Skip to main content

Advertisement

SpringerLink
Log in

Influence of Socio-Technological Factors on Smallholder Farmers’ Choices of Agroforestry Technologies in the Eastern Highlands of Uganda

  • Original Research
  • Published:
Small-scale Forestry Aims and scope Submit manuscript

Abstract

In Sub-Saharan Africa, agroforestry has been identified as the most sustainable remedy to counter declining farm productivity. Over the last decades, researchers and other actors have promoted several agroforestry technologies to improve farm productivity. Sometimes, the promotion message provided through extension assumes a homogenous smallholder farmers’ context. However, smallholder farmers’ social and farm contexts are heterogeneous. Smallholder farmers make different choices of which technologies fit their contexts. A range of factor categories influence and (re)shape choice decisions of smallholder farmers. In this paper, the authors seek to articulate the importance of socio-technological factors shaping smallholder farmers’ choices of specific agroforestry technologies on their farms. Knowledge of these factors provides insights that inform the design of refined farmer context-based extension messages, consequently enhancing the scaling-up of agroforestry technologies. The Decomposed Theory of Planned Behaviour was used as the main framework to understand smallholder farmers’ choice decisions among agroforestry technologies. We used a mixed methods approach. Quantitative data were collected from 277 randomly selected farming households in the eastern highlands of Uganda. Qualitative data that complemented the quantitative were collected using focus group discussions. An alternative-specific conditional logit model was used to model smallholder farmers’ agroforestry choices. Results indicated that the number of tree species desired by the farmer and the perceived value of the technology were the most critical factors that commonly influence smallholder farmers’ choice of agroforestry technologies. The influence of other factors such as gender, the number of training sessions attended, total land owned, peer influence and perceived behavioural control were technology-specific, suggesting the need to tailor agroforestry interventions to specific farmer categories.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Ajzen I (1991) The theory of planned behavior. Org Behav Hum Decis Process 50:179–211

    Article  Google Scholar 

  • Anang BT, Sipilainen T, Backman S, Kola J (2015) Factors influencing smallholder farmers access to agricultural microcredit in Northern Ghana. Afr j Agric Res 10:2460–2469

    Article  Google Scholar 

  • Anderson CL, Reynolds TW, Gugerty MK (2016) Husband and wife perspectives on farm household decision-making authority and evidence on intra-household accord in rural Tanzania. World Dev 90:169–183

    Article  Google Scholar 

  • Aziz S, Afaq Z (2018) Adoption of Islamic banking in Pakistan an empirical investigation. Cogent Bus Manag 5:1548050

    Article  Google Scholar 

  • Bala P, Ojunga SO, Okumu J, Kisiwa A, Langat D, Nyambati R (2020) Tree-based conflict management mechanism among small landholders in agroforestry systems of Kenya. East Afr J for Agrofor 2(2):24–39

    Article  Google Scholar 

  • Bernard B, Joshua W, Winnie N (2020) Determinants for the adoption of residential rainwater harvesting systems on the slopes of Mt. Elgon, East-Africa. How do they perform? Sustain Water Resour Manag 6:115

    Article  Google Scholar 

  • Bomuhangi A, Nabanoga G, Namaalwa JJ, Jacobson MG, Abwoli B, Wich S (2016) Local communities’ perceptions of climate variability in the Mt. Elgon region, eastern Uganda. Cogent Environ Sci 2:1168276. https://doi.org/10.1080/23311843.2016.1168276

    Article  Google Scholar 

  • Borges JAR, Oude Lansink AGJM, Marques Ribeiro C, Lutke V (2014) Understanding farmers’ intention to adopt improved natural grassland using the theory of planned behaviour. Livest Sci 169:163–174

    Article  Google Scholar 

  • Bukomeko H, Jassogne L, Kagezi GH, Mukasa D, Vaast P (2018) Influence of shaded systems on Xylosandrus compactus infestation in Robusta coffee along a rainfall gradient in Uganda. Agr Forest Entomol 20:327–333

