Does Mobile Money Adoption Increase Informal Business Performance in Zambia?

Abstract

Innovation in digital technology has changed the way firms make business. The objective of this paper is to analyse the effect of mobile money adoption on the performance of informal businesses in Zambia. The data are from the 2019 Zambia Informal Sector Business Survey of the World Bank Group with a sample of 914 firms. An instrumental variable bivariate probit model was used to analyse the data. We find that mobile money use helps significantly improve informal business performance. The finding is robust for different purposes of mobile money use. These results can be attributed to the lower transaction costs and the improved liquidity related to the use of mobile money financial services. An important policy implication is that the use of digital technologies such as mobile money could be a key element for improving informal business performance.

Introduction

For recent decades, shadow economy considerably increases and has been a research subject of growing interest among scholars and policymakers (Medina and Schneider, 2019; Beck et al., 2018; Islam et al., 2018; Bosire and Ntale, 2018; La Porta and Shleifer, 2014). This sector is prevailing in developing countries. According to Medina and Schneider (2019), while informal activities account for only 20% of GDP in OECD countries, they occupy a much larger place in Latin American and sub-Saharan African countries, with a share of 38% and 39% of GDP, respectively. In Zambia, as in most African countries, the informal sector is the largest provider of employment. According to ILO (2018), this sector employs about 72% of wage earners in sub-Saharan Africa; this proportion is even higher in Zambia where the informal sector employs about 90% of wage earners.

Guérineau and Jacolin (2014) find that most African populations operate on the margins of the formal financial system and consequently do not have a debit or credit account to carry out their various economic or financial transactions. Thus, most of the time, payments for goods and services, whether legal or not and regardless of the amount, are made in cash. Firms are also faced with limited access to financing from financial and banking institutions, a fact that is often related to their inability to provide financial statements or collateral for credit (Beck et al., 2018; Gosavi, 2017). Recent developments and innovations in information and communication technologies have provided alternative solutions to this situation. Indeed, they have not only facilitated communication between individuals but also access to information on different markets and services. This is the case with mobile money services, where accounts are linked to a telephone number provided by an operator and allow for different types of financial transactions like money transfers or savings (Islam et al., 2018; Mbiti and Weil, 2016; Onyango et al., 2014; Jack and Suri, 2014).

Several authors have shown that mobile money adoption improves business performance (Nyaga and Okonga, 2014; Kirui and Onyuma, 2015; Mararo and Ngahu, 2017). The results of this work have led to the formulation of policies to facilitate the diffusion, adoption and use of mobile money services.

However, an important limitation is that most of these studies focus on formal businesses. The objective of this paper is therefore to fill this gap by estimating the impact of mobile money adoption on the performance of informal businesses in Zambia, a country where the vast majority of micro and small enterprises operate in the informal sector.

This study is of twofold interest. First, to the best of our knowledge, this work is the first to analyse empirically the adoption of mobile money on the performance of Zambian informal businesses. Second, we model mobile money adoption using a representative sample survey. The few empirical studies conducted to date on this topic have typically relied on small, non-representative samples at the city or national level (see, for example, Chale and Mbamba, 2015; Bosire and Ntale, 2018).

To address this issue, we use the 2019 Zambia Informal Sector Business Survey Dataset. Results from instrumental variable probit model allow us to show a significantly positive impact of mobile money adoption on informal business performance.

The remainder of the paper is organized as follows: the second section provides a theoretical background for the study of the relationship between mobile money adoption and informal business performance; the third section presents the data and the estimation methodology adopted; the fourth section reports and discusses the results; and the fifth section concludes.

