adoption theories

Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.

CA2Africa Inception Workshop, 2-4 March Nairobi

Session 3 Overview of existing modelling approaches

Adoption Decision Theories and

Conceptual models of Innovations Systems

Hycenth Tim NdahJohannes Schuler

Sandra UthesPeter Zander

Tuesday 2nd of March 2010


Content

� Clarification of terms and principles of CA

� Adoption decision theories

� Selected Adoption decision theories

� Conceptual Models of Innovation system

� Innovation systems approach and CA

� Selected conceptual models of innovation systems

� Applicability of some selected theories and conceptu al models in Agricultural studies

� Perspective (PhD work-Schematic presentation)CA2Africa; Theories, Conceptual models of Innovation Systems and challenge of BEFMs in comprehending adoption


Clarification of Terms and meaning of CA� Theory

In English, it is used as a “concept or scheme”. Psychologist say its all about human thought and behaviour while scientist say it’s a tested and testable concept explaining an occurrence

� Adoption Adoption is seen as the first or minimal level of behavioural utilization (Rogers 2003)

� Diffusion is the process by which an innovation is communicated through certain channels over time among the members of a social system (Rogers 2003)

� Innovation Any new knowledge introduced into and utilized in an economic or social process (OECD, 1999) New products and equipment but also new methods and ideas (Hoffmann, 2005)

� Innovation systemdefined as a network of organizations, enterprises, and individuals focused on bringing new products, new processes, and new forms of organisation into economic use, together with the institutions and policies that affect their behavior and performance (The World Bank 2007)

� Agentscomprising individuals and firms as well as public institutions and nonstate actors (constitute the main operating components of the System)

N/B: A good functional Innovation System creats an enabling environment for adoption

Calgeri and Ashburner, 2006

CA


Adoption Decision theories

Categories

� Behavioral Theories

� Cognitive Theories

� Development Theories

� Humanist Theories

� Personality Theories

Adoption Decision Theories in Agriculture


Cognitive Theories

� Action is triggered through the uncomfortable tension which comes from holding two conflicting thoughts in the mind at the same time

� Focus on internal state such as:• motivation• problem solving • decision making• thinking and attention


Behavioural Theories

� Learning based on the idea that all behaviour is acquired through…….

…………… “ conditioning”

� used in therapeutic settings to help clients learn knew skills and behaviours


Why Adoption Theories in Agriculture ?

�Because of focus of economic models on interest and profit max ("Economic men and women“

�Because economic models fail to conceptualize the social dimensions of knowledge, information, communication and rationality (Leeuwis,1993)

�Because of limited ability of economic models to explain decision and to capture complexity of farmers attitudes and behaviour

N/B: Adoption theories therefore try to fill this gaps


Selected “Adoption decision”theories

� Theory of Psychological Field (Kurt Lewin)

� Theory of Behaviour Modification (Albrecht et al 1987)

� Hohenheim diffusion Theory (Hoffmann 2006)

� Diffusion of Innovation Theory (Rogers 2003)

� The Theory of planned Behaviour (Ajzen 1991)


Theory of psychological field (Kurt LEWIN)

b = f (P, Esubj. )

Where;behaviour (b) is a function of the individuals subjectively perceived environment (P,Esubj.)

Subjectively perceived environment

target

barrier

IndividualPerson(farmer)

route

Adapted from Albrecht et al. 1987 after Lewin, In: Hoffmann, 2005


Theory of psychological field (Kurt LEWIN)

� Human behaviour is seen as a result of the interplay of diverse forces that create a set of circumstances through the dynamic interaction of man and his environment (Albrecht et al. 1987 in; Hoffmann, 2005; Ndah, 2008)

� According to the psychological Field theory of Kurt LEWIN, the interaction of situational forces with the perceived environment can be described as a field of forces, a system in tension or a psychological field.

� Human behaviour can be described as follows: A person (P) in his subjectively perceived environment feels something is worth striving for (a target e.g CA). He/she then mobilizes his/her personal powers to achieve this goal (adopt CA)

� When something negative or undesirable occurs, he activates his personal powers in the same way to avoid the negative situation.

