Impact of Consumer Behaviour on Organic Food Consumption in Select Cities in Maharashtra Thesis Submitted to the Padmashree Dr. D. Y. Patil University, Department of Business Management, in partial fulfillment of the requirements for the award of the Degree of DOCTOR OF PHILOSOPHY In BUSINESS MANAGEMENT Submitted by MS. DOEL MUKHERJEE (Enrolment No. DYP-PhD 076100016 ) Research Guide Dr. R. GOPAL DIRECTOR, DEAN & HEAD OF DEPARTMENT PADMASHREE DR. D.Y. PATIL UNIVERSITY, DEPARTMENT OF BUSINESS MANAGEMENT, Sector 4, Plot No. 10, CBD Belapur, Navi Mumbai – 400 614 November 2012
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Impact of Consumer Behaviour on Organic Food Consumption in Select Cities in
Maharashtra
Thesis Submitted to the Padmashree Dr. D. Y. Patil University, Department of Business Management,
in partial fulfillment of the requirements for the award of the Degree of
DOCTOR OF PHILOSOPHY
In
BUSINESS MANAGEMENT
Submitted by
MS. DOEL MUKHERJEE
(Enrolment No. DYP-PhD 076100016)
Research Guide
Dr. R. GOPAL
DIRECTOR, DEAN & HEAD OF DEPARTMENT
PADMASHREE DR. D.Y. PATIL UNIVERSITY,
DEPARTMENT OF BUSINESS MANAGEMENT,
Sector 4, Plot No. 10,
CBD Belapur, Navi Mumbai – 400 614
November 2012
Impact of Consumer Behaviour on Organic
Food Consumption in Select Cities in
Maharashtra
i
DECLARATION
I hereby declare that the thesis entitled ―Impact of Consumer Behaviour on
Organic Food Consumption in Select Cities in Maharashtra‖ submitted for
the Award of Doctor of Philosophy in Business Management at the
Padmashree Dr. D.Y. Patil University Department of Business
Management is my original work and the thesis has not formed the basis
for the award of any degree, associate ship, fellowship or any other similar
titles.
Place: Navi Mumbai.
Date:
Signature of the Signature of the Signature of
the Guide Head of Dept. Student
ii
CERTIFICATE
This is to certify that the thesis entitled ―Impact of Consumer Behaviour on
Organic Food Consumption in Select Cities in Maharashtra‖ submitted by
Ms. Doel Mukherjee is a bonafide research work for the award of the
Doctor of Philosophy in Business Management at the Padmashree Dr. D.
Y. Patil University Department of Business Management in partial fulfilment
of the requirements for the award of the Degree of Doctor of Philosophy in
Business Management and that the thesis has not formed the basis for the
award previously of any degree, diploma, associate ship, fellowship or any
other similar title of any University or Institution. It is also certified that the
thesis represents an independent work on the part of the candidate.
Place:
Date:
Signature of the
Head of the Department Signature of the Guide
iii
ACKNOWLEDGEMENT
I am greatly indebted to Padmashree Dr. D.Y. Patil University, Department
of Business Management which has accepted me for the Doctoral Program
and provided me with an excellent opportunity to carry out the present
research work.
I am grateful to Dr. R. Gopal, my guide, for his continuous encouragement
and patience with me during the course of the study. It would not have
been possible for me to complete the study without his advice and proper
direction.
I am thankful to my parents, husband and sister without whose support this
study would never have fructified; and to the almighty for giving me the
strength to carry on in spite of many hurdles on the way.
I owe my thanks to many other people dear to me who have supported me
in this research all of whose names will be impossible to mention. I would
like to convey my sincere thanks to all of them for their effort and time.
Place:
Date:
Signature of the student
iv
TABLE OF CONTENTS
Chapter No. Title Page
No.
DECLARATION i
CERTIFICATE ii
ACKNOWLEDGEMENT iii
LIST OF TABLES vi
LIST OF FIGURES viii
LIST OF ABBREVIATIONS x
EXECUTIVE SUMMARY xiii
1 INTRODUCTION 1
1.1 The meaning and origin of organic 2
1.2 The Organic Food Market – General
Trends
3
1.3 Consumers’ organic food purchase
behaviour
36
1.4 The future of organic food 37
2 REVIEW OF LITERATURE 40
2.1 International studies on consumers of
Organic food
40
2.2 Studies on consumers of organic food in
India
50
2.3 Gaps in literature 61
3 OBJECTIVES & RESEARCH
METHODOLOGY
62
3.1 Objectives of the study 63
3.2 Hypotheses 64
v
3.3 Research Methodology 65
4 THE ORGANIC FOOD MARKET IN INDIA 71
5 DIFFUSION OF ORGANIC PRODUCTS 112
5.1 Organisations and their role in the spread
of organic food
121
5.2 Barriers to the diffusion of
environmentally friendly products
149
6 THEORETICAL FRAMEWORK 154
6.1 Consumer Behaviour Theories 155
6.2 Factors influencing food choice 174
7 FINDINGS 188
7.1 Profile of the sample 188
7.2 Findings of the survey 189
8 INTERPRETATIONS AND CONCLUSION 193
9 SUGGESTIONS AND
RECOMMENDATIONS
218
10 SCOPE FOR FUTURE RESEARCH 224
Annexure I BIBLIOGRAPHY 226
Annexure II A QUESTIONNAIRE FOR USERS 263
Annexure II B QUESTIONNAIRE FOR NON-USERS 269
Annexure III STATISTICAL TABLES OF SPSS
FINDINGS
271
vi
LIST OF TABLES
Table 1 Sampling Statistics 69
Table 2 Status of India’s organic food industry 76
Table 3 Average farm gate prices in India 83
Table 4 Certification Agencies in India 92
Table 5 Maharashtra- Organic Crop wise
statistics
97
Table 6 APEDA Export Figures 142
Table 7 Commodity Wise export data from
APEDA
143
Table 8 Summary of Hypotheses 192
Table 9 Variables used for Discriminant analysis 198
Table 10 Frequency table - Taste of Organic food 201
Table 11 Cross tabulation of Consumption and
Taste
201
Table 12 Chi Square output Consumption and
Taste
202
Table 13 Cross tabulation of User category by
Income
214
Table 14 Chi Square for User Category by Income 215
vii
Table 15 Cross tabulation of User Category by
Age
216
Table 16 Chi Square values for User category by
Age
216
Table 17 User category by Education table 217
viii
LIST OF FIGURES
TITLE PAGE
NO.
Figure 1 Countries with the largest organic markets 3
Figure 2 Distribution of organic sales by country
2010
4
Figure 3 Countries with the most organic
agricultural land 2010
5
Figure 4 Countries with the highest number of
producers
6
Figure 5 Countries with the highest per capita
consumption
7
Figure 6 Farmland growth vs Retail Sales in the U.S. 9
Figure 7 US Organic food sales 11
Figure 8 Development of Organic Agriculture in
Europe
12
Figure 9 Development of organic market in Europe 13
Figure 10 Product share of the French organic market 20
Figure 11 Distribution of French organic retail market 21
Figure 12 Districts of Maharashtra 94
Figure 13 Districts of Uttarkhand 103
Figure 14 End to End Integrated Projects 111
Figure 15 The India Organic Logo 146
ix
Figure 16 The Theory of Buyer Bahavior Model 159
Figure 17 The Nicosia Model 161
Figure 18 The Andreasen Model 165
Figure 19 The Engel-Blackwell-Miniard Model 168
Figure 20 The Pilgrim Model 175
Figure 21 The Steenkamp Model 176
Figure 22 Component Plot for Nutrition/ Lifestyle
Seekers
206
Figure 23 Component plot for media exposure/
consumption
212
x
LIST OF ABBREVIATIONS
1. AMS – Agricultural Marketing Service (Unites States Department of
Agriculture)
2. APEDA – Agricultural and Processed Food Export Development
Authority (India)
3. CAP – Common Agricultural Policy (Europe)
4. CII – Confederation of Indian Industries
5. COF- Centre for Organic Farming, Uttarakhand, India
6. DITC – Division on International Trade in Goods and Services, and
Commodities (UNCTAD)
7. EAGGF – European Agricultural Guidance and Guarantee Fund
8. EC – European Commission
9. EU: European Union
10. FAO: Food and Agriculture Organization of the United Nations
11. FIBL: Research Institute of Organic Agriculture (Forschungsinstitut
für Biologischen Landbau)
12. FIELD – Foundation for International Environmental Law and
Development (United Kingdom)
13. FVO – Farm verified organic (FVO)
14. GAIN – Global Agriculture Information Network (United States)
15. GMO – Genetically Modified Food
16. GOI – Government of India
17. GTZ – German Organization for Technical Cooperation
18. HACCP – Hazard Analysis and Critical Control Point
xi
19. IAASTD: International Assessment of Agricultural Knowledge,
Science and Technology for Development
20. IAP – IFOAM Accreditation Programme
21. IBS – IFOAM Basic Standards
22. ICAR: Indian Council of Agricultural Research
23. IFAD: International Fund for Agricultural Development
24. IFOAM: International Federation of Organic Agriculture Movements
25. IFPRI : International Food Policy Research Institute
26. IMO – Institute for Market Ecology (Switzerland)
27. IOAS – International Organic Accreditation Service
carriers, government agencies and universities. The program also
administers a program involving financial grants to states for marketing
improvements. In addition, the division assists in the planning and design
of marketing facilities, processes, and methods in cooperation with state
and local governments, universities, farmer groups, and other segments of
the U.S. food industry. This program is intended to enhance the overall
135
effectiveness of the food marketing system, provide better quality products
to the consumer at reasonable cost, improve market access for growers
with farms of small to medium size, and promote regional economic
development.
The Organic Trade Association (OTA) is a membership-based business
association that focuses on the organic business community in North
America.
The Organic Trade Association (OTA), formerly the Organic Foods
Production Association of North America (OFPANA), was established in
1985 in the United States and Canada. Since its inception, the association
has been a key player in shaping both the regulatory and market
environment for organic products.
OTA's mission is to promote ethical consumerism, promoting and
protecting the growth of organic trade to benefit the environment, farmers,
the public and the economy. OTA is a member of The International
Federation of Organic Agricultural Movements (IFOAM) and The
International Working Group on Global Organic Textile Standard.
It also promotes and protects organic trade to benefit the environment,
farmers, the public, and the economy. OTA envisions organic products
becoming a significant part of everyday life, enhancing people's lives and
the environment.
OTA is a leader in advocating and protecting organic standards so that
consumers can have confidence in certified organic production. With input
136
from its diverse membership, OTA continues to develop and refine organic
standards for emerging product areas.
OTA monitors the work of government agencies, takes positions on
legislation that affects organic agriculture and products, and represents the
industry to regulators, elected officials, and international bodies. For this
reason the OTA has been widely criticized for being an agent of big
business interests working to undermine the credibility of the organic
movement. The OTA Rider attached to the Agriculture Appropriations Act,
which the USDA approved, and passed before Congress in 2006, opened
the door for non-organic, non-agricultural, and synthetic additives in food
products bearing the "organic" label. The Organic Consumers Association
(OCA) derided the OTA‘s attack. The OCA stated, ―In the broadest and
most basic sense, the OTA rider takes away the organic community‘s
leading role in setting and monitoring organic standards for processed
organic foods, and instead places this power in the hands of the USDA and
industry‖
OTA is helping in increasing the amount of agricultural land under organic
management for the good of the planet and its inhabitants. A healthy
supply chain is integral to the continued growth of the organic industry and
to consumer choice in the marketplace. OTA works on many fronts to
support the transition to organic farming, processing, and handling. OTA‘s
HowToGoOrganic.com website is a clearinghouse of resources for farmers
and businesses interesting in becoming organic or creating new organic
businesses.
137
Through press releases and events, a media newsletter What‘s News in
Organic, and a consumer web site http://www.organicitsworthit.com/, OTA
shares the benefits of organic with the public and helps expand markets for
organic products. OTA directly promotes organic products at retail via its
cooperative marketing programs. OTA is a primary source for fact-based
information about organic products and processes throughout North
America.
OTA‘s membership directory, The Organic Pages, is a fully searchable
directory with comprehensive indexing and twice monthly updates. It is a
virtual organic marketplace, connecting buyers and sellers of organic
products and services, from farm to retail. OTA also publishes an online
Export Directory for international buyers interested in purchasing U.S.
Organic Products.
OTA is the founder of the ―All Things Organic‖ Conference and Trade
Show. All Things Organi is the largest business-to-business trade show
and conference in North America focusing exclusively on organic products
and organic trade issues.
OTA works with public and private organizations to support scientific
research regarding organic production and processing. Research-based
information on the environmental, health, and nutritional impacts of organic
agriculture and its products is critical for the small but fast-growing organic
industry.
138
European Agricultural Fund for Rural Development (EAFRD)
The EARDF supports rural development, the second pillar of the Common
Agricultural Policy (CAP), which has been introduced progressively since
the 1970‘s and institutionalised in 1997 with Agenda 2000. The EARDF,
along with the EAGF (European Agricultural Guarantee Fund), is one of the
two financial instruments of the Common Agricultural Policy established by
Regulation (EC) No 1290/2005.
The reforms of the CAP of June 2003 and April 2004 focuses on rural
development by introducing a financial instrument and a single programme
in the form of the European Agricultural Fund for Rural Development
(EAFRD). It improves the management and controls of the rural
development policy for the period 2007-2013. This Regulation lays down
the general rules governing Community support for rural development,
financed by the EAFRD. It also defines the aims of rural development and
the framework governing it. The Fund contributes to improving:
The competitiveness of agriculture and forestry
The environment and the countryside
The quality of life and the management of economic activity in rural
areas
The Fund complements national, regional and local actions, which
contribute to Community priorities. The Commission and the Member
States are also to ensure that the Fund is consistent and compatible with
other Community support measures.
