Factor Analysis of Perceived Challenges for Listing on SME Platforms: A Study of SMEs in Gujarat State
- Prajapati Dahyalal Bansilal
- Dr Chirag Rasikbhai Patel
- 1214-1223
- Jun 20, 2025
- Economics
Factor Analysis of Perceived Challenges for Listing on SME Platforms: A Study of SMEs in Gujarat State
Prajapati Dahyalal Bansilal1, Dr Chirag Rasikbhai Patel2
1Research Scholar, Sankalchand Patel University, Visnagar, Adidhan Ventures Private Ltd.,
2Associate Professor, Sankalchand Patel University, Visnagar
DOI: https://doi.org/10.51584/IJRIAS.2025.1005000108
Received: 06 June 2025; Accepted: 09 June 2025; Published: 20 June 2025
ABSTRACT
SMEs play a crucial role in any country’s economic development. 90% of firms in India are SMEs. Availing financing is one of the critical issues with respect to growth and sustainability of SMEs. Their personal savings, friends and family, banks, NBFCs, venture capital, private equity, angel investors and public equity are just a few of the numerous ways they exercise to fund their business requirements. Public equity is a significant source of funding for all business enterprises. Many countries have created frameworks for SMEs to list on exchanges and obtain debt-free funding as well as alternative investment markets or SME platforms. As listing on exchanges is one of the mainstay options, it is essential to understand what challenges do SMEs face while thinking of listing. Perceived challenges while listing on SME platforms were examined in the current study. A total of 132 SMEs were contacted in order to gather primary data through structured questionnaire. Factor analysis and descriptive analysis were carried out to identify leading challenges with respect to listing on SME platforms. BSE SME is more known to respondents compared to NSE Emerge. Less than 16% SMEs have mindset to get listed on SME platform. The factor analysis revealed six main challenges: Compliance Intensity, Funded Scale and External Control, Structure and Stability, Strategic Ownership Defense and Longevity, Regulatory Conformity for Brand Growth and Perceived Complexity in Decision Making.
Keywords: SME, SME Platform Awareness, SME Listing Challenges, Factor Analysis
INTRODUCTION
Small and medium businesses are important for most of the economies in the world. Globally, half of jobs and ninety percent of enterprises are taken care by SMEs. If one looks at numbers among emerging economies, SMEs contribute up to 40% of GDP (WorldBank, 2024). This contribution to GDP is by far significant. Small and medium enterprises (SMEs) or Micro, Small and Medium Enterprises (MSME) are companies that fall below a specific threshold in terms of revenue, assets or workforce size. Every nation has a different definition of a small to medium-sized business. Table no. 1 explains SMEs definition in India.
Table No. 1: Classification of Micro, Small and Medium Enterprise (MSME) Sector Based on Composite Criteria
Classification | Investment in Plant & Machinery / Equipment | Annual Sales Turnover |
Micro | Up to ₹1 crore | Not exceeding ₹5 crores |
Small | Up to ₹10 crores | Not exceeding ₹50 crores |
Medium | Up to ₹50 crores | Not exceeding ₹250 crores |
In India, the Micro, Small, and Medium Enterprise (MSME) sector has grown to be a major economic player generating jobs, exporting goods and services and fostering inclusive growth. Micro, Small, and Medium-Sized Enterprises (MSME) constitute the foundation of our nation’s socio-economic advancement. In addition, it makes up 40% of all exports, 45% of industrial production and a sizeable portion of the GDP. The MSME manufacturing sector provides 7.09% of the GDP. Additionally, MSMEs account for 30.50% of services. MSMEs provide 37.54 percent of the GDP overall.[1] These statistics are reflective of their role. Numbers are bound to expand in next couple of decades.
For SMEs to launch, expand, and prosper, they must have access to suitable funding sources. The situation is far from ideal. They want funding a lot more than a lot more! However, persistent obstacles still exist in their way (OECD, 2024). SMEs need access to suitable funding sources for all phases of their life cycle. This does include when they begin as startups, while expanding and for development. SME access to bank financing is impacted by fluctuations and shocks in the credit markets on which they are too dependent for survival and more (OECD, 2024). SMEs’ ability to grow and expand depends significantly on availability of finance. The case becomes severely so in case SMEs are from emerging economies. This is perceived as one of the most frequently considered barriers to becoming larger entities (WorldBank, 2024). On one hand availing bank finance is difficult and on the other hand growing SMEs need more funding for multiple purposes and tenures. To summarize better, a constant and quick growth in funding requirements and fluctuating credit availability happen to eclipse future, operating efficiency and potential scaling up.
