Special Issue Journals with ICEC 2024
The selected papers from ICEC 2024 will be invited to the special issues of the journals such Decision Support Systems (SCIE), Data Science and Management (Scopus), Journal of Information Technology Service (KCI).
Decision Support Systems, DSS
Special Issue of Decision Support Systems
Empowering Bright Internet and Bright Artificial Intelligence (AI)
Short Title : Bright Internet and Bright AI
The rapid evolution of technology with the established interconnectedness of our global society has led us to an unprecedented era of opportunities. Concurrently, the negative aspects of information and communication technologies (ICT) are also on the rise. More recently, as Artificial Intelligence (AI) systems are becoming prevalent in our daily lives and organizations' processes, the topic of AI is a subject of intense debate, encompassing both its potential benefits and negative consequences it might inflict upon individuals, organizations, society, and governance. Accordingly, two prominent issues that require intensive research are the intersection between cybersecurity and AI. CIOs in the United States regard cybersecurity and privacy as the most essential organizational issue in the last ten consecutive years. In this respect, previous studies have shed light on the dual nature of AI, demonstrating its capacity to yield positive outcomes alongside detrimental impacts within organizational contexts (Mikalef et al., 2022). However, there is no promising vision of mitigating the cybersecurity community as vaccines can preventively overcome an impending AI-driven pandemic.
AI has become popular since AlphaGo won the human champion in 2016. The recent advancements in generative AI (GAI), such as OpenAI's ChatGPT and Google's Bard, have sparked the promise of revolutionizing many management processes. It appears that Large Language Models and GAI have demonstrated their potential and give high expectations of a revolutionary change in human intellectual jobs in many aspects and various domains. For example, it will provide positive value for human society regarding automating tasks that humans cannot perform well and economically. However, it will also give the adverse threats of deep fake and changing the robot-manipulated weapons of crimes and wars.
Given this context, this special issue pays attention to the Principles of Bright Internet, which aims to preventively mitigate the threat sources from the origins (Lee, 2015; Lee et al., 2020). For instance, AI and intelligent models can be used to build spam filtering models for inbound and outbound spam mail. This can be regarded as AI-enabled Bright Internet. Similarly, we can look at AI with the Principle of Bright Internet: Origin Responsibility, Deliverer Responsibility, Identifiable Anonymity, Privacy Protection, and Global Collaboration to prevent such risks (Lee 2015; Lee et al. 2018; Lee et al. 2020). Note that let us call this perspective of research Bright AI, but the themes of Bright AI do not intend to limit these principles and perspectives, although it can be a useful framework. From a comprehensive view, it can cover relevant high-level principles, such as fairness, transparency, accountability, social responsibility, and privacy, to ensure the responsible development and execution of AI systems (De Cremer 2020; Mikalef et al., 2022).
Objectives of the Special Issue
This special issue calls the various research perspectives and topics of Bright Internet and Bright AI that can maximize the benefit of AI controlling the risks that AI may cause as ethics of AI and humans. The Bright Origin can be studied from the perspective of individual, organizational, and national origins.
Recall the Bright Internet was proposed as an approach to preventive cybersecurity that can mitigate the threat sources from the origins. It was announced in 2015 as a grand vision of the Association of Information Systems (Lee 2015). Since then, the first Bright Internet Global Symposium has been held every December 2017 in Seoul as a workshop at the International Conference of Information Systems. It was held annually in Seoul, San Francisco, Munich, Austin, and Hyderabad. The history of the symposium is posted at www.brightintenet.org. The Bright Internet Regional Symposium was also held annually. Since 1998, the symposium has been held in cooperation with the International Conference on Electronic Commerce (htttp://www.icec.net). The theme of the forthcoming ICEC2024 in Seoul is “Empowering Bright Internet and Bright AI” as a continuing endeavor. This Special Issue will be organized in cooperation with the symposium of ICEC2024 that will be held on May 29, 2024, in Seoul, South Korea. Authors of high-quality symposium papers will be invited to submit their complete versions for fast-track review in the special issue.
