Empirical and Experimental Methods

The nature of supply chain initiatives affect a range of cost components and could generate various revenue opportunities. Inventory, forming one of the largest components of current assets, is often the focal point. It is thus imperative to explore and test the quantitative effects of SCM initiatives. For this purpose, we employ the gamut of empirical methods - taking both primary and secondary data into account. Some relevant settings:

Stock market and corporate value:
Stock prices react swiftly to supply chain events: a factory flooding, failed international joint ventures, excess inventory, recalls, or product rumors on the other side of the world. Which supply chain events matter to shareholders  in the short run and on a long-term basis?  

As one of the largest components of current assets (some 20%!) with its effects on costs of goods sold - is the focus of many supply chain finance initiatives; so are safety stocks. To what extent does better inventory management lead to higher shareholder value? What external (macroeconomic) factors influence inventory and drives performance?

Behavioral operations and laboratory experiments:
Much time in university is devoted to quantitative models searching for optimal solutions (e.g., forecasting, newsvendor). However, it is observed that decision makers systematically deviate from profit maximizing solutions! Why do decision makers depart from optimal normative solutions? To what extent do overconfidence, bounded rationality, ethicality, or culture influence decisions? How can we improve decision-making processes?

Supply Chain Collaboration in emerging countries: 

Companies that succeed in China succeed for similar reasons - however, every company that fails, fails in its own way (e.g., Google, Best Buy, eBay). Aligning the supply chain can be challenging when ‘navigating through unchartered waters’. Why do big (and small) American and European businesses fail (or succeed) in Mainland China? What are the promoting and hindering factors (related to supply chain decisions) doing business in emerging economies?

Exemplary publications

  • Sachs, A. L., & Minner, S. (2014), The data-driven newsvendor with censored demand observations. International Journal of Production Economics 149: 28-36.