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This study aims to explore what characteristics contribute to the definition of relevance in business-to-business (B2B) marketing research and how/why different strands of B2B marketing maintain or lose their relevance.

This study is conceptual. It adopts a performative-phenomenal standpoint for B2B marketing research and approaches relevance through the concept of episteme, which is considered pivotal for understanding this phenomenon.

This study proposes four axioms that define the characteristics of relevance in B2B marketing research and discusses their implications for scholars and practitioners. Consequently, an action plan for revitalizing B2B marketing research is developed, comprising learning and temporal dimensions, resulting in nine different relevance types.

The central argument put forward in this study is that different research strands of B2B marketing have deeply rooted epistemic underpinnings that influence their interpretation of relevance. Consequently, fostering dialogue between practitioners and scholars is considered necessary to sustain relevance in B2B marketing research. B2B scholars are urged to think beyond their subspecialized silos and acknowledge how the business environment and the various strands of B2B marketing congruently shape B2B marketing relevance, while also embracing research methods that bring them closer to business practice.

Marketing practitioners and academics continue to drift apart. This study puts forward three recommendations to bring marketing academics and practitioners closer together.

The study contributes to the B2B marketing literature by grappling with the theory-praxis gap and critically exploring what constitutes relevance in B2B marketing research.

Cause-related B2B marketing programs involve sponsoring organisations working with B2B suppliers with the help of non-profit organisations (NPOs) on practises relating to environmental friendliness, workforce diversity, human rights, safety, philanthropy and business ethics. The study aims to identify the combinatory factors driving the adoption of Digital B2B platforms for managing cause-related B2B marketing programs.

The study adopts an innovative approach of fuzzy-set qualitative comparative analysis (fsQCA) on data collated from top corporations in India supporting cause-related B2B marketing programs. Sponsoring organisations and NPO dyads (i.e. survey both) filled out an email survey on 264 cause-related B2B marketing programs.

The study establishes that the combination of technological, organisational and environmental factors would lead to the adoption of Digital B2B platforms in managing cause-related B2B marketing programs. The study identifies six combinations of these factors for adopting Digital B2B platforms within and across sponsoring organisations and NPOs.

The study findings would aid cause-related B2B marketers in developing Digital B2B platforms’ capabilities by understanding the different combinations of factors driving adoption. Digital B2B platforms’ capabilities can improve market performance if developed as core competencies.

The study findings would enable improvements in the implementation and performance of cause-related B2B marketing programs. Better management of cause-related B2B marketing programs would help increase beneficiary coverage and the realisation of societal goals.

To the author’s knowledge, this is the first study to apply the TOE framework in conjunction with complexity theory to explain the diffusion of adoption of Digital B2B platforms for managing cause-related B2B marketing programs.

While few studies have examined business-to-business (B2B) mobile application (app) usage, none have examined the challenges in developing these technological assets. This study aims to examine B2B marketing executives’ perceptions regarding benefits, barriers and facilitators in app development.

A survey of 311 B2B marketing executives at selling firms in the USA was conducted to identify key themes related to the benefits, barriers and facilitators in developing B2B apps. The research featured “open-ended” questions exclusively, and advanced textual and thematic analysis of executives’ responses produced several key themes.

Results show that the perceived benefit of lowering customer servicing and costs drives development more so than trying to realize new revenue opportunities (e.g. “saving” vs. “making” money). Achieving internal buy-in/participation was perceived as a larger barrier than the commitment of financial resources. Additionally, training and education were viewed as the strongest facilitators of an app’s success over its design and functionality. Implications for B2B firms are discussed.

The open-ended format of this research captures a greater breadth of perspectives at the expense of more granular analysis of any particular issue.

The themes generated from the responses offer novel insights into the benefits sought in developing an app, as well as the technological, organizational and environmental factors that act as barriers and facilitators. The open-ended format of this research captures a greater breadth of perspectives at the expense of a more granular analysis of any particular issue.

Drawing on justice theory, this study aims to investigate the determinants and consequences of post-recovery satisfaction in a business-to-business (B2B) sales environment. In addition, customer demandingness is used as a moderator in this study to assess the relationship between distributive justice (DJ), procedural justice (PJ) and interactional justice (IJ) and post-recovery satisfaction.

A conceptual framework was developed by testing five hypotheses based on data collected from 337 salesperson–customer dyads.

The findings of this study reveal that DJ, PJ and IJ are positively linked with post-recovery satisfaction. In addition, post-recovery satisfaction negatively impacts customer distrust. On the contrary, customer distrust positively influences value co-creation behavior and has a negative impact on trusting intention. Finally, the customer’s level of demandingness significantly and positively moderates the linkage between the dimensions of justice perception and post-recovery satisfaction.

Despite extensive literature on distrust, a research model that examines customers’ distrust attitudes toward service failure and B2B recovery satisfaction needs to be developed and validated. In this regard, the authors developed a framework to measure post-recovery satisfaction and its association with customers’ distrust in B2B a context.

ChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing realm. To address this gap, the current study explores ChatGPT’s application in marketing by mining social media data. Additionally, the study employs the stages-of- growth model to assess the current state of ChatGPT’s adoption in marketing organizations.

