基于元分析的跨界搜索与企业创新绩效关系研究

跨界搜索在企业创新活动中的作用日益凸显,相关研究也非常活跃,但结果仍存在差异。基于此,本文对2001-2019年期间的53篇实证文献、26812个样本的55个效应值进行了元分析,证实了跨界搜索对企业创新绩效的促进作用,并且发现,企业的国别差异、行业特征、创新能力能够调节跨界搜索对其创新绩效的贡献程度,中国企业、制造业企业、非高创新能力企业的跨界搜索活动对创新绩效的积极影响更为显著;跨知识边界的搜索均对企业创新绩效存在显著的正向影响,但程度上存在差异,具体表现在,扩大搜索宽度比加强搜索深度积极影响更大,本地搜索的促进作用比非本地搜索更大,市场知识跨界搜索的积极影响比技术知识跨界搜索更大。     

The micro-determinants of meso-level learning and innovation: evidence from a Chilean wine cluster

Most analyses of the relationship between spatial clustering and the technological learning of firms have emphasised the influence of the former on the latter, and have focused on intra-cluster learning as the driver of innovative performance. This paper reverses those perspectives. It examines the influence of individual firms’ absorptive capacities on both the functioning of the intra-cluster knowledge system and its interconnection with extra-cluster knowledge. It applies social network analysis to identify different cognitive roles played by cluster firms and the overall structure of the knowledge system of a wine cluster in Chile. The results show that knowledge is not diffused evenly ‘in the air’, but flows within a core group of firms characterised by advanced absorptive capacities. Firms’ different cognitive roles include some—as in the case of technological gatekeepers—that contribute actively to the acquisition, creation and diffusion of knowledge. Others remain cognitively isolated from the cluster, though in some cases strongly linked to extra-cluster knowledge. Possible implications for policy are noted.     

University spillovers and new firm location

This paper examines the impact of locational choice as a firm strategy to access knowledge spillovers from universities. Based on a large dataset of publicly listed, high-technology startup firms in Germany, we test the proposition that proximity to the university is shaped by different spillover mechanisms—research and human capital—and by different types of knowledge spillovers—natural sciences and social sciences. The results suggest that spillover mechanisms as well as spillover types are heterogeneous. In particular, the evidence suggests that new knowledge and technological-based firms have a high propensity to locate close to universities, presumably in order to access knowledge spillovers. However, the exact role that geographic proximity plays is shaped by the two factors examined in this paper—the particular knowledge context, and the specific type of spillover mechanism.     

A growing trend toward knowledge work in Canada

This paper answers three questions related to the growing trend toward knowledge occupations in Canada: (i) What was the magnitude of the trend between 1971 and 1996? (ii) Was the trend a widespread phenomenon or was it restricted to specific industries? (iii) What are the proximate causes of the trends? Using five censuses—1971, 1981, 1986, 1991, 1996—and the input/output (I/O) data, the paper provides evidence that the Canadian economy is becoming increasingly knowledge-based, although the upgrading trends differ across knowledge occupations. Moreover, we find that this phenomenon is spread across all industrial sectors. Finally, using a decomposition analysis borrowed from Wolff and Baumol, three factors—the substitution effect, the productivity-lag effect and the demand effect—have been examined in order to shed some light on these trends. We find that these effects vary according to the nature of the knowledge involved in these different groups of occupations, thus reflecting not only the importance of the technological change ‘skill bias’ but also the increasing complexity of controlling and managing the new economic activities.     

风险投资网络社群信息传播对投资绩效的影响

信息传播有利于风险投资克服信息不对称性和项目不确定性等关键问题,对风险投资网络社群具有重要意义。利用2000至2015年CVsource数据库中风险投资数据,本文研究风险投资网络社群信息传播对投资绩效的影响及其机理。研究发现,风险投资网络社群信息传播对投资绩效有显著影响,具体表现为项目信息传播对投资绩效呈先增后减的倒U型影响,经验信息传播对投资绩效呈显著正向影响。知识获取分别在项目信息传播和经验信息传播与投资绩效的关系中具有部分中介作用。另外,吸收能力显著负向调节知识获取对投资绩效的正向影响。上述结果意味着,信息传播不仅可以直接作用于投资绩效,而且可以通过知识获取及吸收能力对投资绩效产生间接作用。利用一个社会网络的分析框架,本文论证了信息传播对风险投资绩效的影响机理,并且为风险投资网络社群行为优化以及投资绩效提升提供了经验证据。     