    Article  Google Scholar 

  • Buyinza J, Nuberg IK, Muthuri CW, Denton MD (2020) Psychological factors influencing farmers’ intention to adopt agroforestry: a structural equation modeling approach. J Sustain for 45:1–12

    Google Scholar 

  • Cameron AC, Trivedi PK (2005) Microeconometrics: methods and applications. Cambridge University Press, New York

    Book  Google Scholar 

  • Coulibaly JY, Chiputwa B, Nakelse T, Kundhlande G (2017) Adoption of agroforestry and the impact on household food security among farmers in Malawi. Agric Syst 155:52–69

    Article  Google Scholar 

  • Dai X, Pu L, Rao F (2017) Assessing the effect of a crop-tree intercropping program on smallholders’ incomes in rural Xinjiang, China. Sustainability 9(9):1542

    Article  Google Scholar 

  • Denkyirah EK, Okoffo ED, Adu DT, Bosompem OA (2017) What are the drivers of cocoa farmers’ choice of climate change adaptation strategies in Ghana? Cogent Food Agric 3:1–21

    Google Scholar 

  • Dewees PA (1995) Trees and farm boundaries: farm forestry, land tenure and reform in Kenya. J Int Afr Inst 65:217–237

    Article  Google Scholar 

  • Field A (2009) Discovering statistics using SPSS: (and sex, drugs and rock “n” roll), 3rd edn. SAGE Publications, Los Angeles

    Google Scholar 

  • Gangwal N, Bansal V (2016) Application of the decomposed theory of planned behaviour for M-commerce adoption in India. In: Hammoudi S, Maciaszek L, Missikoff MM, Camp O, Cordeiro J (eds) Proceedings of the 18th international conference on enterprise information systems (ICEIS 2016), vol 2. SCITEPRESS. Science and Technology Publications Lda, Rome, Italy, pp 357–367

  • Gram G, Vaast P, van der Wolf J, Jassogne L (2017) Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda. Agrofor Syst 32:443. https://doi.org/10.1007/s10457-017-0111-8

    Article  Google Scholar 

  • Greene WH (2012) Econometric analysis, 7th edn. Prentice Hall, Boston

    Google Scholar 

  • Hernandez JMC, Mazzon JA (2006) Adoption of internet banking: proposition and implementation of an integrated methodology approach. Int J Bank Mark 25:72–88

    Article  Google Scholar 

  • Iiyama M, Mukuralinda A, Ndayambaje JD, Musana BS, Ndoli A, Mowo JG, Garrity D, Ling S, Ruganzu V (2018) Addressing the paradox—the divergence between smallholders’ preference and actual adoption of agricultural innovations. Int J Agric Sustain 16:472–485

    Article  Google Scholar 

  • Kalanzi F, Nansereko S (2015) Exploration of farmers’ tree species selection for coffee agroforestry in Bukomansimbi district of Uganda. Int J Res Land Use Sustain 1:9–17

    Google Scholar 

  • Kassie M, Jaleta M, Shiferaw B, Mmbando F, Mekuria M (2013) Adoption of interrelated sustainable agricultural practices in smallholder systems: evidence from rural Tanzania. Technol Forecast Soc Change 80:525–540

    Article  Google Scholar 

  • Kassie GW (2016) Agroforestry and land productivity: Evidence from rural Ethiopia. Cogent Food Agric 2:99–116

    Google Scholar 

  • Keil A, Zeller M, Wida A, Sanim B, Birner R (2008) What determines farmers’ resilience towards ENSO-related drought? An empirical assessment in Central Sulawesi, Indonesia. Clim Change 86:291–307

    Article  Google Scholar 

  • Kidane SM, Lambert DM, Eash NS, Roberts RK, Thierfelder C (2019) Conservation agriculture and maise production risk: the case of Mozambique smallholders. Agron J 111:1–11

