Researches in job satisfaction started in early 20^th Century and it had received focus during the Hawthorne Studies at Western Electric. Ever since, a number of studies have been done in this area and presently we are having volumes of data about job satisfaction.

Employee satisfaction is one of the most researched topic in India (Ganesh, 1990; Khandwalla, 1988; Sinha, 1981; Sinha & Singh, 1995). Studies have revealed job satisfaction to be of great significance for the effective functioning of any organisation. It has been found to be intimately related to morale. It is often a factor in worker productivity, influences his attendance and stability, and has a spillover effect on employee relations and accidents (Bhattacharya & Gosh, 1984; Srivastava & Roy, 1996; Prakasam, 1982; Mowday, 1981; Scarpello & Campbell, 1983).

The reason for the popularity of the subject job satisfaction is not hard to explain. Most individuals spend a large part of their working lives at the work. So an understanding of factors involved in job satisfaction is relevant to improving the well being of a large number of individuals in an important aspect of their lives. Another important reason for investigating job satisfaction is the belief that increasing job satisfaction will increase productivity and hence the profitability of organisations (Gruneberg, 1979).

Robbins (2005) defines job satisfaction as “collection of feelings that an individual holds toward his or her job”. There is no dearth of definitions for the term and social scientists who have attempted to define job satisfaction have brought forth varying definitions for the term. DuBrins (1988) on the other hand defines job satisfaction as:

Job Satisfaction is the amount of pleasure or contentment associated with a job. If you like your job intensely, you will experience high job satisfaction. If you dislike yourjob intensely, you will experience job dissatisfaction.

According to Davis, Keith (1981) “Job satisfaction is the favourableness or unfavourableness with which employees view their work”. Employee attitude, job satisfaction and industrial morale are often used synonymously but they are not the same. A favourable attitude may contribute to job satisfaction because job satisfaction is the result of so many attitudes. Likewise job satisfaction and morale do not carry the same meaning, though job tatisfaction is the result of so many attitudes.

Job satisfaction plays an important role for an organisation in terms of its productivity, efficiency and employee relation (Locke, 1976), and for an employee in terms of health and well being (Khleque, 1984). The concept is central to many aspects of industrial and organizational behaviour (Joshi & Sharma, 1977) and is believed to be a good predictor of employee behaviour (Ganguli, 1994). Job satisfaction is widely researched and there is no dearth of literature about the topic. Certain researchers have attempted to study the relationship between job satisfaction and demographic variables.

The results have been inconclusive and a number of studies have established diametrically opposite results. For instance, Krishnan & Krishnan (1984) and Lindstrom (1988) established positive and linear relationships between age and job satisfaction, However, Kacmar & Ferris (1989) and Snyder (1988) found the opposite. Khaleque & Rahman (1987) in their study of job satisfaction of workers of jute industries found that older, married and more educated workers were more satisfied than younger, unmarried and less educated workers.

Sinha & Sing (1995) found no significant relationship between employees’ job satisfaction and demographic variables like age, educational level, family size, level in the organization and years of service. However, they established that the more educated the workers or the higher their position, the more dissatisfied they were. Some other studies have established certain association between age and sources of satisfaction (De, 1977; Glenn & Taylor, 1977). Hunt & Saul (1975) examined the relationship between ages, tenure and job satisfaction among male and female white-collar workers. Age was found to have stronger relationship with job satisfaction than tenure among males. Reverse relationship was found among females.

In their study of white-collar employees, Glenn & Taylor (1977) found a moderate but consistent positive correlation between age and job satisfaction. Similar trends have been observed among blue-collar workers. De (1977) found a positive correlation between age and job satisfaction for top-level employees, a negative correlation for middle level employees, and insignificant correlation for lower level employees. While job satisfaction of top-level employees increased with age, it decreased with age among middle-level employees. The study highlighted the intervening influence of levels of organizational hierarchy in the relationship between job satisfaction and age.

Promila Kumari & Elawadhi (1986) examined the relationship between job satisfaction and locus of control to see the effect of interaction between job level and locus of control upon job satisfaction. It was indicated that high and low internal officers and clerks do not differ significantly with respect to their overall job satisfaction.

Bhatt (1993) studied job satisfaction of college teachers in relation to demographic variables like physical appearance, place of work and transfer. Findings reveal that job satisfaction among college teachers was not differentiated by physical appearance, job location and college transfers.

Several Indian and Western studies have also shown that wages continues to be perceived as a major factor constituting job satisfaction (e.g., Monga, 1978; Prakasam, 1982) Srivastava (1985) collected data on 100 employees of HAL, Kanpur. His results showed that as many as 76.3 per cent employees affirmed that higher wages would induce them to put in extra work, while 9.4 per cent said that such increase would have no effect. The rest were neutral to the issue.

Some Western studies on job satisfaction also support the point that pay remains most important in terms of satisfaction to most of the employees. For example, Porter (1961) found that managers attached more importance to the aAiount of pay they received than to the amount of autonomy, esteem, or social need fulfillment they received. Lawler & Porter (1968) found that “although presidents and vice presidents attached slightly less importance to pay, for both groups it was rated as very important. Khaleque et al (1992) measures the overall job satisfaction, mental health, fatigue and performance of the subjects. The results reveal that significant numbers of the respondents are satisfied with their present job. The results further indicate that there is significant influence of job satisfaction on mental health, fatigue and performance of industrial workers.

