Preventives Versus Treatments Redux: Tighter Bounds on Distortions in Innovation Incentives with an Application to the Global Demand for HIV Pharmaceuticals

Kremer and Snyder (Q J Econ 130:1167–1239, 2015) show that demand curves for a preventive and treatment may have different shapes though they target the same disease, biasing the pharmaceutical manufacturer toward developing the lucrative rather than the socially desirable product. This paper tightens the theoretical bounds on the potential deadweight loss from such biases. Using a calibration of the global demand for HIV pharmaceuticals, we demonstrate the dramatically sharper analysis achievable with the new bounds, allowing us to pinpoint potential deadweight loss at 62% of the global gain from curing HIV. We use the calibration to perform policy counterfactuals, assessing welfare effects of government policies such as a subsidy, reference pricing, and price-discrimination ban. The fit of our calibration is good: we find that a hypothetical drug monopolist would price an HIV drug so high that only 4% of the infected population worldwide would purchase, matching actual drug prices and quantities in the early 2000s before subsidies in low-income countries ramped up.     

Blockchain in Additive Manufacturing and its Impact on Supply Chains

Additive manufacturing (AM) appears to be a particularly attractive use case for blockchain. This research combines inductive in‐depth interviews with the Delphi method to explore what potentials blockchain technology in AM creates, which adoption barriers firms need to overcome, and how supply chains will be affected by the integration of these two potentially disruptive technologies. The results suggest opportunities that are related to intellectual property (IP) rights management, the monitoring of printed parts throughout their lifecycle, process improvements, and data security. The most important barriers for blockchain adoption in AM are an absence of blockchain‐skilled specialists on the labor market, missing governance mechanisms, and a lack of firm‐internal technical expertise. By addressing important limitations of AM, blockchain is expected to improve the competitiveness of AM in parts’ production, catalyzing the trend toward more decentralized manufacturing resulting in more agile, resilient, and flexible supply chains and reduced logistics costs. Beyond that, blockchain‐based AM platforms are expected to enhance supply chain visibility, drive supply chain digitalization, support supply chain finance, and contribute to the emergence of shared factory systems.     

Outward foreign direct investment by Polish state-owned multinational enterprises: is ‘stateness’ an asset or a burden?

State-owned enterprises (SOEs) are commonly associated with undue advantages due to preferential treatment by the state. Simultaneously they are often quoted as handicapped given the notorious state interference, management problems and agency tensions. They used to be regarded as a mainly domestic issue but in the context of globalisation and the fact that states enter treaties with new obligations, SOEs’ performance ceased to be solely a domestic problem, increasingly so as state-owned multinational enterprises (SOMNEs) emerge. This article presents the results of research on Polish SOEs’ outward foreign direct investment (OFDI). It offers an overview of overseas activities of nine major Polish firms with a state stake and aims to contribute to the conceptual literature on foreign investments conducted by SOMNEs. We distinguish between FDI by SOMNEs as specific – privileged (facilitated) or discriminated (hampered) – investments subject to the home country’s state power and the host country’s state perception.     

Alliances and the innovation performance of corporate and public research spin-off firms

We explore the innovation performance benefits of alliances for spin-off firms, in particular spin-offs either from other firms or from public research organizations. During the early years of the emerging combinatorial chemistry industry, the industry on which our empirical analysis focuses, spin-offs engaged in alliances with large and established partners, partners of similar type and size, and with public research organizations, often for different reasons. We seek to understand to what extent alliances of spin-offs with other firms (either large- or small- and medium-sized firms) affected their innovation performance and also how this performance may have been affected by their corporate or public research background. We find evidence that in general alliances of spin-offs with other firms, in particular alliances with large firms, increased their innovation performance. Corporate spin-offs that formed alliances with other firms outperformed public research spin-offs with such alliances. This suggests that, in terms of their innovation performance, corporate spin-offs that engaged in alliances with other firms seemed to have benefitted from their prior corporate background. Interestingly, it turns out that the negative impact of alliances on the innovation performance of public research spin-offs was largely affected by their alliances with small- and medium-sized firms.     

Modularization of hybrid censoring schemes and its application to unified progressive hybrid censoring

In this paper, a structural analysis of hybrid censoring models is presented. This new modularization approach to hybrid censoring models enables a convenient derivation of distributional results. For instance, it allows to derive the exact distribution of the MLEs under an exponential assumption for very complex hybrid scenarios. In order to illustrate the benefit of this idea, we apply it to four new unified progressive hybrid censoring schemes. They are extensions of already proposed unified Type-I/II/III/IV hybrid censoring schemes to progressively Type-II censored data. The resulting analysis shows that the modularization approach provides a powerful, efficient, and elegant tool to study even more complex hybrid censoring models.     

A study of the relationships among sensory experience,emotion, and buying behavior in coffeehouse chains

Studies that simultaneously explore the effects of sensory experience on consumer emotions and behavior are rare. This paper builds a model of buying behavior based on sensory experience, 570 valid questionnaires were obtained from coffeehouse customers. Using structural equation modeling and multiple regression analysis, this paper validates the concept model and verifies that sensory experience is a significant antecedent to buying behavior. This study indicates that certain sensory experiences significantly influence emotion. Emotion also plays a mediating role in the relationship between sensory experience and behavioral intentions. The findings are theoretically and practically profound as they address the relationships among sensory experience, consumer emotions, behavioral intentions, and buying behavior, as well as explore how the five senses affect emotions and buying behavior. This paper concludes by indicating managerial implications and research limitations.