Getting Around to It: How Design Science Researchers Set Future Work Agendas

Background: There is a long tradition of writing about future work in research papers, and information systems design science research (IS DSR) is no exception. However, there is a lack of studies on (1) how IS DSR authors currently envision the next steps for their work and (2) guidelines to improve the communication of opportunities to accumulate knowledge. Method: This paper contributes to this topic, building on a systematic literature review of 123 IS DSR papers published between 2018 and 2022. Results: Design-oriented research requires the research team to decide which tasks to carry out immediately in building the future and which to postpone as research debt. The paper\u27s contribution is threefold. First, we propose a research debt lifecycle to support (1) project stakeholders, (2) IS DSR community, and (3) societies looking for better futures. Second, we discuss the anatomy of future work in recent IS DSR. Finally, we suggest guidelines to manage and report the next research steps. Conclusion: This paper presents a pioneering assessment of future work suggestions in the IS field, focusing on the design science research paradigm. Future work directions emerge from researchers\u27 choices during the IS DSR process that must be continuously managed

Designing Real-Time Feedback for Bidders in Homogeneous-Item Continuous Combinatorial Auctions

Although combinatorial auctions are important mechanisms for many specialized applications, their adoption in general-purpose marketplaces is still fairly limited, partly due to the inherent difficulty in evaluating the efficacy of bids without the availability of comprehensive bidder support. In this paper, we present both theo-retical results and computational designs to support real-time feedback to bidders in continuous combinatorial auctions, where bidders are free to join and leave the auction at any time. In particular, we focus on the broad class of single-item multi-unit (SIMU) combinatorial auctions, where multiple identical units of one homogenous item are being auctioned. We also consider two common ways to express bidding preferences: OR bids and XOR bids. For SIMU auctions with each of the two bid types, we present comprehensive analyses of auction dynamics, which can determine winning bids that satisfy allocative fairness, and compute critical evaluative metrics needed to provide bidder support, including bid winning and deadness levels. We also design the data structures and algorithms needed to provide bidder support in real time for SIMU auctions of practically relevant sizes. The computational tools proposed in this paper can facilitate the efficient and more transparent implementation of SIMU combinatorial auctions in business- and consumer-oriented markets