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In recent times, the field of corporate intelligence has gained substantial prominence, employing advanced data analysis techniques to yield pivotal insights for instantaneous strategic and tactical decision-making. Expanding beyond rudimentary post observation and analysis, social media analytics unfolds a comprehensive exploration of diverse data streams encompassing social media platforms and blogs, thereby facilitating an all-encompassing understanding of the dynamic social customer landscape. During an extensive evaluation of social media presence, various indicators such as popularity, impressions, user engagement, content flow, and brand references undergo meticulous scrutiny. Invaluable intelligence lies within user-generated data stemming from social media platforms, encompassing valuable customer perspectives, feedback, and recommendations that have the potential to revolutionize numerous operational facets, including supply chain management. Despite its intrinsic worth, the actual business value of social media data is frequently overshadowed due to the pervasive abundance of content saturating the digital realm. In response to this concern, the present study introduces a cutting-edge system known as the Enterprise Just-in-time Decision Support System (EJDSS).

Leveraging deep learning techniques and advanced analytics of social media data, the EJDSS aims to propel business operations forward. Specifically tailored to the domain of marketing, the framework delineates a practical methodology for extracting invaluable insights from the vast expanse of social data. This scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.

To substantiate the efficacy of the EJDSS, a detailed case study centered around reverse logistics resource recycling is presented, accompanied by experimental findings that underscore the system’s exceptional performance. The study showcases remarkable precision, robustness, F1 score, and variance statistics, attaining impressive figures of 83.62%, 78.44%, 83.67%, and 3.79%, respectively.

This scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.

This study aims to investigate the comprehensive conceptualization how digital marketing and its adoption increase the productivity of small and medium-sized enterprises (SMEs), as well as the impact of technological orientation, customer relationship management and digital marketing on SMEs’ business performance in emerging markets (EMs).

Anchored by social network theory, 178 SMEs were conveniently drawn from the National Board for Small Scale Industries now Ghana enterprise agencies in Ghana. The hypotheses were analysed using the SPSS package tool, and structural equation modelling was used, as well.

This study reveals that the conceptualization and adoption of digital marketing positively affect the performance of SMEs’ business management in EMs. In addition, a positive moderating effect of dynamism is observed in the relationship between digital marketing and SMEs’ business performance.

This study focuses only on SMEs from the Greater Accra and Ashanti regions of Ghana as an EM, and it proposes priorities for future research streams in both developed and emerging countries.

The findings encourage SMEs to develop quality digital marketing technologies, good customer relationships and technological orientation and customer relationship management competencies in EMs to maximise profit.

This paper fills considerable knowledge, evidence and contextual gaps in the literature on SMEs, entrepreneurship and marketing in EMs by presenting a comprehensive overview of how SMEs can use digital marketing in an EM context to achieve the following: customer acquisitions, satisfaction and retention; increased profitability; quality service delivery; value creation; and cost reductions.

The study seeks to explore the intricate dynamics among customer relationship management (CRM) practices, guest satisfaction and loyalty in the hospitality context. Additionally, it aims to examine the moderating influence of guest engagement on the relationships between CRM practices and guest satisfaction and loyalty.

An integrated theoretical framework is developed by incorporating CRM practices and guest engagement into the satisfaction-loyalty framework. Two research instruments were adapted from the literature to assess the perspectives of customers and employees in the hotel industry in Kashmir. The customer survey measured guest satisfaction, loyalty, and engagement, while the employee survey focused on CRM practices, including key customer focus and CRM organization. Data was collected using a pen-and-paper survey with convenience sampling across 10 qualifying hotels, each classified as 3-star or above. A total of 270 matched responses from guests and employees were obtained and analyzed using descriptive analysis, structural equation modeling (SEM), and moderation analysis with SPSS and AMOS software. The study utilized a rigorous data matching process to ensure reliability, with guest-employee pairs verified and cross-checked with hotel records.

The results indicate CRM practices play a pivotal role in shaping guest satisfaction and loyalty. Notably, personalization and a targeted customer approach emerged as the most influential factors in enhancing tourist satisfaction. Similarly, prospecting, personalization, and effective knowledge management significantly contributed to visitor loyalty. The establishment of robust relationships is underscored through collaborative active guest engagement. Furthermore, the study highlights the nuanced relationship between satisfaction and loyalty moderated by guest engagement. High levels of guest engagement amplify the positive impact of satisfaction on loyalty, while lower engagement levels attenuate this effect. Moreover, the moderating influence of guest engagement on the relationships between CRM practices and guest satisfaction and CRM practices and guest loyalty was notably strong at elevated guest engagement levels and relatively weaker at lower engagement levels.

While the study findings encourage organizations to prioritize customer relationship development, hospitality entities must emphasize the adoption of CRM philosophy and robust guest engagement measures. Actively involving guests in co-creating services can yield incremental benefits in terms of attracting, retaining, and effectively serving guests.

