Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression

Vishwa Nath Maurya; Swammy Vashist; Diwinder Kaur Arora; Kamlesh Kumar Shukla

doi:doi:10.11648/j.ajbes.20150101.14

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Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression

Vishwa Nath Maurya, Swammy Vashist, Diwinder Kaur Arora, Kamlesh Kumar Shukla

Published in American Journal of Biological and Environmental Statistics (Volume 1, Issue 1)

Received: 6 June 2015 Accepted: 25 June 2015 Published: 1 July 2015

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Abstract

This paper aims to investigate institutional factor analysis influencing vegetable production in six small-scale vegetable projects in Alice town in the Nkonkobe Municipality of Eastern Cape of South Africa. An attempt has been made to amidst worsening poverty in the wider society to make out how vegetable production can contribute to enhancing food security. Seeking some insights on effectiveness of the agrarian reforms on small holder farmers in South Africa, key objectives of the present study was to identify and explore institutional factors that influence vegetable production. The data were drawn from 62 farmers in the projects investigated. Descriptive analysis and binary logistic regression were employed to analyze the data and explain the patterns of interactions among the identified institutional factors influencing vegetable production. The results of our study explored herein revealed that some institutional factors need to be addressed to enhance vegetable production. The binary logistic results show that both the formal and informal norms are important in vegetable production. The most significant institutional variables revealed by the analysis were attributes of the formation and organizational structure of the projects, land tenure, extension service, collective action in production and marketing. In addition, here our findings suggest that institutional change in respect to aforementioned variables and other complementary institutions such as contract farming and credit access can significantly contribute to increased, efficient and sustainable vegetable production.

Published in	American Journal of Biological and Environmental Statistics (Volume 1, Issue 1)
DOI	10.11648/j.ajbes.20150101.14
Page(s)	27-37
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Institutional Factor Analysis, Small-Scale Vegetable Projects, Purposive Sampling Design, Binary Logistic Regression Operation

