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.     

Three Pillars of Conventional Wisdom

This paper considers three pillars of contemporary economic wisdom that form part of the so-called 'Washington consensus': that free markets work best; that price stability is a good thing; and that deregulated financial markets work best. We argue that these propositions apply in certain circumstances, but do not have general validity. After discussing the circumstances in which these propositions do not hold we suggest how the conventional policy wisdom should be revised.     

Second contribution to the ENE critique: Reply to Davidson,part 1

On first encounter, the ergodic/nonergodic (ENE) approach has apparent plausibility. Although concerned by some of its problems for many years, it was only after more concentrated reflection on both its parts and their combinations that I became aware of its manifold deficiencies, some of which I outlined in my previous critique (O’Donnell, 2014 ———. “A Critique of the Ergodic/Nonergodic Approach to Uncertainty.” Journal of Post Keynesian Economics, 2014, 37 (2), 187–209.[Web of Science ®] , [Google Scholar]). In this paper, facilitated by Davidson’s (2015b ———. “A Rejoinder to O’Donnell’s Critique of the Ergodic/Nonergodic Explanation of Keynes’s Concept of Uncertainty.” Journal of Post Keynesian Economics, 2015b, 38, 1–18.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) rejoinder, these criticisms are deepened, broadened, and strengthened. Because the debate deals with fundamental matters in several disciplines, a considerable amount of investigation, unpacking, and logical dissection is required to clarify the argumentation beneath the compressed and seemingly smooth surface of the ENE position. For this reason, my reply is divided into two parts. This contribution primarily examines the central role of framing in ENE arguments, and clarifies the various misunderstandings and misrepresentations to which it leads. The subsequent contribution provides more detailed discussion of mathematical, stochastic, and methodological issues.     

Does Skill Content Explain Total Trade and Intra‐Industry Trade?*

This study compares the results of skill content tests for types of trade flows under alternative assumptions about the technologies used to produce imports and exports. For trade between high‐ and middle‐income countries, we show that the match between the actual skill content of trade and that predicted by endowments in a Heckscher–Ohlin–Vanek framework improves substantially if technological heterogeneity across countries is allowed for and if the factor content of intra‐industry trade is included with that of inter‐industry trade. Endowment differences are important in explaining net trade and vertical intra‐industry trade, but not horizontal intra‐industry trade.     

Strange bed(side) fellows physician-finance collaboration

Financial and physician leaders need alignment, cooperation, and goodwill based on trust and transparency to cope with the challenges facing the healthcare industry. Organizational silos need to be broken down to encourage communication and cooperation between financial and clinical leaders. Incentive compensation plans should be designed to reward meeting team goals rather than individual accomplishment. Cross-discipline communication skills are crucial for leaders at all levels throughout the organization.     

An overview of probability,expectations, uncertainty and rationality in Keynes's conceptual framework 1

Keynes's writings on the cognate topics of probability, expectations, uncertainty and rationality exhibit considerable complexity. This paper seeks to provide a clarifying overview of his position on these topics, both in his main philosophical workThe treatise on probability, and his main economic workThe general theory. It is argued that the most useful approach for understanding the deeper structure of Keynes's thought in each work is by means of a two-dimensional, two-domain analysis.Such an analysis helps demonstrate some of the ways in which the conceptual framework of The treatise on probability provides an essential part of the philosophical foundations of The general theory, while at the same time recognizing some of the key differences between the two works. It also illuminates Keynes's non-neoclassical theorization of rationality, and his path-breaking attempt to develop a theory of rationality under irreducible uncertainty.