The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs). Manuscripts may draw from diverse methods and methodologies, including those from decision theory, economics, econometrics, statistics, computer supported cooperative work, data base management, linguistics, management science, mathematical modeling, operations management, cognitive science, psychology, user interface management, and others. However, a manuscript focused on direct contributions to any of these related areas should be submitted to an outlet appropriate to the specific area.

Examples of research topics that would be appropriate for Decision Support Systems include the following:

1. DSS Foundations e.g. principles, concepts, and theories of enhanced decision making; formal languages and research methods enabling improvements in decision making. It is important that theory validation be carefully addressed.

2. DSS Functionality e.g. methods, tools, and techniques for developing thefunctional aspects of enhanced decision making; solver, model, and/or data management in DSSs; rule formulation and management in DSSs; DSS development and use in computer supported cooperative work, negotiation, research and product.

3. DSS Interfaces e.g. methods, tools, and techniques for designing and developing DSS interfaces; development, management, and presentation of knowledge in a DSS; coordination of a DSS's interface with its functionality.

4. DSS Implementation - experiences in DSS development and utilization; DSS management and updating; DSS instruction/training. A critical consideration must be how specific experiences provide more general implications.

5. DSS Evaluation and Impact e.g. evaluation metrics and processes; DSS impact on decision makers, organizational processes and performance.

Special Issue on Generative AI: Transforming Human, Business, and Organizational Decision Making
截稿日期: 2024-11-30

Generative Artificial Intelligence (GenAI) represents the next level of machine learning by going beyond recognizing patterns and making inferences to generating new content that mimics the training data of a variety of forms including text, audio, image, video, music, artwork, simulation, and even programming codes [1,5,9]. Hence, GenAI uses algorithms to enable users to generate new content based on a variety of inputs (prompts) that can be in multiple forms such as text, audio, image, video, and musical notes [4]. Given that prompts serve as the bridge between human intent and machine understanding, the ability to generate and use effective prompts has become an essential skill for users to maximize the outcomes of the human-GenAI interaction.

The rapid rise of GenAI technologies has raised both unprecedented opportunities and challenges to human, business, and organizational decision making for the future of work [4,7]. The impact of GenAI models, such as ChatGPT, is far-reaching, and its applications keep growing, ranging from large language models (LLMs) to learning from available data to predict the response of a target group to advertisements and marketing campaigns to creating new advertisements and marketing campaigns for specific target groups, and from generating a travel itinerary to clinical decision support in screening, prevention, and treatment [3]. Gartner identified GenAI as one of the most impactful and rapidly evolving technologies in the productivity revolution in its report on Emerging Technologies and Trends Impact Radar for 2022 [6]. The Gartner report also predicts that by 2026, more than 90% of IT operations management vendors will have embedded GenAI capabilities in their products and/or services, up from less than 5% in 2023. On the one hand, GenAI tools or systems have the potential to transform the way people learn, create multimedia content, perform tasks, and make decisions [2]. They can help simplify organizational tasks and operations with efficiency across a variety of use cases. On the other hand, the newfound capability of GenAI also raises risks and concerns about misinformation, plagiarism, copyright infringements, harmful or offensive content, biases, deepfakes, etc. that may result in significant negative impact on individuals, organizations, and society at large [1,4,5,8]. Hence, responsible, trustworthy, and ethical GenAI regulation and content moderation need to be in place.

GenAI can transform or revolutionize decision making in a variety of ways. For example, the predictive and generative prowess of GenAI enables not only more accurate forecasts but also accelerates data-driven design and decision making based on trends and discoveries from large datasets. GenAI can help generate innovative solutions to problems and organizational designs that are too complex for traditional analytical methods and reduce repetitive manual processes by automating content creation tasks to enable real-time, on-the-fly decision making that can produce remarkable outcomes. 

Special Issue on Decision Support Systems on Improving Societal Outcomes with Design Science Research
截稿日期: 2025-01-31

This special issue targets DSR that addresses societal problems. In particular, we encourage submissions linked to any of the 17 sustainable development goals (SDGs) identified by the United Nations , as well as work dealing with technologies that are transforming the world in which we live, such as Artificial Intelligence (AI).

