Journal of Modelling in Management

Wayne S. DeSarbo; Peter Ebbes; Duncan K.H. Fong; Charles C. Snow

doi: 10.1108/17465661011026130pmid: N/A

Purpose – Customer value has recently become a primary focus among many strategy researchers and practitioners as an essential element of a firm's competitive strategy. Many firms are engaged in some form of customer value analysis (CVA), which involves a structural analysis of the antecedent factors of perceived value (i.e. perceived quality and perceived price) to assess their relative importance in the perceptions of their buyers. Previous CVA research has focused upon using aggregate market or market segment level analyses. The purpose of this paper is to expose the limitations of implementing CVA on either an aggregate or market segment level basis, and propose an alternative individual level approach. Design/methodology/approach – The paper develops an extended hierarchical Bayesian approach for cross‐sectional data with one observation per response unit, which allows for estimation at the individual firm level to make CVA more useful. This paper demonstrates the utility of the proposed Bayesian methodology involving a CVA study conducted for a large electric utility company. It also compares the empirical results from aggregate, market segment, and the proposed individual level analyses, and show how traditional approaches mask underlying price and quality importance. Findings – Marketing and management strategy researchers need to exhibit care when conducting such CVA analyses as underlying heterogeneity can be masked when aggregate market or segment level analyses are conducted. Originality/value – This paper provides a new hierarchical Bayes recursive simultaneous model formulation for CVA analyses to provide individual level insights with cross‐sectional data.

Enrico Sevi

doi: 10.1108/17465661011026149pmid: N/A

Purpose – The purpose of this paper is to examine the effects of organizational citizenship behaviour (OCB) on organizational effectiveness. Specifically, it investigates the impact of helping behaviour on a group where members withhold the effort on job. Design/methodology/approach – Results are drawn from an agent‐based simulation model of a workgroup that has to accomplish some tasks for a specific duration. Findings – When there are group members withholding effort, OCB decreases organizational effectiveness; on the contrary, when individuals provide much effort in the job, OCB enhances group performance. High performance is reached by the group who are able to learn when OCB is appropriate and fitting. Research limitations/implications – Limitations of this paper are strictly linked to the absence of empirical analysis. The simulation model provides a logical and consistent theory that needs an empirical validation. Practical implications – This paper helps workers and supervisors since it warns them on the OCB gap and suggests that in the place of a blind OCB, the groups need to share a smart OCB to cultivate altruism with people who work hard, and to exclude the others. Originality/value – In the study of OCBs determinants and consequences, the academy has almost exclusively assembled on positive factors. This paper shows the OCB dark side and it asserts that citizenship effects on organization performance are not predetermined as a conceptual assumption. Effectiveness is assured by a dynamic and selective OCB only toward good workers.

Cataldo Zuccaro

doi: 10.1108/17465661011026158pmid: N/A

Purpose – The purpose of this paper is to discuss and assess the structural characteristics (conceptual utility) of the most popular classification and predictive techniques employed in customer relationship management and customer scoring and to evaluate their classification and predictive precision. Design/methodology/approach – A sample of customers' credit rating and socio‐demographic profiles are employed to evaluate the analytic and classification properties of discriminant analysis, binary logistic regression, artificial neural networks, C5 algorithm, and regression trees employing Chi‐squared Automatic Interaction Detector (CHAID). Findings – With regards to interpretability and the conceptual utility of the parameters generated by the five techniques, logistic regression provides easily interpretable parameters through its logit. The logits can be interpreted in the same way as regression slopes. In addition, the logits can be converted to odds providing a common sense evaluation of the relative importance of each independent variable. Finally, the technique provides robust statistical tests to evaluate the model parameters. Finally, both CHAID and the C5 algorithm provide visual tools (regression tree) and semantic rules (rule set for classification) to facilitate the interpretation of the model parameters. These can be highly desirable properties when the researcher attempts to explain the conceptual and operational foundations of the model. Originality/value – Most treatments of complex classification procedures have been undertaken idiosyncratically, that is, evaluating only one technique. This paper evaluates and compares the conceptual utility and predictive precision of five different classification techniques on a moderate sample size and provides clear guidelines in technique selection when undertaking customer scoring and classification.

Rafael Pastor; Albert Corominas

doi: 10.1108/17465661011026167pmid: N/A

Purpose – The purpose of this paper is to propose a bicriteria integer programming model for hierarchical workforce scheduling in which the first criterion is the cost and the second is the suitability of task assignment to individual employees. The model is based on the integer programming formulation for the hierarchical workforce scheduling problem published in 2007 by Seçkiner et al. , which extends the model proposed by Billionnet in 1999. Design/methodology/approach – The principal hypothesis of this paper is that, although an employee is capable of performing several different tasks with equal efficiency, the type of task to which he/she is assigned affects the overall suitability of the assignment configuration. Therefore, cost‐minimising solutions should also optimise task assignment when possible. This paper considers real cases and confirm that this approach to the problem is appropriate for dealing with common situations in personnel management. Findings – The proposed idea is applied to the example problem used by Seçkiner et al. and the results are compared with Seçkiner et al. 's model results. Originality/value – Consequently, the proposal is more general and a more faithful representation of the problems faced by personnel managers, which should help to bridge the gap between academic studies and practical cases.

Leonidas A. Zampetakis; Vassilis S. Moustakis

doi: 10.1108/17465661011026176pmid: N/A

Purpose – The purpose of this paper is to present an inductive methodology, which supports ranking of entities. Methodology is based on Bayesian latent variable measurement modeling and makes use of assessment across composite indicators to assess internal and external model validity (uncertainty is used in lieu of validity). Proposed methodology is generic and it is demonstrated on a well‐known data set, related to the relative position of a country in a “doing business.” Design/methodology/approach – The methodology is demonstrated using data from the World Banks' “Doing Business 2008” project. A Bayesian latent variable measurement model is developed and both internal and external model uncertainties are considered. Findings – The methodology enables the quantification of model structure uncertainty through comparisons among competing models, nested or non‐nested using both an information theoretic approach and a Bayesian approach. Furthermore, it estimates the degree of uncertainty in the rankings of alternatives. Research limitations/implications – Analyses are restricted to first‐order Bayesian measurement models. Originality/value – Overall, the presented methodology contributes to a better understanding of ranking efforts providing a useful tool for those who publish rankings to gain greater insights into the nature of the distinctions they disseminate.