Paulo B Goes

Interests

No activities entered.

Courses

Scholarly Contributions

Journals/Publications

• Goes, P. B., Goes, P. B., Guo, C., Guo, C., Lin, M., & Lin, M. (2015). Incentive Hierarchies and User Efforts: Evidence from an Online Knowledge Exchange. Information Systems Research.
• Goes, P. B., Ilk, N., Lin, M., & Zhao, L. (2016). When More is Less: Multitasking and Customer Satisfaction. Management Science.
  More info

  Third round revision (listed as "major revision")
• Goes, P. B. (2015). Editor's Comments: Sandy Slaughter: Outstanding Scholar, Incredible Human Being. MIS Quarterly.
• Goes, P. B. (2015). Editor’s Comments: Inflection Point: Looking Back or Looking Forward?. MIS Quarterly.
• Goes, P. B., Sanchez, O., & Costa, P. (2015). Shaping Customer Confidence in Online Purchasing Decision: The role of DSS Tools Supporting an Information Aggregator. Proceedings of HICSS-48, Hawaii International Conference in Systems Science.
• Sarkar, S., Agarwal, R., Goes, P. B., Gregor, S., Henfridsson, O., Saunders, C., & Tan, B. (2015). Roles and Responsibilities of a Senior Editor. JAIS.
• Alirezazadeh, P., Boylu, F., Garfinkel, R., Gopal, R., & Goes, P. (2014). Identity matching and information acquisition: Estimation of optimal threshold parameters. Decision Support Systems, 57(1), 160-171.
  More info

  Abstract: With the growing volume of collected and stored data from customer interactions that have recently shifted towards online channels, an important challenge faced by today's businesses is appropriately dealing with data quality problems. A key step in the data cleaning process is the matching and merging of customer records to assess the identity of individuals. The practical importance of this research is exemplified by a large client firm that deals with private label credit cards. They needed to know whether there existed histories of new customers within the company, in order to decide on the appropriate parameters of possible card offerings. The company incurs substantial costs if they incorrectly "match" an incoming application with an existing customer (Type I error), and also if they falsely assume that there is no match (Type II error). While there is a good deal of generic identity matching software available, that will provide a "strength" score for each potential match, the question of how to use the scores for new applications is of great interest and is addressed in this work. The academic significance lies in the analysis of the score thresholds that are typically used in decision making. That is, upper and lower thresholds are set, where matches are accepted above the former, rejected below the latter, and more information is gathered between the two. We show, for the first time, that the optimal thresholds can be considered to be parameters of a matching distribution, and a number of estimators of these parameters are developed and analyzed. Then extensive computations show the effects of various factors on the convergence rates of the estimates. © 2013 Elsevier B.V.
• Ayanso, A., Goes, P. B., & Mehta, K. (2014). Range query estimation with data skewness for top-k retrieval. Decision Support Systems, 57(1), 258-273.
  More info

  Abstract: Top-k querying can significantly improve the performance of web-based business intelligence applications such as price comparison and product recommendation systems. Top-k retrieval involves finding a limited number of records in a relational database that are most similar to user-specified attribute-value pairs. This paper extends the cost-based query-mapping method for top-k retrieval by incorporating data skewness in range estimation. Experiments on real world and synthetic multi-attribute data sets show that incorporating data skewness provides a robust performance across different types of data sets, query sets, distance functions, and histograms. © 2013 Elsevier B.V.
• Chen, G., Goes, P. B., Wang, H. J., Zhao, J. L., & Wei, Q. (2014). Guest Editorial: Business Applications of the Web of Things. Decision Support Systems.
• Goes, P. B. (2014). Editor's Comments: Big Data and IS Research. Management Information Systems Quarterly.
• Goes, P. B. (2014). Editor's Comments: Design Science Research in Top Information Systems Journals. Management Information Systems Quarterly.
• Goes, P. B. (2014). Editor's Comments: The MISQ Review System - Operational Perspectives. Management Information Systems Quarterly.
• Goes, P. B., Lin, M., & Au Yeung, C. (2014). Popularity Effect in User-Generated Content. Information Systems Research, 25(2), 222-238.
• Chen, G., Goes, P., Zhao, J. L., Wang, H. J., & Wei, Q. (2013). Guest Editorial: Business applications of Web of Things. Decision Support Systems.
• Fang, X., R., O., & Goes, P. (2013). When is the right time to refresh knowledge discovered from data?. Operations Research, 61(1), 32-44.
  More info

  Abstract: Knowledge discovery in databases (KDD) techniques have been extensively employed to extract knowledge from massive data stores to support decision making in a wide range of critical applications. Maintaining the currency of discovered knowledge over evolving data sources is a fundamental challenge faced by all KDD applications. This paper addresses the challenge from the perspective of deciding the right times to refresh knowledge. We define the knowledge-refreshing problem and model it as a Markov decision process. Based on the identified properties of the Markov decision process model, we establish that the optimal knowledge-refreshing policy is monotonically increasing in the system state within every appropriate partition of the state space. We further show that the problem of searching for the optimal knowledgerefreshing policy can be reduced to the problem of finding the optimal thresholds and propose a method for computing the optimal knowledge-refreshing policy. The effectiveness and the robustness of the computed optimal knowledge-refreshing policy are examined through extensive empirical studies addressing a real-world knowledge-refreshing problem. Our method can be applied to refresh knowledge for KDD applications that employ major data-mining models. © 2013 INFORMS.
• Goes, P. B. (2013). Editor's comments. MIS Quarterly: Management Information Systems, 37(1), iii-vii.
  More info

  Abstract: Paulo B. Goes, Editor-in-Chief (EIC) of MIS Quarterly, shares his views about his responsibilities and experience. He has expressed his gratitude to the members of the MISQ Policy Council who trusted him with the job and his colleagues in the field who have supported him. He offers his reflections on IS research in this editorial column, based on his 27 years of experience in the field, along with some thoughts about how he sees the future of the quarterly. Methodological approaches and reference research paradigms have broadened significantly from the time when IS research started. The dissertations of the 1970s have enabled IS research to follow an explanatory paradigm investigating the use and impact of IT and anchored in the disciplines of cognitive sciences, psychology, and organization sciences. He also states that diversified approaches and influences continue to play a key role in advancing IS research significantly.
• Goes, P. B. (2013). Editor's comments. MIS Quarterly: Management Information Systems, 37(3), iii-viii.
• Goes, P. B. (2013). Editor's comments: Commonalities across IS silos and Intradisciplinary information systems research. MIS Quarterly: Management Information Systems, 37(2), iii-viii.
• Goes, P., Yanbin, T. u., & Tung, Y. A. (2013). Seller heterogeneity in electronic marketplaces: A study of new and experienced sellers in eBay. Decision Support Systems, 56(1), 247-258.
  More info

  Abstract: Most online auction studies focus on the buyer side of the marketplace. To bridge the imbalance gap, we investigate seller behavior in this research. Specifically emphasized on seller heterogeneity, an area that has not been well studied in the electronic marketplace literature, this study classifies sellers into new and experienced seller groups and compares their auction performance based on three outcome measures: success rates, ending prices, and feedback ratings. We find that the performance of new sellers is worse than that of experienced sellers in all three measures, namely, lower auction success rates, lower auction ending prices, less likely to receive positive feedback ratings and more likely to receive negative feedback ratings. We also show the dynamics of these auction performances while new sellers evolve into experienced ones. Our empirical analysis reveals structural differences in auction success and price determinants between new and experienced sellers. That is, the determining factors for auction success and ending prices are significantly different between the two seller groups. We also identify several key factors for non-positive (i.e. neutral or negative) feedback ratings received by the two groups and find no significant difference between these factors for both new and experienced sellers. We believe our findings in this study have significant implications to the online auction house and sellers, and contribute towards building more effective and efficient electronic marketplaces. © 2013 Elsevier B.V.
• Zhang, Z., Guo, C., & Goes, P. (2013). Product comparison networks for competitive analysis of online word-of-mouth. ACM Transactions on Management Information Systems, 3(4).
  More info

