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The purpose of this paper is to explore innovations in customer experience at the intersection of the digital, physical and social realms. It explicitly considers experiences involving new technology-enabled services, such as digital twins and automated social presence (i.e. virtual assistants and service robots).

Future customer experiences are conceptualized within a three-dimensional space – low to high digital density, low to high physical complexity and low to high social presence – yielding eight octants.

The conceptual framework identifies eight “dualities,” or specific challenges connected with integrating digital, physical and social realms that challenge organizations to create superior customer experiences in both business-to-business and business-to-consumer markets. The eight dualities are opposing strategic options that organizations must reconcile when co-creating customer experiences under different conditions.

A review of theory demonstrates that little research has been conducted at the intersection of the digital, physical and social realms. Most studies focus on one realm, with occasional reference to another. This paper suggests an agenda for future research and gives examples of fruitful ways to study connections among the three realms rather than in a single realm.

This paper provides guidance for managers in designing and managing customer experiences that the authors believe will need to be addressed by the year 2050.

This paper discusses important societal issues, such as individual and societal needs for privacy, security and transparency. It sets out potential avenues for service innovation in these areas.

The conceptual framework integrates knowledge about customer experiences in digital, physical and social realms in a new way, with insights for future service research, managers and public policy makers.

The purpose of this paper is to offer a step-by-step text mining analysis roadmap (TMAR) for service researchers. The paper provides guidance on how to choose between alternative tools, using illustrative examples from a range of business contexts.

The authors provide a six-stage TMAR on how to use text mining methods in practice. At each stage, the authors provide a guiding question, articulate the aim, identify a range of methods and demonstrate how machine learning and linguistic techniques can be used in practice with illustrative examples drawn from business, from an array of data types, services and contexts.

At each of the six stages, this paper demonstrates useful insights that result from the text mining techniques to provide an in-depth understanding of the phenomenon and actionable insights for research and practice.

There is little research to guide scholars and practitioners on how to gain insights from the extensive “big data” that arises from the different data sources. In a first, this paper addresses this important gap highlighting the advantages of using text mining to gain useful insights for theory testing and practice in different service contexts.

The purpose of this paper is to discuss digital transformation and its four trajectories – digital technology, digital strategy, customer experience and data-driven business models – that could shape the next generation of services. This includes a discussion on whether both the market and organizations are all ready for the digital change and what are the opportunities that will enable firms to create and capture value though new business models.

Providing services is a proven and effective way to secure a competitive position, deliver long-term stable revenues and open up new market opportunities. However, it is also clear that some organisations are struggling to digitally transform. Therefore, the commentary provides a brief insight into how firms explore the possibilities of digital transformation and navigate these uncharted waters.

Today’s digital technologies affect the organisation outside and in, enabling the creation of new business models and transforming the customer experience. The incumbents are acutely aware that they need to transform strategically – to build new networks and value chains.

This commentary extends earlier work exploring the digital disruption within services to highlight a number of connected areas: the challenges and opportunities of digital transformation at a strategic level, as well as understanding and enhancing the customer experience and seeing how new data-driven business models can underpin service transformation.

This paper aims to monitor, evaluate and adjust the joint quality of dissimilar friction stir welded AA2024-T3 and AA7075-T6 Al alloys.

Taguchi analysis for design of experiments and ANOVA analysis were applied. Tensile test, visual inspection and macro and microstructure investigations were carried out at each welding condition. In addition, the grain size of stir zone and the value of heat input were measured.

Using Taguchi analysis, the optimum values of tool rotary speed, welding speed and axial load were 1,200 rpm, 100 mm/min and 1,300 kg, respectively, yielding the maximum tensile strength of the joints of 427 MPa. ANOVA analysis indicated that the most significant parameter on the joint strength is the tool rotary speed, followed by welding speed and axial load, with contributions of 67, 27 and 2 per cent, respectively. Best mixing between Al alloys in the stir zone with no defects was observed at moderate speeds because of proper heat input and grain size, resulting in high strength.

A relation between structure characteristics of the joint, the process parameters and the joint strength was established to control the joint quality.

The purpose of this paper is to derive a taxonomy of business models used by start-up firms that rely on data as a key resource for business, namely data-driven business models (DDBMs). By providing a framework to systematically analyse DDBMs, the study provides an introduction to DDBM as a field of study.

To develop the taxonomy of DDBMs, business model descriptions of 100 randomly chosen start-up firms were coded using a DDBM framework derived from literature, comprising six dimensions with 35 features. Subsequent application of clustering algorithms produced six different types of DDBM, validated by case studies from the study’s sample.

The taxonomy derived from the research consists of six different types of DDBM among start-ups. These types are characterised by a subset of six of nine clustering variables from the DDBM framework.

A major contribution of the paper is the designed framework, which stimulates thinking about the nature and future of DDBMs. The proposed taxonomy will help organisations to position their activities in the current DDBM landscape. Moreover, framework and taxonomy may lead to a DDBM design toolbox.

This paper develops a basis for understanding how start-ups build business models capture value from data as a key resource, adding a business perspective to the discussion of big data. By offering the scientific community a specific framework of business model features and a subsequent taxonomy, the paper provides reference points and serves as a foundation for future studies of DDBMs.

This paper aims to explore the role of international quality assurance and accreditation on higher education quality improvement and competitiveness, as well as assessing the associated benefits and challenges in the Asian context with reference to Taiwan.

The paper used a qualitative approach to examine the case study of Southern Taiwan University of Science and Technology (STUST) accredited by the Association to Advance Collegiate Schools of Business (AACSB). The paper collected survey responses from service providers (i.e. STUST faculty and AACSB) and focus group discussions with students to bridge the perception-expectation gap.

