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The aim
This study aimed to assess factors associated with the Sustainability of VSLAs amidst Covid-19 and its impacts on households’ income levels.
Study design
This study used a quantitative method design to extrapolate in-depth information about the topic under study [30, 31]. In this study, we used an online cross-sectional survey. The study was conducted in Malawi, Africa. Malawi is located in the southern part of Africa, bordering countries like Zambia, Tanzania, and Mozambique [32, 33]. It is one of the least developing countries in the world where a majority of its population still faces hunger, malnutrition, and lives under the poverty line [15, 34, 35], and depend mostly on agriculture for business and feeding the population [36]. In Malawi, the study was specifically conducted in Mzuzu city, which is located in the northern part and the city has an estimated total population of 221, 272, and a land area of 143.8 square kilometers as of 2019. The study area is politically divided into 14 wards, namely; Chibanja, Chibavi West, Chibavi East, Chiputula, Jombo-Kaning’ina, Katawa, Lupaso-Nkhorongo, Luwinga, Masasa, Mchengautuwa East, Mchengautuwa West, Mzilawaingwe, Zolozolo East, and Zolozolo West) as shown in Fig. 1. According to recent research, Mzuzu City is one of Malawi’s fastest-growing cities, primarily to its social-economic activity, with most of its inhabitants dependend on agriculture, business, and working as civil servants in many of the city’s governmental and non-governmental organizations [37]. Given these conditions, it was critical to conduct this study in this city to examine the impacts of Covid-19 that might have a negative influence on the people’s socio-economic status.
Study Area of Mzuzu. Source: Authors 2021
Data collection procedures
We collected data from various VSLAs members operating within Mzuzu City. The data collection exercise was done between November 2020 and January 2021. We recruited and trained a team of four research assistants, who were guided on the aims and how to conduct the study. These research assistants helped to identify VSLAs groups and their members and facilitated the collection of the online survey headed by Mr. Zolo (as head of the Research assistants). The questionnaire was sent to the participants using Facebook, WhatsApp, and email due to the Covid-19 gathering restrictions, as the study was conducted when some social distance measures were being enforced in Malawi. The targeted respondents identified were forwarded the questionnaires links with assistance from the recruited research assistants.
Inclusion and exclusion criteria
All members of VSLAs that were operating within Mzuzu localities, who were below 18 years old were excluded from the survey. To ensure that the respondents were from that country and city, a space was provided in the questionnaire instrument where the respondent stated their country and city of residence. All those who indicated outside the study areas were excluded.
Population, sample size, and technique
The study recruited the respondents that were members of VSLAs in the designated study area. A snowball and respondent-driven sampling technique was used to select the area and determine the sample population. We employed this technique based on the following reasons. First, it was easy to access data due to the researchers’ connections with people associated with VSLAs in the selected country. Second, due to the impact of Covid-19, it is not easy to collect the data physically, taking into consideration the social distance measures in place in all countries [38,39,40].
We recruited 402 participants in the survey based on the inclusion and exclusion criteria. We employed a sampling calculation used by Yamane, with a 95% Confidence Level and, P = 0.05 [41], N = Total Population of Mzuzu City = 221,272 [37].
$$x=frac{N}{1+N{(e)}^{2}}$$
Which gave us 399, as the minimum required number of participants.
Questionnaire’ design
The questionnaire had three sections.
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i.
Demographic data
The first sections captured the social demographic data of the VSLAs members which include; the respondent’s gender, age group, occupation, education level, the status of the household head, and the number of people in the house of which twere measured in the category, and coded in binary form (Table 1).
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ii.
Impact of Covid-19 on Income
The second part of the questionnaire captured data on the impact of Covid-19 on the income of the participants. We asked the respondents to indicate the category of income that they earn per month before and during the outbreak of Covid-19. The income was put in categories/groups of three income bands or levels. The first one was those falling under Less than MK5,000, then those under or above MK5,000 but less than MK10,000, and finally those above MK10,000 (Table 1).
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iii.
Performance and sustainability indicators
The third part of the questionnaire captured the data on the performance which predicted the sustainability of the VSLAs amid Covid-19 based on the literature. Members were asked questions regarding the impacts of Covid-19 on; loan repayment in time, loan obtainment frequency, shared contributions in time or not, and if the members were meeting. All variables were categorical and were measured in binary form (Table 1).
Validity and reliability
A pilot study was conducted to pre-test the instruments before the actual collection of data which involved 43 respondents comprising VSLAs members, Masters’ and Ph.D. students. The validity and reliability of the instrument were tested by sending the instrument to experts for comments before actual data collection. The research instrument was tested by using Cronbach’s Alpha in SPSS and was found to be 0.8.
Ethical clearance
Ethical clearance of this study was reviewed and approved by the School of Economics and Management of Yangtze University (Approval number REF/YU/2020/08 (Fig. 3)) and Mzuzu City Council (Approval letter reference number MCC/dated on August 12, 2020 (Fig. 4)). Further, the researchers observed and followed the 1964 Helsinki Declaration under conducts of research involving human beings. Participation in the survey was voluntary and the participants gave their informed consent to this questionnaire before completion.
Data analysis
After collecting the data using the google form, we coded it in Microsoft Excel and later imported it into SPSS Version 23 for analysis. We presented the results of the descriptive statistics using frequency tables, graphs, and charts. The Chi-Square test was performed to determine associations between socio-demographic variables and other variables. P-value was statistically significant at p < 0.05. Lastly, due to the nature of our dependent variables, a binary logistic regression model was performed.
Econometric model specification
This was used to address our second research question: to predict the factors associated with the sustainability of VSLAs. We used Certainty of Future of VSLAs as our dependent variable, which was coded or characterized as a two-categorical variable. The coding was that if the VSLAs members attest that they have certainty in the future and sustainability of VSLAs regarding the current situation of Covid-19, then the value given was 1; otherwise, 0. Therefore, the dichotomy of the dependent variables directed and suggested to us used the binary logistic regression model, which was deemed fit as used by other scholars[14, 42, 43].
In this study, a logistic regression model, the dichotomous variable is defined as,
$$y={int }_{0}^{1}whereas 1=The Presence of the Characteristics 0=The absence of the Characteristics$$
whereas the odd is defined as,
$$Odds=frac{p}{p-1}=frac{The Probability of the Presence of the characteiricts}{The probability of the absence of the characteristics}$$
whereas the definition of the logit model is like this,
(Logitleft(pright)={beta }_{0}+{beta }_{1}{X}_{1}+{beta }_{2}{X}_{2}+{beta }_{3}{X}_{3}+cdots +{beta }_{k}{X}_{k})[43, 44]
Where the probability of the presence of the characteristic of interest is represented with p. The logit transformation is defined as the log of odds.
(mathrm{log}left(frac{p}{1-p}right)=Logitleft(pright)={beta }_{0}+{beta }_{1}{X}_{1}+{beta }_{2}{X}_{2}+{beta }_{3}{X}_{3}+dots +{beta }_{k}{X}_{k}+e)[43, 44]
Whereas;
({beta }_{0})= Constant,
({beta }_{1}-{beta }_{k})= are the coefficients of logistic regression,
({X}_{1}-{X}_{k})= are independent explanatory variables, and.
(e)= is an error term.
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