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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: 28 March 2023

Yupeng Lin and Zhonggen Yu

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely…

1568

Abstract

Purpose

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

Design/methodology/approach

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Findings

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

Research limitations/implications

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

Originality/value

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

Article
Publication date: 13 September 2022

Rohit Bhagat, Vinay Chauhan and Pallavi Bhagat

Technology has been witnessing a rapid growth. The advent of artificial intelligence has further enhanced the satisfaction level of consumers, which makes it even more vital in…

5514

Abstract

Purpose

Technology has been witnessing a rapid growth. The advent of artificial intelligence has further enhanced the satisfaction level of consumers, which makes it even more vital in the current scenario. This paper aims to explore the factors affecting practical implacability of artificial intelligence and its impact on consumers’ online purchase intention.

Design/methodology/approach

This paper has used a technology-based model as the base to explore the different factors affecting consumers’ purchase intention towards e-retailing. This study has formulated a model that demonstrates the integration of artificial intelligence in retailing by the business organizations so as to understand the needs of customers and help them accept technology. This study has further explored faith, subjective norms and consciousness as constructs which enhance the implacability of artificial intelligence.

Findings

This study shows that artificial intelligence positively influences consumers’ buying behaviour. This study through a model also shows that integration of artificial intelligence enhances consumers’ purchase intention.

Research limitations/implications

The study has been focusing on a portion of target population. So there is scope to include the whole set of the population to get closer-to-accurate results.

Practical implications

The study offers useful inputs for academicians as well as marketers for predicting buying behaviour of consumers. Marketing managers can use artificial intelligence–embedded technology to enhance online purchase intention.

Social implications

The study shows that an increase in consciousness towards e-retailing has made consumers keenly analyse and purchase products on the basis of merit and usefulness of the products.

Originality/value

The contribution has been made with the best of knowledge in formulating an integrated artificial intelligence model for consumers’ purchase intention in e-retailing.

Details

foresight, vol. 25 no. 2
Type: Research Article
ISSN: 1463-6689

Keywords

Article
Publication date: 6 March 2020

Pavitra Dhamija and Surajit Bag

“Technological intelligence” is the capacity to appreciate and adapt technological advancements, and “artificial intelligence” is the key to achieve persuasive operational…

7480

Abstract

Purpose

“Technological intelligence” is the capacity to appreciate and adapt technological advancements, and “artificial intelligence” is the key to achieve persuasive operational transformations in majority of contemporary organizational set-ups. Implicitly, artificial intelligence (the philosophies of machines to think, behave and perform either same or similar to humans) has knocked the doors of business organizations as an imperative activity. Artificial intelligence, as a discipline, initiated by scientist John McCarthy and formally publicized at Dartmouth Conference in 1956, now occupies a central stage for many organizations. Implementation of artificial intelligence provides competitive edge to an organization with a definite augmentation in its social and corporate status. Mere application of a concept will not furnish real output until and unless its performance is reviewed systematically. Technological changes are dynamic and advancing at a rapid rate. Subsequently, it becomes highly crucial to understand that where have the people reached with respect to artificial intelligence research. The present article aims to review significant work by eminent researchers towards artificial intelligence in the form of top contributing universities, authors, keywords, funding sources, journals and citation statistics.

Design/methodology/approach

As rightly remarked by past researchers that reviewing is learning from experience, research team has reviewed (by applying systematic literature review through bibliometric analysis) the concept of artificial intelligence in this article. A sum of 1,854 articles extracted from Scopus database for the year 2018–2019 (31st of May) with selected keywords (artificial intelligence, genetic algorithms, agent-based systems, expert systems, big data analytics and operations management) along with certain filters (subject–business, management and accounting; language-English; document–article, article in press, review articles and source-journals).

Findings

Results obtained from cluster analysis focus on predominant themes for present as well as future researchers in the area of artificial intelligence. Emerged clusters include Cluster 1: Artificial Intelligence and Optimization; Cluster 2: Industrial Engineering/Research and Automation; Cluster 3: Operational Performance and Machine Learning; Cluster 4: Sustainable Supply Chains and Sustainable Development; Cluster 5: Technology Adoption and Green Supply Chain Management and Cluster 6: Internet of Things and Reverse Logistics.

Originality/value

The result of review of selected studies is in itself a unique contribution and a food for thought for operations managers and policy makers.

Details

The TQM Journal, vol. 32 no. 4
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 1 January 1986

Emerson Hilker

We have long been obsessed with the dream of creating intelligent machines. This vision can be traced back to Greek civilization, and the notion that mortals somehow can create…

1917

Abstract

We have long been obsessed with the dream of creating intelligent machines. This vision can be traced back to Greek civilization, and the notion that mortals somehow can create machines that think has persisted throughout history. Until this decade these illusions have borne no substance. The birth of the computer in the 1940s did cause a resurgence of the cybernaut idea, but the computer's role was primarily one of number‐crunching and realists soon came to respect the enormous difficulties in crafting machines that could accomplish even the simplest of human tasks.

Details

Collection Building, vol. 7 no. 3
Type: Research Article
ISSN: 0160-4953

Book part
Publication date: 29 May 2023

Mahantesh Halagatti, Soumya Gadag, Shashidhar Mahantshetti, Chetan V. Hiremath, Dhanashree Tharkude and Vinayak Banakar

Introduction: Numerous decision-making situations are faced in education where Artificial Intelligence may be prevalent as a decision-making support tool to capture streams of…

Abstract

Introduction: Numerous decision-making situations are faced in education where Artificial Intelligence may be prevalent as a decision-making support tool to capture streams of learners’ behaviours.

