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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.

The purpose of this paper is to investigate the impact of customer-focus on small medium enterprise (SME) performance from the perspective of a resource-based view (RBV).

This research study implemented a survey strategy to gather data from 255 respondents on the registered list of Ghana Enterprise Agency (GEA) in the eastern region of Ghana. Scales used to gather data were operationalized from previous research studies. A structural equation modeling (SEM) path analysis was used to estimate the impact of customer-focus on the performance of SMEs.

The outcomes of this study indicate that customer-focus has a significant positive impact on SME performance, hence backing the current demand for investigating the distinct influence of customer-focus on SME performance. The results show that customer-focus has a positive and significant relationship with financial performance, customer performance, internal business process performance and learning and growth performance, thus supporting the literature on the positive impact of customer-focus on SME performance. Therefore, customer-focus determinants used in this study, including co-creation, networking ties, customer insight and artificial intelligence marketing (AIM), are critical to the optimization of SME performance.

Notwithstanding the importance of this research study mentioned earlier, the study has limitations. Notably, the sample size of this study can be increased to capture SME respondents in other geographical zones that were not included in this study. Future research studies may address how business environment conditions moderate the relationship between customer focus and performance, and also the cause-effect of the relationship between customer focus and business environment conditions on SME performance.

The practical implications consist of two main items. First, this study empowers SME owners and managers to develop a customer focus technique as a central strategic goal in their quest for SME performance optimization. Second, SME owners and managers should progressively exploit the four determinants of customer focus which include co-creation, networking ties, customer insight and (AIM in order to accrue important resources for effective utilization of their customer focus competences as a way to enhance their performance.

This study is targeted at the sound development of SMEs to bring about poverty alleviation and employment. Poverty, unemployment and poor living standards are recognized as vital social challenges in most emerging economies. The establishment of customer focus as an important strategic capability provides opportunities for SME survival, profitability and growth.

Generally, the findings of this research study provide a strong backing to RBV perspective and the proposition that customer-focus and its determinants (i.e. co-creation, networking ties, customer insight and AIM) should be acknowledged as a vital strategic resource for optimizing the performance of SMEs. This research study also provides new knowledge contribution to the present body of knowledge on customer-focus orientation and management literature, particularly in the context of an emerging economy.

The purpose of this study is to examine the trends and developments of subscription business models (SBMs) over the past two decades.

The study extracted 469 documents (articles and reviews) from the Scopus database during 2000–2022 and analysed 132 documents (articles and reviews). A bibliometric methodology of scientific mapping was employed, including a cluster analysis based on the bibliographic coupling of documents. Content analysis was also conducted to reveal emerging trends in SBMs.

The study revealed six emerging themes in SBMs related to consumer behaviour, digital advertising, online news media, journal publications, circular economy and sustainability strategies.

The results of this study provide new and unique insights into the development and trends of SBMs over the past two decades and offer guidance for future researchers to investigate further the phenomenon of SBMs in emerging areas.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

Several high street retail banks are extending their brands into digital banking through fully digital, app-only neobanks, which have been described as traditionally-driven neobanks (TDNBs). These TDNBs are considered a form of brand extension, representing the increased complexity of branding banks and financial institutions. This study explicitly addresses the branding strategies employed by TDNBs.

This study has adopted a case study research design, using a multi-stage data collection strategy. Initially, interviews were conducted with bank managers, followed by interviews with customers. Later, user-generated content was extracted through verified reviews from the app store. Subsequently, these three strands of data were thematically analysed and triangulated, in order to gain a holistic understanding of the branding strategies used by TDNBs.

Three key themes emerged regarding the branding strategies of the TDNBs: aligning with the parent brand, reinforcing the digital experience, and enhancing the brand image.

This study contributed to the growing body of research on marketing, branding, and digital transformation of bank services. As more traditional banks are exploring opportunities to pivot and explore other fintech options, this study offers significant insights that will help in managing brand experience and promotion across customer journeys in the banking sector.

