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This study examines whether corporate social responsibility (CSR) initiatives positively impact customers’ selection of retail banks in Hong Kong (HK) and identifies which CSR domains affect customers’ selection of banks.

This study adopted a quantitative approach. Primary data were collected from 416 customers of 22 retail banks in HK. The theoretical framework of this study was developed from a literature review, prior studies by Oberseder et al. (2013 and 2014), and CSR initiatives implemented by leading retail banks in HK. Descriptive statistics and statistical tests were used to analyze the data.

The study found that CSR initiatives positively affect customers’ bank selection. CSR initiatives related to the customer and environment domains are likely to have a greater impact on customers than those related to the society domain and are not likely to significantly impact customers’ bank selection.

This study contributes to the CSR literature by offering enhanced insight into the dynamics of CSR and its effects on customer bank selection. Furthermore, this study tests consumers’ perceptions of CSR initiatives in each CSR domain in the banking sector in Hong Kong – a novel approach that has not been previously explored in existing studies. These findings can help banks review the effectiveness of their CSR initiatives and make informed decisions on which initiatives should pursue improved CSR performance and efficient resource allocation.

Pricing is widely acknowledged as a market entry challenge for servitising companies. The purpose of this research is to ascertain the attributes that contribute to willingness to pay (WTP) for industrial services and suggest incorporating those attributes to a pricing model.

Three attributes (Quality of Service, Nearness of Service Provider and Brand Equity of Service Provider) were analyzed at three respective levels to ascertain their importance on WTP. Conventional conjoint analysis (CCA), using an orthogonal design, was the method used. The 346 respondents were decision-makers and top management professionals from various industries.

Brand Equity emerged as the most significant attribute contributing to WTP, having more than 45% importance – followed by the Quality and Nearness.

The scope of the study is limited to the industries and its Allies. However, the relative importance of the attributes may vary depending on the type of service.

The importance of attributes and their WTP preference helps future researchers create a pricing model involving these attributes. This helps service providers price their services rationally, thus succeeding in servitization.

Product life is extended because the manufacturers themselves are servicing it and also help recycle the product with their expertise. Servitization is also helpful for the Indian economy, as it is turning into a manufacturing economy.

This research investigates three attributes that contribute to WTP, in accordance with their level of contribution. It also provides a direction to establish an adequate pricing model for industrial services.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

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.

In industrial buyer–supplier relationships, being an attractive customer has been found to result in superior supplier performance. However, there is a limited understanding of how these benefits transfer to the public domain. This study aims to explore the influence of customer attractiveness on supplier resource mobilization efforts toward the public sector.

A qualitative approach was used, focusing on in-depth interviews with 23 informants from 3 critical and complex supplier markets. The data were processed using inductive coding and thematic analysis.

The findings indicate that customer attractiveness in the public sector influences suppliers’ mobilization efforts on several dimensions. In addition to stimulating competition in the tender phase, customer attractiveness can yield important benefits to quality, supply stability and innovation during the business relationship. It appears imperative for the public sector to improve its standings with suppliers to both mitigate the apparent risk of sub-par treatment and to unlock the preferential supplier treatment associated with being an attractive customer.

Receiving increased mobilization from suppliers will result in better use of public money and help improve resilience and innovation in public procurement.

This study extends the research on customer attractiveness in the public sector by being the first to explore the range and nature of its influence on supplier mobilization efforts.

Variations in customer expectations pose a challenge to service quality improvement in the airline industry. Understanding airline customers' expectations and satisfaction help service providers improve their offerings. The extant literature examines airline passengers' expectations in isolation, neglecting the overall impact of online reviews on service quality improvement. This paper systematically evaluates the airline industry's passengers' expectations and satisfaction using expectation confirmation theory (ECT) and the SERVQUAL framework. The paper analyzes online reviews to examine the relationship between airline service quality attributes and passengers' satisfaction.

The SERVQUAL framework was employed to examine the effects of customer culture, the reason for traveling, and seat type on customer's expectations and satisfaction across a large sample of airline customers.

A total of 17,726 observations were gathered from the Skytrax review website. The lowest satisfaction ratings were from passengers from the USA, Canada and India. Factors that affect perceived service performance include customer service, delays and baggage management. Empathy and reliability have the biggest impact on the perceived satisfaction of passengers.

This research increases understanding of the consumer expectations through analysis of passengers' online reviews. Results are limited to a small sample of airline industries.

This study provides airlines with valuable information to improve customer service by analyzing online reviews.

