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1 – 10 of over 21000The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely…
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.
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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…
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.
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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…
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.
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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…
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.
Kirill Krinkin, Yulia Shichkina and Andrey Ignatyev
This study aims to show the inconsistency of the approach to the development of artificial intelligence as an independent tool (just one more tool that humans have developed); to…
Abstract
Purpose
This study aims to show the inconsistency of the approach to the development of artificial intelligence as an independent tool (just one more tool that humans have developed); to describe the logic and concept of intelligence development regardless of its substrate: a human or a machine and to prove that the co-evolutionary hybridization of the machine and human intelligence will make it possible to reach a solution for the problems inaccessible to humanity so far (global climate monitoring and control, pandemics, etc.).
Design/methodology/approach
The global trend for artificial intelligence development (has been) was set during the Dartmouth seminar in 1956. The main goal was to define characteristics and research directions for artificial intelligence comparable to or even outperforming human intelligence. It should be able to acquire and create new knowledge in a highly uncertain dynamic environment (the real-world environment is an example) and apply that knowledge to solving practical problems. Nowadays artificial intelligence overperforms human abilities (playing games, speech recognition, search, art generation, extracting patterns from data etc.), but all these examples show that developers have come to a dead end. Narrow artificial intelligence has no connection to real human intelligence and even cannot be successfully used in many cases due to lack of transparency, explainability, computational ineffectiveness and many other limits. A strong artificial intelligence development model can be discussed unrelated to the substrate development of intelligence and its general properties that are inherent in this development. Only then it is to be clarified which part of cognitive functions can be transferred to an artificial medium. The process of development of intelligence (as mutual development (co-development) of human and artificial intelligence) should correspond to the property of increasing cognitive interoperability. The degree of cognitive interoperability is arranged in the same way as the method of measuring the strength of intelligence. It is stronger if knowledge can be transferred between different domains on a higher level of abstraction (Chollet, 2018).
Findings
The key factors behind the development of hybrid intelligence are interoperability – the ability to create a common ontology in the context of the problem being solved, plan and carry out joint activities; co-evolution – ensuring the growth of aggregate intellectual ability without the loss of subjectness by each of the substrates (human, machine). The rate of co-evolution depends on the rate of knowledge interchange and the manufacturability of this process.
Research limitations/implications
Resistance to the idea of developing co-evolutionary hybrid intelligence can be expected from agents and developers who have bet on and invested in data-driven artificial intelligence and machine learning.
Practical implications
Revision of the approach to intellectualization through the development of hybrid intelligence methods will help bridge the gap between the developers of specific solutions and those who apply them. Co-evolution of machine intelligence and human intelligence will ensure seamless integration of smart new solutions into the global division of labor and social institutions.
Originality/value
The novelty of the research is connected with a new look at the principles of the development of machine and human intelligence in the co-evolution style. Also new is the statement that the development of intelligence should take place within the framework of integration of the following four domains: global challenges and tasks, concepts (general hybrid intelligence), technologies and products (specific applications that satisfy the needs of the market).
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Jeannette Paschen, Jan Kietzmann and Tim Christian Kietzmann
The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this…
Abstract
Purpose
The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this paper describes the foundational building blocks of any artificial intelligence system and their interrelationships. This paper also discusses the implications of the different building blocks with respect to market knowledge in B2B marketing and outlines avenues for future research.
Design/methodology/approach
The paper is conceptual and proposes a framework to explicate the phenomenon AI and its building blocks. It further provides a structured discussion of how AI can contribute to different types of market knowledge critical for B2B marketing: customer knowledge, user knowledge and external market knowledge.
Findings
The paper explains AI from an input–processes–output lens and explicates the six foundational building blocks of any AI system. It also discussed how the combination of the building blocks transforms data into information and knowledge.
Practical implications
Aimed at general marketing executives, rather than AI specialists, this paper explains the phenomenon artificial intelligence, how it works and its relevance for the knowledge-based marketing in B2B firms. The paper highlights illustrative use cases to show how AI can impact B2B marketing functions.
Originality/value
The study conceptualizes the technological phenomenon artificial intelligence from a knowledge management perspective and contributes to the literature on knowledge management in the era of big data. It addresses calls for more scholarly research on AI and B2B marketing.
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Faten F. Kharbat, Abdallah Alshawabkeh and M. Lynn Woolsey
Students with developmental/intellectual disabilities (ID/DD) often have serious health issues that require additional medical care and supervision. Serious health issues also…
Abstract
Purpose
Students with developmental/intellectual disabilities (ID/DD) often have serious health issues that require additional medical care and supervision. Serious health issues also mean increased absence and additional lags in academic achievement and development of adaptive and social skills. The incorporation of artificial intelligence in the education of a child with ID/DD could ameliorate the educational, adaptive and social skill gaps that occur as a direct result of persistent health problems.
Design/methodology/approach
The literature regarding the use of artificial intelligence in education for students with ID/DD was collected systematically from international online databases based on specific inclusion and exclusion criteria. The collected articles were analyzed deductively, looking for the different gaps in the domain. Based on the literature, an artificial intelligence–based architecture is proposed and sketched.
