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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.

This study explores the role of institutional pressures and top management support in digital corporate social responsibility (CSR) adoption. It also investigates the impact of digital CSR on social trust and corporate sustainability.

Data were collected from 279 managers of Jordanian companies. Smart PLS was utilized to analyze the research model and test hypotheses.

The results reveal that coercive pressures, normative pressures, memetic pressures and top management support significantly impact digital CSR adoption. The results also show that digital CSR significantly impacts social trust and corporate sustainability.

This study provides worthwhile insights into the literature on drivers of digital CSR, social trust and corporate sustainability in unprecedented crises. This study enriches the literature on the relationship between institutional theory and innovative IT solutions adoption theories. The review of prior research confirms an absence of empirical examinations of the causal relations among institutional forces, digital CSR, social trust and corporate sustainability.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

This study aims to delve into entrepreneurs’ perceptions and interpretations of short video marketing on TikTok.

In light of the study’s exploratory nature, a qualitative approach was used. The authors conducted in-depth interviews with 17 entrepreneurs to uncover their insights on short video marketing via TikTok. Data analysis was carried out using thematic analysis and NVivo, and rigorous measures were in place to ensure the quality of the study.

This study’s findings suggested that entrepreneurs’ usage of TikTok is customer-oriented, with the purposes of promoting their businesses, generating word-of-mouth and managing customer relationships. As such, the gratification of connection with their audience, entertainment and information provision needs motivate entrepreneurs’ use of TikTok for social media marketing. Additionally, entrepreneurs’ use of TikTok may also contribute to their gratification of creativity and spontaneity needs, which may otherwise be limited in the context of other social media platforms.

This study expands the previous literature on entrepreneurship, social media marketing and the uses and gratification approach by revealing the specifics, nuances and dynamics of TikTok marketing from the entrepreneurs’ emic perspective.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

This study explores the mediating role of marketing management in the relationship between online presence and product innovation among Small and Medium Enterprises (SMEs).

The sample comprises 205 Costa Rican SMEs collected by the Global Competitiveness Project during the first half of 2019. The data were analyzed using a two-stage modeling strategy for ordinary regression models to analyze mediation effects.

Marketing management as a strategic resource or capability accounts for the relationship between online presence and product innovation performance in SMEs, meaning that online presence resources require complementary organizational capabilities in marketing management to enhance product innovation.

This study, grounded in the resource-based view theory, contributes to the innovation field by identifying marketing management capabilities as an intermediate strategic interaction between online presence and product innovation performance in SMEs. Thus, managers should recognize the advantages of integrating marketing management principles and tactics into online presence tools to realize the value of their products by tailoring them to their client’s needs.

There is limited research examining the relationship between social media and green food purchasing behaviour. In the current study, we examine the factors that affect consumers’ green food purchasing behaviour in Türkiye.

Data collected from the participants by survey method were analysed using Smart PLS 4.0 with IBM SPSS 26 and PLS to run SEM.

Our findings have revealed that from all the structural elements in the theory of planned behaviour (TPB), only attitude and perceived behavioural control contribute to consumers’ green food purchasing behaviour, while subjective norms do not contribute to consumers’ green food purchasing behaviour. Additionally, it was found that social media usage (SMU) and digital marketing interactions (DMI) have a positive and significant effect on green food purchasing behaviour. More information, experiences, opinions and recommendations on green foods in social media channels can encourage consumers to buy more green food.

This study first evaluates the applicability of the TPB model in explaining green food purchasing behaviour. This study is extended with two new factors included in the original framework of the TPB model, namely, SMU and DMI.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

With the rapid development of social media, many organizations have begun to attach importance to social media platforms. This research studies the management and the use of social media in academic music libraries, taking the Center for Chinese Music Studies of the Chinese University of Hong Kong (CCMS) as a case study.

We conducted a sentiment analysis of posts on Facebook’s public page to analyze the reaction to the posts with some exploratory analysis, including the communication trend and relevant factors that affect user interaction.

Our results show that the Facebook channel for the library has a good publicity effect and active interaction, but the number of posts and interactions has a downward trend. Therefore, the library needs to pay more attention to the management of the Facebook channel and take adequate measures to improve the quality of posts to increase interaction.

Few studies have analyzed existing data directly collected from social media by programming based on sentiment analysis and natural language processing technology to explore potential methods to promote music libraries, especially in East Asia, and about traditional music.

In the present era, digital technology can be used responsibly to provide developed and developing countries with high-quality health-care services to nations. This study aims to explore Saudi Arabia’s intentions to adopt digital health-care practices.

To be consistent with previous studies, this study used a quantitative methodology to collect the data from health-care professionals working in Saudi Arabia’s public and private health institutes. Consequently, this study’s findings are based on 306 valid samples.

On the one hand, the path analysis reveals that health-care professionals believe in perceptions relating to the use of e-health and technology (PEHT) and experiences regarding internet use (ERIU) and that these have positive and significant effects on attitudes toward the use of e-health and technology (ATEHT) and intentions to use e-health services (ITUES). On the other hand, barriers to using e-health (BUEH) negatively impact ATEHT and ITUES. Finally, ATEHT also has a positive and significant effect on ITUES.

This study’s findings will help Saudi Arabia’s policymakers and the country’s health ministry to develop policies to provide e-services that health-care professionals can use to improve the quality of the country’s health care, patients’ human rights and social care. Furthermore, this study’s findings are helpful in developing attitudes and intentions toward either e-health or digital health to provide better health facilities to serve Saudi Arabia’s citizens.

This study empirically confirms among Saudi Arabia’s health-care professionals the PEHT, ERIU and BUEH toward ATEHT and ITUES.