Sustainability Factors of Self-Help Groups in Disaster-Affected Communities

Abstract

Self-help groups are informal associations that use social capital to overcome resource constraints and act as a catalyst for rural development, women, and social empowerment. This study tries to identify the factors that affect the sustainability of self-help groups in natural disaster-affected communities. Natural calamities in the form of droughts, floods, or cyclones pose major challenges to livelihood in disaster-prone regions. The study is based on survey data from two different disaster-prone locations: the cyclone- and flood-prone Sundarbans, and drought-prone Bankura in West Bengal, India. Applying principal component analysis to the responses of 143 self-help group members, the study identifies four factors responsible for the sustainability of these self-help groups. This study shows that managerial functions, trust, fund utilization, and easy financing are the factors that matter the most. The findings suggest that policymakers and local governments can focus on these aspects to ensure the effectiveness of self-help groups in meeting their social objectives.

1. Introduction

This paper aims to help identify the factors responsible for the sustainability of social enterprises, specifically self-help groups within marginal communities. It explores how a social organization copes with sustainable development challenges by focusing on its challenging factors. The word “factor” in this study has been used as a synonym of the word “component”, not as an abbreviation of factor analysis, and does not have any statistical connotation. It has been used for easier understanding for the nonstatistical audience.

Since 1987, sustainable development has been at the forefront of the world development agenda. The Brundtland Commission of 1987 [1] published a report, Our Common Future, aiming to link environmental stability and economic development. The Brundtland report defined the first definition of sustainable development as development that meets the needs of the present without compromising the ability of future generations to meet their own needs. This can be considered a seminal work in the area of sustainable development. The report stresses poverty alleviation through employment generation.

One of the biggest challenges faced by these microsocial enterprises (i.e., SHGs) is mitigating economic shocks related to climate change and natural disasters. For example, cyclone Aila in 2010 and the recent cyclone Bulbul in 2019 have devastated people’s livelihoods in the Sundarbans region of India and Bangladesh. Similarly, deficient rainfall and temporal and spatial variability in intensity and magnitude in the Purulia, Bankura, and Midnapore districts have made them drought-prone. Rural communities worldwide depend on agricultural activities for their livelihood, making them vulnerable to the adverse effects of climate change due to their strong dependence on agricultural production. Therefore, many SHGs in these regions face extreme conditions in their efforts toward poverty alleviation and empowerment.

This study identifies the sustainability elements of the SHGs, with particular reference to those involved in mitigating challenges related to climate change and natural disasters. Secondly, having identified the factors, a framework for evaluating the sustainability of such microsocial enterprises has been developed.

Cyclone Aila had a devastating effect on the lives of people in the Sundarbans. Their fields and ponds were inundated by saltwater, thus making them unfit for farming or fishery. Governmental and nongovernmental interventions were taken up to regenerate these farmlands and ponds. This research will revisit the Aila-affected areas of the Sundarbans after ten years to understand the elements responsible for the sustainability of the social initiatives launched and the finding of a sustainable measurement model.

The research objective is to identify the social, economic, political, technological, and managerial factors which help social enterprises, especially self-help groups, become sustainable. This identification of factors at an early stage will help newly formed social enterprises with prominent members take the necessary steps. For the exploratory study, the area of investigation will be restricted to a block in the Sundarbans in India, which had experienced severe damage to land and inland water bodies due to Cyclone Aila. The unit of analysis will be those families who had suffered damages from saltwater ingress during the cyclone to their fields and water bodies, leaving them unfit for any farming or fishery activity. The next sections discuss the prior work done to identify sustainability measurements and indicators, followed by this study’s data and methodology, results, discussion, and conclusions.

2. Social Enterprises and Sustainability Measurement

Social enterprises are commonly identified as not-for-profit organizations. In this study, the social enterprises that have been considered are widely known as self-help groups in the South Asian region. Self-help groups, also known as mutual help, mutual aid, or support groups, are groups of people who provide mutual support for each other. The members of the self-help groups share a common economic, social, or health problem. The members share a common goal to help each other cope with and recover from the situation.