Financial institutions play a vital role in the economic and industrial growth of any country. Development and prosperity of any country be it be developing or developed is fully dependent on their financial institutions like banks, insurance etc. While financial institutions provide the needed credit to the economy, it is insurance industry that provides protection against misfortunes that the economy is likely to face. India is no exception to this. Ever since, the independence Indian banks have played a vital role in providing the much required and often needed credit. The Indian insurance industry, be it be Life or General, also played its due and positive role in this sphere. The protection provided by the insurance companies help the economy in general and the industries in particular to concentrate in their respective areas of operation. It has acted as a tool for security to the industry as a whole. This has indeed been a boon as regard the industries are concerned.

The Insurance sector in general and General Insurance sector in particular has been showing consistent growth and profitability over a period of time. Consequently, the success of general insurance companies deserves a critical appraisal from various view points. In any organisation, the quality of the work force is a major factor, especially in service sector. The satisfaction of the various categories of employees thus becomes a natural subject of investigation. Such an investigation in any organisation assumes greater importance when the working of that organisation has not previously been investigated.

Employee’s satisfaction and growth of organisation are inter-linked. Satisfied employees are indispensable for the growth and development of any organisation. The present scenario which is represented by severe competition and demand for better customer service, organisations require employees who are highly dedicated, motivated and satisfied. General Insurance industry is not an exception to this. Insurance companies should periodically assess the satisfaction level of their employees and corrective measures should be initiated wherever required. A comprehensive and serious study to assess the satisfaction levels of General Insurance employees is found to be lacking. The present study attempts to measure and compare the satisfaction levels of various classes of employees.

Based on the review of literature and previous studies on the topic, the following hypothesis has been formulated by the present investigator, for verification through empirical investigation.

The tool used for the present study was job satisfaction inventory developed by Indresan (1999) The tool consisted of 25 items. The items belonged to variables like nature of job, nature of supervision, working condition, equitable reward, opportunities for promotion, work group, employee morale, etc. The tool has a five point scale, viz. “Very much less than what it should be”, “Less than what it should be”, “Just what it should be”, “More than what it should be” and “Very much more than what it should be”.

The demographic details were collected by way of personal data form. The personal data form elicited details like sex, age, residence, number of family members, qualification, designation, monthly income, name of the company, completed years of service, number of promotions received, etc.

The data collected for the study were analysed using various statistical techniques. The various techniques used were ANOVA, t-test and correlation.

The total sample was classified as highly satisfied, moderately satisfied and dissatisfied based on the scores obtained by them. The mean value of the job satisfaction scores for the sample was found to be 75.59 and standard deviation as 16.63. Considering mean plus half of the standard deviation, to be highly satisfied category, it was found to be 83.91, whereas the mean minus half standard deviation the score value was found to be 67.27. Out of the 81 samples under study, 16 samples were found to be highly satisfied and 17 samples were found to be dissatisfied. The remaining samples of the population were found above the score value of 83.91. Score value was taken as moderately satisfied. The results are presented in Table 10.

The result of ANOVA between the various age groups based on the total job satisfaction score is presented in Table 11. The F value in the comparison between Age and the total value for Job Satisfaction, presented in Table 11 was found to be significant at 0.05 level (1.323). It denotes existence of significant difference in the variable, age of the respondents with respect to the overall job satisfaction. Studies in this area have provided inconclusive and diametrically opposite results. Krishnan & Krishnan (1994) and Lindstrom (1988) while established positive relationship between the factors under study, Kacmar & Ferries (1989) established the opposite. Further, it was also established that age factor is having strong relationship with job satisfaction (Hunt & Saul, 1975). The result of the comparison between designation and job satisfaction was found to be significant at 0.01 level (5.690). The results are provided in Table 12.

The result of ANOVA with respect to income and job satisfaction is provided in Table 13. It is found that there is significant difference at 0.01 level (11.794) for the variables under study. This is in line with the findings of Porter (1961) who established relationship between pay and job satisfaction. Further, several other studies have also shown that wages are perceived to be a major factor that leads to job satisfaction.

Significant difference at 0.01 level was found in the comparison of the number promotions received and the job satisfaction of the sample studied. The F value is 7.292 (Table 14). The results of ANOVA for the comparison between completed years of service and job satisfaction is presented in Table 15. As in the earlier case, it is observed that there is significant difference at 0.01 level with respect to the completed years of service and Job satisfaction.

The result of t-test comparing male & Female respondents with respect to job satisfaction is shown in the Table 16. The t-value of 3.757 shows that it is very significant. It is also observed that mean value of male respondents is 80.3191 and that of female respondents is 70.5000. Further the standard deviation of male respondents is 12.7877 whereas that of female respondents is 9.7305. It clearly indicates that the job satisfaction of male respondents is higher than that of female.

