孵化网络结构、风险传播对孵化网络最终健康水平的影响——结构可视化的调节作用

风险在孵化网络中的传播影响孵化网络健康水平，并会导致在孵企业高失败率与低成长率。为实现有效的网络治理，以两家国家级孵化器形成的实际网络为例，运用复杂网络理论中的SIR模型和仿真方法，模拟特定情境下风险在不同网络结构中的传播机理及其对孵化网络最终健康水平的影响。研究发现：孵化网络结构、风险传播与网络健康间具有显著相关性；在低初始健康分布情景下，无标度网络具有更快的恢复速度；在不同网络结构下，可视化水平均有助于提升孵化网络风险化解能力。     

天使众筹联合投资网络结构及动态演变的探索性研究

天使众筹通过开放的互联网平台连接投资人与创业者，使得天使众筹联合投资网络的形成情境不同于风险投资联合投资网络。基于2015—2018年蚂蚁天使众筹平台联合投资数据，分析天使众筹联合投资网络结构特征与演变趋势，结果表明，天使众筹联合投资网络与风险投资联合投资网络具有显著差异，前者是强凝聚性和高开放性并存的网络，后者则是弱凝聚性和低开放性并存的网络。结论可丰富联合投资网络和众筹领域的理论研究，有助于深入分析天使众筹联合投资网络及其在数字经济时代的作用。     

知识产权运营领域数据要素市场化配置路径研究

基于马克思经济学资源配置理论，探讨知识产权运营与数据要素市场化配置的关联性。在梳理数据要素市场化配置基础政策、关联政策和专门政策的基础上，对知识产权大数据平台系统、大数据金融产品、大数据中心建设和大数据产业应用联盟进行比较。结果发现:第一，我国知识产权运营领域数据要素市场化配置改革主要存在3大瓶颈：数据要素产权界定不明、交易流转不畅及安全监管不易；第二，知识产权运营领域数据要素市场化配置路径需从加快知识产权运营数据汇聚共享、推动知识产权运营数据产业化应用和强化知识产权运营数据安全治理3个方面予以完善。     

IFRS adoption and stock misvaluation: Implication to Korea discount

Analyzing publicly traded stocks in Korea surrounding IFRS adoption in 2011, we find that the gap between stock price and firm value, value-to-price (V/P) ratio, narrows following the IFRS adoption and that this narrowed gap is observed only for higher V/P firms. We further find that the return predictability of V/P decreases in the post-IFRS period. Using a path analysis, we report further evidence that mandatory IFRS adoption decreases idiosyncratic volatility and improves trading volume and market liquidity, thereby contributing to the narrowed gap between value and price. We conclude that IFRS adoption contributes to resolution of Korea discount.     

Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic

Since the level of markets’ information efficiency is key to profiteering by strategic players, Shocks; such as the COVID-19 pandemic, can play a role in the nature of markets’ information efficiency. The martingale difference and conditional heteroscedasticity tests are used to evaluate the Adaptive form of market efficiency for four (4) major stock market indexes in the top four affected economies during the COVID-19 pandemic (USA, Brazil, India, and Russia). Generally, based on the martingale difference spectral test, there is no evidence of a substantial change in the levels of market efficiency for the US and Brazilian stock markets in the short, medium, and long term. However, in the long term, the Indian stock markets became more information inefficient after the coronavirus outbreak while the Russian stock markets become more information efficient. Intuitively, these affect the forecastability and predictability of these markets’ prices and/or returns. Thereby, informing the strategic and trading actions of stock investors (including arbitrageurs) towards profit optimization, portfolio asset selection, portfolio asset adjustment, etc. Similar policy implications are further discussed.     

资本市场开放与股权资本成本——基于沪港通、深港通的实证研究

本文基于沪港通和深港通研究资本市场开放对中国内地股权资本成本的影响。研究发现,受政策风险和市场环境等因素所限,沪港通在初始阶段并未对沪市公司的股权资本成本产生显著影响,但随着政策进一步完善、市场逐渐稳定和交易不断活跃,其对股权资本成本的降低效果于实施两年后开始显现;深港通建立在沪港通的制度基础和运行经验上,其在开通后显著降低了标的公司的股权资本成本。本文还进一步分析了资本市场开放影响股权资本成本的竞争渠道和信息渠道,发现深港通对股权资本成本的降低作用主要集中在投资者竞争程度较高,或是公开信息质量较高、信息不对称程度较低的股票样本。     

Market impact: a systematic study of the high frequency options market

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders—large orders that are split into smaller pieces before being sent to the market—on one of the main Asian markets. In line with our previous work on the equity market [Said, E., Bel Hadj Ayed, A., Husson, A. and Abergel, F., Market impact: A systematic study of limit orders. Mark. Microstruct. Liq., 2018, 3(3&4), 1850008.], we propose an algorithmic approach to identify metaorders, based on some implied volatility parameters, the at the money forward volatility and at the money forward skew. In both cases, we obtain results similar to the now well-understood equity market: Square-Root Law, Fair Pricing Condition and Market Impact Dynamics.     

The moderating effect of average wage and number of stores on private label market share: A hierarchical linear model analysis

Existing research on private label market share is primarily in the context of the Western market. The Chinese market context research is scarce, although private labels are developing rapidly in the past several years. This study investigates how the average wage and number of stores affect the Chinese market's private label market share. More importantly, this paper examines the moderating effect of the average wage and the number of stores on the relationship between the private label market share and product assortment as well as the relationship between the private label market share and pricing. Data collected from a Chinese supply chain dyad is analyzed to study category management using hierarchical linear models. The results reveal that the average wage and the number of stores positively affect the private label market share. Furthermore, the average wage enhances the negative effect of the number of brands, weakens the negative effect of the private label price, weakens the positive effect of national brand price. Meanwhile, the number of stores enhances the positive effect of the SKU proliferation of private label, enhances the negative effects of the number of brands, and enhances the negative effect of the private label price. This study contributes to category management. Furthermore, the findings will be valuable to domestic and international grocery marketers and retailers operating private labels in China.     

优化营商环境与外资企业FDI动机——市场寻求抑或效率寻求

在优化营商环境已成为当前发展中国家引资竞争新优势的背景下,针对优化营商环境影响外资企业FDI动机的考察变得尤为重要。本文在构建企业层面营商环境指数的基础上,考察了发展中国家优化营商环境影响外资企业FDI动机的机制及效应。结论表明:优化营商环境减弱(增强)了外资企业的市场(效率)寻求型FDI动机;内资企业竞争力的增强、外资企业特惠资源的取消和加工贸易型外资企业的存在,使得优化营商环境降低了外资企业的生产率,进而市场(效率)寻求型FDI动机减弱(增强)。细分样本的考察发现,上述结论仅存在于独资企业、工业和低收入国家的外资企业中,对于合资企业、服务业和高收入国家的外资企业,优化营商环境对其FDI动机无显著影响,且生产率的中介效应不存在。本研究从优化营商环境的视角为当前中国引资政策的制定提供了更为具体的政策启示。     

Optimal targeting of latent tourism demand segments

This paper identifies for the first time the optimal target markets employing the latent tourism demand expenditure, a novel concept in tourism literature. The study quantifies latent tourism demand between each pair of origin-destination through distinguishing by type of tourism and seasonality. It works with market shares that are estimated via a fractional regression model. Moreover, latent demand is clustered using a market segmentation approach based on a latent class regression. Finally, the optimal target markets are chosen depending on the expected latent tourism expenditure. The result has clear policy implications in terms of which markets are promoted, the optimal channels of communication and the maximum budget for each marketing campaign.