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Entrepreneurs Attitude towards the Performance of Industrial Estates in Southern Districts of Tamilnadu-A Study

Selvaraj N*

Department of Commerce, Saraswathi Narayanan College, Madurai, Tamilnadu, India

*Corresponding Author:
Selvaraj N
Department of Commerce
Saraswathi Narayanan College
Madurai, Tamilnadu, India
Tel: 09843727975
E-mail: [email protected]

Received November 09, 2015; Accepted November 26, 2015; Published December 10, 2015

Citation: Selvaraj N (2015) Entrepreneurs Attitude towards the Performance of Industrial Estates in Southern Districts of Tamilnadu-A Study. Bus Eco J 7:198. doi:10.4172/2151-6219.1000198

Copyright: © 2015 Selvaraj N. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

An individual’s behaviour is a function of attitude. An attitude is also a cognitive element; it always remains inside a person. Attitude influences the perception of objects and people, exposure to and comprehension of information, choice of friends and so on. It basically consists of the feeling a person has towards an object. The cognitive component represents the belief of a person about an object. It consists of individual’s perception beliefs and ideas about an object. The overt component is concerned with the way one intends to behave towards a particular object. Both the affective and cognitive components influence the way a person intends to behave towards an object. The study is based on primary data. Primary data have been collected from the selected entrepreneurs in the southern districts of Tamil Nadu. The attitude in the present study shows the level of satisfaction towards the operational performance of industrial estates.  

Keywords

Attitude; Industrial estates; Entrepreneurs; Operational performance

Introduction

The small-scale industrial sector which plays a pivotal role in the Indian economy in terms of employment and growth has recorded a high rate of growth since independent in spite of stiff competition from the large scale sector and not so encouraging support from the Government. This is evident by the number of registered units which went up from 16,000 in 1950 to 36,000 units in 1961 and 58.57 lakhs units in 2006-07. During the last decade alone, the small-scale sector has progressed from the production of simple consumer goods to the manufacture of many sophisticated and precision products like electronic control systems, micro-wave components, electro-medical equipment, TV sets and the like. But not this is really a tough period for the entrepreneurs to survive because of uncontrollable variables causing unforeseen situations like changing roles of Government, threats from multinational corporations and other internal variables.

An individual’s behaviour is a function of attitude. An attitude is also a cognitive element; it always remains inside a person. Attitude influences the perception of objects and people, exposure to and comprehension of information, choice of friends and so on. Gorden et al. stated that attitude is a mental and neutral state of readiness, organised through experience, exerting a directive or dynamic influence upon the individual response to all objects and situations with which it is related. Attitude is an enduring organization of motivational, emotional, perceptual and cognitive process with respect to some aspect of the individual’s world.

A person’s attitude comprises three components namely affective, cognitive and overt. The affective or feeling component refers to the emotions associated with an object [1]. It basically consists of the feeling a person has towards an object. The cognitive component represents the belief of a person about an object. It consists of individual’s perception beliefs and ideas about an object. The overt component is concerned with the way one intends to behave towards a particular object. Both the affective and cognitive components (feeling and belief) influence the way a person intends to behave towards an object.

Data source

The study is based on primary data. Primary data have been collected from the selected entrepreneurs in the southern districts (Madu The study is based on primary data. Primary data have been collected from the selected entrepreneurs in the southern districts (Madurai, Theni, Dindigul, Virudhunagar, Ramanathapuram and Sivaganga) of Tamil Nadu with the help of an interview schedule. Secondary data have been obtained from the books, journals, web sites and unpublished records.

Period of the study

The primary data relating to the entrepreneurs of has been collected during 2014-2015.

The attitude of the entrepreneurs towards the performance of industrial estates is very important to enrich their talents in the field in future. Hence, an attempt has been made on the measurement of attitude towards the industrial estates, association of profile variables and attitudes, the factor that influences their attitude and the factors discriminating the satisfied and the dissatisfied.

The attitude represents the inner feeling of the individual towards a particular aspect. The favorable attitude towards an object motivates the respondent to involve in it. The attitude in the present study shows the level of satisfaction towards the operational performance of industrial estates. The attitude towards the operational performance of industrial estates is measured at a five point scale namely highly satisfied, satisfied, moderate, dissatisfied and highly dissatisfied which carries 5, 4, 3, 2 and 1 mark respectively [2]. The classification of respondents according to their level of attitude towards the operational performance of industrial estates is shown in Table 1.

