Business and Management Studies in the 2014 Research Excellence Framework

The Research Excellence Framework 2014 (REF 2014) was the 7th formal assessment of research in UK universities and other institutions of higher education. Participation in these assessments is voluntary, and institutions can decide which staff to include and under which discipline to include them. A hundred and one institutions chose to submit research in Business and Management Studies, and this work was assessed by a panel of academic researchers and research users nominated by a wide range of academic constituencies. The previous assessment exercise was conducted in 2008, and REF 2014 shows that the quality of UK research in Business and Management Studies, already high in 2008, has improved since then. The operation of the Business and Management Studies sub‐panel is described, the results are summarized, and a few caveats are discussed so as to aid the Business and Management Studies community in its endeavours to understand and evaluate the process and the results.     

The Role of Industry Studies and Public Policies in Production and Operations Management

The research domain Industry Studies and Public Policy (IS&PP) seeks to further our understanding of industrial practices and managerial challenges by explicitly considering contextual details in the design and interpretation of research studies. These details can be vital considerations when shaping public policies. This article reviews a sample of IS&PP publications and analyzes the content of 180 selected papers—85 papers published in the Production and Operations Management (POM) journal and 95 papers published in related journals between 1992 and 2014. Our analysis of the sample dataset and examination of exemplar papers provide four findings. First, studies in different industries emphasize different themes of operational decisions. This difference in emphasis reveals potential research opportunities, especially for conducting inter‐industry studies. Second, our analysis reveals a shift in focus over time. Earlier studies contain a mix of benchmarks and inter‐industry comparisons, while later studies tend to be context‐specific, intra‐industry studies. Third, we report on empirics → analytics → empirics cycles that reveal gaps for building novel theories. Finally, we observe that the relationship between POM decisions and public policy is bi‐directional. This highlights the need to jointly examine operational decisions with policy considerations, especially in information goods, healthcare, sustainable operations and high‐tech manufacturing industries.     

Catholic Civics Education in the Early Cold War: Zeal for Democracy,Zeal for Christ

In the late 1940s and 1950s American Catholic educators faced the dilemma of how to transmit Catholic faith and culture to the next generation while also reassuring their non-Catholic neighbors that they were fully American in lifestyle and loyalties. This article examines one response to that dilemma: the convergence of public and Catholic school civics curricula through the widespread use of experiential pedagogy in Catholic civics education. Using a content analysis of civics textbooks and teacher's guides from both school systems, this article demonstrates how both kinds of schools converged on an experiential style of civics education, despite vocal opposition to “progressive” pedagogy at elite levels of Catholic educational discourse. The article then presents a partial explanation for this dissonance, demonstrating the moral certainty exhibited in the same Catholic-school textbooks, and suggesting that Catholic educationists understood American Catholics to be morally privileged in a way that gave them special insight into American democracy and protected them from the negative influences of secular educational philosophy. This case study speaks to larger questions of how organizations manage conflicts between abstract principles and practical action, and suggests the value of including religious schools in the sociological study of “loose coupling” in educational organizations.     

Robust estimation of a multilevel model with structural change

We postulate a spatiotemporal multilevel model and estimate using forward search algorithm and MLE imbedded into the backfitting algorithm. Forward search algorithm ensures robustness of the estimates by filtering the effect of temporary structural changes in the estimation of the group-level covariates, the individual-level covariates and spatial parameters. Backfitting algorithm provides computational efficiency of estimation procedure assuming an additive model. Simulation studies show that estimates are robust even in the presence of structural changes induced for example by epidemic outbreak. The model also produced robust estimates even for small sample and short time series common in epidemiological settings.     

