Thirsty in an Ocean of Data? Pitfalls and Practical Strategies When Partnering With Industry on Big Data Supply Chain Research

Increased volume, velocity, and variety of data provides new opportunities for businesses to take advantage of data science techniques, predictive analytics, and big data. However, firms are struggling to make use of their disjointed and unintegrated data streams. Despite this, academics with the analytic tools and training to pursue such research often face difficulty gaining access to corporate data. We explore the divergent goals of practitioners and academics and how the gap that exists between the communities can be overcome to derive mutual value from big data. We describe a practical roadmap for collaboration between academics and practitioners pursuing big data research. Then we detail a case example of how, by following this roadmap, researchers can provide insight to a firm on a specific supply chain problem while developing a replicable template for effective analysis of big data. In our case study, we demonstrate the value of effectively pairing management theory with big data exploration, describe unique challenges involved in big data research, and develop a novel and replicable hierarchical regression‐based process for analyzing big data.     

Sessions organized by the Industrial Organization Society at the ASSA Meetings,Washington D.C., January 6–8, 1995

Sessions organized by the Industrial Organization Society at the ASSA Meetings, Washington D.C., January 6–8, 1995     

Do Financial Institutions Matter?

In standard asset pricing theory, investors are assumed to invest directly in financial markets. The role of financial institutions is ignored. The focus in corporate finance is on agency problems. How do you ensure that managers act in shareholders' interests? There is an inconsistency in assuming that when you give your money to a financial institution there is no agency problem, but when you give it to a firm there is. It is argued that both areas need to take proper account of the role of financial institutions and markets. Appropriate concepts for analyzing particular situations should be used.     

Multiproduct Outputs and Scale Economies in Electric Power Production: Some New Estimates

The present study offers an argument, through a technical exposition, which suggests that there are cost differences inherent in serving different types of buyers in the electric utilities industry. To this end, we employ a translog joint cost function (for electricity production) with three outputs, which allows for the examination of the cost differences between wholesale and retail trade for vertically integrated, investor-owned companies in the industry. The regression estimates suggest different costs at the means, however the estimated marginal cost curve for wholesale power is not as robust as those for low-voltage and industrial power.