139
Implementing the strategic plans is carried out through rural development
programmes containing a package of measures grouped around 4 axes
which include:
1. Improving the competitiveness of the agricultural and forestry sector:
These measures are aimed at promoting knowledge and improving
human potential through vocational training and information actions,
schemes promoting the establishment of young farmers, early
retirement for farmers, the use of advisory services by farmers and
forest holders and the establishment of advisory services, farm relief
and farm management support services. The use of these services
should help assess and improve the performance of their holdings.
2. Improving the quality of production and of products: such as
assistance to farmers in adapting to the demanding rules laid down
in EU legislation, partly offsetting the additional costs or loss of
revenue resulting from these new responsibilities, encouraging
farmers to participate in schemes that promote quality food and that
give consumers assurances of the quality of a product or production
method, providing added value to primary products and boosting
trade opportunities, support producer groups in their information and
promotion activities for products covered by food quality schemes.
The above schemes definitely allow the farmers to expand their horizon to
include organic farming without bearing all the difficulties of the transition
period. Further the axis 2 which deals with improving the environment and
the countryside EAFRD contributes to supporting sustainable development
140
by encouraging farmers and forest holders to employ methods of land use
compatible with the need to preserve the natural environment and
landscape and protect and improve natural resources. The main aspects to
take into account include biodiversity, the management of NATURA 2000
sites, water and soil protection and climate change mitigation. Against this
backdrop, the Regulation provides, in particular, for support for mountain
regions with natural handicaps and other disadvantaged areas (defined by
the Member States on the basis of common objective criteria) and for agri-
environmental or forest-environmental payments, which only cover
commitments that go beyond the corresponding obligatory standards.
Assistance also covers support for non-productive investments linked to
the achievement of agri or forest-environmental commitments or the
achievement of other agri-environmental objectives, as well as measures
aimed at improving forestry resources with an environmental objective
(support for the first afforestation of agricultural land, establishment of
agro-forestry systems or restoring forestry potential and preventing natural
disasters).
The EARDF has been allocated a budget of EUR 96.3 billion for the period
2007-2013, or 20 % of the funds dedicated to the CAP. (European
Commission, 2012)
APEDA – Agricultural and Processed Food Export Development
Authority (India)
The Agricultural and Processed Food Products Export Development
Authority (APEDA) was established by the Government of India under the
Agricultural and Processed Food Products Export Development Authority
141
Act passed by the Parliament in December, 1985. The Act (2 of 1986)
came into effect from 13th February, 1986. The Authority replaced the
Processed Food Export Promotion Council (PFEPC). In accordance with
the Agricultural and Processed Food Products Export Development
Authority Act, 1985, (2 of 1986) the following functions have been assigned
to APEDA:
Development of industries relating to the scheduled products for
export by way of providing financial assistance or otherwise for
undertaking surveys and feasibility studies, participation in enquiry
capital through joint ventures and other reliefs and subsidy
schemes;
Registration of persons as exporters of the scheduled products on
payment of such fees as may be prescribed;
Fixing of standards and specifications for the scheduled products for
the purpose of exports;
Carrying out inspection of meat and meat products in slaughter
houses, processing plants, storage premises, conveyances or other
places where such products are kept or handled for the purpose of
ensuring the quality of such products;
Improving of packaging of the Scheduled products;
Improving of marketing of the Scheduled products outside India;
Promotion of export oriented production and development of the
Scheduled products;
142
Collection of statistics from the owners of factories or
establishments engaged in the production, processing, packaging,
marketing or export of the scheduled products or from such other
persons as may be prescribed on any matter relating to the
scheduled products and publication of the statistics so collected or
of any portions thereof or extracts therefrom;
Training in various aspects of the industries connected with the
scheduled products;
Details of the export of organic food through APEDA is shown below
The Major Importing countries
1) USA
2) GERMANY
3) UNITED KINGDOM
4) JAPAN
5) FRANCE
Total production 3.88 million M.T.
Total quantity exported 69837 M.T
Value of total export USD 157.22 million (Rs. 699 Crores)
Total area under Certification (including wild harvest)
4.43 million hectares
Total area under certified organic cultivation 0.24 million hectares
Share of Exports to total Production 4% approx.
Increase in Export Value over previous year 33% approx.
Table 6 APEDA export figures
Source: APEDA website
APEDA has marked its presence in almost all agro potential states of India
and has been providing services to agri-export community through its head
office, five Regional offices and 13 Virtual offices.
143
Commodity Wise Export Data from APEDA
PRODUCT CATEGORIES EXPORT
VOLUME (MT) % SHARE
Oil Crops (exept Sesame) 17966 25.73
Cotton & Textiles 17363 24.86
Processed Food 8752 12.53
Basmati Rice 5243 7.51
Tea 2928 4.19
Sesame 2409 3.45
Honey 2409 3.45
Rice 1634 2.34
Dry Fruits 1472 2.11
Cereals 1348 1.93
Spices-Condiments 1174 1.68
Medicinal & Herbal Plants/Products 627 0.90
Coffee 320 0.46
Vegetables 167 0.24
Aromatic Oil 39 0.06
Table 7 Commodity Wise Export Data from APEDA
Source: APEDA website
The top ten destinations for APEDA products are Bangladesh, U.A.E,
Saudi Arabia, Malaysia, U.S.A., Kuwait, U.K. , Indonesia, Yemen, Arab
Republic, Cote D Ivoire (Ivory Coast)
The National Centre of Organic Farming (NCOF) is under the
Department of Agriculture and Cooperation, Ministry of Agriculture,
Government of India. It is the apex body in India for record keeping for
the government. The specific activities of NCOF/RCOFs (Regional
Centre of Organic Farming) are
144
To collaborate all stakeholders of organic farming in the country and
abroad and act as main information centre on various aspects of
organic farming.
Documentation of indigenous knowledge and practices, compilation
of integrated organic packages and publication of technical literature
in all the languages.
Preparation and publication of uniform and authentic training
literature and training course contents.
Publication of Biofertilizers and Organic Farming Newsletters for
national and international updates on quarterly and half yearly basis.
To provide necessary technical assistance to production units for
quality production of various organic inputs such as biofertilizers,
composts etc.
To serve as data collection centre for biofertilizers and organic
fertilizer production, biofertilizer and organic fertilizers production
units and their production capacities and for details on total area
under certification and various crops being grown under organic
management.
To maintain National and Regional culture collection bank of
biofertilizer organisms for supply to production units.
Development, procurement and efficacy evaluation of biofertilizer
strains and mother cultures.
To act as nodal quality control laboratory for analysis of biofertilizers
and organic fertilizers as per the requirement of Fertilizer Control
Order.
145
To provide all sorts of technical assistance to implementing
agencies for successful implementation of project targets
NPOP – National Programme for Organic Production
India is now understood to be a potential supplier of organic products to the
international market. Presently India is exporting these products to Europe,
US and Japan.
To provide a well focused and well directed development of organic
agriculture and quality products, the Ministry of Commerce, Government of
India has launched the National Programme for Organic Production in the
year 2000 under the Foreign Trade and Development Act. The standards
and procedures have been formulated in harmony with international
standards such as Codex and IFOAM.
The National Programme for Organic Production proposes to provide an
institutional mechanism for the implementation of National Standards for
Organic Production, through a National Accreditation Policy and
Programme. The aims of the National Programme for organic production,
include the following:
(a) To provide the means of evaluation of certification programmes for
organic agriculture and products as per the approved criteria.
(b) To accredit certification programmes
(c) To facilitate certification of organic products in conformity to the
National Standards for Organic Products.
146
(d) To encourage the development of organic farming and organic
processing
The NPOP programme will be developed and implemented by the
Government of India through its Ministry of Commerce and Industry as the
apex body. The Ministry will constitute a National Steering Committee for
National Programme for Organic Production, whose members will be
drawn from Ministry of Commerce and Industry, Ministry of Agriculture,
Agricultural and Processed Food Products Export Development Authority
(APEDA), Coffee Board, Spices Board and Tea Board and other
government and private organisations associated with the organic
movement. To advise the National Steering Committee on relevant issues
pertaining to National Standards and Accreditation, sub-committees will be
appointed.
Figure 15 The India Organic Logo
Source: NPOP Website
The National Steering Committee for National Programme for Organic
Production will formulate a National Accreditation Policy and Programme
and draw up National Standards for Organic Products, which will include
147
standards for organic production and processes as well as the regulations
for use of the National Organic Certification Mark.
Recognizing that India's rain fed agriculture — that accounts for 60 percent
of planted area (Government of India's Economic Survey) — can
potentially make good use of organic methods, the Government has
recently taken a number of steps to promote and regulate organic
production and marketing. The Ministry of Agriculture has set up a special
working committee for organics and the Ministry of Commerce set up a
National Steering Committee that prescribed The National Standards of
Organic Produce (NSOP).
Institute of Integrated Rural Development (IIRD)
IIRD is one of the many NGO‘s in India that is helping with various
activities related to organic agriculture. It was founded by Dr Alexander
Daniel in 1987 with encouragement, support, and advice of Dr A. A
Deshpande, Padmakar Kelkale, Dr. Ulhas Gawli, Raosaheb Shinde, Mr.
Anil Shine and Dr Rajnikant Arole. IIRD started with a mission of economic
and social justice along with sustainable environment for rural communities
of Marathwada region of Maharstra and beyond. From 1987 to 1991 it
functioned from a small hut in the village Kanchan Nagar in Aurangabad.
From 1992 it started training programs in carpentry, the Jeevan Aadhar
and Adopt a Granny Programme (Elderly Care), a Nutrition Programme
was started in 6 villages. IIRD also started training the Vikas Sevika in
various sectors like health, nutrition, child welfare, social and civil
education. In 1993 the total number of villages that IIRD was working in
148
went up to 36. Environment Education Programme and sustainable
Organic Agriculture education was imparted to the people. IIRD purchased
land in Babulgaon where it started organic agriculture workshops. ITI
(technical training) courses were conducted in Bidkin. IIRD became a
member of IFOAM in this year. In 1996 the IIRD office became the Asia
coordinating office for IFOAM.
In 1998 IIRD established the National Voluntary Standards for Organic
Agriculture. In 1999- IIRD received the SARD award. The concept of
organic bazaar started and two Organic Bazaars were started in
Aurangabad city. From then on IIRD‘s growth was phenomenal. In 2000
seed banks were established at all the six Community Learning Centres.
The Organic Agriculture Manual was prepared and farmers started
receiving Community based Certification in organic production. In 2001 the
1st National Conference on Organic Agriculture was organized at IIRD‘s
campus in Bidkin. Peter Proctor of NewZeland came to IIRD and trained
the women farmers on organic agriculture. In 2002- IIRD started working in
other States of India like Kerala, Aandhra Pradesh, West Bengal,
Karnataka and Tamil Nadu. It established the Group certification of organic
produce. In 2003 IIRD started working in other districts of Marathwada
region. These districts include Beed, Hingoli, Parbhani and Jalna. In 2004
an organic retail outlet, Organic Link opened in Aurangabad city. IIRD also
started attending and organising several International Training
Programmes in Sri Lanka, Vietnam, Phillipines, Lahose, etc. IIRD started
47 Farmers Clubs started in Marathwada region. In 2010 the concept of
revolving fund initiated for rural enterprises like drip irrigation, vermin-
149
compost units, CPP, etc. IIRD received the Krishi Bhushan Award from the
Government of Maharastra. IIRD has also started an IGNOU certificate
courses on Water Management and Organic Agriculture.
5.2 Barriers to the diffusion of environmentally friendly products
The rapid diffusion of green technologies will require openness to trade
and investment and promotion of adequate local conditions – including
human capital and access to financing – in order to improve the capacity to
absorb innovation. (OECD, WorldBank, & UN, 2012)
In a number of advanced economies there are important trade barriers on
biofuels.
1. The United States recently let lapse a tax credit and specific-rate
import tariff that previously protected domestic producers of fuel ethanol.
2. Russia, as part of its accession to the WTO (approved at the end of
2011), will start to reduce import tariffs on all industrial goods, including
environmental goods.
3. Encouraging job creation and promoting equity: Labour market
institutions that provide sufficient labour market flexibility with adequate
protection of workers‗ rights, financial, training and job search support for
job seekers will help reduce the costs of transition to green growth. Some
relevant are:
4. The G20 Mutual Assessment Process indicates that Canada, China,
Germany, the European Union and Russia have recently reduced barriers
to labour mobility or are planning to do so.
150
5. France has eased job protection in 2008 and improved incentives
for low-wage workers to take up work with a more gradual withdrawal of
benefits and efforts to improve the efficiency of public job intermediation
services.
6. High-quality education and training will foster countries‗ability to
develop and adopt greener technologies, while enhancing the adaptability
of the workforce to structural change. All G20 countries are engaged in
efforts to improve their education systems. Some countries have put in
place training and other active labour market programmes with a specific
green angle, including for example:
7. The Australian Green Skills Agreement seeks to build the capacity
of the vocational education and training sector to deliver the skills for
sustainability required in the workplace and to enable individuals,
businesses and communities to adjust to and prosper in a sustainable, low-
carbon economy.
8. As part of Brazil's policies for biofuel production and use, the
―RenovAção‖ programme will retrain manual cane cutters displaced by
the total mechanisation of the sugarcane harvest in the state of São Paolo,
expected to be completed by 2014. More than 7000 workers in six
sugarcane regions in the state will be retrained and re-qualified for jobs
either in the sugarcane sector or in other sectors such as reforestation,
construction and tourism.
9. India‗s Natural Rural Employment Guarantee Act provides at least
one hundred days of guaranteed wage employment to every household
whose adult members volunteer to do unskilled manual work in the areas
151
that help limit drought, soil erosion or contribute to sustainable
development in other ways. Turkey has a temporary employment
programme for the unemployed focussing on landscaping and planting
work.
10. Mexico runs a temporary employment programme that includes jobs
sponsored by the National Forestry Commission, involving soil
conservation, wildlife conservation and sustainable use, prevention of
forest fires, integral waste management, ecotourism, reforestation and
water conservation.