The qualitative results highlighted 10 key success factors and performance indicators which were later used to build a balanced scorecard (BSC) strategy for STUST quality improvement and competitiveness. Findings show that education quality assurance (via AACSB process) can directly influence the competitive advantage (i.e. for AACSB, STUST and Students) or indirectly via education quality enhancement. The results from faculty and students are consistent with the value co-creation trend to achieve continuous quality improvement more effectively and efficiently.

This research paper is unique as the first qualitative in-depth study to discuss assurance related factors that positively or negatively affect competitiveness and quality improvement for Higher Education Institutions (HEIs) in Asia and Taiwan. The paper also contributed by designing a BSC framework and strategy-map applicable to HEIs.

Customer service conversations are becoming increasingly digital and automated, leaving service encounters impersonal. The purpose of this paper is to identify how customer service agents and conversational artificial intelligence (AI) applications can provide a personal touch and improve the customer experience in customer service. The authors offer a conceptual framework delineating how text-based customer service communication should be designed to increase relational personalization.

This paper presents a systematic literature review on conversation styles of conversational AI and integrates the extant research to inform the development of the proposed conceptual framework. Using social information processing theory as a theoretical lens, the authors extend the concept of relational personalization for text-based customer service communication.

The conceptual framework identifies conversation styles, whose degree of expression needs to be personalized to provide a personal touch and improve the customer experience in service. The personalization of these conversation styles depends on available psychological and individual customer knowledge, contextual factors such as the interaction and service type, as well as the freedom of communication the conversational AI or customer service agent has.

The article is the first to conduct a systematic literature review on conversation styles of conversational AI in customer service and to conceptualize critical elements of text-based customer service communication required to provide a personal touch with conversational AI. Furthermore, the authors provide managerial implications to advance customer service conversations with three types of conversational AI applications used in collaboration with customer service agents, namely conversational analytics, conversational coaching and chatbots.

The paper attempts to address the following research questions (RQs): RQ1: What are the main research topics within PSS research? RQ2: What are future trends for PSS research?

Twenty years of research (1999–2018) on product-service systems (PSS) produced a significant amount of scientific literature on the topic. As the PSS field is relatively new and fragmented across different disciplines, a review of the prior and relevant literature is important in order to provide the necessary framework for understanding current developments and future perspectives. This paper aims to review and organize research contributions regarding PSS. A machine-learning algorithm, namely Latent Dirichlet Allocation, has been applied to the whole literature corpus on PSS in order to understand its structure.

The adopted approach resulted in the definition of eight distinct and representative topics able to deal adequately with the multidisciplinarity of the PSS. Furthermore, a systematic review of the literature is proposed to summarize the state-of-the-art and limitations in the identified PSS research topics. Based on this critical analysis, major gaps and future research challenges are presented and discussed.

On the basis of the results of the topic landscape, the paper presents some potential research opportunities on PSSs. In particular, challenges, transversal to the eight research topics and related to recent technology trends and digital transformation, have been discussed.

Responding to an increasing call for a more comprehensive conceptualization of customer delight, the purpose of this paper is to expand the theory of customer delight and to examine the implications of such an expanded view for service theory and practice.

This paper presents the results of three qualitative studies. The first study explores customer delight through self-reported consumption experiences in customer-selected contexts, followed by one-on-one in-depth interviews. The second involves focus groups and the third examines self-reported incidents of delightful customer experiences.

This research finds that customer delight goes beyond extreme satisfaction and joy and surprise to include six properties that—individually or in combination—characterize customer delight. An expanded conceptualization of how customer delight can be defined is proposed in which customer delight is associated with various combinations of six properties – the customer experiencing positive emotions, interacting with others, successful problem-solving, engaging customer’s senses, timing of the events and sense of control that characterizes the customer's encounter.

It is clear from the findings of this research that there is no single property that is associated with delight. Through the facilitation of multiple properties, managers have the potential to create a multitude of routes to delight. It is recommended that future research (1) identify and explicate these alternative routes for engendering delight using the six properties identified, and (2) develop a general typology based on service context and characteristics, customer segment, etc. that further stimulates scholarship on delight, and offers more industry-specific insights for managers.

Insights from this investigation will encourage managers and service designers to think more broadly and creatively about delight. Doing so will open up new opportunities for achieving customer delight, beyond merely focusing on extreme satisfaction or surprise and joy strategies currently dominating discussions of customer delight.

This paper makes several contributions to the service literature. First, it extends current conceptualizations of customer delight and offers an expanded definition. Next, it demonstrates how this new understanding extends the existing literature on delight. Finally, it proposes an agenda for future delight research and discusses managerial implications, opening up new opportunities for firms to design delightful customer experiences.

The purpose of this paper is to investigate how and why some service ecosystems are more resilient and, consequently, more sustainable than others during turbulent times, and how resilience can be cultivated to enable pathways to service ecosystem sustainability.

This work integrates disparate literature from multiple service and sustainability literature streams, iterating through constant comparison with findings from 44 semistructured interviews conducted in the context of primary health care clinic service ecosystems.

The authors offer a novel conceptual framework comprising pillars (shared worldview, individual actor well-being and multiactor interactions), changing practices to cultivate resilience through resilience levers (orchestrators, individual actor effort, actor inclusivity and digitaltech–humanness approach), and pathways to service ecosystem sustainability (volume vs value, volume to value, volume and value). The authors demonstrate that service ecosystems need to change practices, integrating resources differently in response to the turbulent environment, emphasizing the importance of a shared worldview across the ecosystem and assessing different pathways to sustainability.

This paper offers new insights into the important intersection of service marketing, sustainability and health care. The authors provide guidance to practitioners aiming to cultivate resilience in service ecosystems to achieve pathways to sustainability in primary health care clinics. Finally, implications for theory are discussed, and directions to guide future service research offered.