Decision Analytics and Service Science

The Decision Analytics and Service Science Track got started more than 20 years ago at the HICSS-31 in 1998 under the name Modelling Technologies and Intelligent Systems. The name and the focus shifted at HICSS-33 to Decision Technology in Management and the use of information systems in support of managerial planning, problem solving and decision making. The theme changed again to Decision Technology and Service Science for HICSS-43. The track was run with quite some success, with around 12 mini-tracks that collected high-quality papers.

We reacted to the rise of mobile technology early on and started a mini-track on mobile commerce and mobile services at HICSS-35 in 2002. Mobile technologies quickly got adopted by several other tracks and a first critical mass of papers to one track could be realized at HICSS-45. The track changed name to Decision Technology, Mobile Services and Service Science in 2012 when Dan Dolk asked Prof Christer Carlsson of the Abo Akademi University in Finland to join him as track co-chair.

As Dan Dolk stepped down after running the track successfully for 14 years, Prof Haluk Demirkan, University of Washington, was elected to join Christer Carlsson as track co-chair. Discussions had been going on for some years to incorporate the new analytics movement, which is a major shift in producing critical data, information and knowledge for managerial planning, problem solving and decision making. Analytics relies on software to make use of analytical theory and advanced algorithms as part of corporate and enterprise information systems. The track changed name to Decision Analytics, Mobile Services and Service Science for HICSS-46 in 2013. One more change was made for HICSS-53, the name is now Decision Analytics and Service Science (DA/SS) as mobile services have merged with digital services, at least in the perceptions of the users. Digital technology is moving into the core of research in information systems and decision analytics into both business planning and the use of information systems.

There have been several memorable events organized by the track over the two decades of operation. Space does not permit to report them in any detail – we discussed some moments in one of the history sessions at HICSS-50 – but the full-day workshop Evolution of Mobile Ecosystems that Nokia and Microsoft organized at HICSS-46 is probably historic, some of the disruptions that changed the mobile technology industry forever took form in the workshop in which a group of invited professors challenged Nokia and Microsoft executives. Nokia later sold its mobile phones division to Microsoft and refocused on digital network technology and 5G networks. The DA/SS Track works out emerging managerial and organizational decision-making strategies, processes, tools, technologies, services and solutions in the Digital Age. This is done in 2 interrelated themes. The first theme, Decision Analytics, focuses on decision making processes, analytics tools and supporting technologies which has collected papers on big data and analytics, machine learning, business and service analytics, gamification, virtual and augmented reality, visual decision analytics, soft computing, logistics and supply chain management, explainable AI, etc., which now are core research themes in analytics. Challenges and issues of service industries, service science, digitalization of services, digital mobile services, smart service systems, smart cities and communities, smart mobility services, social robots, etc. form the Service Science.

In the 2022 HICSS, the DA/SS Track has grown to 34 minitracks:

1. Machine Learning and Predictive Analytics in Accounting, Finance, and Management
2. Accountability, Evaluation, and Obscurity of AI Algorithms
3. Algorithm-based Advisory in the Service Sector
4. Big Data and Analytics: Pathways to Maturity
5. Delivering IoT Services using Blockchain
6. Data, Text and Web Mining for Business Analytics
7. Co-Creating Value in the Circular Economy with Financial Services
8. Data-driven Services in Manufacturing: Management, Engineering and Organizational Transformation
9. Decision Analytics, Machine Learning, and Field Experimentation for Defense and Emergency Response
10. Digital Innovation in a Networked World
11. Digital Mobile Services for Everyday Life
12. Digital and Cybernized Services and Digitalization of Services
13. Simulation Modelling and Digital Twins for Decision Making in the Age of Industry 4.0
14. Fairness in Algorithmic Decision Making
15. Fraud Detection Using Machine Learning
16. Gamification
17. Analytics and Decision Support for Green IS and Sustainability Applications
18. Case Studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Platforms
19. Learning Analytics
20. Practitioner Research Insights: Applications of Science and Technology to Real-World Innovations
21. Personal Data: Analytics and Management
22. Education, Research and Application of Quantum Computing
23. Service Analytics
24. Service Science
25. Decision Support for Smart City
26. Smart Mobility Ecosystems and Services
27. Smart Service Systems Design
28. Soft Computing: Theory Innovations and Problem Solving Benefits
29. Intelligent Decision Support for Logistics and Supply Chain Management
30. Technology and Analytics in Emerging Markets (TAEM)
31. Social Robots - Robotics and Toy Computing
32. Mixed, Augmented and Virtual Reality: Services and Applications
33. Interactive Visual Analytics and Visualization for Decision Making
34. Explainable Artificial Intelligence (XAI)

The minitrack chairs have written brief summaries of their mini-tracks and overviews of the papers in their sessions. We wish to thank all the people who have worked effectively and diligently to develop the DA Track. The authors who have contributed new research results, the MT chairs who have spent countless hours to get good quality papers, to get reviewers to accept work for HICSS and then to evaluate and judge the review results. The high-quality collection of 114 accepted papers in the DA Track (with an acceptance rate of 48.93 %) is a result of their efforts.

Christer Carlsson
IAMSR & Abo Akademi University
Christer.Carlsson@abo.fi

Haluk Demirkan
University of Washington - Tacoma
haluk@uw.edu