Operations & Supply Chain Management

It is widely accepted that entrepreneurial creation affects destruction, as new and better organizations, technologies and transactions replace old ones. This phenomenon is labeled creative destruction, but it might more accurately be called destructive creation, given the driving role of creation in the process. We reverse the typical causal ordering, and ask whether destruction may drive creation. We argue that economic systems may get stuck in suboptimal equilibria due to path dependence, and that destruction may sweep away this inertia, and open the way for entrepreneurship.

We consider a bandit problem which involves sequential sampling from two populations (arms). Each arm produces a noisy reward realization which depends on an observable random covariate. The goal is to maximize cumulative expected reward. We derive general lower bounds on the performance of any admissible policy, and develop an algorithm whose performance achieves the order of said lower bound up to logarithmic terms. This is done by decomposing the global problem into suitably "localized" bandit problems.

Suresh Sundaresan offers several insights on the development of financial markets in Asia and the Pacific. First, financial market development in the region should take account of the large number of households who are effectively unbanked, given the potential for positive feedback effects between financial markets, economic growth and stability. Second, there is a need for fundamental banking reforms of capital structures and liquidity sources to mitigate bankruptcy risks, as well as the cost to taxpayers of insolvency and bailouts.

We develop a structural demand model that endogenously captures the effect of out-of-stocks on customer choice by simulating a time-varying set of available alternatives. Our estimation method uses store-level data on sales and partial information on product availability. Our model allows for flexible substitution patterns, which are based on utility maximization principles and can accommodate categorical and continuous product characteristics.

Recent years have seen extensive investigation of the information aggregation properties of prediction markets. However, relatively little is known about conditions under which a market will aggregate the private information of rational risk averse traders who optimize their portfolios over time. We consider a market model involving finitely many informed risk-averse traders interacting with a market maker. Our main result identifies a basic smoothness condition on the price in the market that ensures information will be aggregated.

We consider an agent interacting with an unmodeled environment. At each time, the agent makes an observation, takes an action, and incurs a cost. Its actions can influence future observations and costs. The goal is to minimize the long-term average cost. We propose a novel algorithm, known as the active LZ algorithm, for optimal control based on ideas from the Lempel-Ziv scheme for universal data compression and prediction.

Social commerce is an emerging trend in which sellers are connected in online social networks, and where sellers are individuals instead of firms. This paper examines the economic value implications of a social network between sellers in a large online social commerce marketplace. In this marketplace each seller creates his or her own shop, and network ties between sellers are directed hyperlinks between their shops.

We establish that the min-sum message-passing algorithm and its asynchronous variants converge for a large class of unconstrained convex optimization problems, generalizing existing results for pairwise quadratic optimization problems. The main sufficient condition is that of scaled diagonal dominance. This condition is similar to known sufficient conditions for asynchronous convergence of other decentralized optimization algorithms, such as coordinate descent and gradient descent.