Research Spotlights
Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence
1107
Juan Feng, Xin Li, Xiaoquan (Michael) Zhang
Online product reviews are arguably one of the most easily accessible sources of marketing data for online retailers. It is possible to build machine learning tools to learn consumers' opinions from online word of mouth (WOM). Menu costs are practically trivial for online retailers, and it is not difficult to program automatic price changes based on live feeds of online review data. This paper argues that sellers can use online product reviews to develop better pricing strategies. We first build a theoretical model to examine a seller's optimal pricing strategy when online WOM information is taken into consideration. We find that, with consumer reviews, firms may take price-skimming and penetration strategies depending on the combination of consumer characteristics (such as misfit cost) and product characteristics (such as product quality). We examine a book retailing data set collected from online stores to offer empirical support for the analytical predictions.
The Strategic Value of Information Technology in Setting Productive Capacity
1124
Dawei (David) Zhang, Barrie R. Nault, Xueqi (David) Wei
Capacity is the maximum short-run output with capital in place under normal operations, and capital investment increases capacity. Excess capacity can be used as entry deterrence by lowering average costs over a greater range of output and as an operations strategy by providing value through flexibility to manage demand fluctuations and production disturbances. We study the way that information technology (IT) can contribute to a strategy of holding excess capacity by comparing the relationship between IT capital and capacity with that of non-IT capital and capacity. We find that increases in IT capital yield almost fourfold greater expansion in capacity than do increases in non-IT capital. Thus, as both types of capital are constraints on capacity, for a strategy of holding excess capacity, IT capital is a more valuable constraint to relax than non-IT capital. In addition, since the late 1990s, IT capital and, to a lesser extent, non-IT capital have reduced capacity utilization (output divided by capacity), meaning increasing levels of excess capacity are being held across manufacturing industries and utilities across the economy.
How Pair Programming Influences Team Performance: The Role of Backup Behavior, Shared Mental Models, and Task Novelty
1145
Thomas Kude, Sunil Mithas, Christoph T. Schmidt, Armin Heinzl
Many organizations and software firms these days use pair programming to meet the challenges posed by digital transformations and to meet customer needs. They use pair programming to become more agile and responsive to their competitive environment. Although some studies suggest that pair programming can potentially increase the quality of developed software code and the satisfaction and confidence of developers, very little is known as to how pair programming affects team performance. Therefore, we conducted an empirical study at one of the largest enterprise software firms that serves a large number of Fortune 500 companies, and we collected data from the software developers, Scrum masters, and product owners of 62 software development teams. Our findings show that pair programming affects team performance positively by changing cognitive structures and behavioral patterns in software teams. Pair programming helps team members develop shared mental models and, as a consequence, increases backup behavior among team members. Backup behavior is particularly valuable for teams facing high task novelty. Our findings have critical implications for organizations and senior managers as they lead their digital transformation efforts where they often rely on autonomous teams for providing digital innovation. We show that pair programming can be a key ingredient for high-performance teams. Establishing the practice of pair programming promises to be particularly valuable for those teams that lack shared mental models and teams whose members fail to provide each other backup.
When Seeing Helps Believing: The Interactive Effects of Previews and Reviews on E-Book Purchases
1164
Angela Aerry Choi, Daegon Cho, Dobin Yim, Jae Yun Moon, Wonseok Oh
For many products, particularly digital content, consumers base purchase-related decisions on not only others' evaluations (e.g., online reviews) but also their own direct experiences (e.g., previews). Many of them therefore combine “seeing” through their own encounters with “believing” the assessments of others, often being confronted with a situation wherein the former contradicts the latter. This study investigates the dynamics underlying the interactive relationships between online reviews and previews to shed light on how consumers collectively use these prebuying resources as guidance in purchasing e-books. Our research reveals that consumers wisely leverage previews in accordance with the characteristics of reviews (e.g., volume, valence, and variance). The positive effects of previews increase with decreasing review volume and average valence. Consumers also rely heavily on previews in situations wherein a high variance exists among the indirect evaluations of reviewers. We detect the presence of order effects with respect to exposure to previews and reviews; exposure to previews after accessing reviews more effectively drives sales than when exposure to reviews precedes the encounters. These results provide content providers with useful managerial insights into how they can maximize consumers' overall prepurchase experiences and enhance content sales through the excellent leveraging of previews and reviews.
