A Study on Effectiveness of Institutional Supports to Small Business Management in South Andaman Islands

 

Dr. Treemurutulu B. ¹

 

¹ Assistant Professor, Department of Commerce, Andaman College, ANCOL, Andaman and Nicobar Islands, India

 

1. INTRODUCTION

Globally recognized micro and small enterprises (MSEs) are known for their important contribution to economic growth Osotimehin et al. (2012). MSEs have become one of the most important tools for dealing with economic and social issues and achieving development goals in both developed and developing nations Bai et al. (2021), Miah et al. (2015), OECD (2017a). MSE sectors are seen as a key catalyst for jobs, unemployment, and social development as a whole for the rapidly increasing workforce worldwide Awartan and Millis (2018). In both developed and developing economies, MSEs have been recognized as indispensable components of national development. They have also been recognized internationally as economic growth and development instruments Oppong et al. (2014), Osotimehin et al. (2012). Indian MSMEs lack up-to-date information and are often unaware of the latest technologies present in the global market. Sometimes they lack the managerial skills, entrepreneurial knowledge, and technology-intensive education needed to run a competent MSME Mukherjee (2018). According to the Asian Development Bank. (2009), a few constraints were highlighted, such as limited access to finance, scarce medium- and long-term finance restricted connectivity to markets, insufficient physical infrastructure, underprivileged women entrepreneurs, and the absence of a credit rating information system for SME borrowers in the context of MSMEs. The Indian MSME is recognized as a major contributor to economic growth. It is said to be the backbone of the Indian economy. It has provided resilience to ward off global economic shocks and adversities. Nearly 20% of the Indian MSME is based out in the rural areas of India and continues to provide employment opportunities to nearly 40% of India’s labor force. In India, there are various policies and schemes of the Government of India for assisting in the development of rural industries through the utilization of local resources and raw materials, locally available manpower, and local administration support for promoting small and rural businesses. In this context, institutional support includes financial support from banking sectors, training, marketing, and raw material support from other institutions from time to time. Other support tools include testing facilities, training for entrepreneurship development, project report preparation, technical and managerial consultancy services, export assistance, pollution, energy, marketing the products, acquiring quality standards, and so on. All these institutional support services cater to micro and small enterprises in the areas of raw material procurement, product marketing, credit, and the acquisition of technology, the adoption of modern practices, and the ensuring of technology. MSME policies and programs are framed from time to time relating to enterprises, they make recommendations to the government in formulating the policies for the growth of SMEs. Andaman and Nicobar Islands have huge potential in industries such as marine-based businesses; the Coir industry, wood-based industries, and marine-based industries all have huge markets and high demand internationally. This study focuses on the gap in the contribution of micro- and small enterprises in the Islands region with the support of various institutions such as finance, marketing, raw materials, and training for promoting and developing eco-business in the Islands region.

 

2. REVIEW OF LITERATURE

1)    Ayalu et al. (2022) aim to assess the contributions of MSEs towards sustainable community livelihood in Emba Alaje, Wereda, Ethiopia. The results of the study revealed that MSEs contributed to economic growth, employment formation, and income generation for the local community. The study indicated that MSEs were significantly affected by different determinant factors such as infrastructure, raw materials, working premises, and human capital. The study clearly indicated that there was a gender gap in participation in different MSE sectors.

2)    Dwivedi and Tiwari (2013) this paper deal with promoting entrepreneurship and a force of economic change in business communities for survival. The study also deals with strategies needed to create an environment conducive to entrepreneurship training and teaching. In addition, the study also considers the prospective role of entrepreneurship development (ED) institutions in training entrepreneurs in economic development.

3)    Osoro and Muturi (2014) argue that small enterprises (SEs) play an important role in the Kissi town of Kenya's economy. Financial training was found to be playing a crucial role in the growth of small enterprises, especially in assisting businesses to repay their loans in order to get more credit in the future. The research further found that the accessibility of marketing information and its availability to entrepreneurs also affects their performance in a positive way. The study recommends that the government and financial institutions should make microcredit more accessible and available to enhance the growth and development of small enterprises.

4)    Ahsan et al. (2021) This article examines the entrepreneurial persistence of opportunity-motivated entrepreneurs in Ghana. It develops a theoretical model focusing on the relationships among perceived institutional support, entrepreneurial persistence, and small venture performance. Entrepreneurial networks condition the relationship between institutional support and entrepreneurial persistence. The study used time-lagged data from 373 opportunity-motivated entrepreneurs leading small ventures in Ghana. The study provides an integrative understanding of the relationships among perceived institutional support, entrepreneurial persistence, and venture performance in an adverse environment.