Perception in Enterprises Number of Respondents Percentage
Highly satisfied 38 16.89
Satisfied 49 21.78
Moderate 50 22.22
Dissatisfied 51 22.67
Highly dissatisfied 37 16.44
Total 225 100.00

Table 1: Attitude towards performance of industrial estates.

From Table 1, it has been observed that around 38.67% of the entrepreneurs are either satisfied or highly satisfied with the performance of industrial estate whereas around 39.11% of the entrepreneurs are either highly dissatisfied or dissatisfied. In total 22.22% of the entrepreneurs are moderately viewing about the performance industrial estates. Those satisfied with their enterprises include the highly satisfied, satisfied and moderate whereas the dissatisfied consist of dissatisfied and highly dissatisfied.

Association between profile of entrepreneurs and their attitude towards industrial estates

An attempt has been made to analyze the association between the profile of entrepreneurs and their attitude towards the performance of industrial estates with the help of chi-square analysis. The chisquare value and its significance are calculated for each profile variable separately. The fourteen profile variables and the five different levels of satisfaction are analyses separately with help of contingency table. The results are presented in Table 2.

Profile Variables Calculated Chi-Square Value Table Value at 5% level Significance
Age 31.0130 26.185 Significant
Education 50.0854 36.304 Significant
Sex 7.0139  2.377 Significant
Caste 11.0855  21.017 Not significant
Nature of family 5.0659   9.377 Not significant
Marital status 13.5109 21.015 Not significant
Family size 22.1413 26.185 Not significant
Earning members per family 20.0671 26.185 Not significant
Occupational background 36.0812 31.31 Significant
Material possession 24.5091 26.185 Not significant
Monthly income 16.5721 26.185 Not significant
Family income 28.0717 31.31 Not significant
Personal traits 29.0819 26.185 Significant
Involvement index 36.1031 26.185 Significant

Table 2: Association between profile of entrepreneurs and attitude towards industrial estates

From Table 2, it has been inferred that the significantly associated profile variables with the attitude of entrepreneurs towards the operational performance industrial estates are age, education, sex, occupational background, personal traits and enterprise involvement index, since their calculated chi-square values are greater than the respective chi-square table value at 5% level [3]. There is no association between attitude towards industrial estates and the profile variables namely caste, nature of family, marital status, family size, earning members per family, material possession, monthly income and family income since the respective chi-square values are less than the related table values at 5% level.

Testing of Hypotheses

There is a significant relationship between age, education, sex, occupational background, personal traits and involvement index and operational performance of industrial estates. Hence, the null hypothesis is rejected. Therefore, it could be inferred that the profile variables such as age, education, sex, occupational background, personal traits and involvement index does not influence the attitude of the respondents towards performance of industrial estates.

Attitude towards the various performance of the industrial estates

The performance is reflected in so many ways like monetary or non-monetary. In general, the performance of industrial estates is observed with the help of so many aspects like sheds at low cost, banks, material, transport, space, service, road facility, canteen, postal service, water, market, power and labour. In the present study, the attitude of the entrepreneurs is measured regarding their performance towards facilities available in the industrial estates. The attitude towards the above said performance variables is measured at a five-point scale of highly satisfied, satisfied, moderate, dissatisfied and highly dissatisfied which carries 5, 4, 3, 2 and 1 marks respectively [4]. The mean score in the attitude towards various performance variables is measured among the satisfied and dissatisfied entrepreneurs separately.

In this study, the entrepreneurs are classified into two groups as the satisfied and the dissatisfied on the basis of their overall attitude towards the performance of industrial estates. The entrepreneurs who are highly satisfied, satisfied and moderate in their attitude towards the enterprise are classified as the satisfied group and the dissatisfied and highly dissatisfied are the dissatisfied group. The number of satisfied entrepreneurs is 137, whereas the remaining 88 are grouped as dissatisfied. The t-test has been applied to find out the significant difference between the mean of each performance variable. The resulted mean and its respective ‘t’ statistics are shown in Table 3.

Facility Average Score
Satisfiers Dissatisfiers t-statistics
Sheds at low cost 3.5706 1.2106 2.3147*
Banks 3.1657 2.3057 0.8019
Material 3.0560 1.1057 2.1021*
Transport 2.5731 1.2152 1.3818
Space 3.4506 2.1270 1.4785
Service 3.7107 1.8281 1.8412*
Road facility 4.0135 2.5764 3.0142*
Canteen 3.5071 1.6071 2.3928*
Postal service 2.1133 1.1055 1.8089*
Water 2.7530 2.0560 0.7071
Market 2.0712 1.9712 2.9289*
Power 2.3322 1.0351 1.5091
Labour 2.5302 2.0602 3.0721*

Table 3: Attitude towards various performance of industrial estates.