How Do EHRs and a Meaningful Use Initiative Affect Breaches of Patient Information?
1184
Seung Hyun Kim, Juhee Kwon
Effective use of electronic health records (EHRs) is considered an important step toward the goal of improving the quality of U.S. healthcare while reducing its costs. However, did EHRs and a meaningful use (MU) initiative increase the risk of a breach of patient information as many people were worried about? This study shows that implementing EHRs led to a 3.081 times higher risk of a breach of patient information. This heightened risk was mostly driven by the occurrence of more accidental breaches. Undertaking MU initiatives increased the risk of accidental breaches by 1.771 times but not the risk of malicious breaches. We also found that these risks increased more among relatively larger hospitals. We conclude that, despite recent evidence that the usage of EHRs has improved the quality of healthcare, quality must go hand in hand with the protection of patient information. Thus, we argue that the government's future revision of the criteria for MU should better reflect the risk of accidental breaches. Our study also suggests that policy makers should carefully address the possible increase in the risk of privacy breaches when considering whether to promote industry-wide adoption of digitized data and processes.
When and How to Leverage E-commerce Cart Targeting: The Relative and Moderated Effects of Scarcity and Price Incentives with a Two-Stage Field Experiment and Causal Forest Optimization
1203
Xueming Luo, Xianghua Lu, Jing Li
The rise of online shopping cart-tracking technologies enables new opportunities for e-commerce cart targeting (ECT). However, practitioners might target shoppers who have short-listed products in their digital carts without fully considering how ECT designs interact with consumer mindsets in online shopping stages. The authors find that ECT has a substantial impact on consumer purchases, inducing a 29.9% higher purchase rate than e-commerce targeting without carts. Moreover, this incremental impact is moderated: the ECT design with a price incentive amplifies the impact, but the same price incentive leads to ineffective e-commerce targeting without carts. By contrast, a scarcity message attenuates the impact but significantly boosts purchase responses to targeting without carts. Interestingly, the costless scarcity nudge is approximately 2.3 times more effective than the costly price incentive in the early shopping stage without carts, whereas a price incentive is 11.4 times more effective than the scarcity message in the late stage with carts. The authors also leverage a causal forest algorithm that can learn purchase response heterogeneity to develop a practical scheme of optimizing ECT. These findings empower managers to prudently target consumer shopping interests embedded in digital carts in order to capitalize new opportunities in e-commerce.
The Adaptive Roles of Positive and Negative Emotions in Organizational Insiders' Security-Based Precaution Taking
1228
A. J. Burns, Tom L. Roberts, Clay Posey, Paul Benjamin Lowry
Protecting organizational information is a top priority for most firms. This reality, coupled with the fact that organizational insiders control much of their organizations' valuable information, has led both researchers and practitioners to acknowledge the importance of insiders' behavior for information security. Specifically, insiders must take precautions in the workplace to help ensure organizational information security. Emotions are a fruitful area of investigation to better understand insiders' precaution taking because emotions are an adaptive intermediary between stimuli and behavior. Thus, organizations' failure to account for insiders' broad experience of emotions when dealing with security threats can influence insiders' precaution taking and, subsequently, organizational information security. The results of our research study demonstrate important relationships between both positive and negative emotions and insiders' precaution taking. Importantly, the relationship between certain discrete emotions and precaution taking is mediated by insiders' psychological capital, a higher-order, work-related construct of positive psychological resource capabilities, and psychological distancing, a coping mechanism characterized by insiders' attempts to detach themselves psychologically from a situation. Researchers and practitioners can use these findings to better understand insiders' precaution taking in the workplace and develop security training programs that more effectively utilize emotional appeals.
Impact of Live Chat on Purchase in Electronic Markets: The Moderating Role of Information Cues
1248
Xue (Jane) Tan, Youwei Wang, Yong Tan
Live chat tools have emerged as a channel for fostering synchronous communication between sellers and buyers. However, a positive link between live chat and conversion does not suggest causation because customers with high purchase intention are more likely to initiate live chat in the first place. Our research accounts for such selection and studies the impact of live chat with the presence of information cues: product sales volumes and seller feedback scores. Using granular data from Alibaba, we find that live chat can increase purchase probability of tablets by 15.99%. Further, the substitutional or complementary patterns between live chat and the information cues allow us to understand how live chat tools change the ways consumers evaluate product quality and seller credibility. We observe a substitutional effect of live chat on seller feedback score such that sellers with low feedback scores benefit more from live chat conversations than sellers with high scores. On the contrary, products with a high past sales volume sell better after live chat, indicating a reinforcement effect. Such findings deepen our understanding of the difference between various information cues in electronic markets and delineate the specific type of benefit live chat brings if put into best use by sellers and online marketplace designers.