� Ways of reaching targets and avoiding negative situations can be blocked or impeded by barriers or inhibiting forces (lack of knowledge, uncertainty about outcome, insufficient capital, cultural practices, lack of opportunities for scaling up of CA innovation etc)


Theory of Behaviour modification (Albrecht et al 1987)

time

Perception of problem

Driving forces

Phase 1

Phase 3

Phase 2

Behaviour at different times

Inhibiting forces

Disturbance of former equilibrium

Shift to new equilibrium

Stages of implementation

Stabilisation of modified behaviour

Solution to problem or relapse

CB=+DF-IFwhere:CB=Change in BehaviourDF=Driving ForcesIF=Inhibiting Forces

Albrecht et al. 1987


Theory of Behaviour modification (Albrecht et al 1987)

• Inhibiting forces-forces negatively influencing beh avioural change (adoption of CA)

e.g lack of subsidies, limited liquidity (for labou r hiring, buying herbicide, seeds of legumes for soil coverage, etc) , lack of machinery, and limited knowledge

• driving forces-forces conducive to positive target (adoption)

e.g. financial assistance, technical advice, traini ng, provision of inputs, financial assistance, linkage with market outlets, etc

• Behaviour (adoption) is thus seen as resulting from the psychological field of inhibiting and driving forces

hence these forces are present in a state of equili brium or dis-equilibrium with varying degrees of tension between them

• Once such forces are identified in the farmers deci sion making process, the chances of diffusion can be estimated and consequences for promotion programs can be concluded (Kriesemer and Grötz 2008).


Diffusion of Innovation Theory (Rogers 2003)

An innovation is :• an idea, • practice, or • object � perceived as new by an individual or other units of adoption

1) Innovators-Venturesome, educated

2) Early adopters-Social leaders, popular, educated

3) Early majority-deliberate, many informal social contacts

4) Late majority- sceptical, 5) Laggards- traditional, lower social economic class

2 3 41

Number of adopters per unit of time

Time

5

Rogers, 2003

“ audience segmentation”


The Diffusion Theory (Hohenheim Concept :Hoffmann 2005)

� Diffusion- “ process by which an innovation is communicated thro ugh certain channels over time among members of a social system ”

(Rogers 2003)

Hoffmann, 2005

1 The innovator as disruptive element

2 The critical phase (end or turning point)

3 Transition to the self-sustaining process

4 Final phase of the wave23 4

1

Number of adopters per unit of time

Time

“ phases of diffusion”


Determinants of adoption (Rogers 2003)

Dependent VariableIndependent variables

Attributes of innovation: relative advantage, compatibility, complexity, Trial

ability, observability.

Innovation decision: Optional, collective, Authority

Communication Channels: mass media or interpersonal

Social system: norms, degree of network connection

Extent of change Agents Promotion efforts

Rate of adoption of innovation (CA)

Adapted from Rogers, 2003


Determinants of adoption (Rogers 2003)

� Perceived attributes

• Comparative advantage -the degree to which an innovation is perceived better than the idea it supersedes.

• Complexity - the degree to which a practice is perceived as relatively difficult to understand and to adopt. negatively related to its rate of adoption

• Trialability -degree to which an innovation (CA) may be experimented at a limited basis.

• Compatibility -degree to which sustainable practice is perceived as consistent with the existing values, past experience and needs of potential adopters.

� Type of innovation decisionproces through which an individual passes from; knowledge to attitude and finally to adopting (indivual or collective, optional or authority)

� Communication Channelsinterpersonal or mass media, originating from specific or diverse sources

� Social system: norms, network interconnectednesssocio-cultural practices and norms that can inhibit or drive adoption

� Efforts of promotion agent past and present efforts made to promote CA (national, international bodies)


Theory of Planned Behaviour (TPB) Ajzen, 1991

Adapted from Ajzen, 1991

Fascilatting & impeding factors

Expectation of others

Likely outcome of behaviour (adop)

e.g Adoption


Theory of planned Behaviour TpB (Ajzen 1988, 1991)

� The theory helps to understand how people’s (adoption decision ) behaviour can be influenced.