The study collected tweets related to ChatGPT and marketing using a web-scraping technique (N = 23,757). A topic model was trained on the tweet corpus using latent Dirichlet allocation to delineate ChatGPT’s major areas of applications in marketing.

The topic model produced seven latent topics that encapsulated ChatGPT’s major areas of applications in marketing including content marketing, digital marketing, search engine optimization, customer strategy, B2B marketing and prompt engineering. Further analyses reveal the popularity of and interest in these topics among marketing practitioners.

The findings contribute to the literature by offering empirical evidence of ChatGPT’s applications in marketing. They demonstrate the core use cases of ChatGPT in marketing. Further, the study applies the stages-of-growth model to situate ChatGPT’s current state of adoption in marketing organizations and anticipate its future trajectory.

This paper aims to integrate the consumption perspective within the Industrial Marketing and Purchasing (IMP) debate. The study delves into how consumer communities can be conceived like other network business actors. The perspective of sustainable new ventures (SNVs) in the fashion industry is adopted, considering their specific connection with consumer communities.

Adopting a multiple case study methodology, this paper uses a qualitative approach. Data collection mainly relies on interviews conducted with 10 SNVs in the fashion industry; this sector is a fertile ground for studying sustainability and consumer communities. For data analysis, the abductive approach of systematic combining is applied.

The paper identifies four distinct types of consumer communities and four roles that they can assume as business actors in the business network. Owing to their engagement in these specific roles, consumer communities become part of the SNVs’ network, akin to other business-to-business players.

This study represents one of the initial endeavors to introduce consumption into the IMP theoretical framework. In this paper’s conceptualization, consumer communities are groups of consumers and collective actors in the business network. Additionally, this study advances the research on sustainability as a network concept by including consumer communities’ roles in business networks.

Data-driven marketing is replacing conventional marketing strategies. The modern marketing strategy is based on insights derived from customer behavior information gathered from their facial expressions and neuro-signals. This study explores the potential for face recognition and neuro-marketing in modern-day marketing.

The study conducts an in-depth examination of the extant literature on neuro-marketing and facial recognition marketing. The articles for review are downloaded from the Scopus database, and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is then used to screen and choose the relevant papers. The systematic literature review method is applied to conduct the study.

An extensive review of the literature reveals that the domains of neuro-marketing and face recognition marketing remain understudied. The authors’ review of selected papers delivers five neuro-marketing and facial recognition marketing themes that are essential to modern marketing concepts.

Neuro-marketing and facial recognition marketing are artificial intelligence (AI)-enabled marketing techniques that assist in gaining cognitive insights into human behavior. The findings would be of use to managers in designing marketing strategies to enhance their marketing approach and boost conversion rates.

The uniqueness of this study lies in that it provides an updated review on neuro-marketing and face recognition marketing.

Future is rarely explicitly addressed or problematized in business network research. This study aims to examine the possibilities of developing a business actor’s future orientation to network studies and imports ideas and concepts from futures research to support the development.

The study is conceptual and interdisciplinary. The authors critically analyze how extant studies grounded in the sensemaking view and process research approach integrate future time and how theoretical myopia hinders the adoption of a future orientation.

The prevailing future perspective is restricted to managers’ perceptions and actions at present, ignoring the anticipation and exploration of alternative longer-term futures. Future time is generally conceived as embedded in managers’ cognitive processes or is seen as part of the ongoing interaction, where the time horizon to the future is not noticed or is at best short.

To enable a forward-looking perspective, researchers should move the focus from expectation building in business interaction to purposeful preparation of alternative future(s) and from the view of seeing future as enacted in the present to envisioning of both near-term and more distant futures.

This study addresses the growing need of business actors to anticipate future developments in the rapidly changing market conditions and to innovate and change business practices to save the planet for future generations.

This study elaborates on actors’ future orientation to business markets and networks, proposes the integration of network research concepts with concepts from futures studies and poses new types of research questions for future research.

This paper contributes to studies on the relationship between dynamic capabilities (DCs) and performance by showing how domain-specific DCs – international dynamic marketing capabilities (IDMCs) – affect the international performance of exporting firms in the context of extreme environmental dynamism – during the COVID-19 pandemic.

The authors focus on a sample of 277 exporting manufacturers from the post-transition economy of Poland. The authors use hierarchical multiple regression analysis to test this study's hypotheses.

This study's findings show that deployment of IDMCs by export manufacturers in the context of environmental jolts contributes to better performance, and this relationship is mediated by adaptation to foreign markets and product development capability. Additionally, this study's results reveal that the significant and positive indirect effect of IDMCs on international performance (through mediators) is, however, weakened under conditions of extreme environmental dynamism.

The limitations pertain to the cross-sectional nature of this study and the research sample, characterised by the dominance of export manufacturers of final products, the dominance of manufacturers operating in the business-to-business sector, or in the business-to-business and business-to-customer sectors simultaneously.

The study provides suggestions to managers on how to build resilience in international markets during turbulent times. These activities involve investments in IDMCs that support activities centred around product development and adaptation to foreign markets.

The novel construct of IDMCs is introduced and operationalized. The study empirically tests the direct and indirect relationship between IDMCs and performance contingent upon extreme environmental dynamism. The results demonstrate the boundary conditions for the effectiveness of these domain-specific DCs in such a research setting.