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In response to the tech skills gap, this research paper aims to examine the influence of occupational characteristics, gender and work-life balance on IT professionals' satisfaction with and commitment to their chosen occupation. In addition, the authors explore occupational differences across these investigated factors.

The authors employed a survey research method and partial least squares (PLS) modeling using 293 responses collected from professionals representing five clusters of Information Technology (IT) occupations. Authors further conducted exploratory post-hoc analysis of variance (ANOVA) tests to check for significant differences in key constructs across five IT occupational clusters.

Occupational characteristics were found to be significantly related to respondents' occupational satisfaction while work-life balance was associated with their level of occupational commitment. Authors also found that that the influence of work-life balance on occupational commitment was more positive for females than for males. Finally, significant differences were found for task significance, task variety, task autonomy, work-life balance and compensation across the five occupational clusters examined.

A key contribution of this study is the focus on IT professionals' satisfaction with and commitment to their chosen occupation rather than a job, organization or profession. Accordingly, the authors contribute a nuanced understanding of an occupation as a facet of job, professional and career outcomes. Authors also explore how gender moderates the influence of work-life balance on occupational commitment. Finally, rather than treating the IT profession as a unified whole as has been done in most prior studies, authors explore satisfaction and commitment related differences across occupational clusters.

The purpose of this paper is to explore the demand for big data and analytics curriculum, provide an overview of the curriculum available from the SAP University Alliances program, examine the evolving usage of such curriculum, and suggest an academic research agenda for this topic.

In this work, the authors reviewed recent academic utilization of big data and analytics curriculum in a large faculty-driven university program by examining school hosting request logs over a four-year period. The authors analyze curricula usage to determine how changes in big data and analytics are being introduced to academia.

Results indicate that there is a substantial shift toward curriculum focusing on big data and analytics.

Because this research only considered data from one proprietary software vendor, the scope of this project is limited and may not generalize to other university software support programs.

Faculty interested in creating or furthering their business process programs to include big data and analytics will find practical information, materials, suggestions, as well as a research and curriculum development agenda.

Faculty interested in creating or furthering their programs to include big data and analytics will find practical information, materials, suggestions, and a research and curricula agenda.

We propose an elaboration of the social structure and personality framework from sociological social psychology that is intended to promote integration across social psychological traditions and between social psychology and sociology, using the study of inequality as an example.

We develop a conceptualization of “generic” proximate processes that produce and reproduce inequality in face-to-face interaction: status, identity, and justice.

The elaborated framework suggests fundamental questions that analysts can pose about the macro-micro dynamics of inequality. These questions direct attention to the “how” and “why” of macro-micro relations by connecting structural and cultural systems, local contexts, and the lives of individual persons; highlighting implicit processes; making meaning central; and directing our attention to how people act efficaciously in the face of constraint.

Applying this framework, scholars can use existing theories and generate new ones, and can do so inductively or deductively.

Research on inequality is enriched by social psychological analyses that draw on the full complement of relevant methods and theories.

We make visible the social psychological underpinnings of sociological research on inequality and provide a template for macro-micro analyses that emphasizes the centrality of social psychological processes.

Modelling has been a mainstay of conventional planning support tools (PSTs) since the 1960s and is instrumental in transport and land use planning decision-making. Numerous studies have been conducted to model the potential impacts of emerging vehicle automation and sharing technologies. A systematic review of recent modelling studies of autonomous and shared vehicles in the research literature examines the extent of their contribution to ‘smart’ mobility knowledge. The findings suggest a limited knowledge base from which to support future planning. PSTs that can offer more pluralistic, discursive, and transparent methods in order to understand and proactively shape a transition to a planned urban future are also needed.

This chapter examines the framing of the Black Lives Matter (BLM) Movement in mainstream media. An analytic sample of 4,303 articles collected from the Dow Jones Factiva database reveals variation in depth, breadth, and intensity of BLM coverage in the following newspapers between 2012 and 2016: The St. Louis Post-Dispatch, The New York Times, The Washington Post, The Wall Street Journal, and Al Jazeera English. We review contemporary literature on racial inequality and employ Media Framing and Critical Race Theory to discuss the implications of our findings on public perceptions, future policy formation, and contemporary social protest worldwide.

This review article focuses on the factors that affect the selection and implementation of three principles of distributive justice (i.e., equity, equality, and need) to reward systems in group and organizational settings. After presenting an overview of the assumptions, goals, and possible consequences associated with each of the three perspectives, the article then describes the moderating factors influencing distribution rule preferences across four levels of analysis: (1) the interorganizational, (2) the intraorganizational, (3) the work group, and (4) the individual. Some of the variables discussed include cross‐cultural differences, reward system implementation, task interdependency, work group climate, and individual characteristics. This material is then summarized through the use of a new conceptual model for describing allocation rule preferences. The article concludes with suggestions for future research.