This study contributes to the growing body of research on marketing, branding, and digital transformation of bank services. Even as more traditional banks explore opportunities to pivot as well as other fintech options, this study offers significant insights to help manage brand experience and promotion across customer journeys in the banking sector.

While previous studies on banking and financial services have concentrated on traditional retail and high street banks, there is a need for a greater understanding of the brand positioning of digital banks, especially those created by traditional banks.

Data-driven marketing is replacing conventional marketing strategies. The modern marketing strategy is based on insights derived from customer behavior information gathered from their facial expressions and neuro-signals. This study explores the potential for face recognition and neuro-marketing in modern-day marketing.

The study conducts an in-depth examination of the extant literature on neuro-marketing and facial recognition marketing. The articles for review are downloaded from the Scopus database, and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is then used to screen and choose the relevant papers. The systematic literature review method is applied to conduct the study.

An extensive review of the literature reveals that the domains of neuro-marketing and face recognition marketing remain understudied. The authors’ review of selected papers delivers five neuro-marketing and facial recognition marketing themes that are essential to modern marketing concepts.

Neuro-marketing and facial recognition marketing are artificial intelligence (AI)-enabled marketing techniques that assist in gaining cognitive insights into human behavior. The findings would be of use to managers in designing marketing strategies to enhance their marketing approach and boost conversion rates.

The uniqueness of this study lies in that it provides an updated review on neuro-marketing and face recognition marketing.

This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger.

The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis.

The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency.

This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management.

Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations.

In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment.

This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.

Social commerce (s-commerce) has gained widespread popularity as a social platform where customers engage in resource-sharing activities such as information exchange, advice-seeking and expressing their opinions on mutual interests. However, existing studies have not fully comprehended the drivers of electronic customer-to-customer interaction (eCCI) and how such behavior contributes to the customer “stick” on s-commerce sites. This study develops the Motivation–Opportunity–Ability (MOA) theory and investigates the impact of MOA factors on eCCI, which in turn affects customer stickiness.

A survey was used to acquire data from 455 valid respondents, and the research employed a combination of fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling.

The results revealed associations between perceived self-efficacy, intrinsic motivation, tie strength with other customers, eCCI and customer stickiness.

Considering the limited availability of complete eCCI frameworks in existing scholarly works, the authors present valuable perspectives on the role of consumer characteristics as both antecedents and consequences of eCCI. Additionally, this study proposes a research agenda for the field of eCCI on s-commerce sites.

This study aims to investigate the conflicting views in supply chain and strategic management literature regarding cooperative supply chain relationships (CSCR) and firm performance. Supply chain literature suggests a universally positive impact of CSCR on performance, irrespective of a firm’s strategy. In contrast, strategic management literature contends that the effectiveness of CSCR depends on their alignment with the firm’s competitive strategy. The research aims to clarify this disparity, offering insights into the strategic use of CSCR for enhancing firm performance.

This paper theorizes the integration of perspectives for the impact of CSCR on firm performance by examining the relationships considering the alignment of cost leadership and product differentiation strategies with supplier and customer relationships. Plant-level survey data is analyzed using regression techniques to test four hypotheses.

All four main relationships (cost leadership, product differentiation, supplier relationship and customer relationship) on firm performance are statistically significant. However, cost leadership firms are better aligned to their chosen strategy when they have strong relationships with suppliers, whereas similar relationships with customers create misalignment, negatively influencing firm performance. In contrast, product differentiators benefit by investing in relationships with customers rather than with suppliers.

A firm’s performance does not solely depend on its CSCR efforts but on aligning them with the firm’s overall strategy. Therefore, managers need to be cognizant of the firm’s competitive strategy when investing in CSCR. Failing to do so could negatively impact firm performance and, eventually, its ability to compete in the marketplace.

Scholars have advocated for the importance of examining competing perspectives of phenomena, both within and across various bodies of literature, as cross-disciplinary analysis often brings enhanced focus and depth, leading to improved understanding. This research is one of the initial efforts to empirically analyze the varying perspectives on CSCR in supply chain and strategic management literature. This cross-disciplinary approach can yield a more integrated perspective.

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.