Adi Wijaya
| Jiuhardi Jiuhardi | Saida Zainurossalamia ZA | Nurjanana Nurjanana | Erwin Kurniawan A.*
© 2023 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
In 1997-1998, the resilience of small and medium enterprises (SMEs) was tested when the monetary recession paralysed Indonesia. At that time, only SMEs were detected as shining and the most prominent from other sectors. This study is oriented to investigate the effect of the quality of human resources (HR), capital, and business length on turnover, labor cost, market share, and profit. The study design is offline survey, where primary data is collected from a sample that invites 285 respondents in three zones of Indonesia. Sources of information focused on and addressed to three SME scales covering the fields of trade, industry, and services. Then, the data is processed, filtered, and set using the structural equation model (SEM). The findings confirm that the HR quality and capital drives an increase in turnover, labor cost, market share, and profit. At one point, the business length actually only stimulated turnover, labor cost, and market share, but did not generate significant profits. But, significant of labor cost, market share, and profit followed the increase in turnover. Similarly, between labor cost to market share and profit, where the results are significant. The market share affects profit. It is important for a country to realize that disruptions in financial access, HR capabilities, and experience attributes trigger the inhibition of domestic market performance. These three alternatives give birth to strong SMEs.
HR quality, capital, business length, turnover, labor cost, market share, profit
In many countries, the growth of small and medium enterprises (SMEs) is one driver of the economy [1-4]. Garbie [5], Armawan and Sudarmiatin [6], Villaschi [7] and Haryadi et al. [8] understand that the level of competitiveness of SMEs in countries such as Singapore, Taiwan, Brazil, and South Korea or those who are members of the Newly Industrializing Countries (NIC's) are in productive, successful, and efficient phases and characteristics. Case studies for developed countries, such as India, China, and Saudi Arabia SMEs account for 32% of total exports and 40% of manufacturing industry output [9, 10]. Uniquely, Nanziri and Wamalwa [11], Lekhanya [12], Monteiro [13], Ndiaye et al. [14], and Adeosun and Shittu [15] review the portrait of the modernization of micro-enterprises in the African region which expands employment opportunities and national aggregates.
Throughout 2018-2019, the circulation of SMEs in creating added value continued to rise sharply to 2.88%, which was marked from 49,824,123 in 2018 to 51,257,537 units in 2019 [16]. Interestingly, although the prospects for SMEs are getting peaked, at the micro-level, the aggregates are massive [17].
Recent publications discussing the relevance of HR quality to SME turnover were examined by Arief et al. [18] and Nam and Luu [19]. As a result, a reliable HR element will cause an effective business transition for SMEs. Observations on the relationship between HR quality and turnover were explored, where training, development, and HR behavior are valuable investments for SMEs [20-22]. Integrated HR quality starts with market share and profit in SMEs [23-29]. This is because capital also takes part in shaping contemporary turnover, labor costs, market share, and profit [30-40].
Apart from the two scenarios above, SMEs are also required from the experience attached to the time span (duration). In the last decade, the effort to ensure increased turnover, labor costs, market share, and profit [41-47]. For discussion, Ugoani [48], Gyanwali [49], Coetzer et al. [50], and Yamin and Pratiwi [51] examine the integrated turnover of labor costs, market share, and profit in SMEs. Turnover involvement seems to have a significant effect. In order to protect market share and synergies with SME profits, there must be a firm determination of labor costs [52, 53]. Salavou [54] identifies the urgency of SME profit, without compromising an integrated market share.
Based on previous publications that presented logical consequences and differing facts about the perspective of production management, HR management, and financial aspects to improve the feasibility of SMEs, this study attempts to examine the function of HR quality, capital, and business length on turnover, labor costs, market share, and profits for SMEs in Indonesia. The procedure for this paper is structured: Step 1- Introduction, Step 2- Literature review, Step 3- Methodology, Step 4- Research results, and Step 5- Conclusions
The milestones of achievement of SMEs in the relatively inclusive national economy, but unfortunately it has no impact the business climate ecosystem, which is damaged by internal and external aspects. In detail, Lobo et al. [55], Sani et al. [56], Noreen and Junaid [57], Abrar-ul-haq et al. [58], and Engidaw [59] mention three crucial things towards improving SMEs. The first factor is ownership and control of production assets, the second is the suboptimal capacity of human resources, and business institutions have not been intense in distributing adequate infrastructure. On the other hand, Ogbole et al. [60], Al-Maskari [61], Sitharam and Hoque [62], Wang [63], and Lestari et al. [64] examines seven external points that frustrate SMEs, including the economic downturn with its various implications, disproportionate 'stealth' levies, fraudulent practices (manipulation), market failures, minimal commodity innovation, some crafts and fashion are hit by popularity, funding allocations credit is still unequal in the village, and guarantees of legality (recognition) for SMEs. On the way, the condition of low education is a technical obstacle for SMEs. In the context of knowledge, education will affect insight, thinking techniques, and decision making [65, 66]. With intelligence acceleration, it becomes easier for skills in entrepreneurship [67].
