Article
Engineering, Civil
Kai Yang, Boqi Li, Wenbo Shao, Xiaolin Tang, Xiaochuan Liu, Hong Wang
Summary: This paper proposes a risk-aware decision-making (RADM) framework to handle the epistemic uncertainty of prediction models due to insufficient training data. The framework utilizes a multi-agent prediction network with uncertainty quantification and model predictive control technique to process the prediction results and consider the uncertainty. Experimental results demonstrate that RADM can reduce driving risk and improve safety.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Ethics
Jakob Mokander, Jessica Morley, Mariarosaria Taddeo, Luciano Floridi
Summary: The article examines the feasibility and efficacy of ethics-based auditing (EBA) as a governance mechanism to validate claims made about ADMS. EBA can promote procedural regularity and transparency, with seven criteria proposed for successful design and implementation of EBA procedures. The article also identifies and discusses the constraints associated with EBA in various aspects.
SCIENCE AND ENGINEERING ETHICS
(2021)
Article
Computer Science, Cybernetics
Milan Zorman, Bojan Zlahtic, Sasa Stradovnik, Ales Hace
Summary: This article discusses the current state and future trends of collaborative robotics and autonomous driving, and proposes the transfer of meta-knowledge to accelerate progress. The researchers believe that in the coming years, autonomous driving and collaborative robotics will converge and merge in certain areas.
Article
Multidisciplinary Sciences
Mustafa Karatas, Keisha M. Cutright
Summary: Research shows that when people think about God, they are more likely to accept recommendations based on Artificial Intelligence (AI). Eight preregistered experiments involving 2,462 participants demonstrate that people are more willing to consider AI-based recommendations when God is salient. This effect is observed across various contexts and is driven by a heightened feeling of smallness and recognition of human fallibility when God is salient.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Psychology, Multidisciplinary
Cindy Candrian, Anne Scherer
Summary: Delegation is crucial for organizational success, as it allows individuals to overcome personal shortcomings and draw upon the expertise of others. The emergence of AI as an option for delegation brings new opportunities and challenges. Research shows that people prefer to delegate decisions to AI, especially when the decisions involve losses.
COMPUTERS IN HUMAN BEHAVIOR
(2022)
Article
Engineering, Electrical & Electronic
Yongli Chen, Shen Li, Xiaolin Tang, Kai Yang, Dongpu Cao, Xianke Lin
Summary: This article proposes an interaction-aware decision-making approach for autonomous vehicles, which models the interaction between vehicles and pedestrians, and balances safety and efficiency through optimization.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Engineering, Electrical & Electronic
Minrui Xu, Dusit Niyato, Junlong Chen, Hongliang Zhang, Jiawen Kang, Zehui Xiong, Shiwen Mao, Zhu Han
Summary: This paper proposes an autonomous driving architecture that utilizes generative AI to synthesize unlimited conditioned traffic and driving data for improving driving safety and traffic control efficiency. By using digital twin technology and virtual simulators, data sharing and driving decision-making can be simulated in the vehicular mixed reality (MR) Metaverse. A multi-task digital twin offloading model is employed to execute heterogeneous digital twin tasks with different requirements at roadside units (RSUs), and virtual simulators synthesize unlimited conditioned datasets based on AV's digital twins and real-world data. Finally, a multi-task enhanced auction-based mechanism is proposed to incentivize RSUs in providing resources for autonomous driving.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2023)
Article
Computer Science, Information Systems
Phong X. Nguyen, Tho H. Tran, Nguyen B. Pham, Dung N. Do, Takehisa Yairi
Summary: This paper proposes a method for generating explanations in the form of free-text human language to help users understand the behaviors of RL agents. The method is evaluated in two simulated environments and consistently generates accurate rationales, bridging the trust gap encountered when employing RL agents.
Article
Law
Adrienn Lukacs, Szilvia Varadi
Summary: Artificial Intelligence is rapidly spreading in our everyday life, including the world of work. AI is shaping employment context through augmented and automated decision-making. Compliance with data protection frameworks is unavoidable as AI-based decision-making relies on personal data. This paper examines the specific data protection challenges raised in the context of AI-based automated decision-making in employment, providing a detailed overview of the European legal framework on data protection aspects and offering guidelines on addressing these challenges.
