Entrepreneurs of Small Scale Sector: A Factor Analytical Study of Business Obstacles

Entrepreneurs of Small Scale Sector: A Factor Analytical Study of Business Obstacles Anil Kumar Associate professor, Haryana School of Business, Guru Jambheshwar University of Science & Technology, Hisar -125001, Haryana (India) e-mail: anil_k6559@yahoo.co.uk

Abstract This paper examines the obstacles faced by entrepreneurs of small scale sector. A sample of 160 entrepreneurs has been taken from two states of northern India i.e. Haryana and Punjab. 20 statements were administered to entrepreneurs of small scale sector Questionnaire containing various questions related to problems of small scale sector on Likert type five degree scale was administered to entrepreneurs of small scale sector. Factor analytical model, one and two way analysis of variance (ANOVA) and correlation techniques were applied. Factor analytical model reduced 20 statements in five factors which act as barriers for the entrepreneurs of small scale sector. These relate to financial barriers, labour related issues, pricing of the product, infrastructural constraints and demand estimation. Inter- correlation matrix reveals high degree of correlation among five factors. One and two way analysis of variance (ANOVA) results revealed that different types of strategies be followed while dealing with entrepreneurs having different profile in small scale sector. There is a need to follow modern human resource management practices by the entrepreneurs of small scale sector. Government should follow more liberalised policies for the growth of small scale sector. More emphasis be laid to further strengthen infrastructure and promotional measures 1. Introduction: Rapid industrialization is considered as an engine of economic growth. Industrialisation helps in solving the large number of problems encountered by developing economies. But these economies can not rely entirely on large scale industries for the industrial development due to paucity of financial, technological and manpower resources. These economies have to depend on small scale sector for speedy development of their economies. The problem of poverty, inequality and unbalanced regional development can be abridged by expansion of small scale units. This sector also contributes towards the growth of export in the country. It helps in solving the problem of balance of payment in the economy. Small scale sector maintains better rapport between employer and employees thereby maintaining better industrial relations in the economy. Small scale sector requires less capital as compared to large scale units, can be started by new generation of entrepreneurs. This sector can act as a nursery of entrepreneurship in the developing economies. Keeping in view the significance of small scale sector, in this paper an attempt has been made to analyse the business problems faced by entrepreneurs of small scale sector. It becomes more imperative in the era of free market economies, where efficiency is the way of life. 2. Review of Literature: The literature cites the various studies conducted in this area. The some of the studies conducted in this area have been discussed in the following paragraphs: Taylor and Brooksbank (1995) examined the marketing practices among small New Zealand organisations by taking a sample of 427 small business owners. Findings revealed that the small business firm looks the marketing practices

differently from their larger counterparts. Small business owners use marketing practices according to their financial capacity and sometimes have to resort to world of mouth methods. Matlay, H. (2002) has examined industrial relations in the SME sector of teh British economy. A sample of 6000 respondents was taken for the study. Study has concluded that small business owners are using informal management styles in their organizations. Industrial relations were managed informally and this process improves the communication between labour and management. Micro and small businesses were not having trade unions. On the other hand, unionism affects the industrial relations of medium size businesses. Mambula, C. (2002) analysed major constrains faced by SMEs in Nigeria. A sample of 32 small business entrepreneurs was taken. Analysis of data revealed that majority of SMEs face the problem of finance and infrastructure while managing their businesses. The author recommended that small business entrepreneurs should collaborate with each other to sort out the various problems faced by them. There is a need to form alliance of Government, Research Institutions and Financial Institutions to create appropriate training for prospective small business. All these measures will go a long way to strengthen the growth of small scale sector. Tagoe, et al (2005) has examined the financial challenged facing by urban SMEs under financial sector liberalisation in Ghana. Main challenges faced by urban SMEs are access to affordable credit over a reasonable period. To manage this challenge SMEs should manage record keeping in an effective manner. Moreover, availability of collateral improves SMEs access to formal credit. But better availability of investment avenues further reduces the accessibility of credit to SMEs. Kuruba, G. (2006) has examined issues in the promotion of small business enterprises in Botswana. The author has observed that Botswana economy has congenial atmosphere for growth of small business enterprises. There is a need to provide training, financial and institutional support for these enterprises. Ismail, et al (2006) has examined motivation in business start up among Malay entrepreneurs and problem faced by these entrepreneurs. The study has concluded that there is large number of motivational factors but chief among them are personal development and financial security. Insufficient finance and tough competition from others are the main problems faced by entrepreneurs. Wu et al (2008) have examined an empirical evidence of small business financing in China. A sample of 60 small businesses from three cities of china was taken. The study has revealed that at the initial stage SMEs in China have used own sources and finances from relatives in friends. But at the alter stages, SMEs in China have used bank finance. The reason being, banks in China require various formalities to be fulfilled by SMEs such as taxation submission reports, accounting and credit rating scores documentations, etc.

