Performance guarantees for model-based Approximate Dynamic Programming in continuous spaces

Authors: Paul N. Beuchat, Angelos Georghiou, and John Lygeros

Publication: IEEE Transactions on Automatic Control, Forthcoming

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Evaluation of the allocation performance in a fashion retail chain using data envelopment analysis

Authors: He Huang, Shanling Li & Yu Yu

Publication: The Journal of The Textile Institute, Forthcoming

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Does social capital moderate the association between children's emotional overeating and parental stress? A cross-sectional study of the stress-buffering hypothesis in a sample of mother-child dyads

Authors: Jennifer Mandelbaum, Spencer Moore, Patricia P. Silveira, Michael J. Meaney, Robert D. Levitan, and Laurette Dubé

Publication: Social Science and Medicine, Forthcoming

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Multi-behavioral obesogenic phenotypes among school-aged boys and girls along the birth weight continuum

Authors: Andre Krumel Portella, Catherine Paquet, Adrianne Rahde Bischoff, Roberta Dalle Molle, Aida Faber, Spencer Moore, Narendra Arora, Robert Levitan, Patricia Pelufo Silveira, Laurette Dubé

Publication: PLoS ONE, 14(2): February 2019, e0212290

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Professor Ramaprasad appointed Associate Editor of Management Science

Jui Ramaprasad, Associate Professor in Information Systems, was recently appointed as Associate Editor to Management Science.

Pollution avoidance and green purchase: The role of moral emotions

Authors: Dapeng Liang, Chenxuan Hou, Myung-Soo Jo, and Emine Sarigollu

Publication: Journal of Cleaner Production, Volume 210, 10 February 2019, Pages 1301-1310

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Extrinsic versus Intrinsic Rewards for Contributing Reviews in an Online Platform

Authors: Warut Khern-am-nuai, Karthik Kannan, Hossein Ghasemkhani

Publication: Information Systems Research, Forthcoming

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Firms have considered various forms of incentives for writing reviews, including the use of extrinsic rewards to attract reviewers. Building on this literature, we study the implications of monetary incentives on online reviews in the context of a natural experiment, where one review platform suddenly began offering monetary incentives for writing reviews. We refer to this as the treated platform. Along with data from Amazon.com and using the difference-in-differences approach, we compare the quantity and quality of reviews before and after rewards were introduced in the treated platform. We find that reviews are significantly more positive but that the quality decreases. Taking advantage of the panel data, we also evaluate the effect of rewards on existing reviewers. We find that their level of participation after monetary incentives decreases but not their quality of participation. Last, even though the platform enjoys an increase in the number of new reviewers, disproportionately more reviews appear to be written for highly rated products.

Read abstract: Information Systems Research

Developing a gamified mobile application to encourage sustainable energy use in the office

Authors: Divinus Oppong-Tawiah, Jane Webster, Sandy Staples, Ann-Frances Cameron, Ana Ortiz de Guinea, Tam Y. Hung

Publication: Journal of Business Research, Forthcoming

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The Decision Rule Approach to Optimization under Uncertainty: Methodology and Applications

Authors: Angelos Georghiou, Daniel Kuhn, Wolfram Wiesemann

Publication: Computational Management Science, Forthcoming

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Robust Dual Dynamic Programming

Authors: Angelos Georghiou, Angelos Tsoukalas, Wolfram Wiesemann

Publication: Operations Research, Forthcoming

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Multi-stage robust optimization problems, where the decision maker can dynamically react to consecutively observed realizations of the uncertain problem parameters, pose formidable theoretical and computational challenges. As a result, the existing solution approaches for this problem class typically determine suboptimal solutions under restrictive assumptions. In this paper, we propose a robust dual dynamic programming (RDDP) scheme for multi-stage robust optimization problems. The RDDP scheme takes advantage of the decomposable nature of these problems by bounding the costs arising in the future stages through lower and upper cost to-go functions. For problems with uncertain technology matrices and/or constraint right-hand sides, our RDDP scheme determines an optimal solution in finite time. If also the objective function and/or the recourse matrices are uncertain, our method converges asymptotically (but deterministically) to an optimal solution. Our RDDP scheme does not require a relatively complete recourse, and it offers deterministic upper and lower bounds throughout the execution of the algorithm. We demonstrate the promising performance of our algorithm in a stylized inventory management problem.

The Effects of Analyst‐Country Institutions on Biased Research: Evidence from Target Prices

Authors: Mark T. Bradshaw, Alan G. Huang, Hongping Tan

Publication: Journal of Accounting Research, Forthcoming

Abstract: 

Prior research demonstrates that a strong institutional infrastructure in a country moderates self‐serving behavior of market participants. Cross‐country economic activities have increased significantly, presenting a research opportunity to examine the relative influence of local versus foreign institutional infrastructure on individual market participants. We utilize variation in analyst‐country location relative to covered firm location to examine institutional determinants of optimism in analyst research. Focusing on target prices, where persistent optimism is well documented, we find that analysts domiciled in countries with stronger institutional infrastructures exhibit significantly attenuated target price optimism and more value‐relevant target prices. Our results demonstrate the importance of domestic country‐level institutional factors in moderating self‐serving behavior of market participants engaged in cross‐country activities.

Optimizing Foreclosed Housing Acquisitions in Societal Response to Foreclosures

Authors: Senay Solak, Armagan Bayram, Mehmet Gumus, Yueran Zhuo

Publication: Operations Research, Forthcoming

Abstract:

A dramatic increase in U.S. mortgage foreclosures during and after the great economic recession of 2007-2009 had devastating impacts on the society and the economy. In response to such negative impacts, non-profit community development corporations (CDCs) throughout the U.S. utilize various resources, such as grants and lines of credit, in acquiring and redeveloping foreclosed housing units to support neighborhood stabilization and revitalization. Given that the cost of all such acquisitions far exceeds the resources accessible by these non-profit organizations, we identify socially optimal policies for CDCs in dynamically selecting foreclosed properties to target for potential acquisition as they become available over time. We evaluate our analytical results in a numerical study involving a CDC serving a major city in the U.S, and specify social return based thresholds defining selection decisions at different funding levels. We also find that for most foreclosed properties CDCs should not offer more than the asking price, and should typically consider overbidding only when the total available budget is low. Overall, comparisons of optimal policies with historical acquisition data suggest a potential improvement of around 20% in expected total impacts of the acquisitions on nearby property values. Considering a CDC with annual fund availability of $4 million for investment, this corresponds to an estimated additional value of around $280,000 for the society.

Synergistic, Antagonistic, and Asymmetric Media Interactions

Authors: Ceren Kolsarici, and Demetrios Vakratsas

Publication: Journal of Advertising, Vol. 47, No. 3, 2018

Protecting positioning innovations: the emergence of non-traditional trademark registrations

Authors: S. Mishra, Demetrios Vakratsas, and A. V. Krasnikov

Publication: Marketing Letters, Vol. 29, No. 3, September 2018