� It predicts deliberate behaviour, since behaviour can be deliberate and planned.

� Theory assumes human action to be guided by three kinds of considerations:

� Behavioural Beliefs (beliefs about the likely consequences of the behaviour-adoption)

� Normative Beliefs (beliefs about the normative expectations of others)

� Control Beliefs (beliefs about the presence of factors that may facilitate or impede performance of the behaviour-adoption).

N/B: Ajzen's three considerations are crucial in circumstances such as projects (e.g CA2Affrica) when analysing peoples behaviour or attitude towards a practice (e.g CA)

http://www-unix.oit.umass.edu/~aizen/tpb.html


Conceptual Models of Innovation System

� The interest of an innovation systems approach applied to the understanding of CA development is that it allows to identify

…….which stakeholders are lacking (diagnostic)? or……..may be needed (recommendation)? ……

…… in the CA development process to overcome bottlenecks and constraints and generate the needed knowledge, technologies or institutional arrangements.

� Various conceptual model of local innovation systems can be used as frameworks for analysing the quantity and quality of the flows of information (exchanges of knowledge, training processes) and…..

…......the decision processes (technical adaptations) between the main actors.


Selected Conceptual models of Innovation systems

� Innovation Systems model (The World Bank 2006)

� The Innovation Policy Terrain-a map of issues (OECD 1997)

� Elements of National Innovative Capacity (Speirs et al 2008 based on Porter and Stern 2002)

� A Generic National Innovation System (OECD, 2003)

� A simple innovation network, from Wall et al., 2002, based on Rycroft and Kash, 1994

� Innovation system perspective (Lundvall 1985)expanded model for adoption of conservation practices (Clearfield and Osgood, 1986)


A stylized Innovation System(The World Bank, 2006)

Adapted from : Lynn k. Mytelka, Local Systems of Innovation in a Globalised Economy“ in industriy and Innovation, Vol. 7, 2000, Cited in : the World bank 2006

Sanitory and phytosanitorystandards

Licensing

DNA Genotyping

Increased InternationalInvestment

& Knowledge flows

Global Concentration

Agricultural Policies

Interactions


Relating the stylized Innovation System to the case of CA2Africa

CA Innovation System:

� All CA actors (Farmers, experts, machine developers, Input suppliers, policy makers etc)and….

� their linkages (interactions) involved in the production and use of (CA) knowledge and….

� the rules and mechanisms –institutional and policycontext that shapes the processes of (CA) knowledge

…………….access, sharing and learning.


The Innovation Policy Terrain (IPT)-a map of issues (OECD,1997)

� broader framework conditions (region, district)• legal, economic, financial, and educational setting

• rules and range of opportunities for innovation;

• science and engineering base (accumulated knowledge and the science and technology)

• institutions ( technological training and scientific knowledge)

� transfer factors (region, district)• Human, social and Cultural factors: influenceing the

effectiveness of the linkages, flows of information and skills to firms and learning by them

� innovation dynamo• is the domain most central to business innovation

it covers dynamic factors

• within or immediately external to the firm and very directly impinging on its innovativeness.

OECD, 1997


Elements of National Innovative Capacity (ENIC) mod el (Porter and Stern 2002 as cited in: Speirs et al. 2008)

The Common Innovation Infrastructure (region, distri ct)� set of human, financial, public policies, economy’s level of technological

sophistication, environment within which all innovating enterprises mustoperate.

� Cluster-Specific Conditions (region, district)� defined as a: “….geographic concentration of interconnected companies and

institutions in a particular field.”

– further viewed as four interrelating attributes, each contributing to the innovative capacity of the ‘cluster’.

– the context for firm strategy and rivalry,

– factor or input conditions (human capital, risk capital, research infrastructure and information infrastructure),

– demand conditions (insight gained from sophisticated local demand) related supporting industries (local suppliers, related companies and the presence of these in localised industries or ‘clusters)

� Quality of Linkages (region, district)� relationship between the common infrastructure and a nation’s industrial

clusters.

� described as reciprocal as clusters are said to be able to feed and benefitthe common infrastructure.