This study introduces novel dimensions to the existing CRM framework within the hospitality context, specifically exploring the impact of hotel-specific elements (personalization and prospecting) on customer satisfaction and loyalty. Furthermore, it innovatively investigates the moderating role of guest engagement in the satisfaction-loyalty relationship, expanding its scope to include the relationships between CRM practices and guest satisfaction and guest loyalty.

The purpose of this study is to contribute to previous research on customer relationships by quantitatively examining differences in the monetary benefits obtained by consumers using social and commercial relationships to make purchases from small and medium-sized enterprises (SMEs).

Customer transaction and relationship data from an SME in the USA is used to quantitatively assess the value of different marketplace relationships in an entrepreneurial context. Tobit regression is used to empirically model and test the impact of specific relationship characteristics on customer discounts.

Customers using social connections to make purchases obtain significantly larger discounts than customers using commercial connections; customers using direct connections attain significantly larger discounts than consumers using indirect connections (referrals). Interestingly, when examined by connection type, direct and indirect connections do not produce significant differences for social connections, yet they yield notable differences for commercial connections. The findings provide valuable insights to entrepreneurs for understanding and managing customer relationships.

This study empirically demonstrates that social relationships can be both prevalent and influential in the marketplace. The methodology used to quantitatively assess the monetary value associated with different methods of engaging with SMEs allows objective comparisons among different types of customer relationships. Quantification also allows important relationship characteristics to be empirically examined, including how the relationships compare to one another and to nonpersonal marketing activities. Ultimately, these novel contributions generate important insights to help marketers and entrepreneurs better understand customer relationships.

Based on relationship marketing theory, this study aims to test the effect of social customer relationship management (social CRM) on customer satisfaction (CS) and loyalty (CL).

To assess the proposed framework, structural equation modeling was performed on the data of 314 automotive customers surveyed online.

Social CRM dimensions [traditional CRM (TCRM) and social media (SM) technology use] have a direct and positive effect on CS. On the other hand, only TCRM has a direct and significant influence on CL, while the SM technology use effect seems to be indirect rather than direct. Indeed, the findings have provided empirical support for the contention that CS plays a mediating role between social CRM dimensions and CL.

In the automotive sector and developing countries in particular, companies’ managers could increase CS and CL and consequently enhance their competitiveness and market share by adopting an effective social CRM strategy. From this perspective, companies should focus their social CRM campaigns on the most SM used by customers, offer personalized choices and improve customer experience, interaction and value co-creation.

This paper enriches the understanding of how social CRM can affect CS and CL. The scales of social CRM, CS and CL were validated in the context of developing countries and the automotive sector. Furthermore, the direct and mediating effect of CS between social CRM (TCRM and SM) and CL was also confirmed.

Basándose en la teoría del marketing relacional, este estudio pretende comprobar el efecto de la gestión social de las relaciones con los clientes (CRM social) sobre la satisfacción y la fidelidad de los clientes.

Para evaluar el marco propuesto, se realizó un modelado de ecuaciones estructurales sobre los datos de 314 clientes de automoción encuestados online.

Las dimensiones del CRM social (CRM tradicional y uso de tecnología de medios sociales) tienen un efecto directo y positivo en la satisfacción del cliente. Por otro lado, solamente el CRM tradicional tiene una influencia directa y significativa en la fidelidad del cliente, mientras que el efecto del uso de la tecnología de medios sociales parece ser más indirecto que directo. De hecho, los resultados han proporcionado apoyo empírico a la afirmación de que la satisfacción del cliente desempeña un papel mediador entre las dimensiones del CRM social y la fidelidad del cliente.

Este artículo enriquece la comprensión de cómo el CRM social puede afectar a la satisfacción y la fidelidad de los clientes. Las escalas de CRM social, satisfacción del cliente y fidelidad del cliente se validaron en el contexto de países en vías de desarrollo y del sector automovilístico. Además, también se confirmó el efecto directo y mediador de la satisfacción del cliente entre el CRM social (CRM tradicional y medios sociales) y la fidelidad del cliente.

En el sector de la automoción y en los países en desarrollo en particular, los directivos de las empresas podrían aumentar la satisfacción y fidelidad de sus clientes y, en consecuencia, mejorar su competitividad y cuota de mercado adoptando una estrategia eficaz de CRM social. Desde esta perspectiva, las empresas deberían centrar sus campañas de CRM social en los medios más utilizados por los clientes, ofrecer opciones personalizadas y mejorar la experiencia del cliente, la interacción y la cocreación de valor.