In this special issue, we are interested in novel and thought-provoking contributions about Bright Internet and Bright AI across all levels and domains. We welcome a wide spectrum of research on related issues without any constraints in terms of theory, method, or context. Potential topics of interest for this special issue include the following areas in general but not limited to:
AI and its impact on Bright Internet in general
AI and ethical implications for Bright Internet
AI governance for Bright Internet
Fostering collaboration with AI for Bright Internet
AI security challenges faced by individuals, organizations, communities, and/or countries and strategies to address them
Privacy and data breaches relevant to the usage of AI systems for Bright Internet
Novel preventive security mechanisms using AI for deterring cyber threat
Transparency and explainability in AI systems for Bright Internet
Bias and fairness considerations in AI systems for Bright Internet
Trust and accountability mechanisms for AI systems for Bright Internet
Building a trustful society based on the trustful email-based ID
Organizational Bright Origin as Social Responsibility
Effect of outbound spam mail management
Balancing privacy with cybersecurity and self-defense right
Framework of Origin Responsibility of AI
Balancing the Identifiability and Anonymity of AI
Applications of Bright Internet in e-Commerce Platform
Applications of Bright Internet in Social Networks
Regulation and market-driven models of Bright Internet deployment
Stakeholders of Bright Internet and Business Models
Generative AI: Framework of intellectual property right and ownership
Addressing discrimination and the dark side of AI
Social and ethical governance of virtual digital human for Bright Internet
Digital responsibility of AI systems for Bright Internet
Ethical AI in Bright Internet Ecosystem
AI and digital inclusion
Special Issue Guest Editors
Daegon Cho (email@example.com): Coordinating guest editor
College of Business, KAIST, Korea
Shan Liu (firstname.lastname@example.org)
Xi’an Jiaotong University, China
Dan J. Kim (email@example.com)
University of North Texas, USA
Special Issue Guest Advisory Editor
Jae Kyu Lee (firstname.lastname@example.org)
Xi’an Jiaotong University, China and College of Business, KAIST, Korea
Submission start date: January 1, 2024.
Submission deadline: July 31, 2024.
Target publication date: April 2025.
All the submissions should follow the general author guidelines of Decision Support Systems available at https://www.elsevier.com/journals/decision-support-systems/0167-9236/guide-for-authors.
Kindly submit your paper to the Special Issue category (SI: Empowering Bright Internet and Bright AI) through the online submission system (https://www.editorialmanager.com/decsup/default2.aspx) of Decision Support Systems. Each paper submitted in the SI would undergo a minimum of 2-3 rounds of double-blind peer review. Each manuscript would have 2-3 reviewers who would attempt to provide constructive feedback.
To be invited for a fast-track ICEC 2024 symposium paper, submit a complete version of the paper to ICEC 2024 submission systems first. Selected manuscripts will be invited to submit via the submission system of Decision Support Systems. For information regarding the paper submission procedure for ICEC2024, please visit http://ICEC.net.
Benjamin, V., Valacich, J. S., & Chen, H. (2019). DICE-E: A framework for conducting Darknet identification, collection, evaluation with ethics. MIS Quarterly, 43(1), 1–22.
Bera, D., Ogbanufe, O., & Kim, D. L. (2023). Towards a thematic dimensional framework of online fraud: An exploration of fraudulent email attack tactics and intentions. Decision Support Systems, 171, 113977.
Bose, I., & Leung, A. C. M. (2019). Adoption of identity theft countermeasures and its short- And long-term impact on firm value. MIS Quarterly, 43(1), 313–327.
Chau, M., Li, T. M. H., Wong, P. W. C., Xu, J. J., Yip, P. S. F., & Chen, H. (2020). Finding people with emotional distress in online social media: A design combining machine learning and rule-BASED classification. MIS Quarterly, 44(2), 933–956.