References

[1]	Adebiyi M.A. and Obasa B.B., Institutional framework, interest rate policy and financing of Nigeria manufacturing sub-sector, 2004. Accessed10/04/2011Onlinehttp://www.tips.org.za/files/Institutional_Framework_Interes_Rate_Policy_Obasa_Adbiyi.PDF.
[2]	Brown L.R., In a search for a system model for decision making behaviour of first generation black commercial farmers in Border-keiskamahooek Region of Easter Cape Province. Unpublished PhD Thesis University of Fort Hare, 2000.
[3]	Chan Y.H., Multinomial logistic regression analysis. Singapore Medical Journal, Vol.46(6), pp.259-269, 2005.. Online: http://www.sma.org.sg/smj/4606/4606bs1.pdf. 02/04/2011
[4]	Chikazunga D., Collective action and smallholder farmers’ participation in agricultural markets.http://www.findavenue.co.za/AEASA/Presentations/Chikazunga%202.pdf. Accessed: 14/08/2010
[5]	Coase R.H., The Institutional structure of Production. The American Economic Review, Vol.82 (4), pp. 713-719, 1992.
[6]	Darroch M.A.G. and Clover T.A., Factors Affecting the Survival, Growth and Success of Small, Medium and Micro Agribusiness in KwaZulu-Natal, South Africa, International food and agribusiness management association world foodand agribusiness symposium, June 25-26, 2005, Chicago.U.S.A.
[7]	Fao, Approaches to linking producers to markets: A review of experiences to date. United Nations, Rome, 2007.
[8]	Fao, Rethinking public policy in agriculture: Lessons from distant and recent history. Cambridge, London, 2009.
[9]	Flom. P.L., Multinomial and ordinal logistic regression using proc logistic. Online: http://www.nesug.org/proceedings/nesug05/an/an2.pdf. Accessed on 09/04/2011
[10]	Greenberg S., Status report on Land and Agricultural policy in South Africa. Research report, Vol. 40, 2010.
[11]	Gujarati D., Essentials of Econometrics. MacGraw–Hill, New York, 1992.
[12]	Hoff K. and Stiglitz J., Imperfect Information and Rural Credit Markets – Puzzles and Policy Perspectives, World Bank Economic Review, Vol.4(3), pp.235–250, 1990
[13]	Hou Y. and Smith D.L., Informal Norms as a Bridge between Formal Rules and Outcomes of Government Financial Operations: Evidence from State Balanced Budget Requirements. Journal of Public Administration Research and Theory, Vol. 20(3), pp.655-678, 2009. Online: http://jpart.oxfordjournals.org/content/20/3/655.short. Accessed 16/07/2010
[14]	Ifpri, Collective action and property rights for sustainable development: Understanding Collective Action, 2006. Online:http://www.ifpri.org/sites/default/files/pubs/2020/focus/focus11/focus11_02.pdf. Accessed 01/04/2011
[15]	Insights on Institutional Change and Natural Resource Availability in Rural South Africa. University of Colorado at Boulder. Working paper.
[16]	Jacobs P., Market Development and Smallholder Farmers-A Selective Literature Survey, 2008. http://www.Scincedirect.com/science? Accessed on line on the 12/04/2010
[17]	Jari B. and Fraser G., An analysis of institutional and technical constraints influencing agricultural marketing amongst smallholder farmers in the Kat river valley, Eastern Cape, South Africa. African Journal of Agricultural research, Vol.11 (4), pp. 1129-1137, 2009.
[18]	Kirkland T., Hunter M., and Twine W., 2005. “The bush is no more”:
[19]	Kirsten J. and Satorius K., Linking agribusiness and small-scale farmers in developing countries: Is there a new role for contract farming? Development Southern Africa, Vol. 19(4), October 2002
[20]	Lal D., Culture, democracy and development: Role of formal and informal Institutions and development, 1999. Online: http://www.imf.org/External/pubs/FT/seminar/1999/reforms/lal.htm. Accessed 23 August 2010
[21]	Leedy P.D., and Ormrod J.E., Practical research. Planning and design. Pearson Merrill prentice hall-Ohio. USA, 2005
[22]	Liao F.T., Interpreting Probability Models. Sage Publications Inc, New Delhi, 1994.
[23]	Long J.S., Regression Models for Categorical and Limited DependentVariables: Advanced Quantitative Techniques in the Social Sciences, Volume 7. Sage Publications Inc, Thousand Oaks, 1997.
[24]	Magingxa L., Zerihun G., Alemu H.D. and Van Schalkwyk, Factors influencing access to produce markets for smallholder irrigators in South Africa, Development southern Africa, Vol.26 (1), pp.47-58, 2009.
[25]	Makosholo M., Comparative advantage of Long-term crops in Lesotho. MSc Thesis. University of Free State, South Africa, 2005.
[26]	Maurya V.N., Arora D.K., Vashist S., Sharma R.S., Maurya A.K., and Madaki Umar Yusuf, Empirical study for academic assessments and records management of contemporary tertiary institutions using stratified and proportional sampling techniques, American Journal of Modeling and Optimization, Special Issue: Review and Future Scope of Computational Modeling, Simulation and Optimization Techniques in Engineering Science and Industrial Technology, Science and Education Publishing, New York, USA, Vol. 3, 2015, ISSN (Print) 2333-1143, ISSN (Online) 2333-1267
[27]	Maurya V.N., Jaggi C.K., Singh B., Arneja C.S., Maurya A.K. and Arora D.K., Empirical analysis of work life balance policies and its impact on employee’s job satisfaction and performance: descriptive statistical approach, American Journal of Theoretical and Applied Statistics, Special Issue: Scope of Statistical Modeling and Optimization Techniques in Management and Decision Making Process, Science Publishing Group, USA, Vol.4(2-1), pp.33-43, 2015, ISSN: 2326-9006
