Daily deals platforms have emerged as an integral part of the marketing mix for retailers and have enjoyed a wide acceptance among consumers. However, there is considerable ambiguity about the effects of deals on brand evaluations, in particular the effects on pre-consumption brand evaluations. This ambiguity can influence the decisions by retailers to join daily deals platforms, which operate as double-sided networked markets. We perform a series of experiments to test the effect of offering a deal in these platforms on consumers’ pre-consumption brand evaluations. Our research shows that brand evaluations are contingent on retailer characteristics (price segment and age), customarily reported deal performance statistics (number of views and purchases of the focal deal), and competitive deal intensity. Furthermore, the paper finds that the effect of daily deals on brand evaluation differs substantially from that associated with regular print coupons, which operate without the benefits of a platform-based model. Finally, local competition from deals in the platform is shown to have a significant negative spillover effect on neighboring retailers who do not offer deals. Our work thus informs retailers considering joining deals platforms about potential costs associated with such a decision, while also providing insights for platform owners on how they may help mitigate some of these losses in brand value for members of their ecosystem. Our research thus provides for a fuller and more nuanced evaluation of daily deals’ effects on brand evaluations.
Measuring quality in the service industry remains a challenge. Existing methodologies are often costly and unscalable. Furthermore, understanding how elements of service quality contribute to the performance of service providers continues to be a concern in the service industry. In this paper, we address these challenges in the restaurant sector, a vital component of the service industry. Our work provides a scalable methodology for measuring the quality of service providers using the vast amount of text in social media which is associated with economic outcomes for the providers. We use text present in online reviews on Yelp.com to identify and extract service dimensions using Non-Negative Matrix Factorization for a large set of restaurants located in a major city in the United States. We subsequently validate these service dimensions as proxies for service quality using external data sources and a series of laboratory experiments. Finally, we use econometrics to test the relationship between these dimensions and restaurant survival as additional validation. We find that our proposed service quality dimensions match industry standards and are correctly identified by subjects in a controlled setting. Furthermore, we show that specific service dimensions are significantly correlated with the survival of merchants, even after controlling for competition and other factors.This work has implications for the strategic use of text analytics in the context of service operations, where an increasingly large text corpus is available. We discuss the benefits of this work for service providers, as well as for platforms, such as Yelp and OpenTable.
The benefits of recommendation systems in online retail contexts have received much attention in prior work. Much of this work has been conducted in PC-based settings, while mobile devices are becoming increasingly central to the online shopping experience. It remains to be examined if the effects of recommendation systems in retail differ across these two channels, in terms of customer-level decision outcomes. In this paper, we examine these differences in some detail, studying how product views and sales attributed to a recommendation system are different across mobile and PC-based channels. Further, we examine how the effect of a recommendation system across channels influences sales diversity, an important outcome in the retail industry. We conduct our analysis using a randomized field experiment, conducted in partnership with an online retailing firm in South Korea, where the experimental treatment is access to a recommendation system. Our results show that the use of recommendation systems enhances customer-level outcomes, such as views and sales of recommended products, clickthrough rate, and conversion. More importantly, the marginal impacts of the recommendation system are significantly higher for mobile users, indicating that the higher search costs imposed through mobile devices are more effectively reduced through recommendation systems. With respect to sales diversity, we observe that while the mobile channel leads to more diverse sales, we see no interaction effects of the recommendation system and mobile use on sales diversity. These results provide boundary conditions for the efficacy of recommendation systems in retail contexts where online sales occur across both PC-based and mobile channels. We discuss the managerial implications of these results for online retailers and conclude with opportunities for further research.
Information technology (IT) service providers are often advised to consider moving their service offerings along the value chain as a way to enhance their competitiveness. On the basis ofthis advice, service providers operating successfully at the lower end of the value chain have tried to expand into higher-order consulting services, while those operating higher up on the value chain have sought to expand into more routinized services. In both cases, such efforts have been metwith limited success. In this paper, we examine why this might be the case, using an agent-based model developed specifically for this purpose. As part of the model, we use the resource-based view of the firm to construct agents, representing individual IT services firms with three distinct strategic orientations (archetypes) operating at different parts of the value chainwith varying resource endowments. We then examine the outcomes associated with these firms when they transition along the value chain. While we find that moving along the value chain is generallyrisky, we identify specific conditions under which such moves may be favorable to firms. We find that firmsmoving upthe value chain are likely to be successful only if such moves are accompanied by significant resource changes. In contrast, firms moving downthe value chain are likely to be successful only if such moves are accompaniedby learning capability arising out of higher absorptive capacity. We find that resource fungibility moderates these relationships. We conclude with a discussion of the managerial implications of our study as well as opportunities for future empirical research within the IT services industry based on our propositions.
