Sridhar Seshadri

We present a method for forecasting sales using financial market information and test this method on annual data for US public retailers. Our method is motivated by the permanent income hypothesis in economics, which states that the amount of consumer spending and the mix of spending between discretionary and necessity items depend on the returns achieved on equity portfolios held by consumers. Taking as input forecasts from other sources, such as equity analysts or time‐series models, we construct a market‐based forecast by augmenting the input forecast with one additional variable, lagged return on an aggregate financial market index. For this, we develop and estimate a martingale model of joint evolution of sales forecasts and the market index. We show that the market‐based forecast achieves an average 15% reduction in mean absolute percentage error compared with forecasts given by equity analysts at the same time instant on out‐of‐sample data. We extensively analyze the performance improvement using alternative model specifications and statistics. We also show that equity analysts do not incorporate lagged financial market returns in their forecasts. Our model yields correlation coefficients between retail sales and market returns for all firms in the data set. Besides forecasting, these results can be applied in risk management and hedging.

We study the linkages between firm‐level quality initiatives such as quality management systems (QMS) and total quality management (TQM) and output productivity in the Indian auto component industry. We use externally validated quality certification and quality awards as proxies for QMS and TQM, respectively, as it is difficult to directly measure the QMS and TQM efforts of firms. We use an unbalanced panel of 220 firms and a balanced panel of 73 firms from the Indian auto component industry over the period 1993–2006 to study these links. Both parametric as well as non‐parametric approaches are used, as appropriate, to measure the rate of change in productivity and the impact of quality initiatives on productivity change during this period. We determine the proportion of productivity resulting from technical change and relative efficiency change, thus providing insights into the structure of productivity improvements. We find that TQM efforts resulted in a high rate of productivity change (11%) in the award‐winning firms after the award. On the other hand, pre‐certification productivity change due to QMS was 5% and post‐certification change was 3.6%. In the periods prior to certification, productivity change was driven mainly by technical change; whereas the source of productivity change after certification is mixed. However, prior to awards, productivity change was driven mainly by relative efficiency change, whereas post‐award productivity change was due to technical change. The results suggest that management focus on attaining certification did generate conceptual learning (linked to technical change) during the period leading to certification, but these effects were not significant after certification. The results also suggest that the TQM programs generated significant productivity gains in the long run, although setting the associated systems in place did not result in significant productivity change prior to winning awards. Thus, the study provides direct but nuanced evidence linking quality certification as well as the adoption of TQM programs to the associated conceptual and operational learning processes and their impact on the change in productivity.

We study a sourcing problem faced by a firm that seeks to procure a product or a component from a pool of alternative suppliers. The firm has a preference ordering of the suppliers based on factors such as their past performance, quality, service, geographical location, and financial strength, which are commonly included in a supplier scorecard system. Thus, the firm first uses available inventory from supplier 1, if any, then supplier 2, if any, and so on. The suppliers differ in costs and prices. The buyer firm seeks to determine which suppliers to purchase from and in what quantities to maximize its total expected profit subject to the preference ordering constraint. We present the optimal solution to this problem, and show that it has a portfolio structure. It consists of a sub‐set of suppliers that are ordered by their underage and overage costs. This portfolio achieves a substantial profit gain compared to sourcing from a unique supplier. We present an efficient algorithm to compute the optimal solution. Our model applies to component sourcing problems in manufacturing, merchandizing problems in retailing, and capacity reservation problems in services.

We consider a two‐echelon supply chain with a manufacturer supplying to multiple downstream retailers engaged in differentiated Cournot competition. Each retailer has private information about uncertain demand. The manufacturer is the Stackelberg leader who sets the contract terms with the retailers, and benefits from retailers sharing their private information. When all retailers are given the same wholesale price, truthful information sharing is not an equilibrium outcome. We propose two variants of differential pricing mechanisms that induce truthful information sharing by all retailers. The first variant rewards a retailer for providing optimistic information and achieves truthful information sharing as a unique equilibrium. The differential pricing mechanism is optimal in the class of linear‐price, incentive‐compatible, direct mechanisms. The second variant, which incorporates provision for a fixed payment in addition to wholesale prices, preserves all the equilibrium properties of the first variant and additionally “nearly coordinates” the supply chain. Our analysis of differential pricing with a fixed payment provides interesting observations regarding the relationship between product substitutability, number of retailers, information precision, and market power. As products become closer substitutes and/or number of retailers increase, the manufacturer's market power increases, enabling her to extract a larger fraction of the supply chain surplus.