SMEs often struggle to secure bank loans for business start-ups, relying on internal capital or family support. As per an estimation of International Finance Corporation, there are about 65 million firms whose funding requirements are unfulfilled. Another number, 40% of small firms from developing nations are funding starved. Additional $5.2 trillion are required annually to take care of SMEs needs. This number is 1.4 times existing global lending to SMEs (WorldBank, 2024). This indicates extreme shortage of credit by miles. Banks and other financial institutions are the most preferred source of funding, although MSMEs still rely on their own resources. These may include friends and family as one of the first priorities within internal sources. They even consider money lenders for meeting financing needs of their business (Sarkar & Ghosh, 2024). As bank credit is formal source of credit involving structured credit assessment, appraisal of business activities and even promoter groups, SMEs try to manage through internal and informal sources of credit. There they prefer to raise money internally, with bank funding coming in second, primarily in the form of long-term loans and money from financial and governmental agencies. External equity is the least desired source of funding (Baker, Kumar, & Rao, 2020). Here, small businesses revolve around multiple options and each option has its advantages and limitations with respect to cost and consequences. For example, bank loans and financing by government agencies are two comprehensively different sources of credit with respect to cost and consequences.
Listing on a stock market enables businesses to raise long-term equity financing by making shares available to investors. This is often used for consolidation and expansion goals, such as building new facilities or repaying venture capital backers. Listing also attracts private investors such as venture capital trusts, business angels and enterprise investment schemes. However, listing has its disadvantages. They include high costs, compliance burdens, uncertain timing, additional regulatory requirements and loss of control over the company[2]. Listing broadens the canvas for small businesses and for that sake businesses of any size. Diverse set of market participants as listed above are involved depending upon attractiveness of the issue on offer. To some extent if the business has set of competencies and potential to grow there happens to be a healthy competition among those investing entities or individuals.
There are total of 633.9 lakh MSMEs in India. Out of that 99% of MSMEs are micro-enterprises that make up to 630.5 lakh enterprises. There are 3.3 lakh small businesses i.e. 0.5% of all MSMEs and just 0.05 lakh are medium businesses i.e. 0.01% of all MSMEs[3]. But only 695 SMEs got listed on BSE SME[4] platform and 535 companies on NSE Emerge[5]. The data indicates that external equity or listing on SME exchanges is least preferred source of financing for SMEs. As against the universe of SMEs, the ones listed are negligible in numbers. However, it must be noted that all SMEs are not necessarily expected to list themselves. Listing is one of the biggest transitioning for SMEs in their life cycle. Thus, it is important to study all those businesses that qualify for listing should be facilitated through wherever support is required by them. In the present study, an attempt was made to understand perceived challenges for listing on SME exchanges.
LITERATURE REVIEW
Various studies were found with respect to factors affecting listing and challenges for SMEs while they wish to list their enterprises. Some studies were revieved from emerging econmies. There is a study conducted in Zambia. The factors influencing SME listing in Zambia were examined by Kawimbe, Sishumba, Sikazwe and Saidi (2022). Numerous important aspects such as the business management, the legal environment and the channels available to help SMEs have a major role in determining the listing of SMEs. This provides basic and broad framework to explore the subject under study. In order to foster the growth of alternative securities markets for small and medium-sized enterprises (SMEs), it is imperative to evaluate many criteria including corporate governance, regulatory compliance, information accessibility and support for SME platforms as the determining factors for small and medium-sized business listing. In this case, support for platforms derives a constructive context. As per the report of International Organization of Securities Commissions (IOSCO), the number of years that SMEs have been in business, the number of public shareholders, the minimum number of shareholders, profitability requirements, and registration fees for admission to trading and listing maintenance are among the factors that have been found to have an impact on SMEs’ listings. In addition to this, high cost of raising capital from market, filing prospectus and other documents are also challenges for SME listing (IOSCO, 2015). Khatun & Amanullah (2021) have studied SMEs and exchanges within Bangladesh. They identified few more factors like change of forms of business, shared ownership, managing pre issue funds, reporting and disclouser, cost of listing etc. Semenya & Dhilwayo (2020) studied that why SMEs are not listing on Johneseburg Stock Exchange on the Alternative Exchange (AltX) platform of South Africa. Nassr & Wehinger (2016) studied opportunities and challenges of public equity markets for SMEs. Some reasons were found for not using public equity markets for fund raising like ‘having own sufficient funds’, ‘not interested to list’, ‘control of business’ etc. These studies have direction from their geographival landscape. Chitekuteku & Sandada (2016) studied factors influencing SMEs to register on alternate securites market (ASM) in Zimbabwe. They found ‘information accessibility’, ‘regulatory requirement’, ‘corporate governance’ and ‘SME support platforms’ as relevant factors.