Benzing, et al (2009) has examined the motivation, success factors and problems of entrepreneurs of SMEs in Turkey. A sample of 139 entrepreneurs from Ankara has been taken has been for the analysis. Factor analytical technique has been used to analyse the data. The study concluded that increase in income was one of the motivating factors of the entrepreneurs, followed by job security and independence. The success factors of entrepreneurs were reputation, honesty and friendliness. The entrepreneurs in Turkey faced the problem of cumbersome tax structure, unreliable employees, inability to maintain good record and weak economy. The authors have suggested that Government should actively support the business education at vocational and higher level. Irwin. D. and Scott, J.M.(2010) have analysed the barriers faced by SMEs in raising bank finance in U.K. A survey of 400 SMEs was conducted. Three personal characteristics such as ethnicity, gender and education have been taken. The study has observed that entrepreneurs having graduate level of education least face the problem in raising finance. In case of ethnicity of entrepreneurs, black owner mangers encountered more problems in raising finance. The study has concluded that the suitable policy measures be formulated to provide finance to marginalised group on liberal terms and conditions. 3. Objectives and Methodology: The study has been pursued to analyse the obstacles faced by entrepreneurs of small scale sector. To achieve these objectives, a sample of 160 entrepreneurs has been taken from the two States of Northern India i.e. Haryana and Punjab. To analyze the various business related problems faced by entrepreneurs, Likert type five degree scale from a great extent to not at all has been developed. Study is based entirely on primary data collected from the entrepreneur, because data relating to intensive study on the above said area is not available through secondary sources. Primary study helps the researcher to arrive at the meaningful inferences more effectively. Data was collected during 2010. A well designed questionnaire was prepared and administered to the respondents of the small scale sector. 20 statements were administered to the entrepreneurs of small scale sector. One way, two way analysis of variance (ANOVA) and factor analytical model were applied to analyse the data. 4. Results and Discussion: The general purpose in usage of this technique is to find a way to condense and summarise the information contained in a number of original variables into a smaller set of new composite factors with minimum loss of information. The factor analytical technique has been used to identify a set of latent dimensions that are not easily observed. The Table 1 highlights the results of Kaiser-Meyer-Olkin (KMO) and Bartlett s test of sphericity. The KMO test measure of sampling adequacy equal to 0.789 vividly reveals that data is fit for factor analysis. Bartlett s test of sphericity (1833.889) further corroborates our findings.

Insert table 1 here Table 2 shows the varimax rotated factor matrix results for all workers in our study. five factors have been extracted which altogether account for 64.634 per cent of variance. It shows that 64.634 per cent of total variance is explained by information contained in varimax rotated matrix. The communalities have been shown at the right side of the Table 2, which explains the amount of variance in the variable that is accounted by two factors taken together. Large communalities indicate that a large amount of variance in a variable has been extracted by factor solution. Insert table 2 here A factor loading represents the correlation between an original variable and its factors. Factor loading is nothing but coefficient of correlation. Only the factors having eigen values greater than 1.00 have been considered significant. All factors with eigen values less than 1.00 are considered insignificant and therefore disregarded. The name of factors, statements label and factor loading are summarized in Table 3. Insert table 3 here Financial problems (F1): The first factor which emerged from the factor analytical model is problem of finance. 36.861 per cent of the variations have been explained by this factor. The eigen value of this factor is 7.372. The eigen value more than one reveals the significance of this factor. Five statements out of 20 statements have been included in this factor. These relate to the problem of taking loans from the banks, higher rate of interest charged by financial institutions, labour relations, changes in markets and regulatory of work. The entrepreneurs of small scale sector reveals that they are facing the problem of finance along with higher rate of interest prevailing in the market. There is a need to formulate policies to assist entrepreneurs of small scale sector. The financial institutions need to be more liberalised while dealing with small scale sector. Most of these entrepreneurs have to depend on informal sources of finance to meet their financial requirement and have to pay higher rate of interest. Financial institutions should pay more attention while dealing with small scale sector. Paper formalities and other procedure needs to be made simple and cost effective. Procrastination in decision should be minimised. More specialised branches meant for small scale sector be opened to deal with cases pertaining to small scale sector. Seminars and workshops be conducted for the entrepreneurs of small scale sector to impart them the latest information on the policies to be followed by government. Labour related obstacles (F2): The second factor which has emerged from the factor model is labour related obstacles. 9.262 per cent of variations have been explained by this factor. The eigen value for this factor is 1.852, which is greater than one. Five statements out of 20 have been included in this factor. These relate to the problem of availability o skilled manpower, increase in cost of labour, opening of the

