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The purpose of this paper is twofold. First, the authors provide a survey of operations management (OM) research applications of traditional hierarchical and nonhierarchical clustering methods with respect to key decisions that are central to a valid analysis. Second, the authors offer recommendations for practice with respect to these decisions.

A coding study was conducted for 97 cluster analyses reported in six OM journals during the period spanning 1994-2015. Data were collected with respect to: variable selection, variable standardization, method, selection of the number of clusters, consistency/stability of the clustering solution, and profiling of the clusters based on exogenous variables. Recommended practices for validation of clustering solutions are provided within the context of this framework.

There is considerable variability across clustering applications with respect to the components of validation, as well as a mix of productive and undesirable practices. This justifies the importance of the authors’ provision of a schema for conducting a cluster analysis.

Certain aspects of the coding study required some degree of subjectivity with respect to interpretation or classification. However, in light of the sheer magnitude of the coding study (97 articles), the authors are confident that an accurate picture of empirical OM clustering applications has been presented.

The paper provides a critique and synthesis of the practice of cluster analysis in OM research. The coding study provides a thorough foundation for how the key decisions of a cluster analysis have been previously handled in the literature. Both researchers and practitioners are provided with guidelines for performing a valid cluster analysis.

To the best of the authors’ knowledge, no study of this type has been reported in the OM literature. The authors’ recommendations for cluster validation draw from recent studies in other disciplines that are apt to be unfamiliar to many OM researchers.

Presents a new approach to working set generation for personnel scheduling problems. In full‐time (FT) and mixed‐workforce (MW) experiments, generates the schedules in the working sets from the use of two‐phase heuristic labour scheduling solution procedures. The solution procedures were implemented on a 386 microcomputer and did not require the specification of the size of the working sets in advance. In the FT experiment, the general set‐covering formulations (GSCFs) associated with the produced working sets were solved with integer programming. The new working set procedure yielded optimal integer solutions for all 36 test problems in the FT experiment. Owing to the size and complexity of the problem data in the MW experiment, the GSCFs associated with the working sets were solved with linear programming, and heuristic rounding procedures were applied to obtain feasible integer solutions. The mean labour costs of these solutions averaged 0.69 per cent less than the mean cost of solutions obtained via the application of heuristic rounding procedures applied to the linear programme solutions for the GSCFs associated with the master sets. Compares solution costs for the new working set method with those associated with other working set generation/refinement procedures. Results indicate that the new method produces lower solution costs in less control processing unit time.

Examines an alternative approach to labour utilisation, based on the concept of simulated annealing, implemented on a microcomputer. Demonstrates the use of the new approach in a study of the potential labour utilisation effect of two types of scheduling flexibility: shift length flexibility and meal‐break placement flexibility. Finally, offers implications of the new approach for management.

Cross‐utilization of the labour force is widely recognized as a method for improving productivity in service organizations. This paper investigates the effect of cross‐utilization on workforce staff size, at the aggregate level, for a two‐skilled labour force. Workers are assumed to have 100 per cent productivity in their primary skill, and cross‐training policies ranging from zero to 100 per cent productivity in the secondary skill were investigated across a variety of labour demand conditions. The results suggest that small degrees of cross‐utilization can provide significant workforce savings and that there tend to be diminishing returns beyond 50 per cent productivity in the secondary skill.

Labour scheduling heuristic methods have been applied in service operating environments using both actual and synthetic demand patterns. Two important characteristics of these demand patterns are (1) demand smoothness and (2) mean demand. Investigates the effects of demand smoothness and mean demand on the solution quality associated with four prominent heuristic methods. Indicates that both characteristics can affect the performance of the heuristic methods. An especially important finding is that the two methods which use information from linear programming solutions are far more robust to changes in the degree of demand smoothness. Concludes that managers should consider linear programming methods as an alternative or supplement for making their scheduling decisions. Also recommends that labour scheduling researchers use multiple levels of mean demand and demand smoothness when evaluating new heuristic methods.

This research aims to utilize a social network analysis approach to examine the effect of organizational position within a network of strategic partnerships on innovation as measured by perceptions of industry analysts. Specifically, the purpose of the paper is to examine how network characteristics such as degree centrality (being centrally located in a network), between centrality (being positioned as an intermediary), and closeness centrality (having a short average distance to all other firms in the network) affect the innovation ranking of the focal firm.

