The Moderating Effects of National Age Stereotyping on the Relationships between Job Satisfaction and its Determinants: A Study of Older Workers across 26 Countries

This research explores how national age stereotypes impact older workers' job‐related perceptions by examining probability based samples across 26 countries taken from the European Social Survey. Multilevel data analysis was undertaken. Results show that, at the individual level, both extrinsic rewards and intrinsic rewards directly impact older workers' job satisfaction. At the country level, significant variations are found in the relationships between job satisfaction and related rewards for older workers across the 26 countries. Society's stereotypical views towards older people explained some of these cross‐country variations. This study contributes to extant literature by explicating the process by which society's age stereotypes and the meta‐stereotypes held by older workers affect how these workers make sense and take meaning out of their job‐related circumstances leading to enhanced or diminished job satisfaction. Implications highlight the need for management to be vigilant in identifying and dealing with age stereotypes in the workplace. Furthermore, managers need to be more aware of the potential harmful consequences arising from negative meta‐stereotypes and should implement strategies to tackle workplace stereotypes that would lead to negative meta‐stereotypes held by older workers.     

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.     

Disrupting an imposed racial identity or performing the model minority? The pursuit of postsecondary education by young African immigrant men in Southern Ontario,Canada

ABSTRACT

This article examines how young African immigrant men in Southern Ontario cope with the dominant racial identity at school in an effort to improve their academic performance and access postsecondary education (PSE). Critical race theory in education is employed to explain how the young men distance themselves from stereotypes about Black masculinity by regulating their own behaviour and differentiating themselves from their Caribbean immigrant peers. Sixty-seven young men who had immigrated to Southern Ontario from several African countries over the last 10 years were interviewed individually and in focus groups for the study. The findings suggest that the research participants adopted a model minority status within an educational system that clearly embodies racist and systemically oppressive frameworks.     

A NORMATIVE RESOURCE TRANSFER MODEL

In this paper, the author suggests a methodology for facilitating interactive decision making in a decentralized organization by providing information which may result in the transfer of divisional resources. The resource-transfer information is generated at the beginning of the planning period so that the organization's production control and evaluation systems may be formalized.     

Transforming technology management education: Value creation-learning in the early twenty-first century

Management education is often criticized as irrelevant, out of touch, too “trade-school,” too interested in training financial services professionals and consultants, and insufficiently focused on innovation, the major driver of the economy. Technology management (TM) education has always focused on practical and relevant issues and innovation has been a major theme. We believe however that rapid changes in the global environment of business demand changes in the underlying assumptions of TM. Starting with a brief overview of the field, this paper examines the major environmental changes that must be addressed by TM and the skills that future graduates will require.     

Harnessing the Theoretical Foundations of the Exponential and Beta‐Poisson Dose‐Response Models to Quantify Parameter Uncertainty Using Markov Chain Monte Carlo

Dose‐response models are the essential link between exposure assessment and computed risk values in quantitative microbial risk assessment, yet the uncertainty that is inherent to computed risks because the dose‐response model parameters are estimated using limited epidemiological data is rarely quantified. Second‐order risk characterization approaches incorporating uncertainty in dose‐response model parameters can provide more complete information to decisionmakers by separating variability and uncertainty to quantify the uncertainty in computed risks. Therefore, the objective of this work is to develop procedures to sample from posterior distributions describing uncertainty in the parameters of exponential and beta‐Poisson dose‐response models using Bayes's theorem and Markov Chain Monte Carlo (in OpenBUGS). The theoretical origins of the beta‐Poisson dose‐response model are used to identify a decomposed version of the model that enables Bayesian analysis without the need to evaluate Kummer confluent hypergeometric functions. Herein, it is also established that the beta distribution in the beta‐Poisson dose‐response model cannot address variation among individual pathogens, criteria to validate use of the conventional approximation to the beta‐Poisson model are proposed, and simple algorithms to evaluate actual beta‐Poisson probabilities of infection are investigated. The developed MCMC procedures are applied to analysis of a case study data set, and it is demonstrated that an important region of the posterior distribution of the beta‐Poisson dose‐response model parameters is attributable to the absence of low‐dose data. This region includes beta‐Poisson models for which the conventional approximation is especially invalid and in which many beta distributions have an extreme shape with questionable plausibility.     

A Risk Assessment Framework for the Socioeconomic Impacts of Electricity Transmission Infrastructure Failure Due to Space Weather: An Application to the United Kingdom

Space weather phenomena have been studied in detail in the peer‐reviewed scientific literature. However, there has arguably been scant analysis of the potential socioeconomic impacts of space weather, despite a growing gray literature from different national studies, of varying degrees of methodological rigor. In this analysis, we therefore provide a general framework for assessing the potential socioeconomic impacts of critical infrastructure failure resulting from geomagnetic disturbances, applying it to the British high‐voltage electricity transmission network. Socioeconomic analysis of this threat has hitherto failed to address the general geophysical risk, asset vulnerability, and the network structure of critical infrastructure systems. We overcome this by using a three‐part method that includes (i) estimating the probability of intense magnetospheric substorms, (ii) exploring the vulnerability of electricity transmission assets to geomagnetically induced currents, and (iii) testing the socioeconomic impacts under different levels of space weather forecasting. This has required a multidisciplinary approach, providing a step toward the standardization of space weather risk assessment. We find that for a Carrington‐sized 1‐in‐100‐year event with no space weather forecasting capability, the gross domestic product loss to the United Kingdom could be as high as £15.9 billion, with this figure dropping to £2.9 billion based on current forecasting capability. However, with existing satellites nearing the end of their life, current forecasting capability will decrease in coming years. Therefore, if no further investment takes place, critical infrastructure will become more vulnerable to space weather. Additional investment could provide enhanced forecasting, reducing the economic loss for a Carrington‐sized 1‐in‐100‐year event to £0.9 billion.