The service failure phenomenon is a long-recognized problem in hospitality industry’s marketing, and has consequently attracted significant research attention (Chan, Wan, & Sin, 2007). Once service failures occur, customers usually assess the causes of the problem. Researchers have thus studied the impact of service failures on customer failure attribution and their behavioral outcomes toward the service provider. Usually, studies examine consumer psychological processes when only one service firm is involved. However, it is unclear whether customer failure assessments are the same when they have to assess more than one service at the same time. According to a review article by Cohen, Prayag, and Moital (2014), consumer behavior has been extensively examined in the field of tourism in many aspects (e.g., decision making, motivations, satisfaction, and loyalty); however, research assessing failure attribution within tourist satisfaction literature is still rare. Moreover, in service marketing studies, it is somewhat surprising that existing service research has overlooked the fact that customers may confront failure situations where there are two or more service providers involved (Weber & Sparks, 2010). Hence, this study makes two key contributions. First, it addresses scholars’ calls for more research assessing failure attribution within a tourist satisfaction context. Second, it contributes to our understanding of consumer behavior in tourism industry by studying customer perceptions of service failures within service networks, where at least two firms are involved in the incident. This study uses in-depth interviews for data collection. And interview results indicate that relational and network characteristics have a significant influence on how customers attribute service failures to different service providers.

During the last decade, customer complaint management received considerable attention in marketing literature, e.g., researchers examined the consequences of a negative incident on customer attitudes towards the provider and the associated behavioral intention such as self-reported repurchase intentions ( e.g. Evanschitzky, Brock, and Blut, 2011; Smith and Bolton, 2002; van Doorn and Verhoef, 2008). However, this stream of research has not examined actual purchase behavior after the complaint (e.g., de Matos, Henrique, and Rossi, 2007). Hence, it is unclear whether service recovery only affects self-reported outcomes (i.e., purchase intention) or actual purchase behavior. Moreover, recent research has indicated that customer inertia explains a large proportion of the variance of a customer’s repurchase behavior (e.g. van Doorn and Verhoef, 2008). So far, no research has assessed the impact of inertia in the service recovery context. It is indicated that the relationship between the provider and the customer is strongly affected by the service failure (van Doorn and Verhoef, 2008), but as of now, the role of past behavior has not been investigated. This study contributes to the complaint management literature by (1) analyzing the effects of service recovery on actual purchase behavior after recovery and (2) by assessing the role of inertia in situations of service recovery. Results indicate that complaint satisfaction has a significant positive impact on post complaining purchase behavior while overall satisfaction has no such effect. Furthermore, past purchase behavior has the strongest impact; thus, inertia plays a substantial role in complaint management.

Marketing and information systems research has a long history of studying the customer’s acceptance and adoption process of new technologies (Venkatesh et al., 2003). These studies are often motivated by the potential of new technologies such as smart home systems to improve our everyday life. To benefit from these technologies, individuals have to accept them in the first place. To better understand the acceptance process, scholars regularly employ various theories in their studies such as technology acceptance model (Davis, 1989), innovation diffusion theory (Rogers 2003), and perceived risk theory (Featherman and Pavlou, 2003). Although each of these theories provides valuable insights, only recently scholars started combining them in larger framework and examining their interrelationships. These studies argue that each theory has the potential to make a unique contribution to understanding of technology acceptance, but the combination of theories leads to novel insights. The purpose of this study is the development of a comprehensive adoption model combining constructs from various theories and testing these theories against each other to provide new insights. The study develops this model in a smart home applications context which is a complex technological system. The study is based on an online survey consisting of 409 participants; the data is analyzed using structural equation modelling.

