Nikolay Osadchiy is an Associate Professor of Information Systems & Operations Management at Emory University's Goizueta Business School. His research interests are in supply chain management, where he studies how supply networks affect risk and operational performance, and in revenue management where he studies the impact of behavioral regularities on pricing. He has published in the leading academic journals including Management Science, Operations Research, and Production and Operations Management. He serves as a Senior Editor at Production and Operations Management.
Nikolay has taught an elective Supply Chain Management and the core Process and Systems Management courses in the BBA, MBA, and EvMBA programs, and an Operations Management seminar in the Doctoral program. He holds a PhD in Operations Management from the New York University Stern School of Business and MS in Applied Mathematics and Physics from Moscow Institute of Physics and Technology.
PhD in Operations ManagementNew York University Leonard N. Stern School of Business
MPhil in Operations ManagementNew York University Leonard N. Stern School of Business
MS in Applied Mathematics and PhysicsMoscow Institute of Physics and Technology
The Right Way to Mix and Match Your Customers
“The costs of demand variability can put you out of business.” That blunt assessment, recently offered to us by the director of sales and operations planning at a Fortune 500 company, reflects what managers already know: Peaks in demand can drive high overtime costs, stockouts, and lost sales, while slowdowns leave capacity idle and increase excess inventory. The impact on customer service levels — not to mention the bottom line — can be significant. But how can companies best manage this variability, especially when deciding which potential new customers to target?
The Bullwhip Effect in Supply Networks
We offer a new network perspective on one of the central topics in operations management—the bullwhip effect (BWE). The topic has both practical and scholarly implications. We start with an observation: the variability of orders placed to suppliers is larger than the variability of sales to customers for most firms, yet the aggregate demand variability felt by suppliers upstream does not amplify commensurably. We hypothesize that changes to the supplier’s customer base can smooth out its aggregate demand. We test the hypothesis with a data set that tracks the evolution of supply relationships over time. We show that the effect of customer base management extends beyond the statistical benefits of aggregation. In particular, both the formation and the dissolution of customer-supplier relationships are associated with the smoothing of the aggregate demand experienced by suppliers. This provides fresh insight into how firms may leverage their customer-supplier relationships to mitigate the impact of the BWE.
Supply Network Drivers of Risk and Performance
This chapter reviews historical and contemporary research in economics, operations management, and finance that adopts a network perspective for modeling interactions between agents. It argues that incorporating extended network characteristics in the analysis can yield unique insights compared to the analysis done at the level of dyads or local neighborhoods. The chapter explains how new network-based models contribute to the academic debate and advance our understanding of supply network drivers of performance and risk. This includes a discussion on the structural configuration of a firm’s interconnected portfolio of upstream supplier and downstream customer relationships and its role in influencing financial and operational performance as well as its innovation.
Systematic Risk in Supply Chain Networks
Industrial production output is generally correlated with the state of the economy. Nonetheless, during times of economic downturn, some industries take the biggest hit, whereas at times of economic boom they reap most benefits. To provide insight into this phenomenon, we map supply networks of industries and firms and investigate how the supply network structure mediates the effect of economy on industry or firm sales...
Behavioral Anomalies in Consumer Wait-or-Buy Decisions and Their Implications for Markdown Management
A decision to buy an item at a regular price or wait for a possible markdown involves a multi-dimensional trade-off between the value of the item, the delay in getting it, the likelihood of getting it and the magnitude of the price discount. Such trade-offs are prone to behavioral anomalies by which human decision makers deviate from the discounted expected utility model.
Are Patients Patient? The Role of Time to Appointment in Patient Flow
The current state of outpatient healthcare delivery is characterized by capacity shortages and long waits for appointments. Yet a substantial fraction of valuable doctors’ capacity is wasted due to no-shows. In this paper, we examine the effect of wait to appointment on patient flow, specifically on a patient’s decision to schedule an appointment, and subsequently arrive to it. These two decisions may be dependent, because appointments are more likely to be scheduled by patients who are more patient and are thereby more likely to show-up. To estimate the effect of wait on these two decisions, we introduce the willingness to wait (WTW), an unobservable variable that affects both bookings and arrivals for appointments. Using data from a large healthcare system, we estimate WTW with a state of the art non-parametric method. The WTW in turn allows us to estimate the effect of wait on no-shows. We observe that the effect of increased wait on the likelihood of no-show is disproportionately greater among patients with low WTW. Thus, although reducing the wait to appointment will enable a provider to capture more patient bookings, the effects of wait time on capacity utilization can be non-monotone. Contrary to the previously reported findings, our results suggest that increasing wait can sometimes be beneficial for reducing no-shows.
Sales forecasting with financial indicators and experts' input
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.
Selling with binding reservations in the presence of strategic consumers
We analyze a revenue management problem in which a seller endowed with an initial inventory operates a selling with binding reservations scheme. Upon arrival, each consumer, trying to maximize his own utility, must decide either to buy at the full price and get the item immediately or to place a nonwithdrawable reservation at a discount price and wait until the end of the sales season where the leftover units are allocated according to first-come-first-serve priority...