[28]	Maurya V.N., Misra R.B., Jaggi C.K. and Maurya A.K., Performance analysis of powers of skewness and kurtosis based multivariate normality tests and use of extended Monte Carlo simulation for proposed novelty algorithm, American Journal of Theoretical and Applied Statistics, Special Issue: Scope of Statistical Modeling and Optimization Techniques in Management and Decision Making Process, Science Publishing Group, USA, Vol.4(2-1), pp.11-18, 2015, ISSN: 2326-9006
[29]	Maurya V.N., Misra R.B., Jaggi C.K., Arneja C.S., Maurya A.K. and and Maharaj Yogesh, Comparative analysis for the maximum precision using systematic and stratified random sampling techniques, Edited Book on Dynamics of Business through Management, Engineering, Science & Technology, Mohit Publications, New Delhi, India, 2014
[30]	Maurya V.N., Misra R.B., Jaggi C.K., Arneja C.S., Sharma R.S., Maurya A.K., Design and estimate of the optimal parameters of adaptive control chart model using Markov Chains technique, American Journal of Theoretical and Applied Statistics, Special Issue: Scope of Statistical Modeling and Optimization Techniques in Management and Decision Making Process, Science Publishing Group, USA, Vol.4(2-1), pp.19-26, 2015, ISSN: 2326-9006
[31]	Maurya V.N., Misra R.B., Jaggi C.K., Vashist S., Sharma Rama Shanker, Arneja C.S., Maurya A.K., and Arora D.K., Impact of some significant factors for intern’s job satisfaction and performance using t-test and ANOVA method, American Journal of Modeling and Optimization, Special Issue: Review and Future Scope of Computational Modeling, Simulation and Optimization Techniques in Engineering Science and Industrial Technology, Science and Education Publishing, USA, Vol.3, 2015, ISSN (Print) 2333-1143, ISSN (Online) 2333-1267
[32]	Maurya V.N., Sharma R.S., Aljebori S.T.H, Maurya A.K., and Arora D.K., Correlation analysis between the corporate governance and financial performance of banking sectors using parameter estimation, American Journal of Theoretical and Applied Statistics, Special Issue: Scope of Statistical Modeling and Optimization Techniques in Management and Decision Making Process, Science Publishing Group, USA, Vol.4(2-1), pp.27-32, 2015, ISSN: 2326-9006
[33]	Maurya V.N., Singh Bijay, Reddy N., Singh V.V., Maurya A.K., Arora D.K., Cost-effective perspective and scenario development on economic optimization for multiple-use dry-season water resource management, American Open Journal of Agricultural Research, Academic & Scientific Publishing, New York, USA, Vol. 2(1), pp. 1-21, 2014, ISSN:2333-2131
[34]	Maurya V.N., Yusuf M.U., Singh V.V. and Modu B., The prevalence of broncho pulmonary dysplasia among infants using logistic regression: empirical study of UMTH Maiduguri and UDTH Sokoto in Nigeria, American Journal of Modeling and Optimization, Special Issue: Review and Future Scope of Computational Modeling, Simulation and Optimization Techniques in Engineering Science and Industrial Technology, Science and Education Publishing, USA, Vol.3, 2015
[35]	Mohammed M.A. and Ortmann G.F.,.Factors influencing Adoption of Livestock Insurance by Commercial Dairy Farmers in Three Zobatat of Eritrea.Agrekon, Vol.44(2), pp. 172-186, 2005.
[36]	Monde N., Household Food Security in Rural areas of Central Eastern Cape. PhD thesis, University of Fort Hare, 2003.
[37]	Motteux N., The Development and Co-ordination of Catchment Fora through the empowerment of Rural Communities, Catchment Research Group. WRC Report K5/1014. Water Res. Commission, Pretoria, 2001.
[38]	Nel E. and Davies J., Farming against the odds: an examination of the challenges facing farming and rural development in the Eastern Cape province of South Africa. Department of Geography, Rhodes University, Grahamstown. pp.22, 1999.
[39]	Nkonkobe Municipality,.Nkonkobe Integrated Development Programme, 2009.
[40]	North D., Institutions, institutional change and economic performance. Cambridge University Press, Cambridge, 1993.
[41]	Obi, A. Unlocking Markets to smallholder: Lessons from South Africa. Wageningen, Netherland, 2011.
[42]	Randela R., Integration of emerging cotton farmers into the commercial agricultural economy. Unpublished PhD thesis, University of the Free State, Bloemfontein, 2005.
[43]	Salami A., Kamara A.B. and Brixiova Z., Smallholder Agriculture in East Africa: Trends, constraints and opportunities. The working paper, 2010. Online: http://www.afdb.org/fileadmin/uploads/afdb/Documents/Publications/WORKING%20105%20%20PDF%20d.pdf. Accessed on 06/05/2011
[44]	Schultz T., Transformation of Traditional Agriculture. New Haven Yale University press, 1964.
[45]	Seibel H.D., Agricultural Development Banks: Close them or reform them. Finance andDevelopment, Vol.37(2), pp.1-4, 2000. Online: http://www.imf.org/external/pubs/ft/fandd/2000/06/pdf/seibel.pdf. Accessed on 12/08/2011
[46]	Swinnen J.F.M. and Gow H.R., Agricultural credit problems and policies during the transition to a market economy in Central Eastern Europe. Food Policy, Vol.24( 1 ), pp. 21-47, 1999.
[47]	WFP, Fighting hunger worldwide: 3 ways to help smallholder farmers help themselves, 2009. Online: http://www.wfp.org/stories/3-ways-help-smallholder-farmers-help-themselves. Accessed on 26/08/2010
[48]	Williamson O.E. The New Institutional Economics: Taking Stock, Looking Ahead. Journal of Economic Literature, Vol.38 (3), pp.595-613,2000. http://www.jstor.org/stable/2565421?seq=3. Accessed on the 20/10/2011.

