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This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.

This study aims to develop an empathetic and user-centric customer support service design model. Though service design has been a critical research focus for several decades, few studies focus on customer support services. As customer support gains importance as a source of competitive advantage in the present era, this paper aims to contribute to industry and academia by exploring the service design model.

The study adopted a theories-in-use approach to elucidate mental models based on the industry’s best practices. In-depth interviews with 62 professionals led to critical insights into customer service design development, supported by service-dominant logic and theory of mind principles.

The ensuing insights led to a model that connects the antecedents and outcomes of empathetic and user-centric customer service design. The precursors include people, processes and technology, while the results are user experience, service trust and service advocacy. The model also emphasises the significance of the user’s journey and the user service review in the overall service design.

The model developed through this study addresses the critical gap concerning the lack of service design research in customer support services. The key insights from this study contribute to the ongoing research endeavours towards transitioning customer support services from an operational unit to a strategic value-creating function. Future scholars may investigate the applicability of the empathetic user service design across cultures and industries. The new model must be customised using real-time data and analytics across user journey stages.

The empathetic and user-centric design can elevate the customer service function as a significant contributor to the overall customer experience, loyalty and positive word of mouth. Practitioners can adopt the new model to provide superior customer service experiences. This original research was developed through crucial insights from interviews with senior industry professionals.

This research is the original work developed through the key insights from the interview with senior industry professionals.

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.

Understanding the effect of assortment composition on attentional levels is an essential topic for academic researchers and practitioners. This work has important implications when analyzing the influence of shopping frame time and search effort on the relationship between the reaction to assortment composition and visual attention to stock-keeping units (SKUs) pricing.

Two experimental studies through gauze behavior analysis technology (using eye-tracking equipment) analyze the variable's large assortment, visual attention to SKU pricing, search effort and shopping frame time.

The results suggest that, although it increases the search effort, a large assortment decreases the visual attention to SKU pricing. Further, our results indicate a moderating effect associated with mitigating the negative effect by medium-low levels of search effort and a moderating impact of time in this relation.

Marketing professionals can carefully optimize the in-store experience by managing the assortment and variety and by influencing consumers' visual attention to SKU pricing along the journey as part of the experience. Assortment and SKU pricing strategies need to be aligned with consumer journey design.

Our findings contribute to assortment theory and management by detailing the relationship between consumers' reactions to assortment perception and visual attention to SKU pricing in time flow. We reinforce the importance of considering assortment strategies from the consumer perspective and giving reliable information about in-store behavior.

The COVID-19 pandemic has generated unprecedented public fear, impeding both individuals’ social life and the travel industry as a whole. China was one of the first major countries to experience the COVID-19 outbreaks and recovery from the pandemic. The demand for outings is increasing in the post-COVID-19 world, leading to the recovery of the ride-sharing industry. Integrating protection motivation theory and the theory of reasoned action, this study aims to investigate ride-sharing customers’ self-protection motivation to provide anti-pandemic measures and promote the resilience of ride-sharing industry.

This study followed a two-phase mixed-methods design. In the first phase, the authors executed a qualitative study with 30 interviews. In the second phase, the authors used the results of the interviews to inform the design of a survey, with which 272 responses were collected. Both studies were conducted in China.

The present results indicate that customers’ perceived vulnerability of COVID-19 and perceived COVID protection efficacy (self-efficacy and response efficacy) are positively correlated with their attitude toward self-protection, thus leading to their self-protection motivation during the rides. Moreover, subjective norms and customers’ distrust appear to also impact their self-protection motivation during the ride-sharing service.

The present research provides one of the first in-depth studies, to the best of the authors’ knowledge, on customers’ protection motivation in ride-sharing services in the new normal. The empirical evidence provides important insights for ride-sharing service providers and managers in the post-pandemic world and promote the resilience of ride-sharing industry.

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.

The purpose of this study is to determine if blockchain-supported carbon offset information provision and shipping options with different cost and environmental footprint implications impact consumer perceptions toward retailers and logistics service providers. Blockchain and carbon neutrality, each can be expensive to adopt and complex to manage, thus getting the “truth” on decarbonization may require additional costs for consumers.

Experimental modeling is used to address these critical and emergent issues that influence practices across a set of supply chain actors. Three hypotheses relating to the relationship between blockchain-supported carbon offset information and consumer perceptions and intentions associated with the product and supply chain actors are investigated.

