More from Desautels 22


How does the implementation of enterprise information systems affect a professional's mobility? An empirical study

Authors: Brad N. Greenwood, Kartik K. Ganju and Corey M. Angst

Publication: Information Systems Research, Vol. 30, No. 2, June 2019, Pages 563-594


Although significant research has examined the effect of enterprise information systems on the behavior and careers of employees, the majority of this work has been devoted to the study of blue- and gray-collar workers, with little attention paid to the transformative effect information technology may have on high-status professionals. In this paper, we begin to bridge this gap by examining how highly skilled professionals react to the increasing presence of enterprise systems within their organizations. Specifically, we investigate how the implementation of enterprise systems-in the form of electronic health records-affects the decision of physicians to continue practicing at their current hospital. Results suggest that when enterprise systems create complementarities for professionals, their duration of practice at the organization increases significantly. However, when technologies are disruptive and force professionals to alter their routines, there is a pronounced exodus from the organization. Interestingly, these effects are strongly moderated by individual and organizational characteristics, such as the degree of firm-specific human capital, local competition, and the prevalence of past disruptions, but are not associated with accelerated retirement or the strategic poaching of talent by competing organizations.

Published: 24 Jul 2019

Yu Ma article selected as a finalist 2019 Paul E. Green Award

Congratulations to Yu Ma, Associate Professor of Marketing and Bensadoun Scholar,  whose article “The Club Store Effect: Impact of Shopping in Warehouse Club Stores on Consumers' Packaged Food Purchases” has been selected as one of four finalists for the Journal of Marketing Research’s 2019 Paul E. Green Award

The Paul E. Green Award recognizes the best article in the Journal of Marketing Research within the last calendar year that demonstrates the most potential to contribute significantly to the practice of marketing research.

Publication: Journal of Marketing Research, Vol. 55, No. 2, April 2018

Authors: Kusum L. Ailawadi, Yu Ma and Dhruv Grewal

This article studies the impact of shopping at the warehouse club format on households' packaged food-for-home purchases. In addition to low prices, this format has several unique characteristics that can influence packaged food purchases. The empirical analysis uses a combination of households' longitudinal grocery purchase information, rich survey data, and detailed item-level nutrition information. After accounting for selection on observables and unobservables, the authors find a substantial increase in the total quantity (servings per capita) of purchases attributable to shopping at this format. Because there is no effect on quality of purchases, this translates into a substantial increase in calories, sugar, and saturated fat per capita. The increase comes primarily from storable and impulse foods and it is drawn equally from foods that have positive and negative health halos. The results have important implications for how marketers can create win–win opportunities for themselves and for consumers.

Published: 24 Apr 2019

Collective Information System Use: A Typological Theory

Authors: Bogdan Negoita, Liette Lapointe and Suzanne Rivard

Publication: MIS Quarterly, Vol. 42 Issue 4, 1281-1301, 2018


As the nature of information systems (IS) has evolved from primarily standalone, to enterprise, and distributed applications, the need for a better understanding of collective IS use has become a research and practical necessity. In view of contributing to this understanding, we conceptually define collective IS use as a unit level construct, rooted in instances of individual-level IS use within the context of a common work process. Its emergence from the individual to the unit level is shaped by different configurations of task, user, and system interdependence between instances of individual-level IS use. On the basis of this definition, we propose a typology of collective IS use that comprises four ideal types, namely siloed use, processual use, coalesced use, and networked use. For each ideal type, we theorize on the emergence process from the individual to the unit level and we consider the measurement implications for each.

Published: 23 Apr 2019

A Primal-Dual Lifting Scheme for Two-Stage Robust Optimization

Authors: Angelos Georghiou, Angelos Tsoukalas, Wolfram Wiesemann

Publication: Operations Research, Forthcoming


Two-stage robust optimization problems, in which decisions are taken both in anticipation of and in response to the observation of an unknown parameter vector from within an uncertainty set, are notoriously challenging. In this paper, we develop convergent hierarchies of primal (conservative) and dual (progressive) bounds for these problems that trade off the competing goals of tractability and optimality: While the coarsest bounds recover a tractable but suboptimal affine decision rule approximation of the two-stage robust optimization problem, the refined bounds lift extreme points of the uncertainty set until an exact but intractable extreme point reformulation of the problem is obtained. Based on these bounds, we propose a primal-dual lifting scheme for the solution of two-stage robust optimization problems that accommodates for generic polyhedral uncertainty sets, infeasible problem instances as well as the absence of a relatively complete recourse. The incumbent solutions in each step of our algorithm afford rigorous error bounds, and they can be interpreted as piecewise affine decision rules. We illustrate the performance of our algorithm on illustrative examples and on an inventory management problem.