5)    Zindiye et al. (2012) The purpose of this paper is to investigate the influence of government and other institutions' support on the performance of small and medium enterprises (SMEs) in the manufacturing sector in Harare, Zimbabwe. The target population for this study was 609 SMEs, of which a sample of 241 SME owners or managers participated in the study. Data analysis was done using the Chi-square test to test for association. The results indicated that the government and other institutions are playing a positive role in the performance of SMEs despite the prevailing economic conditions.

6)    Forkuoh et al. (2016) assessed the impact of institutional support in the provision of managerial capacity building on the growth of selected SMEs in Ghana. Using firm-level data from 500 SMEs from the ten regional capitals of Ghana, the results indicated that the provision of institutional support in the training of procurement personnel, bookkeeping, and accounting experts, and business plan preparation experts had a positive impact on the growth and development of the SMEs. In the long run, this has an impact on national growth and development. It is therefore not an accident to see several governments and other institutions support SMEs by training and maintaining a quality workforce.

 

3. METHODOLOGY AND RESEARCH DESIGN

This section of the study gives detailed information relating to the methodology adopted in the research study. The research design, types and sources of data, profile of the study area and statistical tools that were adopted for analysis.

 

 

 

 

4. RESEARCH DESIGN

The research design proposed for this research work is based on well-structured schedule for investigating the socio-economic condition of owners of micro, small enterprises in the South Andaman district. Sample units were divided into micro and small units. The primary data was collected by the researcher using an interview schedule from micro and small businesses operating in various parts of South Andaman district. The sample selection is based on stratified proportionate random sample method by which responses from 344 owners of small businesses were collected from South Andaman District. The sample size was determined by the following formula n= N/1+N (e) ², Where; n= sample size, N= Population 2,433, e = standard error (i.e.0.05). Substituting these values in the formula, we get; N=344. Hence, the sample size of this study is 344 small businesses.

 

5. PROFILE OF THE STUDY AREA

Andaman and Nicobar Islands (ANI) is a Union Territory of India that lies in the Bay of Bengal. It consists of three districts, viz., South Andaman district, North & Middle Andaman district and Nicobar district. The capital of the state is Port Blair which is located at South Andaman district. Andaman & Nicobar Islands consists of about 527 islands, both small and large, out of which only 38 Islands are inhabited.

 

6. ANALYSIS AND DISCUSSION

In this section of the study, the empirical results of the research are presented to address the research objective. This section of the study presents the information about the owners charecteristics of the respondents like gender, age and types of enterprises of the respondents i.e. entrepreneurs who are involved in micro and small businesses in Andaman and Nicobar Islands. The summarization of the busines profile of the respondents  are presented in below.

Table 1           

Table 1 Classification Based On Busines Profile
Demographic factors	Particulars	Type of Enterprise		Total	c2 Values
		Micro	Small
Gender	Male	147 (62.03%)	90 (37.90%)	237 (68.90%)	12.60*** (0.000)
	Female	87 (81.31%)	20 (18.69 %)	107 (31.00%)
	Total	234 (68.02 %)	110 (31.98 %)	344 (100%)
Age (Years)	Less than 35 years	57 (74.03%)	20 (25.97%)	77 (22.38%)	9.819*** (0.007)
	36 to 50 years	92 (59.35%)	63 (40.65%)	155 (45.06%)
	Above 50 years	85 (75.89%)	27 (24.10%)	112 (32.56%)
	Total	234 (68.02 %)	110 (31.98 %)	344 (100%)
Types of enterprises	Manufacturing	147 (66.22)	95 (33.78)	222 (64.53)	1.942 (0.331)
	Service	87 (71.31)	35 (28.69)	122 (35.47)
	Total	234 (68.02 %)	110 (31.98 %)	344 (100%)

 

7. CLASSIFICATION BASED ON GENDER OF THE ENTREPRENEURS

From the Table 1, it can be observed that 237 (68.90 %) are male respondents out of which 147 (62.03%) are from micro enterprises and 90(37.90%) respondents are from small enterprises. 107 (31.00%) are female respondents out of which 87(81.31%) are from micro enterprises and 20(18.69%) respondents are from small enterprises. The result of  Chi-square test reveals that there is a significant association (c2 =12.60, df=1. N=344, p value = 0.000) between gender and the type of enterprises at 5 % of the significant level ie., there significant relationship between gender and the business activity. It is also found that 237(68.90 %) majority of male respondents’ entrepreneurs.

