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The purpose of this study is to develop a model of a starting situation for relationship initiation in turbulent business networks.

The study is designed as an extreme single case study that takes its point of departure in a company’s bankruptcy in the Swedish automotive industry.

This study illustrates how a new business relationship can start from a resource combination previously controlled by one actor (i.e. a single company) in a turbulent business network, thereby bringing nuances to the common understanding that new relationships start in stable business networks where resource combinations are developed between actors in established business relationships.

Previous studies have stated that the development of a mutual orientation between actors leads to the formation of a business relationship. The business relationship then leads to resource adaptations between the two companies. The developed model, however, illustrates that this pattern can be reversed in situations of turbulence. Hence, previously adapted resources might lead to the formations of a business relationship. Based on this observation, the authors argue that there are reasons to question if previous models of business relationship initiation and development in business networks are adequately equipped for analysis in turbulent business networks.

Although the prior literature has identified the relevance of dealer participation for multinational enterprises (MNEs), it is unclear whether such participation could also be an important means for local dealers to learn from MNEs. By adopting local firms’ viewpoint, our study draws on organizational learning theory to examine how local dealers benefit from their participation with foreign suppliers in Africa.

The empirical setting is a combinative dataset of secondary data and primary survey of 164 small- and medium-sized local dealers with nine subsidiaries of a Chinese motorcycle company in six countries of Sub-Saharan Africa.

This research shows that dealer participation is positively associated with dealer performance, and this positive effect is stronger when local dealers operate in regions with low government corruption and high government support. However, the positive relationship is weaker when local dealers use the local tongue extensively but becomes stronger when their foreign suppliers have a high dealer coverage.

By taking a local-participant perspective, our study extends the participation literature to show how firms from a resource-constrained region may benefit from their proactive participation with foreign counterparts. Additionally, we identify the boundary conditions of institutional factors and strategic choices of local dealers and foreign suppliers, providing a nuanced understanding of firm behaviors in complex and uncertain markets.

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 user experience during the use of activities and services is a fundamental aspect for sports managers and can provide a competitive advantage. The purpose of this study was to identify the dimensions of experiential quality and the relationship of this construct with customer trust and customer satisfaction in achieving behavioral intention.

Using a convenience sampling technique, a total of 322 gym users in Turkey participated. A two-step approach was used to test both the model and the research hypotheses [confirmatory factor analysis (CFA) and structural equation modeling (SEM)].

The interaction quality, physical environmental quality, outcome quality and enjoyment quality were positively related to experiential quality. Similarly, the experimental quality was positively related to customer satisfaction and customer trust. Finally, customer satisfaction was related to behavioral intentions.

This study provides empirical evidence about the importance of experiential quality to gain a competitive advantage in the context of fitness centers.

The purpose of this study is to provide an in-depth understanding of the B2B customers’ perspective regarding salespeople’s social media use.

The study adopts a qualitative approach based on semi-structured interviews with 26 key informants performing their job in customer role in various industries.

The authors inductively identify five themes regarding the B2B customers’ perspective of social media use in B2B selling. These themes allow for valuable implications for social selling activities and expected outcomes.

Against a growing body of literature on drivers, best practices and outcomes of social media use by B2B salespeople, less attention has been paid to the customer’s side. The authors extend current research by providing a more complete picture of social selling activities and expected outcomes.

The purpose of this study is to look at the factors that drive people to participate in the sharing economy (SE). Based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), the study proposes a mathematical model. The study’s ultimate objective is to help businesses attract more involved customers and promote collaborative consumption as a sustainable alternative to typical consumption patterns. The study offers a conceptual framework established via a thorough literature review to examine Indian customers’ use behavior toward SE platforms. A one-sample two-tailed t-test is used to assess the framework’s efficacy. The research fills gap in the literature on the SE by investigating the factors that determine subjective norms (SN), attitudes (A), and perceived behavioral control (PBC). A framework is provided that takes behavioral intention (BI) contemplated as a mediating variable. The research improves TAM and TPB by including new factors such as technical characteristics. This research adds to the body of knowledge on the digital SE by underlining the relevance of usage behavior in comprehending Indian customers, where A, SN, and PBC are important aspects. The research presents a paradigm for better understanding customers’ attitudes and behaviors toward various SE platforms, which might help academics, practitioners, and policy makers situate their initiatives within the larger field of sharing. The study’s categorizations of Indian consumers’ A, SN, PBC, and BI toward the SE might potentially advise on future research and government policies.

