Karan Girotra

Valuing R&D Projects in a Portfolio: Evidence from the Pharmaceutical Industry

Understanding the value of a product development project is central to a firms choice of project portfolio. The value of a project to a firm depends not only on its properties but also on the other projects being developed by the firm. This is due to interactions with the other projects that address the same consumer need and require the same development resources. In this study, we empirically investigate the structure and significance of these portfolio-level project interactions. Using a self-developed pharmaceutical industry data set, we conduct an event study around the failure of phase III clinical trials and their effect on the market valuation of the firm. The study exploits the natural experiment of a product development failure to give us a measure of the value of a drug development project to a firm. We then explain the variance in the value of projects based on interactions with other projects in the firms portfolio. We find that the presence of other projects targeting the same market and a build-up of projects that require the same development resources reduce the value of a development project. In addition to providing evidence on the significance and structure of these portfolio-level project interactions, the empirical model estimated in this paper also provides a data-driven approach to valuing projects that may be relevant to licensing transactions.

Electric Vehicles with a Battery Switching Station: Adoption and Environmental Impact

The transportation sectors carbon footprint and dependence on oil are of deep concern to policy makers in many countries. Use of all-electric drive trains is arguably the most realistic medium-term solution to address these concerns. However, motorist anxiety induced by an electric vehicles limited range and high battery cost have constrained consumer adoption. A novel switching-station-based solution is touted as a promising remedy. Vehicles use standardized batteries that, when depleted, can be switched for fully charged batteries at switching stations, and motorists only pay for battery use. We build a model that highlights the key mechanisms driving adoption and use of electric vehicles in this new switching-station-based electric vehicle system and contrast it with conventional electric vehicles. Our model employs results from repairable item inventory theory to capture switching-station operation; we embed this model in a behavioral model of motorist use and adoption. Switching-station systems effectively transfer range risk from motorists to the station operator, who, through statistical economies of scale, can better manage it. We find that this transfer of risk can lead to higher electric vehicle adoption than in a conventional system, but it also encourages more driving than a conventional system does. We calibrate our models with motorist behavior data, electric vehicle technology data, operation costs, and emissions data to estimate the relative effectiveness of the two systems under the status quo and other plausible future scenarios. We find that the system that is more effective at reducing emissions is often less effective at reducing oil dependence, and the misalignment between the two objectives is most severe when the energy mix is coal heavy and has advanced battery technology. Increases in gasoline prices by imposition of taxes, for instance are much more effective in reducing carbon emissions, whereas battery-price-reducing policy interventions are more effective for reducing oil dependence. Taken together, our results help a policy maker identify the superior system for achieving the desired objectives. They also highlight that policy makers should not conflate the dual objectives of oil dependence and emissions reductions as the preferred system, and the policy interventions that further that system may be different for the two objectives. This paper was accepted by Yossi Aviv, operations management.

OM Forum---Business Model Innovation for Sustainability

A systematic approach to innovating business models can help identify new business models that encourage sustainable use of products and services, or facilitate wider adoption of new environmentally friendly technologies. This paper provides a brief summary of a conceptual framework that we have developed to systematize the study and identification of new business models. Our approach advocates that the key to identifying new business models is understanding the context of decision making in existing models and the associated inefficiencies. We propose a three-step approach: First, existing business models must be audited for identifying information and incentive misalignment inefficiencies that destroy value. Next, new business models can be identified by changing the context of the decision associated with the most consequential of these inefficiencies. We conjecture that four elements of the decision context are most significant: WHAT decisions are made, WHEN they are made, WHO makes them, and WHY they are made. We provide a set of idea triggers to stimulate brainstorming of new business models by changing one of these four Ws. Finally, we advise that generated business models should be analyzed and experimented with to identify the most promising ones. We close the paper by describing the design of a pedagogical program based on this framework.

Managing Global Sourcing: Inventory Performance

The use of global suppliers has increased considerably over the last three decades. Operations management theory establishes that global sourcing requires more units of inventory, but since these units are often procured at a lower cost from global suppliers the capital invested in inventory and the consequent financial burden may increase or decrease with global sourcing. This study provides rigorous firm-level empirical evidence that links the global sourcing practices of public U.S. firms and their inventory investments. We process bill of lading manifests customs forms to extract information on over half a million sea shipments from global suppliers to U.S. public firms and link this information with quarterly financial data from the Compustat database. We provide stylized facts on the participation of different firms and sectors in global trade. Using a simultaneous equation model, we find that an increase in global sourcing results in an increase in inventory investment. A 10% shift in sourcing from domestic to global suppliers increases the inventory investment by 8.8% for an average firm in our sample. We also find that increasing the number of suppliers can mitigate this increase in inventory investment: for example, going from single to dual sourcing reduces inventory investment by about 11%. We illustrate the use of our estimates to identify the impact of changing global sourcing strategy on inventory investment and operational performance metrics. This paper was accepted by Martin Lariviere, operations management.

Bike-Share Systems: Accessibility and Availability

The cities of Paris, London, Chicago, and New York (among many others) have set up largescale bike-share systems to facilitate the use of bicycles for urban commuting. This paper estimates the impact on bike-share ridership of two facets of system performance: accessibility (how far the user must walk to reach stations) and bike-availability (the likelihood of finding a bicycle). Our analysis is based on a structural demand model for spatially differentiated products that includes distinct mechanisms for the short and long-term effects of bike-availability (via lost sales and increased user-interest, respectively). The bike-share context, and the distinct mechanisms require us to go beyond past work in incorporating real time changes in product (bike)-availability information, and including much finer data on potential demand sources. These enhancements render traditional estimation methods computationally infeasible; we transform our estimation from the time domain to the “local-stockout- state” domain to address this. Our estimates for the Velib’ bike-share system in Paris suggest that a 10% increase in station density would increase ridership by 5.09% (±0.45%), while a 10% increase in bike-availability would increase ridership by 12.29% (±0.39%), three-fourths of which comes from fewer lost-sales, and the rest from increased user interest. We illustrate the use of our estimates in identifying neighborhoods and times to target for improvements, and in comparing alternate operational improvements and station networks.

