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Drawing from social comparison theory, this study investigates the factors influencing benign or malicious envy toward influencers and the effects of envy on social media users' choice of endorsed or rival brands.

A sample of 453 social media users was obtained to examine the research model.

Homophily and symbolism positively affect both benign and malicious envy. Credibility affects benign envy positively but malicious envy negatively. Deservingness affects malicious envy negatively but exerts no effect on benign envy. Benign envy has a greater influence on choosing brands endorsed by influencers than it does on choosing rival brands; these effects are more substantial under conditions of high perceived control. By contrast, malicious envy significantly affects the choice of purchasing rival brands; however, this effect is not influenced by perceived control.

This study unveils a key aspect of the endorser–follower relationship by analyzing the effect of envy toward social media influencers on followers' intention to purchase endorsed or rival brands. This study identifies the differential effects of two types of envy on brand choice.

When customers make their purchase decisions, they use all the available information from all the initiatives and behaviors that companies carry out with their stakeholders. This research aims to identify whether a company's financial performance and reputation determine the customer's perception of the company, which affects their engagement. This study is based on the theories of engagement, stakeholder and signalling. Are customers engaged solely based on their feeling of satisfaction, or do employees and brand value play a role in this engagement?

Secondary data was collected from 14 automotive companies and empirically tested through a longitudinal study over the period 2010–2018. For panel data analysis this study used weighted least squares.

The variables proposed in this research, firm value and corporate reputation, were significant for the analysed panel sample. Furthermore, employee satisfaction influences customer engagement as an independent and moderating variable, just like brand value.

This research contributes to the emerging stream of customer engagement research by combining insight as a company-initiated resource, with the sheer transaction, integrating data obtained from employees and customers in an international context.

The purpose of this paper is to investigate how customer relationship management (CRM) implementation affects internal capital allocation efficiency, the efficiency with which a firm allocates its capital across its business segments.

The authors use a statistical regression method to analyze a sample of 801 unique firms in the USA from COMPUSTAT and the Computer Intelligence database. This analysis examines the relation between CRM implementation and internal capital allocation efficiency and identifies the conditions under which firms benefit more from CRM implementation. They also use instrumental variables (IVs) to address endogenous concerns with a two-stage least squares (2SLS) model.

The authors find that CRM implementation is positively related to internal capital allocation efficiency. The results are robust to the 2SLS analysis with IVs. This positive relation is more pronounced for firms with effective internal control and for those operating in highly competitive markets.

The research implies that that CRM can have a significant cross-functional effect on corporate financing and budgeting. This also suggests that when chief marketing officers plan marketing initiatives and implement CRM, they should communicate to chief financial officers not only the direct effect but also the indirect strategic benefits of such initiatives to a firm.

The authors reveal a previously overlooked aspect of marketing accountability by suggesting marketing’s impact on internal capital markets. They also enrich the body of literature on CRM benefits by showing a cross-functional benefit from marketing to finance (or capital allocation).

Digitalization and marketing technologies have made it possible to overcome some barriers to pricing – a multidisciplinary field between marketing, finance and IT – and have set the stage for a paradigm shift in the pricing profession. Value creation, the pricing process, and price communication have been transformed by innovative business models and advanced algorithmic and human–machine solutions. This chapter synthesizes the literature to date and provides a comprehensive framework for an all-encompassing 360° pricing approach that broadens the understanding of pricing in the context of digital business across all steps of the price management process. Starting from product attributes and motivational beliefs in consumers' value assessment and adoption of (technological or digital) products or services, new business models and pricing models emerge in the digital economy, human–machine solutions for price implementation and repricing are increasingly applied, and price search and communication take place through a variety of digital communication channels. Each stage of this framework discusses concrete examples, highlighting the freemium strategy, the subscription model, price tracking and repricing tools, and digital price information channels such as e-commerce, marketplace, or price comparison platforms. The implications for price management in a digital, technology-driven landscape are discussed from the executive level to the analyst level.