However, a review of studies in the Indian context would avail more precise direction for this research. Pimple & Rai’s 2015 study on 85 MSME in Maharashtra revealed that SMEs fear being listed due to a lack of awareness. This fear is a major reason for the slow growth of SME Exchanges in India, as entrepreneurs lack knowledge about the program’s benefits, technical requirements, and the listing process. Small and medium-sized enterprises prefer to wait a few years to list on the main exchange board, as they have minimal regulatory obligations and nearly identical compliance costs compared to regular listed companies. Verma & Tiwari (2022) have studied issues and challenges of SME exchanges in India. Lungu (2020) have examined factors using factor analysis method. They found what stops SMEs from listing. Additional factors were corporate governance and transaction cost.
Research Gap
Despite the critical role SMEs play in Gujarat’s economy, there is limited research focusing specifically on the challenges they face when listing on SME platforms like BSE SME and NSE Emerge. Existing studies are predominantly national or international and fail to address regional differences. Additionally, there is a lack of detailed analysis that breaks down the perceived challenges into specific actionable factors. Addressing these gaps is essential for developing effective interventions and policies to support SME listings in Gujarat.
RESEARCH METHODOLOGY
The research was aimed (i) to understand funding preferences of SMEs and (ii) to study perceived listing challenges and identify leading factors from perceived challenges. In the present study, Organisation characteristics, awareness about SME platforms and challenges of listing on SME platforms were studied. The challenges of SME listing were measured through 21 statements on five-point Likert scale (strongly agree to strongly disagree). Total 132 SMEs across Gujarat state were contacted for the responses to understand the scenario. Research type in present study is fundamental or pure or basic research (Kothari, 2004). The data was collected only once so descriptive single cross sectional research design was used (Cooper & Schindler, 2014). The secondary data in the form of past research work, articles, comments etc. were collected from various sources. Primary data was collected through systematically designed interviewer administered questionnaire. The non-probability convenience sampling method was used for data collection. For data analysis descriptive analysis and factor analysis was performed. With the help of factor analysis, major challenges for SME listing were identified.
Data Analysis
Table No. 2 Descriptive Analysis (N = 132) | ||||
Sr. No. | Variable | Items | Frequency | Percentage (%) |
1 | No. of Years of Establishment | upto 10 | 73 | 55.3 |
11 to 20 | 47 | 35.6 | ||
21 to 30 | 6 | 4.5 | ||
>30 | 6 | 4.5 | ||
2 | Nature of Industry | Manufacturing | 77 | 58.3 |
Service | 39 | 29.5 | ||
Trading | 16 | 12.1 | ||
3 | Scale of Business | MICRO | 33 | 25 |
SMALL | 57 | 43.2 | ||
MEDIUM | 42 | 31.8 | ||
4 | Experience of Respondents | LESS THAN 3YEARS | 19 | 14.4 |
3-5 YEARS | 30 | 22.7 | ||
5-10 YEARS | 36 | 27.3 | ||
10-20 YEARS | 38 | 28.8 | ||
MORE THAN 20 YEARS | 9 | 6.8 | ||
5 | Annual Sales | LESS THAN 25CR | 79 | 59.8 |
25-50 CR | 30 | 22.7 | ||
50-100CR | 11 | 8.3 | ||
100-200CR | 8 | 6.1 | ||
MORE THAN 200CR | 4 | 3 | ||
6 | Qualification of Respondents | UPTO HSC | 8 | 6.1 |
GRADUATE | 46 | 34.8 | ||
ELEMENTARY SCHOOLING | 2 | 1.5 | ||
POST GRADUATE | 62 | 47 | ||
PROFESSIONAL DEGREE | 14 | 10.6 | ||
7 | No. of Employees | LESS THAN 50 | 93 | 70.5 |
51-100 | 26 | 19.7 | ||
101-300 | 6 | 4.5 | ||
301-500 | 5 | 3.8 | ||
MORE THAN 500 | 2 | 1.5 | ||
8 | Average Annual Capital Requirement | 11-30CR | 26 | 19.7 |
31-50 CR | 8 | 6.1 | ||
LESS THAN 10 CR | 94 | 71.2 | ||
51-100 CR | 3 | 2.3 | ||
MORE THAN 100 CR | 1 | 0.8 |
The study reveals that the majority of small and medium enterprises (SMEs) have been established for up to 10 years. A substantial portion (35.6%) have been operational for 11 to 20 years. Manufacturing is the most prevalent sector among SMEs, with 58.3% involved in this sector. Service-oriented SMEs constitute 29.5%, while trading enterprises form the smallest segment at 12.1%. The experience of respondents varies widely, with 14.4% having less than three years of experience, 22.7% having 3-5 years, and 28.8% with 10-20 years of experience. The qualification of respondents shows a significant portion are well-educated, with only 6.1% having education up to the Higher Secondary Certificate, 34.8% being graduates, and 1.5% having elementary schooling. 47% of respondents are postgraduates, and 10.6% hold professional degrees indicating a high level of educational attainment within the SME sector. 70.5% of SMEs have fewer than 50 employees. The average annual capital requirement for most SMEs is less than Rs. 10 crores.
