大数据能力对企业创新绩效的影响——IT-业务融合与双元环境的调节作用

基于动态能力理论和权变理论，以IT-业务融合、双元环境为调节变量，探究大数据能力与企业创新绩效间的作用关系，结果发现：大数据能力对创新绩效具有正向促进作用；IT-业务融合调节大数据能力与创新绩效的关系，IT-业务融合水平越高，大数据能力对创新绩效的正向影响就越显著；双元环境能够调节大数据能力与创新绩效间关系。其中，环境动态性在大数据能力与创新绩效关系间起正U型调节作用，而环境竞争性在大数据能力与创新绩效关系间起倒U型调节作用。从内外部情境视角解释大数据能力的创新转化，对中国企业大数据应用具有指导意义。     

环境政策工具对生态创新的影响: 研究回顾及实践意义

各种环境政策工具用来推进生态创新的开发、传播与应用，但不同政策工具对生态创新的作用效果还有待进一步挖掘。系统梳理了环境政策工具对生态创新影响的相关研究，探究不同政策工具的作用及其本质，以理解在推动生态创新开发、传播与应用情景下环境政策工具的作用及其实践意义。     

组织遗忘、组织即兴与环境动态性视角下企业原始性创新构建路径

原始性创新是企业获得核心竞争力的关键，但当前对企业如何获得原始性创新的研究严重不足。为此，以我国环渤海经济带179家高技术企业为样本，从组织遗忘和即兴角度研究原始性创新形成问题，并进一步分析环境动态性在组织遗忘和原始性创新间的作用。结果发现：组织遗忘和组织即兴对原始性创新具有积极效应；组织即兴在组织遗忘和原始性创新间发挥着部分中介作用；环境动态性对组织遗忘和原始性创新的关系具有正向调节效应。     

债务违约、社会责任与政府支持

转型期中国，地方国有企业作为地区经济发展的一股中坚力量，当其发生债务违约时，作为实际控制人的地方政府究竟是否愿意提供支持，会优先选择哪些企业提供支持，政府的支持行为是否会影响到信贷资源的配置效率呢?为得到验证，文章选取2007-2016年沪深A股地方国有上市企业作为研究样本，实证分析了地方国企发生债务违约后，地方政府的支持行为及其对信贷资源配置效率的影响。研究结论表明：第一，地方国企发生债务违约后，地方政府会提供更多的"支持"，且支持额度与债务违约额呈显著正相关关系；第二，债务违约前，承担了更多社会责任（环保投资、捐赠以及就业等）的地方国企，在债务违约后可相应地获得更多的地方政府支持；第三，违约企业，尤其是得到更多政府支持的违约企业可获得更多的信贷资源，而其经营业绩却往往更差。由此表明政府干预一定程度上降低了信贷资源配置效率。     

Risk aversion,prudence and temperance: An experiment in gain and loss

We characterize the individual's attitude towards risk, prudence and temperance in the gain and loss domains. We analyze the links between the three features of preferences for a given domain and between domains for each feature of preferences. Consequently, the reflection effect, the mixed risk aversion and the risk apportionment, are key concepts of our study. We also display some determinants for risk aversion, prudence and temperance in each domain. To do this, we conducted a lab experiment with students eliciting risk aversion, prudence and temperance in the two domains, and collected information about each subject's characteristics.     

The valuation relevance of environmental performance revisited: The moderating role of environmental provisions

This study attempts to broaden our understanding of the value relevance of environmental performance by providing empirical evidence on the moderating role of financial environmental reporting. Previous studies find that firms' environmental performance can be both positively and negatively associated with market value. Such contradictory findings can be attributed to the fact that environmental performance is associated with future economic benefits and costs. This study suggests that firms with recognized environmental provisions on their balance sheets enable investors to disentangle these opposite effects either by signaling strong future financial performance or by enhancing the reliability of environmental performance information. Regardless of the mechanism by which this moderation effect is invoked, it is hypothesized that capital market participants place a positive and significantly higher value on the environmental performance ratings of firms with recognized environmental provisions than on the ratings of firms without environmental provisions. Utilizing a sample of 692 firm-year observations of French listed firms and employing a linear price-level model that associates the market value of a firm's equity with its environmental performance, I provide empirical evidence to corroborate this thesis. In addition to contributing to the academic debate on the market valuation implications of environmental performance, this study intends to provide useful insights from a country that can be considered a pioneer of environmental reporting legislation; hence, it provides valuable lessons for other jurisdictions that are in the process of developing their sustainability reporting regulations. Finally, the findings of this study support the calls for more integrated reporting showing that the interaction of financial and non-financial information has market valuation implications.     

Forecasting unknown-unknowns by boosting the risk radar within the risk intelligent organisation

This theoretical perspective paper interprets (un)known-(un)known risk quadrants as being formed from both abstract and concrete risk knowledge. It shows that these quadrants are useful for categorising risk forecasting challenges against the levels of abstract and concrete risk knowledge that are typically available, as well as for measuring perceived levels of abstract and concrete risk knowledge available for forecasting in psychometric research. Drawing on cybersecurity risk examples, a case is made for refocusing risk management forecasting efforts towards changing unknown-unknowns into known-knowns. We propose that this be achieved by developing the ‘boosted risk radar’ as organisational practice, where suitably ‘risk intelligent’ managers gather ‘risk intelligence information’, such that the ‘risk intelligent organisation’ can purposefully co-develop both abstract and concrete risk forecasting knowledge. We also illustrate what this can entail in simple practical terms within organisations.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

A COMPREHENSIVE REVIEW FOR GREEN PRODUCT TERM: FROM DEFINITION TO EVALUATION

Nowadays, interest in corporate environmental strategies shifts from cleaner processes to the holistic nature of green products. The relevant literature argues that firms have the opportunity to pioneer through green product innovation, allowing them to differentiate and thus gain competitive advantage. Environmental burden of products during their entire life cycle is undeniable. Due to the weakness of the existing literature that inadequately addresses a commonly accepted green product definition, as well as the thereby caused inconclusive academic empirical results on firms' competitiveness, there are many cases of businesses greenwashing behavior. The overall contribution of this exploratory paper, on determining and evaluating the degree of greenness of a product, is twofold; first, starting with a systematic literature review, authors further contribute by proposing an integrative definition that addresses the so far existing terminological gap. Next, after reviewing the existing environmental assessment tools, authors based on the developed definition and in accordance to its dynamic dimension contribute to the existing methodology, as the paper reveals issues that need to be considered in the evaluation of green products.     

Hedging and temporal permit issuances in cap-and-trade programs: The Market Stability Reserve under risk aversion

Cap-and-trade programs such as the European Union's Emissions Trading System (EU ETS) expose firms to considerable risks, to which the firms can respond with hedging. We develop an intertemporal stochastic equilibrium model to analyze the implications of hedging by risk-averse firms. We show that the resulting time-varying risk premium depends on the size of the permit bank. Applying the model to the EU ETS, we find that hedging can lead to a U-shaped price path, because prices initially fall due to negative risk premiums and then rise as the hedging demand declines. The Market Stability Reserve (MSR) reduces the permit bank and thus, increases the hedging value of the permits. This offers an explanation for the recent price hike, but also implies that prices may decline in the future due to more negative risk premiums. In addition, we find higher permit cancellations through the MSR than previous analyses, which do not account for hedging.