Literature Review

Mobile money is a money transfer and storage instrument using the messaging system initially developed in Kenya and then spread to several developing countries (Beck et al., 2018). It is emerging as a tool of choice for the financial system with the development of new technologies. Access to digital finance would reduce information asymmetry and transaction costs, facilitate access to financial services and optimize the allocation of resources through the market (Aron, 2018; Jack and Suri, 2014). The experiment with mobile money as a payment instrument is gaining momentum after Safaricom developed the M-Pesa application to facilitate money transfers between individuals in 2007 in Kenya. Many African countries as Zambia have also adopted mobile money technologies for various services such as cash-outs, mobile transfers, mobile saving or bill payments. According to FinScope 2020 Survey Report, mobile money transfer services use by Zambian adults increased to 48.7% in 2020 compared to 36.8% in 2015. The use of cash has been a long held custom, and most of SMEs conduct their transactions using cash which can be a scarce resource while mobile money appears to be an efficient way to move money and alleviate transaction-related challenges (Nan and Park, 2022; Aron, 2018; Jack and Suri, 2014).

The use of mobile money makes financial services much more convenient, secure and accessible compared to traditional financial services (Mbiti and Weil, 2016; Aron, 2018). This has promoted its adoption not only by individuals but also by businesses. There are different reasons why businesses may use mobile money accounts in their operations: depositing money received from customers and made to suppliers, employees and bill payments, withdrawing money, building up savings or obtaining microcredit. It should be noted that these services are provided via a messaging service linked to a telecommunication operator without the intervention of a financial or banking institution. Indeed, services offered by M-Pesa in Kenya show that the use of mobile money has spread not only in that country but also to other countries in Africa and around the world.

The existing literature on the financial impact of mobile money use by firms shows that it increases revenue from sales and thus profits (Mohamed and Nor, 2021; Akyoo and Sife, 2015; Nyaga and Okonga, 2014), increases the size of small and very small businesses (Bosire and Ntale, 2018 ; Chale and Mbamba, 2015), increases turnover (Talom and Tengeh, 2020; Kirui and Onyuma, 2015), increases the probability of investment of those firms (Islam et al., 2018; Islam and Muzi, 2020) and improves the labour productivity of those firms (Konte and Tetteh, 2022; Beck et al., 2018; Gosavi, 2017).

Beck et al. (2018) analyse the effects of mobile money adoption as a payment instrument on entrepreneurship growth and finance in the case of 1000 SMEs in Kenya. They find that an efficient payment technology such as mobile money can remove constraints on access to credit and boost entrepreneurs’ performance through the productivity of their activities. Access to finance could indeed be a determinant of business performance since most small businesses face a financing constraint from banks or microfinance institutions. Various financial barriers such as the amount of initial deposit often required to open an account and cumbersome administrative procedures are likely to make access to financial services difficult (Beck et al., 2018). With such conditions, the opportunity arises for economic agents to turn to informal financial services whose costs and risks are often high. La Porta and Shleifer (2014) highlight the fact that informal businesses are intended to disappear due to their lower productivity and profitability. Indeed, one of the characteristics of the informal economy is the difficulty of transitioning to the formal sector as economic growth occurs; the informal sector slows down, while the formal sector tends to dominate the economy (La Porta and Shleifer, 2014). Identifying factors that can enhance their performance would be a springboard for them to expand their activities.

Bosire and Ntale (2018) conduct a survey on 50,000 small and medium enterprises in the city of Nairobi to study the relationship between money transfer services and the growth of these businesses. Their results show that mobile money services, whether related to payment, credit or banking, increase the size of these businesses in terms of both revenue and profit. Thus, suitable mobile money services should be offered to these businesses in order to increase their usage and the performance of these businesses.

The works of Kirui and Onyuma (2015) and Nyaga and Okonga (2014), respectively, show that transactions via mobile money increase the performance of very small businesses and that mobile money services increase sales and business size. This is because they save time, reduce costs and ensure flexibility as transactions can be done regardless of location. Similarly, Talom and Tengeh (2020) find in their study on a sample of 285 SMEs in Douala (Cameroon) that sales increase after the adoption of mobile money services. The adoption of mobile money transfer services appears to facilitate financial transactions. Using data from the Kisii Municipality in Kenya, Onyango et al. (2014) in the same vein show, through a random sampling method, that mobile money has a significant effect on the performance of small- and medium-sized enterprises (particularly in terms of customer satisfaction, improved communication with employees, suppliers and customers, storage of customer data and reduced operational costs). However, this work does not take into account business growth indicators such as sales, revenues or profits, to name a few, but only the processes of these businesses and their efficiency.

