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Artificial intelligence (AI) has become a pivotal technology in both marketing and daily life. Despite extensive research on the benefits of AI, its adverse effects on customers have received limited attention.

We employed meta-analysis to synthesise effect sizes from 45 studies encompassing 50 independent samples (N = 19,503) to illuminate the negative facets of AI's impact on customer responses.

Adverse effects of AI, including privacy concern, perceived risks, customer alienation, and uniqueness neglect, have a negative and significant effect on customers' cognitive (perceived benefit, trust), affective (attitude and satisfaction) and behavioural responses (purchase, loyalty, well-being). Additionally, moderators in AI (online versus offline), customer (age, male vs. female), product (hedonic vs. utilitarian, high vs. low involvement), and firm level (service vs. manufacturing) and national level (individualism, power distance, masculinity, uncertainty avoidance, long-term orientation) moderate these relationships.

Our findings inform marketing managers about the drawbacks of utilising AI as part of their value proposition and provide recommendations on how to minimise these effects in different contexts. Additionally, policymakers need to consider the dark side of AI, especially among the vulnerable groups.

This paper is among the first research studies that synthesise previous research on the dark side of AI, providing a comprehensive view of its diminishing impact on customer responses.

Gaining and maintaining trust in e-commerce is crucial for online purchases. Specifically, understanding trust formation and its consequences in a cross-market online shopping context is important, as cross-market studies are scarce. Therefore, this study examines antecedents and consequences of consumer trust in online shopping (TOS) by comparing advanced and emerging markets.

To test the formulated hypotheses, data including 397 responses from Austria and 205 from Moldova are analysed. Using partial least squares (PLS) path modelling, implications for theory and practice in cross-market e-commerce are obtained.

Empirical findings show that company reputation, perceived security and website quality positively influence consumer TOS. TOS corresponds directly positively with purchase intentions (PI). Our research confirms the negative relationship between trust and perceived risk (PR) as well as that between PR and PI. Furthermore, a significant difference between Austria and Moldova regarding the influence of experience and perceived website quality (PWQ) on TOS is observed.

Our study fills research gaps concerning TOS within the context of cross-market e-commerce. It contributes theoretically and practically and reveals the importance of customer trust and risk reduction for online retailers within advanced and emerging markets in order to provoke online PI.

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.

Trust plays a crucial role in overcoming uncertainty and reducing risks. Uncovering the trust mechanism in the sharing economy may enable sharing platforms to design more effective marketing strategies. However, existing studies have inconsistent conclusions on the trust mechanism in the sharing economy. Therefore, this study aims to investigate the antecedents and consequences of different dimensions of trust (trust in platform and trust in peers) in the sharing economy.

First, we conducted a meta-analysis of 57 related articles. We tested 13 antecedents of trust in platform (e.g. economic benefits, enjoyment, and information quality) and eight antecedents of trust in peers (e.g. offline service quality and providers’ reputation), as well as their consequences. Then, we conducted subgroup analyses to test the moderating effects of economic development level (Developed vs Developing), gender (Female-dominant vs Male-dominant), platform type (Accommodation vs Transportation), role type (Obtainers vs Providers), and uncertainty avoidance (Strong vs Weak).

The results confirm that all antecedents and consequences significantly affect trust in platform or peers to varying degrees. Moreover, trust in platform greatly enhances trust in peers. Besides, the results of the moderating effect analyses demonstrate the variability of antecedents and consequences of trust under different subgroups.

This paper provides a clear and holistic view of the trust mechanism in the sharing economy from an object-based trust perspective. The findings may offer insights into trust-building in the sharing economy.

Prior research has proposed a number of scales measuring the customer experience (CX), which tend to conceptualize and operationalize CX differently, raising potential confusion among researchers (e.g. regarding which scale to use). Addressing this issue, this article conducts a systematic review to inventorize key CX scales and assess their theoretical rigor, with a focus on the identification of potential scale-related drawbacks or risks.

Drawing on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach, 104 CX scale development studies published between 1996 and 2024 are identified and analyzed in terms of their respective CX conceptualization, dimensionality, itemization, and adopted theoretical perspective to evaluate their theoretical rigor.

The findings reveal the existence of five main risks associated with the adoption of specific CX or related scales, including (1) defining experience with explicit reference to other extant constructs, (2) failure to accurately and comprehensively capture the experience, (3) experience-based tautology and theoretical indeterminacy, (4) experience-based composite constructs, and (5) lacking robustness of experience-based conceptual models. Based on these observations, recommendations are offered for scholars to improve the rigor of their adopted, refined, or proposed CX or related scales.