The purpose of this paper is to present a framework of ideation pathways that organically extend the current stock of knowledge to generate new and useful knowledge. Although detailed, granular guidance is available in the strategy literature on all aspects of empirically testing theory, the other key aspect of theory development – theory generation – remains relatively neglected. The framework developed in this paper addresses this gap by proposing pathways for how new theory can be generated.

Grounded in two foundational principles in epistemology, the Genetic Argument and the open-endedness of knowledge, I offer a framework of distinct pathways that systematically lead to the creation of new knowledge.

Existing knowledge can be deepened (through introspection), broadened (through leverage) and rejuvenated (through innovation). These ideation pathways can unlock the vast, hidden potential of current knowledge in strategy.

The novelty and doability of the framework can potentially inspire research on a broad, community-wide basis, engaging PhD students and management faculty, improving knowledge, democratizing scholarship and deepening the societal footprint of strategy research.

Knowledge is open-ended. The more we know, the more we appreciate how much we don’t know. But the lack of clear guidance on rigorous pathways along which new knowledge that advances both theory and practice can be created from prior knowledge has stymied strategy research. The paper’s framework systematically pulls together for the first time the disparate elements of transforming past learning into new knowledge in a coherent epistemological whole.

This study investigates the impact of large-scale teaching in higher education on students’ preparedness for the workforce within the context of evolving labour market demands, the expansion of higher education and the application of high-impact teaching strategies. It synthesizes perspectives on employer work readiness, the challenges and opportunities of large-scale teaching and strategies for fostering a dynamic academia-industry feedback loop. This multifaceted approach ensures the relevance of curricula and graduates’ preparedness while addressing the skills gap through practical recommendations for aligning teaching methodologies with employer expectations.

The research methodically examines the multifaceted challenges and opportunities inherent in large-scale teaching. It focuses on sustaining student engagement, maintaining educational quality, personalizing learning experiences and cultivating essential soft skills in extensive student cohorts.

This study highlights the critical role of transversal skills in work readiness. It also uncovers that despite its challenges, large-scale teaching presents unique opportunities. The diversity of large student groups mirrors modern workplace complexities, and technological tools aid in personalizing learning experiences. Approaches like peer networking, innovative teaching methods, real-world simulations and collaborative resource utilization enrich education. The importance of experiential learning for augmenting large-scale teaching in honing soft skills is emphasized.

This manuscript contributes to the discourse on large-scale teaching, aligning it with employer expectations and the dynamic requirements of the job market. It offers a nuanced perspective on the challenges and opportunities this educational approach presents, providing insights for crafting engaging and effective learning experiences in large cohorts. The study uniquely integrates experiential learning, co-creation in education and industry-academia feedback loops, underscoring their importance in enhancing student work readiness in large-scale teaching.

Integrating artificial intelligence (AI) into various industries, including the financial sector, has transformed them. This paper aims to examine the influence of integrating AI, including machine learning, process automation, predictive analytics and chatbots, on financial institutions and explores its various aspects and areas. The study aims to determine the impact of AI integration on financial services, products and customer experience.

The research study uses quantitative and qualitative methods, as well as secondary data analysis. It investigates four AI subfields: machine learning, process automation, predictive analytics and chatbots.

The research findings indicate that integrating AI, particularly in machine learning and chatbot subfields, holds promise and high strategic potential for financial institutions. These subfields can contribute significantly to enhancing financial services and customer experience. However, the significance of predictive analytics integration and process automation is relatively lower. Although these subfields retain their usefulness, they might necessitate alternative workflows and tools that incorporate human involvement. Overall, AI integration minimizes human interactions and errors in financial institutions.

The research study contributes original insights by exploring the specific subfields of AI within the financial industry and assessing their strategic significance. It provides recommendations for financial institutions to adopt AI integration partially in multiple phases, measure and evaluate the impact of the transformation and structure internal units and expertise to strategize adoption and change.

This study aims to focus on the resource-based faultline of a top management team (TMT) and intends to investigate the impact of TMT resource-based faultline on corporate green innovation, by indicating the environmental management as a mediator and slack resources as a moderator to understand the relationship.

Based on the empirical data of Chinese listed manufacturing companies from 2008 to 2020, this study assesses the hypotheses using an OLS model with fixed effects of time and industry.

