Research Paper Series

  • Title
  • Author(s)


Departments: Information Systems and Operations Management, GREGHEC (CNRS)

Problem definition: Process innovation is commonly claimed to be a major source of competitive advantage for firms. Despite this perceived influence it has received substantially less attention than product innovation and much uncertainty remains about its true association with firm performance. We investigate the relationship between a pharmaceutical manufacturing firm's process-innovation portfolio and its economic performance.Academic/Practical relevance: Our study uniquely conducts a multi-dimensional evaluation of a firm's portfolio of process innovations at the product level. This allows a quantitative evaluation of both the relative benefit of the different dimensions of a portfolio as well as the potential complementarities between these.Methodology: Through a collaboration with expert patent attorneys we develop a unique longitudinal dataset that combines secondary data and evaluations of a firm's portfolio of process patents along three key dimensions: novelty, scope, and locus. We conduct econometric analyses for a large-scale sample of drugs open to competition from generics, where process innovation is the main source of competitive advantage.Results: We find a positive association between overall process innovation and firm performance. When differentiating between dimensions of process innovation, results further suggest that high novelty is beneficial, and complemented by a broad scope, but only for patents applying to the later phase of the pharmaceutical manufacturing process.Managerial Implications: Our results provide important practical insights that can inform process-related R&D investments in the pharmaceutical sector. In particular, it may not be economically beneficial to invest in high-novelty process innovations in early production stages, which are characterized by numerous opportunities to innovate with potentially higher but less predictable economic payoffs. On the other hand, at later stages of the production process, where the opportunities to innovate are less numerous with potentially lower but more predictable economic payoffs, portfolios that are jointly characterized by high novelty and high scope could be more valuable.


Departments: Information Systems and Operations Management

Problem definition: Contrary to classic applications of matching theory, in most contemporary on-demand service platforms, matches can not be enforced because workers are flexible – they choose their tasks. Such flexibility makes it difficult to manage workers while keeping customers satisfied. We build a framework to compare platform matching policies with less flexible and more flexible workers, and empirically quantify by how much worker flexibility hurts customer satisfaction and customer equity.Academic/Practical relevance: In academic literature, there is no established framework that allows for the comparison of matching policies in on-demand platforms. Further, the link between worker flexibility and customer satisfaction is understudied.Methodology: We propose a tripartite framework for empirical evaluation and comparison of the operational policies with different degrees of worker flexibility. Step 1: Predictive modeling of customer satisfaction based on estimation of individual unobservable characteristics: customer difficulty and worker ability (item-response theory model). Step 2: Evaluation of the effect of matching policy (under a given level of flexibility) on customer satisfaction (bipartite matching). Step 3: Quantification of the associated monetary impact (customer lifetime value model).Results: We apply our framework to the dataset of one of the world's largest on-demand platforms for residential cleanings. We find that customer difficulty and cleaner ability are good predictors of customer satisfaction. Granting full flexibility to workers reduces customer satisfaction by 3% and customer lifetime revenue by 0.2%. We propose a family of matching policies that provide sufficient flexibility to workers, while alleviating 75% of the detrimental effect of worker flexibility on customer satisfaction.Managerial implications: Our results suggest that, in platforms with flexible workforce, the presence of worker and customer heterogeneity reduces customer satisfaction through matching inefficiency. Our empirical framework helps practitioners to decide on the right level of worker flexibility and the means for achieving it.

Keywords: workforce flexibility, decentralization, customer satisfaction, service operations, labor management, labor platforms, customer relationship management, business analytics


Departments: Information Systems and Operations Management, GREGHEC (CNRS)

We examine the impact of a new mobile-based, dockless bike-sharing service on public transportation. In contrast to traditional rental bikes that are parked at fixed stations, the dockless bikes can be picked up and returned at literally anywhere. This dockless feature of the shared bikes likely provides a solution to the last mile problem, potentially making it a complement to public transportation. Assembling a unique panel data of shared-bike rides and subway traffic, we estimate the relationship between shared-bike ridership and public transportation. Our results show that increases in shared-bike rides lead to increases in subway traffic. This positive effect is stronger for peak hours during weekdays and non-peak hours during weekends. We argue this effect is most likely driven by shared bikes promoting public transportation use and substituting for private cars (substitution effect) and also stimulating new travel (stimulating effect). Overall, we find that dockless shared bikes, in contrast to most of the other sharing economy phenomenon, acts as a complement rather than a substitute for public transportation. In addition, increased use of dockless shared bikes has a positive societal impact, leading to less urban congestion and better environmental protection.