From Table 3, it has been inferred that the important variables of performance of industrial estates among the satisfied entrepreneurs are road facility, service and sheds at low cost. Their mean scores are 4.0135, 3.7107 and 3.5706 respectively. Among the dissatisfied entrepreneurs, the identified variables are road facility and banking services since their mean scores are 2.5764 and 2.3057 respectively. There is significant difference among the satisfied and dissatisfied entrepreneurs with all factors of business except banks, transport, space, water and power since their respective ‘t’ statistics are not significant at 5% level [5].

Impact of attitude on business performance variables

An attempt has been made to find out the influence of the attitude on performance variables on the overall satisfaction among the entrepreneurs. The Multiple regression model have been applied. The fitted regression model is

Y = a.X1b1 X2b2 X3b3 X4b4 X5b5 X6b6 X7b7 X8b8 X9b9 X10b10 X11b11 X12b12 X13b13 e

This is converted into log from

Log Y = log a + b1 log X1 + b2 log X2 + b3 log X3 + b4 log X4 + b5 log X5 + b6 log X6 + b7 log X7 +b8 log X8 + b9 log X9 + b10 log X10 + b10 log X10 + b11 log X11 + b12 log X12 + b13 log X13 + e.

Whereas,

Y = Score of an overall satisfaction.

X1 = Score on the attitude towards sheds at low cost.

X2 = Score on the attitude towards banks.

X3 = Score on the attitude towards materials.

X4 = Score on the attitude towards transport.

X5 = Score on the attitude towards space.

X6 = Score on the attitude towards service.

X7 = Score on the attitude towards road facility.

X8 = Score on the attitude towards canteen.

X9 = Score on the attitude towards postal service.

X10 = Score on the attitude towards water.

X11 = Score on the attitude towards market.

X12 = Score on the attitude towards power.

X13 = Score on the attitude towards labour.

a = Intercept.

e = Error terms.

b1, b2,..bn = Regression coefficients of the independent variables.

The resultant regression coefficients with its statistical significance are shown in Table 4.

Enterprising Variables Regression Coefficient t-statistics
Constant 0.5076  
Sheds at low cost 0.1082* 8.0195
Banks 0.1014 1.0217
Material 0.0105* 3.4445
Transport -0.0832 0.7234
Space 0.0327 0.2102
Service 0.1717* 7.7061
Road facility 0.0605 1.2535
Canteen -0.0179 0.0771
Postal service 0.0815* 10.2396
Water 0.1313 1.0297
Market 0.0778* 8.0611
Power 0.0622 1.2522
Labour -0.0171 0.0778
R2 0.6621  
F-Statistics 16.0272*  

Table 4: Impact of attitude towards performance variables.

From Table 4, it has been observed that the attitude towards sheds at low cost, material, service and postal service and market significantly influences the overall satisfaction. That is a unit increase in the aforesaid variables increases the overall attitude by 0.1082, 0.0150, 0.1717, 0.0815 and 0.0778 units respectively. Even though the attitude on other variables except attitude on bad debts and credibility are positively influencing the overall attitude towards the enterprises, their respective regression coefficients are not significant at 5% level. The coefficient of determination for the regression model conveys that the change in overall attitude is influenced by the change in attitude towards various factors of business performance to the extent of 66.21%.

Impact of profile variables towards satisfaction of the entrepreneurs

The profile variables may influence the overall attitude towards performance of industrial estate. In the present study, an attempt has been made to analyze the influence of each profile variable on the overall attitude towards performance of industrial estate. The score on overall attitude towards performance of industrial estate is treated as the score of dependent variables whereas the score on the profile variables is taken as score of independent variables. The resultant regression coefficients are shown in Table 5.

