Effectiveness and Efficiency of Cross-Border Knowledge Transfer: An Empirical Examination

abstract    Based on a sample of 102 US organizations, this study examines the impact of knowledge characteristics, recipient learning intent, source attractiveness, and relationship quality on the effectiveness and efficiency of knowledge transfer from the international business affiliates of these organizations. Findings indicate that recipient learning intent and source attractiveness positively impact the effectiveness of knowledge transfer. In addition, recipient learning intent was found to have a positive effect on knowledge transfer efficiency. In particular, results highlight the strong positive impact that the quality of the relationship between the source and the recipient has on both the efficiency and effectiveness of cross-border knowledge transfer. The study also indicates that knowledge value is positively associated with recipient learning intent and that knowledge value, rarity and non-substitutability influence source attractiveness. Finally, findings suggest that the relationship between knowledge characteristics and knowledge transfer is partially mediated by recipient learning intent and source attractiveness.     

Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles

ABSTRACT

UK logistics fleets face increasing competitive pressures due to volatile fuel prices and the small profit margins in the industry. By reducing fuel consumption, operational costs and carbon emissions can be reduced. While there are a number of technologies that can reduce fuel consumption, it is often difficult for logistics companies to identify which would be the most beneficial to adopt over the medium and long terms. With a myriad of possible technology combinations, optimising the vehicle specification for specific duty cycles requires a robust decision-making framework. This paper combines simulated truck and delivery routes with a metaheuristic evolutionary algorithm to select the optimal combination of low-carbon technologies that minimise the greenhouse gas emissions of long-haul heavy goods vehicles during their lifetime cost. The framework presented is applicable to other vehicles, including road haulage, waste collection fleets and buses by using tailored parameters in the heuristics model.     

Does intraday technical analysis in the U.S. equity market have value?

This paper investigates whether intraday technical analysis is profitable in the U.S. equity market. Surveys of market participants indicate that they place more emphasis on technical analysis (and less on fundamental analysis) the shorter the time horizon; however, the technical analysis literature to date has focused on long-term technical trading rules. We find, using two bootstrap methodologies, that none of the 7846 popular technical trading rules we test are profitable after data snooping bias is taken into account. There is no evidence that the market is inefficient over this time horizon.     

Rare disaster risk and the expected equity risk premium

Consistent with the predictions of rare disaster models, we find that a proxy for the time‐varying probability of rare disasters helps to explain fluctuations in expectations of the equity risk premium. Our proxy for disaster risk is a recently developed measure of global political instability, and the expected market risk premium is from Value Line analysts' expected stock returns. Consistent with long‐run risk models, uncertainty about expected GDP growth and expected consumption growth is also significantly positively related to the expected market risk premium. We obtain similar results when we use the earnings–price ratio and the dividend–price ratio as proxies for the expected market risk premium.     

Time series momentum and moving average trading rules

We compare and contrast time series momentum (TSMOM) and moving average (MA) trading rules so as to better understand the sources of their profitability. These rules are closely related; however, there are important differences. TSMOM signals occur at points that coincide with a MA direction change, whereas MA buy (sell) signals only require price to move above (below) a MA. Our empirical results show MA rules frequently give earlier signals leading to meaningful return gains. Both rules perform best outside of large stock series which may explain the puzzle of their popularity with investors, yet lack of supportive evidence in academic studies.     

Recent estimates of exchange rate pass-through to import prices in the euro area

This paper provides an update on the exchange rate pass-through (ERPT) estimates for 12 euro area (EA) countries. First, based on quarterly data over the 1990–2012 period, the study does not find a significant heterogeneity in the degree of pass-through across the monetary union members, in contrast to previous empirical studies. As the authors use a longer time span for the post-EA era than existing studies, this is not surprising, since the process of monetary union has entailed some convergence towards more stable macroeconomic conditions across EA member states. Second, when assessing the stability of pass-through elasticities, the authors find very weak evidence of a decline around the inception of the euro in 1999. However, their results reveal that a downtrend in ERPT estimates became apparent starting from the beginning of the 1990s. This observed decline was synchronous to the shift towards reduced inflation regimes in their sample of countries. Finally, the authors notice that the distinction between “peripheral” and “core” EA economies in terms of pass-through has significantly decreased over the last two decades.     

Default contagion and systemic risk in loan guarantee networks

This paper studies systemic risk in the Chinese debt market stemming from inter‐corporate loan guarantees using field data from Zhejiang Province. We apply a weighted and directed network model to analyse the implications for default contagion and systemic risk under different stress testing scenarios. The empirical results indicate that the topology of the loan guarantee network is close to a ‘scale‐free’ structure, which is known to be robust against accidental failures but vulnerable to coordinated attacks. Hence, the network is able to cope with idiosyncratic shocks resulting from single company failures, but can easily suffer from more widespread contagion if a group of systemically important companies are hit by a targeted shock. We further demonstrate that within our sample of small and medium‐sized enterprise (SME) companies, increasing leverage reduces network stability and exacerbates the effects of contagion. More lenient bank lending policies increase the survival rate of sample companies and thereby reduce the losses from default contagion.