According to Rantapuska and Ihanainen [68], the type of entrepreneur controlled productivity with an educational background, comprehensive expertise, and adaptive technology adjustment. In addition, the ability of entrepreneurs to take risks and make it easier for them to overcome polemics [69-71].
Controversial discussions of SMEs in the third world, especially urban areas in Indonesia, often find the inability of small industries to bridge and reduce poverty or unemployment crises [72-74]. Behind that, there are concerns about the government's attention to the existence of the informal sector and small industries [75]. In fact, SMEs are the foundation that strengthen the economy of business activists [76]. Another fact is that local governments are committed to the formal sector, which is easier to control and which already has prestige than conservative businesses that are still trying to get out of the trap of a myriad of problems [77, 78]. In general, Melliny et al. [79], Tambunan [80], and Cosrojas and Eguia [81] reasoned that SMEs absorb around 60% of workers who are concentrated in big cities in developing countries. In the end, even though SMEs are not facilitated by the government, they are pioneers in natural resource management, providing employment, establishing market networks, tying extensive trade connections, supporting various groups, and opening partnerships [82-86]. Unexpectedly, SMEs in Indonesia survived the economic contraction in 1997-1998 and are now the foundation of social life [87-89].
Recently, Indonesia has been known as a holistic 'initial endowment' [90]. It articulated this diversity of resources as a business inspiration that SME activists who have limited capital can use. Rationally, SMEs employ local communities and migrants, thereby supporting superior economic growth (GDP) [91, 92]. In turn, economic calm will increase, which is reflected in per capita income [93, 94].
3.1 Measures
This research is a study that validates causal relationships between variables through hypothesis testing or explanatory based [95-97]. The causal relationship discussed regarding the relationship between the set variables includes capital, productivity, and SME profit. Small capital comprises physical and non-physical capital. The dimensions of productivity per sector of small businesses are concentrated in the trade, industry, and services sectors (see Table 1).
Table 1. Map of variables and expectations
|
Dependent |
Independent |
Prediction |
Literatures |
|
Turnover |
HR quality, capital, and business length |
+ |
[98-100] |
|
Labor cost |
HR quality, capital, business length, and turnover |
+ |
[24, 101-103] |
|
Market share |
HR quality, capital, business length, turnover, and labor cost |
+ |
[48, 104-106] |
|
Profit |
HR quality, capital, business length, turnover, labor cost, and market share |
+ |
[33, 107-110] |
Referring to these premises, a study model that focuses on the profit of SMEs is designed in a holistic strategic context in fundamental market mechanisms. Furthermore, considering that trade, manufacturing, and services, the inputs and outputs of these businesses support small businesses are also different. This variation in the inputs and outputs of small businesses makes the study unravel and adjust to groups of business units during 2021 (quarterly).
The object of the study is small businesses belonging to the SME group, while the data set subjects are small entrepreneurs in western, eastern and central Indonesia. The selection of research zones in Indonesia is related to the dynamics of SMEs. The specific relationship between the observed case study is motivated by inequality in welfare, the backwardness of the SME cluster and regulatory pressures to achieve SME growth. In addition, Indonesia has a more complete diversity of SMEs per sector and is dispersed between the spheres of trade, industry and services. Thus, Indonesia represents providing data. We conducted interviews between February 2022 – May 2022.
3.2 Population and sampling
Study concentration is 3,701 SMEs, where this business unit is under the auspices of the government, which is empowered in terms of capital and legality. Considering that the SME unit is relatively large, the sampling needs to be considered with the assumption that the SME tendency is homogeneous, so that the sample reflects the characteristics of the population. It applied sampling using a cluster random sampling approach for the three types of businesses (trade, industry, and services) inhabited by small businesses [111-114]. Pu et al. [115] explained that cluster random sampling is applied by dividing the population into small clusters, then observing the sample is chosen at random. This parameter is widely applied to field surveys of geographic disciplines [116, 117]. The population is divided into groups, then a sample of observations is randomly selected. The advantage of this technique is that it makes the sampling process cheaper and faster than using simple random sampling [118, 119]. Determination of sample size through the Slovin function is formulated below.