Furthermore, Nan and Park (2022) analyse the role and impact of mobile money in times of crisis on SMEs in Zambia. Their results show that mobile money use improves Zambian SME resilience amidst of the COVID-19 pandemic as these SMEs are more likely to experience catastrophic sales drop. Hence, SMEs using mobile money seem less likely to face disastrous sales drop than non-users. Mohamed and Nor (2021) also show that an increase of mobile money adoption not only increases access to finance but also the growth sales of small- and medium-sized enterprises in Somalia.

According to the previous studies presented, adoption and use of mobile money can help increase performance of small businesses in their day-to-day activities. This performance can mainly be measured by the sales growth or profit or sales turnover.

Methodology

Data and Descriptive Statistics

The data used for this study are from the 2019 Zambia Informal Sector Business Survey Dataset, a survey conducted by the World Bank Group. This survey was conducted over the period of April 2019 to February 2020 in three main cities: Kitwe, Lusaka and Ndola. For the purposes of this survey, informal businesses are those whose products or services are not illegal under Zambian law but are produced by entities that are not officially registered. In addition, the survey covers all non-agricultural sectors and all sizes of businesses that meet the informality requirement.

Most informal businesses in Zambia do not always exist in official registers and databases, making it difficult to count them. These businesses are found in certain geographical areas, such as low-income areas and bus or train stations. The 2019 Zambia Informal Sector Business Survey uses an innovative area-based sampling methodology; the primary sampling unit is an establishment or business unit rather than a geographic area. Since firms can be clustered, the survey uses adaptive (stratified) cluster sampling. This involves selecting cities as the starting sample and adaptively sampling the surrounding cities based on the number of informal businesses found in the listed cities. Subsequently, all informal businesses in the selected cities are enumerated using a short-form questionnaire, which collects basic information about the business, prior to submission to the main survey questionnaire. Of the 8006 informal businesses in the three cities, 914 were randomly selected and completed the questionnaires. Summary statistics are presented in Table 4 in Appendix.

Table 4.

Descriptive statistics

Variables	Obs.	Mean	Std. Dev.	Min	Max
Profit of last month	914	0.522	0.450	0	1
Adoption of mobile money	914	0.411	0.492	0	1
Adoption of mobile money to pay suppliers	914	0.137	0.344	0	1
Adoption of mobile money to save	914	0.365	0.482	0	1
Adoption of mobile money to pay utility bills	914	0.225	0.418	0	1
Adoption of mobile money to receive payment from customers	914	0.204	0.404	0	1
Number of employees	913	2.249	1.477	1	9
Female owner	914	0.486	0.500	0	1
Age of main owner	911	37.712	10.415	16	82
Owner years of experience	889	4.917	6.524	1	45
Owner level of education	908	3.371	1.166	1	7
Connexion to electricity	914	0.245	0.430	0	1
Premise=household	914	0.445	0.497	0	1
Premise non-household permanent structure	914	0.227	0.419	0	1
Premise non-household temporary structure	914	0.273	0.446	0	1
Main business: manufacturing	914	0.111	0.315	0	1
Main business: retailing	914	0.779	0.415	0	1
Main business: provision of service	914	0.109	0.312	0	1
Activity start	909	2015.953	5.969	1975	2020

The dependent variable is the performance of Zambian informal businesses as measured by the profit obtained by these businesses in the month before the survey. It takes the value of 1 if the profit of the businesses is positive and 0 otherwise. The main explanatory variable captures mobile money use by Zambian informal businesses. We also capture four different purposes of mobile money use (payment of suppliers, savings, payment of utility bills and payment received from customers) by four binary variables. To address endogeneity, we use an instrumental variable probit model where the instrument is a binary one showing the use of a mobile phone or a smartphone for mobile money transactions. The latter variable takes a value of 1 if one of these communication tools is used and 0 otherwise.

The other explanatory variables used are the gender of the business owner, his or her age, level of education, professional experience, firm size (number of employees) and the main business activity (re-selling goods, provision of services or manufacturing)). The definitions, measures and expected effects of these variables are presented in Table 1.

