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Given the intensified competitiveness in the wine retail industry, partnering with quality suppliers becomes critical to ensure a steady supply of high-quality products and sustainable business growth. This study aims to explore how wine supplier quality attributes impact wine retail businesses and if such effects differ depending on wine retail types.

Data were obtained from wine purchasing managers in Korea. To validate the proposed relationships, structural equation modeling was used. A multigroup analysis was conducted to test distinct roles of on/off-premise wine retail types within this research framework.

Results support the significance of supplier quality attributes in shaping the landscape of wine retail businesses. Operational and strategic benefits exhibited a positive effect on both financial performance and suppliers’ relationship satisfaction, thereby improving the intent to continue working with suppliers. This study revealed noteworthy distinctions in the effects of supplier quality attributes on operational and strategic benefits between on-premise and off-premise wine retailers.

Findings provide valuable insights to wine suppliers and buyers concerning the establishment of a mutually beneficial long-term interdependent relationship. The approach sheds light on the unique dynamics of wine retail types, contributing to a more comprehensive understanding of the distinct roles of supplier quality attributes on on-premise and off-premise retailers.

This study developed an integrative framework, emphasizing the importance of supplier quality attributes in the wine retail industry. This model offers valuable insights into creating favorable buyer–supplier relationships that result in mutual benefits for both wine retailers and suppliers.

Sharing co-owned information on social network platforms has become a common and inevitable phenomenon. However, due to the uniqueness of co-owned information, the privacy calculus theory based on a single information owner cannot explain co-owned information disclosure. Therefore, this study tries to investigate the underlying mechanism of users’ co-owned information disclosure from a collective privacy calculus perspective.

Through a survey of 740 participants, covariance-based structural equation modeling (CB-SEM) was used to verify the proposed model and hypotheses.

The results show that personal benefit, others’ benefit and relationship benefit promote users’ co-owned information disclosure by positively affecting personal distributive fairness and others’ distributive fairness perception. Meanwhile, personal privacy risk and others’ privacy risk prevent users’ co-owned information disclosure by negatively affecting personal distributive fairness and others’ distributive fairness perception. Besides, others’ information ownership perception enhances the positive effect of others’ distributive fairness perception on co-owned information disclosure intention. Furthermore, others’ information ownership strengthens the mediating role of others’ distributive fairness.

The findings of this study enrich the research scope of information disclosure and privacy calculus theory and help social network platform developers design collective privacy protection functions.

This study develops a collective privacy calculus model to understand users’ co-owned information disclosure on social network platforms, confirming the mediating role of collective distributive fairness and the moderating role of others’ information ownership perception in the process of collective privacy calculus.

The purpose of this study is to contribute to previous research on customer relationships by quantitatively examining differences in the monetary benefits obtained by consumers using social and commercial relationships to make purchases from small and medium-sized enterprises (SMEs).

Customer transaction and relationship data from an SME in the USA is used to quantitatively assess the value of different marketplace relationships in an entrepreneurial context. Tobit regression is used to empirically model and test the impact of specific relationship characteristics on customer discounts.

Customers using social connections to make purchases obtain significantly larger discounts than customers using commercial connections; customers using direct connections attain significantly larger discounts than consumers using indirect connections (referrals). Interestingly, when examined by connection type, direct and indirect connections do not produce significant differences for social connections, yet they yield notable differences for commercial connections. The findings provide valuable insights to entrepreneurs for understanding and managing customer relationships.

This study empirically demonstrates that social relationships can be both prevalent and influential in the marketplace. The methodology used to quantitatively assess the monetary value associated with different methods of engaging with SMEs allows objective comparisons among different types of customer relationships. Quantification also allows important relationship characteristics to be empirically examined, including how the relationships compare to one another and to nonpersonal marketing activities. Ultimately, these novel contributions generate important insights to help marketers and entrepreneurs better understand customer relationships.

This study aims to investigate the nature of relationships between consumers and green brands and notably their role in shaping green brand evangelism. More particularly, the study first focuses on the influence of green relational benefits (confidence, self-expression, socialisation and altruistism) on green brand loyalty and subsequently the direct effect of green brand loyalty on green brand evangelism.

Data were collected using an online survey administered to a sample of 101 graduated female consumers of green personal care and beauty brands. Partial least square structural equation modelling was used to test the hypothesized relationships of the proposed conceptual model.

The study results demonstrate the existence of a positive and direct impact of confidence, socialization and self-expression benefits on green brand loyalty, with a stronger influence of confidence compared to the other benefits. Green brand loyalty generates a positive green brand evangelism from consumers.

To promote green brand evangelism, managers should invest in actions that enhance consumer loyalty towards green brands through a combination of confidence, socialization and self-expression benefits.

Although previous studies have discussed how relational benefits contribute to the development of brand loyalty, the issue has not been examined from a green brand perspective. In addition, this paper explores the antecedents of green brand evangelism, which have not been sufficiently addressed in the existing literature.

As internet dividends are gradually disappearing, loyalty programs have become the panacea for monetizing traffic, attracting new customers and retaining existing customers. Improving their effectiveness has thus become key to enterprises’ market competitiveness. However, member customers’ hedonic adaptation to this relationship strategy undermines its effectiveness. Based on the hedonic adaptation theory, this study aims to analyze the process of member customers' hedonic adaptation to preferential treatment in loyalty programs and explore the boundary conditions of alleviating this effect.

This study surveyed 271 member customers in China and tested the hypothesized relationships using structural equation modeling and multigroup analysis.

