Exploring the Structure of Software Development Research: A Preliminary Text Analysis

Software development projects are critical to organizations when seeking operational efficiencies, competitive advantage, or both. In this research we use text analytics and bibliometrics to identify the key topics of software development that were studied in IS research published in four top IS journals. We also discuss the distribution of various topics across years and the underlying cluster groupings

Toward Understanding the Dynamics of Bidder Behavior in Continuous Combinatorial Auctions: Agent-Based Simulation Approach

Combinatorial auctions represent sophisticated market mechanisms that are becoming increasingly important in various business applications due to their ability to improve economic efficiency and auction revenue, especially in settings where participants tend to exhibit more complex user preferences and valuations. While recent studies on such auctions have found heterogeneity in bidder behavior and its varying effect on auction outcomes, the area of bidder behavior and its impact on economic outcomes in combinatorial auctions is still largely underexplored. One of the main reasons is that it is nearly impossible to control for the type of bidder behavior in real world or experimental auction setups. We propose an agent-based modeling approach to replicate human bidder behavior in continuous combinatorial auctions and leverage our agents to simulate a wide variety of competition types, including experimentally unobserved ones that could not otherwise be studied. The capabilities of the proposed approach enable more comprehensive studies (via richer controlled experiments) of bidding behavior in the complex and highly dynamic decision environment of continuous combinatorial auctions

A USER’S COGNITIVE WORKLOAD PERSPECTIVE IN NEGOTIATION SUPPORT SYSTEMS: AN EYE-TRACKING EXPERIMENT

Replying to several research calls, I report promising results from an initial experiment which com-pares different negotiation support system approaches concerning their potential to reduce a user’s cognitive workload. Using a novel laboratory-based non-intrusive objective measurement technique which derives the user’s cognitive workload from pupillary responses and eye-movements, I experi-mentally evaluated a standard, a chat-based, and an argumentation-based negotiation support system and found that a higher assistance level of negotiation support systems actually leads to a lower user’s cognitive workload. In more detail, I found that an argumentation-based system which fully automates the generation of the user’s arguments significantly decreases the user’s cognitive workload compared to a standard system. In addition I found that a negotiation support system implementing an additional chat function significantly causes higher cognitive workload for users compared to a standard system

Information Systems Research Themes: A Seventeen-year Data-driven Temporal Analysis

Extending the research on our discipline’s identity, we examine how the major research themes have evolved in four top IS journals: Management Information Systems Quarterly (MISQ), Information Systems Research (ISR), Journal of the Association for Information Systems (JAIS), and Journal of Management Information Systems (JMIS). By doing so, we answer Palvia, Daneshvar Kakhki, Ghoshal, Uppala, and Wang’s (2015) call to provide continuous updates to the research trends in IS due to the discipline’s dynamism. Second, building on Sidorov, Evangelopoulos, Valacich, and Ramakrishnan (2008) we examine temporal trends in prominent research streams over the last 17 years. We show that, as IS research evolves over time, certain themes appear to endure the test of time, while others peak and trough. More importantly, our analysis identifies new emergent themes that have begun to gain prominence in IS research community. Further, we break down our findings by journal and show the type of content that they may desire most. Our findings also allow the IS research community to discern the specific contributions and roles of our premier journals in the evolution of research themes over time

A Principal-Agent Model of Bidding Firms in Multi-Unit Auctions

Principal-agent relationships in bidding firms are widespread in high-stakes auctions. Often only the agent has information about the value of the objects being sold. The board wants to maximize the profit, but the management wants to win the package with the highest value. In environments in which it is efficient for firms to coordinate on jointly winning packages, we show that the principals would coordinate, while the agents would not. We analyze environments with decreasing levels of information that the principal has about the valuations. Depending on the auction format it can be impossible to set budget constraints that align the agents’ strategies in equilibrium. The analysis helps explain price wars in high-stakes auctions

Corporate Sponsorship of Academic Research: The Trend, Its Drivers, and Its Implications

Budgets are shrinking in higher education, and greater financial accountability is simultaneously being demanded of universities. One of the consequences is that internal funding for research is more difficult to access than in years past. In such an environment, corporate sponsorship is an alternative that must be considered. In this article, we describe the forces compelling business schools to seek corporate sponsorship for research. Then, we discuss why some business faculty may perceive undesirable constraints in corporate-sponsored research. We also describe the challenges that researchers often need to address in order to secure corporate sponsorship and take full advantage of it. We conclude by describing some of the implications of this paradigm shift in research funding. When corporate funding is accessed and the relationship with the sponsoring organization is managed well, incentives are aligned among researchers, universities, and corporations. Benefits also include the development of new knowledge, solutions to real-world business problems, funding for researchers and universities, enhanced teaching, and a clear demonstration of the value of academic research

