Institutional Fleecing: The Slow Death of Dutch Provinces

Many theories on organizational change depart from the assumption of change for the better, that is, change in order to gain a stronger position in relation to its competitors, to become more effective or efficient, or at least to improve the organization. It is our idea that the theories developed on this basis are biased. Contrasting to this dominant approach, this article gives a longitudinal analysis of the development in an organization in decline. It is directed at explaining the downfall of a Dutch province. In the medieval empire of Charlemagne it was one of the most powerful duchies of Europe. Later it became one of the seven provinces in the powerful Dutch Republic, and nowadays it has lost nearly all its tasks and functions. Departing from neo-institutional theory this paper seeks the major causes for this downfall and specifies some of the relations in the theoretical model of punctuated equilibrium. It concludes that the historical institutional dynamics can be seen as a self-enforcing process in which punctuations can be explained by the increasing distance between individual preferences within the organization, and the pressures originating from developments in the environment.Dr. M.S. de Vries is professor in Public Administration at the Radboud University Nijmegen. Address: Thomas van Aquinostraat 5 (room 5.1.56). P.O. Box 9108, 6500 HK Nijmegen, The Netherlands, tel;++31 24 3615691.     

Trope Control: The Costs and Benefits of Metaphor Unreliability in the Description of Empirical Phenomena*

The process of communicating and interpreting the meaning of metaphors in business writing is deeply unreliable. This stems from the structure of metaphors in which some of the characteristics of a source domain are transferred to a target domain. The precise selection of characteristics is made by the reader rather than the author of the metaphor, thus creating uncertainty of meaning. Although there are some benefits stemming from the inherent ambiguity of metaphor, the unreliability of the trope not only makes it impossible to choose between competing metaphors, but may distort our view of reality and thus lead to poor management decision‐making. Moreover, the unreliability of the interpretation process is so pronounced that some authors have attempted to reject the use of metaphor entirely. However, this paper argues that although it is impossible to avoid employing metaphor, contrary to the conventional wisdom in this subject area, it is possible to improve meaning reliability. Drawing on linguistic theory to explain the recommendations, and illustrative examples from business literature and practice, the papers offers several recommendations for so doing that may be applied throughout the Business and Management field.     

The Role of Shocks in Employee Turnover*

This paper reports the findings from a recent study of nurse leavers at eight large hospitals in the National Health Service (NHS) of England and Wales. The study develops and extends an influential theory of employee turnover by describing how for some leavers a single, jarring event or shock triggers the decision to quit. By elaborating on the nature of shocks for this sample of 352 nurse leavers, the paper allows for improved understanding of nursing turnover and thus offers an example of relevant management research. The analysis of shock illustrates how conventional research methodologies can lead to a distorted picture of turnover. This has wider implications, both for any organization wishing to manage turnover effectively and for future research. The paper adds to the limited body of empirical analysis on actual leavers, thereby contributing to an ongoing methodological debate concerning the use of proxy variables. By highlighting flaws in the dominant methodology used to study turnover, the paper offers an example of management research that is also rigorous, and thus ‘pragmatic’.     

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity – which includes omitted variables, omitted selection, simultaneity, common-method variance, and measurement error – renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation could be confounded; these methods include fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66% and up to 90% of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.     

Regulation by disclosure: the case of internal control

In this paper we explore the use of disclosure as a regulatory tool, using as an illustration the current UK requirements regarding the disclosure of information about internal control. After discussing the broad concept of regulation by disclosure, we trace the evolution of concepts of internal control and its reporting, describing the background to the Turnbull guidance for directors on internal control reporting, the basis of current UK requirements. We then examine recent examples of internal control disclosures, identifying the range of ways in which they address the disclosure requirements and considering the possible impact of the disclosure requirements on corporate behaviour and on the audiences for disclosure. We conclude with some reflections on the disclosure life cycle. The paper contributes to the literature on disclosure by specifically considering the role of disclosure as a regulatory tool and by examining the nature of specific disclosures in an area of continuing interest, that of internal control.     