11. Working for Water is a government programme in South Africa that
employs and trains jobless individuals to clear alien invasive plants. These
are heavy water users in South Africa‗s arid climate, so their removal frees
water resources for both human needs and the environment.
12. Under agreements signed between the Ministry of the Environment
and the Ministry of National Education the ―15 million seedling for 15
million students‖ campaign has been organised as part of large-scale
afforestation programmes in all Turkish provinces.
13. Argentina seeks to promote job creation in the primary sector
through financial and technical help for afforestation projects organised by
rural communities.
14. The United States, through its Green Jobs Grants, provides funding
for a competitive grants programme for research, worker training and
placement, and labour exchange in the energy efficiency and renewable
energy sectors. These grant programmes have played an important role in
connecting with other Federal agencies‗ green training and job creation
152
programmes. The Green Jobs for Youth programme provides education
and training for at-risk youth. The Environmental Protection Agency also
funds training grants in the environmental field.
15. Social policies are needed to help the poor shoulder the costs of –
and benefit from – green growth policies. Improved public transportation
can help further reduce emissions, while at the same time providing an
affordable alternative to private transportation, where costs may rise as a
result of higher fuel taxes and subsidy withdrawal,. India, starting in
Ahmenabad, and Mexico, starting in Mexico City, have put in place very
successful Bus Rapid Transit Systems, that have induced many
passengers to switch from private vehicles or minibuses, thus reducing
travel time and emissions.
16. A number of countries including Australia, Brazil, India and Mexico
have increased social transfers to compensate poor and sometimes
middle-class citizens for the effects of pricing environmental externalities or
removing environmentally harmful subsidies. The United States
government helps fund energy efficiency improvements in low-income
households. The United Kingdom imposes energy efficiency improvement
targets on energy suppliers that they need to fulfil specifically by supporting
lower-income households to achieve these savings. The Brazilian
government has created a programme, Bolsa Verde, of income transfer for
families in extreme poverty that contribute to environment conservation in
protected or rural settlement areas.
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17. National green growth strategies will need to consider country-
specific local economic, social and environmental conditions but could
usefully incorporate:
The organisations listed above are trying to bring sustainable choices to
the people in general. Their size and wealth put them in front but there are
many small organisations throughout the world that are promoting organic
in remote places.
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CHAPTER 6
THEORETICAL FRAMEWORK
A researcher may use inductive reasoning or deductive reasoning when
making the framework of a research. Inductive reasoning starts with details
of an experience and moves to a general picture while deductive reasoning
is a process of starting with the general picture or the theory, and moving
to a specific direction for practice and research. Deductive reasoning uses
two or more related concepts, that when combined, enable suggestion of
relationships between the concepts (Feldman 1998).
Inductive and deductive reasoning are basic to frameworks for research.
The theoretical framework is a collection of related concepts that guides a
research; determines what things are needed to measure and/or what
statistical relationship to look for. It is used in deductive, theory-testing
studies.
Theory may be looked at as a set of interrelated concepts, which provides
a systematic view of a phenomenon. It guides practice and research;
practice enables testing of theory and generates questions for research;
research contributes to theory-building, and for selecting guidelines for
practice. So, what is learned through practice, theory and research
interweaves to create the knowledge fabric of a discipline. (Liehr & Smith,
2012)
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6.1 Consumer Behaviour Theories
Models of buying behaviour have been developed since the 1940s to
satisfy the objectives of describing and predicting consumer behaviour, so
that a fuller understanding of customers is achieved. Earlier it was studied
by modelling consumer behaviour as a search for utility, thus an
assumption is made that consumers behave rationally, always choosing
the alternative that will lead to the highest utility (Eagly and Chaiken 1993).
The modelling of consumer behaviour using the subjective expected utility
model of decision-making has become increasingly complex as
researchers strive to improve the ability to predict consumer behaviour.
The next part will look at behavioural models and try to illustrate some of
the well known multivariable consumer behaviour models that have been
developed. These models also form the basis for the future models that
have been developed for food purchase behaviour.
The Theory of Buyer Behavior - Howard-Sheth
The Howard Sheth theory of buyer behaviour (Howard & Sheth, 1969) is a
sophisticated integration of the various social, psychological and marketing
influences into a coherent sequence of information processing on
consumer buying behaviour. It aims not only to explain consumer
behaviour in terms of cognitive functioning but to provide an empirically
testable depiction of such behaviour and its outcomes. Utilizing the
learning theory thoroughly and systematically, John Howard came out with
the first truly integrative model of buyer behaviour. He was the first to
introduce the difference between problem solving behaviour, limited
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problem solving and routinised response behaviour. The model is
essentially an attempt to explain brand choice behaviour over time and
therefore especially pertinent to the field. Focussing on repeat buying, the
model relies on four major components - stimulus inputs, hypothetical
constructs, response outputs and exogenous variables. The theory relies
on three levels of decision making, which are:
1. Extensive problem solving – refers to the early stages of decision
making in which the buyer has little information about brands and has not
yet developed well defined and structured criteria by which to choose
among products.
2. Limited problem solving - this is a more advance stage, choice criteria
are well defined but the buyer is still undecided about which set of brands
will best serve him. Thus the consumer still experiences uncertainty about
which brand is best.
3. Routinised response behaviour - buyers have well defined choice criteria
and also have strong predispositions toward the brand. Little confusion
exists in the consumer's mind and he is ready to purchase a particular
brand with little evaluation of alternatives.
The model then borrows from learning concepts to explain brand choice
behaviour over time as learning takes place and the buyer moves from
exclusive to routinized problem solving behaviour. Here the four major
components get involved.
The Input Variables
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The input variables consist of informational cues about the attributes of a
product or brand (i.e. quality, price, distinctiveness, service and
availability). This informational cues may be significative if they influence
the consumer directly through the brand's attributes or symbolic if they
derive from the same factors as they are portrayed in the mass media and
by salespeople, influencing the consumer in a indirect way. These two
sources are commercial, in that they represent the efforts of the firm to
build and project these values in the product. A third set of informational
cues may come from the buyer's social environment, including the family,
reference groups and social class - which are influences that are
internalized by the consumer before they can affect the decision process.
Hypothetical Constructs
Hypothetical constructs have been classified in two groups - perceptual
constructs and learning constructs. The first deals with the way the
individual perceives and responds to the information from the input
variables, accounting for stimulus ambiguity and perceptual bias. The
second deals with the stages from buyer motives to satisfaction in a buying
situation. The purchase intention is an outcome of the interplay of buyer
motives, choice criteria, brand comprehension, resultant brand attitude and
the confidence associated with the purchase decision. The motives are
general or specific goals impelling to action, impinging upon the buyer
intention are also the attitudes about the existing brand alternatives in the
buyer's evoked set, which result in an arrangement of an order of
preference regarding brands. Brand comprehension and the degree of
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confidence that the buyer has about it, choice criteria and buying intentions
converge through the intention to buy.
As a feedback component of learning, the model includes another learning
construct- satisfaction which refers to the post purchase evaluation and
resultant reinforcing of brand comprehension, attitudes etc. (shown by
broken lines in the figure).
Output Variables
The five output variables are the buyer's observable responses to stimulus
inputs. They are arranged in order from Attention to Actual Purchase. The
purchase is the actual, overt act of buying and is the sequential result of
the attention (buyers total response to information intake), the brand
comprehension, brand attitude (referring to the evaluation of satisfying
potential of the brand) and the buyer intention (a verbal statement made in
the light of the above externalising factors that the preferred brand will be
bought the next time the buying is necessitated.
Exogenous Variables
The model also includes exogenous variables which are importance of
purchase, time pressure, financial status, personality traits, Social and
organisational setting, Social class and culture which are taken as
constant. These influence all or some of the constructs explained above
and through them, the output.
Most scholars agree that the study of consumer behaviour was advanced
and given an impetus by the Howard-Sheth Model. The major advantage
and strength of the theory lies in the precision with which a large number of
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variables have been linked in the working relationships to cover most
aspects of the purchase decision and the effective utilization of contribution
from the behavioural sciences.
Figure 16 A simplified Description of the Theory of Buyer Bahaviour
Source: Bennet and Kassarjian, Consumer Behaviour, 1996
The weakness stems from the fact that, there being substantial
measurement error, the theory cannot be realistically tested. The
distinction between the exogenous and endogenous variables is not clear
cut. And some of these variables do not lend themselves easily to
measurement and others defy precise definition.
In spite of the limitations, the model has given a frame of reference for
studying the buying decision process over time. This is possible because of
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its comprehensive coverage of almost all aspects of the purchase decision
and operational explanation of the underlying stimuli and responses.
The Nicosia model of Consumer Decision Process (1966):
The model proposed by Francesco Nicosia in 1966, was one of the first
models of consumer behaviour to explain the complex decision process
that consumers engage in during purchase of new products. Instead of
following a traditional approach where the focus lay on the act of purchase,
Nicosia tried to explain the dynamics involved in decision making.
Presenting his model as a flow-chart, he illustrated the decision making
steps that the consumers adopts before buying goods or services; decision
fraiming was presented as a series of decisions, which follow one another.
The various components of the model are seen as interacting with each
other, with none being essentially dependent or independent; they are all
connected through direct loops as well as feedback loops. Thus, the model
describes a flow of influences where each component acts as an input to
the next. The consumer decision process focuses on the relationship
between the marketing organization and its consumers; the marketing
organization through its marketing program affects its customers; the
customers through their response to the marketer‘s action, affects the
subsequent decisions of the marketer; the cycle continues.
The various components that are further distinguished into main fields and
subfields of the model are marketer's communication affecting consumer‘s
attitude, consumer's search and evaluation, purchase action, consumption
experience and feedback. The first field ranges from the marketer (source
of message) to the consumer (attitude); the second from the search for to
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the evaluation of means/end(s) relation(s) which forms the pre-action field;
the third field relates to the act of purchase; and the fourth to feedback.
Figure 17 The Nicosia Model
Source: Loudon, D.L. and Della Bitta A.J
The output from one field acts as the input for the next. These are
explained as follows:
1. Marketer's communication affecting consumers‘ attitude: This comprises
Field 1 (―from the source of a message to the consumers‘ attitude‖). The
consumer is exposed to the firm‘s attributes through the marketing
communication; this marketing communication could take place
impersonally via mass media (TV, newspaper, websites, etc) as well as
personally. The information could relate to the firm attributes as well as the
product, price and distribution. This message relating to the firm‘s attributes
affects the consumers‘ perception, predisposition and attitude toward the
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firm and its offering. Of course, the impact on perception and attitude is
also dependent upon the consumer‘s personal characteristics, values,
experiences, culture, social influences etc. Thus, the marketer‘s
communication affects the consumers‘ attitude.
2. Consumer's search and evaluation: After an attitude is formed, the
consumer moves to Field 2 of the model, i.e. the consumer‘s search for
and evaluation of means/end(s) relation(s) which forms the pre-action field.
The consumer searches for information about the product category and the
varying alternatives, and thereafter evaluates the various brands on criteria
like attributes, benefits, features etc. These criteria could be based on his
learning and past experiences as well as the marketer's inputs. This step
creates a motive in the mind of the consumer to purchase the product.
3. Purchase action: The motivated state leads to Field 3 of the modelwhich
is the decision making on the part of the consumer and the act of
purchase. The consumer finally gets into action and buys the product from
a chosen retailer.
4. Consumption experience and feedback: The purchase action leads a
consumer to Field 4 of the model which is consumption experience and
feedback. After purchasing the product, and the resultant consumption, the
consumer may have two kinds of experiences. A positive experience in
terms of customer satisfaction may reinforce his predisposition with the
product/brand and make him loyal towards it. A negative experience on the
other hand, implying consumer dissatisfaction would affect his attitude
negatively, lower down evaluations about the product/brand and even
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block his future purchases. This Filed provides feedback to the marketer,
who can modify its mix accordingly.
In the first field, the marketer communicates with the customer and
promotes an unfamiliar product to him; depending upon the existing
predispositions and his evaluation, the consumer develops an attitude. In
the second field, the consumer searches for information and evaluates it
based on his attitudes; thereafter, he develops a motivation to act. In the
third field, he makes and purchase and in the fourth field, he would provide
feedback and also memorize his experience and learning for future use.
Thus, the firm communicates with consumers through its marketing
messages and the consumers react through an act of purchase. Both the
firm and the consumer influence each other.
An Assessment of the Model:
Nicosia‘s model is an integrative model that tries to integrate the body of
knowledge that existed at the time of its formulation in the area of
consumer behaviour. It was a pioneering attempt to focus on the conscious
decision-making behaviour of consumers, where the act of purchase was
only one stage in the entire ongoing decision process of consumers. The
flowcharting approach proposed by Nicosia, simplifies and systemizes the
variables that affect consumer decision making. It contributes to the step
by step "funnel approach" which views consumers‘ movement from general
product knowledge toward specific brand knowledge and from a passive
position to an active state which is motivated toward a particular brand.
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However, the model suffers from limitations in the sense that the model
proposes assumptions, boundaries and constraints that need not be
realistic. It has been argued that attitude, motivation and experience may
not occur in the same sequence. Variables in the model have not been
clearly defined. Factors internal to the consumer have not been defined
and dealt with completely. The mathematical testing of the model and its
validity are questionable.
In the paper Attitudes and Customer Behavior: A Decision Model, Alan
Andreason (1966) proposed one of the earliest models of consumer
behaviour. The model recognizes the importance of information in the
consumer decision-making process. It also emphasizes the importance of
consumer attitudes although it fails to consider attitudes in relation to
repeat purchase behaviour. (The model is shown on the next page)
The Engel – Kollat- Blackwell Model
This model talks of consumer behaviour as a decision making process in
the form of five step (activities) which occur over a period of time. Apart
from these basic core steps, the model also includes a number of other
related variables grouped into five categories.
Step 1: Problem Recognition: The consumer will recognize a difference
between his or her actual state and what the ideal state should be. This
may occur on account of an external stimulus.
