An Integrative Framework for Measuring the Extent to which Organizational Variables Influence the Success of Process Improvement Programmes

abstract    Studies on the three types of process improvement programmes (Continuous Improvement, Reengineering and Benchmarking) have appeared many times in the literature. These studies suggest that certain organizational variables act as enablers and their presence or absence can significantly influence success rates. Such studies have tended to examine companies where a single programme has been implemented. In contrast, this paper examines a sample of companies who have experienced all three programmes. Our aim is to compare and contrast each programme's impact on firm performance and identify which organizational variables are common and which are programme-specific enablers of success. We build and test an integrative framework to support our analysis. Our study found that: (1) Reengineering delivered the greatest impact on performance; (2) executive commitment was needed to make this happen; (3) strategic alignment was the major influence on the success rate of Reengineering and Continuous Improvement programmes; and (4) employee empowerment was necessary for each programme to work effectively.     

Pseudo empirical likelihood method in the presence of missing data

In this paper, we propose an estimator for the population mean when some observations on the study and auxiliary variables are missing from the sample. The proposed estimator is valid for any unequal probability sampling design, and is based upon the pseudo empirical likelihood method. The proposed estimator is compared with other estimators in a simulation study.     

An application of the extended cross impact method to generating scenarios of social change in Japan

Scenarios of Japanese society in 2000 are obtained by applying an extended correlational cross impact analysis. Since the scope of the scenarios is extensive, a procedure is developed to generate the scenarios that consists of a preprocessing of the events of interest and a step-by-step application of a cross impact method. Three scenarios are described, based on a workshop where the procedure was applied.     

Managing academic innovation in Taiwan: Towards a ‘scientific-economic’ framework

Since the passage of the Science and Technology Basic Law in 1999, Taiwanese universities have taken a more “scientific-economic” approach to protect and commercialize their research. This research mainly examines innovation activities such as patenting, licensing, and incubated startups in the context of Taiwanese higher education institutions (HEIs). The “scientific-economic” framework used to analyze the strategic aspects influencing these academic innovations includes (1) intellectual property managerial capabilities, (2) the strength of external industrial partnerships, (3) the university entrepreneurial orientation, and (4) government research policy. Four hypotheses were developed. Data were collected via a questionnaire with all 122 HEIs in Taiwan surveyed.The research reveals that the aspects of intellectual property managerial capability, HEI-industry partnerships, and academic entrepreneurial orientation are useful to distinguish the university's innovation performance on patent grants, licensing incomes, and firm incubation. Also, government support on research plays a moderating role in academic innovation. Managerial and policy implications for managing innovation effectively in universities were drawn.     

Learning by doing,spillovers and shakeouts

This paper studies industry evolution driven by non strategic learning by doing and spillovers. We characterize a dynamic process of cost and output changes and its effect on welfare and industry profits. The paper gives conditions for shakeouts to occur and analyzes the key factors affecting these conditions. Since shakeouts could lead to a long-run social loss due to higher market concentration, there is a role for a government to play in limiting unnecessary shakeouts. The most effective way to do so is to enhance spillovers.JEL Classification: L11, L13, O31Correspondence to: Michael TroegeWe would like to thank Hans Mewis, Christophe Moussu and an anonymous referee for valuable comments and suggestions. We also benefited from comments of seminar participants at WZB, Humboldt University, Northwestern University and the EEA/ESEM 1999 meetings. Part of the research was carried out while Michael Tröge was visiting Northwestern University. Financial support by the German Research Council (DFG) is gratefully acknowledged.     

The entropies: Some roots of ambiguity

Entropy concepts have developed in four general contexts—thermodynamics, communication theory, statistical information theory and social and life sciences. These concepts have five distinct mathematical forms. Ambiguity and complexity in utilization of the concept has been heightened by this multi-faceted heritage. Effective utilization may be strengthened by a sharper articulation of entropy through combinations of literal, mathematical and graphical modes of expression. Geography and planning as user disciplines have important responsibilities in enhancing cross-disciplinary communication of this important adisciplinary concept. Implications of these arguments for the social sciences include the need for caution in drawing social analogies from the ambiguous entropy concepts of statistical mechanics; and an indication of the potential benefits of social science models based on the unambiguous entropic constructs of statistical information theory.     

Robustness to the unavailability of data in block designs

We present general results for finding or boundingt _maxB , the maximum number of arbitrary whole blocks of observations which can be removed from a block design, and still leave all of the elementary treatment contrasts estimable. The block sizes may be larger than the number of treatments. The results are applied to BBDs, reinforced BIBDs and BBDs, BTIBDs, and a series of variance balanced incomplete block designs with two block sizes. Also given for most of these designs, are results fort _max, the maximum number of arbitrary, scattered observations that can become unavailable, and still leave all of the elementary treatment contrasts estimable.The work was undertaken while Dr. Whittinghill was visiting Ohio State University, and supported by a grant from the Natural Sciences Division, Colby College, Waterville, Maine.