With the emergence of the internet as a new business channel and its impact on the overall role of today¿s customers, existing models for the measurement of perceived quality, satisfaction and loyalty are worth revisiting. This is specifically important in light of the prominent progress of some of the new business concepts, particularly customer experience management, and the rising emphasis on customers¿ hedonic and emotional needs. This study attempts to bridge the gap in existing literature by examining the online customer experience in its entirety, attending within the study to both the utilitarian and hedonic needs of online customers and giving special attention to emerging aspects in the online environment, such as customer engagement in self-driven experiences. Therefore, the study includes a comprehensive review of a large body of knowledge, both in consumer behaviour and marketing literature as well as quality management literature, in addition to a scrutiny of 50 studies for different evaluation models in the online environment. This is in order to identify a list of attributes and factors that impact customer evaluations of online experiences. Upon the synthesis of the list of attributes and factors that impact customer evaluations of online experiences, an online blog was created as an environment for asynchronous focus groups. The online blog was beneficial in creating a deeper understanding of what online customers want and what impacts their experiences. Following, an online questionnaire was administered in two stages, once for measure purification purposes which received 90 pilot responses and once for mass data collection purposes which received 366 responses. As a result of this study, an integrated model for the measurement of online customer experience that emphasises the significance of the emotional component was proposed. The model consists of three components, each serve a specific measurement purpose. The XQual construct which consists of 7 attributes and 30 factors, is a performance measure of the experience in relation to specific aspects that address customers¿ utilitarian and hedonic needs. The satisfaction continuum consists of four factors and is an output measure for each experience or transaction with the online firm. The loyalty continuum consists of four factors and is an outcome measure that indicates customers¿ attitudinal commitment towards the online firm.

Existing literature about digitalization and business transformation in the manufacturing industry has mainly focused on understanding the supplier´s internal transformation of processes, the development of key capabilities, the relationship between suppliers and customers to co-create value and the transformation from product providers to service providers. The digitalization in essence is a new topic within this industry, then there is scant regard for how digitalization has transformed the perception of value from customers’ perspective in the energy industry. The understanding of value perception from customers perspective is relevant due to the growth and development of servitization as well as challenges regarding slow adoption of digital solutions in this industry.

The purpose of this dissertation was to understand and compare the effect of training non-native English Speaking (NNES) learners (N = 480) in two distinct learning environments, (i) traditional face-to-face and (ii) online synchronous hybrid learning (SHL). In the traditional training mode, NNES learners (n = 360) were trained by NNES voice and accent (VANC) trainers in a physical, face-to-face setting. In the second, CAPT+SHL training mode, the NNES learners were trained by NNES VANC trainers with the help of a native-English computer-assisted pronunciation training (CAPT) tool in an online SHL environment. Factor analysis, higher-order factor analysis, hierarchical cluster analysis, and multidimensional scaling yielded a reliable scale, Eddie's Voice Test (EVT). Multiple regression yielded a predictive model between NNES pronunciation and their performance. In addition, the CAPT+SHL training mode produced higher scores on pronunciation and performance than the traditional training mode, suggesting a combination of NES and NNES VANC instructors are more effective in training NNES learners than NNES instructors by themselves. The case study (n = 3) on VANC trainers' perception of CAPT and SHL yielded three themes: (1) challenges with synchronous hybrid learning (sub-themes include physical challenges, social challenges, and cognitive challenges); (2) computer-assisted pronunciation training (CAPT) impact on non-native-English-speaking (NNES) learner pronunciation (sub-themes include self-paced pronunciation learning and pronunciation benchmarking; and (3). SHL as an equitable learning environment.

The advancement of artificial intelligence and its diverse applications have attracted great interests from several research scholars examining communication between humans and chatbots. Many have explained the motivations of chatbot use, however, less emphasis has been given to myriad customer experiential needs for the interaction with this AI-powered technology. Therefore, in the light of U&G theory, this thesis presents a conceptual framework for customer experience as the needs for chatbot use. SOR model was also adopted to establish the links among customer experience as organisms (utilitarian – perceived informativeness and credibility; hedonic – perceived transparency, enjoyment and engagement; anthropomorphism – mindful and mindless anthropomorphism; and social presence), their primary stimuli (functionality, communication style similarity and aesthetics) and responses (customer satisfaction and reuse intention). 417 convenient samples were collected from the UK where chatbots are widely used. Results from SEM revealed that perceived credibility, informativeness, enjoyment, functionality and communication style similarity hold the keys for customer satisfaction, while effects of anthropomorphism and social presence are not significant in this research setting. This study has enriched U&G theory by addressing customer experience as ones’ motivations to use chatbots. Also, it has presented a fresh understanding of customer experience in chatbot context by considering utilitarian, hedonic, anthropomorphism and social presence as dimensions of customer experience rather than merely measuring how customers think, feel, sense, act and relate. In addition, practical implications and direction for future research are discussed.

