “IoT” and the words “smart” and

“sensors”. However, for a more robust analysis, a confirmation of the strings in previous

published literature would be recommended. In this way, we also filtered from the 5,906

documents, the ones related to a literature review process, searching in the title of the articles

the following key-words: RESEARCH DIRECTIONS (STANKOVIC, 2014); STATE OF

THE ART (AHMED et al., 2016); DEFINITIONS (BAIOCCHI et al., 2016,

DORSEMAINE et al., 2015); REVIEW (RAUN, 2016, SAHA et al., 2016, MIRAZ et al.,

2015, LEE; LEE, 2015, SURESH et al., 2014). No article was found with the keywords

BIBLIOMETRIC, THEORY or LITERATURE. After the review of the word-count and a

detailed analysis of the nine documents, it was possible to develop a new set of strings,

presented in Figure 3.

Figure 3 - Complete list of strings




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Source: Authors

We have decided to use the full written form of the strings (e.g. “Internet of things”, as well as

its acronyms (e.g. “IoT”), given the amount of titles and key-words of articles using only the

short format. It is important to mention that the search with the strings related to “smart” were

not added to the complete search, because its meaning can be applied to several other study

fields, increasing the number of non-related results exponentially.

3.2 Complete search

After the preliminary search and the loop to define the complete list of strings, we went back

to “item c” of the methodology: the primary source database WoS. In this way, the strings

were input altogether. The extraction of data was made on February 6th 2017 and, as expected,

this expanded list of strings brought a lot more documents. Considering all types of

documents, the number reached 72,592 in total in many categories. However, considering the

criteria of “item e” in the methodology (peer reviewed articles only), our database went down

to 22,085 articles.

The same item also considers the focus on content: IoT and LSCM. Since our search was

already by topic of IoT related content, it was missing only the analysis of LSCM in the

content. The platform allows to extract the Title, Year, Abstract, Key words, Authors,

Publication and complete list of citation for each document, allowing us to filter the articles

with at least one of the following words in their titles or summaries: “Logistics” or “Supply

Chain”. In this case, the definition of the words related to LSCM was much simpler, since the

subject in the academia is better defined by the academia (CHRISTOPHER, 2016) The

number of articles dropped immensely, going to 185 articles. To procced with the

methodology approach, the qualification of articles (methodology “item f”) considering the




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SJR metrics was performed. Articles without SJR rank were not considered, decreasing our

pool of articles to 111. After an initial read of the titles of the articles, we decided to take a

step back in the methodology (“item e”), to review if the results were adequate to the strings

around IoT and LSCM. Even with the combination of filters, a lot of articles related to health

and education were still on the list, because of that a new analysis of all the 111 titles and

summaries were performed to review the relationship of the paper to the business content.

After the new review, we were finally able to get to our final list of articles: 39 (Figure 4).

Figure 4 - Qualification analysis of the articles

Source: Authors and SCIMAGO (2007)

The SCIMAGO (2007) quartiles ranks all the journals per their Impact Factor and categorized

by quartiles (Q1 to Q4): Q1 represents the top 25% of the journals with highest Impact Factor,

Q2 is the range of 25% to 50% and so on. With that information, it was also possible to

identify the top Journals publishing articles in the field (i.e. the ones with more than 1

publication) as described in the Table 1. Even considering all the evaluations of the SJR (Q1

to Q4), the Journals with marks Q1 and Q2 were the ones with more publications in this topic,

demonstrating the relevance of the topic in important journals.

Table 1 – Top Journal with publications on IoT and LSCM

Journal

Number of articles

by SJR ranking

Q1 Q2

Journal of Network and Computer Applications (1084-8045) 3

Internet Research (1066-2243) 3

Sensors (1424-8220)

3

Journal of Intelligent Manufacturing (0956-5515) 2

IEEE Transactions on Industrial Informatics (1551-3203) 2

International Journal of Production Economics (0925-5273) 2




8

International Journal of Advanced Manufacturing Technology (0268-3768) 2

Source: Authors

3.2.1 Papers by methodologies or topic

It was possible to find only 3 types of methodologies among all the selected papers: Literature

Review, Survey and Single Case Studies, however most articles (85%) were single case study,

which shows that IoT has many applications in real world solutions, as shown in Figure 5.

