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This study aims to examine the relationship between cultural intelligence and organisational commitment and its effect on learning goal orientation and turnover intention within the expatriate society of the United Arab Emirates (UAE).

A survey instrument was developed to collect data from 173 non-management expatriates employed by multinational corporations located in Dubai, UAE. SmartPLS bootstrap software was used to analyse the path coefficients and test the research hypotheses.

The results demonstrate that cultural intelligence enhances both learning goal orientation and turnover intention of expatriates. Moreover, organisational commitment partially mediates the relationship between cultural intelligence and turnover intention/learning goal orientation.

This study contributes by advancing extant knowledge with regard to cultural intelligence and organisational commitment effects on turnover intention and learning goal orientation of expatriates within a context of high cultural heterogeneity.

The purpose of this study is to understand how the level of readiness for artificial intelligence (AI) affects the overall performance of companies, determine the role of organizational flexibility in adapting to new technologies and business models and assess the importance of lean sustainability and value creation for technology-focused companies.

Technology companies working in technoparks in Istanbul were determined, and a questionnaire was applied to senior employees such as experts, engineers and managers working in these companies. The results were processed with a sample of 456 units. SmartPLS program was used for analysis.

As a result of the analyzes, it is supported by hypotheses that AI readiness and organizational flexibility have positive effects on lean sustainability and value creation.

When evaluated in terms of the limitations of the research, it would not be correct to evaluate the results of the analysis in general, since the data were collected from technology-focused companies in technoparks in Istanbul.

Examining the variables that make up the research model in technology-oriented companies helps to understand the critical factors for the future success of companies. At the same time, this research is important for companies to make more informed decisions in their strategic planning, technological transformation processes and value creation strategies.

This research topic offers a unique approach in terms of bringing together topics such as AI readiness, organizational flexibility, sustainability and value creation. These issues play an important role in the strategic planning of technology-focused companies, and when considered together, they are important in terms of examining the critical factors that affect the future success of companies.

This study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.

The study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.

The results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.

The study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.

This research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.

This study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.

This study aims to focus on the five most relevant and discursive emerging technologies in accounting (cloud computing, big data and data analytics, blockchain, artificial intelligence (AI) and robotics process automation [RPA]). It investigates the adoption and use of these technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey.

The study investigates the adoption and use of emerging technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey. This study considers the said nature and characteristics of emerging technologies and proposes a model using the factors that have been found to be significant and most commonly investigated by existing prior technology-organization-environment (TOE)-related technology adoption studies. This survey applies the TOE framework and examines the influence of significant and most commonly known factors on Canadian firms’ intention to adopt the said emerging technologies.

Study results indicate that Canadian accounting professionals’ self-assessed knowledge (about these emerging technologies) is more theoretical than operational. Cloud computing is highly used by Canadian firms, while the use of other technologies, particularly blockchain and RPA, is reportedly low. However, firms’ intention about the future adoption of these technologies seems positive. Study results reveal that only the relative advantage and top management commitment are found to be significant considerations influencing the adoption intention.

Study findings confirm some results presented in earlier studies but provide additional insights from a new perspective, that of accounting professionals in Canada. The first limitation relates to the respondents. Although accounting professionals provided valuable insights, their responses are personal views and do not necessarily represent the views of other professionals within the same firm or the official position of their accounting departments or firms. Therefore, the exclusion of diverse viewpoints from the same firm might have negatively impacted the results of this study. Second, this study sample is limited to Canada-based firms, which means that the study reflects only the situation in that country. Third, considering the research method and the limit on the number of questions the authors could ask, respondents were only asked to rate the impact of these five technologies on the accounting field and to clarify which technologies are used.

This study’s findings confirm that the organizational intention to adopt new technology is not primarily based on the characteristics of the technology. In the case of emerging technology adoption, the decision also depends upon other factors related to the internal organization. Furthermore, although this study found no support for the effect of environmental factors, it fills a gap in the literature by including the factor of vendor support, which has received little attention in prior information technology (IT)/ information system (IS) adoption research. Moreover, in contrast to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study findings may serve as a guide for researchers, practitioners, firms and other stakeholders, particularly technology providers, interested in learning about emerging technologies’ adoption and use in Canada and/or in a relevant context. Contrary to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study provides insights into the said technologies’ actual adoption and improves the awareness of firms and stakeholders to the effect of some constructs that influence the adoption of these emerging technologies in accounting.

The paper focuses on bridging the existing literature gap on the role of leadership in influencing employee engagement considering the advancement in technologies. With this, the author explores how the three critical elements of service-based companies' business environment-artificial intelligence (AI) success, employee engagement, and leadership are interlinked and are valuable for raising the engagement level of employees.

A purposive sampling strategy was used to select the employees working in the respective companies. The survey was distributed to 150 senior management employees but responses were received from only 56 employees making the response rate 37.33%. Consequently, an empirical examination of these 56 senior management employees belonging to service-based companies based in Delhi NCR using a survey questionnaire was conducted.

