Yuliya Kolomoyets

The preamble and the three studies of the dissertation are designed to answer two research questions. First, "What is the anatomy of service experience value from customer and provider perspectives?, followed by "How do contextual factors influence the service providers' capacity to recover value when services fail?" The preamble introduces the concept of value, outlining its evolution, emphasizing the critical disparities among the dominant research perspectives, and justifying the urgency of the present research. The dissertation adopts the Grönroos-Voima value model to tap into value co-creation processes across three spheres: customers, service providers, and joint sphere. This is done by uncovering the structure of the customer value-in-use perceptions (Study 1), evaluating service providers' value proposition against those perceptions (Study 2), and assessing the impact of service recovery actions on customers forgiveness and service expectations in the context of varying prior service experiences and harm direction (Study 3). The dissertation identified the fifteen key attributes describing the value of the hotel experiences and uncovered the critical discrepancies between the value perceptions and value proposition narratives. It also determined the varying effect of prior service recovery experience and service recovery actions on forgiveness on victims and observers of service transgressions. Each study outlined the limitations of the empirical research along with the theoretical and managerial implications of the findings.

This experimental study examined how service recovery strategies (apology, apology with compensation, apology with excuse) affect forgiveness among victims and observers of service failure and recovery experiences in the hotel context. The results of surveying 471 respondents revealed the disproportional effect of recovery strategies on emotional and decisional forgiveness among victims and observers. Apology and compensation were the most compelling strategies for both groups, with the effect stronger for observers. Only for the latter recovery, specifically, apology and excuse led to emotional forgiveness. The study confirms the spillover effect of both tangible and psychological recovery strategies on customers indirectly involved with service failure and recovery experiences. Moreover, given the capacity of the psychological recoveries, such as an apology and excuse to facilitate emotional forgiveness among observers, service providers should pay special attention to the training of the frontline staff and create a welcoming and friendly climate throughout the customer journey.

Online reviews are an important source of consumer opinions about the service experiences across industries. Growing number of research investigate the potential of online reviews to explain consumer behaviour and to predict business performance, while only few engage into the examination of the textual content of the reviews. Large volume and unstructured format of the textual data make it unamenable to analysis with traditional methods like survey. To fill the emerging gap, this study will rely on automated text mining methodology to explore how consumers reflect on the perceived service quality in the online reviews. Specifically, sentiment analysis, text classification and regression modelling will be applied to investigate the dimensions of perceived service quality together with their contribution to the overall rating of service experience (e.g. star rating). The results are expected to extend the understanding of perceived service quality; to illustrate the value of the automated text mining methods for maximising the usefulness of online reviews and helping businesses reach their strategic goals.

It is well established in marketing literature that aligning value creation with customers' aspirations promotes satisfaction, repurchasing, and competitiveness. This study employs structural topic modeling and sentiment analyses on online documents to provide an empirical account of value alignment from customers' and service providers' perspectives. This generates insights into i) the attributes valued by customers and service providers, respectively, ii) the valence of those attributes, iii) the sources of value formation, iv) the value alignment between customers and service providers, and v) the relative importance of value attributes for budget and upscale hotels. The results indicate that guests focus on interaction, cleanliness, and comfort, while service providers most frequently discuss service-related aspects; however, the first two attributes also affect hotel ratings. Furthermore, the sources of value differ in terms of valence. These insights show that structural topic modeling is a scalable approach to understanding value from both perspectives.

Online reviews have been studied for their potential to explain consumer behaviour and to predict business performance. However, large volume and unstructured format of the textual part of the reviews make them unamenable to analysis with traditional methods like survey. By employing the automated text mining methodology this study explores how consumers reflect on the perceived service quality in the online reviews. Specifically, sentiment analysis, text classification and predictive modelling will be applied to investigate the dimensions of perceived service quality together with their contribution to the overall rating of service experience. The results are expected to extend the understanding of perceived service quality; to illustrate the value of the automated text mining methods for maximising the usefulness of online reviews and helping businesses reach their strategic goals.