COMPUTER LAW & SECURITY REVIEW
(2023)
Article
Engineering, Civil
Yuchao Feng, Wei Hua, Yuxiang Sun
Summary: In recent years, the advancement of deep-learning technologies has greatly promoted the research progress of autonomous driving. However, the lack of explainability in deep neural networks makes it unsafe to deploy them in unseen or unexpected environments. To address this issue, we propose a deep neural network that predicts decision-making actions along with natural-language explanations based on semantic scene understanding. We also provide a large-scale dataset with hand-labelled ground truth for evaluation.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Business
Shavneet Sharma, Nazrul Islam, Gurmeet Singh, Amandeep Dhir
Summary: This article investigates customers' adoption of AI-based autonomous decision-making processes by analyzing 454 customer responses. The results reveal that effort expectancy, performance expectancy, facilitating conditions, and social influence are positively associated with customers' adoption of autonomous decision-making processes. Collectivism strengthened the positive association of social influence with customer attitude, whereas uncertainty avoidance dampened the associations of other factors with attitude.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Business
Yash Raj Shrestha, Vaibhav Krishna, Georg von Krogh
Summary: The growing field of artificial intelligence in management studies has reinvigorated research on decision-making in organizations, particularly with the use of deep learning algorithms. The concept of deep learning-augmented decision-making (DLADM) is illustrated through two case studies involving image recognition and sentiment analysis tasks. Challenges and recommendations for managers in addressing these challenges are also discussed.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Energy & Fuels
Eric Cayeux, Benoit Daireaux, Adrian Ambrus, Rodica Mihai, Liv Carlsen
Summary: The complex drilling process is prone to vibrations and lacks uniform monitoring due to the long and slender system. To achieve autonomous drilling operations, a method capable of estimating internal states and making safe decisions is necessary. The developed solution optimizes the time to reach total depth, adapting to various drilling conditions for effective and cautious operations.
Article
Computer Science, Artificial Intelligence
Wenli Shan
Summary: E-commerce online stores serve as virtual platforms to connect with potential clients worldwide. By utilizing cloud data and artificial intelligence algorithms, this study identifies variables influencing pricing decisions and develops variable pricing techniques. A B2B e-commerce store in Hong Kong successfully implemented the Smart-Quo system, resulting in significant progress in pricing decisions.
Article
Political Science
Carl Gahnberg
Summary: The challenge of governance in artificial intelligence lies in understanding its fundamental properties as artificial agents and systematically analyzing relevant rules across different applications. Additionally, studying AI governance can serve as a means to bridge insights between social science and technical perspectives.
POLICY AND SOCIETY
(2021)
Book Review
Hospitality, Leisure, Sport & Tourism
Stanislav Ivanov
JOURNAL OF TOURISM FUTURES
(2022)
Article
Hospitality, Leisure, Sport & Tourism
Craig Webster, Stanislav Ivanov
Summary: The study reveals that the general public has a positive attitude towards the use of robots in events, particularly when they are employed to provide information. However, the acceptance of using robots as entertainers is relatively low. People's acceptance is positively correlated with the ratio of robots in the labor force at events.
Article
Hospitality, Leisure, Sport & Tourism
Stanislav Ivanov, Stefano Duglio, Riccardo Beltramo
Summary: The purpose of this perspective paper is to investigate the role of robots in tourism towards achieving the Sustainable Development Goals (SDGs). The authors analyze the positive and negative impacts of robots in tourism on the SDGs, finding that while robots can contribute to several goals, their adoption can also have negative consequences. Robots can provide a safe work environment and improve efficiency in the tourism industry, but they also have environmental impacts, such as resource consumption and waste management.
Article
Business
Stanislav Ivanov, Craig Webster, Faruk Seyitoglu
Summary: This study investigates tourists' preferences for the humans-robots ratio in the service delivery systems of tourism and hospitality companies, and examines the factors that influence these preferences. The sample consists of 1537 respondents from nearly 100 countries. The findings demonstrate that tourists' higher preference for robots is positively linked to the perceived emotional skills of robots, their usefulness in the tourism/hospitality context, expectations of robotic service, attitudes towards robots in general, and being male. Conversely, it is negatively associated with the perceived disadvantages of robots compared to human servers and the household size of respondents.
Article
Hospitality, Leisure, Sport & Tourism
Maya Ivanova, Stanislav Ivanov, Irina Petkova
Summary: This paper explores the digital skills gaps in the Bulgarian tourism industry through mixed methods research, surveying 135 respondents and interviewing 16 participants. It reveals that key digital literacy skills such as operating systems, MS Office software, and digital equipment adjustment skills are most important, while skills related to artificial intelligence, robotics, augmented and virtual reality, and computer programming are currently lacking. Despite expectations for growth in the future, these skills remain among the least important. On-the-job training was the preferred method for digital skills training, but many companies were found to provide no such training at all.