Data for 563 firms are generated from three distinct data sources (SDC Platinum: Alliances and Joint Ventures, COMPUSTAT, and Fortune's America's Most Admired Companies) and analyzed via social network analysis and linear regression.

The network characteristics of degree centrality and between centrality positively relate to industry perceptions or innovativeness whereas closeness centrality had no significant effect. Additionally, there were no discernable differences in innovativeness when comparing manufacturing firms to service organizations.

Insignificant findings related to closeness centrality and the good/service differential may be attributable to the data sources, in that, the information is limited to firms within the respective sources. This data limitation may limit the potential of examining the effect of all network characteristics. Additionally, some included companies participate in multiple industries (i.e., have multiple SIC codes), which may serve as the blurring of any differences between good and service firms.

The results highlight the importance of considering strategic partnerships that establish configurations of partnership webs when pursuing innovation activities. Specifically, the findings suggest that firms should seek numerous strategic partnerships (high degree centrality) and attempt to broker information or control the extent to which partners collaborate (high between centrality). These results provide insights for firms seeking to establish new supply‐chain relationships in order to enhance their level of innovation.

This research provides a unique empirical examination of the impact of network positional characteristics on the innovativeness of a focal firm.

This paper aims to introduce knowledge discrimination to consumer research. It also examines the antecedent effects of objective knowledge and confidence in knowledge on consumer knowledge discrimination. Research in psychology has sought to distinguish between calibration and discrimination, two related skills in probabilistic judgments. Though consumer research has sought to examine knowledge calibration, the construct of knowledge discrimination has not attracted any attention.

The paper reports on three studies which use a cross-sectional design using a structured questionnaire. The hypotheses are tested using regression. In addition, the paper also reports the results of an experimental study.

The paper finds that the objective knowledge has a positive effect on discrimination. But confidence in knowledge does not have a consistent effect on discrimination. The paper also finds that feedback improves discrimination.

The study adds a new dimension to the examination of metaknowledge and metacognitions in the consumer domain.

The study suggests some ways in which companies/government agencies can improve consumer knowledge discrimination.

Knowledge discrimination is expected to reduce consumer vulnerability and enhance consumer competence.

This is the first study to examine knowledge discrimination in the consumer domain. Prior research has observed that there could be a trade-off between calibration and discrimination. Hence, the study of knowledge discrimination can inform the study of knowledge calibration.

The purpose of this study is use a bibliometric analysis to explore the relational nature of knowledge creation in WFM in operations. Companies live under constant pressure to find the best ways to plan their workforce, and the workforce emangement (WFM) is one of the biggest challenges faced by managers. Relevant research on WFM in operations has been published in a several range of journals that vary in their scope and readership, and thus the academic contribution to the topic remains largely fragmented.

To address this gap, this review aims to map research on WFM in operations to understand where it comes from and where it is going and, therefore, provides opportunities for future work. This study combined two bibliometric approaches with manual document coding to examine the literature corpus of WFM in operations to draw a holistic picture of its different aspects.

Content and thematic analysis of the seminal studies resulted in the extraction of three key research themes: workforce cross-training, planning workforce mixed methods and individual workforce characteristics. The findings of this study further highlight the gaps in the WFM in operations literature and raise some research questions that warrant further academic investigation in the future.

Likewise, this study has important implications for practitioners who are likely to benefit from a holistic understanding of the different aspects of WFM in operations.

Studies on consumer knowledge calibration have used different measures of calibration. The purpose of this paper is to undertake a comparative assessment of important measures. In addition, it seeks to identify the best performing measure.

The paper reports on three studies. The first study uses eight survey data sets. The second and third studies use experiments.

The study found that the Brier score component measure is most responsive to feedback and is the most suitable measure of knowledge calibration. The results also indicate that researchers should use measures that use item-level confidence judgements, as against an overall confidence judgement.

By documenting the relationship between the different measures of knowledge calibration, the study enables proper interpretation and accumulation of results of various studies that have used different measures. The study also provides guidance to researchers in psychology and education where this issue has been noted.

The study provides guidance to managers in knowledge intensive industries, such as finance and insurance, interested in understanding their consumers’ knowledge calibration.

This is the first study in consumer research that examines this issue.