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APA Style

Vishwa Nath Maurya, Swammy Vashist, Diwinder Kaur Arora, Kamlesh Kumar Shukla. (2015). Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression. American Journal of Biological and Environmental Statistics, 1(1), 27-37. https://doi.org/10.11648/j.ajbes.20150101.14

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ACS Style

Vishwa Nath Maurya; Swammy Vashist; Diwinder Kaur Arora; Kamlesh Kumar Shukla. Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression. Am. J. Biol. Environ. Stat. 2015, 1(1), 27-37. doi: 10.11648/j.ajbes.20150101.14

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AMA Style

Vishwa Nath Maurya, Swammy Vashist, Diwinder Kaur Arora, Kamlesh Kumar Shukla. Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression. Am J Biol Environ Stat. 2015;1(1):27-37. doi: 10.11648/j.ajbes.20150101.14

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@article{10.11648/j.ajbes.20150101.14,
  author = {Vishwa Nath Maurya and Swammy Vashist and Diwinder Kaur Arora and Kamlesh Kumar Shukla},
  title = {Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression},
  journal = {American Journal of Biological and Environmental Statistics},
  volume = {1},
  number = {1},
  pages = {27-37},
  doi = {10.11648/j.ajbes.20150101.14},
  url = {https://doi.org/10.11648/j.ajbes.20150101.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbes.20150101.14},
  abstract = {This paper aims to investigate institutional factor analysis influencing vegetable production in six small-scale vegetable projects in Alice town in the Nkonkobe Municipality of Eastern Cape of South Africa. An attempt has been made to amidst worsening poverty in the wider society to make out how vegetable production can contribute to enhancing food security. Seeking some insights on effectiveness of the agrarian reforms on small holder farmers in South Africa, key objectives of the present study was to identify and explore institutional factors that influence vegetable production. The data were drawn from 62 farmers in the projects investigated. Descriptive analysis and binary logistic regression were employed to analyze the data and explain the patterns of interactions among the identified institutional factors influencing vegetable production. The results of our study explored herein revealed that some institutional factors need to be addressed to enhance vegetable production. The binary logistic results show that both the formal and informal norms are important in vegetable production. The most significant institutional variables revealed by the analysis were attributes of the formation and organizational structure of the projects, land tenure, extension service, collective action in production and marketing. In addition, here our findings suggest that institutional change in respect to aforementioned variables and other complementary institutions such as contract farming and credit access can significantly contribute to increased, efficient and sustainable vegetable production.},
 year = {2015}
}

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TY  - JOUR
T1  - Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression
AU  - Vishwa Nath Maurya
AU  - Swammy Vashist
AU  - Diwinder Kaur Arora
AU  - Kamlesh Kumar Shukla
Y1  - 2015/07/01
PY  - 2015
N1  - https://doi.org/10.11648/j.ajbes.20150101.14
DO  - 10.11648/j.ajbes.20150101.14
T2  - American Journal of Biological and Environmental Statistics
JF  - American Journal of Biological and Environmental Statistics
JO  - American Journal of Biological and Environmental Statistics
SP  - 27
EP  - 37
PB  - Science Publishing Group
SN  - 2471-979X
UR  - https://doi.org/10.11648/j.ajbes.20150101.14
AB  - This paper aims to investigate institutional factor analysis influencing vegetable production in six small-scale vegetable projects in Alice town in the Nkonkobe Municipality of Eastern Cape of South Africa. An attempt has been made to amidst worsening poverty in the wider society to make out how vegetable production can contribute to enhancing food security. Seeking some insights on effectiveness of the agrarian reforms on small holder farmers in South Africa, key objectives of the present study was to identify and explore institutional factors that influence vegetable production. The data were drawn from 62 farmers in the projects investigated. Descriptive analysis and binary logistic regression were employed to analyze the data and explain the patterns of interactions among the identified institutional factors influencing vegetable production. The results of our study explored herein revealed that some institutional factors need to be addressed to enhance vegetable production. The binary logistic results show that both the formal and informal norms are important in vegetable production. The most significant institutional variables revealed by the analysis were attributes of the formation and organizational structure of the projects, land tenure, extension service, collective action in production and marketing. In addition, here our findings suggest that institutional change in respect to aforementioned variables and other complementary institutions such as contract farming and credit access can significantly contribute to increased, efficient and sustainable vegetable production.
VL  - 1
IS  - 1
ER  -

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Author Information

Vishwa Nath Maurya

Department of Applied Mathematics & Statistics, School of Science & Technology, The University of Fiji, Lautoka, Fiji
Swammy Vashist

Department of Accounting & Finance, Dilla University, Gedeo, Ethiopia
Diwinder Kaur Arora

Group Centre, Central Reserve Police Force, Guwahati, Assam, Ministry of Home Affairs, Govt. of India
Kamlesh Kumar Shukla

