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INDIAN JOURNAL OF INDUSTRIAL RELATIONS

VOLUME 13

NUMBER 1 JULY 1977

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Book Reviews Readings in Indian Labour and Social Welfare (J.N. Mongia, ed.)

S.M. Pandey 9 3

The Multi-Nationals: Industrial Relations and the Trade Union Response (John Gennard)

M.S. Ashraf 94

Abidjan: Urban Development and Employment in Ivory Coast (Heather Joshi, Harold Lubell & Jean Mouly) Wage Structure and Labour Mobility in a Local Labour Market: A Study in Ahmedabad (T.S. Papola and K.K. Subrahmanian)

ORGANIZATIONAL CULTURE AND ITS IMPACT ON MANAGERIAL REMUNERATION P. SINGH, T. MATHEW & G.S. DAS Importance of intrinsic and extrinsic rewards in motivating people is still a contro-

R.K. Srivastava 96 versial issue. By and large most of the researches which have examined this subject do not rule out the importance of extrinsic reward. However, these studies have not analysed the relative pull and logic behind people demanding economic rewards. The authors of this paper have tried to test the hypothesis that the quality of the organizaC.K. John 98 tional life does not determine the level of economic rewards.

If we examine the behaviour of a group of persons in a work situation, we may find some glaring differences in the way they organize their efforts and do their jobs. Some perform their task in a much better and more efficient manner than others. Some are more involved and put in their Employment and Unemployment in Ethiopia— J.N. Upadhyay 10 1 best efforts. The possible explanations offered by the social scientists for Report of the Exploratory Employment such behaviour differences are: individuals' ability and their level of motivaPolicy Mission Organised tion. It is agreed that individual behaviour patterns and performance are (I.L.O.) governed by their level of motivation. There is, however, a considerable amount of disagreement on what motivates the individuals. Since the famous Hawthrone studies (Roethlisberger and Disckson, 1939) and the Index of Periodical Articles on Industrial Relations in India 107 work of Lewin and his associates on "Democratic Leadership" (Coch and French, 1948; Lewin, Lippit and White, 1939) a great deal of research work has been done in this area. Notwithstanding this, social scientists have not yet solved this problem. This controversy is more pronounced in India where managerial class is not fully convinced of the role of other motivational factors except money. They believe that money is the main instrument of motivation and by and large in this country people work primarily for money (Prabhu, Singh et al., 1975; Sharma and Dayal, 1975). The present•paper is designed to explore into this controversy. The founder of scientific management, Taylor, stipulated money as a motivational tool on the assumption that workers put forth extra efforts for their economic gains. Money is perceived as a generalized conditioned re-enforcer when it is repeatedly paired with primary re-enforcers (Holland and Skinner, 1961; Kellher and Gollub, 1962; Skinner, 1953). It is postulated that such generalized re-enforcers are very effective because of the

EDITOR : S.M. PANDEY

Prof. P. Singh is the Chairman of Organizational Behaviour and General Management, Xavier Labour Relations Institute, Jamshedpur, Mr. T. Mathew is Assistant Professor, NITIE, Bombay, and Mr. G.S. Das is Research Associate, Xavier Labour Relations Institute, Jamshedur.

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Discussion and Communication

86

sideration of the ratio of non-production to total workers as an approximate variable for the occupational mix. Our pre-occupation with this variable is not quite arbitrary for the following reasons: (i) it is reasonable to believe that the adoption of a new technology depends on the availability of highly skilled manpower; (ii) on the assumption of complementarity between fixed capital and highly skilled manpower it can be argued that if there is a qualitative or even quantitative change in the former, the proportion of non-production workers would change in a predictable way; and finally (iii) it can also be argued that if technical change is a function of expenditure on research and development which in turn determines the employment of say, scientists, engineers, etc., that the above ratio is crucial for understanding productivity changes. This paper is divided into four sections: section I describes the model, section II deals with the data, section III presents the results and finally in section IV some extensions are suggested.


87

linear and log-linear functional form. However, as the linear equation performed better than the log-linear, we have confined ourselves only to the former in the subsequent analysis. Algebraically,

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However, a perusal of this formulation suggests that there is a noticeable heterogeneity among the groups of non-production workers and, therefore, three different specifications of this variable, i.e. IL ) are tried. , These are as follows:

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where —=ratio of 0 and I category of non-production workers to

THE MODEL

This exercise involves estimation of a production function with value added per worker as the dependent variable and the ratio of non-production workers to total workers and fixed capital per unit of workers as the independent variable. This is with a view to isolating the contribution of non-production labour input in total productivity. Algebraically a production function may be put down as follows: Y=--z(L',

K)

L2

total workers, and

—= ratio of 2 and 3 category of non-production workers to total workers.

Henceforth, to observe the joint effect of 0-1 and 2-3 categories of the said workers in productivity in industries in question we have employed the following equation:

(i)

O

where Y is the output and L' and K are the non-production labour and capital, respectively. With a slight modification, the algebraic formulation of our model stands as:

fLi L2 K

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(vi)

THE DATA

=z 0 where — =Value added per worker in industries in question. L L' =Ratio of 0 to 3 categories of non-production workers to total workers, and K 47----Capital per unit of worker. In order to estimate this relationship we have experimented with both

Non-production workers comprise those engaged in executive, pur chasing, finance, accounting, legal, sales, sales deliveries, advertising, professional and related activities, science and technology, medicine and the like.' In terms of the National Classification of Occupation for 1958, the first four categories cover these workers.* *A specification of the occupational classification of workers is as follows: Category 0—Professional, Technical and Related Workers. Category 1—Administrative, Executive and Managerial Workers. Category 2—Clerical and Related Workers. Category 3—Sales Workers.