Danaher, B., Hersh, J., Smith, M. D., & Telang, R. (2020). The effect of piracy website blocking on consumer behavior. MIS Quarterly, 44(2), 631–659.
Dennis, A. R., Moravec, P. L., & Kim, A. (2023). Search & Verify: Misinformation and source evaluations in Internet search results. Decision Support Systems, 171, 113976.
De Cremer, D. (2020). What does building a fair AI really entail. Harvard Business Review.
Ju, J., Cho, D., Lee, J. K., & Ahn, J. H. (2021). Can It Clean Up Your Inbox? Evidence from South Korean Anti-spam Legislation. Production and Operations Management, 30(8), 2636–2652.
Lee, J. K. (2015). Guest editorial: Research framework for AIS grand vision of the bright ICT initiative. MIS quarterly, 39(2), iii-xii.
Lee, J. K. (2016). Reflections on ICT-enabled bright society research. Information Systems Research, 27(1), 1–5.
Lee, J. K., Chang, Y., Kwon, H. Y., & Kim, B. (2020). Reconciliation of Privacy with Preventive Cybersecurity: The Bright Internet Approach. Information Systems Frontiers, 22(1), 45–57.
Lee, J. K., Cho, D., & Lim, G. G. (2018). Design and validation of the bright internet. Journal of the Association for Information Systems, 19(2), 63–85.
Lee, J. K., Park, J., Gregor, S., & Yoon, V. (2021). Axiomatic theories and improving the relevance of information systems research. Information Systems Research, 32(1), 147–171.
Mikalef, P., Conboy, K., Lundström, J. E., & Popovič, A. (2022). Thinking responsibly about responsible AI and ‘the dark side’ of AI. European Journal of Information Systems, 31(3), 257-268.
Samtani, S., Chai, Y., & Chen, H. (2022). Linking Exploits from the Dark Web to Known Vulnerabilities for Proactive Cyber Threat Intelligence: An Attention-Based Deep Structured Semantic Model. MIS Quarterly, 46(2), 911–946.
Shin, Y. Y., Lee, J. K., & Kim, M. (2018). Preventing state-led cyberattacks using the bright internet and internet peace principles. Journal of the Association for Information Systems, 19(3), 152–181.
Wei, X., Zhang, Z., Zhang, M., Chen, W., & Zeng, D. D. (2022). Combining Crowd and Machine Intelligence to Detect False News on Social Media. MIS Quarterly, 46(2), 977–1008.
Xu, J., Chen, D., Chau, M., Li, L., & Zheng, H. (2022). Peer-to-Peer Loan Fraud Detection: Constructing Features from Transaction Data. MIS Quarterly, 45(3), 1777–1792.
Data Science and Management, DSM
Special Issue of Data Science and Management
"AI-powered E-Commerce and Information Management"
In recent years, artificial intelligence (AI) has been deeply integrated with customer service and supply chain optimization, reshaping the e-commerce with great changes. Based on its powerful analysis competence and excellent learning ability, AI presents opportunities to gain useful insights from big data, promote information management, and perform several tasks autonomously that were previously performed by humans. For example, AI-powered recommendation systems and chatbots can help to provide precise, convenient, and personalized customer services (Hoyer, Kroschke, Schmitt, Kraume, & Shankar, 2020), thus improving customers’ experience (Ameen, Tarhini, Reppel, & Anand, 2021) and employees’ work efficiencies. Although increasing research focusing on AI-powered E-Commerce has explored the impact of AI on the behavior of customers and employees, the emerging Generative Artificial Intelligence (GAI) such as ChatGPT (Paul, Ueno, & Dennis, 2023) is calling into question our existing assumptions due to the tendency of transforming from weak AI to strong AI.
