| dc.description.abstract | The core research objective in this thesis is to address the ways in which Customer Experience (CX) emerges through the combinational effects of multiple customer interactions at touchpoints and their resulting CX responses. The empirical study designed in this work is positioned to build upon existing literature within the Service Management field. According to extant work, CX can be viewed from both the provider’s perspective (e.g. ‘intended’ or designed), and the customer’s perspective (e.g. ‘realised’ or subjective). The thesis integrates both accounts through the presentation of a new conceptual model which forms the basis for the design of the empirical study.
Several limitations are addressed in this work. First, building on the notion that CX emerges across multiple touchpoint interactions (Lemon and Verhoef, 2016) the study explores the impact multiple interaction types, and their associated responses, have on overall CX. Extant studies have tended to view CX at single touchpoint interactions (Becker and Jaakkola, 2020). CX emerges across multiple touchpoint interactions, which each induce responses in the customer. As it stands, little is known about how this process occurs, or the relationships which exist between customer interaction, customer response, and overall CX. Second, the study widens the field and its understanding of the servicescape from an ‘unbounded’ perspective (Rosenbaum and Massiah, 2011). Traditionally, studies have explored CX through the impact of provider-owned touchpoints, predominantly within bounded service sites. The study addresses requests to explore the impact of wider, non-provider-controlled touchpoints on overall CX (Kandampully et al., 2018). Relating to this aim, very little existing work deals with the impact of natural servicescape touchpoints on CX. The case studies in this work have been chosen for their suitability to address this gap.
The study employs a comparative case study approach from the cultural heritage sector. Text mining (TM) and text analytics (TA) techniques are employed to capture and assess CX elements found within customer feedback data from an online review depository. Contrary to existing work in this field, the study employs a three-step annotation process to concept classification which can ensure rigour in the results. The purpose of the analysis process is to capture patterns of CX responses and customer interactions within the data and assess their relationship to overall CX ratings. Both quantitative measures (e.g. statistical analysis) and qualitative measures (e.g. verbatim text analysis) are used to explore a number of key questions relating to the core research objective.
The empirical study performed in this work results in several key findings. The study finds that CX arises as a combination of customer interactions and CX responses, with each pattern impacting the overall experience in different ways. Results suggest that pattern prevalence and prominence are not core drivers of customer rating, but rather that significance measures need to be employed. From a customer perspective, negative CX responses have a stronger effect on overall CX rating than positive responses. These can be induced through touchpoint interactions beyond the control of the provider. The emotional content of the experience is key, with customer surprise, anger, and sadness significantly impacting CX to a greater degree than other discrete emotions. The findings suggest that customer expectations play an important role in the delivery of CX. Customer expectations can be used to make sense of the differences in terms of patterns and the statistical significance of their relationship to CX rating. Several potential avenues for future work to further develop these themes are put forward in the final stages of the thesis. | en_GB |