  Abstract: Enabled by Web 2.0 technologies social media provide an unparalleled platform for consumers to share their product experiences and opinions-through word-of-mouth (WOM) or consumer reviews. It has become increasingly important to understand how WOM content and metrics thereof are related to consumer purchases and product sales. By integrating network analysis with text sentiment mining techniques, we propose product comparison networks as a novel construct, computed from consumer product reviews. To test the validity of these product ranking measures, we conduct an empirical study based on a digital camera dataset from Amazon.com. The results demonstrate significant linkage between network-based measures and product sales, which is not fully captured by existing review measures such as numerical ratings. The findings provide important insights into the business impact of social media and user-generated content, an emerging problem in business intelligence research. From a managerial perspective, our results suggest that WOM in social media also constitutes a competitive landscape for firms to understand and manipulate. © 2013 ACM.
• Goes, P. B., Karuga, G. G., & Tripathi, A. K. (2012). Bidding behavior evolution in sequential auctions: Characterization and analysis. MIS Quarterly: Management Information Systems, 36(4), 1021-1042.
  More info

  Abstract: Retailers are increasingly exploiting sequential online auctions as an effective and low cost distribution channel for disposing large quantities of inventory. In such auction environments, bidders have the opportunity of participating in many auctions to learn and choose the bidding strategy that best fits their preferences. Previous studies have mostly focused on identifying bidding strategies in single, isolated online auctions. Using a large data set collected from sequential online auctions, we first characterize bidding strategies in this interesting online environment and then develop an empirical model to explain bidders' adoption of different strategies. We also examine how bidders change their strategies over time. Our findings challenge the general belief that bidders employ their strategies regardless of experience or their specific demand. We find that bidders' demand, participation experience, and auction design parameters affect their choice of bidding strategies. Bidders with unit demand are likely to choose early bidding strategies, while those with multiple unit demand adopt late bidding strategies. Auction design parameters that affect bidders' perception of demand and supply trends affect bidders' choice of bidding strategies. As bidders gain experience within a sequence of auctions, they start choosing late bidding strategies. Our findings help auctioneers to design auction sequences that maximize their objectives.
• H., R., Goes, P., & Stohr, E. A. (2012). Business Intelligence and Analytics education, and program development: A unique opportunity for the Information Systems discipline. ACM Transactions on Management Information Systems, 3(3).
  More info

  Abstract: "Big Data," huge volumes of data in both structured and unstructured forms generated by the Internet, social media, and computerized transactions, is straining our technical capacity to manage it. More importantly, the new challenge is to develop the capability to understand and interpret the burgeoning volume of data to take advantage of the opportunities it provides in many human endeavors, ranging from science to business. Data Science, and in business schools, Business Intelligence and Analytics (BI&A) are emerging disciplines that seek to address the demands of this new era. Big Data and BI&A present unique challenges and opportunities not only for the research community, but also for Information Systems (IS) programs at business schools. In this essay, we provide a brief overview of BI&A, speculate on the role of BI&A education in business schools, present the challenges facing IS departments, and discuss the role of IS curricula and program development, in delivering BI&A education. We contend that a new vision for the IS discipline should address these challenges. © 2012 ACM.
• Bapna, R., Goes, P., Wei, K. K., & Zhang, Z. (2011). A finite mixture logit model to segment and predict electronic payments system adoption. Information Systems Research, 22(1), 118-133.
  More info

  Abstract: Despite much hype about electronic payments systems (EPSs), a 2004 survey establishes that close to 80% of between-business payments are still made using paper-based formats. We present a finite mixture logit model to predict likelihood of EPS adoption in business-to-business (B2B) settings. Our model simultaneously classifies firms into homogeneous segments based on firm-specific characteristics and estimates the model's coefficients relating predictor variables to EPS adoption decisions for each respective segment. While such models are increasingly making their presence felt in the marketing literature, we demonstrate their applicability to traditional information systems (IS) problems such as technology adoption. Using the finite mixture approach, we predict the likelihood of EPS adoption using a unique data set from a Fortune 100 company. We compare the finite mixture model with a variety of traditional approaches. We find that the finite mixture model fits the data better, controlling for the number of parameters estimated; that our explicit model-based segmentation leads to a better delineation of segments; and that it significantly improves the predictive accuracy in holdout samples. Practically, the proposed methodology can help business managers develop actionable segment-specific strategies for increasing EPS adoption by their business partners. We discuss how the methodology is potentially applicable to a wide variety of IS research.
• Goes, P., Ilk, N., Yue, W. T., & Zhao, J. L. (2011). Live-chat agent assignments to heterogeneous E-customers under imperfect classification. ACM Transactions on Management Information Systems, 2(4).
  More info

  Abstract: Many e-commerce firms provide live-chat capability on their Web sites to promote product sales and to offer customer support.With increasing traffic on e-commerceWeb sites, providing such live-chat services requires a good allocation of service resources to serve the customers.When resources are limited, firms may consider employing priority-processing and reserving resources for high-value customers. In this article, we model a reserve-based priority-processing policy for e-commerce systems that have imperfect customer classification. Two policy decisions considered in the model are: (1) the number of agents exclusively reserved for highvalue customers, and (2) the configuration of the classification system. We derive explicit expressions for average waiting times of high-value and low-value customer classes and define a total waiting cost function. Through numerical analysis, we study the impact of these two policy decisions on average waiting times and total waiting costs. Our analysis finds that reserving agents for high-value customers may have negative consequences for such customers under imperfect classification. Further, we study the interaction between the two policy decisions and discuss how one decision should be modified with respect to a change in the other one in order to keep the waiting costs minimized. © 2011 ACM.
• Ilk, N., Zhao, J. L., Goes, P., & Hofmann, P. (2011). Semantic enrichment process: An approach to software component reuse in modernizing enterprise systems. Information Systems Frontiers, 13(3), 359-370.
  More info

  Abstract: In today's dynamic business environments, organizations are under pressure to modernize their existing software systems in order to respond to changing business demands. Service oriented architectures provide a composition framework to create new business functionalities from autonomous building blocks called services, enabling organizations to quickly adapt to changing conditions and requirements. Characteristics of services offer the promise of leveraging the value of enterprise systems through source code reuse. In this respect, existing system components can be used as the foundation of newly created services. However, one problem to overcome is the lack of business semantics to support the reuse of existing source code. Without sufficient semantic knowledge about the code in the context of business functionality, it would be impossible to utilize source code components in services development. In this paper, we present an automated approach to enrich source code components with business semantics. Our approach is based on the idea that the gap between the two ends of an enterprise system-(1) services as processes and (2) source code-can be bridged via similarity of data definitions used in both ends. We evaluate our approach in the framework of a commercial enterprise systems application. Initial results indicate that the proposed approach is useful for annotating source code components with business specific knowledge. © 2010 Springer Science+Business Media, LLC.
• Chen, L., Goes, P., Harris, W., Marsden, J., & Zhang, J. (2010). Preference markets for innovation ranking and selection. Interfaces, 40(2), 144-153.
  More info

  Abstract: Companies face constant challenges to appropriately rank and select innovative technologies for potential strategic investments, and they have used many methodologies to help them with this task; however, these existing processes have several limitations. This paper showcases how information preference markets can be structured and implemented to rank and select these technologies. We demonstrate the market process for a leading company in the Fortune 100 companies list. The results are encouraging and have persuaded the company to make a significant financial commitment to expand its use of preference markets. The work we present here offers readers a step-by-step illustration of how to develop and use preference markets in industry settings. © 2010 INFORMS.
• Goes, P. B., Karuga, G. G., & Tripathi, A. K. (2010). Understanding willingness-to-pay formation of repeat bidders in sequential online auctions. Information Systems Research, 21(4), 907-924.
  More info

