Search results

Drawing on resource-orchestration theory (ROT), this study investigates the influence of market intelligence and entrepreneurial orientation (EO) on international performance of born global (BG) small and medium enterprises (SMEs) in emerging markets with the mediating role of global technological competence. Quality focus is used as a moderator between global technological competence and international performance.

Data were gathered through a survey, and PLS-SEM was employed for hypotheses testing with a sample of 256 BG SMEs.

The results showed that market intelligence, EO, global technological competence and quality focus positively relate to international performance. Moreover, market intelligence and EO are positively associated with global technological competence. Besides, global technological competence significantly mediates the relationship between market intelligence, EO and international performance. Finally, quality focus strengthens the positive relationship between global technological competence and international performance.

Our research demonstrates that if management utilizes or invests on market intelligence, EO, global technological competence and quality focus, then the BG SMEs will increase their international performance.

The paper contribution lies in its focus on exogenous constructs (i.e. market intelligence, EO, global technological competence and quality focus) to determine the international performance of born global SMEs in emerging markets.

Artificial intelligence (AI) is shaping the future of the marketing world. This study is the first to examine the effect of AI marketing efforts, brand experience (BE) and brand preference (BP) in light of the stimulus-organism-response (SOR) model.

The data collected from 398 participants by the questionnaire method were analyzed by SEM (structural equation modeling) using Smart PLS 4.0 and IBM SPSS 26 programs.

We find that four SOR elements of AI marketing efforts (information, interactivity, accessibility and personalization) positively impact bank customer BE, BP and repurchase intention (RPI). Further, we find that BE plays a mediator role in the relationship between AI marketing efforts, RPI and BP.

The findings of the study have significant implications for the bank marketing literature and the banking industry, given the limited evidence to date regarding AI marketing efforts and bank–customer relationships. Moreover, the study makes important contributions to the AI marketing and brand literature and helps banks increase customer experience with artificial intelligence activities and create long-term relationships with customers.

The increased digital interactions in the B2B industry have enhanced the importance of customer engagement as a measure of firm performance. This study aims to map and analyze temporal and spatial journeys for customer engagement in B2B markets from a bibliometric perspective.

The extant literature on customer engagement research in the B2B context was analyzed using bibliometric analysis. The citation analysis, keyword analysis, cluster analysis, three-field plot and bibliographic coupling were used to map the intellectual structure of customer engagement in B2B markets.

The research on customer engagement in the B2B context was studied more in western countries. The analysis suggests that customer engagement in B2B markets will take centre stage in the coming times as digital channels make it easier to track critical metrics besides other key factors. Issues like digital transformation, the use of artificial intelligence for virtual engagement, personalization, innovation and salesforce management by leveraging technology would be critical for improved B2B customer engagement.

The study provides a comprehensive reference to scholars working in this domain.

The study makes a pioneering effort to comprehensively analyze the vast corpus of literature on customer engagement in B2B markets for business insights.

The paper aims to analyze the potential of artificial intelligence (AI) in enhancing marketing capabilities for Indian fast-moving consumer goods (FMCG) firms, with appropriate emphasis on dynamic capabilities (DC). By integrating AI into their operations, companies can enhance diverse marketing practices, leading to improved efficiency and effectiveness. In addition, the study offers valuable insights and guidance for effectively implementing AI in marketing strategies.

In-depth interviews of 26 seasoned professionals from various positions in the Indian FMCG sector were conducted for the study. A systematic approach of coding that includes open, axial and selective coding was made to recognize the themes that represent AI-enabled marketing practices. This approach ensured that the themes were precisely identified and comprehensively analyzed. Interviews followed by a rigorous coding process provide valuable insights into the practical implementation of AI-enabled marketing practices for the Indian FMCG industry.

The study’s results underscore the importance of AI in enhancing marketing practices for FMCG firms, particularly in four critical areas: personalization, consumer engagement, marketing automation and strategic goals. By adopting AI in these areas, Indian FMCG firms can significantly enhance their marketing capabilities, increasing efficiency, effectiveness and gaining a competitive advantage.

The study uses qualitative data analysis to explain how DC through AI technologies can enhance digital marketing practices for Indian FMCG organizations. Furthermore, the study provides valuable insights into how AI technologies can improve marketing capabilities and emphasizes the importance of DC. The study also proposes a framework for AI-enabled Marketing 4.0 that can guide FMCG firms seeking to leverage AI technologies to enhance their marketing practices.

This study outlines the potential for enhancing marketing practices by adapting AI in the Marketing 4.0 environment for Indian FMCG companies, highlighting the importance of DC in achieving this goal.

The aim of this paper is the validation of a scale that has Emotional Intelligence (EI) and Internal Marketing (IM) as determinants of organizational success.

The survey (questionnaire) allows assessing the contribution of motivation and job satisfaction to organizational success and was disseminated on social networks and directly in some national institutions.

The results of this research suggest that the 58 items of the scale can be grouped into eight main dimensions and can be confidently applied to professionals from organizations and companies operating in Portugal.

Furthermore, this study can be considered as an innovative, effective and useful tool for entrepreneurs, managers and organizations, as it can help diagnose the perceptions of their employees and promote a healthy and appealing environment, moving towards an excellent organizational performance, greater profitability and corporate sustainability.