Making and Evaluating Participant Choice in Experimental Research on Information Technology: A Framework and Assessment

Evaluations of participant samples for experiments in information systems research often appear to be informal and intuitive. Appropriate participant choice becomes a more salient issue as the population of information technology professionals and users grows increasingly diverse, and the distribution of relevant characteristics in participant samples such as age, gender, nationality, and experience can often be unrepresentative of the characteristics’ distribution in target populations. In this paper, we present a framework based on widely accepted standards for evaluating participant choice and providing rationale that the choice is appropriate. Using a step-by-step approach, we compare current practice in experimental studies from top information systems journals to this framework. Based on this comparison, we recommend how to improve the treatment of participant choice when evaluating the validity of study inferences and how to discuss the tradeoffs involved in choosing participant samples

Bidder Behavior in Complex Trading Environments: Modeling, Simulations, and Agent-Enabled Experiments

University of Minnesota Ph.D. dissertation. January 2018. Major: Business Administration. Advisor: Gediminas Adomavicius. 1 computer file (PDF); vi, 90 pages.Combinatorial auctions represent sophisticated market mechanisms that are becoming increasingly important in various business applications due to their ability to improve economic efficiency and auction revenue, especially in settings where participants tend to exhibit more complex user preferences and valuations. While recent studies on such auctions have found heterogeneity in bidder behavior and its varying effect on auction outcomes, the area of bidder behavior and its impact on economic outcomes in combinatorial auctions is still largely underexplored. One of the main reasons is that it is nearly impossible to control for the type of bidder behavior in real world or experimental auction setups. In my dissertation I propose two data-driven approaches (heuristic-based in the first part and machine-learning-based in the second part) to design and develop software agents that replicate several canonical types of human behavior observed in this complex trading mechanism. Leveraging these agents in an agent-based simulation framework, I examine the effect of different bidder compositions (i.e., competing against bidders with different bidding strategies) on auction outcomes and bidder behavior. I use the case of continuous combinatorial auctions to demonstrate both approaches and provide insights that facilitate the implementation of this combinatorial design for online marketplaces. In the third part of my thesis, I conduct human vs. machine style experiments by integrating the bidding agents into an experimental combinatorial auction platform, where participants play against (human-like) agents with certain pre-determined bidding strategies. This part investigates the impact of different competitive environments on bidder behavior and auction outcomes, the underlying reasons for different behaviors, and how bidders learn under different competitive environments

Three Studies on Multi-attribute Market Mechanisms in E-procurement

Successful e-procurement depends on selecting the appropriate mechanisms that comprise rules governing and facilitating transaction process. Existing mechanisms have theoretical or practical limitations such as limited number of attributes, disclosure of buyer’s preferences and costly processes. The present research addresses these issues through three studies. Study 1 presents two feasible mechanisms for multi-attribute multi-supplier transactions. They allow buyers to control preference representation and information revelation, assuring that suppliers obtain sufficient information in making effective proposals while protecting confidential information. Following the design-science approach, the mechanisms are implemented to support multi-attribute reverse auctions and multi-bilateral negotiations. Study 2 examines the revelation of information in multi-attribute reverse auctions. Three revelation rules are formulated with admissible bids, winning bids and all bidders’ bids. Their effects on the process, outcomes and bidders’ assessment are tested in two experiments. The results show significant improvement in process efficiency when more information is revealed. The suppliers reached better outcomes with either admissible bids only or all bidders’ bids, while the buyers gained more when revealing the winning bids only. Bidders were more satisfied with the outcomes and system when more information was provided. Study 3 compares multi-attribute reverse auctions and multi-bilateral negotiations in both laboratory and online experiments. The results show that auctions are more efficient than negotiations in terms of the process. Auctions led to greater gains for the buyers, whereas more balanced contracts were reached in negotiations. Suppliers’ assessment was affected by their outcomes, and the winning suppliers were more satisfied with the process, outcomes and system. The buyer’s role was also examined. Different types of information conveyed from buyer influence suppliers’ behavior in making bids/offers and concessions, which in turn affected buyer’s gains. This research provides implications to future studies and practices in e-procurement, in particular, the formulation of a procedure of two multi-attribute mechanisms and the formulation of general guidelines for strategic use of different mechanisms in various e-procurement contexts