Article
Environmental Studies
Faruk Seyitoglu, Stanislav Ivanov
Summary: This study explores the influences of incorporating service robots in the service delivery systems of tourism and hospitality companies on perceived discrimination. It proposes a conceptual framework to explain the relationships between robots-based service delivery systems and discrimination. The study shows that while service robots can eliminate/mitigate perceived discrimination, they can also create or aggravate it. Further empirical studies are needed to shed more light on the relationship between robots-based service delivery systems and discrimination in the tourism and hospitality context.
TOURISM MANAGEMENT
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Ines Carvalho, Stanislav Ivanov
Summary: This paper aims to outline the applications, benefits and risks of ChatGPT and large language models on tourism. The findings suggest that ChatGPT and other similar models will have a profound impact on customer service and productivity in the tourism industry. The study contributes to understanding the implications of ChatGPT in the tourism and hospitality sector.
Book Review
Business, Finance
Stanislav Ivanov
JOURNAL OF REVENUE AND PRICING MANAGEMENT
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Gilda Hernandez-Maskivker, Marta Capdevila-Torres, Stanislav Ivanov, Brian Garrod
Summary: This paper examines different models of academic publishing and their advantages for authors, readers, academic institutions, and society. Factors influencing authors' choice of journal include scope, reputation, and publishing model. These choices, driven by academic institutions, determine access to readers and societal benefits.
Article
Management
Stanislav Ivanov
Summary: The paper focuses on the negative aspects of artificial intelligence in higher education, discussing its impacts on various processes and emphasizing on ethics, creativity, and critical thinking. Potential solutions to mitigate these negative impacts, as well as theoretical, managerial, and policy implications are also discussed.
SERVICE INDUSTRIES JOURNAL
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Tarik Dogru, Nathan Line, Makarand Mody, Lydia Hanks, JeAnna Abbott, Fulya Acikgoz, Albert Assaf, Selim Bakir, Adiyukh Berbekova, Anil Bilgihan, Alec Dalton, Ezgi Erkmen, Mahala Geronasso, Dale Gomez, Sue Graves, Ali Iskender, Stanislav Ivanov, Murat Kizildag, Minwoo Lee, Woojin Lee, John Luckett, Sean McGinley, Fevzi Okumus, Irem Onder, Ozgur Ozdemir, Hyekyung Park, Abhinav Sharma, Courtney Suess, Muzaffer Uysal, Tingting Zhang
Summary: Generative artificial intelligence (GAI) offers significant opportunities for the hospitality and tourism industry in various aspects. However, its implementation requires careful consideration of ethical, legal, social, and economic factors. This study critically examines the impact of GAI applications on stakeholders in the industry and aims to integrate practical and academic insights to drive research forward.
JOURNAL OF HOSPITALITY & TOURISM RESEARCH
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Sheena Carlisle, Stanislav Ivanov, Pilar Espeso-Molinero
Summary: This research is a quantitative survey conducted in 2019 to evaluate senior managers' assessment of employees' social skills proficiency, within the framework of the Next Tourism Generation Alliance project funded by the European Commission. The study examines current and future proficiency levels, social skills gaps, and training in the tourism and hospitality sectors across eight European countries. The findings reveal significant differences based on country, type of organization, operational sector, and organization size, highlighting the need for holistic social skill training to enhance customer experiences and sustainable tourism.
TOURISM & MANAGEMENT STUDIES
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Stanislav Ivanov, Giacomo Del Chiappa
Summary: This paper presents key changes in the European Journal of Tourism Research from 2018 to 2022, including a shift to Platinum open-access, a focus on European tourism, implementation of an online submission system, and expansion of the editorial team. It also discusses the editorial philosophy and vision of the co-editors.
EUROPEAN JOURNAL OF TOURISM RESEARCH
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Stanislav Ivanov, Faruk Seyitoglu, Victoria Yaneva, Maya Ivanova
Summary: This study examines the impact of hospitality work experience factors on hotel employees' preferences to work in chain or independent hotels. The results show that chain hotels provide better operational standards, training, career development, and work experience, but the competition among employees is higher and salaries are not always more competitive. The study also finds that communication and decision-making, as well as resources and planning, have a greater influence on employees' preferences compared to remuneration and working conditions and training and development.
TOURISM AND HOSPITALITY MANAGEMENT-CROATIA
(2023)