  Abstract: Agrowing number of vendors are using a sequence of online auctions to sell large inventories of identical items. Although bidding strategies and bidder behavior in single auctions have been extensively studied, limited research exists on bidding in sequential auctions. We seek to explain how bidders in such an environment learn from the information, and form and update their willingness to pay (WTP). Using a large data set from an online auction retailer, we analyze the evolution of the bidders' WTP as well as the effect of auction design on bidders' WTP in sequential auctions. We see our study in the context of a longitudinal field experiment, in which we were able to track actions of repeat bidders over an extended period of time. Our results show that bidders' WTP in sequential auctions can be explained from their demand characteristics, their participation experience in previous auctions, outcomes in previous auctions, and auction design parameters. We also observe, characterize, and measure what we call a modified demand reduction effect exhibited across different auctions, over time, by multiunit demand bidders. Our findings are important to enable better auction mechanism design, and more sophisticated bidding tools that explore the rich information environment of sequential auctions. © 2010 INFORMS.
• Ilk, N., Goes, P., & Zhao, J. (2010). A framework to support service-oriented architecture investment decision. ICIS 2010 Proceedings - Thirty First International Conference on Information Systems.
  More info

  Abstract: Service-oriented architecture (SOA) is a system paradigm that structures business functions as loosely coupled services to enable business agility. SOA requires significant up-front investments, and in return, promises a vast array of benefits. Unfortunately, in contrast to the costs of the investment, monetary benefits associated with SOA are more difficult to measure. For one reason, benefits such as increased agility or improved flexibility are elusive in nature, making it harder to define metrics for their calculation. For another, SOA value is realized in long term under uncertainty, and traditional capital budgeting methods often fail to capture uncertainty when valuing investments. In this paper, we provide a decision framework to analyze the monetary impact of SOA investment in an organization. Combining traditional NPV analysis with option pricing models, our framework accounts for operational and strategic costs and benefits of SOA and proposes an extended investment value to support managerial investment decision.
• Ayanso, A., Goes, P. B., & Mehta, K. (2009). A cost-based range estimation for mapping top-k selection queries over relational databases. Journal of Database Management, 20(4), 1-25.
  More info

  Abstract: Finding efficient methods for supporting top-k relational queries has received significant attention in academic research. One of the approaches in the recent literature is query-mapping, in which top-k queries are mapped (translated) into equivalent range queries that relational database systems (RDBMSs) normally support. This approach combines the advantage of simplicity as well as practicality by avoiding the need for modifications to the query engine, or specialized data structures or indexing techniques to handle top-k queries separately. However, existing methods following this approach fall short of adequately modeling the problem environment and providing consistent results. In this article, the authors propose a cost-based range estimation model for the query-mapping approach. They provide a methodology for trading-off relevant query execution cost components and mapping a top-k query into a cost-optimal range query for efficient execution. Their experiments on real world and synthetic data sets show that the proposed strategy not only avoids the need to calibrate workloads on specific database contents, but also performs at least as well as prior methods. Copyright © 2009, IGI Global.
• Bapna, R., Chang, S. A., Goes, P., & Gupta, D. A. (2009). Overlapping online auctions: Empirical characterization of bidder strategies and auction prices. MIS Quarterly: Management Information Systems, 33(4), 763-783.
  More info

  Abstract: Online auctions enable market-level interactions or interdependency of outcomes, which were not observed in physical auctions. One such set of interactions takes place when multiple auctions are conducted to sell identical items by an identical seller in an overlapping manner. This research focuses on overlapping auctions, their interactions, and the related impact on bidder behavior. We introduce the notion of auction "overlap" and examine the impact of market-level factors such as the price information revealed from prior auctions, degree of overlap, the auction format, and the overall market supply on a given auction's price. Despite a competitive setting, we find that, ceteris paribus, English auctions, on average, extract roughly 8.6 percent more revenue per unit than multiunit uniform-price Dutch auctions. We discover that the overlapping auctions attract institutional bidders, who bid in a participatory manner across multiple auctions, and that such bidders exert a downward pressure on auction prices. We find that overlap of an auction with other competing auctions has a significant negative influence on prices, and information about following auctions has a stronger negative influence than information about prior closing auctions. By estimating the expected price difference, we provide practitioners, who have private knowledge of their internal holding costs, a benchmark that can be used in deciding between using overlapping single-unit English auctions and multiunit Dutch auctions.
• Bapna, R., Goes, P., & Gupta, A. (2009). Auctioning vertically integrated online services: Computational approaches for real-time allocation. Journal of Management Information Systems, 25(3), 65-97.
  More info

  Abstract: We develop three auction-based pricing and allocation solution methods for the case where a capacity-constrained online service provider offers multiple classes of unique, one-time services with differentiated quality. Consumers desire exactly one of the many service classes offered. We call such a setting a vertically integrated online services market. Examples of these services are webcasting of special events over the Internet, provision of video-on-demand, and allocation of grid computing resources. We model the pricing and allocation decision faced by firms in such a setting as a knapsack problem with an added preference elicitation dimension. We present a variety of computational solution approaches based on adaptations of the traditional greedy heuristic for knapsack problems. The solution approaches vary in efficacy depending on whether bidders are restricted to bid in one service class or allowed to bid in multiple service classes, as well as on the overall variability of the demand. In the case bidders can bid in multiple classes but are interested in consuming only one service class, a direct application of the heuristics developed for the single service case results in a nonfair allocation. We develop a novel data structure to eliminate the unfair allocation while maintaining the original computation complexity of the simpler setting. The paper contributes by presenting a menu of auction clearing mechanisms for selling vertically integrated online services. © 2009 M.E. Sharpe, Inc.
• Chen, L., Goes, P., Marsden, J., & Zhang, Z. (2009). Design and use of preference markets for evaluation of early stage technologies. Journal of Management Information Systems, 26(3), 45-70.
  More info

  Abstract: In the work presented here, we develop and apply preference markets in evaluating early stage technology. Partnering with a Fortune 5 company, we developed and implemented two internal preference markets (field experiments). In both cases, nonmonetary (play money) incentives were utilized, but one market provided additional nonmonetary (play money) incentives. Working with the partner company, our investigation started with seven emerging technologies and expanded to a total of 17 emerging technologies. Our results suggest that even a simple form of additional nonmonetary play money incentive yielded greater price convergence, increased spread across final market prices, and greater consistency with a costly expert panel that was set up by the partner company. Based on the outcomes of our analyses, the partner company is investing in developing extended applications of preference markets as a potentially scalable approach for dealing with its ongoing and expanding strategic identification of promising emerging technologies. © 2010 M.E. Sharpe, Inc.
• Goes, P., Yanbin, T. u., & Tung, Y. A. (2009). Technical opinion: Online auctions hidden metrics. Communications of the ACM, 52(4), 147-149.
  More info

  Abstract: Three auction metrics, namely, auction listing errors, seller frustration, and auction fraud, which do not typically appear on the radar screen of most auction research has been reported. The auction literature provides supporting evidence for better performance by experienced sellers in terms of their positive feedback ratings. Listing errors refer to seller mistakes in setting parameters for an auction and can potentially lead to major frustration of sellers and/or buyers. Online auction fraud poses great concerns to market participants simply because most online transactions are based on trust. Tutorials and online recommendation systems should be in place to minimize listing errors and help sellers make the right selection of auction parameters that can enhance the probability of achieving successful transactions. A more careful investigation of these metrics can lead to a win-win-win situation for the auction house, sellers, as well as buyers.
• Pereira, A., Duarte, D., Meira Jr., W., & Góes, P. (2009). Assessing success factors of selling practices in electronic marketplaces. Proceedings of the International Conference on Management of Emergent Digital EcoSystems, MEDES '09, 261-268.
  More info