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Figure 18 Andreasen Model
Source:"Attitudes and Customer Behavior: A Decision Model," in Lee E. Preston, New Research in
Marketing (Berkeley, CA: The Institute of Business and Economic Research, 1966), 1-16. Reprinted in Harold Kassarjian and Thomas Robertson, Consumer Behavior (Scott, Foresman and Company, 1969)
166
Step 2: Information Search: Initially the information available with the
consumer may be consistent to the beliefs and attitudes held by him or her.
While being involved in an information seeking or search stage, the
consumer will try to gather more information from various sources. These
sources could be sales persons, personal or friends or neighbours or mass
communication media. The information processing takes place in various
stages.
The individual gets exposure of the stimuli which may catch his or her
attention, be received and stored or retained in memory. This method of
information processing is selective in nature and the consumer will accept
the information which is conclusive to what is perceived by them.
Step 3: Alternative Evaluation: The individual will now evaluate the
alternative brands. The methods used for evaluating the various products
will be dependent on the consumers underlying goals, motives and
personality. The consumer also has certain (predetermined) beliefs about
the various brands in terms of the characteristics associated with the
different brands. Based on these beliefs the consumer will respond either
positively or negatively towards a particular brand.
Step 4: Choice: The consumer‘s choice will depend on his or her intention
and attitude. The choice will also depend upon normative compliance (like
getting influenced by other people like family members, friends etc.,) or by
anticipated circumstances (the person‘s choice of the product can also be
dependent on the sensitivity of the individual to handle unanticipated
circumstances like funds diverted for another urgent cause etc.)
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Step 5: Outcome: The outcome may be either positive or negative. If the
end result is positive, the outcome will also be positive. Conversely, if
there is dissonance, that is, a feeling of doubt experienced by the
consumer, about the choice made by him or her the outcome will not be
positive. Now the consumer will search for more information to support his
or her choice.
The EBM model has taken into consideration a large number of variables
which influences the consumer. The model has also emphasized on the
conscious decision making process adopted by a consumer. The model is
easy to understand and is flexible, that is, it recognizes that a consumer
may not go through all the steps always. This is because in case of repeat
purchases the consumer may bypass some of the steps.
One limitation of this model is the inclusion of environmental variables and
general motivating influences but not specifying the effect of these on the
buyer behaviour.
Engel, Blackwell and Miniard (EBM) Model
This model is a development of the original Engel, Kollat and Blackwell
model first introduced in 1968. It shares certain things with the Howard-
Sheth model. Both have similar scope and have the same level of
complexity. Primarily the core of the EBM model is a decision process,
which is augmented with inputs from information processing and other
influencing factors also.
The model has distinctive four sections, namely: Input, Information
Processing, Decision Process and Variables influencing decision process.
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Information Input
Information from marketing and non marketing sources are fed into the
information processing section of the model. The model also suggests
additional information to be collected as a part of an external search
especially when not enough information is available from memory or when
post-purchase dissonance occurs.
Figure 19 The Engel-Blackwell-Miniard Model
Source: Engel et al. (1995)
As the authors argue, the model encompasses all types of need satisfying
behaviour, including a wide range of influencing factors and different types
of problem-solving processes. (Engel, Blackwell and Miniard 1995).
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This model is the most suited for food choice behaviour. This is justified
because, among the more comprehensive models (the Howard-Sheth
model, the Nicosia model, and the Andreasen model), the EBM model
seems to be simultaneously the more parsimonious and the one that can
be applied with fewer problems to different decision situations and product
categories.
Attitude Models
Regarding the mechanisms leading from problem-perception or attitudes to
behaviour, one can distinguish between different approaches. From an
educational perspective, one approach focuses upon the role of pedagogy
in acquiring information and knowledge, and in the development of
personal involvement with particular issues. Some social psychologists
focus on intention as the factor that best predicts behaviour (Fishbein and
Ajzen 1975; Ajzen and Fishbein 1980). Ajzen and Fishbein have identified
attitudes as one of the key factors, which affect consumers purchasing
behaviour. Their model incorporates beliefs, attitudes and behavioural
intention, and by using specific equations they aim to reveal the manner in
which these are related to each other. Ajzen (1985) has later emphasised
the role of perceived behavioural control, i.e. how easy or difficult the
accomplishment of a given behaviour is perceived to be. The Fishbein and
Ajzen model has been widely used in studies of food choice and
purchasing behaviour (Shepherd and Stockley 1985, Shepherd and
Farleigh 1986).
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Three behavioural models are discussed; beginning with the simplest
model of attitude such as Fishbein‘s (1967) expectancy-value model then
moving to the slightly more complex Azjen and Fishbein (1980) model of
behavioural intention, and ending with Azjen‘s (1991) theory of planned
behaviour.
Expectancy-Value Model (1967)
A commonly used subjective utility model of the relationship between
attitudes and behaviour is the expectancy-value model. The expectancy-
value model defines the attitude toward an attitude object as the sum of
expectancy-value products related to the attributes of the attitude object
(Fishbein, 1967). The expectancy-value products are the result of the
expectation that the attitude object possesses specific attributes and the
value that the attitude holder places on those specific attributes (Eagly &
Chaiken, 1993).
Attitude = Σ (Expectancy × Value)
For example, a person‘s attitude toward a food item may depend on the
attributes of nutrition and taste. If the individual believes that the food
possesses nutrition and they value nutrition highly, the product of this
expectancy-value for nutrition can be summed with their expectancy-value
for taste to determine the individual‘s attitude toward the apparel item.
Theory of Reasoned Action / The behavioural intentions model
In the theory of reasoned action, Fishbein and Ajzen (1975) expanded the
expectancy-value model and related attitudes to behaviour by suggesting
that attitudes toward an attitude object, in this case a behaviour, will predict
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an individual‘s intention to engage in a particular behaviour. Besides
attitudes toward the behaviour, the subjective (social) norm, an evaluation
of the attitudes of socially important other individuals, is another variable
included in the model. The theory of reasoned action is also sometimes
called the behavioural intentions model. As the name implies, the theory of
reasoned action is based on a cognitive perspective and suggests that the
cause of behaviour is the decision (intention) to act in a particular way. The
important difference between behaviour and behavioural intention is that,
despite intentions, specific behaviours may not be possible in a given
context (Fishbein & Ajzen, 1975). People may lack the skills, resources or
opportunities to translate their behavioural intentions into actual
behaviours. The difference between behaviour and behavioural intention is
that behaviours can only be predicted from attitudes that are volitional,
under the control of the individual. This focus on behavioural intention also
means that, according to the theory of reasoned action, attitudes do not
predict habitual behaviours. Habitual behaviours are defined as behaviours
performed repeatedly without thought. Taking into account all of these
limitations about the ability of behavioural intentions to predict behaviours,
the theory of reasoned action can be written:
B ≈ BI = wAAB + wSNSN
In this algebraic representation, B is behaviour, BI is behavioural intention,
AB is the attitude toward the behaviour, SN is the subjective norm, and wA
and wSN are weights of the relative importance of the indicated terms.
Intention to engage in a behaviour is a function of the individual‘s
evaluation of the personal beliefs about the behaviour as well as the belief
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of important others about the individual engaging in the behaviour (Eagly
and Chaiken 1993).
The expectancy-value model
Attitude toward a behaviour can be further described in the expectancy-
value model as the sum of behavioural beliefs, the evaluation of
consequences of the behaviour, along with the perceived likelihood of
those consequences. Thus symbolically:
AB = Σi =1 n biei
where bi is the belief that performing the behaviour will lead to some
consequence i, ei is the evaluation of the consequence i and n is the
number of salient consequences (Eagly & Chaiken, 1993). For example, a
behavioural belief such as ―my purchasing an organic food is (unlikely to
likely) to result in a fair price for the organic producers‖ can be combined
with ―I believe that a fair price for organic cotton producers is (unimportant
to important).‖ Studies that measure attitude using the theory of reasoned
action will often measure attitude in two ways, one using a semantic
differential scale (e.g. eating organic food is… (good/bad) or (foolish/wise)),
and the other as described previously. The two measures of attitude can
then be correlated to check reliability while retaining the detail provided
with the expectancy-value formulation. Attitude has been measured in
various manners by a number of studies related to environmental
consumer behaviour (Bamberg & Schmidt, 2003).
Sparks and Shepherd (1992) in their study of self-identity and ‗green
consumerism‘ measured attitude using three items. The first item used a
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traditional semantic differential scale as suggested by Azjen and Fishbein
(1980). The other two items were simple ratings such as ―In general, my
attitude toward eating organic vegetables is…extremely negative to
extremely positive‖ (Sparks & Shepherd, 1992). These items were
correlated with the sum of behavioural beliefs and outcome evaluations.
They then used these items, rather than the summed behavioural beliefs
and outcome evaluations, to predict (β) behavioural intention to consume
organic vegetables in the next week.
Kaiser and Gutscher (2003) also used just the attitude statements without
the summed behavioural beliefs and outcome evaluations. Twelve items
related to six behaviours (e.g. recycling paper) were rated using 2 bipolar
scales (good/bad, appropriate/inappropriate) and were summed to create a
single measure of attitude. This measure of attitude predicted behavioural
intention, which in turn predicted self reported general environmental
behaviour.
Kalafatis et al. (1999) measured both attitude and ―the antecedents‖ to
attitude of behavioural beliefs and outcome evaluations. They do not list
the items used to measure either attitude or behavioural beliefs and
outcome evaluations. In the results of their structural equation modelling
that included both attitude and the summed antecedents, the behavioural
beliefs and outcome evaluations predicted attitude well, while attitude did
not predict behavioural intention well. The authors suggest that other
variables, such as the personal norm, that were not included, might
improve the model fit.
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Finally, Bamberg and Schmidt (2003) also used a modification of the Azjen
and Fishbein (1980) method of assessing attitude in their study of campus
car use. First, four items related to behavioural beliefs (e.g., ―When I use
the car for university routes next time, this will be quick, flexible, etc‖ were
assessed on a bipolar scale from likely to unlikely. There were no items to
assess outcome evaluation, items that measure how important speed or
flexibility was to the respondents. Two bipolar semantic differential scales
measured general attitude toward car use for the next university trip.
Attitude measured in this fashion predicted intention to use a car for the
next university trip and this intention also predicted the actual car use.
6.2 Factors influencing food choice
Food comes in infinite variety, and food choices are a major component of
all purchase decisions made by consumers. However, in spite of the
research that has been conducted, there is no singular commonly accepted
model for explaining consumer behaviour and food evaluation.
As happens with most of the general models, traditionally, the food models
take a cognitive approach to consumer behaviour, where the decision-
making process and the information processing of marketing stimuli are
central to explain consumer behaviour. One of the earliest and most
influential models was proposed by Pilgrim (Pilgrim, 1957).
In his model, food consumption is dependent on perception. Pilgrim
discussed food acceptance rather than food consumption. He
acknowledged that the operational definition of food acceptance is food
consumption. He described Food perception as a function of three factors:
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1) physiological effects of the food, 2) perception of sensory attributes, and
3) influences from the environment. Pilgrim hypothesized that these
determinants will interact in influencing food consumption, but he did not
explore these interrelations. The model is depicted below:
Figure 20 The Pilgrim Model (1956) Source: The Components of Food Acceptance and Their Measurement
The model also incorporates the time factor, with external influences being
either recent or long established, and with some physiological influences
being relatively stable for an individual, while other influences will vary over
short periods with ingestion of foods (e.g., hunger). Pilgrim's model served
as point of departure for many subsequent models of determinants of food
consumption behaviour.
A more recent and one of the most pervasive models concerning consumer
behaviour towards food is the model proposed by Steenkamp. This model
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also distinguishes between the consumers‘ decision-making process with
respect to foods, and the factors influencing this decision process. In the
decision process, ‗borrowed‘ from the EBM model, four stages are
identified: need recognition, search for information, evaluation of
alternatives, and choice. The model is shown below:
Figure 21 The Steenkamp Model (1987)
Source: Agricultural Marketing and Consumer Behavior in a Changing World, JEB Steenkamp
Three groups of factors influencing the decision process are recognized:
properties of the food, factors related to the consumer, and environmental
factors. According to the author, this grouping of factors is based on one of
the earliest and most influential models of factors affecting the behaviour of
food consumers, the Pilgrim model from 1957.
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Comparing the Steenkamp model with the EBM model, the most noticeable
difference is the lack of an explicit treatment of the information processing
perspective. In the Steenkamp model, the marketing stimuli are spread
across the three groups of factors and are considered to influence
consumer behaviour in the same way as culture or the socio-demographic
characteristics of the individual. However, even Steenkamp (1997)
acknowledges that the boundaries between the three groups of influencing
factors are fuzzy and that mutual influences may occur. In the Steenkamp
model a special emphasis is given to the food product, as one of the major
influences on food choice. The food product affects the decision process
mainly through physiological effects and sensory perception. This focus is
probably related to the fact that, in general, food products are commodities,
sold unbranded or unlabelled and with poor or inexistent communication
around them. Consequently, the models and the research dealing with
consumer choice and behaviour relating to food are, mostly, concerned
with the influence of physical and sensory properties of the products and of
price. In summary, it can be said that the Steenkamp model is a simpler
version of the EBM model, which emphasises aspects that are particular to
food products.
Verbeke argued (Verbeke, 2000) that while there is recognition of external
influences such as product availability and economic factors, most food
choice models focus on the interaction between the individual and the food
product. The decision process is facilitated by information processing
mechanisms and conditioned by psychological, social, cultural, and social
influences that, usually, are afforded a peripheral role.
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Environmental concern
Variables such as environmental concern are often measured or
conceptualized as part of larger models of behaviour, theories that suggest
why or when a behaviour occurs. As discussed earlier, a theory of
decision- making popular in both psychology and economics, the
subjective expected utility model of decision-making assumes that an
individual is motivated to choose the alternative (behaviour or object) that
affords the highest overall utility (value).
