Wilfried Kerntke (2004): Mediation als Organisationsentwicklung

Ohne Zusammenfassung     

Efficiency Wages: Signals or Incentives An Empirical Study of the Relationship between Wage and Commitment

Efficiency wage theories arguethat firms induce their employees to work in a moredisciplined way by paying high wages. Two basicmechanisms have been pointed out in economics about how these wage premia motivate employees.The incentives-driven `shirking model' impliesthat employees who have a highly paid job workin a more disciplined way so as to avoid beingdismissed. The ``gift exchange' model is basedon the assumption that high wages change therelationship between employer and employee.Empirical evidence on the incentives approachis mixed and a thorough competitive testingagainst the gift exchange model was notpossible due to the fact that the latter wasnot worked out enough. However, there is a relational theory of efficiency wages which isworked out in detail in order to allow directcompetitive testing. This relationalsignaling approach, as it is called, is basedon framing effects and comes to specifichypotheses about the conditions under whichefficiency wages work. These hypothesescontrast sharply with predictions from theincentives approach. The paper presents anempirical test of the theories and shows thatthe data clearly reject the incentive-basedpredictions and confirm the relationalsignaling predictions.     

Minimization of maximum lateness under linear deterioration

This paper considers a single-machine scheduling problem to minimize the maximum lateness. The processing time of each job is a linear function of the time when the job starts processing. This problem is known to be -hard in the literature. In this paper, we design a branch-and-bound algorithm for deriving exact solutions by incorporating several properties concerning dominance relations and lower bounds. These properties produce synergic effects in accelerating the solution finding process such that the algorithm can solve problems of 100 jobs within 1 min on average. To compose approximate solutions, we revise a heuristic algorithm available in the literature and propose several hybrid variants. Numerical results evince that the proposed approaches are very effective in successfully reporting optimal solutions for most of the test cases.     

Modeling longitudinal binomial responses: implications from two dueling paradigms

The generalized estimating equations (GEEs) and generalized linear mixed-effects model (GLMM) are the two most popular paradigms to extend models for cross-sectional data to a longitudinal setting. Although the two approaches yield well-interpreted models for continuous outcomes, it is quite a different story when applied to binomial responses. We discuss major modeling differences between the GEE- and GLMM-derived models by presenting new results regarding the model-driven differences. Our results show that GLMM induces some artifacts in the marginal models at assessment times, making it inappropriate when applied to such responses from real study data. The different interpretations of parameters resulting from the conceptual difference between the two modeling approaches also carry quite significant implications and ramifications with respect to data and power analyses. Although a special case involving a scale difference in parameters between GEE and GLMM has been noted in the literature, its implications in real data analysis has not been thoroughly addressed. Further, this special case has a very limited covariate structure and does not apply to most real studies, especially multi-center clinical trials. The new results presented fill a substantial gap in the literature regarding the model-driven differences between the two dueling paradigms.     

Progressive multi-state models for informatively incomplete longitudinal data

Progressive multi-state models provide a convenient framework for characterizing chronic disease processes where the states represent the degree of damage resulting from the disease. Incomplete data often arise in studies of such processes, and standard methods of analysis can lead to biased parameter estimates when observation of data is response-dependent. This paper describes a joint analysis useful for fitting progressive multi-state models to data arising in longitudinal studies in such settings. Likelihood based methods are described and parameters are shown to be identifiable. An EM algorithm is described for parameter estimation, and variance estimation is carried out using the Louis’ method. Simulation studies demonstrate that the proposed method works well in practice under a variety of settings. An application to data from a smoking prevention study illustrates the utility of the method.     

A Cross-Validation Analysis of Neural Network Out-of-Sample Performance in Exchange Rate Forecasting

Econometric methods used in foreign exchange rate forecasting have produced inferior out-of-sample results compared to a random walk model. Applications of neural networks have shown mixed findings. In this paper, we investigate the potentials of neural network models by employing two cross-validation schemes. The effects of different in-sample time periods and sample sizes are examined. Out-of-sample performance evaluated with four criteria across three forecasting horizons shows that neural networks are a more robust forecasting method than the random walk model. Moreover, neural network predictions are quite accurate even when the sample size is relatively small.     

Development and Validation of TQM Implementation Constructs

The contemporary quality management (QM) literature prescribes various quality improvement strategies. However, it lacks scientifically developed and tested constructs that represent an integrative QM philosophy. Moreover, an impact of the prescribed QM strategies on a firm's product quality has not been analyzed. Through a detailed analysis of the literature, this research identifies 12 constructs of integrated QM strategies. Using a survey of 371 manufacturing firms, the constructs are then empirically tested and validated. LISREL 7 is used for this purpose. Finally, a framework to examine the effects of integrated QM strategies on a firm's product quality is suggested. Comparisons between this and two other comprehensive scales of TQM are made.     

A Bayesian-loss function-based method in assessing loss caused by ship-source oil spills in the arctic area

It is difficult to assess the risk of ship-source oil spills in Arctic waters for insurance purposes due to many unknowns and the lack of reliable data. However, maritime activities in the Arctic area continue to grow, indicating the urgent needs for the development of innovative methods to estimate loss from potential ship-source oil spills in the Arctic area. To fill this gap, we develop a hybrid Bayesian-loss function-based method to assess ship-source oil spill-related loss and implement an illustrative test on Baffin Island, Nunavut in Canada. The results confirm that our method can accurately assess loss and, subsequently, develop reliable insurance premiums for shipping activities in the Arctic area. This enables governmental and nongovernmental organizations alike to use the method as a reliable loss estimation mechanism for ship-source oil spills. Also, it is a valuable tool in designing measures for safer and more resilient Arctic shipping.