  Abstract: Electronic markets have early emerged as an important topic inside e-commerce research. An e-market is a digital ecosystem intended to provide their users with online services that will facilitate information exchange and transactions. This work presents a characterization and analysis of fixed-price online negotiations. Using actual data from a Brazilian marketplace, we analyze selling practices, considering seller profiles and selling strategies. There are important factors that can be considered when analyzing selling practices, such as the seller's reputation and experience, offer's price, duration, among others. We evaluate which factors impact on the success of selling practices in e-markets, which can be used to support seller's decision and recommend selling practices. Moreover, we investigate some important hypotheses about selling practices in online marketplaces, which allow us to state interesting conclusions, such as: a seller profile can achieve success or not in a trade, depending on the adopted strategy; the offer's price and how it is being advertised are two important success factors. Copyright 2009 ACM.
• Pereira, A., Duarte, D., Meira Jr., W., & Góes, P. (2009). Selling practices in online fixed-price marketplaces. Proceedings - 2009 9th Annual International Symposium on Applications and the Internet, SAINT 2009, 71-77.
  More info

  Abstract: In the last decade, there has been an explosion of online commercial activity enabled by the World Wide Web (WWW). In Brazil, probably by cultural influence, online auctions are not so popular, since users prefer fixed-price for online negotiation. This work presents a characterization and analysis of fixed-price online negotiations. Using actual data from a Brazilian marketplace, we analyze selling practices, considering seller profiles and selling strategies. We study and confirm several important hypotheses about selling practices in online marketplaces, which allow us to state interestingconclusions, such as: the product category impacts the seller profile and the selling strategies; and the best selling practices vary for different products. © 2009 IEEE.
• Pereira, A., Duarte, D., Meira Jr., W., Almeida, V., & Góes, P. (2009). Analyzing seller practices in a Brazilian marketplace. WWW'09 - Proceedings of the 18th International World Wide Web Conference, 1031-1040.
  More info

  Abstract: E-commerce is growing at an exponential rate. In the last decade, there has been an explosion of online commercial activity enabled by World Wide Web (WWW). These days, many consumers are less attracted to online auctions, preferring to buy merchandise quickly using fixed-price negotiations. Sales at Amazon.com, the leader in online sales of fixed-price goods, rose 37% in the first quarter of 2008. At eBay, where auctions make up 58% of the site's sales, revenue rose 14%. In Brazil, probably by cultural influence, online auctions are not been popular. This work presents a characterization and analysis of fixed-price online negotiations. Using actual data from a Brazilian marketplace, we analyze seller practices, considering seller profiles and strategies. We show that different sellers adopt strategies according to their interests, abilities and experience. Moreover, we confirm that choosing a selling strategy is not simple, since it is important to consider the seller's characteristics to evaluate the applicability of a strategy. The work also provides a comparative analysis of some selling practices in Brazil with popular worldwide marketplaces.Copyright is held by the International World Wide Web Conference Committee (IW3C2).
• Pereira, A., Rocha, L., Mourão, F., Góes, P., & Meira Jr., W. (2009). Reactivity based model to study online auctions dynamics. Information Technology and Management, 10(1), 21-37.
  More info

  Abstract: Online auctions have challenged many assumptions and results from the traditional economic auction theory. Observed bidder behavior in online auctions often deviates from equilibrium strategies postulated by economic theory. In this research, we consider an online auction as an information system that provides a long-duration, information-rich, dynamic application environment in which users (bidders) interact with the system in a feedback loop, in what we term reactivity. Bidders react to the observed conditions of the auction and events triggered by actions of other bidders. In this work we propose a new characterization model with the purpose of isolating the segments of the auction in which users react to the auction conditions and events. Through this model, it is possible to enrich the auction characterization. Despite the existence of other bidding characterization models, none of them is enough for understanding the factors that characterize and explain the auction dynamics. We present results which demonstrate the advantages of applying our methodology. The final objective is to gain an understanding of what drives the dynamics of online auctions, the role of reactivity in the auction dynamics, and how the outcome of the auction is affected by the particular dynamics of the system. © Springer Science+Business Media, LLC 2008.
• Bapna, R., Goes, P., Gupta, A., & Karuga, G. (2008). Predicting bidders' willingness to pay in online multiunit ascending auctions: Analytical and empirical insights. INFORMS Journal on Computing, 20(3), 345-355.
  More info

  Abstract: we develop a real-time estimation approach to predict bidders' maximum willingness to pay in a multiunit ascending uniform-price and discriminatory-price (Yankee) online auction. Our two-stage approach begins with a bidder classification step, which is followed by an analytical prediction model. The classification model identifies bidders as either adopting a myopic best-response (MBR) bidding strategy or a non-MBR strategy. We then use a generalized bid-inversion function to estimate the willingness to pay for MBR bidders. We empirically validate our two-stage approach using data from two popular online auction sites. Our joint classification-and- prediction approach outperforms two other naive prediction strategies that draw random valuations between a bidder's current bid and the known market upper bound. Our prediction results indicate that, on average, our estimates are within 2% of bidders' revealed willingness to pay for Yankee and uniform-price multiunit auctions. We discuss how our results can facilitate mechanism-design changes such as dynamic-bid increments and dynamic buy-it-now prices. © 2008 INFORMS.
• Pereira, A., Rocha, L., Mourão, F., Meira Jr., W., & Góes, P. (2008). Reactivity in online auctions: Understanding bidding behavior through reactive transitions. Proceedings - 10th IEEE Joint Conference on E-Commerce Technology and the 5th Enterprise Computing, E-Commerce and E-Services, CEC 2008 and EEE 2008, 279-284.
  More info

  Abstract: Internet systems are a typical scenario where sequences of interactions arise. Modeling the factors that drive the dynamics of an online auction, for example, is complex, since successive interactions become a loop-feedback mechanism, that we call reactivity, that is, the user behavior affects the auction negotiation and vice-versa. In this paper we briefly describes our methodology for characterizing online auctions, considering reactivity. We present the reactive transitions, that is the approach we adopt to model reactivity in online auctions. The reactive transition models the reactivity function, providing a way to discover the bidding behavior's patterns. We also validate our model using actual bidding data from eBay. The results show rich details to understand bidding behavior, that can be used to design support-decision agents and simulate e-markets. © 2008 IEEE.
• Rocha, L., Pereira, A., Mourão, F., Silva, A., Meira Jr., W., & Goes, P. (2008). Evaluating longitudinal aspects of online bidding behavior. WEBIST 2008 - 4th International Conference on Web Information Systems and Technologies, Proceedings, 2, 423-430.
  More info

  Abstract: Online auctions have become a major e-commerce strategy in terms of both number, diversity of participants and revenue. Recent research has characterized online auctions as synchronous interactive computer systems, considering successive interactions as a "loop feedback" mechanism, called reactivity, where the user behavior affects the system behavior and vice-versa. Although some factors that explain user behavior in terms of instantaneous bidding conditions are identified by previous research, there has been no effort to study how bidders' behavior changes over time. This work presents a longitudinal analysis of bidding behavior over a series of auctions. The results show bidding behavior evolves over time and these changes are not random. The identifiable evolution patterns can be partially explained by the presence of instantaneous reactivity patterns that bidders experience throughout the series of auctions they participate. Bidders learn from these reactivity instances and adapt their future participation.
• Silva, A., Calais, P., Pereira, A., Mourão, F., Almeida, J., Meira Jr., W., & Góes, P. (2008). A seller's perspective characterization methodology for online auctions. ACM International Conference Proceeding Series.
  More info

  Abstract: Online auction services have reached great popularity and revenue over the last years. A key component for this success is the seller. Few studies proposed analyzing how the seller and the auction configuration affect the negotiation results. In this work we propose a methodology to characterize online auctions by the seller's perspective. This methodology is based on: (1) recognizing the characteristics of the variables related to the auction results and (2) capturing the correlation among these variables to identify seller profiles and selling strategies. We applied our methodology to a real case study, using an eBay dataset, to validate two hypotheses about sellers and their practices. These results are useful to understand the complex mechanisms that guide ending prices, success (or failure), and the attraction of bids in online auctions, which can support decision strategies for buyers and sellers. Copyright 2008 ACM.
• Ayanso, A., Goes, P. B., & Mehta, K. (2007). A practical approach for efficiently answering top-k relational queries. Decision Support Systems, 44(1), 326-349.
  More info