Table No. 3 Awareness About SME Platform (N=132) | |||
Sr. No. | Name of SME Platform | Frequency | Percentage (%) |
1 | BSE SME | 110 | 83.3 |
2 | NSE Emerge | 82 | 62.1 |
According to the data, the Bombay Stock Exchange SME (BSE SME) platform is the most well-known, with 83.3% of respondents indicating awareness of it. The National Stock Exchange’s NSE Emerge platform is known to 62.1% of respondents. These findings indicate that while both platforms have a significant presence, there is a higher level of awareness and possibly preference for the BSE SME platform among SMEs. Whether this higher level of awareness for the given platform benefits the exchange or not is important. But this level of awareness is reasonable level of awareness.
Table No. 4 Approach for Listing | ||
Answer of SMEs | Frequency | Percentage (%) |
Yes | 21 | 15.9 |
No | 111 | 84.1 |
Only 15.9% of the SMEs have been approached for listing, representing a frequency of 21 out of the 132 respondents. This relatively small percentage indicates that a limited number of SMEs are being directly targeted for listing opportunities on platforms such as BSE SME and NSE Emerge. On the other hand, a substantial majority, 84.1%, have not been approached for listing. This high percentage, accounting for 111 out of 132 respondents, suggests that there is either a lack of outreach or that many SMEs have not yet become targets for such initiatives.
Intention of getting listed: The mean score of the intention of SMEs to get listed on a platform, based on a five-point Likert scale (where 1 = Definitely Yes and 5 = Definitely No), is 2.3030. This score indicates a moderately positive inclination towards getting listed. A score of 2.3030 suggests that, on average, SMEs are leaning towards a positive intention to get listed, but there is still some hesitation. This moderate level of intention could be influenced by various factors, such as the perceived benefits and challenges of listing, the awareness and knowledge about the listing process, and the current financial and operational status of the SMEs.
Challenges for SME listing: There were 21 statements asked to the respondents on a five-point Likert scale (Strongly Agree to Strongly Disagree.).
Table no. 5 Reliability Statistics | |
Cronbach’s Alpha | No. of Items |
0.753 | 21 |
Cronbach’s Alpha is a measure of internal consistency or reliability of a scale. With a value of 0.753 for 21 items, the scale demonstrates acceptable reliability. It is indicating that the items on scale are measuring the same underlying construct fairly consistently.
Factor Analysis: Factor analysis was performed to generate major factors from list of challenges SMEs face for listing on SME platform. Principal component analysis method for factor extraction and varimax rotation method was used. Items having less than 0.5 coefficient value were considered small co-efficient and suppressed. In the current section output tables are presented and discussed. There were six major factors (Challenges to SME Listing) identified.
Table No. 6 KMO and Bartlett’s Test | ||
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. | 0.657 | |
Bartlett’s Test of Sphericity | Approx. Chi-Square | 1417.848 |
df | 210 | |
Sig. | 0.00 |
The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity were conducted to determine the suitability of the data for factor analysis. The KMO value was found to be 0.657. This indicates that the sampling adequacy is acceptable. If Kaiser-Meyer-Olkin Measure of Sampling Adequacy is equal or greater than 0.60 then proceed with Exploratory Factor Analysis; the sample used was adequate. If Bartlett’s test of sphericity is significant (p < 0.05), then proceed with the Exploratory Factor Analysis.
