{"id":4601,"date":"2025-12-04T10:28:04","date_gmt":"2025-12-04T17:28:04","guid":{"rendered":"https:\/\/blogs.ubc.ca\/genemoolee\/?p=4601"},"modified":"2026-04-26T20:26:30","modified_gmt":"2026-04-27T03:26:30","slug":"computational-design-science-and-ai-research-in-information-systems","status":"publish","type":"post","link":"https:\/\/blogs.ubc.ca\/genemoolee\/2025\/12\/04\/computational-design-science-and-ai-research-in-information-systems\/","title":{"rendered":"Computational Design Science and AI Research in Information Systems"},"content":{"rendered":"

First published: December 4, 2025; Updated: April 26, 2026<\/p>\n

In this post, I will discuss the current status of <\/span>computational design science and AI research<\/b> in the Information Systems community, focusing on the <\/span>papers that I have recently handled as an editor in different IS journals (ISR<\/em>, MISQ<\/em>, DSS<\/em>, I&M<\/em>, etc.) and those on which I worked as an author. I will also share my thoughts on the future research agenda.<\/span><\/p>\n

AI is the topic of our time. The reality is that many disciplines are trying to own the AI agenda in business schools (Caro et al. 2025). In my view, the IS community has a unique advantage to lead this AI agenda. To do that, we need to double down on our IS competitive advantage from a <\/span>socio-technical perspective<\/b> (Sarkar et al. 2019). While many neighboring disciplines (e.g., operations, marketing, strategy) can\u00a0<\/span>offer useful societal perspectives on AI, I believe the IS research community has unique strengths in\u00a0opening <\/strong><\/span>the AI black box<\/b>. I don\u2019t think treating AI as one variable is enough. At the same time, if we focus solely on the technical aspects, the distinction from computer science may not be clear. Therefore, our AI research in IS should focus on the <\/span>consequential problems<\/b> in business and society.<\/span><\/p>\n

I had the great fortune to handle many IS papers that fall into this category. Since I started my AE role at ISR<\/em> in 2024, I have accepted the following papers.<\/span><\/p>\n

    \n
  1. X<\/span>ie et al. (2025) proposed a <\/span>novel topic model<\/b> approach to study the <\/span>mental impact (e.g., suicidal thoughts) of short videos<\/b>. After analyzing the limitations of existing neural topic models (across IS and CS), the authors designed a novel topic model that can leverage a <\/span>medical knowledge<\/b> base and evaluated it on two platforms.<\/span><\/li>\n
  2. Gao et al. (2025)\u00a0<\/span>investigated whether\u00a0LLM-based social bots<\/strong> can create socializing values on<\/span> social media platforms. They analyzed comments generated by LLM bots and found that the <\/span>bot<\/b> comment characteristics<\/b> impact user engagement.<\/span><\/li>\n
  3. Wang et al. (2026) proposed a novel computational approach called a\u00a0discrete and regularized deep learning (DRDL)<\/strong> method for multiview data-based dynamic financial risk prediction<\/strong> (DFRP). The proposed approach provides predictive insights into the dynamics of financial risk from entangled information from multiview data.<\/li>\n
  4. Mousavi et al (2026) offered the first holistic comparison of four major approaches of psychometric text analysis<\/strong>: lexicons, custom-built machine learning models, fine-tuned masked language models, and large language models (LLMs)<\/strong>. It also introduced a cognitive-affective prompting strategy for LLMs that emulates these human strengths, yielding performance gains beyond state-of-the-art prompting methods.<\/li>\n<\/ol>\n

    Besides these papers, there are more computational and AI papers in the pipeline.<\/span><\/p>\n

    Moving forward, I think our IS research community should lead the AI agenda in the business school and beyond. In the near future, I hope to see more research in the following areas:<\/span><\/p>\n

      \n
    1. AI impact studies: As a general-purpose technology, AI is making changes across different industry sectors. I hope to see more AI impact studies, but in specific industry sectors such as online videos (Zhang et al. 2025a), journalism (Zhang et al. 2025b), online dating (Kwon et al. 2022), and more.<\/span><\/li>\n
    2. Physical AI: Many AI papers are focusing on knowledge work in the digital space. With the advances of embodied AI, I hope the IS community can also study robots (Lee et al. 2025), drones, and rovers.<\/span><\/li>\n
    3. Quantum AI: I predict that quantum computing will be the next computing paradigm. The IS community can conduct forward-looking research on the topics of quantum computing, quantum communication, and more (<\/span>https:\/\/www3.fox.temple.edu\/discover\/events-conferences\/from-qubits-to-business-value\/<\/span><\/a>).<\/span><\/li>\n<\/ol>\n

