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The study aims to propose an instrument for measuring product-centeredness (i.e. the extent to which comment content is related to a product) using word embedding techniques as well as explore its determinants.

The study collected branded posts from 205 Instagram influencers and empirically examined how four factors (i.e. authenticity, vividness, coolness and influencer–product congruence) influence the content of the comments on branded posts.

Post authenticity and congruence are shown to have positive effects on product-centeredness. The interaction between coolness and authenticity is also significant. The number of comments or likes on branded posts is not correlated with product-centeredness.

In social media influencer marketing, volume-based metrics such as the numbers of likes and comments have been researched and applied extensively. However, content-based metrics are urgently needed, as fans may ignore brands and focus on influencers. The proposed instrument for assessing comment content enables marketers to construct content-based metrics. Additionally, the authors' findings enhance the understanding of social media users' engagement behaviors.

The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers one’s intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience.

The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently.

The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models.

Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverse’s experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverse’s economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust.

In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators.

The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models.

Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual).

Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique.

The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively.

This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

Academics and businesses alike have begun to recognise sustainability as a vital component of supply chain competitive advantage in recent years. Inconclusive results have been found in empirical studies of sustainable supply chain management (SSCM) that have ignored contextual variables concerning the dynamic role of firm capability in favour of testing alternative assumptions about the effect of various elements of the triple bottom line (TBL) on firm performance outcomes. The present study examines whether and how firm capabilities mediate the connection between SSCM, from a TBL standpoint, and firm financial performance outcomes.

Using the stakeholder theory, the study employed 325 survey responses from firms operating in different industries in Ghana (a less-researched context but one that plays a key role regarding SSCM practices) and the partial least squares structural equation model (PLS-SEM) technique to simultaneously assess the relationships amongst the variables.

It was discovered that the connections between all the TBL facets of SSCM practices and firm performance are positive and significant, and these relationships are mediated by firm capabilities.

By examining the underlying variables and relationships that contribute to the establishment of the rather complex relationship between SSCM practices from a TBL perspective and the performance of a firm, the research contributes to current knowledge on SSCM practices, firm capabilities and firm performance.

To examine the effects of the metaverse on firms’ marketing activities.

A conceptual paper.

It provides evidence of the growing importance of different value capture mechanisms in the metaverse.

Among the first articles on this topic.

This study aims to investigate the relationship between boardroom gender diversity (BoGD) and risk-taking by property-liability (P-L) stock insurers from an analytical framework that control for organizational form and ownership structure. It relies on the behavioral agency model, the resource dependency theory and the concept of socioemotional wealth (SEW).

This study builds on an unbalanced panel of 2,285 firm-year observations from 232 European and US P-L stock insurers covering the period 2010–2019 and measure risk-taking by using four proxies: total risk (TR), upside risk (UpR), downside risk (DwR) and default risk (DR). Reverse causality and endogeneity concerns are treated by applying different approaches.

Findings suggest that BoGD mitigates the TR, DwR and DR but does not interfere with the UpR, which conceptualizes firm expectations to enhance patrimony and safeguard SEW for heirs, especially in family-owned insurers. The findings hold in various robustness checks including endogeneity and alternative specifications of BoGD and risk-taking.

This study contributes to practice by contrasting the role of female directors’ bevahior when assuming risk, which seems significantly different depending on the risk-taking specification and the organizational form. The author advises policyholders and policymakers to look at closely on BoGD and ownership structure as they affect insurance company risk-taking.

This study takes a more direct approach to highlight the BoGD’s effect on corporate risk-taking by focusing on the insurance sector which is characterized by risk and uncertainty bearing. To the best of the author’s knowledge, this is the first study to consider the full range of the stock organizational forms and the degree of family control in displaying this effect in both widely traded and closely traded insurers and to assess risk-taking from both market-based and accounting-based aspects.

This study aims to investigate the bright and dark sides of environmental, social and governance (ESG) during the COVID-19 pandemic, including both the outbreak and recovery periods, for the Chinese hospitality industry.

Using panel data of 564 firm-quarter observations from 2018 to 2020, the authors adopt fixed-effects regression estimation with standard errors clustered at the firm level. To address potential endogeneity concerns, the authors also use the two-stage least squares estimator with instrumental variables.

The results suggest that ESG plays different roles in market- and accounting-based performance during the COVID-19 outbreak and recovery periods. Specifically, ESG practices show a bright side as a reputation builder to mitigate the negative pandemic impact on market-based performance, whereas the dark side of ESG practices consumes firm resources to aggravate the negative pandemic impact on accounting-based performance during the coronavirus outbreak. These results also suggest hospitality companies benefit bountifully from ESG practices during the COVID-19 recovery.

ESG plays a vital role for hospitality firms by providing insurance-like protection during and after the COVID-19 outbreak. Additionally, hospitality firms should evaluate their capability to adapt resource-consuming ESG practices.