Table No. 7 Communalities | |||
Sr. No. | Items | Initial | Extraction |
1 | Issue cost is high | 1 | 0.362 |
2 | Low liquidity in stock market | 1 | 0.788 |
3 | Procedural compliance is high | 1 | 0.724 |
4 | Lack of knowledge about market and process | 1 | 0.644 |
5 | Participation of institutional investors is less | 1 | 0.643 |
6 | Disclosure requirements are high | 1 | 0.843 |
7 | Strict regulations are there | 1 | 0.812 |
8 | Right valuation does not meet up | 1 | 0.603 |
9 | Lack of availability of skilled manpower | 1 | 0.574 |
10 | Hostile takeover risk | 1 | 0.718 |
11 | Survival issue in long term | 1 | 0.68 |
12 | Corporate governance follow-up | 1 | 0.75 |
13 | Loose control on company | 1 | 0.806 |
14 | Larger scale | 1 | 0.648 |
15 | More funds | 1 | 0.784 |
16 | External control | 1 | 0.681 |
17 | Greater brand awareness | 1 | 0.525 |
18 | More structure | 1 | 0.727 |
19 | Complying with regulations | 1 | 0.725 |
20 | Conflict among existing owners | 1 | 0.708 |
21 | More difficult decision making | 1 | 0.704 |
Extraction Method: Principal Component Analysis. |
Communalities reflect the proportion of variance in each item that is accounted for by the extracted factors. The values in the “Extraction” column represent the amount of variance each item shares with the factors. Overall, items such as “Disclosure requirements are high” (0.843), “Strict regulations are there” (0.812), and “Loose control on company” (0.806) exhibit high communalities, indicating that these items are well-represented by the underlying factors. These items have substantial variance explained by the factors, suggesting they are strongly related to the dimensions extracted from the data. Conversely, “Issue cost is high” (0.362) has a low communality, suggesting that it shares less variance with the factors and may not be as strongly related to the underlying constructs identified in the analysis. Items with moderate communalities, such as “Larger scale” (0.648) and “Lack of availability of skilled manpower” (0.574), indicate a moderate level of shared variance with the factors, reflecting their partial contribution to the factors.
Table No. 8 Total Variance Explained | |||||||||
Component | Initial Eigenvalues | Extraction Sums of Squared Loadings | Rotation Sums of Squared Loadings | ||||||
Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | |
1 | 5.666 | 26.980 | 26.980 | 5.666 | 26.980 | 26.980 | 3.389 | 16.137 | 16.137 |
2 | 2.378 | 11.323 | 38.303 | 2.378 | 11.323 | 38.303 | 2.773 | 13.203 | 29.340 |
3 | 1.943 | 9.253 | 47.556 | 1.943 | 9.253 | 47.556 | 2.702 | 12.868 | 42.208 |
4 | 1.698 | 8.088 | 55.644 | 1.698 | 8.088 | 55.644 | 2.399 | 11.422 | 53.630 |
5 | 1.602 | 7.627 | 63.272 | 1.602 | 7.627 | 63.272 | 1.718 | 8.183 | 61.813 |
6 | 1.161 | 5.530 | 68.801 | 1.161 | 5.530 | 68.801 | 1.468 | 6.988 | 68.801 |
7 | .945 | 4.501 | 73.303 | ||||||
8 | .890 | 4.239 | 77.542 | ||||||
9 | .813 | 3.871 | 81.412 | ||||||
10 | .698 | 3.325 | 84.737 | ||||||
11 | .554 | 2.636 | 87.373 | ||||||
12 | .524 | 2.496 | 89.869 | ||||||
13 | .407 | 1.937 | 91.806 | ||||||
14 | .350 | 1.665 | 93.471 | ||||||
15 | .307 | 1.463 | 94.935 | ||||||
16 | .250 | 1.191 | 96.126 | ||||||
17 | .245 | 1.168 | 97.294 | ||||||
18 | .197 | .939 | 98.233 | ||||||
19 | .162 | .773 | 99.006 | ||||||
20 | .131 | .624 | 99.630 | ||||||
21 | .078 | .370 | 100.000 | ||||||
Extraction Method: Principal Component Analysis. |
The table no. 8 shows the Initial Eigenvalues. Only components that have Total Initial Eigenvalues greater than 1 should be considered. In the present study 6 (six) components have total initial eigenvalue greater than 1. These six components explain 68.801% of the variance. On the basis of scree plot and initial eigenvalue table, it is confirmed that there are six components (factors). A good factor extraction, according to Kaiser (1960), is one that has a cumulative minimum of 60% of the variance.