Keywords: bike-sharing, public transportation, complement, last mile problem

  • MOSI-2018-1310
  • Practices of Distributed Knowledge Collaboration
  • S. KUDARAVALLI, Samer FARAJ

Departments: Information Systems and Operations Management, GREGHEC (CNRS)

  • MOSI-2018-1309
  • Task Novelty and Knowledge Transformation Processes in Distributed Work
  • S. KUDARAVALLI, S FARAJ

Departments: Information Systems and Operations Management, GREGHEC (CNRS)


Departments: Information Systems and Operations Management

Automakers such as Toyota and GM were recently caught by the U.S. regulator for deliberately hiding product defects in an attempt to avoid massive recalls. Interestingly, regulators in the U.S. and U.K. employ different policies in informing consumers about potential defects: The U.S. regulator publicly announces all on-going investigations of potential defects to provide consumers with early information, whereas the U.K. regulator does not. To understand how these different announcement policies may affect cover-up decisions of automakers, we model the strategic interaction between a manufacturer and a regulator. We find that, under both countries' policies, the manufacturer has an incentive to cover up a potential defect when there is a high chance that the defect indeed exists and it may inflict only moderate harm. However, only under the U.S. policy does the manufacturer have an incentive to cover up a potential defect with significant harm, if there is only a moderate chance that the defect exists. We show that the U.S policy generates higher social welfare only for very serious issues for which both the expected harm and recall cost are very high and the defect is likely to exist. We make four policy recommendations that could help mitigate manufacturers' cover-ups, including a hybrid policy in which the regulator conducts a confidential investigation of a potential defect only when it may inflict significant harm.

Keywords: product recalls, automotive industry, socially responsible operations, public policy


Departments: Information Systems and Operations Management, GREGHEC (CNRS)

We examine empirically how different information types and information channels affect both the intention and the decision to adopt photovoltaic (PV) technology as affected by adoption stage. Analyzing data on a large European utility’s current and potential clients reveals how the effects of various drivers of adoption can change across phases of the adoption process. Our results challenge the common wisdom that information necessarily and homogeneously supports innovation adoption; instead, they strongly support the hypothesis that information types and channels have distinct effects on adoption rates. These results also highlight that, throughout the adoption process, the value of information changes. In addition, we clarify the effects of economic incentives on both the intention to adopt PV technology and actual adoption behavior. Our findings have critical implications for policy makers and for any technology manufacturing company that must optimize its marketing strategy and distribution channels to promote renewable energy systems.

Keywords: innovation adoption; renewable energy; information characteristics; empirical studies


Departments: Information Systems and Operations Management, GREGHEC (CNRS)

Research has suggested that firms may benefit from price uncertainty - about input commodities - because it creates an "option value". We use a stylized mathematical model to explore and generalize this claim and to specify its implications for firms' investment decisions under various setups. In particular, we study firms' motivation for investing in such risk management measures as financial hedging (FH) and technology improvement (TI): technology changes that result in less consumption of an input commodity, fewer waste products and emissions, and lower production costs. We derive a simple expression that explicitly quantities firm's attitude toward input-price risk by considering the firm's (positive or negative) risk premium (i.e., what it would pay to "lock in" the unit input price at its mean) and linking that premium to various firm and industry-level characteristics. Also, we examine the comparative risk management advantages of TI and FH and characterize conditions under which these strategies are complements or substitutes. We find that although input-price uncertainty may be beneficial even for risk-averse firms, they can benefit from investing in risk reduction measures (e.g., TI, FH) because they could increase the option value of that uncertainty. A firm's ability to adjust its price in response to both market competition and input-price variation mediates the benefit of risk-reducing measures and also affects the two strategies' complementarity.

Keywords: Risk Management, Risk Exposure, Technology Improvement, Financial Hedging


Departments: Information Systems and Operations Management, GREGHEC (CNRS)

This paper examines how a restaurant’s online review ratings affect consumers to endorse deal vouchers sold by the restaurant via social media before they redeem the vouchers. While the effect of the average of review ratings is straightforward, we focus on examining how the effect is moderated by the dispersion of review ratings and the discount threshold set for the group-buying deals. A comprehensive literature review suggests that a large rating dispersion can deliver two different messages to consumers (uncertainty in product quality and uniqueness of product taste) and thus may either positively or negatively moderate the effect of average rating on social media endorsement. Discount threshold may serve as a quality signal, reinforcing the effect of average rating. The empirical results show that the effect of average rating is greater when review ratings are more dispersed and discount threshold is relatively large. The findings generate important managerial and research implications.

Keywords: social media endorsement, online reviews, average rating, dispersion of review ratings, discount threshold


Departments: Information Systems and Operations Management, GREGHEC (CNRS)

Energy efficiency projects are often executed by specialized entities, namely energy service companies (ESCOs). A typical ESCO's core business is conducted using performance-based contracts, whereby payment terms depend on the energy savings achieved. Despite their success in public, commercial, and industrial sectors, ESCOs in the residential sector are involved in fewer projects and face several challenges. First, an energy efficiency project often leads to changed consumption behavior; hence it is more difficult to evaluate the energy savings that are due to the project itself. The second challenge is that residential clients are more risk averse and, thus, less willing to contract for projects whose outcomes are uncertain. Third, a lack of monitoring protocols leads to ESCO's moral hazard problems. This paper studies ESCO contract design issues, focusing primarily on the residential market for energy efficiency. As opposed to other sectors, coordinating contracts do not exist. We show, however, that simple piecewise linear contracts work reasonably well. To improve their profitability, ESCOs can reduce uncertainty about the technology employed and/or develop ways of verifying post-project energy efficiency. Since policy makers are understandably keen to promote energy efficiency, we show also how regulations and monetary incentives can reduce inefficiencies in ESCOs' relationships and thereby maximize environmental benefits

Keywords: Sustainable Energy, Energy Efficiency, Performance-Based Contracts, Double Moral Hazard


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