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1 – 10 of 850The 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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This paper aims to explore the dimensions that foster the effectiveness of artificial intelligence (AI) within a business strategy.
Abstract
Purpose
This paper aims to explore the dimensions that foster the effectiveness of artificial intelligence (AI) within a business strategy.
Design/methodology/approach
The paper reviews recent contributions to AI and business success and identifies the key pillars that support the achievement of good results.
Findings
The paper proposes that there are four critical dimensions for developing an effective business strategy with AI. This research finds that AI has the potential to drive significant development when it is leveraged along four main axes: a focused strategy for AI, knowledge of the customers, effective interactions with customers and effective implementation of AI. These four dimensions are essential for nurturing the critical dimensions of AI that enable successful integration with the business strategy. To achieve this integration, the business strategy must take advantage of the insights and capabilities provided by AI while also understanding and deeply knowing the customers through effective interactions with them. The development is structured in an organizational alignment where AI helps employees and learns from them. By continuously learning from the exploitation of knowledge and big data, the organization can enrich its use of AI.
Research limitations/implications
The paper identifies four pillars of AI integration with the development of business strategy as areas for further empirical analysis by business researchers.
Practical implications
This paper offers strategies for managers and professionals to effectively integrate AI into business strategy.
Originality/value
The authors provide a novel perspective on using AI in business strategy by identifying four key axes of success in the current business landscape.
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The integration of artificial intelligence (AI) technologies like conversational AI and HR chatbots in international human resource development (HRD) presents both productivity…
Abstract
Purpose
The integration of artificial intelligence (AI) technologies like conversational AI and HR chatbots in international human resource development (HRD) presents both productivity benefits and ethical challenges. This study aims to examine the ethical dimensions of AI-driven HR chatbots, emphasizing the need for fairness, autonomy and nondiscrimination. It discusses inherent biases in AI systems and addresses linguistic, cultural and accessibility issues. The paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework. By embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.
Design/methodology/approach
Systematic literature review.
Findings
The paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework.
Practical implications
By embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.
Originality/value
This study explores the intricate ethical landscape surrounding AI-driven HR chatbots, spotlighting the imperatives of fairness, autonomy, and nondiscrimination. Uncovering biases inherent in AI systems, it addresses linguistic, cultural, and accessibility concerns. Proposing a pioneering “risk management by design” framework, the study advocates for a holistic approach to ethical integration, ensuring organizations navigate the complexities of AI-driven HR technologies while prioritizing fairness and equity in global workforce management.
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Dina M. Abdelzaher and Muna Onumonu
The COVID-19 pandemic was an eye-opening experience that put to the test our crisis management competencies across many institutions, including those offered by institutions of…
Abstract
Purpose
The COVID-19 pandemic was an eye-opening experience that put to the test our crisis management competencies across many institutions, including those offered by institutions of higher education. This study aims to review the literature on international business (IB) risks and IB education (IBE) to question whether business graduates are equipped to make decisions in today’s volatile, uncertain, complex and ambiguous (VUCA) marketplace.
Design/methodology/approach
While the IB literature has discussed the importance of various sources of risks on global business operations, IBE did not effectively adopt an integrative approach to building the needed risk management competencies related to those risks into our education. The authors argue that this integrative approach to teaching IB is critically needed to prepare future global managers for addressing crises, like that of the pandemic and others. Specifically, this study proposes that this integrated risk management competency can be developed through the building of “synergistic mindsets”.
Findings
This study presents a conceptual framework for the components of the synergistic mindset, with intelligence that directly links to present IB risks. These components are cultural intelligence (CQ), emotional intelligence (EQ), public policy intelligence (PPQ), digital intelligence (DQ) and orchestration intelligence (OQ).
Originality/value
Insights related to IBE effectiveness in addressing today’s VUCA market demands and IB risks are discussed.
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Deval Ajmera, Manjeet Kharub, Aparna Krishna and Himanshu Gupta
The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting…
Abstract
Purpose
The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.
Design/methodology/approach
This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.
Findings
The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.
Social implications
This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.
Originality/value
The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.
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Abstract
Purpose
This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.
Design/methodology/approach
A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.
Findings
Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.
Practical implications
The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.
Originality/value
This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.
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Mingke Gao, Zhenyu Zhang, Jinyuan Zhang, Shihao Tang, Han Zhang and Tao Pang
Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and…
Abstract
Purpose
Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.
Design/methodology/approach
This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.
Findings
This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.
Originality/value
It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.
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Narjess Said, Kaouther Ben Mansour, Nedra Bahri-Ammari, Anish Yousaf and Abhishek Mishra
This study aims to propose a research model integrating technology acceptance model 3 (TAM3) constructs and human aspects of humanoid service robots (HSRs), measured by the…
Abstract
Purpose
This study aims to propose a research model integrating technology acceptance model 3 (TAM3) constructs and human aspects of humanoid service robots (HSRs), measured by the Godspeed questionnaire series and tested across two hotel properties in Japan and the USA.
Design/methodology/approach
Potential participants were approached randomly by email invitation. A final sample size of 395 across two hotels, one in Japan and the other in the USA, was obtained, and the data were analysed using structural equation modelling.
Findings
The results confirm that perceived usefulness, driven by subjective norms and output quality, and perceived ease of use, driven by perceived enjoyment and absence of anxiety, are the immediate direct determinants of users’ re-patronage intentions for HSRs. Results also showed that users prefer anthropomorphism, perceived intelligence and the safety of an HSR for reusing it.
Practical implications
The findings have practical implications for the hospitality industry, suggesting multiple attributes of an HSRs that managers need to consider before deploying them in their properties.
Originality/value
The current study proposes an integrated model determining factors that affect the re-patronage of HSRs in hotels.
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Diana Irinel Baila, Filippo Sanfilippo, Tom Savu, Filip Górski, Ionut Cristian Radu, Catalin Zaharia, Constantina Anca Parau, Martin Zelenay and Pacurar Razvan
The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM…
Abstract
Purpose
The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.
Design/methodology/approach
The methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.
Findings
A series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.
Originality/value
This study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.
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Amir Schreiber and Ilan Schreiber
In the modern digital realm, while artificial intelligence (AI) technologies pave the way for unprecedented opportunities, they also give rise to intricate cybersecurity issues…
Abstract
Purpose
In the modern digital realm, while artificial intelligence (AI) technologies pave the way for unprecedented opportunities, they also give rise to intricate cybersecurity issues, including threats like deepfakes and unanticipated AI-induced risks. This study aims to address the insufficient exploration of AI cybersecurity awareness in the current literature.
Design/methodology/approach
Using in-depth surveys across varied sectors (N = 150), the authors analyzed the correlation between the absence of AI risk content in organizational cybersecurity awareness programs and its impact on employee awareness.
Findings
A significant AI-risk knowledge void was observed among users: despite frequent interaction with AI tools, a majority remain unaware of specialized AI threats. A pronounced knowledge difference existed between those that are trained in AI risks and those who are not, more apparent among non-technical personnel and sectors managing sensitive information.
Research limitations/implications
This study paves the way for thorough research, allowing for refinement of awareness initiatives tailored to distinct industries.
Practical implications
It is imperative for organizations to emphasize AI risk training, especially among non-technical staff. Industries handling sensitive data should be at the forefront.
Social implications
Ensuring employees are aware of AI-related threats can lead to a safer digital environment for both organizations and society at large, given the pervasive nature of AI in everyday life.
Originality/value
Unlike most of the papers about AI risks, the authors do not trust subjective data from second hand papers, but use objective authentic data from the authors’ own up-to-date anonymous survey.
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