From an upset stomach to a life-threatening foodborne illness, getting sick is all too common after eating in restaurants. While health inspection programs are designed to protect consumers, such inspections typically occur at wide intervals of time, allowing restaurant hygiene to remain unmonitored in the interim periods. Information provided in online reviews may be effectively used in these interim periods to gauge restaurant hygiene. In this paper, we provide evidence for how information from online reviews of restaurants can be effectively used to identify cases of hygiene violations in restaurants, even after the restaurant has been inspected and certified. We use data from restaurant hygiene inspections in New York City from the launch of an inspection program from 2010 to 2016, and combine this data with online reviews for the same set of restaurants. Using supervised machine learning techniques, we then create a hygiene dictionary specifically crafted to identify hygiene-related concerns and use it to identify 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. To the extent that social media provides some visibility into the hygiene practices of restaurants, we argue that the effects of information asymmetry that lead to moral hazard may be partially mitigated in this context. Based on our work, we also provide strategies for how cities and policy-makers may design effective restaurant inspection programs, through a combination of traditional inspections and the appropriate use of social media.
New information pertinent to organizational decision making, even when publicly available, may not diffuse rapidly in the form of adoption and transformation of organizational practices. In this study, we examine how different markers of expertise, each representative of human capital at both individual and organizational levels, moderates the speed of response to new information. We do so in the context of medical device utilization, viz. stents, for the treatment of stable coronary arterial disease by physicians practicing in hospitals. Results show physicians possessing specialized expertise developed through deliberate practice adopt new guidelines significantly faster, as compared with physicians endowed with general expertise reflected in elite schooling or tenure. Further, we observe significant spillovers within organizations from expertise gained through deliberate practice, indicating physicians with expertise markers associated with deliberate practice are able to act as influential agents and help diffuse new practices within the organization. Our study thus extends the literature on both information diffusion and expertise by providing quantitative and qualitative evidence of the mechanisms at play in the adoption of new best practices.
Mobile apps are one of the building blocks of the mobile digital economy. A differentiating feature of mobile apps to traditional enterprise software is online reviews, which are available on app marketplaces and represent a valuable source of consumer feedback on the app. We create a supervised topic modeling approach for app developers to use mobile reviews as useful sources of quality and customer feedback, thereby complementing traditional software testing. The approach is based on a constrained matrix factorization that leverages the relationship between term frequency and a given response variable in addition to co-occurrences between terms to recover topics that are both predictive of consumer sentiment and useful for understanding the underlying textual themes. The factorization is combined with ordinal regression to provide guidance from online reviews on a single app's performance as well as systematically compare different apps over time for benchmarking of features and consumer sentiment. We apply our approach using a dataset of over 100,000 mobile reviews over several years for three of the most popular online travel agent apps from the iTunes and Google Play marketplaces.
The Information Technology (IT) industry is characterized by rapid technological change and fast-moving dynamics, a significant part of which may be attributed to entrepreneurial ventures that pioneer new innovations. Correspondingly, the rate of new entry in the form of entrepreneurial ventures poses a critical risk factor for incumbent IT firms. While theoretical work points out a negative relationship between new entry threats (NET) and firm performance, empirical findings are scarce due to the inability to measure NET properly. Leveraging a novel NET measure based on text-mining approaches, we show that a higher level of NET indeed leads to a drop in the incumbent’s performance. We also show that facing high NET, firms with more independent directors are better able to withstand these threats, possibly due to stronger monitoring and the valuable resources and information provided by the independent directors. Effectively, we circumscribe a set of boundary conditions under which board governance mechanisms may contribute to firm performance. To address the endogeneity issues associated with board independence, we use the enactment of the Sarbanes-Oxley Act and related changes to the NYSE/NASDAQ listing rules as exogenous shocks to create instruments, and our results are robust to the instrumental variable regressions. Further, we show that our findings are generalizable to other high tech industries, and discuss the implications for research and practice.