economy and publicity of the product. The entrepreneurs of small scale sector face the problem of availability of skilled manpower and increase in the cost of labour. Interaction with entrepreneurs of small sector reveals that skilled manpower is not easily available in the market and cost of labour has also increased considerably. The reason being, more skilled labour gets employment in large scale enterprises and manpower working in small scale sector after having experience leave the small scale sector due less opportunities available to them. There is need to formulate the policies at the macro level to enhance the human capital base of the population of the country. Formulation of policies at macro level will overcome this problem. More emphasis be given to the growth of technical manpower at the school level. Entrepreneurs of small scale sector need to follow the modern human resource management practices to tackle the labour related issues Problem of pricing of the product (F3): The third factor which accounts for 7.564 per cent of variations and it has been termed as problem of pricing of the product. The eigen value to this factor is 1.513, which is greater than one. Five out of 12 variables have been loaded on this factor. These relate to the problem of pricing, taxation, power break down, labour absenteeism and turnover. Under the new economics order and own account of increase in competition it becomes difficult for the entrepreneurs to fix the price of the commodities. The entrepreneurs also face the problem of cumbersome tax procedure, which further aggravates the problems of small scale sector. Increase in taxation enhances the price of the products. There is a need to stream line the tax structure so that entrepreneurs may not face the problem of fixation of pricing of the products. The frequent power break down along with labour absenteeism also increases the cost of product. Entrepreneurs have to depend on costly methods to run the enterprises smoothly. Infrastructural constraints (F4): The fourth factor has been designated as infrastructural constrains. The percentage of variations explained by this factor is 5.664. Eigen value of this factor is 1.313. The eigen value greater one reveals that infrastructural related issues are one of the main problems faced by entrepreneurs of small scale sector. This factor consists of two statements. The loading of these variables states that the basic issues in infrastructure are the Lack of availability of information, technological development and transportation. The problem of infrastructure is faced by entrepreneurs of small scale sector more intensively as compared to their counterparts in small scale sector. Small scale sector due to paucity of resources can create more infrastructure for them. Technological innovations are taking place rapidly in the economy. It becomes difficult for the entrepreneurs to adopt technological innovations more frequently. Infrastructure in the form of better system of transportation be developed further. Prices of fuel in the form of petrol and other form of energy be reduced. It will reduce the cost of transportation.

Problem of demand estimation (F5): The last factor which emerged from the factor model is estimation of demand of the product. The eigen value of this factor is also more than one. The percentage of variations explained by this factor is 5.291. Demand estimation is a highly technical concept and needs specialised training and knowledge. It has been observed during the discussion with entrepreneurs that specialised type of training is required on this area. The entrepreneurs should go for intensive training regularly in order to overcome these obstacles. The regular training programmes for entrepreneurs be organised. To motivate the entrepreneurs to join the training programmes, incentives should be given to entrepreneurs in form of various concessions. Information on various parameters of population like income, purchasing power etc., be provided to entrepreneurs. Results of inter - correlation Matrix: The results of inter - correlation matrix shows that all the five problems which emerged from the factor model are highly correlated with each other and differ significantly at one per cent level of significant. The Cranach s Alfa for the all five problems are.802,.812,.726,.383 and.557 respectively. It shows that all these five factors have high degree of reliability. The cronbach s Alfa of one factor is found to be low due to less number of statements in this factor. Insert table 4 here ANOVA Results: One way and two way analysis of variance (ANOVA) techniques were applied to find significance difference between the means of factors emerged from factor model and profile of entrepreneurs. Profile of entrepreneurs includes age, education and family background of entrepreneurs. Table 5 highlights the one way analysis of variance (ANOVA) result age, education and occupational background of entrepreneurs. There exist significant difference between age of entrepreneurs and problem of pricing of the product faced by entrepreneurs of small scale sector at 5 per cent level of significance and with other variables there is no significant difference. It means entrepreneurs in different age groups face the problem of pricing of the product. Similarly, education of entrepreneurs and five problems reduced from factor solution reveals that there exist significant difference between education and financial barriers faced by entrepreneurs of small scale sector at 5 per cent level of significance. It shows that significant difference exist between education and financial barriers. There is a need to provide information and training to entrepreneurs in the field of finance. Family background of entrepreneurs found to be statistically significant with problem of estimation of demand of the product at 5 per cent level of significance and with rest of the variables there exist no significant