Unraveling the “Social” in Social Norms: The Conditioning Effect of User Connectivity
1272
Che-Wei Liu, Guodong (Gordon) Gao, Ritu Agarwal
Operating on the basic principle of “telling people about what lots of other people do,” social norms interventions have demonstrated efficacy in inducing behavior change in diverse settings. However, very few studies examine how the effect of social norms is differentially manifest across individuals, especially in the contemporary socially connected digital world. We provide new empirical evidence from a randomized field experiment that included more than 7,000 individuals on an online physical activity community observed for a two-month period. We find that connectivity plays an important role in moderating the effectiveness of social norms: individuals with higher levels of social connectivity are more susceptible to a social norms message. Additional analysis reveals that individuals who engage in information sharing (high followers and low followees) are the most susceptible to the social norms message. This study has important implications for the effective and safe use of social norms in nudging people's behavior. Our finding that social norms do not affect all users equally should help optimize interventions by focusing on users with high susceptibility based on easily observable measures.
The Spillover of Spotlight: Platform Recommendation in the Mobile App Market
1296
Chen Liang, Zhan (Michael) Shi, T. S. Raghu
Product recommendations are ubiquitous in platform-based markets. This paper investigates the externality of platform-provided recommendations by focusing on the demand spillover to related products. In the context of the fast-growing mobile app market, we systematically examine the spillover effect on three groups of related apps: apps by the same developer, apps with similar functionality, and the same apps marketed on a different platform. We distinguish two mechanisms that potentially drive the externality: exposure spillover and quality endorsement spillover. We find that both spillover mechanisms can drive the externality, but their strength and relative importance vary depending on the specific relationship between the featured and nonfeatured products. Furthermore, our heterogeneity analysis suggests that the strength of the spillover effect also depends on the salient characteristics of the featured products, including price and user rating.
A Dynamic Model of Embeddedness in Digital Infrastructures
1319
Daniel Fürstenau, Abayomi Baiyere, Natalia Kliewer
Digital infrastructures result from individual yet interdependent systems evolving in relation to each other. This paper identifies three processes by which individual systems become embedded into digital infrastructures. The first is a parallel process, whereby systems become embedded independently of each other. The second is a competitive process, whereby systems compete for resources and attention and one system usually thrives while the other system loses importance. The third is a spanning process characterizing a situation of boundary-spanning between distinct parts of a digital infrastructure. The three processes, synthesized into a dynamic model of digital infrastructure embeddedness, offer clarity to the question of how digital infrastructures evolve. They also provide insight into the emergence of three forms of digital infrastructures: silofied, regenerated, and unified. Reflecting an interconnection view, our research further facilitates an understanding of infrastructure inertia and its associated consequence. Criticality traps should be avoided by considering the right timing for system replacement in the light of growing embeddedness over time.
How Mega Is the Mega? Exploring the Spillover Effects of WeChat Using Graphical Model
1343
Jinyang Zheng, Zhengling Qi, Yifan Dou, Yong Tan
WeChat, an instant messaging app, is considered a mega app because of its dominance in terms of use among Chinese smartphone users. A major concern for such an app is whether its increasing usage would crowd out the usage of other apps in the broader app market. This study estimates the spillover effects of WeChat on the other top 50 most frequently used apps in China, using users' weekly app usage data. Given the challenge of determining causal inference from observational data, this study borrows a machine-learning method and integrates it with econometrics. We find that WeChat does not crowd out the other apps' use. In fact, only two other apps, Tencent News and Taobao, are affected by WeChat usage causally, and interestingly, both receive positive spillover effects as a result of the complementary effects. This finding alleviates concerns about the threat by WeChat and indicates that WeChat's success is not in exchange for squeezing out the use of other major apps. Instead, WeChat might contribute to the platform by transforming users' nonmobile activities to the mobile setting and by exhibiting some positive spillovers. In addition, this study shows the strength of graphical models in identifying causal relationships from observational data.