Figure 5 – Publications by methodology or topics in the study case

Source: Authors

3.2.2 Topics from the case studies

After an in-depth analysis of the case studies we identified two main types of publications in

the field:

a) Technical papers around IoT platforms (46%): which describes the challenges of

IoT system integration due to its complexity and lack of international standards. There

is no single solution that fits all needs in cooperation between devices, infrastructure

and cloud (VAN DEN ABEELE, F. et al. 2015). From the companies’ perspective, it is

still a challenge to gain scalability, since there are not global standards to make the

several data compatible (LI; ZHU; CHEN, 2013 ZHONG et al., 2016). In addition,

there is a trade-off in the research to miniaturize IoT sensors while increasing storage

capacity (MITTON; SIMPLOT-RYL, 2011) and wireless communications

(TONNEAU; MITTON; VANDAELE, 2015). The benefits of these platforms were

always highlighted by the authors, specially the Radio-frequency identification – RFID,

which has been applied to many business areas in LSCM (NAM; YEOM, 2011),




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substantially improving, for example performance of port operations (SHI; TAO; VOS,

2011) and many other examples (CASTRO; JARA; SKARMETA, 2012).

b) IoT applications (39%): Food supply chain was one of the most studied application

for IoT in LSCM (10%), representing the challenges that global operations have to

transport perishable goods. The following three subcategories had 8% of articles each:

Consumer delivery, which was driven by the demand of a more efficient tracking, with

concerns on trust and reliability (KAFLE; FUKUSHIMA; HARAI, 2016). These issues

are taken very seriously by companies to provide security, privacy and quality of

services (HE; YAN; XU, 2014) due to the risk of systems to be hacked; Real-time data,

which also relates to a good traceability and shorten processing time in logistic centers

due to the large trading volumes and multiple vendors involved in the operations; and

the logistics operations itself, which still contains duplicated processes and information

flow. The next subcategory considers articles around data visualization (3%), and how

the decision-making needs sufficient knowledge and information about the subject and

its environment. The final subcategory was the implementation of smart parking

system (2%), due to a complex vehicular systems demand integrating IoT with the

vehicular data clouds. Table 2 represents the Main topics and subcategories with their

respective sources.

Table 2 – Single case studies subcategories

Tec

hn

ica

l p

ap

ers

Subcategory Authors

Other platforms (VAN DEN ABEELE et al., 2015)

(QIN; WANG; LI, 2016)

(LIN et al., 2015)

(SARRAJ et al., 2014)

(APPEL et al., 2014)

(CHEN; CHEN; HSU, 2014)

(GONG; LIU, 2013)

(LI et al., 2013)




10

(LI; ZHU; CHEN, 2013)

(HUANG; LIANG, 2004)

(RIBAULT; ZACHAREWICZ, 2015)

(TALEVSKI; CHANG; DILLON, 2005)

RFID study (KATAYAMA et al., 2012)

(GAO et al., 2016)

(ZHONG et al., 2016)

(NAM; YEOM, 2011)

(SHI; TAO; VOS, 2011)

(CASTRO; JARA; SKARMETA, 2012)

IoT

ap

pli

cati

on

s

Real-time data

(KONG et al., 2015)

(QIU et al., 2015)

(KANG; PARK; YOUM, 2016)

Food supply chain

(KIDO; NAKAMURA, 2016)

(SHIH; WANG, 2016)

(LUO et al., 2016)

(HAASS et al., 2015)

Consumer delivery (HUI; MIN, 2016)

(HU et al., 2016)

(LIU et al., 2016)

Logistics

operations

(QU et al., 2016)

(GOUDARZI; TABATABAEE MALAZI;

AHMADI, 2016)

(QU; LIU; TAO, 2015)

Data visualization (BI; WANG; DA XU, 2016)

Smart parking (HE; YAN; XU, 2014)

Source: Authors

4. Conclusion

IoT is bringing a revolutionary change in the world, but its benefits seem so far understudied

in the context of Logistics & Supply Chain Management. Our Systematic Literature Review

found very little evidences of studies with that focus (considering the more than 72 thousand

articles around IoT, only 0,5% of the them were in the field of LSCM). The amount of single

case studies and the absence of multiple case studies suggest that this field of research is still

in its early stage development. In particular, we have not identified studies with application of

IoT in Green Supply Chain Management (e.g. Reverse Logistics). In this way, we recommend

future studies exploring other databases beyond the WoS, to confirm the possible gaps on IoT

and LSCM with multiple case-studies, as well as the application on other Supply Chain

operations such as Reverse Logistics.




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