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During the past two decades, service guarantees have received increased attention as a means for service firms to attract and retain customers and gain a competitive edge in the marketplace. Although many academic studies, referring to diverse service guarantee aspects, have appeared during this time, a synthesis of research is needed to clarify what researchers have learned about service guarantees and what remains unknown. To evaluate the state of published research on service guarantees, 109 articles published from 1985 to 2008 are collected and analyzed. The resultant review reveals a significant change in the type of research being performed, including a shift toward greater interest in the impact of service guarantees on consumer behavior and service firms. However, a significant shortfall marks empirical work directed toward the internal and operational effects of service guarantees. The effects of service guarantees on service performance, service recovery, and return on service guarantee investments are topics in need of further research.

This article develops a decision model which enables service firms to optimize their productivity. Companies must efficiently determine the necessary resource input to increase service productivity to meet customer demand. In so doing, managers face service-specific challenges: They must select the appropriate type and quantity of limited resources to deliver services efficiently, consider the volatility of demand to provide services effectively, and integrate the interaction effects of resources in terms of substitution to utilize constraint resources optimally. In addressing these challenges, we develop an interdisciplinary approach by combining insights from service research and operations research to create a decision model that helps managers select the optimal type and quantity of resources available to overcome the abovementioned challenges. We validate our model in several case studies and further generalize our findings by applying it to different data settings. Ultimately, we prove that productivity can be increased significantly if firms optimize resource selection by considering stochastic demand, the effects of substitution among resources, and resource constraints.

Over the past 25 years, the service–profit chain (SPC) has become a prominent guidepost for service managers and researchers. In this article, we reflect on and synthesize published research to clarify what researchers have learned about the SPC and what remains less well understood. Based on an in-depth discussion of the field, we present a revised SPC and propose multiple areas in which further research would be worthwhile, such as internal service quality as specific systems of human resource management practices, both employee and customer well-being as additional mediators, different targets of employee and customer loyalty, contingencies, and non-linear and feedback effects. We conclude by reimagining the SPC, and we discuss digital and artificial-intelligence–driven changes to the SPC's structure. Finally, based on the insights we discuss, we inform scholars of the current state of SPC research and provide a detailed agenda for future research.

Increasingly, customers use social media to voice complaints, making those comments visible to a wide range of uninvolved, virtually present others (VPOs). Many companies seek to shift their complaint-handling efforts away from public online platforms and toward private interactions. However, this approach might not be optimal due to the importance of transparency in social media recovery and its impact on VPOs. Using multiple experiments and building on signaling theory, vicarious learning, and trust repair mechanisms, this study reveals that service recovery transparency acts as an important signal of quality, eliciting trust, and improving VPOs' word-of-mouth (WOM) and purchase intentions. However, service recovery transparency forms a signal of poor quality when the service recovery is unsuccessful, resulting in negative implications for VPOs' WOM and purchase intentions. Conditional transparency provides transparency about selected aspects of the service recovery (i.e., the process or result), enabling companies to exploit the positive aspects of transparency and evoke more favorable VPO intentions than would arise with complete opaqueness. Such efforts are necessary because even high brand equity firms suffer when failing to provide recovery transparency.

Service guarantees are an important feature of many service offerings because consumers recognize greater risk associated with the purchase of services than with the purchase of goods. Despite substantial service guarantee research in the past two decades though, no extant study has examined the return on service guarantee investments. To fill this gap, the authors examine the effect of a service guarantee on a firm's market value by identifying new service guarantee announcements, then using these announcements as events in an event study. The results show that simply offering a service guarantee does not result in greater market value, as measured by a change in stock market returns, for the offering firm. Instead, the market value of a service guarantee depends on its scope and the process required to invoke the guarantee. In particular, service guarantees that are specific in scope or automatically invoked lead to significantly greater market value than unconditional or customer-invoked guarantees, respectively. In addition, these differences are moderated by firm size. From a theoretical point of view, this study extends signaling theory to explain the differential effects of service guarantees, depending on their design.

The coronavirus outbreak has led to abrupt changes in people's daily lives as many state governments have restricted individuals' movements in order to slow the spread of the virus. We conducted a natural experiment in the United States of America in April 2020, in which we compare responses from states with "stay-at-home orders" (3 states) and no such orders (6 states). We surveyed 458 participants (55.6% female, age range 25–64, M(age) = 36.5) and examined the effects of these government-imposed restrictions on social, mental, physical, and financial well-being as well as the mediating role of resilience. Structural equation modeling reveals that resilience buffers stay-at-home orders' potential side-effects on well-being. Specifically, individuals living in states with stay-at-home orders report lower functional well-being than individuals living in states without such orders, which negatively relates to resilience. Resilience in turn is associated with higher social, mental, physical, and financial well-being. Thus, resilience can be seen as an effective means of buffering stay-at-home orders' potential negative effects on the components of well-being. Our results indicate the central role of resilience, which is crucial in dampening the effects of stay-at-home orders on well-being. Following our results, governments and policymakers should focus their efforts on strengthening individuals' resilience, which is a key predictor of social, mental, financial, and physical well-being.

The coronavirus outbreak has led to abrupt changes in people's daily lives as many state governments have restricted individuals' movements in order to slow the spread of the virus. We conducted a natural experiment in the United States of America in April 2020, in which we compare responses from states with "stay-at-home orders" (3 states) and no such orders (6 states). We surveyed 458 participants (55.6% female, age range 25-64, M-age = 36.5) and examined the effects of these government-imposed restrictions on social, mental, physical, and financial well-being as well as the mediating role of resilience. Structural equation modeling reveals that resilience buffers stay-at-home orders' potential side-effects on well-being. Specifically, individuals living in states with stay-at-home orders report lower functional well-being than individuals living in states without such orders, which negatively relates to resilience. Resilience in turn is associated with higher social, mental, physical, and financial well-being. Thus, resilience can be seen as an effective means of buffering stay-at-home orders' potential negative effects on the components of well-being. Our results indicate the central role of resilience, which is crucial in dampening the effects of stay-at-home orders on well-being. Following our results, governments and policymakers should focus their efforts on strengthening individuals' resilience, which is a key predictor of social, mental, financial, and physical well-being.

In many business markets, manufacturers seek service-led growth to secure their existing positions and continue to grow in increasingly competitive environments. Using longitudinal data from 513 German mechanical engineering companies and latent growth curve modeling, this study offers a fine-grained view of the financial performance implications of industrial service strategies. By disentangling the revenue and profit implications of industrial service strategies, findings reveal that such strategies increase both the level and the growth of manufacturing firms' revenue streams. In contrast, they reduce the level but improve the growth of manufacturers' profits. Results further suggest that services supporting the clients' actions (SSC) and services supporting the supplier's product (SSP) affect performance outcomes in different ways. SSCs directly affect revenue and profit streams. In turn, SSPs display only indirect effects on financial performance mediated through SSCs. A moderator analysis identifies two organizational contingencies that facilitate service business success: Only companies with decentralized decision-making processes and a high share of loyal customers can expect favorable financial results from industrial service strategies. In summary, this research provides significant insights and managerial guidance for turning service strategies into financial successes.