Guest editors:

Leona Chandra Kruse, Department of Information Systems, University of Agder, Norway, leona.chandra@uia.no
Jeffrey Parsons, Faculty of Business Administration, Memorial University of Newfoundland, Canada, jeffreyp@mun.ca
Jinsoo Park, College of Business Administration, Seoul National University, South Korea, jinsoo@snu.ac.kr
Thorsten Schoormann, Business Informatics, TU Braunschweig, Germany, Thorsten.Schoormann@tu-braunschweig.de

Special issue information:

Background

Design science research (DSR) deals with the design of artifacts to solve identifiable problems and the abstraction of knowledge from that process. In its original conceptualization, DSR has been popularly characterized as research that “created and evaluates IT artifact intended to solve identified organizational problems” (Hevner et al., 2004, p. 77, emphasis added). More broadly, there is a recognition that DSR leads to artifacts that “serve human purposes” (March and Smith, 1995, p. 253). In particular, DSR can serve as an approach to tackle many of the wicked problems facing society today, including poverty, health, environmental degradation, climate change, disinformation, and terrorism.

This special issue targets DSR that addresses societal problems. In particular, we encourage submissions linked to any of the 17 sustainable development goals (SDGs) identified by the United Nations, as well as work dealing with technologies that are transforming the world in which we live, such as Artificial Intelligence (AI). Recent studies in Decision Support Systems (DSS) have notably contributed to SDGs, spanning from enhancing healthcare quality (e.g., Ojo et al., 2024) to optimizing resource efficiency (e.g., Ge et al., 2024). Storey et al. (2024) emphasized the significance of integrating human-AI synergies in sociotechnical DSS design. Transparency is pivotal in advocating responsible DSR practices and design artifacts (Hevner et al., 2024).

Recent DSR publications reflect a growing consensus within the community regarding the imperative to advance sustainable development. Strobel, et al. (2023) leveraged AI to translate sign language and improve participation of individuals with hearing difficulties in social activities. Wass, Thygesen, and Purao (2023) designed and deployed information systems to promote the social inclusion of people with intellectual and developmental disabilities. With both DSR projects, the authors improved access to quality healthcare and equality. Other examples focus on promoting ecological sustainability, such as Schoormann, Stadtländer, and Knackstedt (2022) and Seidel, et al. (2018). Pan, et al. (2021) conducted an Action Design Research to support wildlife management for the purpose of environmental protection.

Examples such as these demonstrate the promise of DSR as a research paradigm for tangible societal impacts. With this special issue, we hope to encourage fellow design science researchers to create even greater impacts together.

Themes of the Special Issue

This special issue aims to curate and present state-of-the-art design science research on topics related to delivering social good through the design and deployment of information systems. Although conceptual and methodological papers in this vein are welcome, the focus of this special issue on exemplars of DSR. We welcome original research that focuses on a variety of topics and themes, including, but not limited to:

    Contributing to sustainable development with DSR
    Designing and deploying innovative information systems for accessible quality education or quality healthcare
    Designing and deploying innovative information systems to improve access to clean water and sanitation
    The role of DSR in social change
    DSR to mitigate misinformation
    Combining social and technical approaches in DSR for social good
    The challenge of evaluating DSR solutions to wicked problems
    DSR for designing and deploying responsible artifacts
    Considering indigenous values in DSR
    Designing information systems for fairness and justice
    DSR for human flourishing

Manuscript submission information:

The Decision Support Systems’ submission system will be open for submissions to our Special Issue from September 1, 2024. When submitting your manuscript to Editorial Manager, please select the article type “VSI: Design Science for Social Good”. Please submit your manuscript before January 31, 2025.

All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.

Please ensure you read the Guide for Authors before writing your manuscript. The Guide for Authors and link to submit your manuscript is available on the Journal’s homepage at: Guide for authors - Decision Support Systems - ISSN 0167-9236 | ScienceDirect.com by Elsevier