Data transformation
The variables were grouped in six categories. Factor (Component) one – Compliance intensity (3 variables), Factor two – Funded scale and external control (4 variables), Factor three – Structure and Stability (5 variables), Factor four – Strategic ownership defense and longevity (3 variable), Factor five – Regulatory conformity for brand growth (2 variables) and Factor six – Perceived complexity in decision making (1 variable) (Table no. 9).
Table No. 9 Rotated Component Matrixa | ||||||
Component | ||||||
1 | 2 | 3 | 4 | 5 | 6 | |
Strict regulations are there | 0.869 | |||||
Disclosure requirements are high | 0.860 | |||||
Procedural compliance is high | 0.795 | |||||
Lack of knowledge about market and process | ||||||
Issue cost is high | ||||||
Larger scale | 0.773 | |||||
Participation of institutional investors is less | 0.77 | |||||
External control | 0.627 | |||||
More funds | 0.557 | |||||
Right valuation do not meet up | ||||||
Conflict among existing owners | 0.785 | |||||
Corporate governance follow up | 0.695 | |||||
Low liquidity in stock market | 0.624 | |||||
Loose control on company | 0.584 | |||||
More structure | 0.54 | |||||
Hostile takeover risk | 0.791 | |||||
Survival issue in long term | 0.781 | |||||
Lack of availability of skilled manpower | 0.558 | |||||
Complying with regulations | 0.773 | |||||
Greater brand awareness | 0.573 | |||||
More difficult decision making | 0.785 | |||||
Extraction Method: Principal Component Analysis, Rotation Method: Varimax with Kaiser normalizationa and aRotation converged in 10 iterations. |
This table contains the rotated factor loadings, which represent both how the variables are weighted for each factor but also the correlation between the variables and the factor. Because these are correlations, possible values range from -1 to +1. There are six components (factors) found. Component one ‘Compliance Intensity’ is characterized by high loadings from items such as “Strict regulations are there” (0.869), “Disclosure requirements are high” (0.860), and “Procedural compliance is high” (0.795). These items suggest that Component 1 reflects a dimension related to compliance challenges. Component two ‘Funded Scale and External Control’ includes items like “Larger scale” (0.773), “Participation of institutional investors is less” (0.770), and “External control” (0.627). This dimension appears to capture issues related to scale and investor involvement. Items such as “Conflict among existing owners” (0.785), “Corporate governance follow up” (0.695), and “Low liquidity in stock market” (0.624) load on Component three ‘Structure and Stability’. Component four ‘Strategic Ownership Defence and Longevity’ is marked by high loadings from “Hostile takeover risk” (0.791) and “Survival issue in long term” (0.781), indicating it reflects concerns related to company stability and takeover risks. Component five ‘Regulatory Conformity for Brand Growth’ include “Complying with regulations” (0.773) and “Greater brand awareness” (0.573) suggesting it relates to compliance for brand visibility. Component six ‘Perceived Complexity in Decision Making’ is reflective of “More difficult decision making” (0.785) capturing challenges associated with decision-making complexity.
CONCLUSION
A range of factors contribute to evolution of any mechanism. Here, listing on main board exchanges is a long distant dream for small businesses. The main board exchange eco-system may not be either permissive or conducive for SMEs. For SMEs, entering into primary markets through dedicated SME platforms and migrating to main board exchange is seen as organic course of action to kill shortage of long-term funds. One positive in this direction is awareness regarding SME platforms in India. Awareness of SME platforms is relatively high, especially for BSE SME. However, a small percentage of SMEs have been approached for listing, indicating potential gaps in outreach or interest. The factor analysis identified six major challenges: Compliance Intensity, Funded Scale and External Control, Structure and Stability, Strategic Ownership Defence and Longevity, Regulatory Conformity for Brand Growth, and Perceived Complexity in Decision Making. The study’s findings highlight the complexity and varied nature of challenges that SMEs face when considering listing on SME platforms. These challenges range from stringent regulatory requirements and high procedural compliance to issues of corporate governance and market stability.
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FOOTNOTES
[1] https://www.smechamberofindia.com/about-msme-in-india.php
[2] https://www.accaglobal.com/in/en/business-finance/types-finance/stock-market.html
[3] https://www.forbes.com/advisor/in/business/msme-statistics/
[4] https://www.bsesme.com/
[5] https://www.nseindia.com/resources/nse-sme-companies-listed-on-nse-emerge-platform-cross-rs-100000-crore-market-capitalisation-mark