THE DECISION MAKING PROCESS IN THE ADOPTION OF AGROFORESTRY

263 Pages·2011·4.37 MB·English

THE DECISION MAKING PROCESS IN THE ADOPTION OF
AGROFORESTRY TECHNOLOGY BY SMALLHOLDER
RUBBER FARMERS IN INDONESIA

A thesis submitted in partial fulfilment of the requirements
for the Degree of Doctor of Philosophy
by
Dudi Iskandar

School of Forestry
University of Canterbury
Christchurch, New Zealand
2011
Abstract
The Decision Making Process in the Adoption of Agroforestry Technology by
Smallholder Rubber Farmers in Indonesia

A thesis submitted in partial fulfilment of the requirements
for the Degree of Doctor of Philosophy

by
Dudi Iskandar

School of Forestry
University of Canterbury, Christchurch, New Zealand

The contribution of rubber to national economic and social development is important
for Indonesia. However, smallholding rubber, the dominant rubber producer, has low
productivity. Various new technology programmes have been introduced by the
Indonesian government with other agencies to increase the productivity of existing
traditional rubber and incomes among smallholder rubber farmers in Indonesia.
However, the adoption of new technology was low and the reasons for these were still
unclear.
This study explores how smallholder farmers in Indonesia adopt new technology.
Rubber Agroforestry System (RAS) introduced mainly by International Centre for
Research in Agroforestry (ICRAF ) in Jambi and West Kalimantan provinces in
Indonesia is used as a case study. A combination of Ethnographic Decision Tree
Modelling (EDTM) proposed by Gladwin (1989a) and a logistic regression model
were used as the main methodologies to determine the decision criteria of rubber
farmers regarding adoption of clonal rubber. The EDTM as qualitative method helped
to identify the main reasons, motivations and constraints that influenced a farmer’s
decision to adopt or not adopt the new technology and also present details about the
process of the farmers’ decision making. Meanwhile, logit as the quantitative method
was useful to identify the significant variables involved in the decision making
process.
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The results of this study show that the decision making process for adoption of clonal
rubber is complex and influenced by various factors. The decision tree models for
Jambi and West Kalimantan differed showing the importance of social context and
infrastructure. The main reasons for a farmer’s decisions to adopt clonal rubber is the
expectation that clonal rubber is better in growth and yield and it will increase
production per ha and income. The decision to adopt is supported by evidence from
demonstration plots, trust in the technology deliverers and availability of incentives.
The main constraint in adoption for both areas was limitation of capital as the clonal
rubber required more capital to establish. The other constraints are risk and
uncertainties including pest and disease problems, the shortage of labour, lack of
technical knowledge, lack of access to clonal seedlings, and observation of clonal
rubber that has been of low quality or managed inadequately. The decision tree models
have been tested and the results show that the models were able to predict the farmers’
decision making with good accuracy of 82% and 83%. In addition, the quantitative
model shows the significant factors that determine adoption of clonal rubber in Jambi
and West Kalimantan are land, incentives and income factors.
The qualitative and quantitative methods contributed to increased robustness of data
and give different kinds of valuable data and information to stakeholders and policy
makers in Indonesia. In order to encourage rubber farmers in Jambi and West
Kalimantan to adopt clonal rubber, this study suggests improving policies to ensure
they are aligned with needs of the rubber farmers, improving farmers’ access to capital
sources such as credit with simpler mechanisms, increasing the number and skills of
extension workers, encouraging farmer to farmer learning, empowering farmers and
leadership, improving infrastructure including better access to clonal seedlings and
improving partnership with NGOs.

