失败学习对企业绩效的影响机制研究

已有文献认为失败学习对企业绩效具有重要作用，但失败学习通过何种途径促进企业绩效提升的研究并不完善。基于失败学习理论，引入资源拼凑和机会识别作为中介变量，构建失败学习影响企业绩效的多路径模型，探索失败学习对企业绩效的驱动路径及内在机理。实证结果表明：失败学习对企业绩效具有显著积极作用，资源拼凑和机会识别分别在失败学习与企业绩效之间起中介作用，资源拼凑和机会识别在失败学习对企业绩效驱动过程中存在链式中介作用，战略柔性能够强化资源拼凑与企业绩效之间的关系，并正向调节资源拼凑的中介作用。研究结论拓展了失败学习对企业绩效的影响路径，对企业复苏和成长具有重要启示。     

Cardinality-based equality of opportunities

We study possible rankings of opportunity profiles. An opportunity profile is a list of opportunity sets, one for each agent in the society. We compare profiles on the basis of the notion of “equality of opportunities”. Our main results show the necessary and sufficient conditions for this comparison to be made using exclusively the information provided by two cardinal measures: the number of common alternatives in all sets of a given profile and the difference between the number of alternatives in the individual sets. We also show that, under additional axioms, we can combine these criteria only in a weighted procedure or in some lexicographic refinements of a weighted procedure.      

Pitfalls of Normal-Gamma Stochastic Frontier Models

Although conceptually pleasing, normal-gamma frontier models lead to difficult estimation problems. It is shown here that unless the sample size reaches several thousands of observations the shape parameter of the gamma density is hard to estimate, and that this carries over to estimates of the stochastic frontier, the individual inefficiencies, and the allocation of the overall variance to the stochastic frontier and to the inefficiencies.     

基于认知视角的创业机会发展过程研究

理性创业时代背景下，如何把握创业机会已成为创业者普遍关心的问题。选取34位创业者作为研究样本，运用文本挖掘和多案例匹配分析方法对创业机会发展过程进行分析、编码，探究创业行为背后的认知机制。研究发现，在机会发现或创造阶段，创业者通过反事实思维推动的创业警觉和创业拼凑两种途径形成创意，并经过新旧认知体系的排斥与趋同形成心智模型，以揭示创业机会发现或创造的认知机制；在机会评估阶段，创业者通过对风险—收益感觉与知觉的多轮反复交互，形成第一人称机会信念和第三人称机会评估，由此揭示创业机会评估的认知机制；在机会开发阶段，创业者形成机会开发内外两种机制，外在机制围绕“探索导向—商业模式创新—新企业成长”展开，内在机制围绕换位思考、效果推理等认知因素推动企业创新、资源获取展开。结论对丰富创业认知理论和管理实践具有重要意义。     

机会窗口、复合式战略与后发企业追赶——基于大华股份的纵向案例研究

基于中国本土化理论——复合基础观，以浙江大华技术股份有限公司（以下简称大华）为例，结合后发企业追赶需要考虑的重要情境即机会窗口，分析后发企业在追赶过程中，如何合理、灵活地采取复合式战略回应机会窗口，并利用机会窗口带来的发展机遇，实现从初始追赶到超越追赶再到行业前沿的追赶历程。研究发现，同一行业内不同机会窗口之间环环相扣、相互影响，某一机会窗口的出现也会触发其它机会窗口出现，进而引致整个行业机会窗口涌现；基于复合基础观视角，后发企业追赶路径的演变过程为：最初以技术模仿式创新为导向实现边缘赶超，继而以市场把握和扩张为导向实现商业模式创新，然后以全面协同创新为导向实现系统竞争力提升；后发企业通过实施复合式战略回应机会窗口的开启，能够帮助其更好地把握住发展机遇，实现追赶；与追赶路径演变相关联，随着企业内部资源与能力的积累，战略回应机制也相应地呈现为“被动回应—主动回应—引领拓展”的演变过程。     

