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。     

A market-consistent framework for the fair evaluation of insurance contracts under Solvency II

Decisions in Economics and Finance - The entry into force of the Solvency II regulatory regime is pushing insurance companies in engaging into market consistence evaluation of their balance sheet,...     

Exploring sources and outcomes of trust and commitment to nonprofit organizations: The case of Amnesty International Portugal

The interactions between customers and organizations have been regarded as a core aspect in cocreating and developing new products and practices. The current study explores these interactions in the context of citizens and nonprofit organizations. The study comprises two parts: (a) a qualitative approach using interviews and the analysis of social networks to better understand the organization's social media marketing practices and corresponding outcomes and (b) a quantitative approach to analyze antecedents and outcomes of trust and being committed to participate in a nonprofit organization such as Amnesty International. From the qualitative approach, the findings highlight that Amnesty International uses social media (Facebook) to share information, and citizens tend to consider sharing posts, but they do not express new ideas or interact with the organization. These findings contribute to structure the model analyzed in the second stage of the research. Regarding the qualitative approach, the results show that organizational credibility is the most significant driver of trust followed by communicative ability. Affectively commitment to participation and relationship perception act as outcomes of overall commitment.     

Hi-tech start-ups: legitimacy challenges and funding dynamics

Studies on the legitimacy challenges faced by hi-tech start-ups are still scarce, leaving room for research, and policymaking debate. Legitimacy issues may become difficult to face for hi-tech firms in comparison with other start-ups, because they work in an extreme environment where the technological challenges are at the edge of the scientific possibility. The paper proposes a conceptual model to grasp the relevance of three legitimacy drivers of the hi-tech start-ups for investment decisions. We investigated the ability of 30 hi-tech start-up firms to obtain financial resources from the US investors, employing a set-theoretic approach and carried out fuzzy-set Qualitative Comparative Analysis. Our findings clarify that the funding decisions of US investors are driven by the location of headquarter and R&D of hi-tech start-ups and by the educational experience of the founders. Our study has significant theoretical, practical, and policymaking implications.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

A hybrid information approach to predict corporate credit risk

This study proposes a hybrid information approach to predict corporate credit risk. In contrast to the previous literature that debates which credit risk model is the best, we pool information from a diverse set of structural and reduced‐form models to produce a model combination based on credit risk prediction. Compared with each single model, the pooled strategies yield consistently lower average risk prediction errors over time. We also find that while the reduced‐form models contribute more in the pooled strategies for speculative‐grade names and longer maturities, the structural models have higher weights for shorter maturities and investment grade names.     

Social and organisational implications of CAD usage: a grounded theory in a fashion company

This paper focuses on the process of Computer Aided Design (CAD) diffusion into a group engaged in the development of innovative products. Adopting an ethnographic approach, we build a grounded theory for interpreting CAD usage in terms of the interplay between variables such as management orientation, training, actors' specialisation and deskilling, availability of shared archives, technological discontinuities between organisational areas.