This article assesses the benefits and potential risks inherent in the adoption of particular CX scales, equipping researchers with a CX roadmap.

This study aims to explore the extent to which customer orientation and creative benefits offered by a firm may weaken rather than strengthen customer engagement. In doing so, it sheds new light on how customer orientation and creative benefits may facilitate rather than hinder engagement by customers.

A field study provides a test of the proposed effects in a hedonic consumption setting with 1,703 customers of an online dating service. Furthermore, an experimental study with 277 executives in a functional consumption setting (new mobile app) helps affirm the robustness of the field study findings.

This research theorizes and examines how communal relationship norms between customers and a firm, along with customers’ psychological empowerment, mediate the effect of customer orientation and creative benefits on customer engagement. A provocative finding of the study is that communal relationship norms help boost, whereas psychological empowerment reduces, the effects of both customer orientation and creative benefits on customer engagement.

The research examines different relationship norms and how they can become integral to customer–company relationships; this perspective helps reveal the underlying dynamics. It contributes to the literature on customer engagement by theorizing and demonstrating the link between customer orientation and customer engagement, two central constructs in the marketing literature. It theorizes and demonstrates that providing creative benefits brings about a direct competitive advantage for the product itself, and acts as a significant variable that explains the company−customer relationship.

The findings highlight the advantages and challenges associated with encouraging customer engagement. First, they suggest that companies emphasize their customer orientation and creative benefits. Second, managers should try to minimize the possible process of raising customers’ psychological empowerment while maximizing the impact of communal relationship norms.

This study identifies psychological empowerment as a key reason customer-oriented companies that provide creative benefits still struggle to engage their customers. It also suggests viable tactics to overcome barriers to enhanced customer engagement, such as by minimizing the effects of customers’ psychological empowerment while maximizing the impact of their perceived communal relationship norms.

The purpose of this study is to analyze the relationship between lean manufacturing and corporate environmental performance. Scholarly literature has extensively addressed the relationship between those two areas but empirical papers present mixed and inconsistent results, calling for further analysis to establish a clearer understanding of the actual relationship and to identify the causes of conflicting findings across studies. Given the importance of sustainable practices in the current business landscape, this paper aims to provide a comprehensive overview of this relationship through a meta-analysis of previous research, with a focus on integrating quantitative findings to shed light on the potential impact of lean manufacturing on environmental performance and report its intensity with Pearson’s correlation coefficient.

This paper analyzes the data from 29 primary studies published between 2001 and 2022 that have empirically measured the relationship between lean manufacturing and corporate environmental performance and that have been identified in the Web of Science and SCOPUS databases through an exhaustive review of the literature. To integrate previous empirical results and evaluate the evidence for the lean manufacturing’s influence on environmental performance, a meta-analytic methodology was adopted through the Hedges–Olkin random effect approach, based on correlations.

Main findings support the notion that a significant, positive, rather moderated, relationship exists between lean manufacturing and environmental performance, with an overall correlation coefficient r¯ = 0.25. The result seems robust, as several tests confirm that publication bias is unlikely. Overall, various lean practices are correlated to varying degrees with different measures of environmental performance. The environmental efficiency of external lean practices is higher than that observed for internal practices and quality management has a more pronounced effect than other internal lean practices. The 2008 global crisis did not change these relationships and the impact of lean manufacturing on environmental performance does not seem to be moderated by the degree of environmental awareness of the country where applied.

The results conclude that a significant, positive relationship exists between lean manufacturing and environmental performance (r¯ = 0.25). This study tests certain factors that exhibit varying effect sizes and moderate the overall outcome, highlighting that the environmental efficiency of external lean practices is higher than that observed for internal practices. In addition, it suggests a more pronounced effect of quality management among other internal lean practices.

This study provides companies with an opportunity to align their operational strategies with environmental sustainability goals. Understanding that various lean practices exhibit diverse levels of correlation with multiple measures of environmental performance, decision-makers can prioritize their efforts and apply the lean practices that have a stronger effect on the desired environmental outcomes to improve their environmental impact. Conversely, managers are aware that certain lean practices have a week relationship with some environmental performance so they can avoid overestimating environmental benefits of lean manufacturing. Finally, results underscore the importance of organizational commitment to environmental sustainability.