Profile Variables Regression Coefficient
Satisfier Dissatisfier Pooled
Age  -0.1814* -0.1717* -0.1305*
Education 0.2017* 0.0245 0.1814
Sex 0.0111 0.0712 0.0191
Caste 0.0017 0.0715 0.0085
Nature of Family -0.0568 0.0386 0.0703
Marital Status 0.0174 0.0075 0.0821
Family Size  -0.0371* -0.0718 -0.0292
Earning members per family 0.0136 0.0122 0.0827
Occupational background 0.1307* 0.1212*  0.1895*
Material Possession -0.0707 0.0634 0.0215
Monthly Income 0.1187* 0.0871* 0.0871*
Family Income 0.0562 0.1281* 0.0115
Personal Traits 0.1892* 0.0314 0.0787
Enterprise involvement index  0.3138* 0.2718*  0.2127*
Constant 1.1756 0.3135 0.8616
R2 0.5038 0.4832 0.7125
F- Statistics 14.1821* 12.0893* 22.0824*

Table 5: Impact of profile variables towards satisfaction of entrepreneurs towards performance of industrial estates.

From Table 5, it has been inferred that among the satisfied entrepreneurs, the significantly influencing profile variables on the overall attitude towards performance of industrial estates are age, education, family size, occupational background, monthly income, personal traits and involvement index. That is an unit of increase in age and family size of the entrepreneurs results in a decline of overall attitude by 0.1814 and 0.0371 units respectively [6]. An unit of increase in education, occupational background, monthly income, personal traits and enterprise involvement index of satisfied entrepreneurs results in an increase of overall attitude towards performance of industrial estates by 0.2017, 0.1307, 0.1187, 0.1892 and 0.3138 respectively.

The significantly influencing profile variables among dissatisfied entrepreneurs are age, occupational background, monthly income, family income and enterprise involvement index. The regression analysis on the pooled data reveals that an unit of increase in occupational background, monthly income and involvement index of the entrepreneurs results in an increase in overall attitude towards performance of industrial estates by 0.1895, 0.0871 and 0.2127 units respectively. The coefficient of regression conveys that change in overall attitude towards performance industrial estates is explained by the change in profile variables to the extent of 71.25%.

Factors discriminating satisfiers and dissatisfiers towards performance of industrial estates

An attempt has been made to identify the profile variables discriminating satisfied and dissatisfied for the purpose of finding the relative importance of fourteen profile variables with regard to their power to discriminate between the satisfied and the dissatisfied. Fisher’s discriminant function analysis test has been applied. The Mahalanobis D2 statistics was calculated to measure the distance between the two groups. The ‘F’ statistics were used to see if the two groups were different from each other. The resultant discriminant function coefficient, mean differences of discriminant variables and their relative importance in discriminant function are shown in Table 6.

Variables Mean Difference Discriminant Function Coefficient Product Percentage
EI Index 3.11* (9.701) 1.7181 5.7538 24.75
Monthly Income 2.79* (4.124) 1.5813 4.7810 21.46
Education 3.01* (8.063) 1.0727 3.1562 14.29
Occupational background 2.64* (4.615) 1.0639 3.1034 14.06
Age 2.79 (0.712) 0.8123 2.5164 11.46
Family Income 2.24* (5.6069) 0.6124 1.5674 7.23
Sex 0.56* (7.322) 2.2137 1.4514 6.70
Personality Traits 2.01 (1.2624) 0.4184 1.0607 4.62
Marital Status 1.19* (2.788) 0.0115 0.0374 0.55
Caste 0.75 (0.752) 0.0096 0.0048 0.01
Earning Members per family 1.82* (4.725) -0.0856 -0.0735 -0.72
Family Size 1.01* (6.506) -0.2122 -0.2471 -1.39
Material Possession 0.84* (3.412) -0.3817 -0.3513 -2.05
Nature of Family 0.38* (1.273) -1.1227 -0.5131 -2.56

Table 6: Discriminatory profile variables and their relative importance.

From Table 6, it has been observed that the values of D2 and F ratio calculated were 2.1089 and 9.23121 respectively. The ‘F’ ratio is found to be significant at 5% level. Hence, the variation between the satisfied and the dissatisfied is significant. This implies that fourteen variablessignificant difference is found in the case of eleven variables. The ranking of percentages of distance measured by important variables reveals that, the first three ranks comprising enterprises involvement index (25.75%), monthly income (21.46%) and education (14.29%) are found individually contributing more than average distance in terms of discrimination as compared to other factors in discriminating the satisfied and the dissatisfied. together were useful in discriminating the satisfied and the dissatisfied. Among the mean differences obtained over fourteen variables, the

The calculated discriminant score Z1 and Z2 for satisfied and dissatisfied were 2.7152 and 1.0727. The critical value of discriminant score (2) for these two groups is 1.8356. Based on these score, the discriminant function can be used to predict the entrepreneurs as satisfied (> 1.8356) and dissatisfied (< 1.8356).