    Article  Google Scholar 

  • Kiptot E, Franzel S, Hebinck P, Richards P (2006) Sharing seed and knowledge: farmer to farmer dissemination of agroforestry technologies in western Kenya. Agric Syst 68:167–179

    Google Scholar 

  • Kiyingi I, Edriss A, Phiri M, Buyinza M, Agaba H (2016) Adoption of on-farm plantation forestry by smallholder farmers in Uganda. JSD 9:153–161

    Article  Google Scholar 

  • Krejcie RV, Morgan DW (1970) Determining sample size for research activities. Educ Psychol Measur 30:607–610

    Article  Google Scholar 

  • Kutia S, Chauhdary SH, Iwendi C, Liu L, Yong W, Bashir AK (2019) Socio-technological factors affecting user’s adoption of ehealth functionalities: a case study of China and Ukraine ehealth systems. IEEE Access 7:90777–90788

    Article  Google Scholar 

  • Kuyah S, Öborn I, Jonsson M, Dahlin AS, Barrios E, Muthuri C, Sinclair FL (2016) Trees in agricultural landscapes enhance provision of ecosystem services in Sub-Saharan Africa. Int J Biodivers Sci Ecosyst Serv Manag 55:1–19

    Article  Google Scholar 

  • Kyere-Duodu K, Yamoah DD (2011) Adoption of internet banking among Ghanaian consumers: a study using the decomposed theory of planned behaviour. Master's thesis, Lulea University of Technology

  • Lamond G, Sandbrook L, Gassner A, Sinclair FL (2016) Local knowledge of tree attributes underpins species selection on coffee farms. Ex Agric 55:35–49

    Article  Google Scholar 

  • Luedeling E, Smethurst PJ, Baudron F, Bayala J, Huth NI, van Noordwijk M, Ong CK, Mulia R, Lusiana B, Muthuri C, Sinclair FL (2016) Field-scale modelling of tree–crop interactions: challenges and development needs. Agric Syst 142:51–69

    Article  Google Scholar 

  • Mcfadden D (1977) Qualitative methods for analysing travel behaviour of individuals: some recent developments. Cowles Foundation Discussion Paper No. 474. Berkeley: Institute of Transportation Studies, University of California

  • McGinty MM, Swisher ME, Alavalapati J (2008) Agroforestry adoption and maintenance: self-efficacy, attitudes and socio-economic factors. Agroforest Syst 73:99–108

    Article  Google Scholar 

  • Md Husin M, Ab Rahman A (2016) Predicting intention to participate in family takaful scheme using decomposed theory of planned behaviour. Int J Soc Econ 43:1351–1366

    Article  Google Scholar 

  • Meijer SS, Catacutan D, Sileshi GW, Nieuwenhuis M (2015) Tree planting by smallholder farmers in Malawi: using the theory of planned behaviour to examine the relationship between attitudes and behaviour. J Environ Psychol 43:1–12

    Article  Google Scholar 

  • Mignouna DB, Manyong VM, Mutabazi KDS, Senkondo EM (2011) Determinants of adopting imazapyr-resistant maise for Striga control in Western Kenya: a double-hurdle approach. J Dev Agric Econ 3:572–580

    Google Scholar 

  • Moons I, De Pelsmacker P (2015) An Extended decomposed theory of planned behaviour to predict the usage intention of the electric car: a multi-group comparison. Sustainability 7:6212–6245

    Article  Google Scholar 

  • Mubangizi N, Kyazze FB, Mukwaya PI (2017) Smallholder farmers’ perception and adaptation to rainfall variability in Mt. Elgon region, eastern Uganda. Int J Agric Ext 5:103–117

    Google Scholar 

  • Mubangizi N, Kyazze FB, Mukwaya P (2018) Smallholder farmers' access to and use of scientific climatic forecast information in Mt. Elgon area, Eastern Uganda. Int J Agri Sci Res Technol Ext Educ Syst 8(1):29–42