The Benefits of Decentralized Decision-Making in Supply Chains

The inefficiency of decentralized decision-making is one of the most influential findings of the supply chain coordination literature. This paper shows that with the possibility of continuing trade, decentralization can be beneficial in improving supply chain performance. In a supply chain with decentralized decision-making and continuing trade, it is easier to incentivize players to coordinate on efficient actions. There are more gains to be shared from coordination, and by virtue of each player being a smaller influence on the system, any individual player’s opportunism is less of a threat to coordination. These stronger incentives to coordinate manifest themselves in higher profits of supply chains with decentralized decision-making and additional terms of contracting acceptable to all players. Our analysis demonstrates that the widely accepted inefficiency of decentralized decision making is an artifact of the simplifying assumption of one-off trade, and identifies conditions for departures from this result with continuing trade. The newly identified phenomena provide a possible explanation for the paradoxically good performance of very decentralized supply chains seen in emerging market cooperatives, urban logistics, micro-retailing, and other settings.

Supply Networks for Relational Sourcing

Making long-term commitments to exclusive suppliers, or relational sourcing, is critical in industries where quality includes social, ethical, and technical elements concerning which contractual terms would be costly to verify or enforce. This study identifies supplier network topologies that best facilitate such relational sourcing. We consider a brand-owning firm that sources in an ongoing fashion from a general multi-tier network of idiosyncratic suppliers. Alternate network designs are compared in terms of three defining structural properties: network scope, the number of suppliers at each tier in the network; degree of control/delegation, the number of tiers in the network; and network connectivity, the connections between firms located at different tiers. Our analysis reveals that neither network connectivity nor the distribution of costs among suppliers affects the ability to sustain relational sourcing. Networks characterized by more delegation or less scope have the most to gain from relational sourcing, but they are also most vulnerable to exploitation of a relational agreement. We characterize this trade-off and identify preferred network topologies. Our analysis shows that, all else equal, delegation is better than control for products with higher margins, greater sourcing stability, or lower costs of noncompliant quality. Numerical analysis reveals that low-scope networks, too, are preferable for higher-margin products with greater sourcing stability; however, low-scope networks are preferred at higher costs of noncompliant quality. These results are robust to alternate information environments, supplier replaceability and equilibrium concepts.

The Operational Advantages of Threshold Discounting Offers

The authors study threshold discounting, or the practice of offering a discounted-price service if at least a pre-specified number of customers signal interest in it, as pioneered by Groupon. We model a capacity-constrained firm, a random-sized population of strategic customers, a desirable hot period and a less desirable slow period. Compared to a more traditional approach (slow period discounting or closure) threshold discounting has two operational advantages. First, the contingent discount temporally balances demand when the market for the service is large, and reduces supply of the service (preserving higher margins) when the market is small, allowing the firm to respond to the service’s unobserved market potential. Second, activation of the threshold discount signals the market state and the consequent service availability to strategic customers, inducing them into selfselecting the consumption period to one that improves the firm’s capacity utilization. Yet, threshold discounting can be harmful in situations with chronically low demand. In contrast with past work on strategic customers, their presence is advantageous to firms in our context. A calibrated numerical study shows that threshold discounting improves firm profits over a traditional approach by as much as 33% (7% on average); surprisingly, gains are higher in more uncertain markets.

Online Grocery Retail: Revenue Models and Environmental Impact

This paper compares the financial and environmental performance of two revenue models for the online retailing of groceries: the per-order model, where customers pay for each delivery, and the subscription model, where customers pay a set fee and receive free deliveries. We build a stylized model that incorporates (i) customers with ongoing uncertain grocery needs and who choose between shopping offline or online and (ii) an online retailer that makes deliveries through a proprietary distribution network. We find that subscription incentivizes smaller and more frequent grocery orders, which reduces food waste and creates more value for the customer; the result is higher retailer revenues, lower grocery costs, and potentially higher adoption rates. These advantages are countered by greater delivery-related travel and expenses, which are moderated by area geography and routing-related scale economies. Subscription also leads to lower food waste–related emissions but to higher delivery-related emissions. Cet...

Strategic Behavior in Supply Chains: Information Acquisition

Reducing the financial impact of supply–demand mismatches is a central objective of supply chain management. Modern supply chains have multiple independent self-interested actors each with different information about the demand uncertainties facing the supply chain. Strategic behavior by these self-interested actors often enhances the supply–demand mismatches in the supply chain. In this chapter, we present the case of a fashion products supply chain with multiple strategic actors each of which has different information. Traditional contracting strategies in this supply chain lead to excessive supply–demand mismatches. We then propose an alternate contracting strategy. Specifically, we propose that the supply chain starts offering “Advanced Purchase Discounts” in addition to the traditional wholesale price based contracts. We demonstrate that strategic responses to these contracts by agents in the supply chain lead to better information sharing, superior risk bearing, reduced supply–demand mismatches and can lead to Pareto-improving outcomes for all actors in the supply chain. In contrast with conventional wisdom that strategic behavior in the supply chain leads to poorer supply chain performance, our results illustrate that appropriately designed supply chain practices can actually exploit the strategic behavior of actors to improve supply chain performance. We conclude by illustrating the application of the proposed contracts to our motivating example of the fashion products supply chain.