Table 1.

Definition of the explanatory variables expected to impact business performance

Variables	Definition	Expected effect
Female	The owner is female	-
Age	Age of the main owner	+
Education	Owner’s level of education	+
Experience	Owner’s years of experience	+
Firm’s size	Number of workers	+
Main business activity	1 = re-selling goods; 2 = provision of services; 3 = manufacturing	±

Of the 914 informal production units in our sample, 41.14% (about 376 firms) have adopted mobile money. Results in Table 2 present comparisons of averages between firms that have adopted mobile money (adopters) and those that have not (non-adopters) across some characteristics. There is a statistically significant difference between the two groups on a number of variables.

Table 2.

Comparison of averages of mobile money adopters and non-adopters

Variable	Average adopters	Average non-adopters	Difference
Profit	0.564 (0.026)	0.493 (0.0216)	−0.071**
Business size	2.203 (0.073)	2.281 (0.065)	0.078
Female	0.417 (0.025)	0.533 (0.021)	0.116***
Age	37.683 (0.491)	37.733 (0.476)	0.049
Education	3.591 (0.055)	3.217 (0.052)	−0.374***
Experience	4.694 (0.2993)	5.073 (0.307)	0.379
Re-selling goods	0.753 (0.022)	0.797 (.017)	0.045*
Provision of services	0.122 (0.017)	0.100 (0.013)	−0.022
Manufacturing	0.125 (0.017)	0.102 (0.013)	−0.023
Access to electricity grid	0.303 (0.024)	0.204 (0.017)	−0.099***
Activities start	2016.088 (0.265)	2015.858 (0.281)	−0.230
Household	0.402 (0.025)	0.476 (0.021)	0.074***
Premise non-household permanent structure	0.327 (0.024)	0.158 (0.016)	−0.169***
Premise non-household temporary structure	0.231 (0.022)	0.303 (0.020)	0.072***

Robust standard errors are in brackets. * significant at 10 %; ** significant at 5 %; *** significant at 1 %

Source: author from the 2019 Zambia Informal Sector Business Survey Dataset

The results show that firms that use mobile money are more likely to make profit than firms that do not. There is a statistically significant difference among the groups in managerial demographics, managerial education, activities of re-selling goods and access to electricity and type of business premises. Managers of firms that have adopted mobile money are relatively better educated (on average 3.59 years of education) than those of firms that have not adopted it (about 3.21 years of education). Similarly, there is a significant difference in the gender of the main owner of the business. About 53% of non-adopting firms are headed by women, which is relatively higher compared to adopting firms (about 41%). The percentage of businesses operating in re-selling goods that have not adopted mobile money is higher than that of businesses that have adopted it (about 78% versus 75%). On average, 30% of businesses that have adopted mobile money have access to electricity, while only 20% of businesses that have not adopted mobile money have access to electricity. However, there is no significant difference for the business size and the age of the main owner as well as for his professional experience and when the main observed activity of the business is relating to provision of services and to manufacturing. Briefly, firms that adopt mobile money tend to make more profit, have better educated manager and access to electricity and are headed by men and operating in re-selling goods.

Econometric Specification

In this subsection, we present the model estimated to assess the effect of mobile money adoption on the performance of Zambian informal businesses. Usage of mobile money is the main indicator of firms that adopted mobile money for any transaction. A firm use mobile money if it employs mobile money for some transactions. The dataset provides information on the purpose of mobile money use as to pay suppliers, to save money, to pay various current bills or to receive payments from their customers. The correlation between mobile money use and firm profit does not imply causality, but it can be explained by the effect of other factors that affect both variables simultaneously (endogeneity problem). To overcome this problem, it is advisable to consider a bivariate model with instrumental variables composed of two equations, one explaining mobile money adoption and the other explaining the firm’s profit.