The PLS-SEM (partial least squares structured equation modelling) revealed that AI has a positive role in affecting employee engagement levels and confirmed the mediation of leadership. The magnitude of the indirect effect was negative leading to a reduction in total effect magnitude; however, as the indirect effect model has a higher R square value, the inclusion of a mediating variable made the model more effective.

This study contributes to extending the existing knowledge of the academicians about the relationship theory of leadership, AI implementation in organizations, AI association with leadership and AI impact on employee engagement. The author extends the theoretical understanding by showing that more integration of AI-supported leadership could enable organizations to enhance employee experience and motivate them to be engaged. Despite its relevance, due to the limited sample size, focus on a specific geographic area (Delhi NCR) and the constraint of only using quantitative analysis, the findings open the scope for future research in the form of qualitative and longitudinal studies to identify AI-supported leadership roles.

The study findings are beneficial majorly for organizations to provide them with more in-depth information about the role of AI and leadership style in influencing employee engagement. The identified linkage enables the managers of the company to design more employee-tailored strategies for targeting their engagement level and enhancing the level of productivity of employees. Moreover, AI-supported leadership helps raise the productivity of employees by amplifying their intelligence without making technology a replacement for human resources and also reducing the turnover rate of employees due to the derivation of more satisfaction from existing jobs. Thus, given the economic benefit and societal benefits, the study is relevant.

The existing studies focused on the direct linkage between AI and employee engagement or including artificial intelligence as a mediating variable. The role of leadership is not evaluated. The leadership enables supporting the easy integration of AI in the organization; therefore, it has an important role in driving employee engagement. This study identifies the contribution of leadership in organizations by providing the means of enhancing employee satisfaction without hampering the social identity of the company due to the integration of AI.

Artificial intelligence (AI) technologies have led to significant transformations across industries and society, including the field of education. The integration of AI in educational settings has the potential to improve students' learning experience and support their individual competencies when paired with non-AI methods. Despite the growing importance of AI in modern education, there remains a noticeable research gap regarding its use in entrepreneurship education and the effects of Chatbots on students' entrepreneurial competencies. To address this gap, an exploratory study was conducted on undergraduate students who were tasked with using ChatGPT to improve their business model canvas.

The chosen methodology aligned with the research purpose, aiming to explore the relationship between Generative AI and competencies. Due to the novel nature of the research problem, an exploratory study was conducted using a mixed methods approach. A survey with open- and closed-ended questions was designed, and statistical and text analyses were performed to interpret data and test identified propositions.

The findings of this study indicate that ChatGPT can enhance the types of students' entrepreneurial competencies considered in this study: spotting opportunities, creativity, vision, valuing ideas and ethical and sustainable thinking. The results show that ChatGPT can be particularly helpful to improve the ability of students of valuing ideas.

Overall, this study highlights the potential of adopting ChatGPT in experiential learning methodologies for enhancing students' entrepreneurial competencies and improving their learning outcomes.

This chapter explores the role of artificial intelligence (AI), particularly its subfield of machine learning (ML) methods, as a core technology of the fintech revolution in the financial services industry. It simplifies some of the complex concepts related to AI by introducing the main ML paradigms and related techno-methodic aspects. This chapter uses real-world examples to illustrate how next-generation AI powered by ML is transforming the financial services industry. Next, in illustrating the risks associated with AI adoption, this chapter discusses the need for regulation to address the essential facets of AI governance, including transparency, accountability, ethics, and responsible use. Lastly, it looks at emerging regulatory approaches across leading global jurisdictions. The primary goal is to give readers an initial understanding of AI's profound impact on the financial sector.

Export market orientation can be broadly divided into intelligence (generation and dissemination) and responsiveness activities. Although previous studies assess intelligence and responsiveness activities, little is known about what type of international channel partner acts as an enabling condition for the impact of these activities on export venture performance. This study aims to examine the extent to which the selection of international channel partners through word-of-mouth referrals versus direct contacts affects the benefits of intelligence and responsiveness activities.

Data were collected from 246 exporting manufacturers in Japan. To test the hypotheses, we conducted regression analyses using a subjective performance measure at the venture level. We also performed a post hoc analysis using objective performance measure at the function level.

We find that the extent to which international channel partners are selected through word-of-mouth referrals has a moderating role in the export market-oriented activities–performance linkages. Specifically, it acts as an enabling condition for intelligence activity and a disenabling condition for responsiveness activity.

This study contributes to a better understanding of export market orientation by classifying it into intelligence and responsiveness activities and providing empirical evidence on their different interaction effects with partner selection. It also contributes to the elaboration of agency theory by offering insights into the fit between task characteristics and contract type. Our study is critical for business managers as it suggests guidelines for manufacturing exporters engaging in export market-oriented behaviors and export channel management.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.