创业企业何以提高创新绩效——基于创业学习与商业模式创新协同联动视角的QCA方法

以150个创业企业为样本，基于创业学习和商业模式创新理论，运用模糊集定性比较分析方法（fsQCA），探究经验学习、认知学习、新颖型商业模式创新和效率型商业模式创新对创新绩效的影响路径及机制。研究发现，存在新颖型商业模式创新等4条创新绩效产出关键路径；相较于效率型商业模式创新，新颖型商业模式创新在关键路径中更容易提高创新绩效；利用QCA方法证实了影响创业企业创新绩效的组态内部各要素之间的替代性。结论丰富了创新绩效产出内部机制，可为创业企业提高创新绩效提供指导和借鉴。     

锚企业与科技新城共生模式研究:以阿里巴巴和杭州未来科技城为例

以阿里巴巴和杭州未来科技城为例，采用Logistic模型探讨锚企业与科技新城共生模式，结果表明：总体而言，阿里巴巴和未来科技城属于互利共生模式，阿里巴巴成长会促进未来科技城发展，而未来科技城发展也会反哺阿里巴巴的成长。2013-2016年两者共生系数之间的差值不断缩小，表明阿里巴巴和杭州未来科技城的共生模式从偏利共生转向互利共生。     

Correction to: Optimal and robust combination of forecasts via constrained optimization and shrinkage

We provide a correction to Proposition 1 in Optimal and robust combination of forecasts via constrained optimization and shrinkage, published in the International Journal of Forecasting 38(1):97-116 (2021). This correction has no impact on any other result (neither theoretical nor empirical) provided in the above paper.     

Forecasting China's GDP growth using dynamic factors and mixed-frequency data

Forecasting GDP growth is important and necessary for Chinese government to set GDP growth target. To fully and efficiently utilize macroeconomic and financial information, this paper attempts to forecast China's GDP growth using dynamic predictors and mixed-frequency data. The dynamic factor model is first applied to select dynamic predictors among large amount of monthly macroeconomic and daily financial data and then the mixed data sampling regression is applied to forecast quarterly GDP growth based on the selected monthly and daily predictors. Empirical results show that forecasts using dynamic predictors and mixed-frequency data have better accuracy comparing to traditional forecasting methods. Moreover, forecasts with leads and forecast combination can further improve forecast performance.     

Information Contents in Japanese OTC Drug Advertising from Elaboration Likelihood Model Perspective: Content Analysis of TV Commercials and OTC Drug Websites

Based on the Elaboration Likelihood Model, the current study investigates information types that are cross-promoted in Japanese pharmaceutical advertising. The results from a quantitative content analysis of OTC drug brands' TV commercials broadcasted in Japan between 2014 and 2015 and their corresponding product websites (n = 150) show that Japanese OTC drug promotions feature more informational cues in the latter; cues such as price, safety, quality, components, and guarantees/warranties are particularly prominent. Furthermore, product websites tend to focus more on rational appeals, whereas TV commercials emphasize emotional appeals. No difference is found between these media types regarding celebrity and noncelebrity endorser usage.     

城镇就业市场上劳动力工资扭曲程度测度

本文利用CHIPS2007数据库，基于随机前沿模型对我国城镇就业市场上劳动力的工资扭曲程度进行测度。研究结果表明：（1）在城镇就业市场上，由于工资扭曲现象的存在，劳动力实际获得的工资要比他们的边际生产率低45％～60％；（2）已婚、子女个数较少、本地、拥有失业保险、男性、大中型企业的劳动力工资扭曲程度要低于未婚、子女个数较多、外来、没有失业保险、女性、小型企业的劳动力；（3）中低工资水平的劳动力工资扭曲程度要比高工资水平的劳动力严重，且中低工资水平劳动力工资扭曲程度的方差更大。由此，本文提出推进就业市场的市场化改革，完善就业市场信息网络，从而减轻劳动力工资扭曲程度。     

Assessment of land use compatibility and noise pollution at Imam Khomeini International Airport

This study aimed to investigate land use planning around airports, by employing Remote Sensing (RS) and Geographic Information Systems (GIS), in conjunction with an optimization algorithm using an Integrated Noise Model (INM) software, to establish the potential effects of aircraft noise at Imam Khomeini International Airport (IKIA) in Tehran. We also checked for land use compatibility with the noise levels around IKIA and the residents' reaction to the noise. The research was carried out in three stages: a) the establishment of Strategic Noise Map (SNM) scenarios of the airport operation in the years 2011, 2020 and 2030 using the INM software; b) the assessment of the results with emphasis on the study area land uses and application of RS and GIS and the exposure of residents at different levels of environmental noise; and c) the assessment of the intensity of aircraft noise annoyance at various times of day and night. The results indicated that developing IKIA together with the residential development will increase airport noise. Hence proper management and control of noise at IKIA is essential.     

Decision-making in incomplete markets with ambiguity—a case study of a gas field acquisition

We apply utility indifference pricing to solve a contingent claim problem, valuing a connected pair of gas fields where the underlying process is not standard Geometric Brownian Motion and the assumption of complete markets is not fulfilled. First, empirical data are often characterized by time-varying volatility and fat tails; therefore, we use Gaussian generalized autoregressive score (GAS) and GARCH models, extending them to Student’s t-GARCH and t-GAS. Second, an important risk (reservoir size) is not hedgeable. As a result, markets are incomplete which makes preference free pricing impossible and thus standard option pricing methodology inapplicable. Therefore, we parametrize the investor’s risk preference and use utility indifference pricing techniques. We use Least Squares Monte Carlo simulations as a dimension reduction technique in solving the resulting stochastic dynamic programming problems. Moreover, an investor often only has an approximate idea of the true probabilistic model underlying variables, making model ambiguity a relevant problem. We show empirically how model ambiguity affects project values, and importantly, how option values change as model ambiguity gets resolved in later phases of the projects. We show that traditional valuation approaches will consistently underestimate the value of project flexibility and in general lead to overly conservative investment decisions in the presence of time-dependent stochastic structures.     

The information content of implied volatility in developed versus developing FX markets

This article predicts the daily movement of monthly foreign exchange (FX) rate volatility using a linear combination of a time-series model and implied volatilities from options. The focus is on analysing the FX volatilities in three developing economies (the Brazilian real (BRL), the Indian rupee (INR) and the Russian ruble (RUB)) against the US dollar (USD). The empirical exercise utilizes two time-series models, mixed data sampling (MIDAS) and GARCH. The analysis indicates that for both developed and developing economies the predictive power of MIDAS and that of GARCH is comparable. Further on in this article, we will ascertain whether the relationship between realized and implied volatility is fundamentally different in the case of developing economies from that among developed economies. Thus, we compare the pairs USD/BRL, USD/INR and USD/RUB against EURO/USD and USD/Japanese yen to determine the information content and predictive power of implied volatilities. Plots of the MIDAS coefficients show that the volatility is more persistent in developing economies than in developed economies.