The sustainability of these groups forms an area of interest. Viederman’s [2] definition of sustainability is that it is a participatory process that constructs and pursues the notion of a community that is respectful of its available resources—natural, human, artificial, social, cultural, scientific, etc.—and uses them prudently to save them for the future. Sustainability envisions that present generations can achieve a high degree of economic security while exercising democracy and maintaining people’s participation in the control of their communities while simultaneously assuming responsibility for and upholding the integrity of the ecological systems that are crucial for the subsistence of future generations [3]. Sustainable practices put forth provisions for ecological, human, and economic health and vitality. The idea of sustainability considers all resources limited and calls for a conscious effort to utilize them conservatively and prudently to preserve them for long-term use and consequence.

Sethi [4] puts forth social obligation, social responsiveness, and social responsibility as the threefold distinction between levels of corporate intensity around societal matters. Analysing the response of social entrepreneurs to prevailing pressures, it can be stated that their comfort rests in being responsive and preemptively problem-solving. According to Burns, social entrepreneurship can be divided into two parts: integrated and complimentary social entrepreneurship [5]. When profit-generating activities concurrently lead to the conception of social value, it can be termed integrated social entrepreneurship. Contrary to this, complementary social entrepreneurship focuses on cross-subsidization to attain goals. Therefore, for the enterprise, excess profit generated from profit-making activities becomes the subsidy for achieving social objectives.

Dees and Anderson [6] had distinguished three forms of social enterprises in their work: “for-profit social ventures, non-profit business ventures, and socially responsible businesses” [5]. The undertakings aimed at profit-making are predominantly and legally intended to perform a social role, but they are entitled to make a profit. Legal constraints bind the “non-profit” undertakings in the case of profit distribution; however, they are equipped with the prospect of using philanthropic contributions to cover costs. Conversely, the third form of social enterprise attempts to be commercially successful without preceding or flouting ethical and responsible practices. However, the goal of economic value creation has been a predominant purpose of these businesses.

In further years, researchers were concerned with emerging concepts, practices, performance analyses, social entrepreneurship, and stakeholder participation using qualitative methodologies, such as a case study, and quantitative methods, such as factor analysis [7,8,9,10]. In the new decade, researchers have been looking for a new direction for social entrepreneurship [7], and efforts were made to find sustainability for social enterprises [8], which also established that a violation of legitimacy has a spillover effect [9]. Development methodologies and measurements of financial performance have shaped the sustainability of social enterprises [11,12]. It is striking that most of the methodologies selected by the authors were qualitative case analyses [13,14]. A quantitative push has been identified to measure sustainability [10] and the need to form an index for such measures [15]. Alter and Dawan [16] argued that the presence of factors such as “organizational and leadership capacity, business-oriented culture and financial viability” is crucial to achieving the sustainability of social enterprises. Therefore, they promote a cohesive method for performing constant measurement of social value and claim that it is essential to measure these factors to understand that sustainability through financial viability is quantitative and easily measurable. In contrast, factors like leadership and culture are not accurately measurable.

Research on social enterprise has developed and moved beyond arguments on the definition and incorporated the need to scrutinize institutional and organizational processes related to their formation and administration [17]. The study by Jenner [10] upholds the framework proposed by [11] that shifts focus to identifying resources, organizational competencies, cooperative linkages, and validity as significant factors in making social enterprises sustainable. Conversely, according to one prediction [12], research findings divulge that overarching commercial focus and economically driven growth motivations are overriding reasons for the tactical management of social enterprise sustainability [13].

Burkett [14] speaks of the two sides of sustainability in social enterprises. The first aspect is financial sustainability, which demonstrates durability over time. The other side narrates the influence the social enterprise produces concerning its social mission. There must be consideration for both financial and social impacts. Burkett [14] notes that social ventures are burdened to take care of production and operational costs through viable and profitable means of self-sufficiency. However, endowments and subsidies act as effective alternatives to balance the initial costs. Most organizations operate at a low scale with inadequate assets, making their chances to achieve sustainability without grants negligible.

Measuring sustainability as an activity will entrench this issue as an imperative practice in decision-making and administration. Evaluation of sustainability can be made using a set of indices. Irrespective of the sustainability metric used, the measurement activity will be used to assist decision-makers in evaluating a company’s sustainability along with generating information for designing future actions [18,19,20], including demonstrations of latent trends, the ability to anticipate imminent conditions, and the ability to compare places and situations [21].

