This study surveyed MSMEs in Makassar to collect primary data, while secondary data were obtained through journal articles, official documents, reports, and other research publications. The data were analyzed by descriptive and regression analyses.
3.1. Study Site
Makassar is the center of Indonesia’s national activity (as per PEN Programme), and around 65% of the population depend on MSMEs for their living. The city has a vision of “acceleration of realizing Makassar as a global city that is sombere (sociable) and smart with strong immunity for all”, which characterizes urban social sustainability. Three subdistricts were purposively selected, Mariso, Rappocini, and Bontoala, as they represent the significant numbers of MSMEs and the highest population density in Makassar (Fig. S1 and Table S1).
3.2. Measurements
The study was designed using social, economic, and environmental sustainability indicators (Table 1 and Table S2). Social sustainability can be measured by social justice and equity (SJE), social capital (SCA), and social cohesion (SCO) (Hemani et al., 2017; Shirazi and Keivani, 2019). The presence of SJE refers to meeting the community’s needs both intra-generationally and inter-generationally. It also refers to fair treatment of communities regardless of religion, ethnicity, race, gender, or other affiliations of society (Harvey, 2009), ensuring accessibility to economic and political opportunities (Magis and Shinn, 2009) and healthy and safe working conditions in MSMEs (Brady-Amoon, 2012).
Table 1
Codes and definitions of the sub-indicators
Codes | Indicators |
sje1 | promote equality and community security |
sje2 | give women access to management positions |
sje3 | experience crimes surrounding your business |
sje4 | experience discrimination in business development by any stakeholders |
sje5 | satisfaction with this business |
sje6 | satisfaction with the income so far |
sje7 | satisfaction with the place to stay (accommodation) |
sje8 | satisfaction with the surrounding environment |
sca9 | regularly interact with consumers |
sca10 | regularly interact with fellow MSMEs |
sca11 | know consumers |
sca12 | know about MSMEs |
sca13 | initiate regular meetings |
sca14 | interact with the government |
sca15 | provide input to the government |
sca16 | encourage the improvement of community education and skills |
sco17 | promote individual rights, both civil and human rights |
sco18 | proud to do business in this environment |
sco19 | accept locals to work |
sco20 | contribute to the progress of the city community |
sco21 | participate in solving surrounding issues |
sco22 | responsible for social objectives and solidarity |
sco23 | follow the applicable rules |
sco24 | have a good relationship with your neighbors |
eco25 | have access to financial sources as venture capital |
eco26 | have you increased your income since the beginning of your business |
eco27 | the income meets all of the firm's cost needs |
env28 | consider environmental eco-friendly in business management |
env29 | have you received training to develop your business |
env30 | the policies make it easier for business processes |
SCA intangibly exists in interpersonal relations (McBain, 2015) and represents a state of mutual trust (obligations and expectations), mutual openness (information channels), and compliance with socially applicable rules in a social group (social norms) (Forrest and Kearns, 2001).
SCO exists in a social group that has a common goal, is in social order, is solidary, and has social interaction and a sense of belonging to its social environments (Forrest and Kearns, 2001). In addition, SCO measures refer to the intensity of interaction, community involvement, and the breadth of social networks as key aspects of SCO (Shirazi and Keivani, 2017; Larimian and Sadeghi, 2021).
Economic sustainability on a national scale can be assessed through sustainability of income per capita, the GDP per capita, or the GNP per capita (Gutierrez et al., 2009). Overall, the objective is similar: namely, to assess the average value of the standard of living in a given region. At the micro scale (e.g., households, individuals, or firms), the economy is measured through total income, according to Case et al. (2012), which is the total value of the sale of goods and services in a certain period (month, year, etc.).
In the context of MSMEs, usual economic measures are revenue, sales, profit, investment, and asset as well as their indicators. Profit can be calculated as the total value of the sale of goods and services minus cost, including tax, which is referred to as net income. However, this calculation is difficult to apply to the informal sector, which tends not to follow tax regulations and policies. A revenue trend, net asset, and debt can be indicators of MSME’s economic sustainability (Case et al., 2012).
Global scale environmental sustainability covers such fields as climate change, deforestation, air pollution, and rising sea levels. MSMEs play a role in preventing these adverse impacts by strengthening policies and governance (DESA, 2019). Examples include improving access to capital and markets that promote environmental stewardship, as well as policies that encourage ease of green business operations. Environmental measures for MSMEs represent their eco-friendly operations; for instance, raw material efficiency, recyclability of raw materials and packaging, and energy and water consumption (Rao et al., 2006; Sundin et al., 2015; Dragomir, 2018).
The three indicators of social sustainability (SJE, SCA, and SCO) each consisted of eight sub-indicators, while ECO and ENV had three sub-indicators each. Thus, there were 30 sub-indicators in total. Accordingly, SJE, SCA, and SCO scores ranged from 8 to 40 while ECO and ENV scores ranged from 3 to 15. Higher scores represent higher sustainability. The mean score of sub-indicators was calculated to determine the aggregate indicator score.