This study provides the opportunity for airline customers to gain better services when airline companies utilize the findings.

This paper offers insights into passengers' expectations and their perceived value for money in relation to seat types. Previous studies have not investigated value for money as a construct for passengers' expectations and satisfaction relative to service quality dimensions. This paper addresses this need.

This study aims to investigate what past scholars have learned about Muslim consumer compliance behaviour in Islamic banks and identify what future research is needed. In addition, it also explores the relationship model between the previously studied determining factors and the customer’s Sharia compliance behaviour.

This study used a bibliometric–systematic literature review analysis using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) technique by reviewing the articles published from 2013 to 2023. The PRISMA procedures involved several stages, including identification, screening, eligibility, analysis and conclusion based on the findings.

The results found that customer Sharia compliance behaviour determinants in Islamic banks are attitude, subjective norms, perceived behavioural control, Islamic financial literacy, religiosity, consumer conformity, Islamic branding and behavioural intention. Interestingly, the results indicated that such factors as consumer conformity, Islamic branding and sustainable intentions are less discussed.

Decision-makers in Islamic banks must use digital technology to offer better service and make operations more reachable for customers to access information, complete transactions and manage their accounts by Sharia principles. Therefore, the bank needs to continually produce innovative products and services so that customers have a greater variety of options to suit their Sharia-compliant financial needs. Theoretically, this study has contributed by finding the main critical domains influencing customers’ Sharia compliance behaviour, such as attitudes, subjective norms, perceptions of behavioural control, knowledge of Islamic finance, religiosity, consumer conformity, Islamic branding and behavioural intentions. Then, it makes a theoretical contribution by establishing a model that explains how customers make decisions based on Sharia-related factors in the context of their purchases.

Past studies focused on the Sharia compliance behaviour in paying Zakat for takaful customers. Therefore, this study provides critical factors of Sharia compliance behaviour on conformity, Islamic branding and sustainable intention regarding unexplored consensus on the determinants and outcomes of customer Sharia compliance behaviour of Islamic banking.

Designing and developing responsible business practices can create various tensions for service organizations. The purpose of this research is to develop a deeper understanding of the relationship between customer engagement (CE) and responsible business practices (e.g. environmental, social and/or governance [ESG], corporate social responsibility [CSR] and diversity, equity, and inclusion [DEI]) and explore customer engagement tensions that service organizations may face.

This research develops a list of CE-related responsible business practice tensions and empirically explores their relevance through in-depth interviews with nine ESG professionals.

This paper makes three important contributions. First, we find support for nine distinct but related tensions with implications for CE that organizations must navigate when pursuing responsible business practices. Second, interview participants provide some suggestions for tackling these tensions, which we support with relevant theories. Finally, we develop a conceptual framework that may stimulate future service research and inform the implementation of ESG strategies.

To the best of the authors’ knowledge, this research is the first to conceptualize and empirically explore the tensions that emerge between responsible business practices and CE. The authors develop a novel analysis of the CE-related tensions that emerge when pursuing an ESG strategy.

The findings are based on a small sample of ESG professionals. Future research may take a quantitative approach to further evaluate the role that these tensions play in engaging customers.

This research provides a conceptual framework that may guide ESG professionals in understanding, framing and navigating CE-related tensions when pursuing responsible business practices.

A social benefit may be found when service organizations are better able to successfully navigate CE-related tensions when pursuing responsible business practices.

The purpose of this paper is to investigate the influence of employees’ trait rumination on the variability of their state rumination and the continuing influence on their negative affect at home.

A time-lagged experience sampling method was used for the data collection from full-time employees in the hotel industry. The hypotheses were tested with multilevel modeling using a random coefficient modeling approach.

Hotel employees who are high in trait rumination generally show high levels of state rumination and greater within-person variability in state rumination over time. Additionally, the negative effects of workplace state rumination can last until employees come home and the next day before going to work. Furthermore, employees who are high in trait rumination are more likely to be influenced by state rumination, as they experience more negative affect after arriving home.

Rumination has been shown to decrease hotel employee overall well-being. The findings of this study provide suggestions for remedial measures that can be taken by hotel organizations to help employees address ruminative thinking.

Drawing on response styles and work/family border theories, this study contributes to the rumination literature by considering both trait rumination and state rumination in a broader context. For a comprehensive understanding of the dynamic temporal characteristics of state rumination, this study considers the net intraindividual variability of state rumination as the outcome of trait rumination.