difference. It shows that the problem is due to difference in occupation background of the entrepreneurs. Insert table 5 here Table 6 reveals the result of two way analysis of variance (ANOVA) with age, education and family background of entrepreneurs and five major problems encountered faced by entrepreneurs i.e. problem of financial barriers, labour related issues, pricing of product, infrastructural and demand estimation shows different results. Inset table 6 here Age and education of entrepreneurs found to be statistically significant with problem of demand estimation at 1 per cent level of significance and with financial barriers at 5 per cent level of significance. Similarly, age and education of entrepreneurs found to be statistically significant with infrastructural constraints at 10 per cent level of significance. Age and occupational background of entrepreneurs found to be statistically significant with second, third and fourth problems i.e. labour, pricing of product and infrastructural constrains at 5 per cent level of significance and with financial and problem of demand estimation at 1 per cent level of significance. Education and occupational background of entrepreneurs found to be statistically significant with first, third and fifth problems i.e. financial, pricing of product and problem of demand estimation at 5 per cent level of significance and with second and fourth problem i.e. labour and infrastructural constraints there is no significant difference. These findings can be more useful to policy makers while dealing with small scale entrepreneurs. 5. Summary and Conclusion: The foregoing analysis reveals that factor analytical model has reduced the 20 statements in to five major problems. These are financial barriers, labour problems, pricing of product, infrastructural and estimation of demand of product. Inter- correlation matrix shows the high degree of correlation among all major problems faced by them. One way and two way analysis of variance (ANOVA) results shows the different set of inferences which can be adopted to tackle different problems differently. Age of entrepreneurs and one way analysis of variance results show that the problem of pricing of product vary significantly and with education, financial problem differ significantly and with occupational background,the problem of demand estimation differ significantly. Two way analysis of variance (ANOVA) results highlight the different results. There is a need to formulate the policies forte growth of small scale sector. The various problems faced by them be solved collectively. Promotional measures and training to entrepreneurs can go a long way to solve the various problems faced by them. The analysis of variance result can be used to formulate policies to sort out the problems faced by entrepreneurs

of small scale sector. The entrepreneurs of small scale sector should follow modern human resource practices to tackle the various internal problems faced by them and problems which are beyond the control of entrepreneurs be solved by promotional and government agencies. Limitation of the study: The study is based on the data collected from two States, inferences drawn from these cannot be generalised but these results can be useful. Moreover, these States are the hub of small scale industries. For policy formulation in these States, such type of studies are useful. Due to time constrains and non availability of entrepreneurs the sample size was confined to 160 only. References: Bezing, et al (2009), Entrepreneurs in Turkey: A Factor Analysis of motivation,success Factors, and Problems, Journal of Small Business Management, 47(1),58-91 Kuruba, G. (2006), 'Issues in Promotion of Small Business Enterprises in Botswana', Indian Journal of Commerce, 59(1), 77-86. Mambula, C. (2002), Perceptions of SME Growth Constraints in Nigeria, Journal of Small Business Management, 40 (1), 58-65. Tagoe et al. (2005), Financial Challenges Facing Urban SMEs under Financial Sector Liberalisation in Ghana, Journal of Small Business Management, 43 (3), 331-343. Taylor and Brooksbank (1995), Marketing Practices among Small New Zealand Organisations, Journal of Enterprising Culture, 3 (2), 149-160. Irvin, D. and Scott, J.M.(2010), Barriers Faced by SMEs in Raising Finance, International Journal of Entrepreneurship Behaviour and Research, 16(3), 245-259 Ismail et al (2006), A study of Motivation in Business Start-ups Among Malay Entrepreneurs, International Business and Economics Research Journal, 5 (2), 103-112. Matlay, H. (2002), Industrial Relations in the SME Sector of the British Economy, Journal of Small Business and Enterprise Development, 9(3), pp 307-318 Wu et al (208), An Empirical Evidence of S Business Financing in China, Management Research News, 31(12) pp 959-975

