When age does not harm innovative behavior and perceptions of competence: Testing interdepartmental collaboration as a social buffer

Can older managers overcome stereotypes relating age to low competence? We integrate the literature on age and cognitive ability with research on innovation to explore whether—and if so, when—employees' age harms performance and promotability appraisals made by their supervisors. Multisource, time‐lag data from 305 project managers indicate that the negative stereotypes can be explained through decreased innovative behavior. However, older employees are not always seen as poorer performers with less potential to be promoted due to their reduced innovative behavior. Rather, interdepartmental collaboration moderates these effects. Specifically, older employees with low interdepartmental collaboration are less innovative and receive worse performance and promotability appraisals than younger employees, but the “age handicap” vanishes when older employees collaborate with members of other departments. Organizations should foster formal or informal collaboration among units to prevent negative consequences of an aging workforce.     

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 new take on voice: the influence of BlackRock’s ‘Dear CEO’ letters

Review of Accounting Studies - Abstract We examine whether broad-based public engagement by institutional investors influences the behavior of portfolio firms. We investigate this question in the...     

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,...     

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.     

A regularity theory of causality for the social sciences

Quality & Quantity - This article discusses a regularity theory of causality (RTC) for the social sciences. With RTC, causality is a relationship between X and Y characterized by three...     

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.