    Google Scholar 

  • Mukasa AN (2018) Technology adoption and risk exposure among smallholder farmers: panel data evidence from Tanzania and Uganda. World Dev 105:299–309

    Article  Google Scholar 

  • Mwangi M, Kariuki S (2015) Factors determining adoption of new agricultural technology by smallholder farmers in developing countries. J Econ Sustain Dev 6:208–216

    Google Scholar 

  • Mwaura F (2014) Effect of farmer group membership on agricultural technology adoption and crop productivity in Uganda. Afr Crop Sci J 22:917–927

    Google Scholar 

  • Nair RP (1993) An introduction to agroforestry. Kluwer Academic Publisher, Dordrecht

    Book  Google Scholar 

  • Nath CD, Schroth G, Burslem DFRP (2016) Why do farmers plant more exotic than native trees? A case study from the Western Ghats, India. Agr Ecosyst Environ 230:315–328

    Article  Google Scholar 

  • Nigussie Z, Tsunekawa A, Haregeweyn N, Adgo E, Nohmi M, Tsubo M, Aklog D, Meshesha DT, Abele S (2017) Factors influencing small-scale farmers’ adoption of sustainable land management technologies in north-western Ethiopia. Land Use Policy 67:57–64

    Article  Google Scholar 

  • Nyaga J, Barrios E, Muthuri CW, Öborn I, Matiru V, Sinclair FL (2015) Evaluating factors influencing heterogeneity in agroforestry adoption and practices within smallholder farms in Rift Valley, Kenya. Agr Ecosyst Environ 212:106–118

    Article  Google Scholar 

  • Ofoegbu C, Ifejika CS (2017) Assessing rural peoples’ intention to adopt sustainable forest use and management practices in South Africa. J Sustain for 36:729–746

    Article  Google Scholar 

  • Rahn E, Liebig T, Ghazoul J, van Asten P, Läderach P, Vaast P, Sarmiento A, Garcia C, Jassogne L (2018) Opportunities for sustainable intensification of coffee agro-ecosystems along an altitudinal gradient on Mt. Elgon, Uganda. Agr Ecosyst Environ 263:31–40

    Article  Google Scholar 

  • Rogers EM (1983) Diffusion of innovations, 3rd edn. Free Press, Collier Macmillan, New York

    Google Scholar 

  • Sanou L, Savadogo P, Ezebilo EE, Thiombiano A (2017) Drivers of farmers’ decisions to adopt agroforestry: evidence from the Sudanian savanna zone, Burkina Faso. Renewable Agric Food Syst 34:116–133

    Article  Google Scholar 

  • Sassen M, Sheil D, Giller KE, Braak CJ (2013) Complex contexts and dynamic drivers: understanding four decades of forest loss and recovery in an East African protected area. Biol Cons 159:257–268

    Article  Google Scholar 

  • Sinclair FL (1999) A general classification of agroforestry practice. Agric Syst 46:161–180

    Google Scholar 

  • Ssebaggala GL, Kibwika P, Kyazze FB (2017) Contextual mismatch of interventions for reduction of postharvest losses in rice: farmer perceptions, practices and innovations in Eastern Uganda. ASD. https://doi.org/10.18805/asd.v37i2.7988

  • Tanellari E, Bosch D, Boyle K, Mykerezi E (2015) On consumers’ attitudes and willingness to pay for improved drinking water quality and infrastructure. Water Resour Res 51:47–57

    Article  Google Scholar 

  • Taylor S, Todd P (1995a) Decomposition and crossover effects in the theory of planned behaviour: a study of consumer adoption intentions. Int J Res Mark 12:137–155

    Article  Google Scholar 

  • Taylor S, Todd PA (1995b) Understanding information technology usage: a test of competing models. Inf Syst Res 6:144–176

