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This study aims to progress scholarly understanding of the staycation phenomenon by examining customer segments and documenting local customers’ attribute preferences.

A stated choice experiment is used to examine customer preferences for staycation package attributes. Latent class discrete choice modeling is deployed to classify customers into market segments based on their preferences. The profile of each segment is enhanced by documenting customer characteristics and consumption styles.

Six prominent market segments are identified using a combination of sociodemographics, consumption styles and staycation attribute preferences. The findings draw on consumer experiences during the COVID-19 pandemic to generate theoretical insights into preferred staycation packages. Empirically, the estimation results from the research framework and choice experimental method demonstrate that staycation market segments exhibit distinct preference structures.

Practitioners and policymakers can incorporate the findings of this study in designing and/or assessing staycation packages. This can ensure differentiated products for defined segments that resonate within local communities through positive word of mouth, thus offering prospective spillovers to visiting friends and relatives.

This is a pioneering study on preference heterogeneity from the customer perspective, with a focus on staycation markets. The findings can encourage and assist hotel sector leaders to capitalize on local market developments to achieve a more resilient hospitality business model.

Although user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.

The authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.

The authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.

This study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.

The explosion of data due to the sophistication of information and communication technology makes it simple for prospective tourists to learn about previous hotel guests' experiences. They prioritize the rating score when selecting a hotel. However, rating scores are less reliable for suggesting a personalized preference for each aspect, especially when they are in a limited number. This study aims to recommend ratings and personalized preference hotels using cross-domain and aspect-based features.

We propose an aspect-based cross-domain personalized recommendation (AsCDPR), a novel framework for rating prediction and personalized customer preference recommendations. We incorporate a cross-domain personalized approach and aspect-based features of items from the review text. We extracted aspect-based feature vectors from two domains using bidirectional long short-term memory and then mapped them by a multilayer perceptron (MLP). The cross-domain recommendation module trains MLP to analyze sentiment and predict item ratings and the polarities of the aspect based on user preferences.

Expanded by its synonyms, aspect-based features significantly improve the performance of sentiment analysis on accuracy and the F1-score matrix. With relatively low mean absolute error and root mean square error values, AsCDPR outperforms matrix factorization, collaborative matrix factorization, EMCDPR and Personalized transfer of user preferences for cross-domain recommendation. These values are 1.3657 and 1.6682, respectively.

This study assists users in recommending hotels based on their priority preferences. Users do not need to read other people's reviews to capture the key aspects of items. This model could enhance system reliability in the hospitality industry by providing personalized recommendations.

This study introduces a new approach that embeds aspect-based features of items in a cross-domain personalized recommendation. AsCDPR predicts ratings and provides recommendations based on priority aspects of each user's preferences.

There is always a need to discover how a paradox between a customer’s desire for a more personalized experience and their privacy and security concerns would shape their intention to continue using contactless payment methods. However, personalization–privacy paradox has not been well-covered over the area of contactless payment. Therefore, this study aims to empirically examine the impact of personalization–privacy paradox on the customers’ continued intention (CIN) to use contactless payment.

/methodology/approach – The empirical part of the current study was conducted in Saudi Arabia by collecting the primary data using online questionnaire from a convenience sample size of 297 actual users of contactless payment methods.

Based on structural equation modeling, personalization and privacy invasion were approved to significantly impact perceived value of information disclosure (PVD). Strong causal associations were confirmed between perceived severity, structural assurance and response cost with privacy invasion. Finally, both PVD and privacy invasion significantly predict CIN.

There are other important factors (i.e. technology interactivity, technology readiness, social influence, trust, prior experience, etc.) were not tested in the current study. Therefore, future studies would pay more attention regarding the impact of these factors. The current study data were also collected using a convenience sample of actual users of contactless payment methods. Therefore, there is a concern regarding the generalizability of the current study results to other kind of customers who have not used contactless payment.