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Acknowledgments
I would like to express my deep and sincere gratitude to my main supervisor,
Associate Professor Bruce Manley, Head of the School of Forestry, University of
Canterbury. His invaluable advice, knowledge and interest, and detailed and
constructive comments in my research have been of great value. I would like to thank
him for his understanding, encouragement and for finding solutions for every single
problem during the preparation of this thesis.
I am deeply grateful to my co-supervisor, Dr. Alison Loveridge of the School of Social
and Political Sciences, University of Canterbury for introducing to me to the world of
sociology. I am happy to have such a compassionate co-supervisor and I enjoyed her
interest in my study as well as the fruitful discussions. I benefited greatly from her
ideas, guidance and for her patience and consistent support throughout this work.
I wish to express my warm and sincere thanks to Dr. Laxman Joshi. His extensive
discussions around my work and interesting explorations of the rubber world and rural
people have been very helpful for this study. His help during field work in Bogor,
Jambi and West Kalimantan is much appreciated. I learned a lot during that time and I
am sure that this knowledge and experience will help me in the future.
I owe my most sincere gratitude to my adviser Dr. Sarah Beaven from International
Student Service. She gave me and my family untiring help during my difficult
moments as an international student and she provided a solution every time I needed
one.
During this work I have collaborated with many colleagues for whom I have great
regard. My warm thanks go to Dr. Meine van Noordwijk who introduced me to the
ICRAF World from the beginning and built the idea of pursuing my PhD. His
invaluable advice and expertise opened my mind to choosing the topic and working
together with ICRAF. I also thank the Director of ICRAF, Dr. Ujwal Pradhan for his
supports. Thank you to all the staffs in ICRAF especially Elok, Dr. Suyanto,
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Janudianto, Betha, Anna, Diah, Andree and Usman for their kind support that has been
of great value in this study.
My special thanks go to the people who help me during the field work. Ratna
Akefnawati, team leader ICRAF in Jambi, Jasnari and Andi, my field assistants, who
helped me greatly to connect with the people and cultural life of Bungo. Thanks also to
Ilahang and Sujono in Sanggau who assisted me during the field research in West
Kalimantan. Without them the field work would have never been possible. My special
thanks go to all of the rubber farmers in Jambi and West Kalimantan who sacrificed
their valuable time and efforts to support my research. This thesis is basically about
you so I dedicate it especially to you.
I wish to extend my warmest thanks to Dr. Richard Woollons for guidance in statistical
analysis using SAS. Special thanks to Dr. Leonardo Sambodo, for his beneficial
discussion about decision tree model. I would like to thank to Jeanette Allen for her
sympathetic help in secretarial work, Geraldine Murphy and Rob Dewhirst for editing
the English of my manuscript and to Tearlach Mclain of the Student Health Centre
who helped me during a difficult time.
Thank you also to all my fellow postgraduates at the School of Forestry and the
NZAID students. Thank you to the Indonesian students and the Indonesian
community in New Zealand who were always there whenever I needed to cope with
life here in Christchurch. My time at Christchurch was made enjoyable due to the
many friends and family groups that became a part of my life.

I am deeply grateful for the financial support that made my PhD work possible from
New Zealand Development Scholarships (NZAID), World Agroforestry (ICRAF) and
the University of Canterbury.
I wish to thank to all my family who have always supported me. I thank my lovely
parents for inspiring and driving me to reach any dreams with confidence. They
believe that any dream is possible with desire, will, strength of mind and prayer. My
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special gratitude is due to my parents in law, my brothers, my sisters and their families
for their loving support and continual prayer for me during my study.
I owe my loving thanks to my wife Tina Paramita, my lovely daughters Nadia
Ranaputri and Tsania Syaharani. Without their love, encouragement, faithful support
and understanding, it would have been impossible for me to finish this study. To all of
them I dedicate this thesis.
Last but not least, I thank Almighty God, Allah SWT, for granting me the courage to
do my PhD study and strength to deal with challenges and difficulties all through my
study. During the final process of writing of this thesis, Christchurch was hit twice by
big earthquakes on September, 4, 2010 and February, 22, 2011. The University of
Canterbury was closed and I had no access to my office, library and other University
facilities for a while. We have survived those two earthquakes but many people lost
their lives, their family and friends. My hearts will always go out to those who have
lost family or friends in this tragedy.

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List of Abbreviations

BPS (Biro Pusat Statistic = Statistics Centre Bureau)
BAPPEDA Regional Body for Planning and Development
CIFOR Centre for International Forestry Research
DGECI Directorate General for Estate Crops of Indonesia
DFECS District Forestry and Estate Crops Services (Dishutbun)
GDRP Gross domestic regional product
IRRI Indonesian Rubber Research Institute
IDRB International Development & Relief Board
ICRAF International Centre for Research Agroforestry
NES Nucleus Estate Smallholders
NGO Non Governmental Organizations
NSSDP Projects include North Sumatra Smallholders’ Development
PRPTE Replanting Rehabilitation and Expansion of Export Oriented
Commodities
PPKR People's Rubber Plantation Project
RAS Rubber Agroforestry Systems
SRDP Smallholders' Rubber Development Project
WSSDP West Sumatra Smallholders’ Development Project