Cognitive and Economic approaches (Torjusen, Sangstad, Jensen, &
Kjærnes, 2001) respect to environmental issues, includes numerous
studies in which the underlying premise is that if consumers are given
enough information about environmental problems, their acquired
awareness will lead to the adoption of environmentally friendly behaviour.
Organic food has been studied not only in association with environmental
concerns external to the individual consumer, but also within the framework
of ‗risk perception‘, including food safety concerns as well as concerns with
the environmental impacts of food. According to Henson and Northen
(2000:97), much of the literature on consumer perceptions of risks
associated with food has focussed on the attitudes and beliefs underlying
consumer concerns, the factors that make some risks more ―acceptable‖
than others, as well as trust in different sources of information. Slovic
(1987, 2000) has characterised risk perception by means of a series of
polar concepts, including such dimensions as the extent to which risks are
perceived to be ‗voluntary vs. involuntary‘, ‗controllable vs. non-
controllable‘, ‗natural chemicals vs. manmade chemicals‘, etc. Consumer
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perceptions of risk are often investigated along these dimensions. Other
examples of approaches based on psychological theory aim to better
understand key determinants of perceived food safety risks, or to develop
‗mental models‘ of how consumers reach their assessments of risk
associated with pesticide exposure versus other categories of food hazard.
Another typical approach within the consumer behaviour and marketing
literature is the use of the ‗perceived quality risk framework‘3 (Henson and
Northen 2000).
Willingness to pay
Many studies have been designed to measure consumer ‗willingness to
pay‘, most often motivated by the aim of estimating the market potential for
organic foods at premium prices. This task has frequently been combined
with that of distinguishing market segments. In these studies, ‗willingness
to pay‘ is employed as a measure of the relationship between declared
values and the price one is willing to pay for products associated with those
values. Demand, which is the technical term in economics, is a focal point.
However, several factors that can influence demand/‖willingness to pay‖
are often left out of account. These include: the type of products in
question, the relative quality of products at issue, the volume of the
particular product consumed, the social contexts in which the product is
used (weekday/weekend etc.), the social context in which shopping takes
place (Miller 1998), as well as the economic resources of the buyer.
(Examples of studies of organic food, in which ‗willingness to pay‘ has been
in focus, are the Danish studies undertaken by Grünert and Kristensen
(1992) and Hansen and Sorensen (1993). These studies examined the
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priority accorded to environmental concerns in competition with other
consumer considerations, and how the willingness to search and pay for
products from environmentally sound production varied between different
consumer segments
The social psychological focus on ‗risk‘ and the economic focus on
‗willingness to pay‘ should be seen as complementary approaches. In most
cases they share basic assumptions about the character of consumption,
understood as constituting unit acts of (more or less rational) individual
decision-makers, based on underlying values, attitudes and beliefs, as well
as on informational input.
Some important perspectives in social scientific consumer
research
Understanding the consumption of food from social scientific perspectives
implies taking account of the social and cultural contexts in which people
think about, buy, prepare, eat and relationships from social, cultural,
institutional and political perspectives (Mennell, Murcott and van Otterloo
1992). This may concern questions of politics and economy, as related for
example to the distribution of food - including kinds of shopping outlets. It
may also concern questions of culture and tradition, in which food is seen
as one form of symbolic communication, as a tasty source of pleasure or
as a dimension of care in providing for the needs of families.
Food is a meeting point of numerous symbolic codes: personal, familial,
cultural, biological, industrial and environmental, as well as ethical
dimensions of social justice (James 1993). It follows that organic food can
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also be understood in relation to such codes. Some studies are of an
ethnographic character (Lien, 1997). A common feature of these
approaches is a focus upon the meanings we connect with material
products (Campbell, 1987) (Douglas, 1975). This does not imply that the
utilitarian values of products in use are overlooked, but rather an
acknowledgement that there is something more than practical or
instrumental values related to these products (Lien 1995; Holm and
Kildevang 1996).
Sociological and anthropological studies of food and food choices have
pointed out – among other issues – that consumers tend to conceive eating
as a moral matter (Stein and Nemeroff 1995, Germov and Williams 1996).
Food purchase, cooking and eating are activities deeply embedded in the
normative structures and routines of everyday life. Food is not only a form
of meaningful communication; it is also a commodity that consumers pay
for, as well as being a necessity of life. Buying food therefore is an
everyday activity, which constitutes a connection between two different
spheres: the market and family life , a duality, which should also be
reflected in studies of food (Gronow and Warde 2001; Warde 2002).
What emerges from these very diverse social scientific approaches is that
the consumption of organic food can be many-sided and complex. A
common theme is that in order to understand the ways in which people
experience organic food, how they evaluate such key concepts as ‗safety‘
and ‗quality‘, and the extent to which organic foods are chosen in
preference to conventional variants, an approach is needed that takes
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account of the contexts of social action and the manner in which everyday
activities are embedded in interpersonal relationships and institutional
patterns.
Differences in the priority accorded to various quality attributes of food may
reflect differences between the roles of social actors in the food system. In
a Norwegian study of quality conceptions related to the purchase of
vegetables, Lien and Doving (1996) found substantial differences between
consumers, wholesalers, retailers and farmers with regard to their
conceptions of ―good quality‖. Consumers and farmers had a common
focus on quality aspects that are not immediately apparent in the store.
These included the nutritional value of products, their taste and the extent
to which they were produced in an environmentally sound manner,
whereas wholesalers and retailers focussed more on aspects of the
products‘ appearance, such as their size, colour and form Several studies
undertaken during the 90‘s and have addressed the way in which
consumers evaluate food. Many studies document a tendency to evaluate
the quality of products in terms of the extent to which they are perceived as
being ―natural‖ or ―artificial‖ (Wandel and Bugge 1994). Results from a
regional survey in Southern Norway, indicate the need to supplement this
focus on product attributes. It was found that consumer considerations
related to the choice of food include a range of issues related to the
product itself as well as issues related to the food system as such
(Torjusen, Sangstad, Jensen, & Kjærnes, 2001). It is important to note how
broad the range of consumer interests may be, which can be discussed as
consumer conceptions of aspects of ‗quality‘, just as it is important to keep
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in mind that different concerns may be relevant to consumers in specific
contexts.
Organic food as a strategy to deal with worries about the safety and
quality of food: According to the sociologists Ulrich Beck (1992), modern
society is characterised by a higher level of reflection and risk
consciousness among lay people than in former times. Beck argues that
we have moved from ‗industrial society‘ to ‗risk society‘, the latter being
characterised by an increased recognition of the potentially negative
effects of scientific and technological developments. People feel aware of
risks confronting them, which are neither limited in time (future generations
may be affected) nor space (they reach beyond the local community). Food
might be seen as offering a special opportunity to re-link with both the
natural and cultural environment. Consumers‘ interest in information about
the origin of the food, and it‘s further biography along the food chain (food
additives, degree of processing, distance travelled etc) can be interpreted
as their way of finding alternatives to the modern, industrialised food
system.
Concern, uncertainty, worries and mistrust are important issues in
contemporary discussions about food consumption. For example, a Danish
qualitative study found that the choosing of food was associated with
feelings of insecurity, confusion and mistrust in the products, as well as
guilt about the lack of consistency between wishes/intentions on the one
hand and actual choices made on the other (Holm and Kildevang 1996).
Similar conclusions are also drawn in Norwegian studies of consumer trust
and organic food (Torjusen, Lieblein, Wandel, & Francis, 2001). These
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studies suggest that buying organic food can be one of several possible
strategies for dealing with worries about the safety and quality of food, and
they also suggest that consumer concern about the safety and quality of
food is widespread. Those themes which are identified as common
concerns regarding food quality among Danish consumers, are largely the
same as those identified as motives for buying organic food.
Consumers‘ concern about food quality appears to be connected to both
food production and food processing. Concerns about long-term
consequences for health and for the environment are also commonly
mentioned when consumers talk about food. Holm (1999) concludes that,
for some consumers, this concern about modern industrial food production
leads to explicit criticism, while for the majority it presents itself in the more
latent form of mistrust and insecurity. The implications of this for research
are that in the case of latent forms of mistrust and insecurity, consumer
concerns may be far from clearly articulated.
Methodologically speaking, it can be therefore a challenging task to obtain
data that can document the character of these concerns. Kjærnes (2006)
argues for the adoption of a sociological approach to understanding
consumer trust and risk perceptions. Her observation is that distrust has
been traditionally regarded (by market analysts and economists) as
constituting a kind of ―failure‖ (Kjærnes 2012). It has been conceived as a
problem to be fixed, repaired or restored, not as a potentially constructive
force, having creative value or as representing an important input from
consumers.
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Against this point of view, Kjærnes argues that consumer distrust is a
valuable communication from consumers, which could be used in very
constructive ways. In the context of the Organic HACCP project – looking
at the possibilities for defining consumer generated critical control points
for the improvement of organic food production – paying attention to
consumer distrust in food and the food system could be expected to give
us vitally relevant information.
Ethical Attributes
The issue of ethical attributes is a well-known one in the apparel field.
Unethical production methods, including child labour, employee abuse, or
imprisonment, have galvanized consumer sentiment and raised discussion
of the use of labelling for ethical production to allow consumers to place
economic pressure on offending corporations. Labelling for fair trade with
the third world has also created an opportunity for consumers to consider
ethical attributes in a wide variety of products, from crafts to food such as
coffee.
Environmental Behaviour, Environmental Concern
Environmental concern is one of the most commonly studied variables
related to environmental consumer behaviour. It can be defined most
simply as the possession of a concern for the ecosphere itself or over the
degradation of the ecosphere created by human beings. Dunlap and Jones
(2002), researchers in the field of environmental sociology define it as
―Environmental concern refers to the degree to which people are aware of
problems regarding the environment and support efforts to solve them
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and/or indicate a willingness to contribute personally to their solution‖.
Basically, environmental concern is an attitude toward the environment.
Attitudes can be described or measured at various levels of specificity,
ranging from very specific ―It would be satisfying to purchase this recycled
toilet paper at this exact moment in time‖ to the very general ―I desire to
live in a world of pleasure.‖
Concern for the environment can be measured at the most general (least
specific) levels, where it resembles an ideology or worldview. Attitudes or
beliefs about attitude objects that are part of a larger cognitive structure
reflect an ideology or worldview (Eagly & Chaiken, 1993). When Dunlap
and Van Liere (1978) developed a measure of environmental concern, they
called it the New Environmental Paradigm and characterized concern for
the environment as a new way of thinking about nature and the role of
humans in nature. This new paradigm views the environment as
increasingly endangered by the impacts of human behaviour. The authors
were contrasting this new environmental paradigm with the dominant social
paradigm, a worldview where people act out of concern for their personal
benefit rather than concern for the environment.
Environmental concern can also be described in terms of deeply held
values. Values are concepts or beliefs organized into stable motivational
constructs that relate to fairly abstract goals (peace on earth or inner
harmony). One value orientation that has been related to environmental
concern is that of universalism, an orientation that includes values such as
social justice, equality, a world at peace, and unity with nature (Schwartz,
187
1992. Stern, Dietz, Abel, Gaugano, and Kalof (1999) labelled this same
group of values as altruistic (behaviour motivated by these altruistic values)
in their study of support for the environmental movement.
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CHAPTER 7
FINDINGS
The research clearly shows that consumer behaviour towards food is
changing. Earlier consumption of food was mainly based on price whereas
there is an emerging category of consumers who are willing to pay for
better quality and nutritious food. These consumers are well educated and
well to do. They would be the ―innovators‖ and ―early adopters‖ in the
organic food / high value food category.
7.1 Profile of the sample
Consumers of organic food in India are different from the general
population because they are people who are initiating change. The study
used the responses of 400 users and 100 non-users. Since the focus of
study was on the users of organic food the number of users were higher
than those of non users. The questionnaire was administered only to
respondents over the age of 18. The age distribution of the users was
highest in the 18-30 category which is 44% (146 respondents) while 37%
belonged to the age group of 31-40 and 19% belonged to the above 40
category. This reduced percentage with progressing age of users would
conform to the findings of other researches that the younger age group is
more responsive in terms of using organic food. There were 58% male and
42% female respondents of whom 90% held graduation or higher degrees.
Majority (66%) were married and 60% had household income in excess of
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50,000 per month. In the Indian context this would depict a very small
section of the population.
The non users are more equally divided in age as 43% fall in the 18- 30
category and 42% fall in the 31-40 category. The non users were
predominantly male (70%) and 92% who have graduated college. This
balances out the group of users who are also very well educated. But only
55% of the non users have a monthly income of above Rs. 50000 per
month. (Annex III)
The users of organic food respond to recommendations from doctors and
therefore they will probably we convinced if proper authorities could
confirm the higher nutritious value of organic food. The respondents do not
confirm taste being a major reason for the purchase of organic food and
many of them have a disciplined dietary habit.
7.2 Findings of the survey
The survey indicated that organic food users are less in number. The
barriers to usage such as price and availability are high.
Price premiums have a negative effect on purchase of organic food. Only
16.8% of the respondents say they are willing to pay a higher price; 65%
have said they may discontinue purchasing because of price. Even
charging a premium for nutrition is ―strongly agreed‖ by 28% of the
respondents. Tables with the data can be found in Appendix III.
Consumers who have been recommended by physicians or dieticians
seem to be interested to consume organic. The weightage given to organic
food seems to increase due to the credibility of the source.
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The emergence of the fact that there is no distinction between users and
non users in the level of awareness towards organic food is surprising. But
it must be remembered that the non-users in the sample were a highly
educated group. Users would like to have more information on organic
food. While researches in Europe found that there is a correlation between
environmental consciousness and organic food users, this study shows
very little correlation among the variables. Indians seem to be more
conscious about nutritional value in food than issues that pertain to
farmers, biodiversity, certification, chemicals used or even taste.
