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1 – 10 of over 4000
Article
Publication date: 25 December 2023

Isaac Akomea-Frimpong, Jacinta Rejoice Ama Delali Dzagli, Kenneth Eluerkeh, Franklina Boakyewaa Bonsu, Sabastina Opoku-Brafi, Samuel Gyimah, Nana Ama Sika Asuming, David Wireko Atibila and Augustine Senanu Kukah

Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of…

Abstract

Purpose

Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of public–private partnership (PPP) infrastructure projects. Such conferences together with available project reports and empirical studies recommend project managers and practitioners to adopt smart technologies and develop robust measures to tackle climate risk exposure. Comparatively, artificial intelligence (AI) risk management tools are better to mitigate climate risk, but it has been inadequately explored in the PPP sector. Thus, this study aims to explore the tools and roles of AI in climate risk management of PPP infrastructure projects.

Design/methodology/approach

Systematically, this study compiles and analyses 36 peer-reviewed journal articles sourced from Scopus, Web of Science, Google Scholar and PubMed.

Findings

The results demonstrate deep learning, building information modelling, robotic automations, remote sensors and fuzzy logic as major key AI-based risk models (tools) for PPP infrastructures. The roles of AI in climate risk management of PPPs include risk detection, analysis, controls and prediction.

Research limitations/implications

For researchers, the findings provide relevant guide for further investigations into AI and climate risks within the PPP research domain.

Practical implications

This article highlights the AI tools in mitigating climate crisis in PPP infrastructure management.

Originality/value

This article provides strong arguments for the utilisation of AI in understanding and managing numerous challenges related to climate change in PPP infrastructure projects.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 15 December 2023

Masoud Karami and Mokter Hossain

Knowledge of how entrepreneurial alertness (EA) and effectuation impact small firms' performance in uncertain markets is limited. Suggesting effectuation as a mediation mechanism…

Abstract

Purpose

Knowledge of how entrepreneurial alertness (EA) and effectuation impact small firms' performance in uncertain markets is limited. Suggesting effectuation as a mediation mechanism between EA and small firms' performance, the authors explore how entrepreneurs of small firms apply effectual logic to translate their individual alertness to market opportunities into firms' performance.

Design/methodology/approach

A set of hypotheses is tested by partial least squares analysis of survey data collected from small firms in New Zealand.

Findings

The results show that effectuation works as a mechanism that mediates a positive association between founders'/managers' alertness to market opportunities and small firms' performance.

Originality/value

Integrating EA with the effectuation theory, the authors contribute to the literature on new market opportunity development and firm performance. The authors argue that entrepreneurs concentrate on action and resources to further develop their marketing intelligence in developing new market opportunities. The authors also enhance the understanding of entrepreneurial marketing decision-making by small firms in a relatively small economy in the Asia–Pacific region.

Details

Marketing Intelligence & Planning, vol. 42 no. 1
Type: Research Article
ISSN: 0263-4503

Keywords

Article
Publication date: 10 January 2023

Anchal Arora, Sanjay Gupta, Chandrika Devi and Nidhi Walia

The financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of…

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Abstract

Purpose

The financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of artificial intelligence (AI) in the context of FinTech services for enriching customer experiences has become a new norm in this modern era of technological advancement. So, it becomes crucial to understand the customer’s perspective. The current research ranks the factors and sub-factors influencing customers’ perceptions of AI-based FinTech services.

Design/methodology/approach

The sample size for this study was decided to be 970 respondents from four Indian cities: Mumbai, Delhi, Kolkata and Chennai. The Fuzzy-AHP technique was used to identify the primary factors and sub-factors influencing customers’ experiences with AI-enabled finance services. The factors considered in the study were service quality, trust commitment, personalization, perceived convenience, relationship commitment, perceived sacrifice, subjective norms, perceived usefulness, attitude and vulnerability. The current research is both empirical and descriptive.

Findings

The study’s three top factors are service quality, perceived usefulness and perceived convenience, all of which have a significant impact on customers’ experience with AI-enabled FinTech services discussing sub-criteria three primary criteria for customers’ experience for FinTech services include: “Using FinTech would increase my effectiveness in managing a portfolio (A2)”, “My peer groups and friends have an impact on using FinTech services (SN3)” and “Using FinTech would increase my efficacy in administering portfolio (PU2)”.

Research limitations/implications

The current study is limited to four Indian cities, with 10 factors to understand customers’ preferences in FinTech. Further research can focus on other dimensions like perceived ease of use, familiarity, etc. Future studies can have a broader view of different geographical locations and consider new tech to understand customer perceptions better.

Practical implications

The study’s findings will significantly assist businesses in determining the primary aspects influencing customers’ experiences with AI-enabled financial services. As a result, they will develop strategies and policies to entice clients to use AI-powered FinTech services.