The results indicate that TMT resource-based faultline is significantly negatively correlated with corporate green innovation. The conclusion remains valid after endogeneity tests and robustness checks. Mechanism test shows that environmental management plays a mediating role in the association between TMT resource-based faultline and corporate green innovation. Moreover, slack resources diminish the negative association between TMT resource-based faultline and corporate green innovation.

The study not only expands the theoretical understanding of the deeper motivation of TMT faultline on corporate green innovation, but also provides a practical reference for optimizing the human resource allocation of the TMT and accelerating green transformation development.

The purpose of this paper is to set forth a conceptual model describing the actors and roles in ecosystems created to enable productive black entrepreneurship in the USA.

This paper provides a systematic literature review of entrepreneurship ecosystems. It further leverages such literature review by using an autoethnographic approach recommended by Guyotte and Kochacka (2016), drawing on the authors’ practical experience in studying, owning, educating or consulting employer businesses owned by persons of color in the USA and abroad.

Each actor in the ecosystem has practical wisdom and assets that can be shared and leveraged through interacting with the other actors either as role model institutions or capacity development institutions, thus mitigating social inequalities and boosting economic progress by extending entrepreneurial opportunities beyond those that are greatly resourced.

Our literature review is based on selected samples of relevant articles on entrepreneurship ecosystem research and ethnic minority entrepreneurship, and thus, is not exhaustive. The selection was partly influenced by the authors’ opinion of whether a given study was relevant or not to a black entrepreneurship ecosystem. There is the possibility that some relevant studies were excluded. Thus, other actors are encouraged to revise or adapt this model to inform their distinct roles and goals.

The proposed model can help actors involved in the operation or support of a black-owned business make optimal business decisions, enabling each actor to be instrumental in another’s understanding of how to facilitate the success of black American entrepreneurs and business owners and thus, deploy marketing campaigns to boost the visibility and role of each actor. These campaigns play a role in their entrepreneurial marketing efforts.

Responding to Gines and Sampson’s (2020) call, to the best of the authors’ knowledge, this paper is the first to explicitly provide a comprehensive black entrepreneurship ecosystem model that identifies the actors, roles and activities that can help black Americans address social inequalities that limit their ability to become a successful employer business. The proposed model may aid in deepening the theoretical discussion on entrepreneurial ecosystems and be of inspiration for the future works of scholars and practitioners interested in the entrepreneurship and marketing interface.

This study has conducted exploratory research to understand who should comprise the members of a resilient supply chain for promoting an entrepreneurial ecosystem of a startup project and to determine the mechanisms for the balanced coexistence of all stakeholders. This is necessary to ensure mutual benefits for all stakeholders, each of whom has multidimensional interests. Additionally, this supply chain must be able to withstand any potential disruption risks.

This research has employed a mixed-design approach. In this context, the study conducted an extensive qualitative and quantitative investigation, including 30 interviews and a survey involving 180 potential stakeholders in this supply network, respectively in the capital city of Bangladesh, Dhaka. The analysis of the interviews utilized principles of matrix thinking, while structural equation modeling (SEM) through LISREL was employed to understand cause-and-effect relationships.

Network, platform and governance—these three independent constructs have the potential to contribute to the dependent construct, a resilient supply chain, aimed at promoting an entrepreneurial ecosystem for startup projects. It has been revealed that the management of such projects depends on the rules and regulations within the ecosystem. An excellent governance mechanism is essential for this purpose. To facilitate coexistence, the establishment of a platform is crucial, where cooperation among all members is mandatory.

For practitioners, three distinctive but closely interdependent issues are explored and resolved in this philanthropic study. It has unfolded the elements of any startup project with essential settings.

The identification of the structural dynamics of potential stakeholders within the entrepreneurial ecosystem of startups is largely absent in existing literature. Therefore, there is a need to comprehensively investigate the entire network, including their roles, responsibilities and associations. This study makes a significant and novel contribution to the existing literature. Academics and practitioners alike have ample opportunities to learn from this new aspect of relationships across three distinct areas: the entrepreneurial ecosystem, startup projects and the development of a resilient supply chain.