Summary of Hypothesis
Hypothesis Test used Finding
H01 There is no association
between doctor‘s
recommendation and organic
food consuming habit
Logistic
Regression
Analysis
Null hypothesis
rejected
H02 Awareness towards organic
food is not equally distributed
amongst the
users and non-users of
organic food
Discriminant
Analysis
Null hypothesis
rejected
H03 Consumption of organic food
is not independent of its taste
Chi Square Test Null hypothesis
is rejected
H04 Consumption of organic food
is not a matter of status
Factor Analysis Null hypothesis
rejected
H05 There is no significant
variation on the expenditure
of organic food for regular
users
F test Null hypothesis
accepted
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Hypothesis Test used Finding
H06 Exposure to media is not
significantly associated with
consumption of organic food
Factor Analysis Null hypothesis
rejected
H07A Income does not have a
significant association with
the consumers of organic
food
Chi Square Test Null hypothesis
rejected
H07B Age does not have a
significant association with
the consumers of organic
food
Chi Square Test Null hypothesis
Accepted
H07C Education does not have a
significant association with
the consumers of organic
food
Chi Square Test Null hypothesis
Rejected
Table 8 Summary of hypotheses
Organic farming is primarily knowledge intensive whereas conventional
farming is more chemical intensive. Accordingly, it is difficult to establish a
one approach since conditions will vary in different zones. Organic projects
require that time be built into the process for farmers to test and learn new
technology and methods. Knowledgeable extension service is critical.
Local know-how, especially from experienced farmers and knowledgeable
elders, can smooth the transition and reduce risks. It is also important to
provide farmers good access to sources of knowledge about the
application of organic methods to their crops and agro-ecological
conditions. Nevertheless, holistic methods don't often provide a quick fix
and require a longer-term commitment. Therefore, government and local
institutions such as NGOs need to be committed to supporting a multi-year
process. Such a commitment might require: acquisition of organic
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production technology and training, especially for extension service agents;
preparation for certification and initially covering its costs; and very limited
subsidies to cover possible reduced income during the transition period.
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CHAPTER 8
INTERPRETATIONS AND CONCLUSION
The interpretation of each hypothesis is presented one at a time. Most of
the data in the study consists of Likert scale items. As Likert item data are
discrete instead of continuous values, have tied numbers, restricted range
and do not possess a normal probability distribution the t-test was not used
for analysis.
The chi-square statistic is designed for use in a multinomial experiment,
where the outcomes are counts that fall into categories. The chi-square
statistic determines whether observed counts in cells are different from
expected counts. Since the chi-square statistic assumes a discrete
distribution rather than a normal distribution, the results will be statistically
valid and can be used as scientific proof. The Chi Square test of
independence statistic has been used in two of the hypotheses.
Logistic and Discriminant analysis is used with the first two hypotheses
respectively. Logistic regression is intended for the modelling of
dichotomous categorical outcomes. Since the outcome is dichotomous,
predicting unit change has little or no meaning. As an alternative to
modeling the value of the outcome, logistic regression focuses instead
upon the relative probability (odds) of obtaining a given result category. So
here we try to find the odds that doctor‘s recommendation will result in
organic food consumption.
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8.1 Hypothesis 1
The hypothesis that is being tested is:
H01: There is no association between doctor’s recommendation and
organic food consuming habit.
H11: There is an association between doctor‘s recommendation and
organic food consuming habit.
Binary logistic regression has been used to test this hypothesis. The
objective is to estimate the odds (likelihood ratio) of the respondent being
an organic food consumer due to Doctor‘s Recommendation. We also find
the independent contribution of the predictor variables to variations in the
dependent variable (Doctor‘s recommendation) in the form of an OLS
equation. The predictor variables are as follows:
1. The belief in the nutrition value of organic food
2. Having a healthy food habit
3. Taste and
4. Media influence
Out of the 400 respondents 95 were consuming organic food due to a
physician‘s recommendation. They have been labeled Recommended and
have been coded 1. The rest of the respondents (305) who consume
organic food for other reasons have been labeled as a not recommended
and have been coded 2. All these respondents have been asked to rate
the variables belief in nutritional value, healthy dietary habit, taste and
media influence on 5 point Likert scale.
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An Ordinary Least Squares regression on the data has been formed. The
estimated equation is:
P = 1.248+ 0.331 (belief in nutritional value) – 0.032 (taste) – 0.427
(healthy food habit) + 0.096 (media influence)
Logit equation:
(Where P= probability of consuming organic food on Doctor‘s
Recommendation)
The ―variables not in the equation‖ table shows that all 4 Independent
Variables are significant and if included would add to the predictive power
of the model.
The Wald statistic and associated probabilities provide an index of the
significance of each predictor in the equation. The significance value for a
variable (healthy diet) is less than .05 so we reject the null hypothesis as
the variable does make a significant contribution. Using only the constant
the model predicts 76.3%. This increases to 77.3% with the inclusion of the
independent variables. Thus we can say that there is an association
between doctor‘s recommendation and organic food consuming habit and
we may conclude that the null hypothesis is rejected.
The Cox and Snell R square and Nagelkerke R square measures indicates
a regional fit of the model to the data. Here we can see that about 1.4%
change in the dependent variable is explained by the model. The
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significance of the estimated coefficient is based on Walds statistics. We
note that only healthy diet and nutritional value are significant in explaining
Doctor‘s recommendation.
8.2 Hypothesis 2
The hypothesis that is being tested is:
H02: Awareness towards organic food is not equally distributed
amongst the users and non-users of organic food
H12 Awareness towards organic food is equally distributed amongst the
users and non-users of organic food
The null hypothesis that in the population, the means of all discriminate
functions in all groups are equally distributed can be statistically tested in
SPSS. We will be testing if awareness is equally distributed amongst the
users and non users of organic food. 500 respondents were undertaken to
determine the correlates of consumption of organic food based on the
respondent‘s awareness towards organic food. The predictor variables
were the following:
1. I am well aware of organic food
2. Organic food is more nutritious than ordinary food
3. I have been purchasing organic food frequently
4. Organic food is costlier than conventional food
5. I frequently consume organic food
6. I often visit organic food websites
7. I buy organic food because I want to be environmentally
conscious
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8. I often speak to others about the benefits of organic food
Users and non-users were asked to put forward their views on the
statements on a 5 point Likert scale. Discriminant analysis was conducted
where the dependant variable was taken as the respondent‘s awareness or
unawareness towards organic food.
This categorical dependent variable has been divided into two groups. The
grouping variable was awareness where we have taken 1= aware and 2=
unaware.
Respondents who reported a strongly agree on the independent variables
have been classified as aware and the others have been classified as
unaware. (Table shows results of SPSS data sheet)
The assumption that the covariance matrices of the dependent variables
are the same across groups was tested by using Box's M tests. In the case
at hand the p value of 0.237 (which is greater than 0.05) suggests that the
hypothesis of equal covariance matrices cannot be rejected. So we have
not violated the assumption. (Table 7)
Variables in the Analysis
Step Tolerance F to Remove Wilks' Lambda
1 I frequently eat organic food 1.000 11.839
2 I frequently eat organic food .893 6.446 .981
I have been purchasing
organic food frequently .893 4.266 .977
Table 9 Discriminant analysis variables
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The findings that emerged showed that frequency of purchase and
frequency of consuming organic food are the most effective variables in the
group to show significant discrimination among competitive advantages
groups.
The result of the above two group‘s discriminate analysis is shown in the
data table (Annex III). The results were obtained by examining the group
means and standard deviations. It appears that the two groups were more
widely separated in terms of frequency of organic food consumption than
any other variable. There appears to be more separation on the importance
attached to the other influencer.
The Wilks Lamda statistic varies between 0 and 1. A large value near 1
indicates that the group means do not seem to be different. Small values
near 0 indicate that group means do seem to be different. In testing for
significance in the study noted that Wilks associated with the function is
0.96 which transforms to Chi-square of 15.92 with 2 degrees of freedom.
This is significance beyond the 0.05 level. This shows that the two group
means (aware and unaware) do not seem to be different. Awareness about
organic food is therefore equally distributed among the users and non-
users of organic food.
The variable ―I frequently consume organic food‖ significantly differentiates
who are from which group. The Eigen value associated with function is
0.033 and it accounts for 100% of the variance. The canonical correlation
associated with function is 0.178. The square of association is equal to
0.031 indicating that it results only in 3.1 % of the variance in the
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dependant variable. Thus we can conclude that the distribution of
awareness between the users and non users of organic food is not
significantly different. Thus the null hypothesis is rejected indicating
significant discrimination.
There seems to be no significant difference in the awareness between the
users and non users of organic food. Discussion during the survey as well
as the data on media usage shows that there is a desire among users for
more information on organic food. Therefore information requires to be
diffused so that it may satiate the people and help in effective dispersion
through opinion leaders. Lack of information and demand supply inequality
has been a major reason for the lack of information diffusion, availability
and therefore usage. It may also be deducted that higher awareness may
not change the group membership of individuals. So we need to further
research to find what variable along with information is required for the
adoption of organic food.
8.3 Hypothesis 3
The hypothesis that is being tested is:
H03: Consumption of organic food is not independent of its taste
H13 Consumption of organic food is independent of its taste
A chi square (χ2) statistic is used to investigate whether distributions of
categorical variables differ from one another. The data for taste has been
taken from Question number 1.3 which is the statement ―Organic food is
tastier than ordinary food‖. The responses of the 400 respondents were as
follows:
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Likes /Dislikes the taste of organic food
Frequency Percent Valid Percent
Cumulative Percent
Valid Likes 245 61.3 61.3 61.3
Dislikes 67 16.8 16.8 78.0
Undecided 88 22.0 22.0 100.0
Total 400 100.0 100.0
Table 10 Frequency table - Taste of Organic food
Those respondents who have ticked 1or 2 (strongly agreed and agreed) in
the five point Likert scale have been considered to like the taste of organic
food those who have ticked 4 and 5 in the scale have been considered to
dislike the taste of organic food. The ones who have ticked 3 (undecided)
have not been considered for this analysis. There were 88 respondents
with 3 as their response.
Frequency of consumption * Like / Dislike OF Cross tabulation
Like/ Dislike OF
Total
Likes taste of
OF
Dislikes
taste of OF
Frequency
of
consumpti
on
Irregular buyer Count 86 29 115
% of Total 27.6% 9.3% 36.9%
Regular buyer Count 159 38 197
% of Total 51.0% 12.2% 63.1%
Total Count 245 67 312
% of Total 78.5% 21.5% 100.0%
Table 11 Cross tabulation of Consumption and Taste
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The table above gives the classification of regular and irregular buyers by
their liking / disliking of the taste of organic food.
The result of the chi square test is given below in table 12. High vales for
the Pearson Chi Square test statistic indicate the likelihood that the two
variables are not independent. Thus a value of 1.513 which is close to 1
indicates that the two variables are independent. The large p value in the
result indicates that the observed values do not differ significantly from the
expected values.
Value
Degree of
freedom
Significance
(2- sided)
Pearson Chi-Square 1.513a 1 .219
Continuity Correctionb 1.182 1 .277
Likelihood Ratio 1.491 1 .222
Linear-by-Linear Association 1.508 1 .219
N of Valid Cases 312
Table 12 Chi Square output
Thus the variables consumption and taste are independent of each
other. The null hypothesis H03 is rejected and the alternate hypothesis
―Consumption of organic food is independent of its taste‖ is accepted.
Accordingly the taste of the food should not affect the sales of the product.
There is a lot of conviction among the users of organic food that the taste
of the product is better than the food that is grown with fertilizers and
pesticides by green revolution methods. This was so strong that the
researcher was tempted to believe that it could be a strong selling point for
the product.
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8.4 Hypothesis 4
The hypothesis that is being tested is:
H04 Consumption of organic food is not a matter of status
H14 Consumption of organic food is a matter of status
This hypothesis has been analysed using factor analysis. This analytical
process is based on a correlation between the variables. Each statement
has been considered a variable for analysis. For factor analysis to be
appropriate, the variables must correlate. If the correlation between all the
variables is low, factor analysis may not be appropriate. Variables that are
highly correlated with each other would also highly correlate with the same
factors or factors. (Malhotra & Dash, 2011)
Bartletts‘s test of sphericity is used to test the null hypothesis that the
variables are uncorrelated in the population which is based on Chi-square
transformation of the determinant of the correlation matrix. A large value of
the Bartltts‘s test will favour the rejection of the null hypothesis.
The Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy compares
the magnitudes of the observed correlation coefficient to the magnitude of
the partial correlation coefficient. Lower values of the KMO indicate that
factor analysis may not be appropriate; a value greater than 0.5 is
desirable.
In this case the null hypothesis, that the population correlation matrix is an
identity matrix, is rejected by Bartlett‘s test of sphericity and it is significant
at the 0.05 level. The value of the KMO for this data is 0.8 which is greater
than 0.05. The communality for each variable is unity.
203
The Eigenvalues are in decreasing order of magnitude as we go from
factor 1 to the end. The Eigenvalue for a factor indicates that total variance
attributed to that factor. (Table attached in appendix III)
Two segments of consumers were seen to form. Attitudinal statements
depicting status / lifestyle, safety and healthy lifestyle were administered to
the users of organic food, who expressed their preferences on a Likert
scale of 1 to 5. The pilot test contained statements on food safety which
showed very low factor loadings and were deleted from the list. Only 15
statements were used for the final questionnaire.
The results showed the respondents were divided into two major groups.
One group perceived organic food to be nutritious and the other group
perceived organic food to be a status symbol or a lifestyle value.
From the cumulative percentage of variance accounted for, we see that the
first two factors account for 73.34 percent of the variance. And that the gain
achieved in going to three factors is marginal. Thus, two factors appear to
be reasonable in this situation.
The ‗Communalities‘ shows the variance extracted from each variable for
the analysis. Principal components analysis is chosen as the primary
concern is to determine the minimum number of factors that will account for
maximum variance in the data. Of the several procedures that have been
suggested for determining the number of factors including a priori
determination and approaches based on Eigen values, scree plot,
percentage of variance accounted for, split-half reliability and significance
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test for this study we considered, the factors with Eigen values of one and
more than one.