Research carried out by Delai and Takahashi [22] has established that no singular initiative on analysis has proven able to tackle sustainability issues effectively. There is disagreement around the parameters that need to be measured. The main conflicts are as follows: that different enterprises use different criteria to classify disputes between dimensions; similar impacts on the cause–effect relationship can be evaluated at different levels by the same initiative [23]; incongruity about stakeholders of an organization needs to engage with; company influences should also be assessed [24]. A challenge to sustainability measurement has been the absence of agreement on indices of sustainability [25,26]; this has been a major barrier in the formulation and implementation of strategies for sustainability [27], and this, according to Warhurst, drives the necessity to “define common methodological standards and indicator sets” [22]. The possibility of a bias in the measurement scheme when implementing one or another initiative or the struggle to equate performances among establishments arises from this lacuna [28]. Marketing by social enterprises emerges as a misunderstood concept [29]. It appears as a transactional practice of promotion or sales rather than building a durable business-to-business and business-to-customer relationship, and it may not contribute to its sustainability.

3. Sustainability Indicators of Self-Help Groups

A variable is an indicator that is used to identify a concept, where the concept poses as an independent or dependent variable [18]. The literature review of sustainability measurement indicators has been instrumental in understanding and identifying the variables for further investigation. The sustainability measurement indicator of the ability to take care of group activities indicates a successful self-help group was identified by Thapa et al. [19], which eventually was identified as a variable, the size of the group, that plays an essential role in the sustainability of the group [20]. This has been given the variable code V1. Self-help groups mostly comprise economically weaker community members who often share the same socioeconomic background. This same background of economically weaker members makes group work easy [30]; this has been identified as variable V2. For any group to function, efficient meetings and higher attendance are essential [25]. These two items have been categorized under two variables, V3 and V4, respectively. Mere attendance and efficiently conducted meetings will only be sufficient if all members participate in decision-making and equally share responsibility [26]. The factors all members should participate in decision-making and equally share responsibility [31] are classified as variables V5 and V6, respectively. It has been identified that savings is essential [32], and it has been coded as variable V8. Bhatia [33] recalled that easy access to loans is not suitable for the group, so to understand the agreement of stakeholders, this has been taken as variable V9. Loan repayment is an essential aspect of the sustainability of self-help groups. All members are expected to participate in loan repayment [25], which has been taken as variable V10. Resource mobilization and cash handling, two critical functions, have been characterized as variables V13 and V14, respectively [34]. All organizations must maintain bookkeeping and documentation and periodically audit their financial statements [35]; these two critical aspects have been considered as variables V15 and V16 to understand their importance to the group members. The members often come from improvised communities needing training for group functioning [36], and thus the need for training programs has been identified as variable V17. The most crucial aspect of management and use importance in the sustainability of self-help groups [37] have been tested together under variable V18. As per Nielsen and Tripathy [38] rules and regulations, rotation of common fund, avoidance of idle capital, participation in community programs, and literacy are essential for the group, which have been identified and coded under variables V7, V11, V12, V19, and V20, respectively.

These 20 variables were reviewed by industry experts before data collection and were subjected to principal component analysis to identify the elements responsible for the sustainability of self-help groups.

4. Data and Methodology

The research was divided into two distinct methodologies. The first part was a qualitative approach, where variables were identified from the literature review and validated by interviewing industry experts and practicing self-help group members. Interview questions were closed-ended; experts and members were asked to comment on the suitability of twenty variables identified in the literature review to identify the sustainability factors of self-help groups. The results were affirmative for all twenty variables. The questionnaire was translated from English to Bengali. The English version of the questionnaire is provided in Appendix A.

After the interview scripts, the next phase of the questionnaire design was the Likert scale design for the respondents to record their responses. The interview scripts’ results helped decide the variables used in the Likert scale. The questionnaire also recorded demographic details. To summarize the questionnaire design, it can be said that an interview script was designed to collect qualitative responses, and a five-point Likert scale was developed to collect quantitative responses.

The survey sites were villages in the Sundarbans region and the village of Bankata in Bankura, West Bengal. The respondents were divided into industry experts, practitioners, and members and office bearers of self-help groups. The five-point Likert scale was administered to 155 members of SHGs. These SHGs were spread across the Sundarbans and the Bankura district in the eastern part of India. The participant’s population is limited, as each social enterprise, in this case, self-help groups, had only ten members registered, but the active members were much fewer in number. Furthermore, to maintain heterogeneity and remove bias among respondents, two respondents were interviewed from each of the 72 SHGs. After overcoming all of the logistical challenges to reach every member, 22% of total registered members were interviewed. In previous research, Barrett and Kline [39] recommended a minimum sample size of 50 for behavioral studies. Cattell [40] suggested a subject-to-variable ratio of 3:1 or up to 6:1. A ratio of 2:1 was suggested by Kline [41], and a standard minimum of 100 observations was suggested by Rahn [42]. Bryant and Yarnold [43] recommended a ratio of not lower than 5:1. The KMO statistic was analysed to ascertain sample adequacy.