  Abstract: An increasing number of application areas now rely on obtaining the "best matches" to a given query as opposed to exact matches sought by traditional transactions. This type of exploratory querying (also called top-k querying) can significantly improve the performance of web-based applications such as consumer reviews, price comparisons and recommendations for products/services. Due to the lack of support for specialized indexes and/or data structures in relational database management systems (RDBMSs), recent research has focused on utilizing summary statistics (histograms) maintained by RDBMSs for translating the top-k request into a traditional range query. Because the RDBMS query engines are already optimized for execution of range queries, such approach has both practical as well as efficiency advantages. In this paper, we review the strengths and weaknesses of common histogram construction techniques with regard to their structural characteristics, accuracy in approximating the true distribution of the underlying data, and implications for top-k retrieval. We also present our top-k retrieval strategy (Query-Level Optimal Cost Strategy - QLOCS) and demonstrate its "histogram-independent" performance. Based on comparative experimental and statistical analyses with the best-known histogram-based strategy in the literature, we show that QLOCS is not only more efficient but also provides more consistent performance across commonly used histogram types in RDBMSs. © 2007 Elsevier B.V. All rights reserved.
• Chiang, I. R., Goes, P. B., & Zhang, Z. (2007). Periodic cache replacement policy for dynamic content at application server. Decision Support Systems, 43(2), 336-348.
  More info

  Abstract: Web caching has been widely adopted to improve server responsiveness without resorting to costly infrastructure overhauls. However, due to the need to support real-time transactions and content customization, an increasing proportion of web pages contain fragments that are dynamically generated, typically results of database queries, rendering whole-page caching at browser or proxy level inappropriate. A promising approach has been to place dynamic fragments in a web application server cache for multiple web requests. In this paper, we propose a periodic cache replacement policy for dynamic web content at application server. Since the content of a dynamically generated web fragment could become stale, the value of a cached copy of the fragment will likely decrease as updates accumulate at the back-end database. Constantly replacing the cached copy of the fragment will increase its freshness and value, yet will also incur a high cache replacement cost. In addition, not all fragments are equally important to various applications and it is preferable to cache mission-critical fragments. The decision problem then consists of what fragments should be selected to cache and how frequently the cache should be replaced so that the total cache benefits per unit time is maximized. Numerical and simulation experiments show that the periodic cache replacement policy is robust and effective in handling dynamic content. © 2006 Elsevier B.V. All rights reserved.
• Pereira, A., Rocha, L., Mourao, F., Meira Jr., W., & Goes, P. (2007). Characterization of online auctions: Correlating negotiation patterns and bidding behavior. Proceedings - 2007 Latin American Web Conference, LA-WEB 2007, 100-109.
  More info

  Abstract: Online auctions have become a major electronic commerce channel in terms of revenue, reaching an enormous and very diverse population of participants all over the world. Modeling the factors that drive the dynamics of an auction, that is, the interactions that happen during its negotiation, is crucial to improve the customer experience for both sellers and buyers. Auction dynamics can be seen as complex and non-isolated interactions, where successive interactions become a 1oop-feedback mechanism. In what we call reactivity, the user behavior affects the auction negotiation and vice-versa. In this work, we develop a characterization approach for online auctions to capture the reactivity concept. Using the characterization, we are able to model both auction negotiation patterns and bidding behavior and correlate them. Our approach is novel, and the results start to shed light into measuring reactivity in online auctions. Our aim is to explain how the auction negotiation affects the bidders' behavior and vice-versa, and to relate the correlation auction pattern - bidding behavior to outcome measures. © 2007 IEEE.
• Pereira, A., Rocha, L., Mourão, F., Torres, T., Meira Jr., W., & Goes, P. (2007). Analyzing ebay negotiation patterns. Webist 2007 - 3rd International Conference on Web Information Systems and Technologies, Proceedings, SEBEG(EL/-), 84-91.
  More info

  Abstract: Online auctions have several aspects that violate the common assumptions made by the traditional economic auction theory. An online auction can be seen as an interactive economic information system, where user- system interactions are usually very complex. It is important to note that the interactions are not isolated, but successive interactions become a loop-feedback mechanism, that we call reactivity, where the user behavior affects the auction negotiation and vice-versa. In this paper we describe a new hierarchical characterization model for online auctions and apply this model to a real case study, showing its advantages in discovering some online auction negotiation patterns. The results demonstrate that our characterization model provides an efficient way to open the auction dynamics's "black box". We also propose an abstraction named Auction Model Graph (AMG) which enables the temporal analysis of the negotiation. This work is part of a research to analyze reactivity in e-business, that may contribute to understand the business dynamics and has wide applicability to activities such as designing recommendation agents, service personalization, and site interaction enhancement.
• Bapna, R., Goes, P., Gopal, R., & Marsden, J. R. (2006). Moving from data-constrained to data-enabled research: Experiences and challenges in collecting, validating and analyzing large-scale e-commerce data. Statistical Science, 21(2), 116-130.
  More info

  Abstract: Widespread e-commerce activity on the Internet has led to new opportunities to collect vast amounts of micro-level market and nonmarket data. In this paper we share our experiences in collecting, validating, storing and analyzing large Internet-based data sets in the area of online auctions, music file sharing and online retailer pricing. We demonstrate how such data can advance knowledge by facilitating sharper and more extensive tests of existing theories and by offering observational underpinnings for the development of new theories. Just as experimental economics pushed the frontiers of economic thought by enabling the testing of numerous theories of economic behavior in the environment of a controlled laboratory, we believe that observing, often over extended periods of time, real-world agents participating in market and nonmarket activity on the Internet can lead us to develop and test a variety of new theories. Internet data gathering is not controlled experimentation. We cannot randomly assign participants to treatments or determine event orderings. Internet data gathering does offer potentially large data sets with repeated observation of individual choices and action. In addition, the automated data collection holds promise for greatly reduced cost per observation. Our methods rely on technological advances in automated data collection agents. Significant challenges remain in developing appropriate sampling techniques integrating data from heterogeneous sources in a variety of formats, constructing generalizable processes and understanding legal constraints. Despite these challenges, the early evidence from those who have harvested and analyzed large amounts of e-commerce data points toward a significant leap in our ability to understand the functioning of electronic commerce. © Institute of Mathematical Statistics, 2006.
• Chen, A. N., Goes, P. B., Gupta, A., & Marsden, J. R. (2006). Heuristics for selecting robust database structures with dynamic query patterns. European Journal of Operational Research, 168(1), 200-220.
  More info

  Abstract: The success of a company increasingly depends on timely information (internal or external) being available to the right person at the right time for crucial managerial decision-making. Achieving such a "right time/right place" duet depends directly on database performance. A database system has been a core component that supports modern business system such as enterprise resource planning (ERP) system that integrates and supports all enterprise processes including product designing and engineering, manufacturing, and other business functions to achieve highest efficiency and effectiveness of operations. We develop and demonstrate through a proof-of-concept case study, a new "query-driven" heuristics for database design that seeks to identify database structures that perform robustly in dynamic settings with dynamic queries. Our focus is the design of efficient structures to process read-only queries in complex environments. Our heuristics begins with detailed analysis of relationships between diverse queries and the performance of different database structures. These relationships are then used in a series of steps that identify "robust" database structures that maintain high performance levels for a wide range of query patterns. We conjecture that our heuristics can facilitate efficient operations and effective decision-making of companies in today's dynamic environment. © 2004 Elsevier B.V. All rights reserved.
• Pereira, A., Mourão, F., Góes, P., & Meira Jr., W. (2006). Reactivity in online auctions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4254 LNCS, 909-918.
  More info