 

8. CLASSIFICATION BASED ON AGE GROUP OF ENTREPRENEURS

The age of the respondents is categorized into three groups’ viz. less than 35 years, 36 to 50 years and above 50 years. From Table 1 it is observed that 77 (22.38%) of the respondents are within the age group of less than 35 years, of which57 (74.03%) are from micro respondents and 20 (25.97%) are from small enterprises. Further, 155 (45.06%) respondents are in the age group between 36 to 50 years out of which 92(59.35%) are from micro enterprises and 63 (40.65%) are from small enterprises. In the age group of above 50 years, there are 112 (32.56%) respondents, of which 85 (75.89 %) are from micro enterprises and 27 (24.10%) are from small enterprises. The Chi-square test result ensures  that there is a significant association (c2 = 9.819, df= 2, N = 344, p value = 0.007) between the age group and type of enterprise, at 5% of the significant level. Therefore, it is also found that majority of the respondents are in the age group between 36 to 50 years.

 

9. CLASSIFICATION BASED ON TYPES OF ENTERPRISES

From the above Table 1,  it is observed that 222 (64.53 %) respondents are involved in the manufacturing sector and 122 (35.47 %) respondents are in the service sector. The Chi-square test result of the association between the sector and the type of enterprise revealed that there is no significant association (c2  = 1.94, df =1, N = 344,  p value = 0.33) between sector of enteprise and type of enterprise. The result of study reveals that majority of the entrepreneurs’ are involved in manufacturing business and majority of the micro enterprises are engaged in providing services as it requires comparatively lesser investment.

 

 

 

 

10. ANALYSIS ON THE INSTITUTIONAL SUPPORTS TO MSEs

The previous section discussed the socio-economic factors of entrepreneurs in South Andaman. This section further examines the institutional support available to the small entrepreneurs in the study area. Limited by size, lesser investment, limited production, limited opportunities are the major concerns that influence small enterprises to sustain and survive for the long term. The need for providing additional support system to MSEs from different contexts is getting momentum. In this context, this study explores the available supporting mechanisms to facilitate MSEs. The various institutional supports are categorized into four headings viz. financial, training, and marketing and raw materials supporting institutions.

 

11. INSTITUTIONS FOR FINANCIAL SUPPORT

The objective of the study is to identify the various challenges faced by micro and small enterprises with respect of financial sources during different stages of their life cycle. In ANI, banks are the predominant sources of finance to micro and small enterprises. The amount of finance will vary based on size of the enterprises. Most entrepreneurs have started their business without proper financial planning and so they frequently face severe financial crises leading to loss of competitive advantage in their market. This section of the analysis gives a detailed discussion on various sources of finance to micro and small businesses in South Andaman.

 

12.  CLASSIFICATION BASED ON SOURCE OF FINANCE FOR MSEs

MSEs usually depend on financial support for running their business in any of the following five sources viz. banks, family, friends, own savings, and private leaders. The respondents were asked to give their opinion on what sources they used for financing their business. The opinion is tabulated and presented along with Chi-square results in the table below.

Table 2

Table 2 Classification Based on Source of Finance for MSEs
Source of Finance	Opinion	Types of Enterprises		Total	c2 Values
		Micro	Small
Bank	Yes	182 (64.54%)	100 (35.46%)	282 (81.98%)	8.733*** (0.003)
	No	52 (83.87%)	10 (16.13%)	62 (18.02)
	Total	234 (68.02 %)	110 (31.98 %)	344 (100%)
Family	Yes	94 (61.44%)	59 (38.56%)	153 (44.48%)	5.494** (0.019)
	No	140 (73.30%)	51 (26.70%)	191 (55.52%)
	Total	234 (68.02 %)	110 (31.98 %)	344 (100%)
Friends	Yes	38 (86.36%)	6 (13.64%)	44 (12.79%)	7.802**
	No	196(65.33%)	104(34.67%)	300(87.21%)	(0.005)
	Total	234 (68.02 %)	110 (31.98 %)	344 (100%)
Private lender	Yes	94 (65.73%)	49 (34.27%)	143 (41.57%)	1.590 (0.443)
	No	140 (69.65%)	61 (30.35%)	201 (58.43%)
	Total	234 (68.02 %)	110 (31.98 %)	344 (100%)
Own savings	Yes	191(67.25%)	93 (32.75%)	284 (82.56%)	1.444 (0.505)
	No	43 (71.67%)	17 (28.33%)	60 (17.44%)
	Total	234(68.02 %)	110 (31.98 %)	344 (100%)
Source Primay Data, Multiple Selection of the Respondents, Figures In Parenthesis Are Percentages