$n=\frac{N}{1+N e^2}$
where; sample size (n), population (N), and the percentage of allowance for inaccuracy due to tolerable sample error (e). With a population of 3,701 SMEs and the stipulation that the value of e is 5%, the sample unit is formulated as follows:
$n=\frac{3,701}{1+\left\{(3,701)(0.05)^2\right\}}$
$n=\frac{3,701}{12.96}$
$n=285.5$
Based on the Slovin standard, 285.5 units were obtained and rounded up to 285 samples. Table 2 details the distribution of samples from the micro and small business groups.
Table 2. Distribution of samples by classification
|
Pillar |
Population |
Sample |
|
Trade |
2,445 |
188 |
|
Industry |
646 |
50 |
|
Services |
609 |
47 |
Source: [120].
3.3 Data source
Primary data and cross-section data support the data scope. Cross-section data were collected through data groups from different respondents, but at the same time point [121]. Due to the form of an interview invitation, the first source needs to be tabulated with a questionnaire [122]. Thus, the acquisition of primary data highly depends on the questionnaire instrument.
3.4 Econometrics
Based on the structural model in the conceptual framework, it can form statistical equations via multiple regression. Testing the model described the closeness between variables to determine the effect. Interpreting the data was analyzed using a structural equation model (SEM). Model estimation and path analysis begin with operating the equations, thus forming a simultaneous equation system. First, the ratio and ordinal data transformations are adjusted to an interval scale. The chronology of the functional model with a reduced form is described as follows:
Y1 = f (X1, X2, X3)
Y2 = f (X1, X2, X3,Y1)
Y3 = f (X1, X2, X3, Y1, Y2 )
Y4 = f (X1, X2, X3, Y1,Y2, Y3)
where; function (f), HR quality (X1), capital (X2), business length (X3), turnover (Y1), labor cost (Y2), market share (Y3), and profit (Y4). Referring to the equation function above, forming a non-linear regression model or exponential regression with the matrix adapted to be:
lnY1 = lnα0 + β1lnX1 + β2lnX2 + β3lnX3 + μ1
lnY2 = lnα0 + β4lnX1 + β5lnX2 + β6lnX3 + β7lnY1 + μ2
lnY3 = lnα0 + β8lnX1 + β9lnX2 + β10lnX3 + β11lnY1 + β12lnY2 + μ3
lnY4 = lnα0 + β13lnX1 + β14lnX2 + β15lnX3 + β16lnY1 + β17lnY2 + β18lnY3 + μ4
where; α0 (constant), μ1..,4 (error), ln (logarithm), dan β1..,18 (beta coefficient).
4.1 SME characteristics
Table 3 reports that the average sample size for SMEs fostered by the government comes from Western Indonesia. As many as 49% of business units in Java have proven to be successful and growing, while the remaining 23% of the sample of SMEs are in Sulawesi Island and 28% of SMEs are concentrated in Bali and Kalimantan islands. By using a proxy to add up the level of education and work experience, a recapitulation of answers from respondents is got regarding the quality aspect of HR resources.
Small entrepreneurs who receive formal education are almost equal to those who do not have formal education certification, where 43% are respondents with quality human resources below 20 years, while 57% are respondents with quality human resources above 20 years. Although the level of education is low, high entrepreneurial experience accompanied it by small business controllers.
Table 3. Demographic data (n = 285)
|
Profile |
Frequency |
Percentage |
|
Zona
|
65 141 79 |
23 49 28 |
|
HR quality
|
123 162 |
43 57 |
|
Capital
|
138 147 |
46 54 |
|
Business length
|
110 175 |
39 62 |
|
Turnover
|
118 167 |
46 64 |
|
Labor cost
|
172 94 19 |
60 33 7 |
|
Market share
|
50 235 |
18 83 |
|
Profit
|
115 170 |
45 55 |
Source: Authors, based on surveys.
Capital is defined as the operating capital of a small business. Business capital is obtained from individual capital and loan capital, which is measured on an average per year. In general, SMEs with business capital below IDR 15,000,000 amounting to 46% seem to be balanced with businesses with capital above IDR 15,000,000 reaching 54%. For the business length profile, it means that the SME operational period is one year. Meanwhile, 62% of small businesses operating in Indonesia are over 20 years old and 39% are under 20 years old. This represents that small entrepreneurs in Indonesia are classified as continued or successor businesses from the previous generation.