Findings
The findings show that there are many gaps in supporting students with ID/DD through the utilization of artificial intelligence. Given that the majority of students with ID/DD often have serious and chronic and comorbid health conditions, the potential use of health information in artificial intelligence is even more critical. Therefore, there is a clear need to develop a system that facilitates communication and access to health information for students with ID/DD, one that provides information to caregivers and education providers, limits errors, and, therefore, improves these individuals' education and quality of life.
Practical implications
This review highlights the gap in the current literature regarding using artificial intelligence in supporting the education of students with ID/DD. There is an urgent need for an intelligent system in collaboration with the updated health information to improve the quality of services submitted for people with intellectual disabilities and as a result improving their quality of life.
Originality/value
This study contributes to the literature by highlighting the gaps in incorporating artificial intelligence and its service to individuals with ID/DD. The research additionally proposes a solution based on the confounding variables of students’ health and individual characteristics. This solution will provide an automated information flow as a functional diagnostic and intervention tool for teachers, caregivers and parents. It could potentially improve the educational and practical outcomes for individuals with ID/DD and, ultimately, their quality of life.
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Handan Hamarat, Haydar Sahin, Ayşe Koç Apuhan and Ramazan İnan
This study aims to conduct research by making use of studies investigating the negative effects of artificial intelligence on the future careers and work motivation of tourism…
Abstract
Purpose
This study aims to conduct research by making use of studies investigating the negative effects of artificial intelligence on the future careers and work motivation of tourism employees.
Design/methodology/approach
In this research, a literature review, which is one of the qualitative research methods, was used. The study was completed by using a total of 13 articles and two book chapters investigating the negative aspects of artificial intelligence in the research data Science Direct and Web of Science databases as the main references.
Findings
In the articles examined as a result of the research, it was predicted that the entry of artificial intelligence into the tourism sector poses a threat to the future careers of many tourism employees, and this will cause tourism employees to lose their focus and motivation at work. Another conclusion reached as a result of the research is that many tourism workers will be unemployed in the future due to artificial intelligence-supported information systems and robots.
Originality/value
When the literature was reviewed, there was no research that directly examined the negative effects of artificial intelligence on tourism sector employees. Therefore, this research is unique and important in this respect.
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Recently there has been a surge in interest about the use of artificial intelligence in organisations with art galleries introducing new technological innovations that coincide…
Abstract
Purpose
Recently there has been a surge in interest about the use of artificial intelligence in organisations with art galleries introducing new technological innovations that coincide with the digitalisation revolution. Virtual and immersive environments that are supported by social media and digital platforms are significantly changing customer experiences at art galleries. This is internationalising and making art gallery experiences more accessible thereby fostering the competitive advantage of art galleries.
Design/methodology/approach
Art gallery customers, stakeholders and managers are appreciating the use of artificial intelligence with resulting higher satisfaction rates. Building on competency and transformational entrepreneurship theory international art gallery managers were interviewed to understand the role of artificial intelligence in their organisations and the impact of internationalisation.
Findings
The data analysis revealed that the internationalisation of art galleries enabled artificial intelligence to transform in person and online visitor experience, work and marketing, and future art gallery development ideas. Results show that artificial intelligence is opening up new transformations derived from entrepreneurial behaviours.
Originality/value
Key managerial implications are that art gallery managers need to utilise their international networks in order to learn about artificial intelligence and other new technological innovation. Theoretical implications are that existing theory can be adapted to an art gallery and artificial intelligence context. Limitations and future research suggestions focus on the need to focus more on art galleries as cultural entities that are more likely to utilise new technology innovation such as artificial intelligence.
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Milan Zorman, Bojan Žlahtič, Saša Stradovnik and Aleš Hace
Collaborative robotics and autonomous driving are fairly new disciplines, still with a long way to go to achieve goals, set by the research community, manufacturers and users. For…
Abstract
Purpose
Collaborative robotics and autonomous driving are fairly new disciplines, still with a long way to go to achieve goals, set by the research community, manufacturers and users. For technologies like collaborative robotics and autonomous driving, which focus on closing the gap between humans and machines, the physical, psychological and emotional needs of human individuals becoming increasingly important in order to ensure effective and safe human–machine interaction. The authors' goal was to conceptualize ways to combine experience from both fields and transfer artificial intelligence knowledge from one to another. By identifying transferable meta-knowledge, the authors will increase quality of artificial intelligence applications and raise safety and contextual awareness for users and environment in both fields.
Design/methodology/approach
First, the authors presented autonomous driving and collaborative robotics and autonomous driving and collaborative robotics' connection to artificial intelligence. The authors continued with advantages and challenges of both fields and identified potential topics for transferrable practices. Topics were divided into three time slots according to expected research timeline.
Findings
The identified research opportunities seem manageable in the presented timeline. The authors' expectation was that autonomous driving and collaborative robotics will start moving closer in the following years and even merging in some areas like driverless and humanless transport and logistics.
Originality/value
The authors' findings confirm the latest trends in autonomous driving and collaborative robotics and expand them into new research and collaboration opportunities for the next few years. The authors' research proposal focuses on those that should have the most positive impact to safety, complement, optimize and evolve human capabilities and increase productivity in line with social expectations. Transferring meta-knowledge between fields will increase progress and, in some cases, cut some shortcuts in achieving the aforementioned goals.
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