In:
Journal of Asian and African Studies, SAGE Publications
Abstract:
There is a rarity of research about technology management in the solar energy industry in Rwanda and very little analysis is available on the effectiveness of the technology used in solar home systems (SHSs). Using a binary logistic regression to primary data collected through Kobo Collect, this study assesses the factors that are involved in SHS business in Rwanda. The findings reveal a difference in successfully collecting money from customers who purchase SHSs on an installment payment plan concerning the type of SHS (i.e. pay-as-you-go (PAYG) and non-pay-as-you-go (non-PAYG)). In terms of the odds ratio concept, a statistical interpretation was provided. If the customer has a non-PAYG SHS, getting a reminder from the solar energy company’s agent will increase by 9.52 times. That means, it is 9.52 times higher for the non-PAYG SHS as compared to a customer with PAYG SHS. The results also show that the multicollinearity assumptions for the economic, social, technological, and management models are not violated and are optimal because each of the variance inflation factors (VIFs) was close to unity. However, only the socialization predictors were not significant enhancements in the goodness-of-fit relative to the intercept-only model. The Nagelkerke R 2 indicates only an average (49.5%) relationship between the prediction and grouping of the modified economic pricing model. The Hosmer–Lemeshow measures indicate that the models in this research are optimal and good fits for the data studied. Furthermore, the predicted success overall performance for the economic, social, technological, and managerial models was 73.2% on average. The Wald criterion equally demonstrated that only the monthly installment amount (with and without outliers), type of SHS, and payment channel made significant contributions to the prediction optimization problem. Therefore, the solar energy companies in Rwanda need to rely on the findings of studies like this to successfully manage customers’ accounts optimally.
Type of Medium:
Online Resource
ISSN:
0021-9096
,
1745-2538
DOI:
10.1177/00219096241230491
Language:
English
Publisher:
SAGE Publications
Publication Date:
2024
detail.hit.zdb_id:
2040418-9
SSG:
0
SSG:
6,24
SSG:
6,31
SSG:
6,23
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