  Abstract: Interactive computer systems, that is, systems in which users cyclically interact by getting and providing information, have already a widespread and increasing use in all areas of our society. One characteristic of such systems is that the user behavior affects the system behavior and vice-versa. There is strong evidence that much of the user behavior is reactive, that is, the user reacts to the instantaneous conditions at the action time. This paper presents the reactivity concept and describes a framework to model it in interactive systems, in particular Internet-based systems. We analyze an online auction within the framework. Based on eBay data, we identify attributes that affect the winner bidders' behavior, such as the auction time to finish. This paper presents the first findings towards the formal description and understanding of reactivity patterns in an e-commerce application, which will be useful in improving the application and building novel mechanisms. © Springer-Verlag Berlin Heidelberg 2006.
• Bapna, R., Goes, P., & Gupta, A. (2005). Pricing and allocation for quality-differentiated online services. Management Science, 51(7), 1141-1150.
  More info

  Abstract: We explore the problem of pricing and allocation of unique, one-time digital products in the form of data streams. We look at the short-term problem where the firm has a capacitated shared resource and multiple products or service levels. We formulate the allocatively efficient Generalized Vickrey Auction (GVA) for our setting and point out the computational challenges in determining the individual discriminatory transfer payments. We propose an alternative uniform-price, computationally efficient, revenue-maximizing knapsack formulation called the Multiple Vickrey Auction (MVA). While not incentive compatible, the MVA mechanism achieves bounded posterior regret and can be solved in real time. It has the added benefit of realizing imputed commodity prices for the various services, a feature lacking in the discriminatory GVA approach. For service providers that are concerned about the incentive compatibility but want imputed service prices, we suggest a maximal MVA (mMVA) uniform-pricing scheme that trades off revenue maximization for allocative efficiency. For sake of completeness we discuss the properties of a first-price pay-your-bid scheme. While NP-hard and not incentive compatible, this formulation has the perceived benefit of cognitive simplicity on the parts of sellers and bidders. © 2005 INFORMS.
• Albert, T. C., Goes, P. B., & Gupta, A. (2004). Gist: A model for design and management of content and interactivity of customer-centric web sites. MIS Quarterly: Management Information Systems, 28(2), 161-182.
  More info

  Abstract: Customer-centric Web-based systems, such as e-commerce Web sites, or sites that support customer relationship management (CRM) activities, are themselves information systems, but their design and maintenance need to follow vastly different approaches from the traditional systems lifecycle approach. Based on marketing frameworks that are applicable to the online world, and following design science principles, we develop a model to guide the design and the continuous management of such sites. The model makes extensive use of current technologies for tracking the customers and their behaviors, and combines elements of data mining and statistical analyses. A case study based on a financial services Web site is used to provide a preliminary validation and design evaluation of our approach. The case study showed considerable measured improvement in the effectiveness of the company's Web site. In addition, it also highlighted an important benefit of the our approach: the identification of previously unknown or unexpected segments of visitors. This finding can lead to promising new business opportunities.
• Bapna, R., Goes, P., Gupta, A., & Jin, Y. (2004). User heterogeneity and its impact on electronic auction market design: An empirical exploration. MIS Quarterly: Management Information Systems, 28(1), 21-43.
  More info

  Abstract: While traditional information systems research emphasizes understanding of end users from perspectives such as cognitive fit and technology acceptance, it fails to consider the economic dimensions of their interactions with a system. When viewed as economic agents who participate in electronic markets, it is easy to see that users' preferences, behaviors, personalities, and ultimately their economic welfare are intricately linked to the design of information systems. We use a data-driven, inductive approach to develop a taxonomy of bidding behavior in online auctions. Our analysis indicates significant heterogeneity exists in the user base of these representative electronic markets. Using online auction data from 1999 and 2000, we find a stable taxonomy of bidder behavior containing five types of bidding strategies. Bidders pursue different bidding strategies that, in aggregate, realize different winning likelihoods and consumer surplus. We find that technological evolution has an impact on bidders' strategies. We demonstrate how the taxonomy of bidder behavior can be used to enhance the design of some types of information systems. These enhancements include developing user-centric bidding agents, inferring bidders' under-lying valuations to facilitate real-time auction calibration, and creating low-risk computational platforms for decision making.
• Chen, A. N., Goes, P. B., Gupta, A., & Marsden, J. R. (2004). Database design in the modern organization - Identifying robust structures under changing query patterns and arrival rate conditions. Decision Support Systems, 37(3), 435-447.
  More info

  Abstract: We summarize the problem tackled here in the following way: Given a modern database application environment, how can we identify and select the database structure that provides robust performance across changing query patterns and arrival rate conditions? We demonstrate the importance of investigating the underlying relationships and then utilize this information in formulating robust structures. Our work is pre-theory in the philosophy of science sense. That is, the careful identification and observation of relationships will subsequently be utilized in formulating a testable theory of the development of robust database structures under dynamic query patterns and arrival rates. Our first step in providing a database design or "structure selection" method is to determine potential good performers among different database structures. These potential good performers are selected and analyzed across arrays of query patterns. The next step is to identify database structures that are robust structures, that is good performers across the different types of query patterns and arrival rate levels. The presentation includes illustrations of the determination of actual query pattern processing times and the use of these times within a queuing analysis. In fact, for the database layout analyzed, application of our methods demonstrates the existence of such robust database structures. © 2003 Elsevier B.V. All rights reserved.
• Bapna, R., Goes, P., & Gupta, A. (2003). Analysis and design of business-to-consumer online auctions. Management Science, 49(1), 85-101.
  More info

  Abstract: Business-to-consumer online auctions form an important element in the portfolio of mercantile processes that facilitates electronic commerce activity. Much of traditional auction theory has focused on analyzing single-item auctions in isolation from the market context in which they take place. We demonstrate the weakness of such approaches in online settings where a majority of auctions are multiunit in nature. Rather than pursuing a classical approach and assuming knowledge of the distribution of consumers' valuations, we emphasize the largely ignored discrete and sequential nature of such auctions. We derive a general expression that characterizes the multiple equilibria that can arise in such auctions and segregate these into desirable and undesirable categories. Our analytical and empirical results, obtained by tracking real-world online auctions, indicate that bid increment is an important factor amongst the control factors that online auctioneers can manipulate and control. We show that consumer bidding strategies in such auctions are not uniform and that the level of bid increment chosen influences them. With a motive of providing concrete strategic directions to online auctioneers, we derive an absolute upper bound for the bid increment. Based on the theoretical upper bound we propose a heuristic decision rule for setting the bid increment. Empirical evidence lends support to the hypothesis that setting a bid increment higher than that suggested by the heuristic decision rule has a negative impact on the auctioneer's revenue.
• Bapna, R., Goes, P., & Gupta, A. (2003). Replicating Online Yankee Auctions to Analyze Auctioneers' and Bidders' Strategies. Information Systems Research, 14(3), 244-268+315.
  More info

  Abstract: The significance of simulation approach for examining the decision space for both bid takers and bid makers in web-based dynamic price setting processes was discussed. The simulation process was demonstrated by Yankee auctions. Hybrid-bidding strategies derived as a combination of three broad strategies, such as jump bidding and strategic-at-margin (SAM) bidding were also investigated.
• Chen, A. N., Goes, P. B., & Marsden, J. R. (2002). A query-driven approach to the design and management of flexible database systems. Journal of Management Information Systems, 19(3), 121-154.
  More info

  Abstract: The need for timely information in the e-business world provides the impetus to develop a flexible database system with the capability to adapt and maintain performance levels under changing queries and changing business environments. Recognizing the importance of providing fast access to a variety of read-only applications in today's e-business world, we introduce the systems architecture for developing and implementing a flexible database system to achieve considerable gains in processing times of read queries. The key component of a flexible database system is query mining, the concept of determining relationships among query properties, alternative database structures, and query processing times. We validate the flexible database system concept through extensive laboratory experiments, where we embed learning tools to demonstrate the implementation of query mining.
• Garfinkel, R., Gopal, R., & Goes, P. (2002). Privacy protection of binary confidential data against deterministic, stochastic, and insider threat. Management Science, 48(6), 749-764.
  More info