It is, to the best of the authors’ knowledge, the first meta-analytic study to investigate the strength of the association between lean manufacturing and environmental performance and to test whether various lean practices are correlated to different measures of environmental performance. It fills this gap in the literature and therefore it represents a valuable contribution to the field. In addition, this paper explores certain factors that moderate the overall outcome.

In recent decades, organizations globally have faced challenges in adopting disruptive innovation. This chapter explores the relationship between change management and adopting disruptive innovations. Through a systematic analysis of existing literature, common themes and trends in this field are identified. The present study employs a bibliometric and content analysis of 77 publications to analyze the role of change management in the adoption of disruptive innovation. Additionally, a framework is presented to facilitate the understanding of how change management influences the adoption of disruptive innovations within organizations. The research highlights that embracing disruptive innovation is not straightforward; it demands a well-thought-out change management approach. This approach should emphasize cultivating an environment that encourages and nurtures innovation. Creating a culture that empowers employees to take risks and explore new ideas is crucial. Additionally, organizational culture, leadership, communication, and employee engagement emerge as critical factors for the successful adoption of disruptive innovations in the workplace. In summary, it is important to recognize that the successful adoption of disruptive innovations within organizations relies on the successful implementation of change management initiatives.

This study aims to empirical tests an integrated framework of third-party travel apps usage antecedents (system quality, information quality, service quality and user engagement) and its consequences (satisfaction, apps love and behavioral intentions).

A quantitative research design was used, purposively interviewing 551 users of predetermined third-party travel apps. The data was analyzed using partial least squares-structural equation modeling.

The study found that system quality did not significantly impact user engagement, suggesting that users may prioritize content and service over technical features. Both information quality and service quality were positively linked to user engagement, confirming that users are more engaged when app content is relevant and service is adequate. Additionally, higher user engagement led to greater app satisfaction and love, positively influencing users’ behavioral intentions, such as continued use and recommendations.

The results highlight the importance of content and service quality over system features in driving user engagement with smartphone apps. This suggests developers should focus on delivering high-quality information and excellent service to foster user satisfaction and emotional attachment to the app.

The study suggests a shift in focus from technical features to content relevance and service effectiveness, highlighting that users may prioritize these aspects over technical aspects when engaging with an app. This could challenge conventional assumptions about the importance of system quality in user engagement.

本研究实证测试了一个综合框架, 分析第三方旅行应用使用的前因（系统质量、信息质量、服务质量和用户参与）及其后果（满意度、应用依赖和行为意图）。

采用定量研究设计, 有目的地访谈了551位预定的第三方旅行应用用户。数据通过偏最小二乘结构方程模型（PLS-SEM）进行分析。

研究发现, 系统质量对用户参与没有显著影响, 表明用户可能更关注内容和服务而非技术特性。信息质量和服务质量均与用户参与呈正相关, 证实用户在应用内容相关性高且服务得当时更具参与度。此外, 更高的用户参与度提升了应用满意度和依赖性, 进而正向影响用户的行为意图, 如持续使用和推荐。

结果强调了内容和服务质量在推动智能手机应用用户参与中的重要性, 相较于系统特性, 开发者应关注提供高质量信息和优质服务, 以提升用户满意度和对应用的情感依赖。

本研究表明, 用户在应用使用中可能更关注内容的相关性和服务的有效性, 而非技术特性, 这挑战了系统质量对用户参与重要性的传统假设。

This chapter reflects on a media studies project exploring Sylvia Plath poetry on Tumblr. The project ultimately resulted in excess digital data, with no conventional publications or research outputs. Now writing 10 years after data collection, I take a storying approach to explore the original research concerns and the research process, thereby locating a reconfigured ‘research event’ that draws together various biographical, social, political and historical factors. I reflect on my evolving understanding of ‘research’, discussing early teaching experiences and postgraduate pathways that partly structured a particular relationship to research. This serves to bridge a discussion about the challenges of the initial process over a decade ago, including the uncomfortable pairing of inexperience among aspiring researchers and institutional pressures to publish. I then discuss the theoretical perspectives that inspire and, in retrospect, offer clarity for the project, given the amount of time passed since data collection and the synergistic relationship between the storying approach, poststructuralist thought and story-focused methodologies. I argue that Tumblr provides unique opportunities for identity negotiation, aesthetic appreciation, data extraction and commodification, which highlights both the creative agency of digital aesthetic curation and self-work, as well as the importance of algorithmic transparency. I also contend that engaging with excess data led to methodologically and theoretically useful insights, challenging assumptions about the temporality of usable data and the ever-changing relationship between art, technology and freedom.