The dependent variable (informal business performance) is binary and takes a value of 1 if the business made a profit in the month prior to the survey and 0 otherwise. As there is an endogeneity problem in the nexus between informal business performance and mobile money adoption, we need to first identify determinants of mobile money adoption. For modelling the joint determination of factors driving mobile money use by Zambian informal businesses and the effect of mobile money use on their performance, we use an instrumental variable probit model. This model provides a specification for analysing a case in which a probit model contains an endogenous binary variable in one of the equations (Greene, 2012). We suspected mobile money would be endogenous with profit made by those firms, so the bivariate probit model will help detect and correct the likelihood of this endogeneity.

Let MB be the dichotomous variable indicating the fact that the firm has adopted mobile money.

$$\left\{\begin{array}{c}MB=1if{\mathit{MB}}^{*}>0\\ MB=0otherwise\end{array}\right)$$

MB ^∗ is a latent variable with

$${\mathit{MB}}^{*}={\alpha }_1+X_1{\beta }_1+{\epsilon }_1$$ 1

Let PF be the dichotomous variable indicating the firm’s profit defined by

$$\left\{\begin{array}{c}PF=1if{\mathit{PF}}^{*}>0\\ PF=0otherwise\end{array}\right)$$

PF ^∗ is a latent variable given by

$${\mathit{PF}}^{*}={\alpha }_2+X_2{\beta }_2+\delta MB+{\epsilon }_2$$ 2

The model can then be written

$$\left\{\begin{array}{c}{\mathit{MB}}^{*}={\alpha }_1+X_1{\beta }_1+{\epsilon }_1\\ {\mathit{PF}}^{*}={\alpha }_2+X_2{\beta }_2+\delta MB+{\epsilon }_2\end{array}\right)$$ 3

X ₁ and X₂ are the independent variables, and the standard error terms (ε₁ and ε₂) follow a bivariate normal distribution of mean 0 with a variance–covariance matrix written as follows: $\left(\genfrac{}{}{0.0pt}{}{{\epsilon }_1}{{\epsilon }_2}\right)\to N\left(0,,,\sum \right),\text{avec}\sum =\left(\begin{array}{cc}1& {\rho }_{12}\\ {\rho }_{12}& 1\end{array}\right)$

For the model to be identified, at least one of the variables in X₁, called the instrument, must be excluded from X₂. The choice of instruments requires that they be correlated with mobile money adoption and not correlated with firm performance. The instrument chosen in this study is the average of firms that have adopted mobile money in the locality where the firm is located. We assume that the probability of a firm adopting mobile money increases with the average number of firms in its neighbourhood that have adopted this technology. Indeed, “peer effects” among entrepreneurs should exist and could contribute to the spread of mobile money. However, this variable should not have a direct effect on firm productivity.

Results and Discussion

Table 3 presents the determinants of mobile money adoption (in column (1)) and the impact of mobile money use on the profit of informal businesses (in column (2)). The intensity of mobile money use varies according to their objectives; columns (3), (4), (5) and (6) extend the analysis by presenting the relationship between the likelihood of Zambian informal business performance and the purpose of mobile money use respectively to pay suppliers, to save, to pay current bills and to receive payments from customers.

Table 3.