Drawing on the social presence theory, this study aims to explore how supplier–customer social media interactions influence supplier observers’ trust in the customers and what mechanisms contribute to variation in trust experience.

A total of 36 semi-structured interviews were conducted with Chinese suppliers using WeChat for business-to-business interactions. Data were analyzed in three steps: open coding, axial coding and selective coding.

Findings reveal that varied trust is based not only on the categories of social presence of interaction – whether social presence is embedded in informative interactions – but also on the perceived selectivity in social presence. Observer suppliers who experience selectivity during social and affective interactions create a perception of hidden information and an unhealthy relationship atmosphere, and report a sense of emotional vulnerability, thus eroding cognitive and affective trust.

The findings contribute new understandings to social presence theory by exploring the social presence of interactions in a supplier–supplier–customer triad and offer valuable insights into business-to-business social media literature by adopting a suppliers’ viewpoint to unpack the mechanisms of how social presence of interaction positively and negatively influences suppliers’ trust and behavioral responses.

While previous research has demonstrated the positive effects of digital business strategies on operational efficiency, financial performance and value creation, little is known about how such strategies influence innovation performance. To address the gap, this paper aims to investigate the impact of a firm’s digital business strategy on its innovation performance.

Drawing on the dynamic capability view, this study examines the mechanism through which a digital business strategy affects innovation performance. Data were collected from 215 firms in China and analyzed using multiple regression and structural equation modeling.

The empirical analysis reveals that a firm’s digital business strategy has positive impacts on both product and process innovation performance. These impacts are partially mediated by knowledge-based dynamic capability. Additionally, a firm’s digital business strategy interacts positively with its entrepreneurial orientation in facilitating knowledge-based dynamic capability. Moreover, market turbulence enhances the strength of this interaction effect. Therefore, entrepreneurial-oriented firms operating in turbulent markets can benefit more from digital business strategies to enhance their knowledge-based dynamic capabilities and consequently improve their innovation performance.

This study contributes to the understanding of how a firm’s digital business strategy interacts with entrepreneurial orientation in turbulent markets to shape knowledge-based dynamic capability, which in turn enhances the firm’s innovation performance.

The COVID-19 pandemic has significantly affected service small- and medium-sized enterprises (SMEs), increasing the importance of understanding how these businesses can become more resilient and how service innovation can be an effective strategy to increase their adaptive capacity and survival. This study aims to examine the role of dynamic capabilities in service innovation as a factor explaining the resilience of SMEs in Puerto Rico and the Dominican Republic during the COVID-19 crisis and its impact on service innovation. Additionally, the authors assess whether service innovation has a significant impact on value cocreation in these businesses.

This study used a quantitative method by surveying 118 SME owners in Puerto Rico and the Dominican Republic. The data were analyzed using partial least-squares structural equation modeling.

The results reflect important theoretical contributions by analyzing resilience from an innovation perspective instead of a retrospective approach, which is an area that has not been analyzed in the literature. Additionally, theoretical contributions to marketing services in SMEs are discussed, which is an underresearched topic. The results advance by discussing the role of service innovation through the reconfiguration of resources and how this can be an effective strategy to increase value cocreation with customers during crises.

This study is original in that it analyzes resilience from the perspective of innovation, and not from a retrospective approach. It offers a vision in response to the need for studies that provide a clearer conceptualization of resilience in small businesses. This highlights the importance of considering regional differences and service innovation as effective strategies to enhance resilience and value cocreation with customers.

The research aims to explore the relationships between the digital capabilities of micro, small and medium enterprises (MSMEs), their participation in global value chains and their adoption of innovative business models. Additionally, the study investigates how the prior experiences of entrepreneurial failure may influence or moderate these relationships.

To address these research objectives, the study draws upon data obtained from the Flash Eurobarometer 486 survey, a comprehensive dataset that explores the challenges faced by 13,197 European MSMEs as they navigate the complexities of growth, the integration of sustainable business models and the incorporation of digital technologies. To test the proposed hypotheses, the research employs multivariate logistic regression analysis.

Digital capabilities are found to be positively associated with business model innovation, while integration into global value chains is linked to a higher likelihood of implementing new business models. Interestingly, entrepreneurial failure did not significantly influence the relationship between digital capabilities and the adoption of new business models. In contrast, entrepreneurial failure significantly moderated the impact of global value chain inclusion on business model innovation, particularly in MSMEs with a history of failure.

This article provides practical guidance to entrepreneurs and companies interested in enhancing their digital strategies and engagement in global value chains, considering the entrepreneurs' business histories.