5. Results

Principal component analysis is probably the oldest and best-known of all multivariate analysis techniques. It has been done in this study for item reduction. The first test done was Barlett’s test of sphericity to ascertain the suitability of the data for principal component analysis. On confirmation of PCA from Barlett’s test, sample adequacy was checked. On samples with adequate eigenvalues, component loadings were used to arrive at the previously identified factors responsible for the sustainability of social enterprises.

5.1. Bartlett’s Test of Sphericity

Bartlett’s test of sphericity compares an observed correlation matrix to the identity matrix [44]. It tests whether there is a certain redundancy between the variables which can be summarized in a few components; this is only possible when the correlation matrix significantly diverges from the identity matrix. This test’s null hypothesis is that the variables are orthogonal, i.e., not correlated. The alternative hypothesis is that the variables are not orthogonal [44].

Null Hypothesis (H₀). 

Variables are orthogonal (not correlated).

Alternate Hypothesis (H₁). 

Variables are not orthogonal (correlated).

Barlett’s test statistics are given in

Table 1. Barlett’s Test of Sphericity.

χ2	df	p
1061	190	<0.001

. A p-value less than the chosen significance level (0.05) was obtained. Since the result (< 0.001) is significant, the variables are correlated and can be summarized with several components. Hence, principal component analysis was pursued.

5.2. Sample Adequacy and Eigenvalues

The Kaiser–Meyer–Olkin (KMO) test is used in research to determine the sampling adequacy of a dataset. The statistic that is computed is a measure between zero and one. Interpreting the statistic is relatively straightforward: the closer to one, the better. The details of the obtained KMO statistics are mentioned in

Table 2. KMO measures of sample adequacy.

Items	MSA
Overall	0.903
Size of the SHG plays an important role	0.835
Economically weaker members make group work easy	0.914
Meeting every week	0.906
The attendance rate per meeting should be high	0.922
All members should participate in decision-making	0.905
All members should equally share responsibility	0.895
Rules and regulations are important for the group	0.933
Savings is important	0.935
Easy access to loans is good for the group	0.856
All members must participate in loan repayment	0.903
Rotation of the common fund is required	0.875
Idle capital is not good for the group	0.940
Cash handling can be done by any member	0.883
Resource mobilization in one place is good for the group	0.916
Bookkeeping and financial documentation are important	0.947
Auditing is important	0.908
Training programs are critical for group functioning	0.895
Planning, implementation, monitoring, and evaluation of the program by group members is important	0.913
Participation in community programs is essential for group functioning	0.886
Literacy is important for the group	0.858

. The overall measure of sample adequacy (MSA) is 0.903, with the maximum individual MSA reported being 0.947 and the minimum reported being 0.856. The MSA values were close to one, and thus the sample sizes were considered adequate.

To identify the components, components with an eigenvalue greater than one have been chosen as the sustainability factors responsible as per the Kaiser–Guttman rule [45], which simply states that factors to be chosen should have eigenvalues greater than one. The eigenvalues of all the components are shown in

Table 3. Eigenvalues.

Component	Eigenvalue	% of Variance	Cumulative %
1	7.165	35.83	35.8
2	1.362	6.81	42.6
3	1.144	5.72	48.4
4	1.082	5.41	53.8
5	0.895	4.48	58.2
6	0.879	4.39	62.6
7	0.811	4.05	66.7
8	0.761	3.80	70.5
9	0.725	3.62	74.1
10	0.701	3.50	77.6
11	0.615	3.08	80.7
12	0.573	2.86	83.6
13	0.563	2.82	86.4
14	0.493	2.47	88.8
15	0.457	2.28	91.1
16	0.435	2.18	93.3
17	0.373	1.86	95.2
18	0.352	1.76	96.9
19	0.327	1.63	98.6
20	0.289	1.45	100.0

. Thus, the four components with eigenvalues greater than one together explain over 53% of the variance, with Component 1 explaining 35.83% variance alone, and they have been considered for further analysis.

