Abstract
We study the effect of the US Affordable Care Act (ACA) on healthcare borrowing costs. The ACA provides insurance subsidies to low-income enrollees. States could accept funding to expand Medicaid, although many declined, citing the cost burden. The ACA significantly reduced healthcare yields after a favorable 2012 Supreme Court ruling. Furthermore, hospital investment spending increased, and investment-cash flow sensitivities decreased. The yield effect was double in Medicaid expansion states, and insignificant in rural areas of non-expansion states. Our results highlight how the municipal market can be used to evaluate the heterogeneous effects of public policy and guide a targeted policy approach. (C) 2021 Elsevier B.V. All rights reserved.
Abstract
How, and to what extent, consumer choices are influenced by the context in which the product is consumed remain important marketing questions. In this article, the authors develop a parsimonious context-dependent multidimensional unfolding model that can accommodate consumers' context-specific behaviors via ideal points in multiattribute space along with brand locations in that space while accounting for unobserved heterogeneity in consumer behavior. The authors provide an empirical illustration using panel data on beer brand choices in different contexts from U.S. beer consumers. They find more heterogeneity in behavior across social versus nonsocial contexts than across in-home and out-of-home consumption. The authors then show how the model can be used to derive a firm's optimal direction of brand repositioning given its competitive landscape in the various consumption contexts. Since consumer preferences can be correlated across contexts, they show that a movement toward the ideal point in one context does not necessarily improve the firm's market competitiveness in other contexts; thereby hurting the brand's overall performance.
Abstract
Many sellers allow consumers to pay with reward points instead of cash or credit card. While the revenue implications of cash purchases are transparent, the implication of reward sales is not trivial, when a firm that issues points is not a seller. In this case, a seller receives a compensation from the point issuer when a consumer purchases the good with points. We examine how reward sales influence a seller's pricing and inventory decisions. We consider a consumer who can choose to pay with cash or points based on reservation price, point balance, and the perceived value of a point. Then, we incorporate this into a pricing model where a seller earns revenues from both cash and reward sales. In contrast to an intuition that reward sales will increase sales and revenue, we show that the effect of reward sales on the seller's price is non-trivial as the seller could either add a premium or discount depending on the inventory level, time, and the reimbursement rate. Furthermore, such price adjustments can attenuate the optimal mark-up or mark-down level, and reduce the price fluctuation caused by inventory level and remaining time. We investigate settings where the seller has different operational controls over reward sales and find that allowing reward sales is still better even when the revenue from the reward sales is smaller than the cash sales. We also find that a seller with an ability to control availability (i.e., allow a reward sale or not) can achieve a revenue similar to the revenue of a seller with an ability to change point requirements and price.
Abstract
Despite a rising interest in artificial intelligence (AI) technology, research in services marketing has not evaluated its role in helping firms learn about customers' needs and increasing the adaptability of service employees. Therefore, the authors develop a conceptual framework and investigate whether and to what extent providing AI assistance to service employees improves service outcomes. The randomized controlled trial in the context of tutoring services shows that helping service employees (tutors) adapt to students' learning needs by providing AI-generated diagnoses significantly improves service outcomes measured by academic performance. However, the authors find that some tutors may not utilize AI assistance (i.e., AI aversion), and factors associated with unforeseen barriers to usage (i.e., technology overload) can moderate its impact on outcomes. Interestingly, tutors who significantly contribute to the firm's revenue relied heavily on AI assistance but unexpectedly benefited little from AI in improving service outcomes. Given the wide applicability of AI assistance in a variety of services marketing contexts, the authors suggest that firms should consider the potential difficulties employees face in using the technology rather than encourage them to use it as it is.
Abstract
This study explores how firms decide in which businesses to further invest and from which businesses to withdraw resources by examining the detailed product portfolios of firms in the global semiconductor industry. Results show that resource redeployment within incumbent businesses is more prevalent than via new entry or complete exit, since the former is more flexible and easily reversible than the latter. This study further finds that, while underutilized resources may drive resource redeployment, resource shortage by a newly entered or expanding incumbent business may also siphon resources away from other incumbent businesses, leading to their exit or temporary retrenchment. Fabless firms with resource that are more fungible, scalable, and decomposable vis-a-vis integrated device manufacturers show a more flexible and gradual pattern of resource redeployment. Managerial summary In fast-moving environments, firms should quickly redeploy resources to more promising business areas. We find fabless firms with more fungible, scale free, and decomposable resources engage in more active resource redeployment than integrated device manufacturers with specialized fabs and equipment, like Intel or Samsung. Redeployment among the latter requires a well-planned, synchronized approach so as to avoid idle resources. As such, in order to take advantage of dynamic resource redeployment, managers should begin by assessing the characteristics of firm resources along these dimensions. Managers may also consider business model transformation to separate their activities by specializing in areas in which they can best utilize their resources and capabilities, like fabless firms and foundries in the semiconductor industry.