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The purpose of this study was to comprehend the adoption of artificial intelligence (AI) technology-driven natural large language model (LLM)-based chatbots by customers.

A qualitative research study method was conducted. This was to explore managerial perspectives towards consumer centric technology adoption of AI plus LLM-based chatbots. This was specifically for AI-driven natural LLM-based chatbots services. The author conducted conducted in-depth personal interviews with 32 experts of digital content AI + LLM chatbot services. Thematic content analysis was undertaken to analyse the data.

The advent of natural language processing tools driven by AI technology chatbots has altered human-firm interaction. The research findings indicated that the push-pull-mooring (PPM) factors captured the phenomenon in the most comprehensive way. A total of 15 key factors influencing the adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction were identified in this study by the author. The thematic content analysis unraveled insights regarding transformed consumer adoptions towards AI-driven LLM-based chatbots by means of the PPM framework factors.

The empirical research investigation contributed to the literature on the PPM theoretical framework. This was specifically in the context of adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction.

The research study insights would help managers to restructure and reconfigure their organizational processes. This would neccessiated a shift in firm-customer interactions as demanded because of the availability of AI technology-driven natural LLM-based chatbots by customers.

This research study was based upon the PPM theoretical framework. This study provided a unique analysis of the altered firm customer interaction needs and requirements. This was one of the first studies that applied the framework of PPM theory regarding the adoption of AI technology-driven natural LLM-based chatbots by customers.

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.

Past research on luxury is fragmented resulting in challenges to define what the construct of luxury means. Based on a need for conceptual clarity, this study aims to map how research conceptualises luxury and its creation.

This study presents a scoping review of luxury articles published in peer-reviewed journals. Of the initial 270 articles discovered by using the database of Scopus, and after control searching in Web of Science and reference scanning, 54 high-quality studies published before the end of 2020 were found to meet the inclusion criteria and comprised the final analytical corpus.

The findings demonstrate that research approaches luxury and its creation from three different perspectives: the provider-, consumer- and co-creation perspectives. In addition, the findings pinpoint how the perspectives differ from each other due to fundamental and distinguishing features and reveal particularities that underlie the perspectives.

The suggested framework offers implications to researchers who are interested in evaluating and developing luxury studies. Based on the identified luxury perspectives, the study identifies future research avenues.

The study contributes to the luxury research stream by advancing an understanding of an existing pluralistic perspective and by adding conceptual clarity to luxury literature. It also contributes to marketing and branding research by showing how the luxury literature connects to the evolution of value creation research in marketing literature.

This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation targeted to the general audience. The proposed conceptual model suggests that innovation fits well with more abstract language because of the association of innovation with imagination and distal construal. Moreover, communication of innovation may benefit from greater adherence to the narrativity arc, that is, early staging, increasing plot progression and climax optimal point. These effects are moderated by content variety and emotional tone, respectively.

Based on a Latent Dirichlet allocation (LDA) application on a sample of 3225 TED Talks transcripts, the authors identify 287 TED Talks on innovation, and then applied econometric analyses to test the hypotheses on the effects of abstractness vs concreteness and narrativity on engagement, and on the moderation effects of content variety and emotional tone.

The authors found that abstractness (vs concreteness) and narrativity have positive effects on engagement. These two effects are stronger with higher content variety and more positive emotional tone, respectively.

This paper extends the literature on communication of innovation, linguistics and text analysis by evaluating the roles of abstractness vs concreteness and narrativity in shaping appreciation of innovation.

This paper reports conceptual and empirical analyses on innovation dissemination through a popular medium – TED Talks – and applies modern text analysis algorithms to test hypotheses on the effects of two pivotal dimensions of language on user engagement.

Existing research on customer journeys has tended to focus on the customer’s purchase decision-making and firm-controlled touchpoints, overlooking indirect touchpoints where customer resources and behaviors influence the firm and other actors, beyond financial patronage. This article develops the concept of engagement journeys and discusses their implications on journey design and management.

This conceptual article synthesizes the customer journey and engagement literature to delineate the concept of engagement journeys. Insights from engagement research are reflected in the current journey management orthodoxy to provide novel implications for the management of engagement journeys.

The engagement journey is defined as the customer’s process of diverse brand-related resource investments in interactions with the brand/firm and/or other customers, reflecting the customer’s cognitive, emotional and behavioral disposition. The analysis outlines the manifestations and nature of different types of touchpoints along the engagement journey, and the novel requirements for journey management.

The developed conceptualization opens up new avenues in both journey and engagement research.

Some commonly held assumptions regarding journey quality and management do not hold true for engagement journeys, so there is a need for new approaches.

Despite the proliferation of both journey and engagement research, only a handful of studies have considered the link between the concepts. The proposed novel conceptualization of an engagement journey breaks free from a predominant focus on purchase decisions. The analysis of engagement journeys and their management advances both customer journey and engagement research.

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.