A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections
1363
Jorge Mejia, Shawn Mankad, Anandasivam Gopal
From an upset stomach to a life-threatening foodborne illness, getting sick is all too common after eating in restaurants. Although health inspection programs for restaurants are designed to protect consumers, such inspections typically occur sporadically, allowing restaurant hygiene to remain unknown for diners. At the same time, online reviews for restaurants provide a valuable source of information about the current status and quality of a restaurant. In this paper, we use the text contained in these reviews of restaurants to effectively identify cases of hygiene violations in restaurants, even after the restaurants have been inspected. Using data about restaurant hygiene in New York City from 2010 through 2016 and the associated set of online reviews for the same set of restaurants from Yelp, we use supervised machine learning techniques to develop a hygiene dictionary specifically crafted to identify hygiene-related problems. With this dictionary, we report systematic instances of moral hazard, wherein restaurants with positive hygiene inspection scores are seen to regress in their hygiene maintenance within 90 days of receiving the inspection scores. Based on these results, we provide strategies for how cities and policymakers may design effective restaurant inspection programs.
Moving IS Project Control Research into the Digital Era: The “Why” of Control and the Concept of Control Purpose
1387
Martin Wiener, Magnus Mähring, Ulrich Remus, Carol Saunders, W. Alec Cram
The control of information systems (IS) projects is central to creating and capturing value from digitalization. However, the current understanding of IS project control is too restrictive and not well attuned to the digital era, in which collaborative value creation in open-ended digital innovation and transformation efforts is critical to firm competitiveness, ecosystem evolution, and societal advancement. Reviewing earlier research, we find that the dominant view of IS project control emphasizes value capture/appropriation and virtually ignores value creation. To address this shortcoming, we introduce the concept of control purpose (why) and advocate for broadening control activities to encompass the two control purposes of value appropriation and value creation. This implies that practitioners need to strategically decide on and actively manage the balance between different purposes of control activities. By doing so, they will be better equipped to achieving success in digital innovation and transformation initiatives.
“Monday Effect” on Performance Variations in Supply Chain Fulfillment: How Information Technology–Enabled Procurement May Help
1402
Yuliang Yao, Martin Dresner, Kevin Xiaoguo Zhu
If labor productivity varies in unknown ways over time, it could lead to unforeseen fluctuations in production or delivery rates, leading to stockouts or inventory build-up in a supply chain, while contributing to higher operating costs and to lower satisfaction levels for customers. The “Monday Effect,” that is, lower productivity and higher error rates on Mondays compared with other days of the week, has been demonstrated in the finance and industrial relations literature. Using a database of 12 months of purchases from the General Services Administration (GSA) of the U.S. government (a key distributor of goods to government purchasers), we show that, indeed, performance is lower on Mondays compared with other weekdays in terms of order fulfillment and order cycle time. However, when purchasers use the GSA's internet-based electronic market instead of using manual ordering procedures, the fulfillment gap between Mondays and other weekdays narrows considerably, demonstrating the value of information technology in smoothing distribution flows. By acknowledging the Monday Effect, distributors can thus plan for these weekly fluctuations and use information technology to improve service levels.
Optimal Management of Virtual Infrastructures Under Flexible Cloud Service Agreements
1424
Zhiling Guo, Jin Li, Ram Ramesh
Cloud-service agreements entail the provisioning of virtual infrastructures at specified availability levels. The agreements specify the infrastructure prices and penalties borne by providers when assured availabilities are not met. Hence, backup resources should be optimally provisioned by balancing the provisioning costs with penalties. We develop stochastic dynamic optimization models of the backup provisioning problem by integrating methods from Operations Management, Statistics and Machine Learning, and Computer Science. We present two sets of dynamic provisioning strategies: periodic policies where resources are adjusted at regular intervals and aperiodic policies that allow flexible timing of such interventions. A closed-loop optimization model under conservative resource control and a certainty-equivalent optimization model under aggressive resource control are developed for periodic management. Similarly, we propose two strategies for aperiodic management: single intervention with single look-ahead and multiple interventions with single look-ahead. We develop computationally efficient online algorithms for both periodic and aperiodic models. We evaluate the models through computational experiments and validate with Amazon EC2 use cases. We provide cloud service providers practical guidelines for efficiently formulating flexible service agreements and cost-effectively managing the virtual infrastructure resources. The proposed resource optimization framework is most suitable to Infrastructure-as-a-Service and can easily be extended to Platform-as-a-Service environments.