Existing hospitality COVID-19 studies have investigated the effect of ESG on firm performance within a short period with mixed results. This study extends the literature by showing the different effects of ESG practices on market- and accounting-based performance during the COVID-19 outbreak and recovery periods.

The implementation of control systems allows marketing managers to improve operational decisions and organizational results. This paper aims to identify the relationship between control combinations and organizational results and analyze the relationships between the variables attributed to the marketing managers and with marketing control combinations. Decisions involving marketing control combine formal and informal mechanisms and generate control systems that have a favorable relationship with organizational results.

The paper is based on 301 cross-sectional surveys among marketing managers. The classification procedure based on metric distance was implemented to identify the marketing control combinations. A hierarchical cluster analysis was carried out with perceptions about formal and informal control, to validate the control combination classifications. Finally, a discriminant analysis and ANOVA test were carried out for exploring factors associated with the managers. The data analysis was supported by IBM SPSS Statistics 24 software.

The authors found evidence that, when managers perceive high-control systems, the perception of non-financial and financial results is always better, but the presence of high-clan control also returns optimal results. In addition, the manager's satisfaction levels and work motivation are higher with high control systems than with other control systems.

This study contributes to the existing knowledge by providing a broader empirical basis to extend conceptual frameworks about marketing control combinations that emerge in practice.

企業設置營銷控制系統來進行營銷控制,這可讓市場經理能改善其營運決策和組織成果。本文擬確定控制合併與組織成果的關係;本文亦擬分析涉及市場經理的變數與營銷控制合併的關係。涉及營銷控制的決策會結合正式和非正式的機制,而這些決策會帶來與組織成果有良性關係的控制系統。

本研究乃基於對市場經理進行的301項橫斷調查。研究人員實施基於度量距離的分類程式,來確定營銷控制合併;為了證實有關的控制合併分類是正確的,研究人員就對正式控制和非正式控制的觀感和看法、進行了階層式分群法分析;最後,研究人員進行了判別分析和變異數分析 (ANOVA), 以探索與經理有關聯的因素。有關的數據分析得到IBM公司的SPSS (統計產品與服務解決方案) Statistics 24 (統計軟體) 的支持。

我們證實了、若主管感知高控制的系統,其對非財務結果和財務結果的看法必會較好的,但高社群控制亦會帶來最佳的結果。我們亦證實了高控制系統,較其它控制系統,更能提高主管的滿意程度和工作動機。

本研究提供了一個更廣闊的經驗基礎,以擴展涉及在實踐中出現的營銷控制合併的概念框架,就此,本研究豐富了這方面的知識。

Human brands in the music industry use self-presentation tactics on social media to manage audience impressions. This practice has led to many posts asking followers to adopt behaviors favoring the human brand. However, its effectiveness in leveraging relevant performance metrics for musicians outside social media, such as popularity in specialized media, music sales and number of contracted concerts, needs further exploration. This study aims to reveal the effect of impression management tactics conveyed on social media on the market performance of musicians’ human brands.

Secondary data research classifies 5,940 social media posts from 11 music artists into self-presentation tactics (self-promotion, exemplification, supplication and ingratiation). It shows their predictions on three market performance metrics in an annual balanced panel study.

Impression management tactics via posts on social media are mostly self-promotion, improving the musicians’ market performance by increasing the number of contracted concerts. Conversely, ingratiation generated the most positive effect on the musician’s popularity but reduced music sales. Besides lowering the musicians’ popularity, exemplification also reduced the number of contracted concerts, while the supplication had no significant effect.

To the best of the authors’ knowledge, the research is the first to use social media postings of musicians’ official human brand profiles based on self-presentation typologies as a complete impression management tool. Furthermore, it is the first to test the effects of these posts on market performance metrics (i.e. outside of social media) in a longitudinal study.

The aim of this study is to empirically investigate the impact of marketing analytics capability on business performance from the perspective of RBV theory.

This study used a survey method to gather information from 225 food processing SMEs registered with the Ghana Enterprise Agency (GEA) in Ghana’s eastern region. A structural equation modeling (SEM) path analysis was used to assess the impact of marketing analytics capability (MAC) on the performance of SMEs.

The results of the study show that MAC significantly and positively affect the financial performance (FP), customer performance (CF), internal business process performance (IBPP) and learning and growth performance (LGP) of Ghanaian SMEs. The findings of this study also illustrated the significance of MAC determinants, including marketing analytics skills (MAS), data resource management (DRM) and data processing capabilities (DPC), in achieving SME success in Ghana.

The research’s conclusions give RBV theory strong credence. The results of this study also provide credence to previous research finding that SMEs should view MAC and its determinants (i.e. DRM, DPC, MAS) as a crucial strategic capability to improve their performance (i.e. FP, CF, IBPP, LGP). With regard to its contribution, this study broadens the body of knowledge on MAC and SME performance, particularly in the context of an emerging economy.