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Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

The retail industry is undergoing a significant digital revolution. Emerging technologies are changing the way shoppers interact with companies and shops, causing a significant upheaval in the business. The primary purpose of the research is to recognise the concept of retail along with its service applications and novel technologies that will drive the future around the world. Retailers must keep up with the latest technological advancements to remain competitive as the supply chain grows more intricate and consumers become more astute, tech-savvy, and gadget-literate about using multiple channels. The analysis indicates technologies including artificial intelligence (AI), smart labelling, beacons, augmented reality (AR), virtual reality (VR), drone deliveries, and Internet of Things (IoT) have emerged as future trends. It has been found that retailers need to have strong digital relationships to engage and interact with consumers as well as to mould and influence experiences. They can create connections to assist customers in making decisions that are beneficial to them. India’s retail industry is well-positioned to prosper in the dynamic market environment by adopting innovation and transformation and also centred on omnichannel tactics, which offer customers a seamless experience by giving them a comprehensive, single glance at each retail business from the comfort of their home or place of business. The application of literary works to explain the notion of Industry 4.0 in the retail sector while recognising and comprehending pertinent technological developments. This chapter establishes the groundwork for upcoming research on technologies that will eventually be utilised in retail management.

This chapter explains the phenomenon of artificial intelligence (AI) powered by big data in technology and its contribution in knowledge-based marketing in B2B and its impact on rational decision-making in B2B marketing that affects business performance. This chapter is literature review prepared by compiling and reviewing previous literature, studies, articles, books and other sources related to the contribution of big data-enabled AI to B2B marketing. According to the information analysed, the findings show that big data supported by AI plays a significant role in creating user knowledge, external knowledge and customer knowledge, all of which are factors that significantly influence the ability of business-to-business marketers to make rational decisions that affect the performance of their companies. This chapter explains to them the phenomena of AI powered by big data and its effect on B2B marketing rational decision that will enhance company performance and its contribution on knowledge-based marketing in B2B. This chapter contributes to understanding main functions and interactions of AI system powered by big data and how such a system helps in B2B marketing by generating knowledge about customers, users and markets.

This study investigates the impact of open branding on consumer brand attitudes, as mediated by brand warmth and brand competence, and moderated by power distance belief.

This study employs two one-factor (brand strategy: open branding vs closed branding) between-subject experimental designs and a 2 × 2, namely (open branding vs closed branding) × (power distance belief: high vs low) between-subject experimental design to test the hypotheses.

The study indicates that open branding can enhance consumer brand attitudes, and that brand warmth and brand competence mediate the impact of open branding on consumer brand attitudes. Furthermore, power distance beliefs (PDB) moderated these relationships. Specifically, the impact of open branding on consumers brand attitudes is stronger for consumers with low PDB than for those with high PDB.

Brand managers should consider adopting an open branding strategy to enhance consumers brand attitudes when encountering consumers’ unauthorized use of brand-related intellectual property. Additionally, when implementing an open-branding strategy, brand managers should use appropriate language to enhance consumers’ perceptions of brand warmth and brand competence.

This study contributes to the interactive marketing literature by empirically examining the impact of open branding on consumer brand attitudes. Furthermore, it investigates the underlying mechanism of how and the boundary conditions when open branding increases consumer brand attitudes, enriching the current knowledge.

Branding in the labor market is an important issue due to the growing importance of brand. This study aimed to analyze the term of trust in the employee- and employer-based brand equity for gray-, blue-, and white-collar workers using bibliometric analysis. The study design included the formulation of three research questions. Bibliometric data comprised 205 employee-based brand equity publications and 40 employer-based brand equity publications from the Scopus database. The analysis involved quantitative measures such as the number of publications and citations as well as the frequency of source types, authors, and countries. VOSviewer software mapped the co-occurrence of keywords in employee- and employer-based brand equity publications. These mappings revealed eight clusters related to employee-based brand equity publications and four clusters in terms of employer-based brand equity publications. The issue of trust has been analyzed in publications on employee-based brand equity; no such studies have been noted for employer-based brand equity. Employee- and employer-based brand equity has not been analyzed for various collar workers.