This study has integrated both personalization–privacy paradox and protection motivation theory in one model. The current study holds value in providing a new and complete picture of the inhibitors and enablers of customers’ CIN to use contactless payment, including new types of inhibitors. Furthermore, personalization–privacy paradox has not been fully examined over the related area of Fintech and contactless payment in general. Therefore, this study was able to extend the theoretical horizon personalization–privacy paradox to new area (i.e. contactless payment) and new cultural context (Saudi Arabia).

Virtual kitchens are a new business phenomenon, and how customers react to the new business model is still a largely unexplored topic. The purpose of this study is to examine the underlying mechanisms of consumers’ different responses to their reasoning of the new and disruptive business model of the virtual kitchen.

Based on the attribution theory and situated focus theory of power, this study conducts three online experiments to test the proposed framework. A total of 487 US residents who had prior experience with restaurant food delivery participated in the studies.

The results indicate that external attribution (vs internal attribution) and ethnic cuisine (vs mainstream cuisine) are more likely to elicit customers’ empathy and justice, leading to higher purchase intentions with virtual kitchens. A mainstream virtual kitchen is better off attributing itself to external factors. The significant effects of causal attribution and cuisine type on purchase intention only exist with powerful customers and those with high moral identity.

The results of this study provide valuable insight to virtual kitchen businesses to better position and market themselves to gain customers’ support. The findings also suggest that ethnic and mainstream restaurants should strategize their marketing communications about virtual kitchens differently.

To the best of the authors’ knowledge, this study is one of the first to provide in-depth insight into the growing phenomenon of virtual kitchens. It also contributes to the extant literature on attribution theory and situated focus theory of power.

The purpose of this paper is to explore the distinction between human-delivered service and technology-based, automated customer assistance.

This is a conceptual paper. There is no methodology.

The concept of service is primarily delivered when a human helps another. When technology is infused into the process and becomes the major component of delivering the aid that is requested, the process is automated customer assistance. Thus, “self-service” is not service. It is automated customer assistance.

The definition of service is refined to describe the process of a human helping another person. When technology is used to provide the needed aid, it is no longer a service. Instead, it is automated customer assistance. The implication is that researchers should closely examine how users assess and perceive the two separate approaches to providing the needed aid.

The definition of service is refined to describe the process of a human helping another person. When technology is used to provide the needed aid, it is no longer a service. Instead, it is automated customer assistance. Researchers should closely examine how users assess and perceive the two separate approaches. Industry professionals should be mindful of the distinction between the delivery of service, which requires staff, and the provisioning of technology to provide assistance, which requires little to no staff. Intentionality should drive when customers are better helped by a human or by technology.

The value provided helps both providers create and users express when human-based service is needed versus assistance provided by technology.

Inaccurate capturing and processing of customer requirements result in negative economic and ecological effects. Digital twins of customer demands promise to remedy these issues. However, successful implementation necessitates users' technology acceptance. This study contrasts three hierarchical digital twin levels with different degrees of user integration and examines determinants for their respective acceptance.

A structural equation model is applied in a comparative manner, considering different levels of digital twin radicalness. A multidimensional approach is used to measure attitudes towards usage. Data are collected in the context of organisational supply management.

Results show harmonious effects across digital twin levels. This indicates that technological radicality plays only a subordinate role when assessing acceptance determinants such as user perception on ease of use, usefulness, trust and risk.

Rather than focussing solely on technological factors, findings suggest that users prioritise the actual outcome and efficiency of the system. This perspective offers practical implications for organisations seeking to implement advanced systems and emphasises the significance of user perceptions beyond technological features.

The societal impact of this research are an appreciation of customer roles in the supply chain where an enhanced detection of customer needs and preferences aligns businesses with the dynamic and evolving demands of a diverse and a continuously environmentally-conscious consumer base.