Sailing toward sustainability is becoming the strategic focus of shipping firms. Drawing on organizational information processing theory (OIPT) and the theory of planned behavior (TPB), we investigated the impact of digital transformation (DT) on shipping firms’ sustainable management performance and the boundary conditions guiding this relationship.

The authors examined the hypotheses by employing hierarchical linear modeling on two-wave time-lagged data from 189 shipping firm employees in China.

The results suggest that a shipping firm’s DT is positively associated with its sustainable management performance and that the relationship is strengthened by having better cross-functional and customer coordination mechanisms. Furthermore, our three-way interaction analyses show that while injunctive norms in a shipping firm’s networks can strengthen the contingency roles of both cross-functional and customer coordination mechanisms, descriptive norms alone significantly influence customer coordination.

Drawing on organizational information processing and planned behavior theories, the present research provides new insights into leveraging DT for sailing toward sustainable success. Moreover, this study extends the current understandings of the boundary conditions of the relationship between DT and sustainable management performance by showing the two-way and three-way interaction effects of coordination mechanisms and subjective norms. The findings of the present research can be utilized as effective strategies for promoting sustainable management performance.

Drawing from cognitive dissonance theory (CDT) and attribution ambiguity theory (AAT), this paper aims to examine how employees interact with queer customers within the hospitality service and the ways that queer representations regulate emotions when discriminated against by normative gender roles.

This study used a mixed method. Study 1 used firm-level secondary data to analyze hospitality firms’ efforts in diversity, equity and inclusion (DEI) and the effects on firms’ profit margins and customer satisfaction. In Study 2, an experimental design was used to understand how employees’ assailing behavior toward queer customers interacts with employee feelings of guilt and impacts their sabotage and organizational citizenship behavior via self-serving bias. Study 3 further explored how queer customer victimization interacts with stress to influence their perceptions of organization DEI authenticity and corporate social responsibility (CSR) through resilience.

Hospitality firms’ DEI efforts were associated with varying outcomes, including higher profit margins but lower customer satisfaction, while guilt weakened the impact of employees’ assailing behavior on their outcomes and customer stress amplified the effect of assailing behavior on queer customers’ perceptions of DEI authenticity and CSR through resilience.

Hospitality organizations should take proactive measures to address self-serving bias among employees. Moreover, fostering an inclusive culture is crucial, with managers playing a pivotal role in facilitating discussions and creating an environment that values diversity, inclusivity and respect for all employees.

The study makes a remarkable contribution to hospitality literature by focusing on CDT and AAT in providing valuable implications for DEI advocators to be aware of the tensions between heteronormativity and queer representations in service encounters.

The COVID-19 pandemic has presented small-to-medium size enterprises (SMEs) with a massive and unexpected challenge that has caused many to adjust their operational standards. Perhaps the biggest change has been the shift to remote work and away from traditional office spaces. Thus, this study aims to explore the implications of this shift within the context of customer participation in the new product development (NPD) process.

Our study surveys 218 small-to-medium size business-to-business firms in the USA on a variety of questions revolving around their NPD processes, customer collaboration and the shift to remote work. The authors use structural equation modeling in the AMOS program to analyze the data.

The findings indicate that both customer participation breadth and customer participation depth positively impact new product performance. Furthermore, these relationships are found to be contingent upon whether firms rely on remote work during the collaboration process. The results show that accessing a broader variety of explicit customer insights (i.e., breadth) has become easier in the increasingly remote collaboration environment. However, as face-to-face customer participation in NPD has decreased, the prospect of gaining deep, tacit customer knowledge relevant to product development (i.e., depth) has become more challenging.

This study contributes to the knowledge-based view of the firm and the customer participation literature, and it also has implications for managers adjusting to the shift to remote work following the COVID-19 pandemic. The findings provide additional evidence that customer participation is an effective strategy for SMEs (Morgan et al., 2018), but remote work has both positive and negative implications regarding the type of external knowledge that is acquired during customer participation in NPD.

An emerging body of literature has pinpointed the role of supply chain structure in influencing the extent to which supply chain members disclose information about their internal practices and performance. Nevertheless, empirical research investigating the effects of firm-level relational embeddedness on network-level transparency still lags. Drawing on social network analysis, this research examines the effect of relational embeddedness on supply chain transparency and the contingent role of digitalization in the context of environmental, social and governance (ESG) information disclosure.

In their empirical analysis, the authors collected secondary data from the Bloomberg database about 2,229 firms and 14,007 ties organized in 107 extended supply chains. The authors employed supplier and customer concentration metrics to measure relational embeddedness and performed multiple econometric models to test the hypothesis.

The authors found a positive effect of supplier concentration on supply chain transparency, but the effect of customer concentration was not significant. Additionally, the digitalization of focal firms reinforced the impact of supplier concentration on supply chain transparency.

The study findings contribute by underscoring the critical effect of relational embeddedness on supply chain transparency, extending prior literature on social network analysis, providing compelling evidence for the intersection of digitalization and supply chain management, and drawing important implications for practices.