Showing papers by "Jan A. Van Mieghem published in 2011"
TL;DR: In this article, a dynamic decision support model that augments the classic inventory planning model with additional clickstream state variables is introduced. But the model is limited to online clickstream and offline purchasing data.
Abstract: We consider firms that feature their products on the Internet but take orders offline. Click and order data are disjoint on such non-transactional websites and their matching is error-prone. Yet, their time separation may allow the firm to react and improve its tactical planning. We introduce a dynamic decision support model that augments the classic inventory planning model with additional clickstream state variables. Using a novel data set of matched online clickstream and offline purchasing data, we identify statistically significant clickstream variables and empirically investigate the value of clickstream tracking on non-transactional websites to improve inventory management. We show that the noisy clickstream data is statistically significant to predict the propensity, amount, and timing of offline orders. A counterfactual analysis shows that using the demand information extracted from the clickstream data can reduce the inventory holding and backordering cost by 3% to 5% in our data set.
70 citations
TL;DR: In this paper, the authors give an overview of risk management and of the techniques that operations managers can use to mitigate risks using operational instruments such as reserves and redundancy, diversification and pooling, risk sharing and transfer, and reducing or eliminating root causes of risk.
Abstract: This chapter, which is based on Chapter 9 in (18), aims to give an introduction and overview of risk management and of the techniques that operations managers can use to mitigate risks. We start the next section by describing the concept of risk management and viewing it as an ongoing 4-step process and integral part of operations strategy. We distinguish operational from financial risk. In section 3, we identify the various operational risks that companies are exposed to. Then we review methodologies to assess and value those risks both qualitatively (using subjective risk maps) and quantitatively (using risk preference functions and risk metrics). The goal of risk assessment is to improve how we react to risk and to proactively reduce our exposure to it. In section 5, we review tactical risk decisions, including risk discovery and risk recovery. The remaining sections of the chapter illustrates strategic risk mitigation, i.e., how operations can be structured to mitigate specific risks. Hedging refers to any action taken to mitigate a particular risk exposure; operational hedging uses operational instruments. Section 7 posits that there are four generic strategies to mitigate risk using operational instruments: 1) reserves and redundancy; 2) diversification and pooling; 3) risk sharing and transfer; and 4) reducing or eliminating root causes of risk. Section 8 reviews financial hedging of operational risk using options and derivatives. Section 9 illustrates how operational hedging can be tailored to the specific operations strategy of the form using techniques such as: tailored redundancy, dynamic pooling with allocation exibility, chaining, and multi-sourcing. Section 10 finishes the chapter by summarizing some guidelines for operational risk management.
31 citations