Book chapter · 2021
Contemporary Usage of Farm Management Information Systems in Nigeria
In Recent Developments in Individual and Organizational Adoption of ICTs, pp. 82–95, IGI Global · Published
Summary
What question does this chapter answer?
Which demographic factors—such as age, gender, marital status, education, language, land size and software experience—predict farmers’ e-adoption of farm management information systems (FMIS) in central Nigeria?
What did the chapter find?
In a survey of 105 FMIS-using farm owners, managers and laborers in the Jos Plateau region of central Nigeria, only marital status (Rho = −.225, p = .026), gender and language were correlated with FMIS e-adoption. A discriminant model using these three factors was significant (Wilks’ Lambda = 0.892, χ²(3) = 10.669, p = .014) and was reported to classify 100% of participants, with marital status the most important predictor.
Why does it matter?
Agriculture contributes over 24% of Nigeria’s GDP and employs 68% of the labor force, yet farmers are not adopting FMIS to improve productivity. The authors state that the results should generalize to other rural farm decision makers in Nigeria and suggest males were more influential in FMIS use on farms, while widowed women left to run farms after Boko Haram violence were less likely to adopt FMIS.
This study is part of the evidence overview What is holding back Nigerian agriculture and farm technology adoption? Evidence from extension workers and farmer surveys
Key findings
- The study surveyed 105 farm owners, farm managers and laborers using farm management information systems (FMIS) on farms of 0.5–40 hectares in the Jos Plateau region of Plateau State, central Nigeria, in March 2018.
- The Nigerian FMIS sample had a mean age of 31.5 years (SD = 7.9), was 51% female and 49% male, 56% married, and farmed an average of 3.4 hectares with an average of 2 years of FMIS software experience.
- The FMIS e-adoption construct in the Nigeria study showed high internal consistency, with a Cronbach’s alpha of 0.955, and a mean adoption intention of 4.5 (SD = 0.82) on a 1–5 scale.
- Of seven demographic factors tested among Nigerian farmers, only marital status (Rho = −.225, p = .026), gender (Rho = +0.151, p = .051) and language (p = .052) were correlated with FMIS e-adoption; age, education, land size and software experience were not.
- A discriminant analysis using marital status, gender and language to predict FMIS e-adoption among Nigerian farmers was significant (eigenvalue = 0.121, canonical correlation = +0.328, Wilks’ Lambda = 0.892, χ²(3) = 10.669, p = .014) and was reported to classify 100% of participants correctly.
- Marital status was the most important predictor of FMIS e-adoption among the Nigerian farmers (standardized coefficient +0.838, structure loading +0.810), followed by gender (+0.368) and language (−0.426).
- The authors interpret the Nigerian results as indicating that males were more likely to adopt FMIS software, and that widowed women left to run farms after their husbands were killed by Boko Haram were less likely to adopt FMIS.
Source: Vajjhala et al. (2021), In Recent Developments in Individual and Organizational Adoption of ICTs, pp. 82–95, IGI Global. DOI: 10.4018/978-1-7998-3045-0.ch005
Chapter at a glance
| Research question | What demographic factors predict e-adoption of farm management information systems by farmers in central Nigeria? |
|---|---|
| Design | Positivist, predictive correlational survey design using structured, interviewer-assisted questionnaires. |
| Sample | 105 farm owners, farm managers and laborers on FMIS-using farms (0.5–40 hectares) in the Jos Plateau, Plateau State, selected by stratified random sampling in March 2018. |
| Methods | Cronbach’s alpha, Pearson and Spearman correlation, and discriminant analysis in SPSS 25; survey offered in English, Hausa or Berom. |
| Main result | Marital status, gender and language predicted FMIS e-adoption (Wilks’ Lambda = 0.892, p = .014); marital status was the strongest predictor (standardized coefficient +0.838). |
| Implication | Demographic factors, especially marital status and gender, shape FMIS adoption among rural Nigerian farmers; replication with larger samples in other regions is recommended. |
| Citation | Vajjhala et al. (2021) · DOI 10.4018/978-1-7998-3045-0.ch005 |
Abstract
Agriculture is a critical sector in the Nigerian economy, contributing significantly to GDP as well as employment generation. Agricultural technology has evolved substantially over the last decade with significant advancements in farm management information systems (FMIS) as well as agricultural information systems (AIS). FMIS have evolved from addressing simple production tasks to handling complex across multifunctional sectors in farming enterprises. However, the adoption rates of FMIS have been low in Nigeria. In this chapter, the contemporary usage of farm management information systems in central Nigeria is examined, and the various constraints leading to the low adoption rates are explored. In this study, the factors impacting the FMIS adoption by rural farmers in central Nigeria were examined. The findings of this study indicated that some of the demographic factors were influencing the FMIS adoption by rural farmers in central Nigeria. The results of this study in this chapter should help policymakers in framing policies intended to improve FMIS adoption rates in Nigeria.
Abstract as published in Recent Developments in Individual and Organizational Adoption of ICTs.
Key terms
- Farm management information systems (FMIS)
- A planned system of collecting, processing, storing, and disseminating data in a form required to carry out farm-related operational functions (the chapter’s definition, after Sørensen et al., 2010).
- E-adoption
- The acceptance and use of electronic means for accomplishing one or more tasks (the chapter’s definition).
- Discriminant analysis
- A statistical technique that uses several independent factors to predict membership in the categories of a single categorical outcome, here adopting versus not adopting FMIS.
Limitations
- The authors suggest the study be replicated with larger sample sizes using rural farmers from other regions in Nigeria and extended to other developing countries.
How to cite
Vajjhala, N. R., Strang, K. D., & Bitrus, N. S. (2021). Contemporary Usage of Farm Management Information Systems in Nigeria. In O. Yildiz (Ed.), Recent Developments in Individual and Organizational Adoption of ICTs (pp. 82–95). IGI Global. https://doi.org/10.4018/978-1-7998-3045-0.ch005
BibTeX
@incollection{vajjhala2021farm,
title = {Contemporary Usage of Farm Management Information Systems in Nigeria},
author = {Vajjhala, Narasimha Rao and Strang, Kenneth David and Bitrus, Nankyer Sarah},
booktitle = {Recent Developments in Individual and Organizational Adoption of ICTs},
editor = {O. Yildiz},
pages = {82--95},
year = {2021},
publisher = {IGI Global},
doi = {10.4018/978-1-7998-3045-0.ch005},
url = {https://doi.org/10.4018/978-1-7998-3045-0.ch005}
}Related research