Madhu Viswanathan
awesomeprof@ISB
Madhu Viswanathan
ISB, India
I am interested in the nature of inter-firm relationships, organization forms and their effect on various marketing mix elements such as prices and assortments. I have studied questions related to this theme in a variety of industries, such as digital TVs, crop insurance and grocery retail. As an empiricist, I use various econometric techniques with a particular emphasis on structural econometric models to examine these issues.
Savings that Hurt: Production Rationalization and its Effect on Prices
LATEST RESEARCH
Do Activity-Based Incentive Plans Work? Evidence from a Large-Scale Field Experiment
Production rationalization, the process of re-allocating production across facilities so as to reduce total costs, results in firms equating marginal costs across markets. This results in marginal costs, and hence prices, being higher in some markets and lower in others than otherwise would be without production rationalization. The paper also presents empirical evidence on how production rationalization, in the form of fleet re-optimization, affected prices following the US Airways/American Airlines merger.
Activity-based compensation is a common part of many salesforce compensation schemes in practice. Such plans incorporate scores derived from salesperson call reports into incentive compensation along with traditional sales-based incentives. Securing the cooperation of a pharmaceutical firm, we undertook a three-year experiment with three interventions that sequentially added and removed activity-based compensation to salespeople and their managers across 305 sales territories. We find a robust sales gain around 8% from the added incentive pay relative to the baseline. These gains are larger as sales signals become noisier. Surprisingly, these gains accrue even if the added incentive pay is offered only to manager; extending them to salespeople show no additional gain. Managerially, this supports tying incentive compensation to call reports despite the potential for self-serving biases in these measures, particularly when sales signals become noisier.