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Table of Contents

Abstract i
Acknowledgments iii
List of Abbreviations vi
Table of Contents vii
List of Tables xi
List of Figures xiii
Chapter 1 Introduction
1.1 Background 1
1.2 Study Objectives 2
1.3 Main Contributions 4
1.4 Organization of the Thesis 5
Chapter 2 Rubber Agroforestry Technology Adoption in
Indonesia
2.1 Introduction 6
2.2 Forest and Rubber Agroforest in Indonesia 6
2.3 History of Rubber in Indonesia 8
2.4 The Role of Rubber in Indonesia 12
2.5 Rubber Agroforestry: Position and Problems 15
2.6 Introduction of Improved Technologies in Rubber Agroforestry 18
2.7 Problems in the Adoption of New Technologies 26
2.8 Summary 28
Chapter 3 Decision Making in the Adoption of Agroforestry
Technologies
3.1 Introduction 29
3.2 The Adoption of New Technology in Agroforestry 29
3.2.1 Agroforestry Technology 29
3.2.2 Agroforestry Technology Diffusion 31
3.2.3 Agroforestry Technology Adoption 36
3.3 Factors Influencing Adoption 40
3.3.1 Economic 42
3.3.2 Managerial 45
3.3.3 Technical 46
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3.3.4 Social Structure 53
3.3.5 Policy and Institution 54
3.3.6 Farm and Farm Household Preferences 56
3.4 Decision Making Models in the Adoption of Agroforestry 62
3.4.1 Decision Making Models 62
3.4.2 Ethnographic Decision Tree Model (EDTM) 64
3.4.3 Logistic Regression (Logit) 68
3.4.4 The Qualitative and Quantitative Analysis 69
3.5 Summary 71
Chapter 4 Methodology
4.1 Introduction 72
4.2 Characteristics of the Study Areas 72
4.2.1. Bungo District Jambi Province 72
4.2.2. Characteristics of the Villages 76
4.2.3. Sanggau District, West Kalimantan Province 85
4.2.4 Characteristics of the Villages 89
4.3 Selection of Sample Respondents 95
4.4 Data Collection Methods 97
4.4.1 Farmers’ Background 98
4.4.2 Developing the Decision Tree Model 99
4.4.3 Testing the Decision Tree Model 101
4.4.4 Data Collection for Quantitative Modelling 103
4.5 Data Processing and Analysis 105
4.5.1 Decision Tree Modelling 105
4.5.2 Testing the Decision Tree Model 106
4.5.3 Quantitative Model 107
4.6 Summary 110
Chapter 5 The Decision Tree Model for Jambi
5.1 Introduction 112
5.2 Characteristics of Respondents 112
5.2.1. Socioeconomic 112
5. 2.2 Rubber Management 115
5.2.3. Categorisation of Respondents 119
5.3 The Decision Tree Model for Jambi 120
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5.3.1 The Decision to Adopt or Not Adopt 120
5.3.2 The Test of the Decision Tree Model 122
5.3.3 How Rubber Farmers Made the Decision 124
5.4 Decision Criteria 127
5.5 Summary 138
Chapter 6 The Decision Tree Model for West Kalimantan
6.1 Introduction 139
6.2 Characteristics of Respondents 139
6.2.1 Socioeconomic 139
6.2.2 Characteristics of Rubber Management 141
6.2.3 Categorisation of Respondents 146
6.3 Decision Tree Model for West Kalimantan 147
6.3.1 The Decision to Adopt or Not Adopt 147
6.3.2 Test of the Decision Tree Model 149
6.3.3 How Rubber Farmers Made the Decision 151
6.4 Analysis of Decision Criteria 153
6.5 Summary 160
Chapter 7 Discussion
7.1 Introduction 162
7.2 Analysis of Decision Criteria of Jambi and West Kalimantan 162
7.2.1 Economic Factors 163
7.2.2 Managerial Criteria 174
7.2.3 Technical Criteria 177
7.2.4 Social Structure 186
7.2.5 Policies and Institutions 188
7.3 Decision Tree Model and Decision Making 197
7.4 Summary 201
Chapter 8 Quantitative Analysis of Adoption of Clonal Rubber
8.1 Introduction 203
8.2 Result 203
8.2.1 Variables 203
8.2.2 Logit Model Analysis in Jambi 205
8.2.3. Logit Model Analysis in West Kalimantan 207
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