The factor matrix contains the coefficient used to express the variables in
terms of the factors. These factor loadings represent the correlations
between factors and variables. The coefficient with a large absolute value
indicates that the factor and the variable are closely related. Varimax
rotation has been used for this study.
The 15 variables or statements that were used are as follows:
1. Organic food is overrated for its health benefits (H1)
2. Organic food is more nutritious than ordinary food (H2)
3. Healthy lifestyle requires that I consume organic food (H3)
4. There are many nutritional benefits in organic food (H4)
5. Organic food cannot be supplemented by ordinary food (H5)
6. I believe that organic food will keep me healthy (H6)
7. Organic food is free from chemical or pesticide residues (H7)
8. I tend to feel better when I eat organic food (H8)
9. Organic food has more health related benefits than ordinary food
(H9)
10. Wealthy people consume more organic food (S1)
11. Organic food is a status symbol (S2)
12. Consuming organic food is fashionable nowadays (S3)
205
13. Consuming organic makes me feel privileged (S4)
14. People with high rank and status consume organic food (S5)
15. Offering organic to friends shows that I have a high social
standing (S6)
Variables H2 to H9 loads strongly on Factor one. This factor has been
labelled nutrition seeking. While variables S2 to S5 loads strongly on the
other component or factor. This factor could be called status or lifestyle
seekers. The component plot of the factor loading shown below confirms
these interpretations.
Figure 22 Component Plot for Nutrition/ Lifestyle Seekers
206
The rotated component matrix, the table showing the extraction of the two
factors and the scree plot has been shown in the appendix.
Variables at the end of an axis are those that have high loadings on only
that factor and hence describe the factor. Variables near the origin have
lower loadings on both the factors. Variables that are not near any of the
axes are related to both the factors. The scree plot associated with this
analysis shows two distinct breaks occurring at the two factors. Thus the
null hypothesis that organic food is a matter of status is accepted as a
group of consumers do associate the consumption of organic food with
lifestyle. It also means that there is a possibility of sale of the product by
positioning it on the lifestyle platform. This may require financial investment
in the form of branding the product.
8.5 Hypothesis 5
The hypothesis that is being tested is:
H05 There is no significant variation on the expenditure of organic
food for regular users
H15 There is significant variation on the expenditure of organic food for
regular users
Consumers‘ expenses on organic food for two months have been
considered for the testing of this hypothesis. The expenditure of organic
food users for the current month and the previous month has been
considered.
207
The previous month‘s expenditure on organic food has been considered as
the first variable and the current month expenditure has been considered
as a second variable for analysis. The respondents have been divided into
eight groups based on the amount they spend on organic food in two
different months. The amounts were categorised into 8 groups as follows:
less than Rs.1500 , 1500- 2000, 2000-2500, 2500-3000,3000-3500, 3500-
4000,4000-4500,4500-5000.
F-test has been used to carry out the test for the equality of the two
population variances. If a researcher wants to test whether or not two
independent samples have been drawn from a normal population with the
same variability, then we generally employs the F-test. The F-distribution is
most commonly used in Analysis of Variance (ANOVA) and the F test (to
determine if two variances are equal). The F-distribution is the ratio of two
chi-square distributions, and hence is right skewed. It is important to note
that when referencing the F-distribution the numerator degrees of freedom
are always given first, and switching the degrees of freedom changes the
distribution (ie. F(10,12) does not equal F(12,10)).
Formula for F- test:
The obtained F value is 2.398. The calculated value of F is less than the
table value of 12.36 for (8,8) degree of freedom at 5% level of significance.
Hence we accept the null hypothesis and conclude that there is no
significant variation on the expenditure of organic food for regular users.
208
8.6 Hypothesis 6
H06 Exposure to media is not significantly associated with
consumption of organic food
H16 Exposure to media is significantly associated with consumption of
organic food
This hypothesis has been solved using factor analysis. This analytical
process is based on a correlation between the variables. As discussed
earlier, for factor analysis to be appropriate, the variables must be
correlated. If the correlation between all the variables is low, factor analysis
may not be appropriate. The variables that are highly correlated with each
other should also highly correlate with the same factors or factors.
Bartletts‘s test of sphericity is used to test null hypothesis that the variables
are uncorrelated in the population which is based on Chi-square
transformation of the determinant of the correlation matrix. A large value of
the Bartltts‘s test will favour the rejection of the null hypothesis.
Kaiser-Meyer-Olkin measures of sampling adequacy. This index compares
the magnitudes of the observed correlation coefficient to the magnitude of
the partial correlation coefficient. Lower values of the KMO indicate that
factor analysis may not be appropriate; a value greater than 0.5 is
desirable.
The null hypothesis, that the population correlation matrix could be an
identity matrix, is rejected by Bartlett‘s test of sphericity. The approximate
chi-square value is 7312.232 with 78 degrees of freedom, which is
significant at the 0.05 level. The value of the KMO for this data is 0.776
209
which is much greater than 0.05. It can be seen that the communality for
each variable is a unity.
The Eigenvalues are decreasing in order of magnitude as we go from
factor 1 to the end. The Eigenvalue for a factor indicates the total variance
attributed to that factor. The first two factors represent relatively large
amounts of variance whereas subsequent factors represent only small
amount of variance. So the gain achieved in going to three factors is
marginal. Thus, two factors appear to be reasonable in this situation. The
total explained variance from the two factors is 66.04%.
13 attitudinal statements depicting exposure to media and consumption of
organic food were used with a Likert scale of 1 to 5.
The second column under ‗Communalities‘ gives relevant information after
the desired numbers of factors are extracted. Principal components
analysis is used, as the primary concern is to determine the minimum
number of factors that will account for maximum variance in the data.
Several procedures have been suggested for determining the number of
factors. These include a priori determination and approaches based on
Eigen values, scree plot, percentage of variance accounted for, split-half
reliability and significance test. Here we considered factors with one and
more than one Eigen values.
The factor matrix contains the coefficient used to express the standardized
variables in terms of the factors. These coefficients or factor loadings
represent the correlations between factors and variables. The coefficient
with a large absolute value indicates that the factor and the variable are
210
closely related. The method of rotation used in this case is the varimax
procedure.
The thirteen statements used for the survey are:
1. I often visit websites with information on organic food
2. I am satisfied with the information i get on organic food
3. At least one meal in my day has an organic produce
4. I would like sales people to help me when buying organic food
5. I read Newspaper everyday
6. I watch T.V. everyday
7. I shop for organic products once in while
8. I am an occasional user of organic food
9. I read general interest magazines regularly
10. i would like a better source of information on organic food
11. Organic food is not well promoted
12. I have access to the internet throughout the day
13. I am a regular user of organic food
The results showed that three groups were formed. The plot of the factors
in two dimensional space is given below. One group of consumers were
satisfied with the information that they received on organic food. Their main
source of information was the internet. They were proactive and searched
the internet for websites containing information on organic food. These
consumers were also those who have high levels of consumption of
organic food.
211
Figure 23 Component plot for media exposure consumption level
The others group that was formed were well exposed to the various forms
of media like television, newspapers, magazines and internet but were
dissatisfied with the level of information that they received from the media.
They are not proactive and do not look out for information by themselves.
They are looking for better sources of information. They want the sellers to
find out their likes/ dislikes and educate them. They would also prefer help
from the sales people during their purchase. They also consume organic
food but not as much as the earlier group. They would probably increase
their consumption if they were properly informed of the benefits of organic
food.
Conversation with the group also reveals that they want more stores to
carry organic food so that availability and prices are balanced out.
212
The third group of people have lower levels of consumption than both the
other groups and their exposure to media is less than the first group. They
would probably not be the target group for the immediate increase in sale
of the product. This shows that people with different levels of exposure to
media are consumers of organic food. Therefore we can conclude that
exposure to media is not significantly associated with consumption of
organic food. Thus we accept the null hypothesis.
8.7 Hypothesis 7
The hypothesis that is being tested is:
H07 Income, age and education do not have a significant association
with the consumers of organic food.
H17 Income age and education have a significant association with the
consumers of organic food.
This hypothesis has been divided into three parts 7A, 7B and 7C for
convenience. Accordingly:
Hypothesis 7A is
H07a Income does not have a significant association with the consumers of
organic food
H07a Income has a significant association with the consumers of organic
food
Hypothesis 7B is
H07b Age does not have a significant association with the consumers of
organic food
213
H17b Age has a significant association with the consumers of organic food
Hypothesis 7C is
H07c Education does not have a significant association with the consumers
of organic food
H17c Education has a significant association with the consumers of organic
food
Interpretations for Hypothesis 7
H07a Income does not have a significant association with the consumers of
organic food
H17a Income has a significant association with the consumers of organic
food
All respondents have been grouped into four categories based on their
income as shown in the table below. 16 respondents were not willing to
disclose their income (3 non users and 13 users) so the total number of
respondents is 484. The details are shown in the table below:
Table 13 User category by Income Cross tabulation
214
The Pearson Chi square statistic for user by income is 11.163, which is
large. High vales for the Pearson Chi Square test statistic indicate the
likelihood that the two variables are not independent. Thus a value of
11.163 indicates that the two variables are dependent.
The p value less than 0.05 in the result indicates that the observed values
differ significantly from the expected values. Thus the variables income and
consumption are dependent. It can be concluded from the data that the null
hypothesis that ―Income does not have a significant association with the
consumers of organic food‖ is rejected.
Table 14 Chi Square values User Category by Income
Chi-Square Tests
Value Df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 11.163a 3 .011
Likelihood Ratio 12.600 3 .006
Linear-by-Linear Association 6.389 1 .011
N of Valid Cases 484
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 17.64.
Thus it is clear that in the sampled area, the higher income group have the
greater propensity to consume organic food.
Hypothesis 7B
H07b Age does not have a significant association with the consumers of
organic food
H17b Age has a significant association with the consumers of organic food
215
Table 15 User Category by Age
Table 16 Chi Square values for User category by Age
Chi-Square Tests
Value
Degree of
freedom
Significance
(2-sided)
Pearson Chi-Square 1.248a 2 .536
Likelihood Ratio 1.269 2 .530
Linear-by-Linear
Association .130 1 .719
N of Valid Cases 500
a. 0 cells (.0%) have expected count less than 5. The minimum
expected count is 18.20.
As the test statistic value of Pearson Chi-Square gets larger the likelihood
that the two variables are not independent also increases. The value of
Pearson Chi-Square (1.248) being low and close to 1 the variables are
likely to be independent. The probability of the result may happen by
chance is 0.536. The large p value also shows that the observed values do
not differ significantly from the expected values. Therefore it can be
216
concluded from this data that the consumption of organic food is
independent of age. The null hypothesis is accepted.
Hypothesis 7C
H07c Education does not have a significant association with the consumers
of organic food
H17c Education has a significant association with the consumers of organic
food
The respondents have been grouped into 3 categories for the analysis as
shown in table below:
Table 17 User category by Education table
Those respondents who had not passed the three year degree course
were considered under graduates. Those who completed college education
were graduates and all people completing the post graduate degree were
considered as post graduates.
As can be seen from the table, the Pearson Chi square statistic is 15.780,
which is very large. High vales for the Pearson Chi Square test statistic
indicate the likelihood that the two variables are not independent. Thus the
two variables education and user category are dependent. The p value less
217
than 0.05 in the result indicates that the observed values differ significantly
from the expected values.
Chi-Square Tests User Category by Education
Value
Degree of
freedom
Significance
(2-sided)
Pearson Chi-Square 15.780a 2 .000
Likelihood Ratio 15.546 2 .000
Linear-by-Linear
Association 10.891 1 .001
N of Valid Cases 498
a. 0 cells (.0%) have expected count less than 5. The
minimum expected count is 9.44.
This further consolidates the fact that these variables are dependent and
shows that the null hypothesis is rejected. So we can conclude that
Education has a significant association with the consumers of organic food
and the null hypothesis is rejected.
218
CHAPTER 9
SUGGESTIONS AND RECOMMENDATIONS
The suggestions may be divided into three parts for the sake of
understanding. The first suggestion deals with organic farming, the second
set deals with lowering costs, and the third one deals with the training and
education of all the people involved.
Suggestions regarding organic farming
1. Maintain the soil - food web. This would include relationships with
4. Not a regular buyer 5. Others (please specify)________________
3. Please indicate with a tick mark the extent to which you agree or disagree with
the following statements, where 1 = Strongly agree; 2 = Agree; 3= Undecided;
4= Disagree; 5= Strongly disagree
No STATEMENT 1 2 3 4 5
1. Organic food is more nutritious than ordinary
food
2. Organic food is tastier than ordinary food
3. Organic foods are generally fresh
4. I am well aware of organic food
5. I buy organic because it is tastier
6. A wide range of organic food can be bought
where I shop
7. Organic food are free from chemical or
pesticide residues
264
No STATEMENT 1 2 3 4 5
8. There is not much difference between organic
food and regular food
9. I buy organic food because I want to be
environmentally conscious
10. I believe that organic food will keep me
healthy
11. I never buy food at specialised organic food
shops
12. I am satisfied that the food I eat is safe
13. I buy organic food because I want to be
environmentally conscious
14. I am well aware of organic food
15. Organic food is more nutritious than ordinary
food
16. I have been purchasing organic food
frequently
17. Organic food is costlier than conventional
food
18. I frequently consume organic food
19. I often visit organic food websites
20. I often speak to others about the benefits of
organic food
4. Did any of the following factors ever play a role in your discontinuing of purchase of organic food? Please indicate your choice by ticking (√) yes or no:
1 Shelf Life Yes No
2 Price Yes No
3 Appearance Yes No
4 Poor quality Yes No
5 Availability Yes No
2. Purchase Knowledge of Consumers of Organic Food
1. For how long have you been purchasing Organic food?
1. Less than 6 months 2. 6months- 1 year 3.more than 1 year
2. When did you last purchase organic food?
1. Last week 2. .Last month 3. six months ago
265
3. How often do you purchase the following? Please indicate the frequency of
purchase with a tick (√), and mention the amount spent per purchase.