企业内部R&D投入、外部知识获取与创新绩效关系研究

开放式创新成为企业获取外部知识资源、提升创新能力的重要途径之一。目前将内部R&D投入和外部知识获取同时作为调节变量综合考虑其对创新绩效影响的研究成果较为欠缺。论文以我国制造业领域企业为研究对象,在文献回顾和述评基础上,基于科技统计数据和2,905样本企业数据,借鉴Tobit 估计模型,实证分析企业内部R&D投入和外部知识获取这两类R&D活动对创新绩效的影响。研究表明：逐渐依赖于外部R&D活动、获取外部知识资源的企业具有较高创新绩效水平,但当超过一定临界值的时候,会产生替代效应,即更多参与外部R&D活动会使企业绩效水平下降;对于知识储备较高的高技术企业来说,进一步开放R&D创新边界,其机会成本相对较高。     

反思性知识重构、企业即兴能力及其创新效应

本研究探讨并验证了反思性知识重构与即兴能力对创新绩效的影响机理。以196家科技型企业为样本进行层次回归分析,结果表明：反思性知识重构是提高企业创新绩效的重要决定因素;并且,反思性知识重构可通过培育组织即兴能力间接地促进创新绩效。当环境动荡性较高时,组织即兴能力的中介效应更强。此外,还发现技术环境扰动会增强反思性知识重构对即兴能力“创造性”维度的影响,而市场环境扰动会增强反思性知识重构对即兴能力“即时性”维度的影响。本文打开了反思性知识重构影响创新绩效的“黑箱”,并且明确了反思性知识重构提高创新绩效的边界条件。     

Knowledge complexity and the mechanisms of knowledge generation and exploitation: The European evidence

A knowledge complexity trade-off can be identified if and when the complexity of the stock of knowledge engenders positive effects in the recombinant generation of new technological knowledge but negative ones in its exploitation in terms of productivity gains. On the one hand, the complexity of the stock of knowledge increases the scope for recombination and hence the amount of knowledge that each firm is able to generate with a given budget. On the other, the complexity of the stock of knowledge has controversial effects on productivity: the indirect effects -via the larger amount of knowledge generated upstream- are positive but the direct ones can be negative if they generate difficulties in the exploitation of a highly heterogeneous stock of knowledge. The econometric test on the European regions in the years 1997–2009, provides strong empirical evidence about the relevance of the composition of the stock of quasi-public knowledge and its twin positive effects in terms of the direct support of the knowledge generation function and of the indirect one on productivity growth. Moreover, the analysis highlights the negative direct effects on productivity dynamics, though with substantial heterogeneity across different groups of regions.     

Balancing act: Government roles in an energy conservation network

Government-led interorganizational alliance networks present a sensible opportunity to overcome many societal challenges through collaborative governance. In particular, few researchers have studied alliance networks in the field of energy conservation in commercial buildings—a sector with unique barriers to greater diffusion of innovative cost-saving strategies. We applied an analytic inductive case-based method and social network analysis to study one particular alliance network: the United States Commercial Building Energy Alliances representing interests from retail, commercial real estate, and healthcare sectors. This alliance network was initiated by the United States Department of Energy, with assistance from several federally funded research laboratories in the United States, to promote the diffusion of knowledge and ultimately encourage greater deployment of energy efficiency and clean energy strategies in commercial buildings. We draw upon interview data from 28 cases of private, non-profit, and governmental organizations and complete network data from the alliance participants. We honed in on eight focal cases of governmental organizations to provide insight on how the four forms of energy and environmental data, information, and knowledge shared within an alliance network address the challenge of a vastly underutilized energy resource, namely conservation. Further, we identify and discuss the public's four roles—Commissioner, Interpreter, Marketer, and User—in providing balance to the diffusion of both private and public goods in a network.     