We investigate how mass shootings influence the stock price of firearms manufacturers. While it is well known that mass shootings lead to increased firearms sales, the response from financial markets is unclear. On one hand, given the observed short-term increase in demand, firearm stock prices may rise due to the unexpected financial windfall for the firm. On the other, mass shootings may result in calls for regulation of the industry, leading to divestment of firearms stocks in spite of short-term demand. We examine this tension using a market movement event study in the wake of 93 mass shootings in the U.S. between 2009 and 2013. Findings show that stock prices of firearm manufacturers decline after shootings; each event reducing prices between 22.4 and 49.5 basis points, per day. These losses are exacerbated by the presence of a handgun and the number of victims killed, but not affected by the presence of children or location of the event. Finally, we find that these effects are most prevalent in the period 2009-2010 but disappear in later events, indicating that markets appear to have accepted mass shootings as the “new normal.”
It is widely accepted that the information technology (IT) industry has high clockspeed. This very phenomenon has led to IT OEMs finding themselves selling new generation models only to be left holding returned merchandise from older generations. Similarly, customers who migrate to newer generations of products experience uncertainty about how to dispose of older but functional IT equipment. Online liquidation markets have emerged to address these needs by finding ways to resell this equipment. On these liquidation markets, sellers of out-of-date or lightly used durable items like computers and tablets can transact with buyers interested in these products at discounted prices, without needing to alter the state/quality of the product. There is limited understanding of how these markets function and how they may be designed to increase their effectiveness. We report on a unique opportunity for a field experiment that was conducted through the co-operation of a large liquidation company (wholesale liquidator) for IT equipment in the United States. With the specific intention of understanding the design of these liquidation auctions, the research site allowed us to conduct a field experiment on their auction platform for different categories of iPad tablets. By manipulating auction starting prices, we are able to provide insight into the effect of starting prices on the final recovery rates of the returned IT products, and find evidence of cross-product dependencies. To the extent that efficient and viable liquidation markets have ecological and market value, our work provides insights into how sellers may, through the adjustment of starting prices, increase their recovery rates from online auctions.
The software development field has inherently been identified with two field-level institutional logics: logic of the profession and logic of the markets. Traditionally, information systems development methodologies (ISD) have been utilized to reconcile the competing demands from these two logics. In this paper, we study how these two logics manifest in a platform-based software ecosystem, where significant entrepreneurial opportunities are created for independent third-party app developers (indies). Specifically, we study how indie developers manage the two logics on the iOS platform ecosystem, under the influence of the platform owner Apple. We first identify practices of indie developers consistent with the two field logics across three entrepreneurial domains: app ideation, execution and marketing. Second, we identify areas where the two field logics may be in conflict as well as in coexistence. We show that indie developers enact logic conflict through disagreement and denunciation of the opposing logic. When logics that are inherently opposed appear to coexist, we investigate how app developers manage these opposing demands through a process that we term logic synthesis. Using a grounded theory approach, we propose a model of field-level market and professional logics operating in the mobile app platform ecosystem and the practices reflecting such logics within the indie developer community. Our work contributes to the growing literature on platform ecosystems and the processes adopted by third-party app developers in such ecosystems, in addition to furthering the study of institutional logics in technology contexts.
Although the adoption of new technology has received significant attention in management research, investigations of abandonment have lagged. In this study, we examine differences in the rates of abandonment of medical technologies based on whether abandonment occurs in response to the emergence of a superior technology, or in light of new information questioning its efficacy. We link differences in responses to underlying differences in the mission and incentives of organizations. Examining coronary stents across three technological regime changes using a census of approximately 2 million patients admitted to Florida hospitals from 1995-2007, we show meaningful differences across three hospital types: for-profit, not-for-profit, and academic medical centers (AMCs), Results show that for-profit hospitals abandon the earlier generation in favor of a superior technology faster than not-for-profit hospitals, but this is not the case if the efficacy of the technology is questioned. Academic medical centers, however, have the highest rates of abandonment under both triggers. Importantly, we find that organizational factors dominate physician differences as explanatory factors for abandonment. We discuss implications of our study for the role of organizational norms, as related to advancement of best practices in science and pecuniary incentives.