    Article  Google Scholar 

  • UNEP (2014) Africa Mountains Atlas. United Nations Environment Programme (UNEP), Nairobi Kenya

  • Van Hulst FJ, Posthumus H (2016) Understanding (non-)adoption of conservation agriculture in Kenya using the reasoned action approach. Land Use Policy 56:303–314

    Article  Google Scholar 

  • Bucheli VJP, Bokelmann W (2017) Agroforestry systems for biodiversity and ecosystem services: the case of the Sibundoy Valley in the Colombian province of Putumayo. Int J Biodivers Sci Ecosyst Serv Manag 13:380–397

    Article  Google Scholar 

  • Von Carlowitz PG (1989) Agroforestry technologies and fodder production—concepts and examples. Agroforest Syst 9:1–16

    Article  Google Scholar 

  • Wambugu C, Place F, Franzel S (2011) Research, development and scaling-up the adoption of fodder shrub innovations in East Africa. Int J Agric Sustain 9:100–109

    Article  Google Scholar 

  • Wandji DN, Pouomogne V, Binam JN, Nouaga RY (2012) Farmer’s perception and adoption of new aquaculture technologies in the western highlands of Cameroon. Tropicultura 30:180–184

    Google Scholar 

  • Wauters E, Bielders C, Poesen J, Govers G, Mathijs E (2010) Adoption of soil conservation practices in Belgium: an examination of the theory of planned behaviour in the agri-environmental domain. Land Use Policy 27:86–94

    Article  Google Scholar 

  • Whitney CW, Tabuti JRS, Hensel O, Yeh C-H, Gebauer J, Luedeling E (2017) Homegardens and the future of food and nutrition security in southwest Uganda. Agric Syst 154:133–144

    Article  Google Scholar 

  • Zahid H, Din BH (2019) Determinants of intention to adopt e-government services in Pakistan: an imperative for sustainable development. Resources 8:128

    Article  Google Scholar 

  • Zubair M, Garforth C (2006) Farm level tree planting in Pakistan: the role of farmers’ perceptions and attitudes. Agroforest Syst 66:217–229

    Article  Google Scholar 

Download references

Acknowledgements

We thank the German Academic Exchange Service (DAAD), ICRAF and NARO for funding this research. We are grateful to the smallholder farmers who participated in the study for their cooperation and Susan Nansereko for her tremendous efforts during data collection.

Author information

Authors and Affiliations

  1. National Forestry Resources Research Institute (NaFORRI), P.O. Box 1752, Kampala, Uganda

    Fred Kalanzi & Isaac Kiyingi

  2. Department of Extension and Innovation Studies, Makerere University, P.O. Box 7062, Kampala, Uganda

    Fred Kalanzi, Florence Birungi Kyazze & Prossy Isubikalu

  3. Department of Forestry, Biodiversity and Tourism, Makerere University, P.O. Box 7062, Kampala, Uganda

    Lawrence Justus Baguma Orikiriza

  4. Faculty of Agriculture and Environmental Sciences, Muni University, P.O. Box 725, Arua, Uganda

    Clement Okia

  5. CSIR-Forestry Research Institute of Ghana, KNUST, P.O. Box 63, Kumasi, Ghana

    Reginald Tang Guuroh

Authors
  1. Fred Kalanzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Florence Birungi Kyazze
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Prossy Isubikalu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Isaac Kiyingi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lawrence Justus Baguma Orikiriza
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Clement Okia
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Reginald Tang Guuroh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fred Kalanzi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kalanzi, F., Kyazze, F.B., Isubikalu, P. et al. Influence of Socio-Technological Factors on Smallholder Farmers’ Choices of Agroforestry Technologies in the Eastern Highlands of Uganda. Small-scale Forestry 20, 605–626 (2021). https://doi.org/10.1007/s11842-021-09483-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11842-021-09483-8

Keywords

Search

Navigation