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This study is based on a sample of sixteen manufacturing industries. The data for the analysis are obtained from Annual Survey of Industries, 1965, 4 Occupational Pattern in India—Private Sector 1965' and Occupational, Educational Pattern in India—Public Sector 1966,° all our calculations regarding the occupation mix in public and private sector industries are based on the last two reports which are published by the Directorate General of Employment and Training (i.e., DGE & T). The data regarding value added, total workers and fixed capital are collected from the Annual Survey of Industries, 1965. It should be mentioned here that the DGE & T compiles data for public and private sector industries separately in alternate years. Also industries for which detailed occupational data are presented vary. And hence their conversion into a common classification derived from the ASI data is only an approximate one. The consolidated data matrix is shown in the Appendix—Table 1. Finally, let us briefly point out about the choice of the year for which results are presented. Apart from the comparability and coverage problems, which, in fact, accentuated further in the succeeding years, some other constraints were also realized, namely, the strained economic situation which began after 1966 and the resulting recession in the economy and so on. This has seriously affected the productivity as well as the employment opportunities, specifically in the manufacturing sector.' Therefore, it seems that 1965-66 is the most recent normal year for which data are available.

THE RESULTS

We will confine ourselves to the results derived from the linear equations. It has already been explained earlier that our model tries to examine the combined as well as disaggregated effect of the various categories of non-production workers. Considering this, four different formulations are tried and their results are discussed below separately. Equation 1 The first equation includes all the four occupational categories. Despite the fact that this group is a heterogeneous one (i.e., it lumps together the development scientist, physical scientist, engineers of various speciality, medical personnel, creative artists, writers, journalists, managerial and clerical workers, economists and the like), the results are statistically significant (Table 1). The coefficient of non-production workers is positive. This implies also that higher industrial productivity is positively associated


89

with the composition of these categories of workers in the total labour input. Equation 2 In this equation non-production workers include only professional, technical and related workers and administrative, executive and managerial workers. This in our opinion is a much more appropriate specification than that used in Equation 1. Table 1 confirms this. The coefficient has the right sign and is significant at 5% level. Equation 3 Here attempts are made to estimate the effect of clerical and related workers and sales workers. The equation does not have the same analytical appeal as the earlier one and hence the results are not expected to be of much significance. While the coefficient has the right sign, it is significant only at 10% level —and, thus, no important inference can be attempted except, perhaps, a negative one. A possible explanation in this regard max be given in the light of the general belief that public industries tend to over-employ these categories of workers. Our presumption, therefore, is that the introduction of a variable reflecting the share of clerical and sales workers in public and private sector industries may improve the result. This, of course, is not tried in the present study because of the lack of sector-wise output and capital data. Equation 4 In Equation 4 mutually inclusive specification of non-production workers (i.e., 0-1 and 2-3 categories) are included. The result of this equation confirms that the clerical and sales workers do not make any significant contribution to output. Moreover, the scanning of the . original correlation matrix shows that there is a high correlation (i.e., 0.736) between the two categories (i.e., 0-1 and 2-3) of non-production workers. Owing to this, probably the significance of result and the nature of association has been vitiated because of the problem of multi-collinearity.

SUMMARY AND CONCLUSIONS

The role of non-production workers in determining productivity in manufacturing industries is the main focus of our analysis. Our results show that productivity in the industries in question is positively associated

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with non-production labour input. This is borne out from the fact that the combined effect of all categories of non-production workers in total productivity is significant. Specifically, on productivity criterion, the results indicate that the relative significance of the first two categories of nonproduction workers seems to be higher than the subsequent two categories. This suggests the interesting possibility that it is not just the availability of technology and the workers to apply it which determines productivity but also how production is organized. Our analysis confirms this. Hence to overcome the problem of low productivity it is perhaps equally important to consider whether labour management is on sound principles, whether workers have a sense of participation, whether working hours are properly regulated, whether management is dynamic and forward-looking. While our analysis is not so detailed as to decompose labour productivity into the contribution of each of these factors, it does suggest these possibilities. Hence an extension of this analysis to capture the contribution of these variables would enable us to make more specific recommendations for raising productivity in Indian manufacturing industries.

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Nelson, R.R., "Aggregate Production Function and Medium Range Growth Projection", American Economic Review, Vol, LIV, No. 5, Sept. 1964, pp. 575-606. Griliches, Z. and Ringstad, V., Economics of Scale and the Form of the Production Function, North Holland Publishing Company, Amsterdam, 1971. Delehanty, G.E., Non production Workers in U.S. Manufacturing, North Holland Publishing Co., Amsterdam, 1968. Central Statistical Organization, Annual Survey of Industries, Vol. 1, 1965. Directorate General of Employment & Training, Occupational Pattern in India— Private Sector, 1965. Occupational-Educational Pattern in India—Public Sector, 1966. India, Government of., Economic Survey, 1973-74, pp. 78-79.

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