Appendix: Table 1: KMO and Bartlett s Test Kieser-Meyer-Olin Measure of Sampling.789 Adequacy Bartlett s Test of Sphericity Approx. Chi-Square 1833.889 df 190 Sig..000 Table2: Rotated Component Matrix Statement Factor Factor 2 Factor 3 Factor 4 Factor 5 Communalities 1 labour absenteeism in your organisation?.051.339.573 -.142.175.497 availability of skilled labour?.216.851.223.190.182.890 increase in cost of labour? labour turnover in your organisations? labour relations in your organisations? Taxation? getting information? technological changes? frequent break down of power? Do you face the of problem of getting loans from financial institutions? frequent change in market conditions?.391.600.238.188.444.802.267.283.629.094.280.634.520.335.404.463.201.802.336 -.033.447.147.026.336.116.503.112.759 -.082.861 -.065.118.476.623.224.684 -.087.164.569.308 -.437.645.648.308.332.111.084.645.685.228.308.117.115.643

transportation? opening up of the economy? pricing of the product? publicity of product? estimation of demands of the product? regularity of work? collateral security? higher rate of interest? getting raw material?.374 -.042 -.015.616 -.045.523.321.636.304.224 -.004.651.307.216.784.140 -.085.783.114.492.165.247 -.114.357 -.156.207.238 -.278.629.597.602.495 -.071.261.238.737.155 -.064 -.068.101.700.533.694.113.056.033.013.499.486.277.214.313.596.812 Eigen values 7.372 1.852 1.513 1.133 1.058 Percentage of variance 36.861 9.262 7.564 5.664 5.291 Cumulative percentage of variance 36.861 46.123 53.687 58.979 64.643 Extraction method: Principal component analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation Converged in 17 iterations.

Table3: Naming of factors Fact or Name of Factor Name of Statement Factor loading F1 Financial problems labour relations in your organisations? Do you face the of problem of getting loans from financial institutions?.520.648 F2 Labour related obstacles frequent change in market conditions? regularity of work? higher rate of interest? availability of skilled labour? increase in cost of labour?.685.602.694.851.600 F3 Problem of pricing of the product getting information? opening up of the economy? publicity of product? labour absenteeism in your organisation? labour turnover in your organisations? Taxation? frequent break down of power? pricing of the product?.503.636.492.573.629.447.569.784

F4 Infrastructural constraints technological changes?.623 F5 Problem of demand estimation transportation? estimation of demands of the product? collateral security? getting raw material?.616.629.700.596 Table4: Factor wise Inter-Correlations Matrix Name of factors Financial problems Labour related obstacles Problem of pricing of the product Infrastructural Constraints Problem of demand estimation Financial problems Labour related obstacles Problem of pricing of the product Infrastructural Constraints.717**.551**.486** 1 - - - -.547**.444**. 1 - - -.465** 1 - - 1 - Problem of demand estimation.525**.474**..253**.295** 1 Cronbach s.802.812.726.383.891 Alfa N=160, Note: ** indicates 1 per cent level of significance

Table5: One way analysis of variance (ANOVA) result Name of factors Age Education Occupational background F-Value F-Value F-Value Financial problems 1.677 (.159) 9.154**.552 (.577) Labour related obstacles.546 (.702) 1.215 (.300).729 (.484) Problem of pricing of the product 3.698** (.007) 1.858 (.160).175 (.840) Infrastructural Constraints 1.685 (.157).614 (.542).221 (.802) Problem of demand estimation 1.836 (.125).312 (.732) 5.619** (.005) Note: * indicates 1 per cent level of significance ** indicates 5 per cent level of significance

Table 6: Age and education-wise two way analysis of variance (ANOVA) result Name of factors Financial problems Labour related obstacles Problem of pricing of the product Infrastructural Constraints Problem of demand estimation Age and Education Age and occupational background Education and occupational background F-Value F-Value F-Value 2.060** 4.917* 3.768** (.052) (.001) (.026) df=7.872 (.531) df=7 1.365 (.225) df=7 1.941*** (.068) df=7 4.305)* df=7 3.911** (.005) 3.278** (.013) 3.265** (.014) 10.275* Note: * indicates 1 per cent level of significance ** indicates 5 per cent level of significance *** indicates 10 per cent level of significance.843 (.433) 4.724** (.010).933 (.396) 4.820** (.009)