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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.

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.

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 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.

Food delivery apps (FDAs) have rapidly developed due to mobile technologies, changes in modern consumption and increased online use during the COVID-19 pandemic. Despite this, the platforms are struggling to build a stable customer base and make a profit. This study combined tech-driven motivators in an information system success model (ISSM) and emotional attachment operated by affect transfer theory (ATT) to explain why people might continue to use an FDA.

An online quantitative cross-sectional survey was carried out via the Prolific platform. Data were collected from 416 FDA users and analyzed to test the hypotheses using the partial least squares based structural equation modeling.

The study found that system quality, information quality and emotional attachment directly influence the continued use of FDA. Moreover, the results suggest that perceived social interactivity and perceived playfulness are significant antecedents of emotional attachment.

The findings of this study enrich the current literature on continuance intention in online food delivery services by integrating the technology- and affective-based factors. The findings also provide various practical implications for app designers and marketers to foster an emotional bond with users, resulting in high retention rate.

The study proposes the integrated framework of ISSM and ATT for enhancing understanding of consumer behaviors in the post-adoption stage for FDA.

Variations in customer expectations pose a challenge to service quality improvement in the airline industry. Understanding airline customers' expectations and satisfaction help service providers improve their offerings. The extant literature examines airline passengers' expectations in isolation, neglecting the overall impact of online reviews on service quality improvement. This paper systematically evaluates the airline industry's passengers' expectations and satisfaction using expectation confirmation theory (ECT) and the SERVQUAL framework. The paper analyzes online reviews to examine the relationship between airline service quality attributes and passengers' satisfaction.

The SERVQUAL framework was employed to examine the effects of customer culture, the reason for traveling, and seat type on customer's expectations and satisfaction across a large sample of airline customers.

A total of 17,726 observations were gathered from the Skytrax review website. The lowest satisfaction ratings were from passengers from the USA, Canada and India. Factors that affect perceived service performance include customer service, delays and baggage management. Empathy and reliability have the biggest impact on the perceived satisfaction of passengers.

This research increases understanding of the consumer expectations through analysis of passengers' online reviews. Results are limited to a small sample of airline industries.

This study provides airlines with valuable information to improve customer service by analyzing online reviews.

This study provides the opportunity for airline customers to gain better services when airline companies utilize the findings.

This paper offers insights into passengers' expectations and their perceived value for money in relation to seat types. Previous studies have not investigated value for money as a construct for passengers' expectations and satisfaction relative to service quality dimensions. This paper addresses this need.

Waste management is a crucial aspect of sustainable development, but is it economically sustainable for marginalized informal firms? The study tries to answer this question by revisiting the Porter–Wagner dilemma about the association between environmental management (EM) and firm performance (FP). The study looks into the various liquid waste management practices (LWMPs) adopted by them and the overall impact of LWMPs on firms' economic performance.

The study uses the latest available cross-sectional data source on Indian informal firms by the National Sample Survey Office (NSSO), 73rd survey round 2015–16. First, ordered logistic regression was used to analyse the factors that impact a firm's adoption of a particular LWMP. Subsequently, to capture the heterogeneity among the firms based on productivity and size, a quantile regression (QR) was employed to analyse the impact of LWMPs on firm productivity. Additionally, the propensity score matching technique was used to address endogeneity concerns.

The authors find that bigger, urban-located and female-owned firms adopt cleaner LWMPs that positively impact their economic performance. Furthermore, the QR analysis observed that the most productive firms could extract higher returns from adopting cleaner LWMPs, indicating the relevance of the Porter–Wagner dilemma, i.e. environmental and economic sustainability are possibly symbiotic, thus having a feedback mechanism.

To the authors’ limited knowledge, this is the first study analysing the relationship between EM and FP among the informal sector firms, which are away from any regulations or obligations. Since sustainability is a two-way process, policies should be devised that incentivise sustainable business practices.