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This paper aims to investigate the effect of top management’s customer interactions (TMCI) on customer satisfaction. This study argues that TMCI’s overall relationship with customer satisfaction follows an inverted-U shape due to its positive and disruptive effects on the customer relationship efforts of frontline service/sales employees (FSEs). This paper further investigates the frontline competence of both FSEs and the top management team (TMT) as moderators of the impact of TMCI on customer satisfaction.

The conceptual model was tested empirically using data from managers, frontline employees and customers of microfinance firms. A multilevel structural equation modeling approach was used to test the hypothesized model.

The results show that TMCI has a curvilinear relationship with customer satisfaction. The results also show that frontline employees’ collective efficacy attenuates this relationship by shifting the turning point of the curvilinear effect to the right. Furthermore, TMT frontline competence amplifies both the positive and negative effects of TMCI on customer satisfaction.

This study advances knowledge on the effects of TMCI on customer satisfaction and highlights the nuanced relationship between top management involvement and indicators of firm performance.

The findings show the importance of considering the frontline competence of both top management and frontline employees when encouraging TMCI in organizations.

To the best of the author’s knowledge, this study is one of the first to examine TMCI’s direct impact on customer satisfaction and propose the frontline competence of both top management and frontline employees as boundary conditions on this relationship.

The purpose of this study is to examine the role of interaction in supporting value co-creation during pre-purchase customer journey stages when selling professional B-to-B services. First, value co-creation in professional service firms (PSFs) is reviewed, and, second, the role of interaction in the different stages of a customer’s pre-purchase journey is explored, specifically in the context of B-to-B human resource management services.

Qualitative, semi-structured interview data was collected from potential B2B customers of a PSF in question, providing a broad coverage of prospective clients in architecture, engineering and IT sector.

In general, the findings of this study indicate that interaction plays a crucial role in pre-purchasing stages of a customer journey. In particular, these findings form understanding of how various interaction channels and content support PSF’s ability to co-create value with its prospects.

The existing research tends to concentrate on how value is created for existing customers, and far less attention has been paid to the perspective of prospects. This study contributes theoretically by providing novel insights into the current literature on value co-creation in PSFs by providing an understanding of how interactions in pre-purchase phases affect the co-creation of value from the perspective of prospects, which is a less researched viewpoint. Empirically, this study offers managers much-needed, context-specific knowledge of PSFs by comparing differences and pulling together similarities from each customer journey stage of PSF prospects.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

Previous research has studied interactive value formation (IVF) using resource- or practice-based approaches but has neglected the role of emotions. This article aims to show how emotions are correlated in problematic social media interactions and explore their role in IVF.

By combining a text mining algorithm, nonparametric Spearman's rho and thematic qualitative analysis in an explanatory sequential mixed-method design, the authors (1) categorize customers' comments as positive, neutral or negative; (2) pinpoint peaks of negative comments; (3) classify problematic interactions as detrimental, contradictory or conflictual; (4) identify customers' main positive (joy, trust and surprise) and negative emotions (anger, dissatisfaction, disgust, fear and sadness) and (5) correlate these emotions.

Despite several problematic social interactions, the same pattern of emotions appears but with different intensities. Additionally, value co-creation, value no-creation and value co-destruction co-occur in a context of problematic social interactions (peak of negative comments).

This study provides new insights into the effect of customers' emotions during IVF by studying the links between positive and negative emotions and their effects on different sorts of problematic social interactions.

This study aims to develop a comprehensive, theoretically grounded framework of customer-to-customer interaction (CCI) management, by revisiting three older services marketing models: the servuction model, the services marketing triangle and the services marketing pyramid.

Noting the lack of theoretical frameworks of CCI management, this study adopts a problematization approach to identify foundational services marketing models, question their underlying assumptions, develop an alternative conceptual framework and evaluate its adequacy for CCI management, on the basis of a systematic literature review and content analyses.

By revisiting the assumptions underlying three relevant models in the light of the present-day, technology-infused service environment, this study proposes a four-triangle CCI management framework encompassing four specific modes of CCI management: managerial decisions by the firm; frontline employees; the design of the physical environment; and technology. Furthermore, this study emphasizes the triadic relationships involving the focal customer, other customers and the four modes of CCI management. Building on these findings, this study concludes with an extensive research agenda.