      References<\/b><\/p>\n

      Caro, Felipe, Jean-Edouard Colliard, Elena Katok, Axel Ockenfels, Nicolas Stier-Moses, Catherine Tucker, D. J. Wu (2025). Introduction to the Special Issue on the Human-Algorithm Connection. Management Science<\/em>. <\/span>https:\/\/doi.org\/10.1287\/mnsc.2023.intro.v72.n1<\/span><\/a>\u00a0<\/span><\/p>\n

      Gao, Yang, Maggie Mengqing Zhang, Mikhail Lysyakov (2025). Does Social Bot Help Socialize? Evidence from a Microblogging Platform. Information Systems Research<\/em>. <\/span>https:\/\/doi.org\/10.1287\/isre.2024.1089<\/span><\/a><\/p>\n

      Kwon, Soonjae, Sunghyuk Park, Gene Moo Lee, Dongwon Lee (2022). Learning Faces to Predict Matching Probability in an Online Matching Platform. In Proceedings of International Conference on Information Systems<\/em>. https:\/\/aisel.aisnet.org\/icis2022\/digital_commerce\/digital_commerce\/9\/\u00a0<\/a><\/p>\n

      Lee, Myunghwan, Lee, Gene Moo, Shin, Donghyuk, Cho, Wooje, Han, Sang Pil (2025). Service Robots and Workforce Transformation: Evidence from Restaurant Operations. SSRN Working Paper.<\/em> <\/span>http:\/\/dx.doi.org\/10.2139\/ssrn.5288874<\/span><\/a><\/p>\n

      Mousavi, Reza, Brent Kitchens, Abbie Griffith Oliver, Ahmed Abbasi (2026). From Lexicons to Large Language Models: A Holistic Evaluation of Psychometric Text Analysis in Social Science Research. Information Systems Research. https:\/\/doi.org\/10.1287\/isre.2024.1143<\/a><\/p>\n

      Sarker, Suprateek; Chatterjee, Sutirtha; Xiao, Xiao; and Elbanna, Amany (2018). “The Sociotechnical Axis of Cohesion for the IS Discipline: Its Historical Legacy and its Continued Relevance,” MIS Quarterly<\/em>, (43: 3) pp.695-719. https:\/\/doi.org\/10.25300\/MISQ\/2019\/13747<\/a>
      \n<\/span><\/p>\n

      Xie, Jiaheng, Yidong Chai, Ruicheng Liang, Yang Liu, Daniel Dajun Zeng (2025). Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model. Information Systems Research<\/em>. <\/span>https:\/\/doi.org\/10.1287\/isre.2024.1071<\/span><\/a><\/p>\n

      Wang, Zhao, Wanliu Che, Cuiqing Jiang, Huimin Zhao (2026). Leveraging Multiview Data Through Discrete and Regularized Deep Learning for Dynamic Financial Risk Prediction. Information Systems Research<\/em>. https:\/\/doi.org\/10.1287\/isre.2024.1417<\/a><\/p>\n

      Zhang, Xiaoke, Zhou, Mi, Lee, Gene Moo (2025a). AI Voice in Online Video Platforms: A Multimodal Perspective on Content Creation and Consumption. SSRN Working Paper. <\/em><\/span>http:\/\/dx.doi.org\/10.2139\/ssrn.4676705<\/span><\/a>\u00a0<\/span><\/p>\n

      Zhang, Xiaoke, Lee, Myunghwan, Zhou, Mi, Lee, Gene Moo (2025b). Large Language Models in the Institutional Press: Investigating the Effects on News Production and Consumption. SSRN Working Paper<\/em>. <\/span>http:\/\/dx.doi.org\/10.2139\/ssrn.5357471<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

      First published: December 4, 2025; Updated: April 26, 2026 In this post, I will discuss the current status of computational design science and AI research in the Information Systems community, focusing on the papers that I have recently handled as an editor in different IS journals (ISR, MISQ, DSS, I&M, etc.) and those on which […]<\/p>\n","protected":false},"author":51140,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[1264,4381969,4381970,855907],"class_list":["post-4601","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-ai","tag-computational-design-science","tag-design-science","tag-information-systems"],"_links":{"self":[{"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/posts\/4601","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/users\/51140"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/comments?post=4601"}],"version-history":[{"count":19,"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/posts\/4601\/revisions"}],"predecessor-version":[{"id":4689,"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/posts\/4601\/revisions\/4689"}],"wp:attachment":[{"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/media?parent=4601"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/categories?post=4601"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.ubc.ca\/genemoolee\/wp-json\/wp\/v2\/tags?post=4601"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}