Originality/value

Existing AI research investigated several vital topics in the context of FinTech services. On the other hand, the current study ranked the criteria in understanding customer experiences. The research will substantially assist marketers, business houses, academicians and practitioners in understanding essential facets influencing customer experience and contribute significantly to the literature.

Details

Benchmarking: An International Journal, vol. 30 no. 10
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 27 March 2024

Yupeng Mou, Yixuan Gong and Zhihua Ding

Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer…

Abstract

Purpose

Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

Design/methodology/approach

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

Findings

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

Originality/value

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.

Details

Marketing Intelligence & Planning, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-4503

Keywords

Article
Publication date: 12 September 2022

Selim Aren and Hatice Nayman Hamamci

There is strong excitement during Ponzi schemes and financial bubble periods. This emotion causes investors to turn to “unknown and new investment instruments”. This study, the…

Abstract

Purpose

There is strong excitement during Ponzi schemes and financial bubble periods. This emotion causes investors to turn to “unknown and new investment instruments”. This study, the factors that made “unknown and new investment instruments” preferable to “known and experienced investment instruments” were investigated.

Design/methodology/approach

It was taken into account unconscious like phantasy, emotional like emotional intelligence, both affective and cognitive like financial literacy and subjective beliefs like trust and overconfidence. In addition, risk preferences were measured with four different risk variables. In this context, data were collected by online survey method between November 2020 and May 2021 with convenience sampling. First, the data were collected from 832 participants in the pilot study. Additional data were also collected using convenience sampling and online surveys, and a total of 1,692 participants were obtained. Data were analyzed using Statistical Package for the Social Sciences (SPSS) 25 and AMOS 24.

Findings

As a result of the analyses made, the variables that lead investors to choose “unknown and new investment instruments” were determined as risky investment intention, phantasy, risk taking/risk avoidance, confidence, risk tolerance and subjective financial literacy. Trust and risk perception have a very weak effect on preferences. However, no effect of emotional intelligence and objective financial literacy was detected. In addition, a moderately positive and significant relationship was found between objective and subjective financial literacy. Subjective financial literacy was found to have a strong and significant relationship with emotional intelligence, confidence, trust, risky investment intention and phantasy.

Originality/value

This study investigates the factors underlying individuals' investment preferences from a broad perspective. We think that this study is unique in this structure and wide variables. We believe that the findings obtained in this manner are unique to both academics and practitioners. We also believe that the findings of the study will make an important contribution to understanding participation behavior in various Ponzi schemes and financial bubbles.

Details

Kybernetes, vol. 52 no. 12
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 16 October 2023

Subhodeep Mukherjee, Manish Mohan Baral, Ramji Nagariya, Venkataiah Chittipaka and Surya Kant Pal

This paper aims to investigate the firm performance of micro, small and medium enterprises (MSMEs) by using artificial intelligence-based supply chain resilience strategies. A…

Abstract

Purpose

This paper aims to investigate the firm performance of micro, small and medium enterprises (MSMEs) by using artificial intelligence-based supply chain resilience strategies. A theoretical framework shows the relationship between artificial intelligence, supply chain resilience strategy and firm performance.

Design/methodology/approach

A questionnaire is developed to survey the MSMEs of India. A sample size of 307 is considered for the survey. The employees working in MSMEs are targeted responses. The conceptual model developed is tested empirically.

Findings

The study found that eight hypotheses were accepted and two were rejected. There are five mediating variables in the current study. Artificial intelligence, the independent variable, positively affects all five mediators. Then, according to the survey and analysis of the final 307 responses from MSMEs, the mediating variables significantly impact the dependent variable, firm performance.

Research limitations/implications

This study is limited to emerging markets only. Also this study used only cross sectional data collection methods.

Practical implications

This study is essential for supply chain managers and top management willing to adopt the latest technology in their organisation or firmfor a better efficient supply chain process.

Originality/value

This study investigated artificial intelligence-based supply chain resilience for improving firm performance in emerging countries like India. This study tried to fill the research gap in artificial intelligence and supply chain resilience.

Details

Journal of Global Operations and Strategic Sourcing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-5364

Keywords

Article
Publication date: 23 November 2023

Konstantinos Kalodanis, Panagiotis Rizomiliotis and Dimosthenis Anagnostopoulos

The purpose of this paper is to highlight the key technical challenges that derive from the recently proposed European Artificial Intelligence Act and specifically, to investigate…

Abstract

Purpose

The purpose of this paper is to highlight the key technical challenges that derive from the recently proposed European Artificial Intelligence Act and specifically, to investigate the applicability of the requirements that the AI Act mandates to high-risk AI systems from the perspective of AI security.

Design/methodology/approach

This paper presents the main points of the proposed AI Act, with emphasis on the compliance requirements of high-risk systems. It matches known AI security threats with the relevant technical requirements, it demonstrates the impact that these security threats can have to the AI Act technical requirements and evaluates the applicability of these requirements based on the effectiveness of the existing security protection measures. Finally, the paper highlights the necessity for an integrated framework for AI system evaluation.