Results of instrumental variable probit model regression

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	Mobile money	Profit	Profit	Profit	Profit	Profit
Adoption of mobile money		1.342*** (0.502)
Mobile money to pay suppliers			2.749*** (0.465)
Mobile money to save				1.251** (0.489)
Mobile money to pay utility bills					2.398*** (0.203)
Mobile money to receive payments						2.312*** (0.45)
Number of employees	−0.054* (0.03)	0.122*** (0.03)	0.032 (0.05)	0.124*** (0.03)	0.038 (0.05)	0.057 (0.05)
Female	−0.150 (0.10)	−0.012 (0.10)	0.064 (0.10)	0.0047 (0.10)	0.033 (0.09)	−0.016 (0.09)
Age	0.002 (0.00)	−0.004 (0.00)	−0.005 (0.00)	−0.002 (0.00)	−0.006 (0.00	−0.002 (0.00)
Years of experience	−0.015 (0.013)	−0.0073 (0.012)	0.001 (0.012)	−0.005 (0.013)	−0.003 (0.011)	−0.002 (0.012)
Education	0.124*** (0.04)	0.012 (0.06)	0.012 (0.05)	0.044 (0.05)	−0.065 (0.05)	−0.058 (0.06)
Electricity	0.063 (0.11)	0.211* (0.13)	0.077 (0.15)	0.213* (0.12)	0.055 (0.15)	0.226* (0.13)
Household	0.247 (0.21)	−0.117 (0.19)	−0.186 (0.17)	−0.096 (0.19)	−0.075 (0.16)	0.014 (0.17)
Permanent premise	0.595*** (0.22)	−0.908 (0.20)	−0.716 (0.25)	−0.836 (0.20)	−0.470 (0.30)	−0.556 (0.27)
Temporary premise	0.162 (0.21)	−0.331 (0.19)	−0.147 (0.21)	−0.276 (0.20)	−0.057 (0.21)	0.079 (0.24)
Manufacturing	0.228 (0.19)	0.150 (0.20)	0.056 (0.20)	0.182 (0.19)	0.038 (0.19)	0.096 (0.19)
Re-selling goods	−0.065 (0.15)	0.352** (0.15)	0.364** (0.17)	0.369** (0.15)	0.217 (0.19)	0.457*** (0.15)
Activities start	−0.012 (0.01)	0.003 (0.01)	0.008 (0.01)	0.007 (0.01)	−0.007 (0.01)	0.005 (0.01)
Mean mobile money adoption	0.458*** (0.159)
Constant	4.38 (0.79)	−7.564 (0.19)	−5.61 (0.27)	−4.29 (0.72)	3.06 (0.08)	−2.757 (0.47)
Region fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
\ athrho		−0.609* (0.364)	−1.337* (0.785)	−0.584* (0.330)	−2.031 (1.532)	−1.257* (0.725)
\ lnsigma		−0.747*** (0.024)	−1.092*** (0.024)	−0.765*** (0.024)	−0.893*** (0.024)	−0.948*** (0.024)
rho		−0.543 (0.257)	−0.871 (0.189)	−0.526 (0.239)	−0.966 (0.102)	−0.850 (0.201)
sigma		0.473 (0.011)	0.336 (0.008)	0.465 (0.011)	0.409 (0.010)	0.388 (0.009)
Observations	880	880	880	880	880	880
Wald chi2 (13)		135.94***	478.94***	124.26***	1087.65***	398.40***
Wald test of exogeneity chi2 (1)		2.79*	2.90*	3.14*	1.76	3.01*

Standard errors are in brackets. Statistics significant: *** p<0.01, ** p<0.05, * p<0.1. (1) = determinants of mobile money adoption; (2), (3), (4), (5) and (6) = effects of mobile money adoption on business performance

Source: author from the 2019 Zambia Informal Sector Business Survey Dataset

The results in column (1) show that among those variables, the level of education of the business owner and the fact that the business has a permanent location that is not the home of the business owner significantly increase the probability of adopting mobile money by Zambian informal businesses. These variables are with positive sign and statistically significant. On the other hand, the size of the business significantly reduces the probability of adopting mobile money by informal businesses. Indeed, larger and older firms are less likely to adopt the services offered by mobile money (Islam et al., 2018) since they already benefit from banking services due to their formal existence. The results also show that as average adoption of mobile money increases, probability of adopting money significantly increased at 1% level.

Data analysis using instrumental variable probit model regression shows that the models properly fitted the data. The significance of the Wald chi square statistics (p<0.01) explains the results presented. Analysis was carried out by using the mean adoption of mobile money as instrumental variable. The results of the Wald test of exogeneity, which is statistically significant at 10% level, showed that mobile money adoption was truly endogenous (except when the purpose of mobile money adoption by informal businesses is to pay utility bills) and the instrumental variable used was adequate.

