Objective methods for graphical structural learning

Graphical models are used for expressing conditional independence relationships among variables by the means of graphs, whose structure is typically unknown and must be inferred by the data at hand. We propose a theoretically sound Objective Bayes procedure for graphical model selection. Our method is based on the Expected-Posterior Prior and on the Power-Expected-Posterior Prior. We use as input of the proposed methodology a default improper prior and suggest computationally efficient approximations of Bayes factors and posterior odds. In a variety of simulated scenarios with varying number of nodes and sample sizes, we show that our method is highly competitive with, or better than, current benchmarks. We also discuss an application to protein-signaling data, which wieldy confirms existing results in the scientific literature.     

Trading off learning and performance: Exploration and exploitation at work

Employees are increasingly given control over how they learn, and their choices for training are diverse and varied, yet employees must balance competing demands. On one hand, they are expected to be increasingly efficient in their current job duties – on the other hand, they are expected to develop new skills and competencies that enable them to adapt and respond to changing job demands. Drawing from the organizational learning literature, we propose a model of worker and work characteristics that inform choices between two mindsets related to learning at work. The first mindset is exploration, or the pursuit of learning outside one’s current knowledge domain; the second mindset is exploitation, the refinement/deepening of one’s existing knowledge stock focusing on the task at hand. We further propose that these strategic choices, or trade-offs, influence employee learning and performance in unique ways, with different implications for both routine and adaptive performance. Finally, we incorporate the notions of feedback loops and risk assessments that influence ongoing decisions between exploration and exploitation mindsets. Recommendations for future research and extensions of the theoretical model are also proposed.     

创业失败经验对连续创业意愿的影响——创业失败学习与市场动荡性的作用

基于经验学习理论，探究创业失败经验如何通过创业失败学习影响创业者连续创业意愿，以及市场动荡性的调节作用。对176位有失败经历的创业者进行问卷调查，结果表明：创业失败经验对创业失败学习和连续创业意愿均有显著正向影响；创业失败学习在创业失败经验与连续创业意愿关系间起中介作用；市场动荡性负向调节创业失败学习与连续创业意愿的关系，即市场动荡性越高，创业失败学习与连续创业意愿间的关系越弱。研究结论对于拓展创业失败经验与连续创业意愿研究、帮助创业者从失败中复原，以及激励连续创业具有重要理论价值和实践意义。     

On the existence of the ex post symmetric random entry model

This paper studies symmetry among countably infinitely many agents who randomly enter into a stochastic process, one for each period. Upon entry, they observe only the current period signal and try to draw inference about the underlying state governing the stochastic process. We show that there exist random entry models under which agents are ex post symmetric. That is, all agents have identical posterior belief about the underlying states, although they are not ex ante symmetric. The form of the posterior belief is uniquely pinned down by ex post symmetry and a stationarity condition. Our results provide a common prior foundation for the model studied in Liu and Skrzypacz (2014).     

创业企业何以提高创新绩效——基于创业学习与商业模式创新协同联动视角的QCA方法

以150个创业企业为样本，基于创业学习和商业模式创新理论，运用模糊集定性比较分析方法（fsQCA），探究经验学习、认知学习、新颖型商业模式创新和效率型商业模式创新对创新绩效的影响路径及机制。研究发现，存在新颖型商业模式创新等4条创新绩效产出关键路径；相较于效率型商业模式创新，新颖型商业模式创新在关键路径中更容易提高创新绩效；利用QCA方法证实了影响创业企业创新绩效的组态内部各要素之间的替代性。结论丰富了创新绩效产出内部机制，可为创业企业提高创新绩效提供指导和借鉴。     

Adoption of precision farming tools: A context-related analysis

This paper deals with precision farming tools (PFTs), a way of farming which relies on specialized equipment, software and information technologies services, whose importance is underlined in recent documents of the European Union. Precision farming is an integrated and sustainable farm management system making use of modern technologies to increase farm’s profitability, by reducing environmental impact. In this paper we explore the complex mechanisms that affect PFT’s adoption by Italian farmers. More precisely, we try to analyse the context-related factors affecting adoption of PFTs in the Italian farms.Little research has been carried out in Italy on this topic, therefore our paper tries to fill a gap in literature. In order to investigate the process of technology adoption related to precision agriculture, a questionnaire was submitted to a sample of Italian farms. The questionnaire has been structured in order to apply the AKAP (Awareness, Knowledge, Adoption, Product) sequence. Our analysis underlines that context-related factors are fundamental dimensions to be explored in order to specify uptake of PFTs. Therefore, the paper has relevant policy implications, within the context of a new participatory approach to agricultural innovation characterized by bottom-up processes boosted by farmers, which has informed the recent policies of agricultural innovation at the EU level.     

军民融合社会关系网络对军民融合新创企业成长的影响

军民融合新创企业是推动我国国防建设和社会经济融合发展的重要力量，军民融合社会关系网络具有丰富的异质性资源，可以有效促进军民融合新创企业成长。借鉴社会网络理论，构建以关系深度、关系广度、关系高度为代表的军民融合社会关系网络、耦合共生与军民融合新创企业成长理论模型，通过对收集的304份军民融合新创企业问卷数据进行实证分析，结果发现：军民融合社会关系网络对军民融合新创企业成长具有正向影响；耦合共生在军民融合社会关系网络与军民融合新创企业成长间发挥中介作用；创业导向显著调节耦合共生与军民融合新创企业成长的关系。     

Agglomeration economies and university program creation in the knowledge economy

Existing academic literature on the relationship between agglomeration economies and university activities is both under-theorized and relatively sparse in terms of empirical examination. This paper addresses each of these voids by contributing and analyzing a market model of pro-revenue education program creation such as graduate-level executive business education (e.g. EMBA) that reveals some intriguing characteristics. For instance, it shows that demand for these pro-revenue programs is inelastic and therefore uniquely determines their availability. More specifically, we show that through agglomeration economies these types of education programs are more likely to emanate from universities located in metropolitan areas and from less academically prestigious universities. Regression analysis of a cross-section of national public universities lends support to important facets of our formal model by suggesting that agglomeration economies continue to increase the probability of offering EMBA programs through a city size of approximately 2.12 million and that the probability that a given business school will offer an EMBA is negatively related to the academic prestige of the institution to which it is affiliated.