We study the effect of product market competition on the propensity to use corporate venture capital (CVC) as a part of an information technology (IT) firm’s innovation strategy. Using novel measures of product market competition based on product descriptions from firm 10-K statements and accounting for potential endogeneity, we investigate how product market competition during the period 1997-2007 relates to the magnitude of CVC spending. We first find that firms in competitive markets make higher R&D and CVC investments. In addition, we find that increasing product market competition leads to a shift away from internal R&D spending and into CVC. These movements are significantly stronger for technology leaders, i.e. firms with deep patent stocks, in the IT industry. We also find that CVC appears to be an effective way of exploiting external knowledge for technology leaders in the IT-producing industry, but not for technology laggards. CVC investments lead to significantly more patent applications for technology leaders but no appreciable difference for laggards. Our results provide new insights for theories of innovation in competitive, dynamic markets, potentially as part of a portfolio that includes internal R&D as well as open innovation models.
Best Paper Proceedings, AOM Conference 2012, Tech and Innovation Management
Online auction environments provide several sources of information that can be used by bidders to form their bids. One such information set that has been relatively understudied in the literature pertains to reference prices available to the bidder from other concurrent and comparable auctions. In this paper, we study how reference prices from such auctions affect bidding behavior on the focal auction. We also study how the impact of these reference prices is moderated by bidder heterogeneity. Bidders are shown to be influenced by two sets of references prices: internal reference prices from their own historical bidding behavior and external reference prices, formed from other open and just-finished auctions relative to the focal auction. We measure bidder heterogeneity using bidder experience and level of participation in concurrent auctions. Our results show that external reference prices are significantly moderated by bidder heterogeneity. In a departure from current work, we use longitudinal data on auctions and bids in the B2B secondary markets, where goods represent salvage or returned items from big-box retailers and bidders are business buyers. The dataset comprises over 4000 auctions collected from a large liquidator firm in North America and is unique in its comprehensiveness. Our work provides theoretical insights that are complementary to the current set of results from B2C auctions as well as managerial implications for auctioneers in the B2B space.
Best Student Paper Finalist, AOM Conference 2013, Operations Management Division
In this paper, we study the impact of increases in media coverage from two sources, newspapers and blogs, on firm founding rates in the context of technology-based entrepreneurship. Although increasing work in information systems has begun to investigate the effect of user generated content on entrepreneurial behavior, limited attention has been devoted to how media affects firm founding or the boundary conditions of such an effect. Arguing for the direct effect of increased discourse in traditional and user-generated media in the IT industry, results suggest that discourse in traditional media and blogs strongly influences IT firm founding rates. We further consider the differential impacts of media discourse on firm founding in different IT sub-sectors, over time, and in different locations. We test our hypotheses using entrepreneurial firm founding data from VentureXpert from 1998-2007, social media data from the three largest blogging platforms, and traditional media coverage from eleven major US newspapers. Our work contributes to a better understanding of the concurrent effects of multiple forms of media on decision-making and adds to the small but emerging literature addressing entrepreneurship-related research questions in IS.
Best Empirical Paper, Entrepreneurship Division, AOM Conference 2012
The procurement of maintenance, repair and operating (MRO) goods has remained a relatively understudied topic in the literature on supply chain and operations management. Though vital cost efficiencies can be extracted from procurement processes by virtue of investments in Internet-based e-procurement systems, there is little empirical work that addresses the manner in which such systems should be deployed within organizations. In this paper, we focus on the role of e-procurement systems in MRO procurement and study two critical aspects of infusion within service organizations. The first dimension, referred to as intensity, captures the depth of e-procurement use within the procurement function in the organization while the second dimension, acceptance, pertains to the breadth of use. We argue that these two dimensions of e-procurement use, and their interaction, will be related to the performance of the MRO procurement process within the organization. Using survey data obtained from 193 service organizations and structural equation modeling techniques, we show that the two infusion dimensions are significantly associated with improved process performance. In addition, we show a substantial substitutive effect between the two use dimensions on performance. Our work has significant implications for managers who seek to gain efficiencies by the deployment of Internet-based technologies within operational processes. Our conceptualization of e-procurement infusion along two dimensions, capturing intensity and acceptance, also provides a more fine-grained analysis of performance benefits accruing from the infusion of information technologies within service organizations.