The results show that consumer confidence increases when supply chain carbon offset information has greater reliability, transparency and traceability as supported by blockchain technology. The authors also find that consumers who are provided visibility into various shipping options and the product's journey carbon emissions and offset – from a blockchain-supported system – they are more willing to pay a premium for both the product and shipping options. Blockchain-supported decarbonization information disclosure in the supply chain can lead to organizational legitimacy and financial gains in return.

Understanding consumer action and sustainable consumption is critical for organizations seeking carbon neutrality. Currently, the literature on this understanding from a consumer information provision is not well understood, especially with respect to blockchain-supported information transparency, visibility and reliability. Much of the blockchain literature focuses on the upstream. This study focuses more on consumer-level and downstream supply chain blockchain implications for organizations. The study provides a practical roadmap for considering levels of blockchain information activity and consumer interaction.

The huge Muslim population has increased the demand for halal tourism products and destination factors in this niche tourism segment. Despite the growing body of research conducted regarding ChatGPT’s revolutionary impact on the tourism industry, the use of such an artificial intelligence (AI) tool in halal tourism needs more attention. This study aims to provide a comprehensive an overview of using ChatGPT in the tourism industry, specifically in halal tourism, and offer an agenda for further essential research questions exploration.

Through the intensive examination of the tourism literature dealing with AI and halal tourism, this review identifies the implications related to the use of ChatGPT for Muslim travelers and future trends in halal tourism.

This paper identified the possible utilization of ChatGPT in assisting Muslim travelers across various stages of their journey, encompassing pre-trip, staying and post-trip phases. Subsequently, this paper identified the opportunities and challenges associated with implementing ChatGPT in the context of halal tourism. Finally, the paper delves into potential avenues for future research.

The findings serve as crucial implications, contributing to the theory of halal tourism development and the applications of ChatGPT in halal tourism.

This paper provides essential foundational knowledge for upcoming research on halal tourism theory, ChatGPT and the development of halal tourism sector.

This study aims to delve into the lived experiences, challenges and visions of women entrepreneurs in Jordan, placing a magnifying glass on those spearheading or co-pioneering start-ups. It aims to understand the myriad factors that influence their entrepreneurial journey, from motivation to the future of their niche.

Adopting a qualitative lens, this study is anchored in semi-structured interviews encompassing 20 Jordanian women entrepreneurs. Following this, thematic analysis was deployed to dissect and categorize the garnered insights into ten salient themes.

The study reveals that personal experiences and challenges are pivotal in directing these women towards niche markets, aligning with the theory of planned behaviour (TPB). Tools such as digital instruments, customer feedback and innovative strategies like storytelling and augmented reality are integral to their entrepreneurial success, resonating with the resource-based view (RBV). Additionally, challenges like cultural barriers and infrastructural limitations are navigated through adaptive strategies, reflecting the resilience inherent in these entrepreneurs. Networking, mentorship, embracing technological advancements and implementing sustainable practices are highlighted as crucial elements underpinned by the social identity theory (SIT).

Contrary to the extant body of research, this study provides new insights into the challenges faced by women entrepreneurs in Jordan, highlighting the practical relevance of theories like TPB, RBV and SIT for both policymakers and the start-up community in niche markets.

Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by introducing an ensemble attribution model to optimize marketing budget allocation for online marketing channels. As empirical research, this study demonstrates the supremacy of the ensemble model over standalone models.

The transactional data set for car insurance from an Indian insurance aggregator is used in this empirical study. The data set contains information from more than three million platform visitors. A robust ensemble model is created by combining results from two probabilistic models, namely, the Markov chain model and the Shapley value. These results are compared and validated with heuristic models. Also, the performances of online marketing channels and attribution models are evaluated based on the devices used (i.e. desktop vs mobile).

Channel importance charts for desktop and mobile devices are analyzed to understand the top contributing online marketing channels. Customer relationship management-emailers and Google cost per click a paid advertising is identified as the top two marketing channels for desktop and mobile channels. The research reveals that ensemble model accuracy is better than the standalone model, that is, the Markov chain model and the Shapley value.

To the best of the authors’ knowledge, the current research is the first of its kind to introduce ensemble modeling for solving attribution problems in online marketing. A comparison with heuristic models using different devices (desktop and mobile) offers insights into the results with heuristic models.