The workforce in most industrialized countries is aging. However, the role of age in job design has largely been ignored. In the present paper, we apply lifespan development perspectives to the interaction between job characteristics and age. Specifically, we examine the possible joint effects of age and job characteristics on job satisfaction, engagement, and performance, developing a series of propositions to guide future research. We also discuss possible boundary conditions, mediating mechanisms, and future research challenges.

The workforce in most industrialized countries is aging and becoming more age-diverse, and this trend is expected to continue throughout the twenty-first century. Although there has been an increased interest in research on age differences at work, few studies have examined actual interventions designed to support workers at different points across the life span. In this article, we review the literature related to aging at work, including physical, cognitive, personality, and motivational changes; life-span development theories; age stereotyping; age diversity; and work-life balance. Based on this review, we propose a number of avenues for intervention research to address age differences at work. We conclude by identifying critical challenges specific to studying age at work that should be addressed to advance research on interventions.12.1

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The aging of the industrialized workforce has spurred research on how to support people working later in life. Within this context, the concept of work ability, or an employee's ability to continue working in their job, has been introduced as an explanatory mechanism for understanding employee disability, wellbeing, attitudes, and behavior. However, the work ability concept has evolved across disparate literatures with multiple, contentdiverse measures and often with little consideration of theory or examination of its nomological network. Using the job demands-resources model as a framework, we present a meta-analytic summary (k ϭ 247; N ϭ 312,987) of work ability's correlates and potential moderators of these relationships. Taken together, we found consistent negative relationships between job demands and work ability, and consistent positive relationships between job and personal resources and work ability. Work ability was also associated with important job outcomes including job attitudes and behaviors such as absenteeism and retirement. Measures of work ability that include both perceived and objective components generally showed stronger relationships than did exclusively perceptual measures, and occupation type was a significant moderator of certain relations between work ability and its correlates. We supplemented this meta-analysis with a primary data collection to examine differences between perceived work ability and the conceptually similar variables of self-efficacy and perceived fit, demonstrating that perceived work ability can explain incremental variance in joband health-related variables. Our discussion focuses on the value of the work ability construct for both research and practice and future directions for work ability research.

Research on knowledge transfer in organizations has been hampered by the lack of tools yielding valid scores for studying critical constructs in concert. The authors developed survey measures of absorptive capacity (the ability to transform new knowledge into usable knowledge) and experienced community of practice (the extent to which a person is engaged with the given practice community) to provide tools appropriate for field research. A holdout sample of 1,971 engineers in a Fortune 100 science/technology company yielded 583 responses. Confirmatory factor analysis was used to assess internal structure, and convergent and discriminant evidence of validity. Path analysis was used to assess criterion-related validity. Results demonstrate that the new measures are internally consistent, are related in meaningful ways to other organizational variables, and provide distinct explanatory power. An additional 231 responses from a second Fortune 100 science/technology company provides cross-validation.