The main purpose of this study is to provide a relatively integrated perspective on the role of market orientation, strategic flexibility and technological capability as multiple organizational capabilities and their potential effectiveness in promoting business model innovation (BMI) and business performance.

To achieve this objective, an empirical survey was conducted among 379 firms in Greece. Initially, exploratory factor analysis and then confirmatory factor analysis were applied. Finally, the structural relationships among the latent factors were determined through structural equation modeling.

The results show the positive effect of market orientation on strategic flexibility and technological capability. Strategic flexibility drives firms to BMI and then business performance. Furthermore, it is essential that firms build up technological capability to be effective in BMI and business performance.

Data were collected at only one point in time from one country, Greece. This might pose limitations on the generalizability of our results. Future research could also explore how organizations develop strategic flexibility and BMI capabilities in different environmental contexts and organizational structures.

This study sends the message that companies focusing on market orientation and technological capability can led to higher strategic flexibility and BMI capabilities, which in turn act as a catalyst for business improvement.

The proposed model provides plausible guidelines that advance the research on multiple organizational capabilities in companies.

The increasing awareness and adoption of technology, particularly artificial intelligence (AI), reshapes industries and daily life, fostering a proactive approach to risk management and leveraging advanced analytics, which may affect the stock price crash risk (SPCR). The main objective of the current study is to explore how AI adoption influences SPCR.

This study employs an Ordinary Least Squares (OLS) fixed-effect regression model to explore the impact of AI on SPCR in Chinese A-share listed companies from 2010 to 2020. Further, number of robustness analysis (2SLS, PSM and Sys-GMM) and channel analysis are used to validate the findings.

The primary findings emphasize that AI adoption significantly reduces SPCR likelihood. Further, channel analysis indicates that AI adoption enhances internal control quality, contributing to a reduction in firm SPCR. Additionally, the observed relationship is notably more pronounced in non-state-owned enterprises (non-SOEs) compared to state-owned enterprises (SOEs). Similarly, this distinction is heightened in nonforeign enterprises (non-FEs) as opposed to foreign enterprises (FEs). The study finding also supports the notion that financial analysts enhance transparency, reducing the SPCR. Moreover, the study results consistently align across different statistical methodologies, including 2SLS, PSM and Sys-GMM, employed to effectively address endogeneity concerns.

Our study stands out for its distinctive focus on the financial implications of AI adoption, particularly how it influences firm-level SPCR, an area that has been overlooked in previous research. Through the lens of information asymmetry theory, agency theory, and the economic implications of integrating AI into financial markets, our study makes a substantial contribution in mitigating SPCR.

This study underscores the pivotal role of AI adoption in influencing stock markets for enterprises in China. Embracing digital strategies, fostering transparency and prioritizing talent development are key for reaping substantial benefits. The study recommends regulatory bodies and service providers to promote AI adoption in strengthening financial supervision and ensure market stability, emphasizing the importance of investing in technologies and advancing talent development.

Artificial intelligence (AI) is increasingly applied by businesses to optimize their processes and decision-making, develop effective and efficient strategies, and positively influence customer behaviors. Businesses use AI to generate behaviors such as customer retention (CR). The existing literature on “AI and CR” is vastly scattered. The paper aims to review the present research on AI in CR systematically and suggest future research directions to further develop the field.

The Scopus database is used to collect the data for systematic review and bibliometric analysis using the VOSviewer tool. The paper performs the following analysis: (1) year-wise publications and citations, (2) co-authorship analysis of authors, countries, and affiliations, (3) citation analysis of articles and journals, (4) co-occurrence visualization of binding terms, and (5) bibliographic coupling of articles.

Five research themes are identified, namely, (1) AI and customer churn prediction in CR, (2) AI and customer service experience in CR, (3) AI and customer sentiment analysis in CR, (4) AI and customer (big data) analytics in CR, and (5) AI privacy and ethical concerns in CR. Based on the research themes, fifteen future research objectives and a future research framework are suggested.

The paper has important implications for researchers and managers as it reveals vital insights into the latest trends and paths in AI-CR research and practices. It focuses on privacy and ethical issues of AI; hence, it will help the government develop policies for sustainable AI adoption for CR.

To the author's best knowledge, this paper is the first attempt to comprehensively review the existing research on “AI and CR” using bibliometric analysis.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

This study aims at investigating how hybrid intelligence might enhance employee engagement in breakthrough innovation. Specifically, it empirically examines the mediating role of self-extinction and moderating role of social intelligence.

This study, using the lens of socio-technical system (STS) theory, collected data from 317 employees through cross-sectional survey. The hypotheses were tested using MPlus 8.3 by applying Structural Equation Modelling (SEM).

The results support the proposed model, suggesting that hybrid intelligence fosters employees' breakthrough innovation engagement and such a relationship is fully mediated by self-extinction. Besides, the findings provide support for the positive moderating impact of social intelligence on such indirect relationships in a way that high social intelligence will further strengthen the relationship.

As a pioneering contribution, the study uncovers the social mechanism that underlies hybrid intelligence–breakthrough innovation engagement relationship via self-extinction. The research suggests managers leveraging employees' social intelligence for playing a critical role in countering the negative impact of self-extinction by enhancing the employees' engagement in the breakthrough innovation process.