Alternatives to the archetypal model of full-time regular employment are now both prevalent and wide-ranging. Over a fifth of U.S. workers, and even more globally, now perform economic work under arrangements that differ from full-time regular employment. Yet most of our management and social science notions about economic work are based on the full-time employment model. We know relatively little about the operation and consequences of alternative arrangements in part because while these arrangements vary considerably, they are commonly grouped together for research purposes using existing classification systems. We outline an inclusive classification system that distinguishes clearly between employment and its alternatives. It also distinguishes among the alternatives themselves by grouping work arrangements into categories that share common properties and that are distinct from each other in ways that matter for practice and for research. The classification system is based on distinctions about the sources and extent of control over the work process, the contractual nature of the work relationship, and the parties involved in the work relationship. Our classification system is both informed by and reflects the legal distinctions among these categories. We explore implications of our system for research and theory development.

There is a substantial gap between the promise and reality of artificial intelligence in human resource (HR) management. This article identifies four challenges in using data science techniques for HR tasks: complexity of HR phenomena, constraints imposed by small data sets, accountability questions associated with fairness and other ethical and legal constraints, and possible adverse employee reactions to management decisions via data-based algorithms. It then proposes practical responses to these challenges based on three overlapping principles—causal reasoning, randomization and experiments, and employee contribution—that would be both economically efficient and socially appropriate for using data science in the management of employees.

Interest in the potential effects of different systems for organizing work and managing employees on the performance of organizations has a long history in the social sciences. The interest in economics, arguably more recent, reflects a general concern about the sources of competitiveness in organizations. A number of methodological problems have confronted previous attempts to examine the relationship between work practices and the performance of firms. Among the most intractable has been a concern about establishing causation given heterogeneity biases in what have typically been cross-sectional data. The results from prior literature are suggestive of important productivity effects but remain inconclusive. To address the major methodological problems we use a national probability sample of establishments, measures of work practices and performance that are comparable across organizations, and most importantly a unique longitudinal design incorporating data from a period prior to the advent of high performance work practices. Our results suggest that work practices that transfer power to employees, often described as "high performance" practices, may rise productivity, although the statistical case is weak. However, we also find that these work practices on average raise labor costs per employee. The net result is no apparent effect on efficiency, a measure that combines labor costs and labor productivity. While these results do not appear to be consistent with the view that such practices are good for employers, neither do they suggest that such practices harm employers. They are, however, consistent with the view that these practices raise average compensation and hence may be good for employees. Overall, then, the evidence suggests that firms can choose "high road" human resources practices that raise employee compensation without necessarily harming their competitiveness.

Interest in the potential effects of different systems for organizing work and managing employees on the performance of organizations has a long history in the social sciences. The interest in economics, arguably more recent, reflects a general concern about the sources of competitiveness in organizations. A number of methodological problems have confronted previous attempts to examine the relationship between work practices and the performance of firms. Among the most intractable has been a concern about establishing causation given heterogeneity biases in what have typically been cross-sectional data. The results from prior literature are suggestive of important productivity effects but remain inconclusive. To address the major methodological problems we use a national probability sample of establishments, measures of work practices and performance that are comparable across organizations, and most importantly a unique longitudinal design incorporating data from a period prior to the advent of high performance work practices. Our results suggest that work practices that transfer power to employees, often described as "high performance" practices, may rise productivity, although the statistical case is weak. However, we also find that these work practices on average raise labor costs per employee. The net result is no apparent effect on efficiency, a measure that combines labor costs and labor productivity. While these results do not appear to be consistent with the view that such practices are good for employers, neither do they suggest that such practices harm employers. They are, however, consistent with the view that these practices raise average compensation and hence may be good for employees. Overall, then, the evidence suggests that firms can choose "high road" human resources practices that raise employee compensation without necessarily harming their competitiveness.