资本结构治理效应:中国上市公司的实证研究

资本结构影响公司治理的结果最终会体现在公司绩效的变化上。本文通过对1992-2004年间我国上市公司资本结构影响公司绩效的实证分析发现:资产主营业务净利润率、经营费用率和资产利用率三个指标比股票价值能更好地解释资本结构对公司绩效的影响;国家股比例对公司绩效的负向影响越来越不显著;法人股比例和负债融资比例对公司绩效有不显著的正向影响等。这些结论表明,完善资本结构是完善我国上市公司治理结构从而提高公司绩效的重要途径之一。     

发行管制条件下的股权再融资市场时机行为及其对资本结构的影响

本文基于A股市场再融资管制环境,检验了A股上市公司股权再融资行为中的市场时机特征及其对资本结构的影响.研究发现,再融资中的市场时机行为显著,表现为两方面:(1)市场高涨时,会有更多的公司申请再融资;(2)申请再融资成功的公司,市场时机适合时融资规模更大.进一步分析发现,无论是申请再融资公司的数量还是再融资规模,市场时机都包括了两部分:一部分是基于股价的时机,另一部分是基于再融资管制政策的时机,后者在配股中约占36%.基于市场时机的更大融资规模导致再融资当年杠杆率下降更多,但由于存在发行价格和规模限制,市场时机对资本结构的 影响短暂.     

知识型团队动态能力构建、团队体系模型与创新运作模式研究

知识型团队是现代组织执行复杂创新任务的重要组织形式.本文从分析知识型团队与知识工作任务的匹配关系入手,在引入知识链及知识链网络等概念的基础上,探讨了基于知识链的知识型团队的动态能力构建机制,分析了围绕知识链网络的知识团队结构体系模型及创新运作机理.     

Absorptive and transformative capacities in nanotechnology innovation systems

We identify managerial challenges offered by an emergent nanotechnology innovation system in which knowledge is dispersed, asymmetric and contested. We argue the proposed models of knowledge absorption and transformation enhance existing theories of knowledge and emergent technology by recognizing how and why knowledge flows among the actors in emergent technology innovation system. We base our argument on combined research evidence from a Delphi study concerning the future of European manufacturing, from which a selected statement has been analyzed, and from analysis of the NanoManufacturing Institute at Leeds University, UK; specifically its work in building ties between different actors associated with nanotechnology. We conclude our paper with suggestions for future research.     

Efficiency and effectiveness of knowledge management systems in SMEs

This paper proposes a 3D fuzzy logic methodology to assess the efficiency and effectiveness of knowledge management systems (KMSs) adopted by small and medium enterprises (SMEs) and identifies a classification bringing together the behaviour of SMEs when adopting KMSs. The proposed methodology was previously tested on an individual SME and then implemented on a sample of SMEs. The results highlight that there is an ample variety of behaviours related to the nature of knowledge and the KMSs used. Specifically, four typologies of behaviour are identified: the efficient and effective SME, the effective but inefficient SME, the efficient but ineffective SME, and the inefficient and ineffective SME. The results show that only 18% of surveyed SMEs are efficient and effective for both KM-Tools and KM-Practices, the remaining 82% are inefficient or ineffective for KM-Tools and/or KM-Practices. Lastly, the paper shows how this methodology may be used by an SME as a managerial tool to suggest appropriate changes to improve the efficient and effective adoption of KMSs supporting SMEs in the knowledge management processes.     

Knowledge sharing for innovation performance improvement in micro/SMEs: an insight from the creative sector

Abstract

As economies become more reliant on innovative, knowledge-intensive firms, understanding the interaction between knowledge and improving innovation performance is increasingly important. Although most UK businesses are micro, small or medium-sized enterprises (micro/SMEs), knowledge management research has tended to focus on large companies Knowledge sharing can be critical for innovation performance, especially for smaller players with limited resources. Our study presents an insight from micro/SMEs operating in the highly knowledge-intensive and innovative games/entertainment software development sector. Using a mixed method approach, we investigate knowledge sharing and its contribution to firm innovation performance improvements. Our findings suggest that micro/SMEs are at the forefront of the creative sector precisely because of their smaller size. Our study reveals evidence of knowledge donation but limited evidence of knowledge collection in the knowledge sharing process. We develop a model highlighting the importance of industry context, individual knowledge and organizational size in knowledge sharing for innovation performance.     

A spanning heuristic for the unordered and ordered matching identification problem

The matching identification problem (MIP) is a combinatoric search problem related to the fields of learning from examples, boolean functions, and knowledge acquisition. The MIP involves identifying a single “goal” item from a large set of items. Because there is commonly a cost associated with evaluating each guess, the goal item should be identified in as few guesses as possible. As in most search problems, the items have a similar structure, which allows an evaluation of each guessed item. In other words, each guessed item elicits partial information about the goal item, i.e. how similar the guess is to the goal. With this information the goal is more quickly identified.The unordered MIP has been studied by Mehrez and Steinberg (ORSA J. Comput. 7 (1995) 211) in which they proposed two different types of algorithms. The purpose of the present paper is to suggest an improved Spanning Heuristic algorithm. Its improvement increases as the problem size increases. Further results and comparisons are derived for the unordered and ordered cases.This research shows that when the search space is very large, it is better to inquire from items that are known not to be the goal (they have been ruled out by previous guesses), for the purpose of acquiring more information about the goal. As the search space is narrowed, it is better to guess items that have not been ruled out.     

Task partitioning in new product development teams: A knowledge and learning perspective

R&D alliances and outsourcing elements of the new product development process are now commonplace practices among many firms. However, little previous work has examined how these organizational choices influence project knowledge and learning. Based on a comparison of three new product development projects in the software industry, this paper examines how task partitioning in the project influences learning and knowledge development within the firm. The paper suggests that internal development projects encourage synthetic learning and development of architectural and tacit knowledge; in contrast, outsourcing and joint ventures encourage analytic learning and development of component and explicit knowledge.