Going beyond technology: Knowledge sharing as a tool for enhancing customer-oriented attitudes

Numerous articles, books and essays have shown that ongoing efforts to meet customers’ needs characterize market leaders. For a firm to successfully develop customer-oriented attitudes throughout the entire organization, employees at all levels and sections need to be committed to providing a high level of service. It is therefore essential to understand what drives employees – especially those who do not interact daily with customers – to adopt a customer-oriented attitude. The aim of this study is to shed some light on one facet of this relationship, namely the mechanism of knowledge sharing that may impact employee customer orientation. The underlying notion is that technology, in its various advanced forms of CRM software, enhances and enables client “knowing.” In other words, it leads to a greater ability on the part of employees to share knowledge, which brings about real customer orientation.This paper provides empirical evidence, based on a sample of 345 Hi-Tech workers from a telecommunication company, of a link between sharing explicit knowledge and tacit knowledge to enhance customer orientation. The findings indicate that sharing tacit knowledge has a positive effect on increasing employee customer orientation and increases sharing of explicit knowledge, while also strengthening communication about customers in the organization. It is concluded that firms should encourage tacit knowledge sharing and its transformation by technology into explicit knowledge to augment employees’ customer-oriented attitudes.     

高管团队政府工作经验、政治网络与企业绩效的关系研究

基于高层梯队理论与资源依赖理论,分析转型经济下,具有政府工作经验的高管团队对企业绩效与战略选择的影响。提出高管团队的政府工作经验会直接促进企业绩效的提高,同时带来企业的政治网络活动,从而提高企业的绩效。     

Distributed R&D, cross-regional knowledge integration and quality of innovative output

We explore the impact of geographic dispersion of a firm's R&D activities on the quality of its innovative output. Using data on over half a million patents from 1127 firms, we find that having geographically distributed R&D per se does not improve the quality of a firm's innovations. In fact, distributed R&D appears to be negatively associated with average value of innovations. This suggests that potential gains from access to diverse ideas and expertise from different locations are, on average, offset by difficulty in achieving integration of knowledge across multiple locations. To investigate whether the innovating teams that do manage cross-fertilization of ideas from different locations achieve more valuable innovations, we analyze innovations for which there is evidence of such knowledge cross-fertilization along any of the followings dimensions: knowledge sourcing from other locations within the firm, having at least one inventor with cross-regional ties, and having at least one inventor that has recently moved from another region. Analysis along all three dimensions consistently reveals a direct positive effect cross-regional knowledge integration has on innovation quality, as well as a positive interaction effect of cross-regional knowledge integration and distributed R&D for innovation quality. More generally, our findings provide new evidence regarding the importance of cross-unit integrative mechanisms for achieving superior performance in multi-unit firms.     

Agent-based modeling of knowledge dynamics

Knowledge is distributed unevenly through most enterprises. Hence, flows of knowledge (e.g., across time, people, locations, organizations) are critical to organizational efficacy and performance under a knowledge-based view of the firm. However, supported principally by narrative textual theory in the emerging knowledge management (KM) field, the researcher has difficulty describing how different kinds of knowledge will flow through various parts of an organization. This causes difficulty also for predicting the effects of alternate approaches to dispersing knowledge that ‘clumps’ in various areas. This problem is also manifest for the KM professional, who lacks clear theory or tools to anticipate how any particular information technology or other managerial intervention may enhance or impede specific knowledge flows in the enterprise. In this expository article, we build upon a steady stream of research in computational organization theory to develop agent-based models of knowledge dynamics. This work draws from emerging theory for multidimensional representation of the knowledge-flow phenomenon, which enables the dynamics of enterprise knowledge flows to be formalized and emulated through computational models. This approach provides the means for knowledge-flow processes to be visualized and analyzed in new ways. Computational experimentation enables the performance of many alternate process designs and technological interventions to be compared through examination of dynamic models, before committing to a specific approach in practice. We illustrate this research method and modeling environment through semi-formal representation and agent-based emulation of several knowledge-flow processes from the domain of software development. We also outline key directions for the new kinds of KM research and practice elucidated by this work.     

