Global Innovative R&D Offshoring with Heterogeneous Labor: The Role of IPR‐Protection on Technology Transfer and the Brain Drain Effect

Using a North–South framework, this study proposes a theoretical general equilibrium model with multiple Northern firms offshoring innovative R&D to the South. Northern firms vary in their ability to manage Southern researchers, and Southern researchers vary in quality. Southern researchers of higher quality are more productive but also more likely to leave the firm and start a competing firm through imitation of the product. A strengthening of Southern IPR‐protection increases offshoring, global welfare, and innovation while eliminating employment opportunities for skilled Southern researchers. Therefore, stronger Southern IPR‐protection has the potential to contribute to the emigration of highly qualified researchers. The model then predicts the effects of changes to the Northern country as a result of this increased emigration. Increases in Northern technology increase offshoring and innovation while decreasing the amount of technology transferred. The effect of an increase in Northern researcher quality depends on the degree of the increase in productivity as a result of the higher quality workers.     

Analyzing the duration of IPOs from offering to listing using the Cox proportional hazards model

Portuguese Economic Journal - This study examines the duration from the offering to the listing of IPOs issued on the Pakistan Stock Exchange (PSX) during the period lasting from 1995 to 2017....     

Rationalizing forecast inefficiency

We show analysts’ own earnings forecasts predict error in their own forecasts of earnings at other horizons, which we argue provides a measure of the extent to which analysts inefficiently use information. We construct our measure by exploiting two sources of variation in analysts’ incentives: (i) more recent forecasts have greater salience at the time of the earnings release so accuracy incentives are higher (lower) at shorter (longer) forecast horizons and (ii) analysts have greater incentives for optimism (pessimism) at longer (shorter) horizons. Consistent with these incentives affecting the incorporation of information into forecasts, we document (i) current year forecasts underweight (overweight) information in shorter (longer) horizon forecasts and (ii) the mis-weighting is more pronounced when recent news is negative—when analysts have greater (weaker) incentives to incorporate the news into shorter (longer) horizon forecasts. Finally, returns tests suggest that forecasts adjusted for the inefficiency we document better represent market expectations of earnings.

     

The Impact of the Platform Economy on Job Creation

This study analysed the platform economy in terms of time, geography and type of platform, with a view to present estimations on its size in terms of revenues and the number of active workers.     

Understanding Managers’ Reactions to Blockchain Technologies in the Supply Chain: The Reliable and Unbiased Software Agent

Organizations investing in supply chain information systems struggle to ensure successful adoption and implementation. Projects fail because of technical caveats, inability to meet business needs, and poor management of implementation. Implementation of blockchain technologies across a network of supply chain partners is more complex than internally focused technologies. It is necessary for partner firms to implement, contribute, and share information, and employees to actively use the capabilities of the technology to realize potential. Blockchain technologies can substitute for traditional interfirm intermediaries acting as an unbiased software agent embedded in the supply chain network. Understanding managers’ perceptions of and willingness to use blockchain technologies is crucial for successful implementation. Integrating design theory with classic diffusion processes, we conducted a scenario‐based role‐playing experiment with industry professionals to examine managers’ perceptions of blockchain technologies and willingness to use. We find that trustworthiness with regard to competence and perceived distributive justice is the focal drivers of managers’ willingness to use the technology. Additionally, both risk and interactional justice are not drivers of willingness to use blockchain technology despite significant claims to that effect. We provide implications for how managers can leverage these drivers to influence supply chain partners’ willingness to use the technology.     

Assessing ocean temperature’s role in fishery production

Journal of Bioeconomics - Ocean temperatures are increasing. Little work has been done to examine the effects that these changes will have on fishery production. The study at hand seeks to...     

EMPLOYING LATENT CLASS REGRESSION ANALYSIS TO EXAMINE LOGISTICS THEORY: AN APPLICATION OF TRUCK DRIVER RETENTION

Multiple regression analysis assumes that one model or theory is relevant for the entire population, yet research has shown that this assumption is often false and may severely limit valid theory development and testing. Latent class regression analysis overcomes this limitation and allows the researcher to identify and develop regression models that are relevant for different segments within the same population. Latent class regression analysis is introduced and is used to analyze truck drivers' intentions to stay with the same firm. This article demonstrates the advantages of testing logistics theory with latent class regression analysis and provides numerous applications for practitioners.     

The duality of decisions and the case for impulsiveness metrics

Customer metrics help firms manage their performance and predict financial outcomes. While many firms focus on customer satisfaction metrics for this purpose, dual-process theories in psychology and neuroscience show that customer decisions are based on two processes. This suggests that metrics which measure the impulsiveness of purchase decisions might effectively complement customer satisfaction metrics. In a series of experiments we demonstrate that satisfaction and impulsiveness metrics make distinct but strong predictions of consumer choices. Satisfaction and impulsiveness influence choice in different ways. While impulsiveness relates to choice directly, the satisfaction-choice path is mediated by loyalty intention. Moreover this relationship is moderated by product involvement such that impulsiveness metrics provide a better prediction for low-involvement than for high-involvement situations. Finally, a field study of 750 customers of 101 firms demonstrates these relationships at a firm level, indicating that satisfaction and impulsiveness metrics have equally strong but distinct relationships with shareholder value. Therefore firms may be able to benefit from complementing customer satisfaction metrics with customer impulsiveness metrics.     

Gendered Paths to Asset Accumulation? Markets,Savings, and Credit in Developing Countries

An extensive literature shows how property inheritance is biased against women in many developing countries, yet relatively little attention has been given to gender bias in other means of acquiring physical assets, such as the market. Using individual-level data from Ecuador, Ghana, and Karnataka, India, this study analyzes modes of acquisition and financing of housing, agricultural land, other real estate, and businesses. The findings show that women acquire fewer of their assets through the market than men, and that in asset markets, both men and women are more likely to use their own savings than to use credit. The study also analyzes current loans for asset acquisition and finds that, in general, women tend to be somewhat disadvantaged in securing formal bank loans. The results suggest that financial inclusion to promote more gender equal access to accumulation of assets should focus on both savings and credit, with priority to savings.