Published: 28 Mar 2019

Professor Ramaprasad appointed Associate Editor of Management Science

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

Published: 22 Feb 2019

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


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 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

Published: 20 Nov 2018

Robust Dual Dynamic Programming

Authors: Angelos Georghiou, Angelos Tsoukalas, Wolfram Wiesemann

Publication: Operations Research, Forthcoming


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.

Published: 15 Nov 2018

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


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.

Published: 15 Nov 2018

Optimizing Foreclosed Housing Acquisitions in Societal Response to Foreclosures

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

Publication: Operations Research, Forthcoming


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.

Published: 15 Oct 2018

A Smart-City Scope of Operations Management

Authors: Wei Qi and Zuo-Jun Max Shen

Publication: Production and Operations Management, Forthcoming


We are entering an era of great expectations towards our cities. The vision of “smart city” has been pursued worldwide to transform urban habitats into superior efficiency, quality and sustainability. This phenomenon prompts us to ponder what role the scholars in operations management (OM) can assume. In this essay, we express our initial thoughts on expanding OM to the smart-city scope. We review smart-city initiatives of governments, industry, national laboratories and academia. We argue that the smart-city movement will transition from the tech-oriented stage to the decision-oriented stage. Hence, a smart city can be perceived as a system scope within which planning and operational decisions are orchestrated at the urban scale, reflective of multidimensional needs, and adaptive to massive data and innovation. The benefits of studying smart-city OM are manifold and significant: contributing to deeper understanding of smart cities by providing advanced analytical frameworks, pushing OM knowledge boundaries (such as data-driven decision making), and empowering the OM community to deliver much broader impacts than before. We discuss several research opportunities to embody these thoughts, in the interconnected contexts of smart buildings, smart grid, smart mobility and new retail. These opportunities arise from the increasing integration of systems and business models at the urban scale.

Published: 10 Sep 2018

Designing Risk‐Adjusted Therapy for Patients with Hypertension

Authors: Manaf Zargoush, Mehmet Gumus, Vedat Verter, Stella S. Daskalopoulou

Publication: Production and Operations Management, Forthcoming


Limited guidance is available for providing patient‐specific care to hypertensive patients, although this chronic condition is the leading risk factor for cardiovascular diseases. To address this issue, we develop an analytical model that takes into account the most relevant risk factors including age, sex, blood pressure, diabetes status, smoking habits, and blood cholesterol. Using the Markov Decision Process framework, we develop a model to maximize expected quality‐adjusted life years, as well as characterize the optimal sequence and combination of antihypertensive medications. Assuming the physician uses the standard medication dose for each drug, and the patient fully adheres to the prescribed treatment regimen, we prove that optimal treatment policies exhibit a threshold structure. Our findings indicate that our recommended thresholds vary by age and other patient characteristics, for example (1) the optimal thresholds for all medication prescription are nonincreasing in age, and (2) the medications need to be prescribed at lower thresholds for males who smoke than for males who have diabetes. The improvements in quality‐adjusted life years associated with our model compare favorably with those obtained by following the British Hypertension Society's guideline, and the gains increase with the severity of risk factors. For instance, in both genders (although at different rates), diabetic patients gain more than non‐diabetic patients. Our sensitivity analysis results indicate that the optimal thresholds decrease if the medications have lower side‐effects and vice versa.