Given the ubiquitous use of AI in e-commerce today, there are many fascinating phenomena and research questions that are understudied. For example, the horrendously accurate recommendation algorithms may bring information cocoons problem (Nechushtai & Lewis, 2019), limiting customers obtain diverse information. It may also give customers a sense of being monitored, raising privacy concerns. For employees, AI increasingly threatens their work processes and even replace their jobs (Mirbabaie, Brünker, Möllmann (Frick), & Stieglitz, 2021). These phenomena highlight the significant negative or detrimental consequences of AI to customers, employees, and organizations that are worthy of further research attention. Therefore, in the context of AI-powered e-commerce, we call for a need to understand the role of AI’s characteristics like autonomy, to investigate the resources and mechanisms of the ethics issues like privacy, and to explore how better human-AI interactions and information management can be achieved by interaction designs.
Possible Topics of Submissions
Based on this context, the topics of this special issue tentatively contain, but are not limited to the following areas:
AI-powered information management, analysis, and optimization
Customer behaviors and experience in AI-powered e-commerce
Employee behaviors and performance in human-AI collaboration
Organization strategies and business model innovations in AI-powered e-commerce
Design for human-AI interaction
Explainability, robustness, responsible AI in e-commerce
Algorithmic bias and fairness issues
Information cocoons and elimination
Ethics issues (e.g., trust, privacy, and accountability) and governance
The impact of GAI in e-commerce
Emerging e-commerce and information management issues in the age of AI
AI and platform economy
The social and regulations issues related to AI
Intelligent applications in industries (e.g., healthcare, e-commerce, and manufacturing)
Data Science and Management
Data Science and Management (DSM) is a quarterly SCOPUS Indexed international journal. It is also on the journal list of FMS Journal Rating Guide. DSM is a peer-reviewed journal for original research articles, review articles and technical reports related to all aspects of data science and its application in the field of business, engineering, and social management. For further information, refer to the Science Direct at https://www.sciencedirect.com/journal/data-science-and-management.
Forms of Submission
This special issue will consist of:
(1) The papers from an open call selected from the ICEC2024 (International Conference on Electronic Commerce 2024) as posted at http://www.icec.net;
(2) Voluntary submitted papers according to the due date; and
(3) Invited papers that are requested from the editorial members.
All submitted papers and invited papers will go through peer review.
The submission due date for ICEC2024 is February 28, 2024, and conference dates are May 29-31, 2024 at Seoul as posted at https://www.icec.net/cfp.
Manuscripts are recommended to submit to ICEC 2024 submission systems first. Then, accepted manuscripts will be selected and invited to revise to submit via the fast-track submissions system of Data Science and Management (https://www.editorialmanager.com/dsm/default2.aspx). The submission schedule of revised papers and new voluntary and invited submission are:
Submission Deadline: 31th July, 2024.
Notification of first round reviews and acceptance: 30th September, 2024.
Revised manuscripts due: 30th November, 2024.
Notification of second round reviews and acceptance: 15th January 2025.
Final manuscript due: 28th February, 2025
Last date for final acceptance: 15th April, 2025
Zhaohua Deng (email@example.com)
Huazhong University of Science and Technology, China
Zhaohua Deng is a Professor of School of Management at Huazhong University of Science and Technology. She serves as an Associate Editor of Data Science and Management. Her research interests include AI, information management, e-health, and knowledge management. Her research has appeared in journals such as Information Systems Journal, Information & Management, Journal of Association of Information Systems and Technology, International Journal of Information Management, Information Systems Frontiers.
Shan Liu (firstname.lastname@example.org)
Xi’an Jiaotong University, China
Shan Liu is a Professor at the School of Management in Xi’an Jiaotong University. His research interests focus on artificial intelligence, IT-enabled supply chain management, and platform economy. He has published more than 80 refereed publications including papers that have appeared in Journal of Operations Management, Information Systems Journal, European Journal of Information Systems, European Journal of Operational Research, Information & Management, and IEEE Transactions on Engineering Management. He currently serves as an Executive Editor of Data Science and Management, and Associate Editor of Decision Support Systems and Electronic Commerce Research and Applications.
