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published_or_final_version / Management Studies / Master / Master of Philosophy

This study was undertaken to investigate the relationships and interdependencies of work-unit technology, structure, leadership style and attitudes of personnel at the middle and lower level of the organizational hierarchy and to determine if a correlation exists between proper alignment of these variables and overall organizational effectiveness. Six variables have been identified by contingency theorists which must be properly aligned if organizations are to operate at peak efficiency and maximum effectiveness. These variables are the firm's outer environment, its objectives and goals, the adaptation of technology to attain these goals, organizational structure to coordinate and confine the technology, and the leadership style and personnel who use the technology within individual work units to satisfy the demands of the outer environment and meet organizational goals and objectives. Previous emphasis in contingency theory has been upon determining what constitutes proper alignment of these variables on a firm by firm or industry by industry basis, neglecting the fact that complex organizations are composed of many interacting work units in which these variables must also be properly aligned if maximum effectiveness is to be achieved. Four U.S. copper mining companies responsible for over 60 percent of domestic production consented to participate in the study. The data suggest that not only is the proper alignment of contingency variables within the firm as a whole important to organizational effectiveness as indicated by prior research, but the proper alignment of these variables within individual work units may be just as important a consideration in determining overall organizational effectiveness. Results further suggest that those mining firms within the industry whose work unit technologies show the closest alignment of routine technologies with mechanistic structures, autocratic leadership styles and personnel willing to conform, and non-routine technologies with organic structures, democratic leadership styles and personnel less willing to conform are more effective than those firms in which these variables were not so closely aligned. Implications of this study are that industrial firms can improve their overall performance and effectiveness by aligning technology, structure, leadership style and personnel within work units. The greater the number or work units in which these contingency variables are properly aligned within a business firm, the greater the success that firm will experience in realizing its primary objectives.

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This thesis is concerned with measuring and explaining the productive efficiency of firms or organizations. In particular, the study compares three alternative methods of measuring efficiency, namely, the deterministic frontier method, the stochastic frontier method, and the data envelopment analysis method (DEA). The dissertation consists of two parts. In Part I, the relative merits of the three methods are discussed and evaluated through a Monte Carlo study under certain known conditions. The study focuses on the effects of exogenous variables on efficiency estimates. The results show that the stochastic frontier method generally produces better efficiency estimates than the other two methods. The DEA, however, has a slight advantage in cases where there are weak input substitution and large variations in input variables. In Part II, the three methods are examined empirically through their applications to a panel of 19 railways in OECD countries and a panel of 36 international airlines. Comparison of the three sets of efficiency estimates confirms that on average the stochastic frontier method yields higher efficiency estimates than the other two methods, as indicated by the Monte Carlo results. The efficiency estimates by the two parametric methods are highly correlated, whereas there are considerable differences between the DEA estimates and those from the parametric methods. This is also consistent with the Monte Carlo results. By comparing the alternative efficiency estimates in the two applications, it is found that there is less discrepancy among the three sets of efficiency estimates in the airline case than in the railway case. This can be partly attributed to the fact that there are fewer variations in the operating environments in the airline case than in the railway case. The simulation results in Part I provide some general guidelines regarding the relative merits of the three alternative methods under certain known conditions. The two applications of the three methods in Part II serve as examples of how these three methods can be applied to practical problems where no a priori knowledge of either the production technology nor the efficiency profile exists. They illustrate some of the problems that may be encountered in empirical applications.

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Thesis (M.S.)--Ohio University, November, 2001. / Title from PDF t.p. Includes bibliographical references (leaves 125-126).

Thesis (M.S.)--Oregon State University, 2005. / Printout. Includes bibliographical references (leaves 178-182). Also available on the World Wide Web.

Part of Thesis (Ph. D.)--University of Chicago, 1930. / Lithographed. "Private edition, distributed by the University of Chicago Libraries."