  Abstract: A practical model and an associated method are developed for providing consistent, deterministically correct responses to ad-hoc queries to a database containing a field of binary confidential data. COUNT queries, i.e., the number of selected subjects whose confidential datum is positive, are to be answered. Exact answers may allow users to determine an individual's confidential information. Instead, the proposed technique gives responses in the form of a number plus a guarantee so that the user can determine an interval that is sure to contain the exact answer. At the same time, the method is also able to provide both deterministic and stochastic protection of the confidential data to the subjects of the database. Insider threat is defined precisely and a simple option for defense against it is given. Computational results on a simulated database are very encouraging in that most queries are answered with tight intervals, and that the quality of the responses improves with the number of subjects identified by the query. Thus the results are very appropriate for the very large databases prevalent in business and governmental organizations. The technique is very efficient in terms of both time and storage requirements, and is readily scalable and implementable.
• Gopal, R., Garfinkel, R., & Goes, P. (2002). Confidentiality via camouflage: The CVC approach to disclosure limitation when answering queries to databases. Operations Research, 50(3), 501-516.
  More info

  Abstract: A practical method is presented for giving unlimited, deterministically correct, numerical responses to ad-hoc queries to an online database, while not compromising confidential numerical data. The method is appropriate for any size database, and no assumption are needed about the statistical distribution of the confidential data. Responses are in the form of a number plus a guarantee, so the user can determine an interval that is sure to contain the exact answer. Virtually any imaginable query type can be answered, and in the absence of insider information, collusion among the users presents no problem. Experimental analysis supports the practical viability of the proposed method.
• Bapna, R., Goes, P., & Gupta, A. (2001). Comparative analysis of multi-item online auctions: Evidence from the laboratory. Decision Support Systems, 32(2), 135-153.
  More info

  Abstract: The dynamics of customer relationship are being reshaped by price-setting processes such as online auctions. This paper analyzes price setting process in business-to-consumer (B2C) online auctions. Typically, these auctions involve multiple identical units and utilize a variant of the traditional English-auction mechanism. We describe an online laboratory experiment that compares the efficiency of such a mechanism with a multi-item version of Vickrey's [Journal of Finance 41 (1961) 8.] second-price auction with respect to both seller's revenue and allocative efficiency. Our results reject the revenue equivalence principle and indicate that English auctions may dominate the Vickrey auctions. However, we observe that the allocative efficiency of Vickrey auctions is higher than the English auctions. © 2001 Elsevier Science B.V. All rights reserved.
• Bapna, R., Goes, P., & Gupta, A. (2001). Insights and analyses of online auctions. Communications of the ACM, 44(11), 42-50.
  More info

  Abstract: Exploring the structure and mechanisms for online mercantile processes and bidding strategies.
• Bapna, R., Goes, P., & Gupta, A. (2001). Simulating online Yankee auctions to optimize sellers revenue. Proceedings of the Hawaii International Conference on System Sciences, 177-.
  More info

  Abstract: The online Yankee auction sells multiple units of the same good to multiple buyers using an ascending and open auction mechanism. One of the important controllable factors of the Yankee auction is the minimum bid increment, specified at the beginning of an auction. Bidders can bid only in the multiples of this bid increment even if they are willing to bid higher than the minimum required bid. This paper presents a simulation approach to optimize sellers' revenue, which is based on theoretical properties of Yankee auctions and utilizes data from real auctions to replicate a given auction. The simulation model can be configured to change the value of bid increment and explore whether a given auction used the optimal bid increment. Our analysis indicates that the auctioneers are, most of the time, far away from optimal choice of bid increment, resulting in substantial losses in a market with already tight margins.
• Gopal, R. D., Goes, P. B., & Garfinkel, R. S. (1998). Interval protection of confidential information in a database. INFORMS Journal on Computing, 10(3), 309-322.
  More info

  Abstract: We deal with the question of how to maintain security of confidential information in a database while answering as many queries as possible. The database is assumed to operate in a query restriction (as opposed to perturbation) mode in which exact answers are given to those queries which, together with those already answered, will not compromise any confidential datum. Those which fail this criterion are not answered. We introduce the concept of interval disclosure where a datum is compromised if the answered queries provide enough information to establish that It is contained in a given interval even if the datum cannot be determined exactly. Models are presented for the problem of deciding whether to answer a query and three techniques, one based on linear programming, are developed and tested. © 1998 INFORMS.
• Chen, N. A., Goes, P. B., & Marsden, J. R. (1997). LAS: A dynamically adaptive database subsystem for better query processing performances. Proceedings - Annual Meeting of the Decision Sciences Institute, 2, 814-.
  More info

  Abstract: For today's information markets and electronic commerce, timely information is crucial to competitive survival. Most of this past research has been focused on designing a single `optimal' database to process foreseeable queries or adopting optimization techniques for existing databases to get better query processing speed. These traditional techniques fall short in meeting the new challenges of today's dynamically changing environment and uncertain/dynamic query patterns. Our objective is to investigate and compare maintenance of multiple databases and/or materialized views for optimally answering specific queries and dynamically redesigning database structures to adapt changing query patterns. We propose that using a learning/assigning subsystem (LAS) detect the changing patterns of queries and then dynamically assign each query to the most suitable database structures and/or materialized views for processing. The learning/assigning subsystem (LAS) includes a learning engine, a knowledge base, and a trigger mechanism. The initial experimental results indicate that the LAS with eight database structures had much better query processing performance with faster response times than the traditional database system using any single database structure.
• Goes, P. B., Gopal, R. D., & Chen, N. (1997). Query evaluation management design and prototype implementation. Decision Support Systems, 19(1), 23-42.
  More info

  Abstract: The increasing customer orientation of information technology applications has resulted in a stronger emphasis on providing query evaluation services to the user community. Applications in electronic markets, data warehousing and decision support systems arenas function in highly dynamic environments serving users who demand increasing flexibility in their interactions with the systems. These characteristics limit a direct application of current query evaluation models. We propose the development of a query evaluation subsystem (QUEM) that is equipped with a knowledge base, a learning component and a decision support component to provide greater flexibility to the users and aid in managing system transitions. A prototype termed QUEST has been built and implemented in a quasi-real world setting. The experimental results validate the practical viability of the proposed architecture.
• Goes, P. B., & Sumita, U. (1996). A closed queueing network model to evaluate the impact of recovery operations on the performance of database servers. Journal of the Operational Research Society, 47(1), 122-135.
  More info

  Abstract: As database servers proliferate in modern information systems architectures in organizations, the issue of protecting and recovering the databases becomes of utmost importance. By developing an analytical model based on a closed network of queues, this paper analyses how different database recovery mechanisms impact on the normal transaction processing. Such a model enables one to capture intricate effects that are peculiar to complex, tightly coupled, multi-component systems, such as database recovery systems, and can be used to facilitate the design and the tuning of database recovery managers. The proposed model provides important performance measures in terms of average transaction processing time and overall systems throughput. Numerical experiments using actual recovery methods demonstrate the effectiveness of the modelling approach.
• Goes, P. B., & Sumita, U. (1995). Stochastic models for performance analysis of database recovery control. IEEE Transactions on Computers, 44(4), 561-576.
  More info

  Abstract: In this paper we develop three analytical models for a comprehensive analysis of database recovery. These models, based on semi-Markov stochastic analysis and queueing networks, not only capture the details of modern recovery mechanisms, but take the complex stochastic behavior of the system into account. Furthermore, we use multiple performance measures to analyze different recovery mechanisms, the impact of environment characteristics and the effect of tunable system parameters, thus offering database designers and administrators a better understanding of the recovery system to be designed or managed. A special case of database recovery that has been studied by previous researchers is analyzed in detail; numerical experiments offer evidence of the effectiveness of our approach. The models developed in this paper, however, are applicable to much more general systems and environments.
• Goes, P. B., Kawashima, H., & Sumita, U. (1992). Analysis of a new thruway communication system with discrete minimal zones. IEEE Transactions on Communications, 40(4), 754-764.
  More info