Food Category Every week (1)
Once in a Month (2)
Amount spent last month (Rs)
Amount spent present month (Rs)
i. Regular Fruits
ii. Organic Fruits
iii. Ordinary Vegetables
iv. Organic Vegetables
v. Ordinary Pulses or
Cereals
vi. Organic Pulses /
Cereals
vii. Ordinary Masala
viii. Organic Masala
ix) Mention two organic products frequently purchased by you______________________
Place of Purchase
4. Where do you make your purchases of organic food from?
1) Directly from producers 2) Specialised organic food shops
3) Supermarkets/ hypermarket 4) Open Markets
5. i)Shop location_____________ ii) Name of brand if any ____________
266
3. Media Exposure
Please indicate with a tick mark the extent to which you agree or disagree with the
following statements, where 1 = Strongly agree; 2 = Agree; 3= Undecided; 4= Disagree;
5= Strongly disagree
Sr No STATEMENTS 1 2 3 4 5
1) I often visit websites with information on organic food
2) I am satisfied with the information i get on organic food
3) At least one meal in my day has an organic produce
4) I would like sales people to help me when buying organic food
5) I read Newspaper everyday
6) I watch T.V. everyday
7) I shop for organic products once in while
8) I am an occasional user of organic food
9) I read general interest magazines regularly
10) i would like a better source of information on organic food
11) Organic food is not well promoted
Sr No STATEMENTS 1 2 3 4 5
12) I have access to the internet throughout the day
13) I am a regular user of organic food
4. Health Benefits and Lifestyle
Please indicate with a tick mark the extent to which you agree or disagree with the
following statements, where 1 = Strongly agree; 2 = Agree; 3= Undecided; 4= Disagree;
5= Strongly disagree
No STATEMENT 1 2 3 4 5
1. Organic food is overrated for its health benefits
2. Organic food is more nutritious than ordinary food
3. Healthy lifestyle requires that I consume organic food
267
No STATEMENT 1 2 3 4 5
4. There are many nutritional benefits in organic food
5. Organic food cannot be supplemented by ordinary food
6. I believe that organic food will keep me healthy
7. Organic food is free from chemical or pesticide residues
8. I tend to feel better when I eat organic food
9. Organic food has more health related benefits than ordinary food
10. Wealthy people consume more organic food
11. Organic food is a status symbol
12. Consuming organic food is fashionable nowadays
13. Consuming organic makes me feel privileged
14. People with high rank and status consume organic food
15. Offering organic to friends shows that I have a high social standing
5. Willingness to pay premium (excess price paid over normal products)
Please indicate with a tick mark () the extent to which you agree or disagree with the following statements, where 1 = Strongly agree; 2 = Agree; 3= Undecided; 4= Disagree; 5= Strongly disagree
No STATEMENTS 1 2 3 4 5
1. A premium can be charged for organic food as they are more nutritious
2. Organic foods are good value for money
3. A premium can be charged for organic food as they protect the bio diversity of the earth
4. A premium can be charged for organic food as they have no chemical waste / pesticides residuals
5. A premium can be charged for organic food as they taste better
6. A premium can be charged for organic food as its production methods are certified
268
No STATEMENTS 1 2 3 4 5
7. A premium can be charged for organic food as its safety is monitored through certification
8. A premium can be charged for organic food as it supports marginal farmers and tribal communities
9. I am willing to pay a premium for purchasing organic products
10. I refrain from buying organic because of the price
6. Socio-Demographic Details (please tick the appropriate answer)
1. Age (i)18 – 30 (ii) 31-40 (iii) over 40
2. Sex (i) Male (ii) Female
3. Education: (i)Under graduate (ii) Graduate (iii) Post Graduate
4. Mention Professional Qualifications, if
any_____________________________
5. Marital status (i) Married (ii) Single
6. Your Hometown ____________________
7. Number of children in the family________
8. Age of children 1st child_____ 2nd child_____ 3rd
child___
9. Your household size: ______________
10. Your Occupation 1) Service 2)Self employed 3)unemployed
I am conducting a survey about preference for organic food as a part of my curriculum.
You are one of the respondents who have been chosen to participate in this survey. I
highly value your opinion and would like to ask you a few questions food consumption.
1. Awareness
Please indicate with a tick mark (√) the extent to which you agree or disagree with the following statements, where 1 = Strongly agree; 2 = Agree; 3= Undecided; 4= Disagree; 5= Strongly disagree
No STATEMENT 1 2 3 4 5
1. I believe food is more nutritious when no pesticides and chemicals are used to grow it
2. I am willing to pay more for food without chemical or pesticide residues
3. Staying healthy is important to me
4. There is not much difference between food without chemical or pesticide and regular food
5. I am satisfied that the food I eat is safe
6. I like to eat nutritious food
7. I consider myself as environmentally aware
8. I refrain from buying organic food because of the price
1. Are you aware of organic food? 1) Yes 2) No
2. Have you ever tried organic food? 1) Yes 2) No
2. Purchase Knowledge of Consumers on food items purchased
How often do you purchase the following? Please indicate the frequency of purchase with a tick (√), and mention the amount spent per purchase.
Food Category Every week
Once in a Month
Amount spent last
month (Rs)
Amount spent present month
(Rs)
i. Fruits
ii. Vegetables
270
iii. Pulses or Cereals
iv. Powdered Masala
3. Please indicate with a tick mark (√) the extent to which you agree or disagree with the following statements, where 1 = Strongly agree; 2 = Agree; 3= Undecided; 4= Disagree; 5= Strongly disagree
Sr No STATEMENTS 1 2 3 4 5
1. I buy organic food because I want to be environmentally conscious
Always Never
2. I am well aware of organic food
3. Organic food is more nutritious than ordinary food
4. I have been purchasing organic food frequently
5. Organic food is costlier than conventional food
6. I frequently consume organic food
7. I often visit organic food websites
4. Socio-Demographic Details (please tick the appropriate answer)
1. Age 18 – 30 31-40 over 40
2. Sex Male Female
3. Education: Under graduate Graduate Post Graduate
4. Marital status: Married Single
5. Hometown ____________________
6. Number of children in the family________
7. Household size: ____________________
8. Your Occupation In Service Self employed neither
9. Monthly Household Income (Rs)
Less than Rs. 50,000 Between Rs. 50 – 1.5 lakh Between Rs. 1.5 -2.5 lakh More than Rs. 2.5 lakh
THANK YOU FOR YOUR TIME
271
ANNEXTURE III
STATISTICAL TABLES OF SPSS FINDINGS
Demographic details of the respondents
Frequency Tables (Users)
Classification by Age
Frequency Percent Valid Percent
Cumulative
Percent
Valid 18-30 176 44.0 44.0 44.0
31-40 148 37.0 37.0 81.0
More than 40 76 19.0 19.0 100.0
Total 400 100.0 100.0
SPSS OP 0-1
Classification by Gender
Frequency Percent Valid Percent
Cumulative
Percent
Valid Male 233 58.3 58.3 58.3
Female 167 41.8 41.8 100.0
Total 400 100.0 100.0
SPSS OP 0-2
272
Classification by Education
Frequency Percent Valid Percent
Cumulative
Percent
Valid Under Graduate 39 9.8 9.8 9.8
Graduate 218 54.5 54.8 64.6
Post Graduate 141 35.3 35.4 100.0
Total 398 99.5 100.0
Missing 99 2 .5
Total 400 100.0
SPSS OP 0-3
Classification by Marital Status
Frequency Percent Valid Percent
Cumulative
Percent
Valid Married 265 66.3 66.3 66.3
Single 135 33.8 33.8 100.0
Total 400 100.0 100.0
SPSS OP 0-4
SPSS OP 0-5 Monthly Household Income
Frequency Percent Valid Percent
Cumulative
Percent
Valid Less than Rs.50000 137 34.3 35.4 35.4
Rs.50000 to Rs.1.5 lacs 78 19.5 20.2 55.6
Rs.1.5 lacs to Rs.2.5 lacs 66 16.5 17.1 72.6
More than Rs.2.5 lacs 106 26.5 27.4 100.0
Total 387 96.8 100.0
Missing 99 13 3.3
Total 400 100.0
273
Frequency Tables (Non Users)
Classification by Age
Frequency Percent Valid Percent Cumulative Percent
Valid 18-30 43 43.0 43.0 43.0
31-40 42 42.0 42.0 85.0
Over 40 15 15.0 15.0 100.0
Total 100 100.0 100.0
SPSS OP 0-6
Classification by Gender
Frequency Percent Valid Percent Cumulative Percent
Valid Male 70 70.0 70.0 70.0
Female 30 30.0 30.0 100.0
Total 100 100.0 100.0
SPSS OP 0-7
Classification by Education
Frequency Percent Valid Percent Cumulative Percent
Valid Under Graduate 8 8.0 8.0 8.0
Graduate 35 35.0 35.0 43.0
Post Graduate 57 57.0 57.0 100.0
Total 100 100.0 100.0
SPSS OP 0-8
274
Classification by Martial status
Frequency Percent Valid Percent Cumulative Percent
Valid Married 66 66.0 66.0 66.0
Single 34 34.0 34.0 100.0
Total 100 100.0 100.0
SPSS OP 0-9
Monthly household income
Frequency Percent Valid Percent
Cumulative
Percent
Valid Less than Rs. 50000 42 42.0 42.0 42.0
Between Rs. 50-1.5 Lakhs 22 22.0 22.0 64.0
Between Rs. 1.5-2.5
Lakhs 22 22.0 22.0 86.0
More Than Rs. 2.5 Lakhs 11 11.0 11.0 97.0
9 3 3.0 3.0 100.0
Total 100 100.0 100.0
SPSS OP 0-10
The cross tabulation of the respondents by age, education and income of
the non users
275
SPSS OP 0-11
Cross tabulation of the users by age, education and income
SPSS OP 0-12
276
Logistic Regression
Case Processing Summary
Unweighted Casesa N Percent
Selected Cases Included in Analysis 400 100.0
Missing Cases 0 .0
Total 400 100.0
Unselected Cases 0 .0
Total 400 100.0
a. If weight is in effect, see classification table for the total number of cases.
Block 0: Beginning Block
Iteration Historya,b,c
Iteration -2 Log likelihood
Coefficients
Constant
Step 0 1 439.547 1.050
2 438.546 1.163
3 438.545 1.166
4 438.545 1.166
a. Constant is included in the model.
b. Initial -2 Log Likelihood: 438.545
c. Estimation terminated at iteration number 4 because
parameter estimates changed by less than .001.
SPSS OP 0-13
277
Classification Tablea,b
Observed
Predicted
logit
Percentage Correct 1 2
Step 0 Logit 1 0 95 .0
2 0 305 100.0
Overall Percentage 76.3
a. Constant is included in the model.
b. The cut value is .500
SPSS OP 0-14
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 0 Constant 1.166 .117 98.556 1 .000 3.211
SPSS OP 0-15
Variables not in the Equation
Score df Sig.
Step 0 Variables nutrition_vlue .057 1 .812
healty_benifit .096 1 .757
taste 1.553 1 .213
media_influence .269 1 .604
Overall Statistics 5.783 4 .216
SPSS OP 0-16
278
Block 1: Method = Enter
Iteration Historya,b,c,d
Iteration -2 Log
likelihood
Coefficients
Constant nutrition_valu
e
taste healty_die
t
media_influe
nce
Step 1
1 434.382 1.113 .236 -.030 -.303 .075
2 432.732 1.274 .324 -.033 -.418 .095
3 432.727 1.284 .331 -.032 -.427 .096
4 432.727 1.284 .331 -.032 -.427 .096
a. Method: Enter
b. Constant is included in the model.
c. Initial -2 Log Likelihood: 438.545
d. Estimation terminated at iteration number 4 because parameter estimates changed by less
than .001.
Omnibus Tests of Model Coefficients
Chi-square df Sig.
Step 1 Step 5.818 4 .213
Block 5.818 4 .213
Model 5.818 4 .213
SPSS OP 0-17
Model Summary
Step -2 Log likelihood
Cox & Snell R
Square
Nagelkerke R
Square
1 432.727a .014 .022
a. Estimation terminated at iteration number 4 because parameter
estimates changed by less than .001.
SPSS OP 0-18
279
Hosmer and Lemeshow Test
Step Chi-square df Sig.
1 134.820 7 .000
SPSS OP 0-19
Contingency Table for Hosmer and Lemeshow Test
logit = 1.00 logit = 2.00
Total Observed Expected Observed Expected
Step 1 1 16 14.396 26 27.604 42
2 4 7.479 24 20.521 28
3 39 11.512 9 36.488 48
4 10 8.146 24 25.854 34
5 0 8.890 38 29.110 38
6 3 24.896 106 84.104 109
7 2 6.219 26 21.781 28
8 12 7.794 25 29.206 37
9 9 5.670 27 30.330 36
SPSS OP 0-20
280
Classification Table
Observed
Predicted
logit
Percentage Correct 1 2
Step 1 logit 1 4 91 4.2
2 0 305 100.0
Overall Percentage 77.3
a. The cut value is .500
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
nutrition_value .331 .187 3.121 1 .077 1.392
taste -.032 .164 .039 1 .843 .968
healty_diet -.427 .191 4.995 1 .025 .652
media_influenc
e
.096 .166 .335 1 .562 1.101
Constant 1.284 .342 14.062 1 .000 3.610
a. Variable(s) entered on step 1: nutrition_value, taste, healty_diet, media_influence.
SPSS OP 0-21
281
Casewise Listb
Case Selected Statusa
Observed
Predicted Predicted Group
Temporary Variable
logit Resid ZResid
26 S 1** .878 2 -.878 -2.685
29 S 1** .924 2 -.924 -3.490
68 S 1** .929 2 -.929 -3.623
69 S 1** .901 2 -.901 -3.019
72 S 1** .860 2 -.860 -2.478
a. S = Selected, U = Unselected cases, and ** = Misclassified cases.
b. Cases with studentized residuals greater than 2.000 are listed.