Published: 8 Aug 2018

Supply Diagnostic Incentives under Endogenous Information Asymmetry

Authors: Mohammad E. Nikoofal, Mehmet Gumus

Publication: Production and Operations Management, Forthcoming


This paper develops a dyadic supply chain model with one buyer who contracts the manufacturing of a new product to a supplier. Due to the lack of experience in manufacturing, the extent of supply risk is unknown to both the buyer and supplier before the time of contract. However, after the contract is accepted, the supplier may invest in a diagnostic test to acquire information about his true reliability, and use this information when deciding on a process improvement effort. Using this setting, we identify both operational and strategic benefits and costs of diagnostic test. Operationally, it helps the supplier to take the first-best level of improvement effort, which would increase efficiency of the total supply chain. Strategically, it enables the buyer to reduce the agency costs associated with implementing process improvement on the supplier. Besides these benefits, diagnostic test increases the degree of information asymmetry along the supply chain. This in turn provides the supplier with proprietary information, whose rent would be demanded from the buyer in equilibrium. Benefit-cost analysis reveals two key factors in determining the value of diagnostic test: (i) degree of endogenous information asymmetry between supply chain firms, and (ii) the relative cost of diagnostic test with respect to process improvement cost. Our results indicate that when both are high, the mere presence of diagnostic test can result in less reliable supply chain. This implies that when incentives are not properly aligned, information asymmetry amplified due to diagnostic test neutralizes all its benefits.

Published: 23 Jul 2018

A Model of Two-Sided Costly Communication for Building New Product Category Demand

Authors: Michelle Y. Lu , Jiwoong Shin

Publication: Marketing Science, Vol. 37, No. 3, May-June 2018


When a firm introduces a radical innovation, consumers are unaware of the product’s uses and benefits. Moreover, consumers are unsure of whether they even need the product. In this situation, we consider the role of marketing communication as generating consumers’ need recognition and thus market demand for a novel product. In particular, we model marketing communication as a two-sided process that involves both firms’ and consumers’ costly efforts to transmit and assimilate a novel product concept. When the marketing communication takes on a two-sided process, we study a firm’s different information disclosure strategies for its radical innovation. We find that sharing innovation, instead of extracting a higher rent by keeping the idea secret, can be optimal. A firm may benefit from the presence of a competitor and its communication effort. The innovator can share its innovation so that competitors can also benefit, which encourages rivals to enter the market. The presence of such competition guarantees a higher surplus for consumers, which can induce greater consumer effort in a two-sided communication process. Moreover, the increased consumer effort, in turn, prompts complementarity in the communication process and lessens the potential free-riding effect in communication between firms. Additionally, it encourages the rival firm to exert more effort, especially when the role of consumers becomes more important. Sharing innovation with a rival serves as a mechanism to induce more efforts in a two-sided communication process.

Published: 23 Jul 2018

Oversight and Efficiency in Public Projects: A Regression Discontinuity Analysis

Authors: Eduard Calvo, Ruomeng Cui and Juan Camilo Serpa

Publication: Management Science, Volume 65, Issue 12, December 2019, Pages 5651-5675.


In the U.S., four in ten public infrastructure projects report delays or cost overruns. To tackle this problem, regulators often scrutinize the project contractor’s operations. We investigate the causal effect of government oversight on project efficiency by gleaning 262,857 projects that span seventy-one U.S. federal agencies and 54,739 contractors. Our identification strategy exploits a regulatory bylaw: if a project’s anticipated budget exceeds a threshold value, the contractor’s operations are subject to surveillance from independent procurement officers; otherwise, these operational checks are waived. Using a regression discontinuity design, we find that oversight is obstructive to the project’s operations, especially when the contractor (i) has no prior experience in public projects, (ii) is paid with a fixed-price contract that includes performance-based incentives, and (iii) performs a labor-intensive task. In contrast, oversight is least obstructive — or beneficial — when the contractor (i) is experienced, (ii) is paid with a time-and-materials contract, and (iii) performs a machine-intensive task.

Published: 10 Jul 2018

Supply Chain Proximity and Product Quality

Authors: Robert Bray, Juan Camilo Serpa and Ahmet Colak

Publication: Management Science, Volume 65, Issue 9, September 2019, Pages 4079-4099.


We explore the effect of supply chain proximity on product quality by merging four independent data sources from the automotive industry, collecting: (i) auto component defect rates, (ii) upstream component factory locations, (iii) downstream assembly plant locations, and (iv) product-level links connecting the upstream and downstream factories. Combining these four datasets allows us to trace the flow of 27,807 products through 529 supplier factories and 275 assembly plants. We estimate that increasing the distance between an upstream component factory and a downstream plant by an order of magnitude increases the component’s expected defect rate by 3.9%. We also find that shorter inter-factory spans are associated with more rapid product quality improvements, and that supply chain distance is more detrimental to quality when automakers: (i) produce early generation models or (ii) high-end products, (iii) when they buy components with more complex configurations, or (iv) when they source from suppliers who invest relatively little in research and development

Published: 11 Jun 2018


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