Relationship lending and innovation: empirical evidence on a sample of European firms

This paper investigates the impact of relationship lending on innovation (the probability to innovate and the intensity of innovation). Using a unique dataset providing detailed information on bank–firm relationships across European firms, we relate different proxies of relationship lending (soft information, long-lasting relationships, number of banks and share of the main bank) to innovation. We find a very strong and robust positive effect of ‘soft-information-intensive’ relationships, a less robust positive effect of long-lasting relationships and a negative effect of credit concentration as measured by the number of banking relationships. We also find that ‘soft-information-intensive’ relationships reduce credit rationing for innovative firms, while long-lasting relationships seem to favour innovation via other relational channels. These results raise some concern on the impact of screening processes based on automatic procedures, as those suggested by the Basel rules, on firms' capability to finance innovative activities in Europe.     

双创环境下发展科技服务业助推经济转型升级问题研究

科技服务业是现代服务业中的新兴产业,在促进经济转型升级中发挥着重要作用。双创环境下,科技服务业主要通过动力机制、利益机制和组织协调机制助推经济转型升级。以江苏省科技服务业为例,分析了当前科技服务业发展现状和存在的问题,探究了双创环境下江苏省发展科技服务业助推经济转型升级的路径,以期为科技服务业发展和经济转型升级提供参考。     

A Dynamic Model of Oligopolistic Market Structure,Featuring Positioning Investments

In their efforts to create and maintain a position in a market, firms make positioning investments of various sorts, in R&D, plant, advertising, and location, or more generally, in product development and maintenance. In an environment where the success of positioning investments is stochastic, the positioning game played by firms that compete to serve a market is necessarily dynamic. We model the positioning and operating decisions of firms in an environment of this sort. When the market is large enough to support at least one active firm, in the steady state equilibrium, the expected number of firms serving the market at a point in time is a nearly continuous function of market size, in sharp contrast to the familiar integer-valued step function seen in classic models, and expected total and consumer surplus are higher than standard non-stochastic models would indicate. This suggests that the classic models are not always a sound guide for policy.     

“严”师出“高”徒？导师完美主义对徒弟创造力的双元影响路径

师徒关系正在成为被制造业企业广泛开发的关键人力资源关系，导师人格特质会对徒弟日常工作态度和行为塑造产生关键作用。基于压力源-应变关系的理论观点，具体探讨了师徒关系中导师完美主义特质对徒弟创造力的双元影响路径和适用情境，基于制造企业中342对师徒样本进行实证检验，得出以下结论：①导师完美主义特质正向影响工作倦怠,工作倦怠负向影响徒弟创造力,导师完美主义通过工作倦怠负向作用于徒弟创造力；②导师完美主义对工作重塑行为产生积极影响,徒弟的工作重塑行为正向影响其创造力,导师完美主义通过工作重塑行为正向作用于徒弟创造力；③工作倦怠/工作重塑对导师完美主义和徒弟创造力间关系的中介作用，均受到促进性焦点的调节。     

服务外包中组织双元学习对供应商创新能力的影响——治理机制的调节作用

通过提升自身创新能力应对市场竞争，已成为多数服务外包供应商的重要战略选择。基于社会网络理论和组织学习理论，运用174对发包企业与供应商企业的有效配对调查数据，探究组织双元学习对供应商创新能力的影响，检验契约治理机制和关系治理机制的调节作用。结果发现：①探索式学习与利用式学习均对供应商创新能力具有积极影响；②关系治理机制在组织双元学习与供应商创新能力关系中起正向调节作用；③契约治理机制在组织双元学习与供应商创新能力关系中呈负向调节效应。研究结论有助于厘清组织双元学习影响供应商创新能力的内在机理，对我国服务外包企业有效运用不同组织学习方式提升自主创新能力具有一定借鉴意义。     

Does asset-light strategy contribute to the dynamic efficiency of global airlines?

This study analyses the effect of asset-light strategy on the dynamic efficiency of global airlines from 2008 to 2013. First, a dynamic data envelopment analysis is employed to estimate the dynamic efficiency of global airlines. Second, the degree of asset-lightness is computed by combining the concepts of the DuPont equation and financial ratios. Third, a multivariate analysis is performed to analyze the association between asset-light strategy and dynamic efficiency. The findings show that asset-light strategy significantly enables global airlines to have better corporate performance. Overall, this study suggests that global airlines should efficiently manage and allocate their light resources to sustain challenges in the dynamic global airline industry.     

The impact of institutional quality on manufacturing sectors: A panel data analysis

We use data on Russian regions to examine the effect of institutional quality on institutionally dependent manufacturing sectors in terms of both output levels and growth rates. Unlike the existing literature on this topic, which mostly uses cross-sectional or pooled specifications for either country-level or regional data, we use panel data. This approach allows us to distinguish between short-term and long-term impacts and mitigates endogeneity concerns. As an additional contribution to the literature, we estimate the full marginal effects of institutions on manufacturing sectors with different degrees of institutional dependence. In terms of policy recommendations, our results imply that significant institutional improvements would be needed for the Russian economy to diversify away from heavy reliance on oil and natural gas.     

Proactive vehicle routing with inferred demand to solve the bikesharing rebalancing problem

Bikesharing suffers from the effects of fluctuating demand that leads to system inefficiencies. We propose a framework to solve the dynamic bikesharing repositioning problem based on four core models: a demand forecasting model, a station inventory model, a redistribution needs model, and a vehicle-routing model. The approach is proactive instead of reactive, as bike repositioning occurs before inefficiencies are observed. The framework is tested using data from the Hubway Bikesharing system. Simulation results indicate that system performance improvements of 7% are achieved reducing the number of empty and full events by 57% and 76%, respectively, during PM peaks.     

The method of endogenous gridpoints in theory and practice

The method of endogenous gridpoints (ENDG) significantly speeds up the solution to dynamic stochastic optimization problems with continuous state and control variables by avoiding repeated computations of expected outcomes while searching for optimal policy functions. I provide an interpolation technique for non-rectilinear grids that allow ENDG to be used in n-dimensional problems in an intuitive and computationally efficient way: the acceleration of ENDG with non-linear grid interpolation is nearly constant in the density of the grid. Further, ENDG has only been shown by example and has never been formally characterized. Using a theoretical framework for dynamic stochastic optimization problems, I formalize the method of endogenous gridpoints and present conditions for the class of models for which it can be used.