        

As shown in Table 2 shows that 282 (81.98 %) respondents availed loans from banks and 62 (18.02 %) not-availed loans from banks. The Chi-square test result for the association concluded that there significant association (c²  = 8.733**, df = 1, N = 344,  p value = 0.003) between  source of finance from bank and the type of enterprise. 153 (44.48 %) respondents were supported by their family members in respect of financing and 191 (55.52 %) had no financial support from family members. The Chi-square test result for the association concluded that there is significant association (c²  = 5.494**, df = 1, N = 344,  p value = 0.005) between  source of finance from family and the type of enterprise. 44 (12.79 %) respondents sourced finance from their friends and relatives and 300 (87.21 %) had no friends and relatives’ support. The Chi-square test result for the association concluded that there is significant association (c²  = 7.802***, df =1, N = 344,  p value = 0.005) between source of finance from friends  and ralatives  and the type of enterprise. Further, 143 (41.57 %) respondents’ generated source of finance from private lenders and 201 (58.43 %) had no private lenders support. The Chi-square test result for the association concluded that there is no significant association (c²  = 1.590, df = 1, N = 344,  p value = 0.443) between  private lenders support and the type of enterprise. Regarding the question on depending on own source of fund, 284 (82.56 %) respondents expressed that they used own savings for their businesses and remaining 60 (17.44 %) did not used own savings for their businesses. The Chi-square test result for the association concluded that there is no significant association (c²  = 1.444, df  = 1, N = 344,  p value = 0.505) between own savings and the type of enterprise. It is further noted from the findings that majority of the micro and small enterprises generated investment for their business from banks and own savings.

 

13. INSTITUTIONAL SUPPORT TO MSEs

The researcher ascertained the opinion of small entrepreneurs about the sort of support they receive from various Government and non-governmental agencies for successfully operating their business in South Andaman. The kind of support that they have received is assessed under four headings viz. financial support, marketing support, raw material support and training support. The result of their opinions’ is presented below. The study intended to examine the role of institutions providing support to MSEs by classifying them under three categories viz. government, private and self-support.      With respect to financial support, the below Table 3 shows that among the respondents, 251 (72.97 %) are supported by the government, 65 (18.90 %) respondents are supported by private institutions and a total of 28 (8.14 %) respondents rely on self-support. The Chi-square test reveals that there is  no significant association (c²  = 0.784, df = 2, N = 344, p value = 0.676) between type of enterrpise and mode of finacial support.

Table 3

Table 3 Classification of Institutional Support to MSEs
Institutions	Types of  enterprises	Institutional support			Total	c2 Values
		Govt. Support	Private support	Self-support
Finance	Micro	169 (72.22%)	47 (20.09%)	18 (7.69%)	234 (68.02%)	0.784 (0.676)
	Small	82 (74.55%)	18 (16.36%)	10 (9.09%)	110 (31.98%)
	Total	251 (72.97%)	65 (18.90%)	28 (8.14%)	344 (100%)
Marketing	Micro	68 (29.06%)	73 (31.20%)	93 (39.74%)	234 (68.02%)	6.704** (0.035)
	Small	23 (20.91%)	27 (24.55%)	60 (54.55%)	110 (31.98%)
	Total	91 (26.45%)	100 (29.07%)	153 (44.48%)	344 (100%)
Raw Materials	Micro	50 (64.94%)	117 (68.82%)	67 (69.07%)	234 (68.02%)	0.437 (0.804)
	Small	27 (35.06%)	53 (31.18%)	30 (30.93%)	110 (31.98%)
	Total	77 (22.38%)	170 (49.42%)	97 (28.20%)	344 (100%)
Training	Micro	140 (70.35%)	48 (75.00%)	46 (56.79%)	234 (68.02%)	6.627** (0.036)
	Small	59 (29.65%)	16(25.00%)	35(43.21%)	110(31.98%)
	Total	199 (57.85%)	64 (18.60%)	81 (23.55%)	344 (100%)
Source Primay data, figures in parenthesis are percentages)

     

With respect to marketing support, Table 3 shows that, among the respondents, 91 (26.45 %) are supported by the government, 100 (29.07 %) respondents are supported by private institutions and a total of 153 (44.48 %) respondents market their products by themselves. The Chi-square test reveals that there is significant association (c²  = 6.704**, df = 2, N = 344, p value = 0.035) between type of enterpise and mode of marketing support. The findings strongly revealed that majority of respondents market their products by their own means.

