技术创业型企业孵化资本投入的风险管控——来自多案例对比

待孵化的技术创业型企业同时具有概念性技术向差异化产品转化的高风险与产品异质性被认同后溢价评估的高收益特点，导致其投资者多处于隔岸观火却欲罢不能的的孵化投资矛盾中。对孵化资本实施有效的风险管控，成为吸引外部资本投入的关键。基于此，选择在可创概念选育与技术创业孵化领域探索出高成功率路径的概念证明中心、YCombinator和创新工场为研究案例，分析其在创业项目筛选、孵化资金运营等关键环节的风险管控方式，以期完善我国孵化资本管控理论、助力我国商业孵化器提高资金风险管控能力、促进外部资本投入。     

A comparative study of eight COVID-19 protective measures and their impact on Swiss tourists’ travel intentions

A comparative vignette-based experimental survey design incorporating various socio-psychological factors, linked to the Theory of Planned Behavior (TPB), the Health Belief Model (HBM) and the Domain-Specific Risk-Taking scale (DOSPERT) was carried out to test variations in eight travel-related COVID-19 protective measures on Swiss tourists’ travel intentions. Among the tested measures, vaccination passports, surgical masks and quarantining are those that stand out the most, with surgical masks having the greatest acceptance and willingness to adopt while traveling. Quarantining, on the other hand, appears to have a deterrent influence on travel intentions, and vaccination passports have the lowest perceived barriers during travel, but the highest perceived benefits in mitigating the spread of the infection. The discussion of individual differences has specific implications for tourism management against the background of our empirical findings.     

论数据权益的刑法保护——民刑交错视角下的法益保护论探讨

关于“数据权益的刑法保护”问题，在理论层面上，可从“刑法解释论”和“刑法立法论”两种路径进行探讨。“刑法解释论”探讨路径以现行《刑法》罪名体系为出发点，主要任务是揭示哪些罪名的犯罪构成之设置是以“数据权益”为规范保护目的；“刑法立法论”探讨路径是在刑法立法层面上探讨立法者为在刑法政策上实现数据权益的刑法保护这一目的，动用刑罚禁止何种行为类型才具正当性的问题。然而，两种探讨路径都将依赖于“数据权益”的内涵确定以及法益格的认定问题，换言之，是刑法法益理论在数据权益刑法保护问题上的具体运用。《民法典》第127条并非是关于数据的确权性规定，且在民法理论界关于数据权益的法律属性存在诸多争议的状况下，“数据权益”内涵不明、法律属性不清导致其并不具备作为刑法保护客体的“法益”格。当前刑法理论界存在的关于“数据权益”的刑法类法益保护模式探讨路径，是对刑法法益保护方式的误读，并未触及“数据权益刑法保护”之规范层面问题的实质。“数据安全”法益观的探讨路径则不仅混淆了现象层面与规范层面上的“数据犯罪”概念的界分，也由于没有论证“数据安全”如何能够构成刑法的保护法益，而导致结论过于武断。在理论探讨上，应该明确作为行为客体的物理层面上的“数据”概念与作为保护客体的法益层面上的“数据权益”概念之间的区别，据此明确“数据权益的刑法保护”在规范层面上是否构成新问题。     

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.     

智慧居家养老服务协同供给的优化路径研究——以广西钦州市智慧居家养老项目的实践经验为例

智慧居家养老服务的协同供给可以形成社会联动效应，降低公共服务成本。运用公共服务协同供给分析框架，通过交叉分类方法从协同主体的利益与目标两个变量的耦合性出发分析广西钦州市智慧居家养老项目中养老服务主体间不同种类的协同关系，可以从加强政府领导、形成合作联盟、建立市场标准、创新扶持政策4个方面完善政府、企业、社会组织之间不同类型的协同供给，实现社会资源的高效利用以及向智慧居家养老服务的发展和转变。     

Addressing plastic pollution through green consumption: Predicting intentions to use menstrual cups in the Philippines

Plastic pollution is a global environmental crisis that poses a huge threat to the health of people and marine ecosystems worldwide. A significant source of plastic pollution is menstrual hygiene management, and an approach that can help address this crisis is the usage of washable and reusable menstrual cups. Using an extended theory of planned behavior model that includes self-identity and perceived quality, the study predicted intentions to use menstrual cups in the Philippines. Structural equation modeling results showed that perceived quality predicted attitudes towards menstrual cup usage. Moreover, attitudes, perceived behavioral control, and self-identity predicted intentions to use menstrual cups. There were also some differences in the factors and predictors of intentions between non-users and regular users of menstrual cups. Among regular users, perceived behavioral control did not predict intentions. These findings provide empirical support for the extended model, and provides insights for governments, non-government organizations, and corporations in promoting the usage of menstrual cups to address the global plastic pollution crisis.     

Conditional Mandates on Management Earnings Forecasts: The Impact on the Cost of Debt

Exploiting a unique conditional disclosure mandate on management earnings forecasts (MEFs) in China, we examine the differential effects of voluntary and mandatory MEFs on the cost of debt. We find that firms providing voluntary MEFs have lower cost of debt than do mandatory forecasters and nonforecasters. The results of the channel analyses reveal that voluntary forecasters have greater commitment to voluntary MEFs in future periods than do mandatory forecasters and nonforecasters, and the precision, accuracy, and timeliness of MEFs are higher for voluntary forecasters than for mandatory forecasters. Additional analyses show that the differential effects of voluntary and mandatory MEFs on cost of debt are stronger for voluntary forecasters operating in opaque information environments, issuing high-quality and confirming forecasts, controlled by private shareholders, and operating in highly competitive product markets. Overall, our results indicate that, compared with mandatory MEFs, voluntary MEFs are more informative for credit investors, particularly for firms facing greater information risk and operating uncertainty.     

Natural resource rents and internal conflicts: Can decentralization lift the curse?

We study how natural resource rents affect the risk of internal conflict within countries and how the federal structure of countries influences this relationship. Natural resource abundance may induce excessive rent-seeking and thus increase the risk of internal conflict. Fiscal and political decentralization as an institutional arrangement for rent-sharing and political codetermination of regions within a country may limit the destructive effect of natural resource rents on internal stability. Using cross-country and panel data from more than 90 countries covering the period 1984–2004, we find evidence that natural resource rents indeed increase the risk of internal conflict, but this relationship is significantly mitigated by political decentralization.     

Identifying Worldviews on Corporate Sustainability: A Content Analysis of Corporate Sustainability Reports

Companies commonly issue sustainability or corporate social responsibility (CSR) reports. This study seeks to understand worldviews of corporate sustainability, or the corporate message conveyed regarding what sustainability or CSR is and how to enact it. Content analysis of corporate sustainability reports is used to position each company report within stages of corporate sustainability. Results reveal that there are multiple coexisting worldviews of corporate sustainability, but the most dominant worldview is focused on the business case for sustainability, a position anchored in the weak sustainability paradigm. We contend that the business case and weak sustainability advanced in corporate sustainability reports and by the Global Reporting Initiative are poor representations of sustainability. Ecological embeddedness, or a locally responsive strategy that is sensitive to local ecosystems, may hold the key to improved ecological sensemaking, which in turn could lead to more mature levels of corporate sustainability worldviews that support strong sustainability and are rooted in environmental science. This must be supported by government regulation. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment