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This paper aims to introduce the experience-dominant (Ex-D) logic model, which synthesizes the creation, perceptions and outcomes of Ex-D logic. It is designed to offer valuable insights for strategic managerial applications and future research directions.

Employing a qualitative approach by using eight selected product launch events from reviewed 100 event videos and 55 in-depth interviews with industrial managers to develop an Ex-D logic model, and data were coded and analysed via NVivo.

Results show that the firm’s Ex-D logic is operationalized as the mentalizing of the three types of customer needs (service competence, hedonic excitations and meaning making), the materializing of three types of customer experiences and customer journeys (service experience, hedonic experience and brand experience) and the moderating of three types of customer values (service values, hedonic values and brand values).

This study has implications for adding new insights into existing theory on dominant logic and customer experience management and also offers actionable recommendations for managerial applications.

This study sheds light on the importance of Ex-D logic from a strategic point of view and provides an organic view of the firm. It distinguishes firm perspective from customer perspective, firm experience from customer experience and firm journey from consumer journey.

This study aims to conceptualize the relationship of perceived artificial intelligence (AI) credibility with consumer-AI experiences. With the widespread deployment of AI in marketing and services, consumer-AI experiences are common and an emerging research area in marketing. Various factors affecting consumer-AI experiences have been studied, but one crucial factor – perceived AI credibility is relatively underexplored which the authors aim to envision and conceptualize.

This study employs a conceptual development approach to propose relationships among constructs, supported by 34 semi-structured consumer interviews.

This study defines AI credibility using source credibility theory (SCT). The conceptual framework of this study shows how perceived AI credibility positively affects four consumer-AI experiences: (1) data capture, (2) classification, (3) delegation, and (4) social interaction. Perceived justice is proposed to mediate this effect. Improved consumer-AI experiences can elicit favorable consumer outcomes toward AI-enabled offerings, such as the intention to share data, follow recommendations, delegate tasks, and interact more. Individual and contextual moderators limit the positive effect of perceived AI credibility on consumer-AI experiences.

This study contributes to the emerging research on AI credibility and consumer-AI experiences that may improve consumer-AI experiences. This study offers a comprehensive model with consequences, mechanism, and moderators to guide future research.

The authors guide marketers with ways to improve the four consumer-AI experiences by enhancing consumers' perceived AI credibility.

This study uses SCT to define AI credibility and takes a justice theory perspective to develop the conceptual framework.

Parenting programmes are increasingly a feature of services and policies aimed at improving outcomes for children and families and tackling inequality, yet they remain underused. This study aims to assess parent engagement and retention in the parent and infant (PIN) programme – a universal, multi-component intervention designed to support parents from birth to when their children reach two years of age. The programme can be tailored to parent/community needs but also includes standardised core elements including two Incredible Years parenting programmes. Programme provider perspectives on recruiting and supporting participation were also explored.

A mixed methods study was conducted involving parents (n = 106) and programme providers involved in the PIN programme. Logistic regression analyses were used to assess the impact of participant demographic characteristics on the likelihood of programme engagement and attendance. Semi-structured interviews explored facilitators’ experiences of parent recruitment and engagement, as well as barriers and facilitators of parental attendance.

First-time mothers were more likely to initially enrol in the PIN programme than younger or lone parents. However, older age and married/cohabiting status were the strongest predictors of attending at least one-third of programme sessions. Qualitative findings highlighted the importance of relationship building and connection in supporting participant recruitment and engagement. Practical and psychological barriers to programme participation are also described.

The findings shed light on factors that influence engagement and attendance in universal, early parent support programmes. Barriers to parent engagement are multi-layered and tailored strategies to promote uptake of parenting programmes are needed.

Higher education has begun to attend to the importance of collaboration and self-awareness for educating sustainability leaders. However, there has been limited discussion on how to design a pedagogy that supports the development of these competencies, particularly the development of self-awareness. In this chapter, we introduce an experiential pedagogy in which students and faculty work together to develop self-awareness as the basis for sustainability leadership. We present three pedagogical principles that support the emotional learning that is foundational for sustainability leadership: student self-discovery, faculty as co-learners, and a developmentally focused learning environment. We demonstrate how these three principles work together to enable students and faculty to grow their self-awareness, providing the foundation for sustainable leadership. We conclude with a discussion on how management educators can learn from this case to develop sustainability leaders who have the self-awareness and relational competency to lead positive, inclusive organizations that are committed to sustainable business practices.

Customer experience management (CXM), which aims to achieve and maintain customers' long-term loyalty, has attracted the attention of many organizations. Improving customer experience management in organizations requires that, first, their relevant capabilities be evaluated. The present study aimed to offer a set of key performance indicators for evaluating customer experience management in commercial banks.

The study, first, attempted to identify the components of evaluating customer experience management by reviewing the related literature and conducting interviews with experts. Then, the extracted components were transformed into assessable metrics using the goal question metric method, and the key performance indicators relevant to customer experience management in commercial banks were selected according to the experts' opinions and the Fuzzy Delphi method.

According to the findings of the study, 21 key performance indicators were identified for customer experience management in commercial banks, and customer satisfaction, the mean number of calls to resolve an issue in customer journey touchpoints, the NPS, and the ratio of the budget allocated to the CXM department to the budget of the marketing department were found as the most significant performance indicator according to banking experts.

The present study was among the first research projects intended to evaluate CXM and offer key performance indicators that could help the managers of commercial banks assess the maturity levels of their CXM.

The purpose of this paper is to unearth various dimensions of employee experience (EX) and explore how pandemic impacted various EX factors using online employee reviews. The authors identify employee-discussed EX-factors and quantify the associated sentiments and importance.

This paper employs Latent Dirichlet Allocation on the online employee reviews to identify the key EX-factors. The authors probe sentiments and importance associated with key EX-factors using sentiment analysis, importance analysis, regression analysis and dominance analysis.

The result of topic modeling identifies 20 EX-factors that shape overall EX. While skill development plays a major role in shaping overall EX, employees perceived Salary and Growth as the most important EX-factor and expressed negative sentiments during the pandemic. Employee sentiments significantly influence overall EX.

When employees have extensive change experience, managers should consider various facets of EX to manage the smooth change and deliver a better EX. This research offers key EX-factors to be considered by managers while dealing with employees. Online employee reviews websites are recommended to include the identified key EX-factors to comprehend the holistic EX.

This study contributes to the growing literature on the employee experience as a concept by identifying various EX-factors. The authors expand the extant EX scales by identifying an inclusive and updated set of EX-factors.

This study aims to investigate the content of hotel brands’ mission statements (MSs) and their relationship with selected attributes of hotel brands.

Content analysis of hotel brands’ MSs was used to detect the MSs’ key words, which were further processed by methods of social network analysis, complemented by clustering techniques and correspondence analysis on the generalized aggregated lexical tables, a special type of correspondence analysis.

Hotel brands operating in luxurious markets more often emphasize experiences than those in midscale markets. Furthermore, hotel brands with longer traditions and those with a large number of controlled rooms communicate words in their MSs that represent a rather traditional approach to hospitality. Younger hotel brands with fewer controlled rooms chose words that indicate a more commercially oriented approach. Finally, cluster analysis revealed four dimensions of hotel brands’ MSs, instead of the nine most typically used in mission statement component models.

Understanding the frequencies and networks of keywords, and their relationship with hotel brand attributes, will help create more focussed MSs. This will strengthen hotel brands, raise their revenues and subsequently increase company performance.

The analysis provides valuable insight into MSs in the specific tourism context of hotel brands. The authors have achieved this with the use of a wide range of advanced network analytic methods. These insights can guide hotel brands to better position themselves in the competitive tourism accommodation market.

The authors examine the role of analysts’ prior experience of forecasting for firms exposed to epidemics on analysts’ forecast accuracy during the COVID-19 pandemic.

The authors examine the impact of analysts’ prior epidemic experience on forecast accuracy by comparing the changes from the pre-COVID-19 period (calendar year 2019) to the post-COVID period extending up to March 2023 across HRE versus non-HRE analysts. The authors consider a full sample (194,980) and a sub-sample (136,836) approach to distinguish “Recent” forecasts from “All” forecasts (including revisions).

The study's findings reveal that forecast accuracy for HRE analysts is significantly higher than that for non-HRE analysts during COVID-19. Specifically, forecast errors significantly decrease by 0.6% and 0.15% for the “Recent” and “All” forecast samples, respectively. This finding suggests that analysts’ prior epidemic experience leads to an enhanced ability to assess the uncertainty around the epidemic, thereby translating to higher forecast accuracy.

The finding that the expertise developed through an experience of following high-risk firms in the past enhances analysts’ performance during the pandemic sheds light on a key differentiator that partially explains the systematic difference in performance across analysts. The authors also show that industry experience alone is not useful in improving forecast accuracy during a pandemic – prior experience of tracking firms during epidemics adds incremental accuracy to analysts’ forecasts during pandemics such as COVID-19.

The study findings should prompt macroeconomic policymakers at the national level, such as the central banks of countries, to include past epidemic experiences as a key determinant when forecasting the economic outlook and making policy-related decisions. Moreover, practitioners and advisory firms can improve the earning prediction models by placing more weight on pandemic-adjusted forecasts made by analysts with past epidemic experience.

The uncertainty induced by the COVID-19 pandemic increases uncertainty in global financial markets. Under such circumstances, the importance of analysts’ role as information intermediaries gains even more importance. This raises the question of what determines analysts’ forecast accuracy during the COVID-19 pandemic. Building upon prior literature on the role of analyst experience in shaping analysts’ forecasts, the authors examine whether experience in tracking firms exposed to prior epidemics allows analysts to forecast more accurately during COVID-19. The authors find that analysts who have experience in forecasting for firms with high exposure to epidemics (H1N1, Zika, Ebola, and SARS) exhibit higher accuracy than analysts who lack such experience. Further, this effect of experience on forecast accuracy is more pronounced while forecasting for firms with higher exposure to the risk of COVID-19 and for firms with a poor ex-ante informational environment.

The purpose of the current study was to examine university students' knowledge, confidence and experience of popular graduate employer selection tests.

A cross-sectional self-report survey was administered to gather a sufficient number of quantitative responses from undergraduate students. A total of 241 students completed the survey with most of them being psychology students from Swansea University. Four key variables were examined: (1) students' experience, (2) confidence and (3) knowledge of selection tests and (4) their desire for more information about selection tests as part of their degree. An audit of selection tests used by the Times Top 100 graduate employers was also conducted.

Students tended to misjudge how often selection tests were used by employers, and generally lacked experience with these tests. Students' confidence in completing each test varied as a function of the selection test; however, prior experience with these tests positively predicted confidence. Additionally, over 70% of students reported a desire for further information about selection tests as part of their degree.

These novel findings suggest that students could benefit from further information about selection tests as part of their degree programme which would be of benefit to both students and universities.

These findings are, to the authors knowledge, the first to explicitly assess second- and third-year undergraduate students' knowledge, experience and confidence with popular graduate employer selection tests and demonstrate that students would like more information about these tests on their programme.

The aim of this work is to provide a theoretical model that can help companies to develop a unique approach to achieve both corporate environmental sustainability (CES) and successful customer experience management (CEM).

A two-phase study achieved the research aim. The first phase consisted of the analysis of contemporary theoretical contributions with a focus on CES and CEM. In the second phase, taking a qualitative approach, the key dimensions identified in the initial analysis were investigated to explore the dominant perceptions of practitioners and to hone the theoretical categories.

Five innovative pathways emerged from the study to inform decision-making while maintaining the dual objectives of CES and successful CEM. These pathways are combined to offer a strategic tool for managers and for research advances. This original integrated model also offers six novel theoretical propositions that describe how to shape corporate decisions to achieve environmental sustainability in CEM.

Firms can benefit from an approach that integrates CES and CEM to develop a new mindset for an innovative and valuable decision-making process and to design more captivating experiences for customers. Nevertheless, the efficacy and generalizability of the theoretical framework and propositions require empirical testing.

This paper makes an original contribution to the environmental sustainability and marketing literature by bringing together all elements in these fields of research in a conceptual model. Moreover, this paper proposes theoretical propositions that advance knowledge of the subject and offer ideas for future research and managers.