� relationship is governed by formal or informal organisations that facilitate the links between the common innovation infrastructure and industrial clusters

Porter and Stern 2002


A Generic National Innovation System (NIC) model (OECD, 2003)

OECD, 2003


A simple innovation network , (from Wall et al., 2002, based on Rycroft and Kash, 1994.

InnovativeFarmers

Input Suppliers

ResearchEquipment Developers

Extension Service

MachineryManu-

facturers

A way to simulate these systems is through multi-agent based modelling or fuzzy-cognitive mapping.


Expanded model for adoption of conservation practices (Clearfield and Osgood, 1986)

�Expanded model potrays a balanced presentation of � socio-psychological, � farm structural, � ecological, � institutional.

�As broad categories of explanatory variable to adoption (CA)

Groups of explantory variables for adopting Conservation practices

Institutional

Ecological

Farm structure

Socio-Psychological

Adapted from Clearfield and Osgood, 1986


Selected applicability of theories, and Conceptual models

� Wauters, E. 2005, Combines TPB (Ajzen 1991) with linear regression techniques to examine the adoption of cover crops, reduced tillage and buffer strips in Belgium

� Kriesemer K.S., Grötz P.A. 2007 combines the theories of Innovation diffusion by Rogers 2003, Behaviour modification by Albrecht et al 1987 and the Hohenhein diffusion concept by Hoffmann 2005a to examine the adoption and diffusion of Small-Scale Aquaculture in Africa with special reference to Malawi

� Ndah H. 2006, uses the behaviour modification Theory along side variables of adoption (Rogers 2003) as a framework to examine the driving and inhibiting forces to Fish Pond Aquaculture in Cameroon

� Sattler, C.; Nagel, U.J., N 2003 uses the attributes of Innovation suggested by Rogers 2003 to examine the factors affecting farmers´ acceptance of conservation measures in north eastern Germany

� Padel, C. 2001 uses the diffusion of Innovation Model (Rogers 1983) in his work; Conversion to organic farming: A Typical Example of the Diffusion of an Innovation?

� Speirs J., Pearson P., Foxon T.,(2008) in the study: Adapting Innovation Systems Indicators to assess Eco-Innovation analysed strands of literature in the four conceptual models

• Innovation Policy Terrain (OECD 1997); • Generic National Innovation system Model ( OECD 2003)• Elements of NIC model (Porter et al. 2002) and • Functions of Innovation sysytem model (Jacobsson & Bergek 2004; Hekkert et al. 2007).

� To develop sets of indicators or guidance for the measurement of eco-innovation


Perspective

Best selected and reviewed Conceptual models, theories, and indicative areas or guidance for capturing systems indicators at linkages, institutions,

and frameconditions levels (review)

Adapting Innovation systems indicators to measure CA adoptive aninnovative capacity with contributions and suggestions- from all

actors in the system

District , Regional, and international actors and institutions ; their linkages, interractions and rules in the CA innovation system. Diagnostic and verifyi ng phase through integrated methodology: selected s tructured, Semi structure qualitative

interviews, focus groups, key informants and Expert interviews1) Reseachers 2) extension workers and rural sciologist 3) Innovative farmers, 4) policy makers 5) input supliers 6) NGOs,

7) farmers groups 8) CA machine manufacturers and developers,

Broad screening and selection of best fit conceptua l models and adoption theories

BEFMs as Computer base technological

Innovation (tool)CA innovation as a

practice

Pre-modellingmodelling and Post

modelling

CA2Africa; Theories, Conceptual models of Innovatio n Systems and challenge of BEFMs in comprehending adoption


Perspective

Best selected and reviewed Conceptual models, theories, and indicative areas or guidance for capturing systems indicators at linkages, institutions,

and frameconditions levels (review)

Adapting Innovation systems indicators to measure CA adoptive aninnovative capacity with contributions and suggestions- from all

actors in the system

District , Regional, and international actors and institutions ; their linkages, interractions and rules in the CA innovation system. Diagnostic and verifyi ng phase through integrated methodology: selected s tructured, Semi structure qualitative

interviews, focus groups, key informants and Expert interviews1) Reseachers 2) extension workers and rural sciologist 3) Innovative farmers, 4) policy makers 5) input supliers 6) NGOs,