As indicated in

Table 4. Intercomponent correlations.

1		2	3	4
1	-	0.00	0.00	0.00
2		-	0.00	0.00
3			-	0.00
4				-

, the intercomponent correlation was zero, indicating a good model fit. This also validates that the right components have come out from the PCA.

The component factor loadings have been shown in

Table 5. Component factor loadings.

	Components				Uniqueness
	1	2	3	4
Auditing is important	0.684				0.443
Resource mobilization in one place is good for the group	0.675				0.431
Training programs are critical for group functioning	0.673				0.427
Planning, implementation, monitoring, and evaluation of the program by group members is important	0.627				0.471
All members must participate in loan repayment					0.530
The attendance rate per meeting should be high					0.503
Cash handling can be done by any member		0.713			0.399
All members should participate in decision-making		0.648			0.424
Rules and regulations are important for the group					0.419
Meeting every week					0.437
Bookkeeping and financial documentation are important					0.523
All members should equally share responsibility					0.602
Savings is important					0.589
Size of the SHG plays an important role			0.706		0.359
Rotation of the common fund is required			0.602		0.439
Idle capital is not good for the group					0.518
Economically weaker members make group work easy					0.591
Literacy is important for the group				0.713	0.387
Participation in community programs is essential for group functioning				0.666	0.443
Easy access to loans is good for the group				0.601	0.314

. Variables with greater than 0.6 factor loadings have been included in the components. Factor loading is the correlation between a latent variable and an observed indicator. Factor loadings above 0.7 are considered to be ideal [46]. Field [47] suggested at least 0.6 factor loading irrespective of sample size. Furthermore, Comrey and Lee [48] suggested using more stringent cutoffs going above 0.63 to be considered as very good; this is further supported by Rahn’s [42] suggestion that a stringent cutoff such as 0.7 should be used. So, to make our cutoff more stringent, we have used the factor loading cutoff of 0.6.

The scree plot is a widely used graphical tool to deal with component and factor selection. It is primarily used as a graphical plot to visualize the degree of variability associated with each component extracted in principal component analysis. This plot allows researchers to examine the pattern of decreasing variability among parts sorted by eigenvalue to inform the selection of components to be considered [49]. The scree plot of the principal component analysis is shown in Figure 1. The blue circles in Figure 1 indicate the eigenvalues of components and the dotted line indicates the cut-off value of the eigenvalue which is equal to 1.

6. Discussion

The principal component analysis was done to identify the variables necessary for the sustainability of self-help groups as indicated by industry experts, practitioners, and ordinary members of these groups. The principal component analysis was divided into three major analytical parts: the test for orthogonality, the sample adequacy test, and the component reduction test. The test for orthogonality tests whether the variables are correlated or not. Only correlated variables can undergo that component reduction and can be summarized with a few components. The data collected showed no orthogonality, suggesting they are correlated. Bartlett’s test of sphericity had a p-value of less than 0.001, which is a significant result to prove the correlation among variables. Hence, further tests were performed. The next test was the Kaiser–Meyer–Olkin (KMO) test, which tests the sample adequacy for each variable and overall sample adequacy for the model. The KMO statistic for the overall test is 0.903, which is very near to one. The lowest measure for sampling adequacy (KMO statistic) was 0.835 for the variable “size of the ECG plays an important role”. The highest measure for sampling adequacy from the KMO test was 0.947 for the variable “bookkeeping and documentation is important”. From these measures, it was concluded that the sampling’s adequacy, which falls within the range of 0.835 and 0.903, (very near to one), is sufficient. Because the samples have been found to be adequate, further principal component analysis was performed.