From Table 3, it is also known that business turnover represents the nominal gross income received by SMEs based on average production or sales during the last 2021. Most of small business turnover is already more than IDR 80,000,000 or 64%. In addition, 46% still have a turnover below IDR 80,000,000. The turnover of SMEs in Indonesia dares to take risks. Regarding labor costs, it is calculated based on labor expenditure costs, such as bonuses, wages, and health insurance. There are 63.8% of SMEs with labor costs below IDR 1,250,000 or have not adjusted to the provincial minimum wage rate (UMP). Only 36.1% of small businesses have implemented UMP to keep their employees above IDR 1,250,000.
Furthermore, market share is the percentage of product control over the entire market that is controlled by similar business actors at a certain time and place. The successful SMEs in Indonesia have a market share of around 83% and 18% of small businesses could not control their market share. Even so, the market share is almost uniform and only a small part does not meet the criteria for domestic and foreign markets. Then, profit is implicitly generated by small businesses for one year. Sales proceeds also supported profit with less cost of goods and operating costs. In Indonesia, 55% of SME profits are above IDR 50,000,000. The rest, there are 45% of SMEs that have a profit below IDR 50,000,000.
4.2 Statistical analysis
The SEM method does not transfer latent variables because, in this study, it does not contain elements of perception indicators, but items with an interval scale. Therefore, Confirmatory Factor Analysis (CFA) is not applied to validity testing, but a Goodness of Fit (GoF) test and a simultaneous test. These statistical parameters aim to examine the independent variables on the dependent variables. Therefore, the study is not to compare which independent variables are the most dominant (comparative analysis) to the dependent variable. SEM analysis shows that this model is fit or workable as a structural model (see Table 4).
Table 4. Evaluation of the model
|
Parameters |
Cutt-off |
Value |
Remarks |
|
Chi-square |
Expected small |
4.068 |
Fit |
|
Probability |
≥ 0.05 |
0.254 |
Fit |
|
Relative Chi-Square |
≤ 2.00 |
1.356 |
Fit |
|
RMSEA |
≤ 0.08 |
0.035 |
Fit |
|
CFI |
≥ 0.94 |
0.998 |
Fit |
|
TLI |
³ 0.95 |
0.985 |
Fit |
Source: Authors, based on AMOS 16.
The parameter provisions based on ‘unstandardized regression weights’ have passed the GoF test, where the model does not use ‘standardized regression weights’ even though it also meets the GoF criteria. The next step is to examine the significance of the relationship between variables (see Table 5). Critical ratio (CR) or probability (ρ) describes partial testing in regression weights. The CR score is the same as the t-value for the ordinary (non-structural) regression method.
Table 5. Estimated intercept
|
Linkages |
Value |
CR |
ρ |
|
Y1 = f (X1, X2, X3) |
12.257 |
19.239 |
0.000 |
|
Y2 = f (Y1, X1, X2, X3) |
9.828 |
3.492 |
0.000 |
|
Y3 = f (Y2, Y1, X1, X2, X3) |
16.975 |
0.446 |
0.655 |
|
Y4 = f (Y3, Y2, Y1, X1, X2, X3) |
2.491 |
2.519 |
0.012 |
Source: Authors, based on AMOS 16.
AMOS 16 output concludes the regression coefficient between the HR quality, capital, and business length on turnover, labor costs, market share, and SME profits. With a positive coefficient, the HR quality affects turnover, labor costs, market share, and profit.
Capital has a positive effect on labor costs (β = 0.458), market share (β = 0.164), market share (β = 0.421), and profit (β = 0.554). The role of capital also increases turnover, labor costs, market share, and profit, where the coefficient is positive (β = 0.341, β = 0.321, β = 3.578, and β = 0.247). Likewise, with the business length, its contribution to turnover, labor costs, market share, and profit is positive, as indicated by β = 0.155, β = 0.107, β = 1.664, and β = 0.031. Table 6 also recognizes that turnover plays a role in the continuity of labor costs (β = 1.406), market share (β = 2.802), and profit (β = 0.448).