7) farmers groups 8) CA machine manufacturers and developers,

Broad screening and selection of best fit conceptua l models and adoption theories

BEFMs as Computer base technological Innovation (tool)Best selected BEFMs,possible integration of adaptedindicators to measure CA

Strenghts and weaknesses of BEFMs and possible contribution ofextensionist, Rural sociologist inimproving the capacity of suchmodels to capture and

conceptualisethe social milieu limitations towardscomprehending adoption of CA

CA innovation as a practiceCA meaning, techniques its variables and attributes to Adoption as an innovation in Practrice (Compartibility Trialability Comparativeadavantage,Observability.

Regional firness to various agroecological zones of Africa underthe various socio economic andand cultural conditions

Pre-modellingmodelling and Post modelling

attempts to capture the socialdimensions of knowledge, information,communication and rationality how this helps in comprehending adoption, further development of the

model, policy recommendation,contribution to DSS

CA2Africa; Theories, Conceptual models of Innovatio n Systems and challenge of BEFMs in comprehending adoption


References

• Rogers, E. M. (2003) Diffusion of innovations, fifth edition. Free Press, New York, U.S.A.

• Hoffmann, V. (2006) Knowledge and Innovation Management, Reader, University of Hohenheim, Stuttgart, Germany.

• Hoffmann, V. (2005) Rural Communication and Extension, Reader, University of Hohenheim, Stuttgart Germany

• Sattler, C.; Uwe Jens, N. (2004) Factors affecting farmers‘ acceptance measures; Leibniz Centre for Agricultural landscape Research (Zalf) e.V., Institute of Socio Economics; Humboldt University of Berlin, Faculty of Agriculture and Horticulture.

• Kriesemer, S. K.; Grötz, A. (2008) The Adoption and Diffusion of Small-Scale Pond-Aquaculture in Africa with special Reference to Malawi

• Ndah, H.T. (2008) Adoption and Diffusion of Fish Pond Aquaculture in Cameroon; An empirical study carried out in the Centre, Southwest and Northwest Provinces of Cameroon

• Hess, S.C. (2007) Customers´ decision Making within Innovation Adoption Process-Understanding Customers´Adoption Behaviour and Managing Adoption Barriers

• Lundvall, B.Å (1985) Product Innovation and User–Producer Interaction. Aalborg University Press

• Leeuwis, C. (1993) Of Computers, myths and modelling; the social construction of diversty, knowledge, information and communication Technologies in Dutch horticulture and agricultural extension

• Spielman, J. (2005) Innovation Systems Perspectives on Developing-Country Agriculture:A Critical Review. ISNAR Discussion Paper 2

• Porter, M.; Stern, S. (2002) The global competitiveness report, World Economic Forum, Geneva, Switzerland (2001), New York,. Oxford University Press: 102-118. Remøe, S. (2005) cited in Jamie Speirs S., Pearson P., Foxon T. (2008) Adapting Innovation Systems Indicators to assess Eco-Innovation

• European Commission (1997) The OSLO MANUAL: The measurement of Scientific and technological activities; Proposed guidelines for collecting and interpreting technological innovation data

• Wauters, E. (2005) Adoption of soil conservation measures in Belgium: applying the theory of planned behaviour

• World Bank (2007) Enhancing Agricultural Innovation: How to go beyond the strengthening of research systems. Washington DC, USA: World bank

• Fischer, A. J.; Arnold, A.J.; Gibbs, M. (1996) Information and the Speed of Innovation Adoption

• http://psychology.wikia.com/wiki/Decision_making Decision_making_models(05.02.09• http://psychology.wikia.com/wiki/Decision_theory(05.02.09)• http://psychology.wikia.com/wiki/Game_theory(05.02.09)• http://www.answers.com/topic/decision-theory(05.02.09)• http://en.wikipedia.org/wiki/Decision_tree#General(05.02.09)• http://changingminds.org/books/changingminds_book.htm (09.02.09)

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