Worldwide, more than 1/3 of all e-commerce transactions in business-to-consumer industries are nowadays executed via mobile devices (Criteo, 2015). Despite its increasing importance, it can be noted that mobile commerce does not seem to “take-off” equally across diverse goods and services contexts. We observe, for instance, that mobile commerce is quite common in service industries for purchasing tickets (e.g., for flights, public transportation, and sport events), while it is less common for services such as financial products. Balasubramanian et al. (2002) addressed this issue and proposed that contexts of m-commerce differ from each other with regard to several characteristics. For example, they propose that location sensitivity (among other characteristics) differs for various m-commerce applications, and that this characteristic may impact acceptance of m-commerce across industries. It may be that acceptance of m-commerce is higher in some industries since use of location sensitive data is appreciated by customers, while it is not valued in other purchasing contexts. Against this background, we propose that examining (1) risk perception related to mobile commerce and (2) different types of mobile commerce applications are essential for gaining a deeper understanding of the phenomenon of differing relevance of m-commerce across industries. In particular, our study acknowledges the differential roles of the financial, performance, and security facets of risk. In addition, we assume that the role of value and risk dimensions differs subject to three mobile commerce application characteristics which are location sensitivity, time criticality, and extent of control. Based on a dataset of 800 respondents, results of our models demonstrate that especially security risk can act as a critical inhibitor of acceptance. The extent to which performance risk and financial risk impact perceived usefulness was found to be moderated by the three contextual characteristics. From a managerial perspective, results show which factors should deliberately be considered in the development of m-commerce applications, and in which different application contexts they matter.

Customer integration has received considerable attention in the service literature in order to foster service innovations (e.g. Vargo & Lusch, 2004; Chan, Yim & Lam 2010; Yim, Chan & Lam, 2012; Grönroos & Voima, 2013). The changing role of the customer from being a passive consumer to becoming an active contributor during service provision and co-creator has a significant impact on numerous service firms. Customer integration is essential to many services and successful integration improves service experience of the customer and it allows development of new services in particular (Magnusson, Matthing & Kristensson, 2003; Melton & Hartline, 2010). Against this background, service industries nowadays face the challenge of dealing with new customer and employee roles in times of digitalization, increasing customer activity, changing interaction channels, and development of new business model. While the impact of employee’s customer stewardship on the employee-customer relationship has been investigated in prior studies, is unclear whether an employee’s commitment to the customer also motivates the employee to contribute to service innovation development.We propose that an employee’s level of customer stewardship represents an important requirement for organizational learning about understanding customer needs and to uncover future trends. Based on stewardship and agency theory, we develop a conceptual model proposing that idea generation, articulation, and implementation depend on employee-related factors (e.g., employee stewardship), structural factors (e.g., incentive system), and control-related factors (e.g., monitoring system). Hypotheses are tested using survey data from 390 frontline employees in financial services. Results underline the important roles of employee stewardship and organizational commitment. Insights provide managers guidance how to improve motivation of frontline employees to engage in these important behaviors.

Although the relationship marketing literature acknowledges the importance of switching costs for increasing customer retention in general, little is known about its relevance in industrial markets. In particular, it is unclear whether switching costs and its dimensions impact relevant behavioral outcomes of buyer-seller relationships in business-to-business (B2B) markets. Against this background, our research intends to make two main contributions: Since we assume differential effects for different types of switching costs, our research first explores the dimensions of switching costs for the B2B domain. Second, it tests the relative impact of the dimensions of switching costs on business customers’ actual purchase behavior. Results suggest that switching costs in B2B settings are a multi-faceted construct, including (i) procedural, (ii) financial, and (iii) relational switching costs. Moreover, we find relational switching costs to be most important for securing B2B buyer-seller relationships since they impact a customer’s (a) share-of-wallet, (b) cross buying behavior, and (c) actual switching behavior. While procedural switching costs only influence share-of-wallet, financial switching costs solely impact customer’s cross-buying behavior across a firm’s product and services categories. These findings contribute to a better understanding about how to secure B2B buyer-seller relationships.

Research on new product development has emphasized the importance of integrating customers, employees, and suppliers in an organization’s innovation processes. While several studies evaluate respective participatory processes, there is, surprisingly, no consensus on which dimension participation quality consists of, and how to measure them consistently. The present study contributes to the literature by identifying the dimensions of participation quality and by constructing a participation quality scale that includes six dimensions, namely (1) project-related resources, (2) early involvement, (3) degree of influence, (4) transparency of processes, (5) incentive mechanisms, and (6) voluntariness of participation. Furthermore, a 24-item measure of participation quality is developed using a mixed-method design. Results of our study show that the developed measure impacts important innovation-related outcomes such as innovation performance, acceptance of the innovation, and intention to participate in future innovation projects. Given that the six identified dimensions of participation quality differentially affect these outcomes, the scale provides the opportunity to better design participatory innovation projects, and thus helps managers to integrate stakeholders more successfully in these projects.