Soft Regionalism in Action: Examining Voluntary Regional Councils’ Structures,Processes and Programs

In the United States, the voluntary regional council is the dominant organizational form used by local, state and federal agencies to address regional issues. However, research addressing the details of their operations including their structures, processes and programs has been limited. This article reports on a survey of thirty of these regional councils that are located in large metropolitan areas. The findings indicate that these councils reflect a form of “soft regionalism.” Primarily, they facilitate, coordinate and energize, but they don’t have the more expansive capabilities of consolidations, regional governments and annexations.     

National Defense,Environmental Regulation,and Overhead Democracy: A View from the “Greening” of the U.S. Military

This study examines the patterns of politics accompanying efforts to hold the United States military accountable to U.S. environmental and natural resources (ENR) laws in the post-Cold War era. This analysis (1) uses three cases to describe what happened, and why, (2) to test several propositions related to military accountability to ENR laws in the post-Cold War era; (3) to offer a typology of tactics used that may help inform future research on intragovernmental regulation more generally; and (4) argues that public agencies have a responsibility to comply with the regulatory processes that hold them accountable to U.S. ENR laws.     

Using Frontier Analysis to Evaluate Company Performance

The measurement of performance is critical to nearly all managerial disciplines. Yet little is known about the aggregation characteristics of the components of performance and how our notion of a ‘good performing firm’ relates to what we use as a dependent variable. In this paper we propose an approach to the measurement of performance that uses the logic of frontier analysis and the technique of data envelopment analysis. The approach is shown to be a reasonable representation of the multidimensional nature of performance and is shown to replicate, effectively, the components that strategic management scholars typically consider when discussing performance. It is also shown to be superior to the simpler alternatives based on traditional approaches to performance measurement.     

Quantitative Risk Assessment of the New York State Operated West Valley Radioactive Waste Disposal Area

This article is based on a quantitative risk assessment (QRA) that was performed on a radioactive waste disposal area within the Western New York Nuclear Service Center in western New York State. The QRA results were instrumental in the decision by the New York State Energy Research and Development Authority to support a strategy of in‐place management of the disposal area for another decade. The QRA methodology adopted for this first of a kind application was a scenario‐based approach in the framework of the triplet definition of risk (scenarios, likelihoods, consequences). The measure of risk is the frequency of occurrence of different levels of radiation dose to humans at prescribed locations. The risk from each scenario is determined by (1) the frequency of disruptive events or natural processes that cause a release of radioactive materials from the disposal area; (2) the physical form, quantity, and radionuclide content of the material that is released during each scenario; (3) distribution, dilution, and deposition of the released materials throughout the environment surrounding the disposal area; and (4) public exposure to the distributed material and the accumulated radiation dose from that exposure. The risks of the individual scenarios are assembled into a representation of the risk from the disposal area. In addition to quantifying the total risk to the public, the analysis ranks the importance of each contributing scenario, which facilitates taking corrective actions and implementing effective risk management. Perhaps most importantly, quantification of the uncertainties is an intrinsic part of the risk results. This approach to safety analysis has demonstrated many advantages of applying QRA principles to assessing the risk of facilities involving hazardous materials.     

Estimating the optimal order quantity and the maximum expected profit for single-period inventory decisions

The paper considers the classical single-period inventory model, also known as the Newsboy Problem, with the demand normally distributed and fully observed in successive inventory cycles. The extent of applicability of such a model to inventory management depends upon demand estimation. Appropriate estimators for the optimal order quantity and the maximum expected profit are developed. The statistical properties of the two estimators are explored for both small and large samples, analytically and through Monte-Carlo simulations. For small samples, both estimators are biased. The form of distribution of the optimal order quantity estimator depends upon the critical fractile, while the distribution of the maximum expected profit estimator is always left-skewed. Small samples properties of the estimators indicate that, when the critical fractile is set over a half, the optimal order quantity is underestimated and the maximum expected profit is overestimated with probability over 50%, whereas the probability of overestimating both quantities exceeds again 50% when the critical fractile is below a half. For large samples, based on the asymptotic properties of the two estimators, confidence intervals are derived for the corresponding true population values. The validity of confidence intervals using small samples is tested by developing appropriate Monte-Carlo simulations. In small samples, these intervals attain acceptable confidence levels, but with high unit shortage cost, for the case of maximum expected profit, significant reductions in their precision and stability are observed.