This study applies a measurement model for technology acceptance in a unique and multidimensional manner. Thereby, a comparative analysis of user perceptions across different digital twin levels sheds more light on a nascent, promising and underexplored technological method. This interdisciplinary research combined knowledge from the supply chain management and management information systems fields by highlighting key factors for the adoption of complex technological methods.

The social venture (SV) is an increasingly popular form of organization to pursue social goals using a commercial approach. Although marketing plays an important role in SV research and a key driver of the performance of SVs, how and the extent to which market conditions play a role remains understudied. This study examines if market turbulence can moderate marketing capabilities and performance relationships.

The authors developed several hypotheses rooted in the marketing literature and tested them using data collected from a sample of 109 SVs from East Asia (i.e. Hong Kong and Taiwan). Using multiple regression analysis and structural equation modeling, the authors analyzed the marketing capabilities and financial and social performance relationships and the positive moderating role of market turbulence.

The results suggested that market turbulence is a positive moderator which influences the effect of the marketing capabilities–financial performance relationship, but not the marketing capabilities and social performance relationship.

This paper attempts to interrogate the SV's marketing capabilities–performance relationship in the East Asian context and how market turbulence may enhance or weaken the relationship. This is one of the earliest papers in this research area. The key findings from this research offer valuable theoretical contribution to the study of SV performance.

The main purpose of this paper is to identify, screen and prioritize customer requirements (CRs) for men’s denim jeans. Moreover, the effect of demographic factors on the primary evaluation criteria has been examined.

The study was initiated by the growing complaints about denim jeans products of a local manufacturing company. First, 24 CRs were identified from the literature and customer complaints. Then, a survey was conducted to rate the identified CRs and solicit more CRs through closed-ended and open-ended questions, respectively. From the survey, 368 usable responses were collected while the participants were shopping in 14 local retail shops. After analyzing the data using factor analysis, univariate and multivariate analysis of variance (MANOVA), and content analysis, the resulting 15 criteria were prioritized by experts’ pairwise comparisons employing the fuzzy analytic hierarchy process (AHP).

Factor analysis extracted six components (primary criteria) including design cues, pocket design, comfort, size and fit, fashionability, and extrinsic cues from the CRs included in the closed-ended questions. MANOVA showed that age and frequency of purchasing denim jeans significantly affected the primary criteria, while educational level and frequency of wearing denim jeans did not. The weights from the fuzzy AHP revealed that colour fastness, price, durability, fabric weight, workmanship, side pocket design and fit as the most important CRs. Moreover, consumers preferred regular fit, stitched round side pockets, patch back pockets and stretchable denim fabric.

The limitations of the study are discussed in the body of the paper in Section 7.

The paper presents exploratory findings on denim jeans evaluation criteria in a developing country’s context. Moreover, the application of fuzzy AHP for prioritizing denim jeans’ CRs is unique.

Effective customer journey design (ECJD) is considered a key variable in customer experience management and an essential source of brand meaning and pro-brand behavior. Although previous research has confirmed its importance for driving brand attitudes and loyalty, the role of consumer-brand identification as a social identity-based influence in this relationship has not yet been discussed. Drawing on construal level and social identity theories, this paper aims to investigate whether effective journeys and the resulting overall journey experience are equally powerful in driving brand loyalty among customers with different levels of consumer-brand identification.

The present article develops and tests a research model using data from the European and US service sectors (N = 1,454) to investigate how and when ECJD affects service brand loyalty.

Across two cultural contexts, four service industries and 33 service brands, the results reveal that ECJD is a crucial driver of service brand loyalty for customers with low consumer-brand identification. Moreover, the findings show that different aspects of journey effectiveness positively impact the valence of customers’ experience related to those journeys – a process that is ultimately decisive for their brand loyalty.

This study is unique because it generates theoretical and practical knowledge by combining the literature streams of customer journey design, customer experience and branding. Furthermore, this work demonstrates that consumer-brand identification is a critical boundary condition to be considered in the relationship between ECJD and brand loyalty in services.