基于关系营销理论, 本研究旨在检验社会化客户关系管理（social CRM）对客户满意度和忠诚度的影响。

为评估所提出的框架, 对 314 名汽车客户的在线调查数据进行了结构方程建模。

社交客户关系管理维度（传统客户关系管理和社交媒体技术使用）对客户满意度有直接的积极影响。另一方面, 只有传统客户关系管理对客户忠诚度有直接和显著的影响, 而社交媒体技术使用的影响似乎是间接而非直接的。事实上, 研究结果为客户满意度在社交客户关系管理维度和客户忠诚度之间发挥中介作用的论点提供了实证支持。

本文丰富了人们对社交客户关系管理如何影响客户满意度和忠诚度的认识。本文以发展中国家和汽车行业为背景, 对社会化客户关系管理、客户满意度和客户忠诚度的量表进行了验证。此外, 还证实了客户满意度在社会化客户关系管理（传统客户关系管理和社会化媒体）与客户忠诚度之间的直接和中介效应。

尤其是发展中国家, 企业管理者可以通过采取有效的社交客户关系管理战略, 提高客户满意度和忠诚度, 进而增强竞争力和市场份额。从这个角度来看, 企业应将社交客户关系管理活动的重点放在客户使用最多的社交媒体上, 提供个性化选择, 改善客户体验、互动和价值共创。

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.

Underpinning social identity theory (SIT) and service-dominant logic (SDL), the current paper seeks to explore the effect of self-presentation on online brand advocacy (OBA). Furthermore, this paper investigates the mediating role of hedonic value and the moderating role of customer interaction with e-commerce websites (i.e. Amazon, Walmart and eBay).

Data were collected from customers of three e-commerce platforms (i.e. Walmart, Amazon and eBay) using a structured questionnaire – multi-group analysis applied on SmartPLS 4.4.

Self-presentation has a positive role in increasing hedonic value and its impact on OBA. The moderating effect of customer interaction on these relationships is also investigated and found to be significant.

Our findings underscore the significance of fostering inclusive online communities and favorable online settings. Existing findings are consistent with overarching objectives of digital empowerment and enhanced online interaction quality. This paper contributes to harmonious and collaborative digital societies by encouraging personalized experiences that foster a sense of belonging among diverse customers.

This paper adds to the existing body of knowledge by comparing customer behavior on three major e-commerce platforms, going beyond the traditional focus on a single platform. Drawing on SIT and SDL, this paper provides a distinct nomological framework for OBA that unifies disparate constructs, filling theoretical gaps in our understanding of online customer behavior.

The purpose of this study is to examine the influence of knowledge creation (KC) process on customer relations management (CRM) in Palestinian commercial banks, taking into consideration which factors of KC process support the CRM system.

The study uses a quantitative research design wherein questionnaires have been used to collect data from 345 respondents in the Palestinian banking sector. Research hypotheses have been tested using multiple regression analysis.

The findings unveil that socialisation and combination processes have a positive impact on CRM. In contrast, internalisation process negatively affects CRM system, but outsourcing knowledge does not significantly affect CRM.

Past studies empirically validated the success of CRM adaptation in the context of different industries. This study provides a new conceptual model which validates the influence of KC on CRM in the banking sector. It also affirms the integral role of KC in supporting CRM from an emerging country perspective like Palestine.

This study offers new insights into creating of knowledge by employees in supporting CRM. It will encourage future scholars to further explore the key dimensions of the KC process for a more detailed investigation at a workplace. This study suggests that banks’ directors and employees should behave in a social manner to support relationship with customers. This study also suggests facilitating knowledge from different resources in innovative ways, through encouraging creative thinking from experiences, using technology in sharing knowledge, focussing on appropriate training to resolve customers' problems and disseminating new knowledge among employees.

This study expands the body of knowledge on KC process in supporting CRM from an emerging country perspective. This study validates the influence of KC on CRM in the Palestinian banking sector. This sheds light on the integration of these two concepts.

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 research addresses the critical challenge of fostering customer loyalty within the highly competitive landscape of the insurance industry. The study investigates the interplay between customer satisfaction, loyalty, and the influence of technology and service quality in the context of insurance services and in periods of crisis.

A quantitative research approach was employed, utilizing a structured questionnaire distributed among diverse insurance customers in Lebanon during crisis conditions. The data were analyzed using SPSS-Amos, incorporating descriptive statistics, correlation analysis, and structural equation modeling (SEM).

This research emphasizes the crucial role of customer satisfaction in fostering loyalty in the insurance sector, especially during crises. High satisfaction levels, influenced by user-friendly online platforms, positively correlate with increased customer loyalty. Technology plays a vital role in maintaining and improving satisfaction, making it a key driver during challenging times. Positive interactions between service quality and satisfaction further highlight the multifaceted impact of technology on shaping customer loyalty.

The research findings provide valuable insights with practical implications for insurers aiming to boost customer loyalty. The study recommends strategic investments in critical areas like claims processing, customer service, communication strategies, digitalization initiatives, and employee training. The study provides insights applicable particularly to insurance companies navigating crisis conditions.

This research contributes both to academic understanding and practical applications by shedding light on the distinctive challenges and opportunities faced by insurers in cultivating customer loyalty within the insurance industry during crisis. The elucidations provided serve as a foundation for developing targeted strategies to address these challenges and to leverage opportunities for enhanced customer loyalty.