The terms sustainability and resilience have raised debates. Some claim sustainability and resilience are the same concept, whereas others claim them to be entirely unrelated. Resilience is the ability of a system to withstand impacts from threats and adapt to insistent stress, whereas sustainability is concerned with environmental, social, and economic systems; however, their objectives are common [50]. Because the resiliency of a sociological system is determined by the magnitude of the strength that an organization can to absorb challenges and continue to carry out its duties, it matches the objectives of sustainability and is mutually inclusive [51]. Thus, sustainability has been chosen as the area of work because tenets of resilience do get addressed by sustainability and vice-versa. Principal component analysis was done to identify the variables necessary for the sustainability of self-help groups. Using the eigenvalue greater than one and factor loading above 0.6, this study helped in identifying 11 variables that impact the sustainability of the chosen self-help groups. The 11 variables were grouped into four components. Component 1, referred to henceforth as Managerial Functions, constitutes four variables (factor loadings in brackets): “auditing is important” (0.684), “resource mobilization in one place is good for the group” (0.675), “training programs are critical for group functioning” (0.673), and “planning, implementation, monitoring, and evaluation of the program by group members is important” (0.627). These variables were also identified by NCAER [35], Shetty and Madheswaran [37], ARAVALI [34], and Kumari and Malathi [36]. Component 2 constitutes two variables: “cash handling can be done by any member” (0.713) and “all members should participate in decision-making” (0.648), as was identified by Singh et al. [26] and AVARALI [34]. This component is referred to henceforth as Trust. Component 3 also constitutes two variables, namely “size of the SHG plays an important role” (0.706) and “rotation of the common fund is required” (0.602). These variables are in concurrence with Thapa et al. [19] and Nielsen and Tripathy [38], and the component is referred to henceforth as Fund Utilization. Finally, Component 4 constitutes three variables, namely “literacy is important for the group” (0.713), “participation in a community program is essential for group functioning” (0.666), and “easy access to loans is good for the group” (0.601). These variables are in line with Nielsen and Tripathy [38] and Bhatia [33], and the component is referred to henceforth as Easy Financing. The intercomponent correlation was found to be zero, indicating that the model and the components are valid and can be used for further research. To summarize the components:

• Component 1—Audit, Resource Mobilization, Training, Planning–Monitoring–Evaluation (henceforth termed as Managerial Functions)
• Component 2—Cash Handling, Participation in Decision-Making (henceforth termed as Trust)
• Component 3—Size and Rotation of Common Fund (henceforth termed as Fund Utilization)
• Component 4—Literacy, Participation in Community Programs, Easy Access to Loans (henceforth termed as Easy Financing)

To summarize, Managerial Functions, Trust, Fund Utilization and Easy Functioning have been identified as the sustainability factors for social enterprises. Managerial Functions ensure that enterprises are guided by able leadership and risks are managed effectively. This also acts as a confidence-building measure through managerial functions such as auditing. This factor leads to the trust members will have for officials, fellow members, and the organization, thus prompting them to remain involved. The need for easy finance and its utilization are the other two key factors for sustainability. This finance can be self-financing or from government institutions. Interestingly, it has also come out that utilization of funds is a key factor for sustainability. All four factors point to Managerial Functions, Trusts, Easy Financing, and Fund Utilization, which agrees with the experts’ views and the literature.

7. Conclusions

The objectives of this research have been achieved by identifying the variables and components. The study’s aim to explore the measurement mechanism of sustainability, including the role of personnel and group effectiveness, was achieved during the literature review where the variables found by early researchers were identified. The next part of the research was all about collecting the data and running a principal component analysis for item reductions, thus arriving at the four components and their constituent variables—namely, Managerial Functions, Trust, Fund Utilization, and Easy Financing—as the key factors for the sustainability of social enterprises.

These findings have an impact on policy decisions regarding extension and training programs pertaining to managerial functions such as planning, organizing, monitoring, and gathering feedback. This intervention is to be introduced into any capacity-building program. Technical training programs should have these interventions. Trust is a common issue, as it can only be ascertained by regular auditing, where members establish trust for the office bearers. Governments can bring out a policy of compulsory audit report presentation for any loan application. This will increase the operational cost, but it can be subsidized by financial institutes because this will bring down their risk. Often, funds remain blocked in bank accounts, thus losing their value to inflation. To counter such scenarios, special interest rate fixed deposits or bonds for social enterprises can be created to ensure rotation of the idle fund. Generally, the members of SHGs are not capable of handling financial instruments, thus secured alternate investments will help them rotate the idle fund. For easy loan disbursement, SHGs can work with their local administration on community programs and regulatory frameworks to support efficient disbursement mechanisms.

Theoretical implications are in the form of future research possibilities, primarily in the field of artificial intelligence in identifying the sustainability of social enterprises; algorithms can source information from databases where SHG financial and regulatory data are stored as well as feedback form the members, all of which can be used to raise alarms for organisations with threatened sustainability.