It is estimated that there are approximately 42,000 beverage establishments in the U.S. whose annual revenue surpasses $20 billion (First Research, 2014). To facilitate discussion of beverage establishments, it is essential to recognize beverage establishments as businesses whose majority of sales come from alcoholic drinks (Moss, 2010a). In this research, beverage establishments are divided into beverage-only bars, bar/entertainment combinations, and food and beverage combinations. Even though they are a well-established industry, beverage establishments have received little academic attention (Moss, 2010b). For example, previous studies have given little attention to the development of the model that examines the relationships between quality attributes, convenience, perceived price fairness, customer experience, and customer loyalty in beverage establishments. However, current research in other service sectors has showed that quality, pricing and convenience have a strong effect on customer experience and behavioral intentions (Baker & Crompton, 2000; Cronin et al., 2000; Taylor & Baker, 1994; Tian-Cole, Crompton, & Willson, 2002; Woodside et al., 1989). Quality is tightly related to customer experience since it positively affects customer satisfaction and therefore company's profitability (Hallowell, 1996). This study has the following objectives: (1) to develop an instrument to measure the antecedents of customer experience in beverage establishments; (2) to examine the relative importance of different antecedents of customer experience in different types of beverage establishments; and (3) to build a model of various antecedents of customer experience in beverage establishments. This study was conducted in six phases. The first phase was the analysis of previous literature regarding quality attributes, convenience, perceived price fairness, customer experience, customer loyalty, and beverage establishments. The second phase was a development of mixed methodology research design. The third phase was the data collection based on interviews with management of beverage establishments, customer focus groups, and a survey of customers of beverage establishments. The fourth phase was a pilot study that involved a refinement of the study instrument. The fifth phase was a main quantitative study based on the survey design. The results from each qualitative and quantitative phase of the study were integrated and analyzed. The results from the instrument development part of the study identified the following eleven antecedents of customer experience in beverage establishments: (1) service quality, (2) product quality, (3) physical environment design, (4) physical environment layout, (5) music quality, (6) social environment, (7) information convenience, (8) location convenience, (9) parking convenience, (10) entrance fee fairness, and (11) perceived price fairness. Additionally, the second instrument development study was used to recognize different customer experiential state dimensions. The factor structure included two customer experiential states: (1) the affective experiential state and (2) the cognitive experiential state. A comprehensive theoretical model that integrates different dimensions of antecedents of customer experience, customer experiential states, customer loyalty and the moderating affect of the type of the beverage establishment was developed. One of the most important findings of the study is the relationship between the social environment and the affective experiential state. The results of the study indicate that the majority of other antecedents of customer experience did not have a significant effect on two experiential states or that effect was relatively weak. However, social environment was the strongest predictor of customers' positive emotions and therefore customer loyalty and behavioral intentions. Finally, the study results confirmed Oliver's (1997) theory of customer loyalty by providing support for the sequential relationship between cognitive, affective, and conative loyalty. This study has several important theoretical contributions. Different antecedents of customer experience in beverage establishments were recognized and an instrument that measures these dimensions was developed. To the best of our knowledge, this is the first scale specifically developed to measure experience in beverage establishments. Additionally, the importance of each of the antecedent of customer experience was examined in regards to their effect on customer experience. Additionally, an instrument that measures cognitive and affective experiential states was developed and was a foundation for the study model. Finally, this study integrates different customer experience and customer loyalty dimensions into a comprehensive theoretical model that could be applied and retested in other service settings.

Background: The concept of the chatbot has been around for nearly 60 years. However, service providers have recently increased the integration of chatbots in distinct industries due to the growth in digitalization and advanced technology. Not only that, chatbots can support service providers in becoming more efficient and reducing overhead costs. As a result, this transformation in service offering has influenced customers in various forms. Thus, this study explores Generation Z's perceptions and experiences using chatbots, with a focus on the influence these systems have on their trust. There is little information about this topic, and this study should aid organizations in learning how to better meet customer expectations, which could lead to more promising customer satisfaction in the future. Purpose: The purpose of this study is to investigate customer perceptions and trust in chatbots which is a form of advanced technology in a customer service setting. The aim is to gather empirical evidence from customers' social reality to answer the research question of this investigation. Method: This research conducted an exploratory qualitative study with an inductive research approach. Semi-structured interviews were conducted with 15 respondents from Generation Z, located in Sweden, Norway, the Netherlands, and Germany to achieve a broad perspective regarding their experiences with chatbots. The respondents were selected using the snowball and networking sampling method. The research paradigm of this study is interpretivism, which supports the examination in exploring and gaining knowledge about this phenomenon. Conclusion: The aim of this study was achieved, and the gathered empirical evidence presents further knowledge regarding customers' experiences with chatbots. This study and other relevant examinations prove that the increase of digitalization in customer service settings has an influence on customer experience. Primarily, the empirical findings indicate that there is an overall lack of trust in advanced technology due to the issue of privacy. Although Generation Z has grown up alongside the worldwide digital transformation, they remain cynical and distrustful of the future of technology. Thus, it occurs that there is a lack of customer trust in chatbots. However, this is confirmed by the fact that customers are sharing low pre-expectations towards chatbots. As a result, customers experience a more dissatisfied feeling towards the service provider. On the other hand, the empirical findings reveal that customers' loyalty remains unaltered towards businesses.