Purpose: The purpose of the present study is to understand the role of AI in student performance assessment and explore the future role of AI in educational performance assessment.

Scope: The study tries to understand the adaptability of AI in the education sector for supporting the educator in automating assessment. It supports the educator to concentrate on core teaching-learning activities.

Objectives: To understand the AI adaption for educational assessment, the positives and negatives of confidential data collections, and challenges for implementation from the view of various stakeholders.

Methodology: The study is conceptual, and information has been collected from sources comprised of expert interactions, research publications, survey and Industry reports.

Findings: The use of AI in student performance assessment has helped in early predictions for the activities to be adopted by educators. Results of AI evaluations give the data that may be combined and understood to create visuals.

Research Implications: AI-based analytics helps in fast decision-making and adapting the teaching curriculum’s fast-changing industry needs. Students’ abilities, such as participation and resilience, and qualities, such as confidence and drive, may be appraised using AI assessment systems.

Theoretical Implication: Artificial intelligence-based evaluation gives instructors, students, and parents a continuous opinion on how students learn, the help they require, and their progress towards their learning objectives.

Details

Smart Analytics, Artificial Intelligence and Sustainable Performance Management in a Global Digitalised Economy
Type: Book
ISBN: 978-1-80382-555-7

Keywords

Book part
Publication date: 15 September 2022

Wolfgang H. Schulz, Oliver Franck, Stanley Smolka and Vincent Geilenberg

Climate change requires society to focus more strongly on sustainability. This requires an adjustment both on the demand side and on the supply side. Consumers must be given…

Abstract

Climate change requires society to focus more strongly on sustainability. This requires an adjustment both on the demand side and on the supply side. Consumers must be given incentives to optimise their consumption according to sustainability aspects. In the supply of capital goods and consumer goods, firms must do their part to ensure that environmental savings are made possible and cost-efficiency. However, there must be doubts that a more resource-efficient production technology leads to the desired environmental effects. Policymakers ignore the Jevon’s paradox. The Jevon’s paradox states that an improved technology that leads to resource savings disproportionately increases the intensity of use. In absolute terms, there is a higher consumption of resources after the technology is introduced. This effect is currently ignored, for example, by all forecasts on demand for lithium for electromobility. Regardless of this, it is fundamentally better to optimise the technologies. However, this raises the question of whether the Jevon’s paradox cannot be undermined by artificial intelligence. Artificial intelligence applied to production promises the possibility to replace partial optimisations with total optimisations. By pursuing an absolute maximum (maximum maximorum), the intensity of use is limited. Therefore, this chapter is concerned with understanding the primary effects of artificial intelligence in production and highlighting the potential effects on sustainability.

Purpose: Increasing the sustainability in industrial production is getting more and more important. Furthermore, the technology of artificial intelligence is getting more and more important as well. For this reason, it is time to understand how artificial intelligence and sustainability are linked with one another in the context of production.

Need for the study: This chapter aims to deliver a solid argumentation regarding the prospects and the relevance of the usage of artificial intelligence in the context of production. Moreover, it specifically aims to show how artificial intelligence affects the sustainability of production.

Method: Literature analysis.

Findings: The findings are that artificial intelligence does enforce cooperative action within the industry via the effects on productivity variables, transaction costs, and production elasticities. Furthermore, the Jevon’s paradox does not seem to apply to artificial intelligence. Therefore, it is suggested that more empirical research has to focus on this topic.

Practical Implications: This chapter highlights the importance of artificial intelligence for the topic of sustainability.

Details

The New Digital Era: Digitalisation, Emerging Risks and Opportunities
Type: Book
ISBN: 978-1-80382-980-7

Keywords

Book part
Publication date: 15 May 2023

Swati Bankar and Kasturi Shukla

Artificial Intelligence (AI) is one of the newest technology that is quickly advancing and can be utilised to improve human resource competence in the age of rapid digital…

Abstract

Artificial Intelligence (AI) is one of the newest technology that is quickly advancing and can be utilised to improve human resource competence in the age of rapid digital transformation. The present competitive scenario demands accurate data that need to be collected and analysed for organisational growth.

Purpose: The research examines the applications and usage of AI in performance management and further analyses the future of PM from the perspectives of AI.

Methodology: The study is conceptual and relies on secondary data from research papers, publications, HR blogs, survey reports and other sources. Employee performance and attitudes were monitored using digital technologies, big data analytics and AI. The quality of employee performance continues to increase with the integration of AI, enabling predictive analytics to increase employee performance.

Research Implication: In employee performance appraisal, a digital performance management system leads to openness and honesty with time, effort and sincerity. It is based on the performance management system’s practical usefulness.

Theoretical Implication: The study’s findings provide HR managers, academics, IT professionals and practitioners with an understanding of how AI may be used for performance management and its consequences on their operations. In addition, the connection between the HR devolution theory on performance management and AI is discussed.

Details

Contemporary Studies of Risks in Emerging Technology, Part B
Type: Book
ISBN: 978-1-80455-567-5

Keywords

Book part
Publication date: 10 February 2023

Ryan Varghese, Abha Deshpande, Gargi Digholkar and Dileep Kumar

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has…

Abstract

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

Details

The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part B
Type: Book
ISBN: 978-1-80455-662-7

Keywords

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