Testing for unit roots in time series models with non-stationary volatility

Many of the key macro-economic and financial variables in developed economies are characterized by permanent volatility shifts. It is known that conventional unit root tests are potentially unreliable in the presence of such behaviour, depending on a particular function (the variance profile) of the underlying volatility process. Somewhat surprisingly then, very little work has been undertaken to develop unit root tests which are robust to the presence of permanent volatility shifts. In this paper we fill this gap in the literature by proposing tests which are valid in the presence of a quite general class of permanent variance changes which includes single and multiple (abrupt and smooth-transition) volatility change processes as special cases. Our solution uses numerical methods to simulate the asymptotic null distribution of the statistics based on a consistent estimate of the variance profile which we also develop. The practitioner is not required to specify a parametric model for volatility. An empirical illustration using producer price inflation series from the Stock–Watson database is reported.     

The Role of Omitted Variables in Identifying a Long-run Equilibrium Relationship for the Italian Government Growth

We discuss the role of omitted variables in the long run empirical modeling of the Italian government growth based on a Wagner's Law framework. We identify a non-spurious long-run relationship between general government expenditure and domestic product only when our Wagner's Law model is enhanced by a measure of bureaucratic power, as a supply-side variable, and by the ratio of local to state expenditure, as an institutional factor that captures the division of competencies between local and central government in allocating public expenditure. This result is independent from the Wagner's Law specification chosen. The persistence profile analysis shows a slow adjustment to equilibrium for the estimated government growth relationship following system-wide shocks, pointing to rigidities and complex functioning of the public sector.     

农业创业情境下商业模式设计的影响机制研究——基于模糊集定性比较分析

农业创业者如何通过整合与管理资源与能力，设计新颖型商业模式创造更多价值，是实现乡村振兴战略的关键措施。文章基于资源编排、商业模式理论，以央视《致富经》栏目40个案例为样本，运用模糊集定性比较分析（fsQCA）方法，剖析资源编排、机会能力、创业学习所构成的前因变量组态对农业创业活动中商业模式设计的影响机制。研究发现，资源编排在农业创业活动中发挥不可或缺的关键作用；相较于资源结构化和资源捆绑，资源利用在新颖型商业模式设计中的作用更为突出；机会能力须与资源编排共同作用，方可实现新颖型商业模式设计；在资源编排作用缺乏时，创业学习的发挥有助于新颖型商业模式设计的形成。研究成果诠释了农业创业情境下资源编排、机会能力与创业学习对商业模式设计的影响机制，为开展农业创业活动提供指导。     

Exploring consumer attitudes to online collaborative consumption: A typology of collaborative consumer profiles

Online collaborative consumption enhances peer networks, members of which communicate, collaborate, and even deliver services to one another via digital sharing platforms. Despite the tremendous increase in collaborative consumption, due in large part to the development of the Internet, the reality of the economic and social movements that underpin this trend is much less visible. Of course, not all consumers seek collaborative consumption or interact through online platforms. Using a qualitative approach, this paper aims to investigate motivational factors and barriers against collaborative consumption and to establish a typology of collaborative consumer profiles, identifying the most suitable type of online sharing platforms for each profile. The findings reveal the following collaborative consumer profiles: committed, pragmatists, intermittent, and skeptical, each demonstrating different preferences for the different type of online sharing platform.     

Reliable Inference in Categorical Regression Analysis for Non‐randomly Coarsened Observations

In most surveys, one is confronted with missing or, more generally, coarse data. Traditional methods dealing with these data require strong, untestable and often doubtful assumptions, for example, coarsening at random. But due to the resulting, potentially severe bias, there is a growing interest in approaches that only include tenable knowledge about the coarsening process, leading to imprecise but reliable results. In this spirit, we study regression analysis with a coarse categorical‐dependent variable and precisely observed categorical covariates. Our (profile) likelihood‐based approach can incorporate weak knowledge about the coarsening process and thus offers a synthesis of traditional methods and cautious strategies refraining from any coarsening assumptions. This also allows a discussion of the uncertainty about the coarsening process, besides sampling uncertainty and model uncertainty. Our procedure is illustrated with data of the panel study ‘Labour market and social security' conducted by the Institute for Employment Research, whose questionnaire design produces coarse data.