This study aims to help uncover corporate culture and values to attract and retain talent by understanding job reviews written by business-to-business (B2B) salespeople.

Over 40,000 job reviews on Glassdoor.com are analyzed by a dictionary-based content analysis tool, Linguistic Inquiry and Word Count (LIWC2015), to explore the links between corporate culture and linguistics characteristics of reviews as articulated by B2B salespeople. This study adopted a multidimensional scaling approach based on the nine cultural value scores to create a map of corporate profiles. A projection of the LIWC2015 scores on this map uncovers differences in language patterns and emotions expressed across the profiles.

Findings reveal a map of corporate profiles with two dimensions, namely, product-centricity and customer-centricity, that divide salesforce subculture into a 2 × 2 matrix of four types: Empathic Innovators, Product Pioneers, Customer Champions and Commodity Traders.

This study combined two data sets, scores on CultureX’s nine cultural values (agility, collaboration, customer orientation, diversity, execution, innovation, integrity, performance and respect) and job reviews on Glassdoor.com. This research seeks to develop profiles of the organizational culture and to use a blend of qualitative and quantitative methods. This study adds to the literature on salesforce subculture and showcases a solution to the methodological difficulty in categorizing and measuring culture.

This study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.

Using a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.

This study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.

This study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.

In the extant research on online knowledge communities (OKCs), little attention has been paid to the influence of membership fluidity on the coevolution of the social and knowledge systems. This article aims to fill this gap.

Based on the attraction-selection-attrition (ASA) framework, this paper constructs a simulation model to study the coevolution of these two systems under different levels of membership fluidity.

By analyzing the evolution of these systems with the vector autoregression (VAR) method, we find that social and knowledge systems become more orderly as the coevolution progresses. Furthermore, in communities with low membership fluidity, the microlevel of the social system (i.e. users) drives the coevolution, whereas in communities with high membership fluidity, the microlevel of the knowledge system (i.e. users' views) drives the coevolution.

This paper extends the application of the ASA framework and enriches the literature on membership fluidity of online communities and the literature on driving factors for coevolution of the social and knowledge systems in OKCs. On a practical level, our work suggests that community administrators should adopt different strategies for different membership fluidity to efficiently promote the coevolution of the social and knowledge systems in OKCs.

The study of mindfulness is still shown to be of interest in different aspects of organisations and/or businesses. Therefore, this study aims to present an integrative, multi-level model of mindfulness based on a holistic approach that can contribute to better governance practices and lead to competitive advantages.

To fulfil this aim, an extensive integrative review of the literature, from the main articles about this topic, was made.

This study shows that the concept of mindfulness, a conscious presence or full attention and its relation with organisations or firms’ personal, behavioural and social characteristics, in the current context of great adversity, uncertainty and unpredictability, is of interest at the individual, organisational and social level.

This conceptual study has important implications for both practice and theory. It demonstrates that mindfulness significantly impacts the manager/business person’s ecosystem at the individual, organisational and social levels, particularly in relation to Sustainable Development Goals.

This study introduces a comprehensive theoretical model that explains this relationship and organises information from a multi-level perspective. This approach can contribute to the advancement of theory by clarifying and discussing the role of mindfulness at the individual, organisational and societal levels. It also identifies opportunities and outlines future research directions, aiming to promote more sustainable development.

This paper aims to conduct an interdisciplinary systematic literature review (SLR) of fake news research and to advance the socio-technical understanding of digital information practices and platforms in business and management studies.

The paper applies a focused, SLR method to analyze articles on fake news in business and management journals from 2010 to 2020.

The paper analyzes the definition, theoretical frameworks, methods and research gaps of fake news in the business and management domains. It also identifies some promising research opportunities for future scholars.

The paper offers practical implications for various stakeholders who are affected by or involved in fake news dissemination, such as brands, consumers and policymakers. It provides recommendations to cope with the challenges and risks of fake news.

The paper discusses the social consequences and future threats of fake news, especially in relation to social networking and social media. It calls for more awareness and responsibility from online communities to prevent and combat fake news.

The paper contributes to the literature on information management by showing the importance and consequences of fake news sharing for societies. It is among the frontier systematic reviews in the field that covers studies from different disciplines and focuses on business and management studies.