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As the IT workforce becomes global, it is increasingly important to understand the factors affecting IT workers’ compensation in labor markets distributed across the globe. Ang et al. (2002) published the first in-depth analysis of compensation for IT professionals juxtaposing human capital endowment (education and experience) and institutional determinants (firm’s size, industry, and sector) of compensation in the Singaporean economy. In this paper, we explore the influence of particular national economies on IT workers’ compensation. We draw on research into the roots of wage differentials in labor economics and build on the Ang et al. research to present a multilevel analysis of IT workers’ compensation in the United States, analyzing the U.S. Bureau of Labor Statistics’ Current Population Survey (CPS) data for 1997, 2001, and 2003. We find that, while institutional differences in Singapore mattered only in conjunction with individual factors, in the U.S. institutional differences had a direct effect on IT workers’ wages. As tightness of IT labor supply decreased in the United States in the early 2000s, the influence of a firm’s size on wages became more pronounced. Also, female IT workers and workers without a college degree fared worse than their male and college-educated counterparts as the IT job market slowed down. We suggest that factors such as presence of job search friction, diversity in the educational system, geographical differences in cost of living, labor mobility, and shortages in IT labor supply vis-à-vis demand help explain the differences among countries. We conclude by outlining the implications of these findings for IT workers, firms, and policy makers.

How does competition impact firms’ incentive to innovate by investing in information technology (IT)? Prior literature suggests opposite predictions on the direction in which competition drives IT investment. This paper analyzes a game theoretic model of duopoly competition and shows that an important feature of IT sheds new light on firms’ investment decisions: IT implementation can fail. Without the possibility of implementation failure, the opportunity to invest in IT hurts firms’ profits because the productivity gains are competed away. Implementation failure creates a possibility of cost-based differentiation and mitigates competition, although these two effects can drive firms’ IT investment in opposite directions. Interestingly, a higher probability of implementation failure can lead to lower investment risks and higher expected profits. Firms in highly competitive markets are better able to recoup the returns to their IT investments and, therefore, more motivated to invest in risky IT than firms in less competitive markets. The online appendix is available at https://doi.org/10.1287/mnsc.2017.3005 . This paper was accepted by Chris Forman, information systems.

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Nonlinear usage-based pricing is applied extensively in software markets. Customers of software products usually cannot vary their required usage volume, a property we label local demand inelasticity. For instance, a client firm that needs a sales force automation software either buys one user license for every salesperson or does not buy at all. It is unlikely to buy licenses for some but not all salespersons. This demand feature violates a critical assumption of the standard nonlinear pricing literature that consumers are flexible with their usage volume, and their valuation changes smoothly with usage volume. Consequently, standard nonlinear pricing solutions are inapplicable to many software products. This paper studies the optimal nonlinear usage-based pricing of software when customers' demand is locally inelastic. This unique demand feature necessitates a new approach to solve the nonlinear pricing problem. We show that under a weak ordering condition of customer types, this complex pricing problem can be decomposed into a set of much simpler subproblems with known solutions. Our pricing solution is easily implementable and applicable to a broad range of demand systems, including those described by the families of exponential and normal distributions. Moreover, local demand inelasticity has a critical impact on key efficiency results.