Cost Analysis of Calcium in Store Brand versus National Brand Grocery Products

Objective: This study was to determine if calcium fortification yields a higher price per serving in grocery store products. Researchers compared store brand to national brand grocery products in relation to cost in order to examine if calcium values were similar between store brand and national brand products. Methods: A total of 112 store brand and 211 national brand grocery products were collected from three low (national chain store), middle and high priced (Virginia and North Carolina regional store) grocery venues. Products were compared using price and calcium percentage per serving. ANOVA was used to determine between store brand and national brand for price per serving and calcium content, and between grocery venues. Results: National brand fortified products had a significantly lower mean price per serving when compared to national brand non-fortified products (p = 0.0002). There was no statistical difference between store brand fortified and non-fortified products (p = 0.9256). Low priced store brand products had the lowest mean price per serving ($0.34 ±0.24). Conclusions: This study found store brand products have similar calcium content as national brand products. Product cost was lower at low priced store compared to middle and high priced stores.     

How does local partners network embeddedness affect international joint venture survival in different subnational contexts?

Do local partners' network attributes affect the survival of high-tech international joint ventures (IJV)? How does the effect of network attributes vary in different subnational institutional environments? While the classic economic explanation for IJV formation and subsequent performance draws from the resource-based view (RBV), we add the relational dimension to explain that IJV survival may be affected by local partners’ relation-specific assets within the local network. We test the effect of the local partners’ network attributes as calculated by UCINET (centrality, network status, and structural hole position) on IJV survival. We additionally assert that this relationship is moderated by subnational institutional heterogeneity. Using our sample of 125 IJV dyadic pairs of US multinational enterprises (MNEs) operating in high-tech industries and their local partners in China, we find partial support for our claims.     

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.     

Does educational diversity of managers matter for the performance of team‐managed funds?

We study the effect of the educational diversity of managers on the performance of team‐managed mutual funds using a large sample of U.S. equity funds from 1994 to 2013. We consider diversity in terms of both final educational degree and field of educational specialisation. We find that, in general, both types of diversity have a positive impact on fund performance, and our results are robust over a wide range of performance metrics and changes in market conditions.     

The US financial crisis and corporate dividend reactions: for better or for worse?

Review of Quantitative Finance and Accounting - We examine how changes in dividend policy in 2008 as the financial crisis was unfolding influenced firm risk-adjusted returns in the following years....     

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.     

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.