  Abstract: A mobile communication system for high-speed thruways is currently under consideration in Japan. The system consists of fixed stations installed at regular intervals (2-5 km) along the thruway which are connected to a host computer. Subscribing customers can communicate with the system as they drive through each station's communication zone of minimal type (40-100 m). The authors develop and analyze a stochastic model for this new communication system. The model closely follows the sequence of operations which actually take place according to a communication protocol for handling collisions, and requires no exponential assumptions for the underlying service times. The tradeoff between the total number of stations installed and the probability of successful completion of a task within z km after the initial submission is investigated. Some numerical results are also given for illustrating the tradeoff, with validation via SIMAN simulation.
• Schweitzer, P. J., Seidmann, A., & Goes, P. B. (1991). Performance management in flexible manufacturing systems. International Journal of Flexible Manufacturing Systems, 4(1), 17-50.
  More info

  Abstract: This article treats several performance management decision problems in flexible manufacturing systems (FMSs). This work differs from a number of other studies in that we allow the processing rates at the machines to be varied, and the system has to meet a given throughput goal per unit time. The managerial decision options modeled here include part routing and allocation of tasks to machines, work-in-progress (WIP) levels, capacity expansions, tool-type selection, the setting of throughput goals, and multiperiod production planning. We discuss and explain the insights and implications, partly nonintuitive, gained from our investigations. Finally, extensive numerical evaluations are included to illustrate the economic and performance impact of the various performance management alternatives. These results demonstrate that substantial economic benefits can be achieved by careful tuning of the FMS operational parameters. © 1991 Kluwer Academic Publishers.
• Sumita, U., Kaio, N., & Goes, P. B. (1989). Analysis of effective service time with age dependent interruptions and its application to optimal rollback policy for database management. Queueing Systems, 4(3), 193-212.
  More info

  Abstract: A stochastic model is developed describing a service system subject to inhomogeneous Poisson interruptions with age dependent interruption periods. By studying the probabilistic flow of the underlying multivariate Markov process, the Laplace transform of the effective service time is explicitly obtained. For general renewal interruptions, only the expected effective service time is derived. As an application, an optimal checkpoint policy is examined for database management. It is shown that an optimal policy maximizing the ergodic availability of the database is to implement a checkpoint as soon as the cumulative uptime of the database reaches a prespecified constant k*. A computational procedure is then developed for finding k* and numerical results are exhibited. © 1989 J.C. Baltzer A.G. Scientific Publishing Company.

Proceedings Publications

• Goes, P. B., Chen, X., Guo, C., & Zhang, C. (2014, October). Social Influence in Online Social Games: Understanding its Effect on Willingness to Play and Willingness to Pay. In INFORMS Conference on Information Systems and Technology.
• Goes, P. B., Sanchez, O., & Cruz, M. (2014, December). Success of IT Outsourcing Contracts: effects of the Complexity of the Activity, Relational Governance and Structure of Incentives. In International Conference on Information Systems.

Presentations

• Goes, P. B. (2015, December). Impact of WITS: Looking Back and Looking Ahead. Workshop on Information Technology and Systems.
• Goes, P. B. (2015, June). Big Data Analytics. 3 lectures in China Doctoral Symposium Annual Meeting. Harbin Institute of Technology, China.
• Goes, P. B. (2015, June). Incentive Hierarchies and User Efforts: Evidence from an Online Knowledge Exchange. Tsinghua University Research Seminar.
• Goes, P. B. (2015, June). Publishing Design Science Research. DESRIST panel, Ireland.
• Goes, P. B. (2015, March). Incentive Hierarchies and User Efforts: Evidence from an Online Knowledge Exchange. Boston University Research Seminar.
• Goes, P. B. (2015, May). Incentive Hierarchies and User Efforts: Evidence from an Online Knowledge Exchange. University of Oklahoma Research Seminar.
• Goes, P. B. (2015, May). Keynote Speech at XX Symposium in e-Government and Smart Cities. XX Symposium in e-Government and Smart Cities. Dubain, UAE.
• Goes, P. B. (2015, November). When More is Less: Field Evidence on Unintended Consequences of Multitasking. Southern Methodist University Research Seminar.
• Goes, P. B., Guo, C., & Lin, M. (2015, October). Word of Mouth vs. Word of Health Inspectors: Evidence from Restaurant Reviews. INFORMS Conference on Information Systems and Technology.
• Goes, P. B., Ilk, N., & Brusco, M. (2015, December). A Two-Stage Solution Approach to the Cross-Training Design Problem. Workshop on Information Technology and Systems.
• Goes, P. B., Ilk, N., & Lin, M. (2015, March). When More is Less: Field Evidence on Unintended Consequences of Multitasking. Utah Winter Conference.
• Goes, P. B. (2014, April). Do Incentive Hierarchies Induce User Efforts? Evidence from an Online Knowledge Exchange. Arizona State University - Seminar Series. Arizona State University.
• Goes, P. B. (2014, April). Do Incentive Hierarchies Induce User Efforts? Evidence from an Online Knowledge Exchange. University of Texas Austin - Seminar Series. University of Texas Austin.
• Goes, P. B. (2014, April). Keynote Speech: Design Science Research in Top-Tier Journals - Has anyone seen it?. Big 10 Information Systems Conference. Notre Dame University.
• Goes, P. B. (2014, August). Key Note Speech: Design Science Research in Top-Tier Journals - Has anyone seen it?. City University of Hong Kong Summer Workshop. City University of Hong Kong.
• Goes, P. B. (2014, December). Keynote Speech: Design Science Research in Top-Tier Journals - Has anyone seen it?. WeB Conference. WeB Conference - Auckland NZ.
• Goes, P. B. (2014, December). Keynote Speech: IS Research in Top-Tier Journals. ICIS 2014 Doctoral Consortium. ICIS Doctoral Consortium - Auckland NZ.
• Goes, P. B. (2014, December). Panel -Big Data and IS Research. WeB Conference. WeB Conference - Auckland NZ.
• Goes, P. B. (2014, December). Panel Coordinator and Facilitator: Data Analytics Research Centers. WITS - Workshop on Information Technology and Systems. WITS 2014 - Auckland NZ.
• Goes, P. B. (2014, December). Panel: IS Research. Pre-ICIS 2014 ISWN Workshop on Advancing Women in IS. 2014 ISWN Workshop on Advancing Women in IS - Auckland NZ.
• Goes, P. B. (2014, June). Do Incentive Hierarchies Induce User Efforts? Evidence from an Online Knowledge Exchange. Tsinghua University - University of Arizona Joint Meeting - ecommerce applications. Tsinghua University, Beijing.
• Goes, P. B. (2014, June). Keynote Speech: IS Research in Top-Tier Journals. Summer Workshop Harbin Institute of Technology. Harbin Institute of Technology Summer Workshop.
• Goes, P. B. (2014, November). Do Incentive Hierarchies Induce User Efforts? Evidence from an Online Knowledge Exchange. University of British Columbia - Seminar Series. University of British Columbia.
• Goes, P. B. (2014, September). Do Incentive Hierarchies Induce User Efforts? Evidence from an Online Knowledge Exchange. Michigan State University - Seminar Series. Michigan State University.
• Goes, P. B. (2014, September). Panel: Information Systems Research. Fourth IS Leadership Conference. University of Texas Austin.
• Goes, P. B. (2014, September). Participation in Two-Sided Platform Environments: Economic Incentives and Social Influence. Copenhagen Business School - Distinguished Lecturer. Copenhagen Business School.