To the best of the authors’ knowledge, this study represents the first scholarly effort in services marketing literature to provide a comprehensive, theoretically grounded framework of CCI management. With its basis in foundational models, the new framework is well-suited to address future challenges to service marketplaces too.

Online customer communities have become a strategic tool for business-to-business (B2B) firms to drive collaboration among customers around the company’s products and services. This paper aims to argue that the three social capital dimensions, that is, structural, relational and cognitive, themselves driven by brand community trust, can affect brand loyalty for the organization.

The authors use a survey to collect data and structural equation modeling to test the conceptual framework by collecting data from 214 participants across three online B2B communities operated by three technology firms in India.

Brand community trust is found to have a strong association with social network ties, identification and norm of reciprocity and shared vision. These three have concomitant effects on the quality of customer-to-customer (C2C) interactions. Such communication generates functional, emotional and social benefits, which, in turn, curate brand loyalty.

The authors’ findings guide community managers in leveraging such conversations in shaping customer loyalty for the corporate brand.

This work provides an integrated framework to explain the important role of C2C interactions in B2B online brand communities.

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.

Social media is widely regarded as a strategic resource to improve firm performance. However, there are mixed findings on how businesses can use social media for better performance. This study aims to propose and test a mechanism through which social media can influence firm performance.

A survey approach was used to collect data from 262 small businesses in South Africa. The data were analysed using structural equation modelling (SEM) to assess the hypothesised relationships.

The findings support the significant role of social media in fostering firm performance. It is observed that the use of social media influences firm performance through three key customer-centric constructs: the strength of customer–firm relationships, customer orientation and customer co-creation. Additionally, the relationship between the strength of customer–firm relationships and firm performance is moderated by customer co-creation.

The study provides new insights into the mechanism through which social media fosters firm performance. Due to a lack of universality in establishing the direct effect of social media use on firm performance, providing evidence of an indirect path becomes vital for advancing knowledge on social media use in business. As such, this study contributes to the literature on social media and entrepreneurship by demonstrating a novel mechanism through which social media influences firm performance.

This paper aims to recall the attention on a key challenge for customer relationship management related to the role of human agents in the management of the “switch point” for ensuring the effectiveness and efficiency in a customer-machine conversation.

This study contributes to the discussion about the firms’ approach to artificial intelligence (AI) in frontline interactions under the conceptual umbrella provided by knowledge management studies.

This paper provides a theoretical model for clarifying the role of human intelligence (HI) in AI-based frontline interactions by highlighting the relevance of the actors’ subjectivity in the dynamics and perceptions of customer-machine conversations.

An AI-HI complementarity matrix is proposed in spite of the still dominant replacement view.

Social media (SM) networks offer a golden opportunity for firms that particularly engage in international activities to set up sustainable customer relationships and improve competitiveness. The purpose of this study is to examine the influence of SM adoption on the export intensity (EI) of firms listed on Borsa Istanbul (BIST) for the years 2010–2020. The authors use social media index (SMI) to measure SM adoption and firm size (FSize) as a moderator on exploring the interaction of SM and EI.

Using a sample of 150 firms listed on the BIST Industrials Index, this study explores how the adoption of SM affects EI by using panel data analysis over the period of 2010–2020.

The results indicate that the SMI has a positive and significant effect on the EI. FSize positively moderates the interaction of SMI and EI, indicating that large firms benefit more from the SM in increasing export performance. The findings reflect high potential of EI improvement through adopting right SM policies in emerging markets.

The sample covers only public companies listed on the BIST Industrials Index. Future studies may extend the coverage and include multiple emerging markets to draw generalized results for the export-oriented firms. This research also analyzes solely four SM networks, i.e. Facebook, Instagram, Twitter and YouTube. However, there are many other SM networks that firms use in online marketing in foreign markets. Finally, this research did not discuss the potential factors that could influence the use of SM in emerging market firms.

This study denotes the significant role of SM adoption on the EI of firms in an emerging market setting from the perspective of resource-based view. It presents an insightful approach in understanding the mission played by SM networks in enhancing the EI of Turkish firms. Policymakers may use the findings to develop public support programs to promote the adoption and implementation of the SM among exporting firms in emerging markets.

The study provides evidence on the effects of SM adoption on the EI from the perspective of emerging countries. It also helps to gain a deeper understanding of how different SM platforms contribute to the internationalization of firms.