Table 6. Verification of hypothesis
|
|
Path |
Coeff. |
CR |
ρ |
Support |
|
H1 |
HR Quality à Turnover |
0.458 |
2.917 |
0.042** |
Adopted |
|
H2 |
HR Quality à Labor Cost |
0.164 |
2.484 |
0.025** |
Adopted |
|
H3 |
HR Quality à Market Share |
0.421 |
2.301 |
0.028** |
Adopted |
|
H4 |
HR Quality à Profit |
0.554 |
3.529 |
0.022** |
Adopted |
|
H5 |
Capital à Turnover |
0.341 |
9.334 |
0.000*** |
Adopted |
|
H6 |
Capital à Labor Cost |
0.321 |
2.631 |
0.036** |
Adopted |
|
H7 |
Capital à Market Share |
3.578 |
2.224 |
0.026** |
Adopted |
|
H8 |
Capital à Profit |
0.247 |
2.205 |
0.047** |
Adopted |
|
H9 |
Business Length à Turnover |
0.155 |
1.823 |
0.059* |
Adopted |
|
H10 |
Business Length à Labor Cost |
0.107 |
1.672 |
0.066* |
Adopted |
|
H11 |
Business Length à Market Share |
1.664 |
2.904 |
0.037** |
Adopted |
|
H12 |
Business Length à Profit |
0.031 |
0.872 |
0.383 |
Rejected |
|
H13 |
Turnover à Labor Cost |
1.406 |
8.139 |
0.000*** |
Adopted |
|
H14 |
Turnover à Market Share |
2.802 |
2.263 |
0.049** |
Adopted |
|
H15 |
Turnover à Profit |
0.448 |
7.388 |
0.000*** |
Adopted |
|
H16 |
Labor Cost à Market Share |
0.193 |
1.969 |
0.056* |
Adopted |
|
H17 |
Labor Cost à Profit |
-0.342 |
16.776 |
0.000*** |
Adopted |
|
H18 |
Market Share à Profit |
0.003 |
1.745 |
0.022** |
Adopted |
Info: *) p <0.1, **) p <0.05 and ***) p <0.01; Source: Authors, based on AMOS 16.
Although labor cost has a positive relationship with market share (β = 0.193), it does not have a positive relationship with profit because β = -0.342. Referring to the acquisition of the coefficient of market share (β = 0.003), then it is evidence that the increase affects profit positively.
Panjaitan et al. [123] and Tambunan [124, 125] filter some causes of the lagging behind SMEs in Indonesia compared with other countries. There are eleven indicators to measure it, namely product clusters and workforce creativity, profit structure, domestic and export market shares, investment, market clusters, business operations and networks, capital stability, excellent human resources, management professionalism, individual conflicts of interest with business, and fairness accountability. With the achievements collected by SMEs in Indonesia, this is contrary to strict supervision and seriousness [126]. Unfortunately, many SMEs are not concerned about fixing the problems related to the pillars described previously.
To answer this challenge, policy makers have high expectations of the existence of SMEs holding the foundation for fair development, bringing jobs, providing broad economic services, supporting millions of people, restoring economic independence, and bringing national stability. To prioritize this, the study responds to and supports SMEs as siding with people's economic business groups, even though the role of SMEs is still limited. It should be noted that the motivation of this study is to provide appropriate terminology regarding the characteristics attached to internal weights and external factors.
The essence of this study aims to explore the determination between the HR quality, capital, and business length on turnover, labor costs, market share, and profit in SMEs in Indonesia. The SEM approach shows the path structure of these variables. Eight hypotheses were tested whether the impact was significant or otherwise. Throughout 2021, the HR quality and capital has had a significant effect on turnover, labor costs, market share, and profit. Although the business length affects turnover, labor costs, and market share significantly, its role does not affect profit. Turnover also influenced the increase in labor costs, market share, and profit. Uniquely, the increase in labor costs has significant implications for market share and profit. Then, a strong market share also supports a significant increase in profit.
The quality of HR is an important part in the survival of SMEs, so the quality of the workforce needs to be accelerated with skilled programs. A provision of formal and non-formal education and training is relevant to the advancement of knowledge. The routines of government institutions and non-government institutions that often organize SME training are the proper answer for small businesses to delegate their talents to learn and hone skills.
The problem of SME capital is very limited. This is certainly a dilemma, given the limited capacity of the government. Although the assistance provided by the government has not been maximized, the government can act as a facilitator connecting access to capital loans at banks and financial institutions. With the increase in capital, it is possible for SMEs in Indonesia to innovate to expand their market network. Efforts to propose and establish an organization for SMEs, such as a business community, for SMEs to simply share experiences and exchange information. This is useful in order to broaden the horizons of SMEs.
There are limitations in this study, so the weakness that appears is that there are still several factors that are thought to influence profits. Indeed, not all variables can be studied, so academic recommendations pose a challenge for future researchers who are interested in studying the topic of SMEs. Other dimensions such as entrepreneurial characteristics, business size, and business environment need to be highlighted their effects on SMEs, enriching the knowledge pool.
The authors thank the Faculty of Economics and Business – Mulawarman University as a sponsor (internal grant) for this study. There is no conflict of interest in this paper. The authors would like to appreciate for the professional blind review of IJSDP.
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