Department of Management, Adama Science and Technology University, Adama, Ethiopia

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APA Style

Vishwa Nath Maurya, Swammy Vashist, Diwinder Kaur Arora, Kamlesh Kumar Shukla. (2015). Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression. American Journal of Biological and Environmental Statistics, 1(1), 27-37. https://doi.org/10.11648/j.ajbes.20150101.14

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ACS Style

Vishwa Nath Maurya; Swammy Vashist; Diwinder Kaur Arora; Kamlesh Kumar Shukla. Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression. Am. J. Biol. Environ. Stat. 2015, 1(1), 27-37. doi: 10.11648/j.ajbes.20150101.14

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AMA Style

Vishwa Nath Maurya, Swammy Vashist, Diwinder Kaur Arora, Kamlesh Kumar Shukla. Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression. Am J Biol Environ Stat. 2015;1(1):27-37. doi: 10.11648/j.ajbes.20150101.14

Copy | Download

@article{10.11648/j.ajbes.20150101.14,
  author = {Vishwa Nath Maurya and Swammy Vashist and Diwinder Kaur Arora and Kamlesh Kumar Shukla},
  title = {Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression},
  journal = {American Journal of Biological and Environmental Statistics},
  volume = {1},
  number = {1},
  pages = {27-37},
  doi = {10.11648/j.ajbes.20150101.14},
  url = {https://doi.org/10.11648/j.ajbes.20150101.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbes.20150101.14},
  abstract = {This paper aims to investigate institutional factor analysis influencing vegetable production in six small-scale vegetable projects in Alice town in the Nkonkobe Municipality of Eastern Cape of South Africa. An attempt has been made to amidst worsening poverty in the wider society to make out how vegetable production can contribute to enhancing food security. Seeking some insights on effectiveness of the agrarian reforms on small holder farmers in South Africa, key objectives of the present study was to identify and explore institutional factors that influence vegetable production. The data were drawn from 62 farmers in the projects investigated. Descriptive analysis and binary logistic regression were employed to analyze the data and explain the patterns of interactions among the identified institutional factors influencing vegetable production. The results of our study explored herein revealed that some institutional factors need to be addressed to enhance vegetable production. The binary logistic results show that both the formal and informal norms are important in vegetable production. The most significant institutional variables revealed by the analysis were attributes of the formation and organizational structure of the projects, land tenure, extension service, collective action in production and marketing. In addition, here our findings suggest that institutional change in respect to aforementioned variables and other complementary institutions such as contract farming and credit access can significantly contribute to increased, efficient and sustainable vegetable production.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Institutional Factor Analysis Influencing Production in Six Small-Scale Vegetable Projects Using Purposive Sampling Design and Binary Logistic Regression
AU  - Vishwa Nath Maurya
AU  - Swammy Vashist
AU  - Diwinder Kaur Arora
AU  - Kamlesh Kumar Shukla
Y1  - 2015/07/01
PY  - 2015
N1  - https://doi.org/10.11648/j.ajbes.20150101.14
DO  - 10.11648/j.ajbes.20150101.14
T2  - American Journal of Biological and Environmental Statistics
JF  - American Journal of Biological and Environmental Statistics
JO  - American Journal of Biological and Environmental Statistics
SP  - 27
EP  - 37
PB  - Science Publishing Group
SN  - 2471-979X
UR  - https://doi.org/10.11648/j.ajbes.20150101.14
AB  - This paper aims to investigate institutional factor analysis influencing vegetable production in six small-scale vegetable projects in Alice town in the Nkonkobe Municipality of Eastern Cape of South Africa. An attempt has been made to amidst worsening poverty in the wider society to make out how vegetable production can contribute to enhancing food security. Seeking some insights on effectiveness of the agrarian reforms on small holder farmers in South Africa, key objectives of the present study was to identify and explore institutional factors that influence vegetable production. The data were drawn from 62 farmers in the projects investigated. Descriptive analysis and binary logistic regression were employed to analyze the data and explain the patterns of interactions among the identified institutional factors influencing vegetable production. The results of our study explored herein revealed that some institutional factors need to be addressed to enhance vegetable production. The binary logistic results show that both the formal and informal norms are important in vegetable production. The most significant institutional variables revealed by the analysis were attributes of the formation and organizational structure of the projects, land tenure, extension service, collective action in production and marketing. In addition, here our findings suggest that institutional change in respect to aforementioned variables and other complementary institutions such as contract farming and credit access can significantly contribute to increased, efficient and sustainable vegetable production.
VL  - 1
IS  - 1
ER  -

Copy | Download