With respect to raw material support, 77 (22.38 %) respondents are getting raw materials through the government institutions, 170 (49.42 %) respondents are getting support from private associations and 97 (28.20 %) respondents are doing business by procuring materials by themselves. The Chi-square test result exibits that there is no significant association (c²  = 0.437, df = 2, N = 344,  P value = 0.804) between the types of enterprises and the institutional support for procuring raw materials for the business.  Hence, it can be concluded that majority of the small entrepreneurs received the raw material support from private institutions. In this context, though certain respondents are benefited by government institutions, but it is not adequate for developing their business. 

With respect to business skills training support, there are 199 (57.85 %) respondents trained by government institutions, 64 (18.60 %) respondents trained by private institutions and 81 (23.55 %) respondents got trained from their own experience. The Chi-square test result reveals that there is significant association (c²  = 6.627, df = 2, N = 344,  p value = 0.036) between the types of enterprisese and institutional support for training. It is found that majority of the respondents got trained by government institution. This is a good indication for government support making significant contribution for promoting MSEs in South Andaman region.

 

14. EFFECTIVENESS OF INSTITUTIONAL SUPPORT TO MSEs

Ranking of respondents’ opinion on the reason for availing financial  support from banks

An attempt is made in this section to understand the resons for which the respondents are borrowing funds from banks. For this, respondents were asked to give their opinion on various reasons in a five point Lickert’s scale that ranges from strongly disagree to strongly agree.  The computed results are given in the following table.

Table 4

Table 4 Ranking of Respondents’ Opinion on the Reason for Financial Support From Banks
Financial Support	SD	D	N	A	SA	Mean Score	Rank
To start business	2 (2)	6 (12)	16 (48)	164 (656)	156 (780)	4.35	1
To expand business	25 (25)	43 (86)	68 (204)	116(464)	92 (460)	3.60	4
To purchase equipment	13 (13)	26(52)	42 (126)	157 (628)	106 (530)	3.92	2
For repay existing dues	25 (25)	49 (98)	80 (240)	104 (416)	86 (430)	3.51	5
To refinance the business	13 (13)	35 (70)	62 (186)	143 (572)	91 (455)	3.77	3
Source (Primary data), (Ranked are based on mean score / N= No. of respondents

          

The Table 4 presents the ranking of respondents’ opinion on the reasons of availing bank finance. From the above table, it is observed that highest mean score of 4.35 represents that ‘to start business’ is the foremost reason for getting bank financial assistance. The next reason is ‘to purchase the equipment’ with the mean score of 3.92. The other reasons are ‘to refinance the businesses’ with the mean score of 3.77, ‘to expand the business with the mean score of 3.6, and ‘for repay existing dues’ with the mean score of 3.51. Therefore, it is clear that starting the business is the prime reason for getting financial support from the banks.

 

15. CONCLUSION

The purpose of the research is to determine the institutional support for MSEs in the Islands region. In India, various institutional supports play important roles in the support of small business firms. The study found that the majority of the respondents were trained by government institutions. This is a good indication of government support for significant contributions to promoting MSEs in the South Andaman region. Further, the study noted from the findings that the majority of the micro- and small-sized enterprises generated investment for their businesses from banks and their own savings. Small businesses in Andaman and Nicobar Islands have enormous potential for higher rates of growth in thrust areas such as tourism, marine, wood, food, handicrafts, and agriculture (Industrial Potential Survey of A&N Islands). Hence, it is recommended that the island's administration be focused on institutional support by the banking sector. Marketing support, the supply of raw materials, and training support are important to the survival and sustained long-term growth and success of small businesses in the Andaman and Nicobar Islands.

 

CONFLICT OF INTERESTS

None. 

 

ACKNOWLEDGMENTS

None.

 

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