Research question: How do AI solutions influence digital customer experiences in Swedish retail companies? Purpose: This study explores how AI technologies affect customer experiences in    Swedish retail by interviewing customers about their perceptions and interactions. The goal is to better understand these experiences and improve how AI is integrated into retail customer relationship management.  Method: This study used qualitative research to explore how AI affects digital customer experiences in Swedish retail. By conducting semi-structured interviews and analyzing podcasts, it gathers detailed insights into customer perceptions and industry trends. With a goal to gain a thorough understanding of AI's role in improving digital retail experiences. Conclusion: AI solutions impact digital customer experiences in Swedish retail in various ways. They improve convenience and personalization but also create concerns about impersonality and data privacy. To get the most out of AI and build customer trust, it is important to balance technological effectiveness with a human-centric approach.

Yes / The growing popularity of robot-related research contexts in hospitality and tourism calls for in-depth analysis of how different product/service designs strategies integrating robots may influence customers’ experiences. Employing a scenario-based 2×2×2 experimental research design, this study assesses service robots applied at three different product/service levels (i.e., core, facilitating, and augmented). From surveying 378 customers of mid-priced casual restaurants and 312 tourists of a mid-priced theme park restaurant, findings of the study suggest that using robots at all three product/service levels lead to a more positive educational experience but not entertainment experience. The study further extends the literature by positioning dining at a robotic restaurant as an important occasion to showcase the latest technologies to customers. By providing memorable entertainment and educational experiences, customers’ technology readiness could be enhanced, making them more willing to try new technologies. Such a focus brings in unique contributions both in literature and practice.

Background: With continuous developments of AI and digitalisation, the fashion industry has transformed remarkably. In Sweden, as a large fashion export, these technological developments have reshaped various aspects of the industry. The digital shift has also contributed to the customer journey’s complexity. The significance of using AI and understanding the customer journey, both has a growing relevance as they are experiencing changes. However, there is limited research on AI’s influence on the customer journey among fashion retailers. Hence, this study highlights the research gap in how fashion retailers can leverage AI technologies in this context.  Purpose: The purpose of this research is to explore how retailers in the Swedish fashion industry can leverage AI to influence the customer journey, from a managerial perspective. Furthermore, to explore Swedish fashion retailers’ perceptions of future possibilities for AI and its influence on the customer journey.        Method: This study is based on a qualitative method with an inductive approach, by combining literature review with six semi-structured interviews of Swedish fashion retailers. It adopts an interpretivist paradigm to ensure quality and depth of the collected data.  Conclusion: The results show that AI is primarily used online and in the prepurchase stage of the customer journey. Implementation of AI tools vary between fashion retailers in Sweden, including tools like targeted advertising. The research presents that fashion retailers have mainly implemented AI tools internally and not directly towards customers. The results highlight factors, like the maturity level of AI, as important for current and future implementations of AI as a fashion retailer. Moreover, Swedish fashion retailers recognise AI’s potential for future implementations to influence the customer journey, especially regarding personalisation and customisation.

The advent of the digital era has profoundly transformed marketing and variousorganizational functions, largely driven by the accessibility to vast repositories ofdigitized data and the integration of artificial intelligence (AI). The purpose of this studyis to examine the impact of artificial intelligence-driven personalization on customerexperience within the context of TikTok, a leading social media platform known for itsinnovative use of AI technology. TikTok leverages AI to analyze user behaviors andpreferences, delivering tailored content that enhances user engagement and satisfaction.The deductive approach is the selected approach to fulfill this study is objective.Particularly, the research hypothesis (H1) posits that AI-driven personalization positivelyinfluences customer experience on TikTok. To test this hypothesis, we conducted aquantitative study involving structured questionnaires distributed to a diverse sample ofTikTok users via social media platforms, resulting in 365 usable answers. The findingsconfirm a significant positive relationship between AI-driven personalization andcustomer experience, underscoring the critical role of AI in shaping user interactions andexperiences on social media platforms - TikTok. This study contributes to the literatureon digital marketing and customer experience management by highlighting theeffectiveness of AI-driven personalization in fostering engagement and satisfaction.