Comparison of Chemical Screening and Ranking Approaches: The Waste Minimization Prioritization Tool versus Toxic Equivalency Potentials

Chemical screening in the United States is often conducted using scoring and ranking methodologies. Linked models accounting for chemical fate, exposure, and toxicological effects are generally preferred in Europe and in product Life Cycle Assessment. For the first time, a comparison is presented in this article of two of the prominent, but structurally different methodologies adopted to help screen and rank chemicals and chemical emissions data. Results for 250 chemicals are presented, with a focus on 12 chemicals of interest in the United Nations Environment Programme's Persistent Organic Pollutants global treaty negotiations. These results help to illustrate the significance of described structural differences and to assess the correlation between the methodologies. The scope of the comparison was restricted here to human health, although the insights would be equally useful in the context of the health of ecosystems. Illustrating the current types of chemical screening and emissions comparison approaches, the relative significance of the scenario and structural differences of the Waste Minimization Prioritization Tool (WMPT) and the Toxic Equivalency Potential (TEP) methodologies are analyzed. The WMPT facilitates comparison in terms of key physical-chemical properties. Measures for Persistence, Bioaccumulation, and Toxicity (PBT) are calculated. Each PBT measure is scored and then these scores are added to provide a single measure of relative concern. TEPs account for chemical fate, multipathway exposure, and toxicity using a model-based approach. This model structure is sometimes considered to provide a less subjective representation of environmental mechanisms, and, hence, an improved basis for screening. Nevertheless, a strong relationship exists between the two approaches and both have their limitations.     

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food–pathogen pairs to provide insights for foodborne outbreak investigations.     

An Empirical Investigation of the Effects of Decision Aids on Problem-Solving Processes*

Despite the growing number of investigations examining decision support systems (DSS), relatively few empirical studies have evaluated the effects of DSS on problem-solving processes. This study uses protocol analysis to investigate the impact of a specific decision aid on problem-solving processes in a semi-structured problem. Results indicate that decision aids influence the problem-solving processes of decision makers. The effect of a decision aid is found to be contingent on familiarity with the decision aid, task familiarity, and the interaction of these two factors. Suggestions for incorporating interaction effects and problem-solving processes into future examinations are proposed.     

Action collective,action de mouvement social: la contribution du syndicalisme à la liberté au travail dans un exemple néo-zélandais

Les syndicats peuvent contribuer à la liberté au travail par une action collective axée sur l'intérêt des membres, mais aussi en nouant des partenariats avec d'autres acteurs de la société civile, dans le cadre d'un mouvement social. Pour traiter ce dernier aspect, encore peu documenté, les auteurs s'appuient sur les définitions de la liberté de Berlin (1988) et MacCallum (1967) puis sur la théorie de la démocratie radicale de Laclau et Mouffe (2019). Ils illustrent leur propos par une étude de cas portant sur les stratégies déployées par des syndicats néozélandais en vue d'accompagner l'action officielle pour une transition juste face au défi climatique.     

Quantitative risk assessment-epidemic curve prediction model for leafy green outbreak investigation

The objective of this study was to leverage quantitative risk assessment to investigate possible root cause(s) of foodborne illness outbreaks related to Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) infections in leafy greens in the United States. To this end, we developed the FDA leafy green quantitative risk assessment epidemic curve prediction model (FDA-LG QRA-EC) that simulated the lettuce supply chain. The model was used to predict the number of reported illnesses and the epidemic curve associated with lettuce contaminated with STEC O157 for a wide range of scenarios representing various contamination conditions and facility processing/sanitation practices. Model predictions were generated for fresh-cut and whole lettuce, quantifying the differing impacts of facility processing and home preparation on predicted illnesses. Our model revealed that the timespan (i.e., number of days with at least one reported illness) and the peak (i.e., day with the most predicted number of reported illnesses) of the epidemic curve of a STEC O157-lettuce outbreak were not strongly influenced by facility processing/sanitation practices and were indications of contamination pattern among incoming lettuce batches received by the facility or distribution center. Through comparisons with observed number of illnesses from recent STEC O157-lettuce outbreaks, the model identified contamination conditions on incoming lettuce heads that could result in an outbreak of similar size, which can be used to narrow down potential root cause hypotheses.