Kyoung Jun Lee (email@example.com)
Kyung Hee University, South Korea
Kyoung Jun Lee is a professor of AI and Business at Kyung Hee University in Seoul, South Korea. He is the director of Research Institute of UCAI (User-Centric AI) Forum and the Humanitas Big Data Research Center. Lee received his B.S., M.S., and Ph.D. degrees in Management Science from the Korea Advanced Institute of Science and Technology (KAIST), as well as a M.S. and Ph.D. in Public Administration from Seoul National University. Lee has won the Innovative Applications of Artificial Intelligence Awards from the American Association for Artificial Intelligence (AAAI) in 1995, 1997, and 2020. He has also served as a visiting scientist and professor at Carnegie Mellon University, the Massachusetts Institute of Technology, and the University of California at Berkeley. Lee was the President of the Korean Intelligent Information Systems Society in 2017. He is a Vice President of the Korean Academic Society for Business Administration and the Korean Management Information Systems Society. He received 2018 Presidential Award for his contribution to e-government of Korea. He was a member of the Government 3.0 Committee of Korea government. He advised LG CNS, MINDS Lab, Harex Infotech, Riiid, Naver, Samsung C&T, LG Electronics, Samsung Electronics, KT, SK Telecom, and BC Card etc. He is now the 4th Industrial Revolution Policy Advisor for the Busan city. He selected the Korea AI Start-up 25 in 2020, and has been serving as the chair of the Selection Committee for Korea AI Start-up 100 in 2021 and 2022.
Haibing Lu (firstname.lastname@example.org)
Santa Clara University, USA
Haibing Lu is a Professor and Department Co-Chair of Information Systems & Analytics at Santa Clara University. He joined Santa Clara University in fall 2011, right after receiving his Ph.D. in Management (Information Technology) from Rutgers University. He earned his B.S. and M.S. degrees both in mathematics from Xi’an Jiaotong University, China, in 2002 and 2005 respectively. He is a frequent recipient of the SCU Leavey Business School’s Extraordinary Research, Teaching and Service Awards. He has expertise in information privacy & security, and data analytics. He is particularly interested in applying state-of-art technologies to real-world problems, e.g., private keyword search in cloud computing, reinforcement learning for sales representative engagement, analytics for smart energy, privacy-preserving textual analytics, machine learning fairness. He has published over 50 well-cited technical papers in leading journals, including IEEE Transactions on Dependable and Secure Computing, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Big Data, ACM Transactions on Management Information Systems, INFORMS Journal on Computing, Manufacturing Service Operations Management, and premium computer science conferences, including KDD, S&P, ICDM, and ICDE. His research has been supported by companies and organizations, e.g., GEIRI North America, Ultimate Software, AKTANA, and Markkula Center. His research is reported by the United Nations, Forbes, and WIRED Magazine.
Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114(September 2020), 106548. https://doi.org/10.1016/j.chb.2020.106548
Hoyer, W. D., Kroschke, M., Schmitt, B., Kraume, K., & Shankar, V. (2020). Transforming the Customer Experience Through New Technologies. Journal of Interactive Marketing, 51, 57–71. https://doi.org/10.1016/j.intmar.2020.04.001
Mirbabaie, M., Brünker, F., Möllmann (Frick), N. R. J., & Stieglitz, S. (2021). The rise of artificial intelligence – understanding the AI identity threat at the workplace. Electronic Markets, (0123456789). https://doi.org/10.1007/s12525-021-00496-x
Nechushtai, E., & Lewis, S. C. (2019). What kind of news gatekeepers do we want machines to be? Filter bubbles, fragmentation, and the normative dimensions of algorithmic recommendations. Computers in Human Behavior, 90(January 2018), 298–307. https://doi.org/10.1016/j.chb.2018.07.043
Paul, J., Ueno, A., & Dennis, C. (2023). ChatGPT and consumers: Benefits, Pitfalls and Future Research Agenda. International Journal of Consumer Studies, 47(4), 1213–1225. https://doi.org/10.1111/ijcs.12928