The results in column (2) show that mobile money adoption is with positive sign and statistically significant at 1% level. This result implies that informal businesses that have adopted mobile money had higher probability of making profit. Indeed, the adoption of mobile money increases the profit earned by these firms in the month prior to the period in which the survey was conducted. This result support the works of researchers such as Nan and Park (2022), Talom and Tengeh (2020), Islam et al. (2018) Gosavi (2017) and Akyoo and Sife (2015), who showed that mobile money increases sales revenue and promotes firm productivity and investment, among others. It can be explained by the fact that mobile money transfer services are a means of facilitating financial transactions, which increases customer satisfaction and reduces operational costs of the business.

The parameters of the purpose of the mobile money services either to pay suppliers, save money, pay various current bills or receive payments from their customers significantly increased the probability of Zambian informal businesses to make profit (p<0.01). This is expected because mobile money adoption can help reduce information and transaction costs and manage day-by-day activities of entrepreneurs (Mbiti and Weil, 2016; Jack and Suri, 2014).

The results further revealed that business size significantly influences the probability of making profit by those businesses in two cases: when they adopt mobile money in general and when the purpose of mobile money services is to save. The effect of small firm’s size on their performance had already been highlighted by several authors (see, for example, St-Pierre et al., 2010; Linasmi, 2017). Connection to the electricity grid also significantly increases the probability of Zambian informal businesses to make profit. Additionally, the results show that when the main business activity is re-selling of goods (services), the probability of making profit significantly increased for the informal businesses that adopted mobile money and more particularly when the purpose is to pay suppliers, to save or to receive payments from customers.

While the likelihood of adopting mobile money increases with the level of education of the owner of the business, firm performance is not affected by the level of education or the type of training of the manager. Bakehe (2016) explains this result by the fact that in Africa, the practice of trade by informal firms does not require specific technical training. Indeed, trade is the primary activity of these firms, and those with vocational training may not be motivated in this sector (which may negatively influence their management style and organizational structure) as it is also likely that those with vocational training who turn to self-employment do so out of necessity, having been excluded from wage employment. As far as the level of education is concerned, its insignificant influence can be explained by the deterioration of the quality of the educational system in Africa but also by the fact that maybe the western type of school does not sufficiently promote the acquisition of entrepreneurial skills and is especially oriented towards the training of future civil servants. Furthermore, the age and gender of the manager have no significant influence on the performance of informal businesses.

Compared to other main business activity, re-selling goods have a higher probability of improving their profit. The comparative advantage of these businesses can be explained by horizontal diversification that provides them security. Indeed, Bakehe (2016) indicates that by diversifying its portfolio of activities, a firm opens up to new markets and thus reaps new profits. In sub-Saharan Africa, in general, and in Zambia, in particular, it is generally observed that small businesses have started their activity by selling fruits, for example. The businesses then offer cigarettes, sweets, cookies, etc., thus spreading their income over several products. The bad results of the sale of one of the products do not put the business in difficulty. Moreover, very often, this type of diversification does not impose any fixed costs (Backiny-Yetna, 2009; Bakehe, 2016).

Conclusion

With a large share in economic activity, informal sector has advantages to adopt mobile money services for their various financial transactions. These are related to the reduction of the need to have cash on hand and the saving of money and time. The objective of this study was to analyse the effect of mobile money adoption on the performance of informal businesses. To do so, we used data collected in 2019 from the Zambia Informal Sector Business Survey. The analysis uses bivariate probit model with instrumental variables to highlight the determinants of mobile money adoption and the effect of money adoption on the performance of these businesses.

The owner’s level of education and the use of a permanent premise for the business are among the determinants of mobile money adoption. The results provide support that mobile money adoption has a positive impact on the performance of informal businesses. This could be explained by the fact that not only do mobile money transfer services facilitate financial transactions, but they also reduce the operational costs of the business. The finding support the fact that the relationship between mobile money and informal business performance is stronger using four purposes of mobile money: payment of suppliers, savings, payment of utility bills or payment received from customers. Public authorities need to focus on measures that promote the development of digital finance and its use by informal businesses given its role in their performance. This can be done by increasing awareness and usage of mobile money at the firm level.

As an extension of this study, it would be interesting to adopt a panel data estimation to observe the temporal evolution of mobile money adoption effect on firm performance.

Appendix

See Table 4.

Declarations

Competing Interests

The author declares no competing interests.