Preferential treatment suffers from hedonic adaptation to member customer engagement and customer gratitude, and customer tenure is a key condition for these effects. Customer gratitude is an intermediary mechanism that explains the hedonic adaptation effect of preferential treatment to member customers engagement. In addition, the structural characteristics of loyalty programs form the boundary condition that alleviates hedonic adaptation. The authors found that high-tier and -payment strategies are more likely to mitigate hedonic adaptation of preferential treatment to customer gratitude.

This study elucidates the factors that influence the effectiveness of preferential treatment and provides constructive insights into customer relationship management and for improving enterprise performance.

Artificial intelligence (AI) is constantly evolving and is poised to significantly transform the world, affecting nearly every sector and aspect of society. As AI continues to evolve, it is expected to create a more dynamic, efficient and personalized education system, supporting lifelong learning and adapting to the needs and pace of each student. In this research, we focus on testing the model of AI acceptance in higher education (HE) through human interaction-based factors including attitudes, competencies and openness to experience. Perceived benefits were our expectation to enhance AI acceptance in HE.

To test the model, we collected data from Arab HE institutions by spreading an online questionnaire. The sample consisted of 1,152 of teaching staff and students in Arab region, which were selected randomly. Partial least squares structural equation modeling (PLS-SEM) was employed to determine the interrelated dependence of relationships among variables. Furthermore, processing analysis was conducted to ensure the reliability and validity of questionnaires, multicollinearity and factor loading, in which the items were tested one more time to ensure their validity after translation into Arab language.

Results reveal that adopted attitude, digital competency and openness to experience have positive and significant relationship with both perceived benefits and AI acceptance in HE in the Arab region. The results also demonstrate the indirect impact of digital factors on AI acceptance in existence of perceived benefits, which was important in the validation of the model.

The research contributes to AI acceptance theory and research by providing evidence of AI acceptance in the Arab region. As generative AI applications continue to expand and change, the way we accept and interact with them will be different. This model could be adopted by authorities to facilitate the acceptance of AI in Arab HE institutions.

How much variance in firm performance can be attributed to firms’ corporate political activities (CPA)? Under what conditions does CPA contribute to firm performance? To theorize and empirically tackle these questions, we build on the resource-based view (RBV) to theorize how CPA might improve or hinder firm performance, and specifically examine the direct relationship between firms’ investments in lobbying activities and their performance. We also expect firm growth rate to moderate the relationship between lobbying and performance.

We empirically test our hypotheses using large-scale longitudinal panel data from publicly traded US firms from 2008 to 2018.

Our analyses support our predictions of the double-edged sword effect of lobbying on firm performance. Moreover, our results show that this effect is steeper for firms with higher growth rates.

Our study contributes meaningful insights to strategy scholarship on the influence of nonmarket strategies, highlighting the relevance of firm-specific conditions in shaping the performance outcomes of such strategies. In particular, we make a contribution by identifying a nonlinear relationship between lobbying and firm performance, which is amplified in fast-growing firms compared to stagnant ones.

This chapter explores the critical relationship between doctoral faculty advisors and their students. It examines the varying interpretations, historical significance, roles and responsibilities, and structural and psychological factors that affect this relationship. Understanding these elements is essential for creating an environment that supports positive outcomes and wellbeing in doctoral faculty advisor–student relationships. The recommendations outlined in the chapter could serve as enablers or guidelines for purposeful advisement or mentoring in doctoral faculty advisor–student dealings.

The purpose of this study is to provide empirical evidence on a possible economic explanation for changes in borrowing costs of US private firms that are going public.

Using an OLS regression with firm fixed effects and the IPO as an information releasing event that alters information asymmetries between borrowers and lenders and relying on several proxies for pre-IPO information asymmetries, I analyze the impact of the IPO on changes in borrowing costs from before to right after an IPO of firms with high pre-IPO information asymmetries.

My findings indicate that small firms, firms with high R&D, firms with negative EBITDA and firms with a single lending relationship benefit more from going public by realizing larger decreases in borrowing costs after an IPO than firms with lower pre-IPO information asymmetries. The results are consistent with changing information asymmetries caused by the IPO event playing a role in changes in borrowing costs after the IPO. Furthermore, I provide empirical evidence that a reduction in the lender’s bargaining power due to the IPO event plays an important role in explaining changes in borrowing costs around that time.

This study uses a hand-collected data set of loans obtained from financial statements issued by US firms at the time of their IPO. As a result, I am able to comprehensively document changes of borrowing costs of US private firms going public and shed light on one of the economic forces behind those changes.

This study aims to perform the bibliometric analysis of the customer engagement (CE) literature, highlights the major research themes and classifies the subdomains. The study also identifies antecedents and consequences, as well as dimension evolution, and suggests future research directions.

This study used a comprehensive bibliometric approach using Scopus data from 2002 to January 2024. Advanced analytical techniques, including bibliometric and cocitation analysis using R and bibexcel, were used. In addition, machine learning (ML)-based Latent Dirichlet Allocation (LDA) was used to extract latent themes.

This study reveals the domain’s past trend and present research scenario. The thematic analysis of CE is classified into three phases. Document cocitation analysis provided four broad clusters: conceptualization and operationalization, value creation through engagement, building relationships with brands and engagement-social media interface. The antecedents and consequences are categorized and presented along with the evolution of the multidimensional nature of CE.

This study adds to the literature in two key ways. First, the entire scholarly production has been compiled into one frame. Second, multiple methods were used to unravel citation, cocitation and textual data. Furthermore, ML-based LDA was used to extract latent themes from clusters and future research directions were proposed.