3.3. Data Collection
The questionnaire collected 13 indicators representing social, economic, and environmental sustainability. All these variables were measured on a five-point Likert Scale from 1 (strongly disagree) to 5 (strongly agree). The scores of the Likert items for each respondent were summed up to obtain a composite/total score for each dimension. The Department of Makassar Cooperative and MSMEs (2020) shows that the MSME population in Mariso, Rappocini, and Bontoala subdistricts were 517, 408, and 381, respectively, with a total of 1,306. The minimum sample size was calculated to be between 93 and 306 according to the margin of error between 5 and 10%, using the following formula:
$$n=\frac{N}{1+N{e}^{2}}=\frac{\text{1,306}}{1+\text{1,306}\times {0.05}^{2}}=306 \left(1\right)$$
$$n=\frac{N}{1+N{e}^{2}}=\frac{\text{1,306}}{1+\text{1,306}\times {0.10}^{2}}=93 \left(2\right)$$
where \(n\) is the minimum suggested sample size, \(N\) is the target population, \(e\) is the margin of error chosen to be 5% for Eqs. (1) and 10% for Eq. (2). Accordingly, the total sample size was decided to be 300. The subsample size for the three subdistricts was calculated as follows:
$${n}_{1}=\left(\frac{{N}_{1}}{N}\right) \times n,{n}_{1}=\left(\frac{517}{\text{1,306}}\right) \times 300=118 \left(1\right)$$
$${n}_{2}=\left(\frac{{N}_{2}}{N}\right) \times n, {n}_{2}=\left(\frac{408}{\text{1,306}}\right) \times 300=94 \left(2\right)$$
$${n}_{3}=\left(\frac{{N}_{3}}{N}\right) \times n,{n}_{3}=\left(\frac{381}{\text{1,306}}\right) \times 300=88 \left(3\right)$$
where (1) is the sample size for MSMEs in the Mariso subdistrict, (2) for Rappocini, and (3) for Bontoala.
From the practical standpoint, convenience sampling was adopted, where MSMEs in the study area were visited one by one. Consent was sought for them to participate voluntarily in this research after being informed of the purpose of the study and the data collection process that would take place.
The questionnaire consisted of closed and open-ended questions. A pilot survey was conducted with 34 MSMEs to improve the survey instrument. Subsequently, the survey began and ended when 300 firms were interviewed. Finally, the raw data were entered into a spreadsheet and transferred into SPSS Statistic and R for quantitative analyses.
3.4. Data Analysis
Prior to the analysis, it is crucial to calculate Cronbach’s alpha coefficients to assess the internal consistency of the indicators (Gliem and Gliem, 2003). The Cronbach score ranges from 0 to 1, expressing the lowest to the highest (Tavakol and Dennick, 2011). The generally accepted rule for the alpha level is the range of 0.6–0.7, implying that a score below 0.6 is not acceptable for representing the concept and that a score above 0.95 indicates redundancy on the items scale of the study (Ursachi et al., 2015). An acceptable alpha level indicates that the set of sub-indicators are usable for assessment and further regression analysis.
Descriptive statistics were used to assess social sustainability indicators. To examine their relations with the economic and environmental indicators, regression analyses were performed by including the social indicators (SJE, SCA, SCO) as independent variables and the economic and environmental indicators as dependent variables. Other covariate variables were included as control variables, such as location, number of workers, and business scales, as well as the managing director’s personal profile, such as age, education, gender, and ethnicity (Makassar, Bugis, and others) (Table S2).
For the independent variables, sub-indicators in the ordinal scale were aggregated into interval scales through averaging over the several indicators. The categorical variables were converted into dummy variables, such as the location of MSMEs and gender. The same applied to the ordinal variable representing education.
The regression model is described as follows:
$${y}_{1}={\beta }_{\text{1,0}}+{\beta }_{\text{1,1}}{\chi }_{1}+{\beta }_{\text{1,2}}{\chi }_{2}+\dots +{\beta }_{\text{1,13}}{\chi }_{13}+{\epsilon }_{1}$$
1
$${y}_{2}={\beta }_{\text{2,0}}+{\beta }_{\text{2,1}}{\chi }_{1}+{\beta }_{\text{2,2}}{\chi }_{2}+\dots +{\beta }_{\text{2,13}}{\chi }_{13}+{\epsilon }_{2}$$
2
where \({y}_{1} \text{a}\text{n}\text{d}{ y}_{2}\) are economic and environmental indicators, respectively, \({\chi }_{1},{\chi }_{2},{\chi }_{3}\) are indicators of SJE, SCA, and SCO, respectively, \({\beta }_{\text{1,0}}\) and \({\beta }_{\text{2,0}}\) are the intercept terms, \({\beta }_{\text{1,1}},{\beta }_{\text{1,2}},{\beta }_{\text{1,3}}\), \({\beta }_{\text{2,1}},{\beta }_{\text{2,2}},\text{a}\text{n}\text{d} {\beta }_{\text{2,3}}\) are the slope coefficients for economic and environmental indicators, \({\chi }_{4} to {\chi }_{13}\) are the covariates, and \(\epsilon\) is the random error term.