The Fisher’s discriminant function analysis test was applied to identify the discriminating business performance variables as satisfied and dissatisfied. The attitude on various business performance variables namely profit, marketing, cash flow, bad debts, competition, future scope expansion of capital base, credibility, financial assistance and management is taken as discriminant variable. The mean difference of the aforesaid variables between the satisfied and dissatisfied, discriminant function coefficient and its relative importance in discriminant function are computed and shown in Table 7.

.
Enterprising Variables Mean Difference Discriminant Function Coefficient Product Percentage
Service 2.26* (7.122) 2.0613 4.7870 34.18
Space 2.03* (4.071) 1.8176 3.8480 27.61
Market 1.79* (6.075) 1.8134 3.5317 25.41
Transport 1.24* (1.505) 1.1517 1.5870 11.76
Banks 1.01* (5.065) 1.3142 1.3452 10.02
Sheds at low cost 0.75* (4.712) 0.7962 0.6364 5.14
Road facility 1.24* (4.871) -0.0643 -0.0817 -0.59
Water 1.16* (1.788) -0.2873 -0.2812 -2.49
Labour 1.27* (6.063) -0.3861 -0.4537 -4.00
Canteen 1.79* (7.712) -0.4064 -1.0429 -7.33
Material 1.27* (5.063) -0.3861 -0.4537 -4.00
Power 1.09* (7.712) -0.3064 -0.3339 -3.33
Postal service 0.97* (4.063) -0.2861 -0.2775 -3.00

Table 7: Discriminating enterprising variables on satisfied and dissatisfied.

Figures in the parentheses are ‘t’ values

From Table 7, it has been inferred that the values of Mahalanobis D 2 and F-ratio calculated are 1.8142 and 11.3580 respectively. The ‘F’ ratio conveys that the distance between satisfied and dissatisfied is significant. This implies that the ‘thirteen’ performance variables together are useful in discriminating satisfied and dissatisfied. Among the mean difference of the above said, ten variables, significant difference is found in all the ten variables. The ranking percentage of distance measured by important variables reveals that the first three are attitude on space, service and marketing, which constitute 34.18, 27.61 and 25.41% respectively. They individually contribute more than the average distance in terms of discrimination as compared to other factors in discriminating satisfied and dissatisfied. The calculated discriminant scores ‘Z1’ and ‘Z2’ for satisfied and dissatisfied are 3.0135 and 1.2735 respectively. The critical value of Z for these two groups is 2.0679. Since the value of discriminant score of given entrepreneurs is more than 2.0679, they are satisfied.

Summary

The attitude of the entrepreneurs towards the performance of industrial estates is very important to enrich their talents in the field in future. Hence, an attempt has been made on the measurement of attitude towards the industrial estates, association of profile variables and attitudes, the factor that influences their attitude and the factors discriminating the satisfied and the dissatisfied. it has been observed that around 38.67% of the entrepreneurs are either satisfied or highly satisfied with the performance of industrial estate whereas around 39.11% of the entrepreneurs are either highly dissatisfied or dissatisfied. In total 22.22% of the entrepreneurs are moderately viewing about the performance industrial estates. Those satisfied with their enterprises include the highly satisfied, satisfied and moderate whereas the dissatisfied consist of dissatisfied and highly dissatisfied. The t-test has been applied to find out the significant difference between the mean of each performance variable. An attempt has been made to find out the influence of the attitude on performance variables on the overall satisfaction among the entrepreneurs. The Multiple regression model have been applied. The Mahalanobis D2 statistics was calculated to measure the distance between the two groups. The ‘F’ statistics were used to see if the two groups were different from each other. The resultant discriminant function coefficient, mean differences of discriminant variables and their relative importance in discriminant function.

Suggestions

Steps and packages of new measures are necessary to encourage and attract the SC and ST entrepreneurs into the industrial scene. Government should provide basic infrastructure facilities in the industrial estates. Entrepreneurs should be given proper training in all the crucial areas to foster entrepreneurship inclinations, which is vital for industrial prosperity.

The promotional agencies have to inculcate the spirit of entrepreneurship among the weaker sections, tribal and women who constitute a large section of Indian masses and need to be brought into the mainstream.

There is a need to nurture and develop entrepreneurial culture, which calls for the involvement, and interaction of different organisations and attitudinal changes in the society.

Entrepreneurship in small and tiny industries cannot be developed without developing large and medium industries and agriculture, as there is a linkage between agriculture and industry and also between large, medium and small industry.

References

 

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