This difference may be due to the house-hold work of female respondents in addition to their routine office work. To and fro journeys by females are very difficult due to the lack of adequate and prompt public transport system. The female employees have to commute solely depending on the public transport systems which may be the reason for their low level of job satisfaction. This finding is in line with the studies conducted by De (1977). They established certain relationship between age and job satisfaction among male and female white collar workers. Further, age was also found to have stronger relationship with job satisfaction among males. Reverse relationship was also found among females.

The result of the t-test for the comparison of officers and subordinate employees is presented in Table 17. It is observed that the t-value is significant at 0.05 level, thereby, denoting difference in the satisfaction level of the classes under study. Further, it is observed that the mean value of officers is 77.857 and that of subordinate staff is 74.4872. This indicates that the officers are more satisfied than the subordinate staff. This may be due to the higher responsibility, decision making power, status and better salary and perquisites enjoyed by the officer as compared to the subordinate staff.

The result of t-test with respect to locale is shown in Table 18. The t-value is found to be not significant (0.637). It may be observed that the mean value of people resident in rural area is 74.47 and that of urban area is 76.65. The standard deviation is 11.4898 and 12.8313 for rural and urban respectively. There is found to be only marginal difference in the mean value and standard deviation. This denotes nil or marginal significant difference between the respondents under study. It may be due to the reduction on difference between rural and urban areas, as the place of residence of the respondents is in the capital district. The places near the capital city may also get more advantage of the state capital and hence not much difference is noticed between rural and urban areas. Further, the rural and urban differentiation is also getting increasingly narrowed or blurred with the facilities and opportunities available in both areas showing not much difference as it used to be in the past.

The result of correlation between various factors under study is provided in Table 20. The findings are of importance with respect to the study undertaken, as correlation was observed with respect to various factors studied by the investigator. The overall job satisfaction score was found to be correlated significantly with factors like sex, locale, qualification, designation and number of promotions received. The correlation scores are.471,.218,.413,.220, and.219 as provided in the correlation matrix. No correlation was observed in factors like class of respondents, age, members in the family and income. A more in depth study into the reasons of the correlation will provide vital clues with respect to the fascinated subject termed ‘job satisfaction’.

ANOVA test was done to make comparison between the total job satisfaction score and various factors like sex, age, locale, income, qualification, etc. The comparison between age and the total value for job satisfaction, presented were found to be significant. It denotes existence of significant difference in the variable, age of the respondents with respect to the overall job satisfaction.

The result of the comparison between designation and job satisfaction was also found to be significant. The result of ANOVA with respect to income and job satisfaction also observed that there is significant difference between the number of promotions received and the job satisfaction of the sample studied. The results of ANOVA for the comparison between completed years of service and job satisfaction observed that there is significant difference with respect to the completed years of service and job satisfaction.

The result of t-test comparing male and female respondents with respect to job satisfaction observed that there is significant difference among male and female respondents whereas the t-test conducted to compare the locale viz. rural and urban areas, the result showed insignificance.

The result of the t-test with respect to officers and subordinate staff were also obtained, that revealed significant difference.

The correlation of the job satisfaction score with the various factors of study was also made.

The results throw adequate light on the hypotheses formulated for the study. The details of the test of tenability of the hypotheses are given below:

The hypotheses formulated for the study that “There is substantial difference between the job satisfaction levels of the two different classes of employees viz. Officers and Subordinates staff, under study” is accepted.

The second hypotheses formulated for the study that “The Officers will have higher levels of job satisfaction as compared to that of the other Subordinate staff’- is accepted.

The results of the study have certain important implications on the general insurance industry. The general belief is that all the employees working in public sector undertakings are having better salary and perquisites and hence all are satisfied. This belief was also prevalent in the general insurance companies. But, the present study revealed that so many factors like sex, age, income, promotions received, years of service etc, will also attribute to the job satisfaction as a whole. Job satisfaction depends on several factors in addition to the intrinsic factors mentioned above. Better working atmosphere may lead to higher productivity and thus focus to higher satisfaction on the job performed.

The present study that examined only a few factors, is acknowledged to be of limited scope. A wide range of multi-dimensional and directional variables including demographic, personality, job and organization related variables are known to influence job satisfaction. There is need to conduct an in depth study covering larger sample size and broader area of investigation. However, the findings of this study being in general agreement with the findings of previous studies, and the theoretical significance of the study is noteworthy. The finding that only 19.75 per cent of the sample is highly satisfied and 17 per cent being dissatisfied does not augment well for any financial institutions. As far as service sector organisations like general insurance sector is concerned, it is the primary responsibility of the management to make cent percent satisfaction among the employees, and thus derive full productivity from its officers and employees which in turn lead to growth of the organisation.

The general insurance companies should initiate steps to identify the reasons for the dissatisfaction of its employees, and take remedial measures for the growth of the insurance sector in long run, especially considering the stiff competition from the private multi-national, private general insurance companies who have registered their presence in the Indian insurance market, and shown dramatic growth in income by means of premium payments.

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* Significant at 0.05 level

* Significant at 0.1 level

* Significant at 0.01 level

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* Significant at 0.05 level

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* Significant at 0.05 level

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