Findings

The findings of the EU AI Act technical assessment highlight the gap between the proposed requirements and the available AI security countermeasures as well as the necessity for an AI security evaluation framework.

Originality/value

AI Act, high-risk AI systems, security threats, security countermeasures.

Details

Information & Computer Security, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2056-4961

Keywords

Article
Publication date: 15 February 2024

Alireza Amini, Seyyedeh Shima Hoseini, Arash Haqbin and Mozhgan Danesh

A better understanding of the characteristics and capabilities of women entrepreneurs can significantly improve their chances of success. Therefore, three studies were conducted…

Abstract

Purpose

A better understanding of the characteristics and capabilities of women entrepreneurs can significantly improve their chances of success. Therefore, three studies were conducted for this exploratory paper. We have discovered the characteristics of entrepreneurial intelligence among female entrepreneurs through semi-structured interviews based on conventional content analysis. According to the second study, qualitative meta-synthesis was utilized to identify characteristics of women's entrepreneurial intelligence at the international level. As a third study, we examined the evolutionary relationships of entrepreneurs' intelligence components following the discovery and creation of opportunities.

Design/methodology/approach

The present paper was based on three studies. In the first study, 15 female entrepreneurs were interviewed using purposive sampling in the Guilan province of Iran to identify the characteristics of entrepreneurial intelligence at the national level. An inductive content analysis was performed on the data collected through interviews. Using Shannon entropy and qualitative validation, their validity was assessed. In the second study, using a qualitative meta-synthesis, the characteristics of women's entrepreneurial intelligence were identified. Then the results of these two studies were compared with each other. In the third study, according to the results obtained from the first and second studies, the emergence, priority and evolution of entrepreneurial intelligence components in two approaches to discovering and creating entrepreneurial opportunities were determined. For this purpose, interviews were conducted with 12 selected experts using the purposeful sampling method using the fuzzy total interpretive structural modeling (TISM) method.

Findings

In the first research, this article identified the components of entrepreneurial intelligence of women entrepreneurs in six categories: entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. In the second study, the components of entrepreneurial intelligence were compared according to the study at the national level and international literature. Finally, in the third study, the evolution of the components of entrepreneurial intelligence was determined. In the first level, social intelligence, presumptuous intelligence and provocative intelligence are formed first and social intelligence and provocative intelligence have an interactive relationship. In the second level, entrepreneurial insight and cognitive intelligence appear, which, in addition to their interactive relationship, take precedence over the entrepreneur's intuitive intelligence in discovering entrepreneurial opportunities. With the evolution of the components of entrepreneurial intelligence in the opportunity creation approach, it is clear that intuitive intelligence is formed first at the first level and takes precedence. At the second level, there is cognitive intelligence is created. At the third level, motivational intelligence and finally, at the last level, entrepreneurial insight, social intelligence and bold intelligence.

Originality/value

This study has the potential to discover credible and robust approaches for further examining the contextualization of women's entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various components of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women's entrepreneurship, this paper challenges the assumption that the characteristics of women's entrepreneurial intelligence are uniform worldwide. It also depicts the evolution of the components of entrepreneurial intelligence.

Details

Marketing Intelligence & Planning, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-4503

Keywords

Article
Publication date: 14 February 2024

Alireza Amini, Seyyedeh Shima Hoseini, Arash Haqbin and Vahideh Shahin

Recognizing women’s potential and directing their talents to realize these potentials can be of great benefit. Accordingly, this paper aims to identify the characteristics of…

Abstract

Purpose

Recognizing women’s potential and directing their talents to realize these potentials can be of great benefit. Accordingly, this paper aims to identify the characteristics of entrepreneurial intelligence in female entrepreneurs, drawing on a national-level study and the international literature on this topic.

Design/methodology/approach

The present paper conducted two studies. First, 15 female entrepreneurs in the Guilan province of Iran, who were selected using purposive sampling, were interviewed to identify the characteristics of entrepreneurial intelligence nationally. The data gathered by interviews were analyzed using inductive content analysis. Then, their validity was tested using qualitative validation and analyzed using Shannon entropy. In the second study, the characteristics of female entrepreneurial intelligence were identified through a qualitative metasynthesis. The results of the two studies were compared together.

Findings

This categorized entrepreneurial intelligence into six categories, namely, entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. Ultimately the characteristics of women’s entrepreneurial intelligence in each category were compared according to the national-level study and the international literature.

Originality/value

This study has the potential to discover credible and robust approaches for further examining the contextualization of women’s entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various dimensions of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women’s entrepreneurship, this paper challenges the assumption that the characteristics of women’s entrepreneurial intelligence are uniform across the world.

Details

International Journal of Innovation Science, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1757-2223

Keywords

Article
Publication date: 22 March 2024

Rongxin Chen and Tianxing Zhang

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Chinese Management Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-614X

Keywords

1 – 10 of over 4000