从科学到技术的知识传播机理研究：基于知识基因

基础研究是技术创新的重要源泉。从基础研究到技术创新的知识转化规律具有重要的理论与实践价值。鉴于以往研究中专利引文方法的局限性,本研究基于知识基因这种特殊知识单元,从知识内容流动的视角,定量研究从科学到技术的知识传播机理。以人工智能技术为研究案例,识别技术领域的知识基因和专利引用的5个关键基础学科,研究各学科与技术领域的知识关系。通过构建知识基因的传播级联网络模型,对知识基因从科学到技术的跨领域传播模式进行分析。研究发现,相比于专利科学引文,知识基因流动能够揭示从各学科到技术领域的更加真实的知识传播关系;知识基因的短期影响力水平与来源学科有关;知识基因从科学到技术的跨领域传播受到马太效应影响;受异质性知识组合效应的影响,跨领域知识基因在传播网络规模、寿命、影响力及创新“催化”能力方面优于技术领域一般知识基因,后者的产生速度和传播速度则更快。研究结论为进一步深入探究从基础研究到技术创新的知识转化规律提供了微观层面的理论基础,同时,对新兴技术领域的创新预测、基础学科布局以及科技政策的制定具有一定参考价值。     

创业拼凑与科技型小微企业创业绩效研究：基于先前经验的视角

资源约束是科技型小微企业创业过程中面临的普遍问题,因此探索突破约束并实现企业快速成长的途径成为创业领域研究的热点。本文基于企业资源观和人力资本理论视角,构建了创业拼凑、先前经验以及科技型小微企业创业绩效三者之间的概念模型,并利用结构方程模型对317家科技型小微企业调研数据进行了实证分析,由此得出了相应的结论：（1）创业拼凑、先前经验与科技型小微企业创业绩效正相关;（2）创业拼凑分别与创业经验、行业经验和工作经验正相关;（3）创业经验、行业经验在创业拼凑与创业绩效之间起中介作用,但工作经验未在创业拼凑与创业绩效之间起中介作用。     

The determinants of regional innovation in Europe: A combined factorial and regression knowledge production function approach

The present paper studies the determinants of regional innovation in Europe through a knowledge production function approach that combines factorial analysis and regression. Our dependent variable are the patents while we used initially 21 explanatory variables that were converted—by a factor analysis—into five non-observable “hypothetical” variables reflecting five important aspects of the innovation systems: the National environment, the Regional environment, Innovating firms, Universities and the R&D done by Public Administration. Our results show that all factors have a statistically significant effect on the production of knowledge (patents), although they present very different impacts.     

创业失败学习与国际新创企业后续创新绩效

失败经验是一种宝贵的创业经验,可为后续创业活动提供具有高价值的隐性知识,提高了企业后续创新绩效。基于知识管理理论和组织学习理论,立足于创业失败学习与国际新创企业后续创新绩效之间的关系,构造了一个多重中介模型探究了创业失败学习、知识库、知识应用对国际新创企业后续创新绩效的作用机制。本文采用问卷调研法,以198份具有创业失败经验的国际新创企业作为样本,通过spss21.0 软件和Mplus7.0软件,对模型加以验证。结果表明：第一：创业失败学习与国际新创企业后续创新绩效具有显著的相关关系;第二：知识库和知识应用在创业失败学习和创新绩效之间起链式中介作用;第三：在考虑了知识库和知识应用的情况下,创业失败学习与创新绩效之间的关系不显著。研究模型打开了创业失败学习和后续创新绩效间的黑箱,对于创业者更好的进行创业失败学习以促进企业后续创新发展带来了一定的启发。     

组织结构、知识吸收能力与研发团队创新绩效:一个跨层次的检验

面对全球化的竞争,研发团队在企业中的价值已经受到普遍关注,但是它与组织结构的关系及内在机制还有待进一步研究.本研究论述了企业组织结构通过知识吸收能力中介影响研发团队创新绩效的过程.研究结果显示:集权程度、反馈速度、部门整合能力对知识吸收能力具有正向影响;知识吸收能力对研发团队创新绩效具有正向影响;知识吸收能力在集权程度、反馈速度与团队创新绩效的关系之间具有部分中介效用,在部门整合能力与团队创新绩效之间具有完全的中介效用.本研究在推进相关理论研究的同时,也为企业研发团队创新实践提供了一定的启示.     

Genetically optimized Hybrid Fuzzy Set-based Polynomial Neural Networks

We investigate a new category of fuzzy-neural networks such as Hybrid Fuzzy Set-based Polynomial Neural Networks (HFSPNN). These networks consist of a genetically optimized multi-layer with two kinds of heterogeneous neurons such as fuzzy set-based polynomial neurons (FSPNs) and polynomial neurons (PNs). We have developed a comprehensive design methodology that helps determine the optimal structure of networks dynamically. The augmented genetically optimized HFSPNN (referred to as gHFSPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of gHFSPNN leads to the selection of preferred nodes (FSPNs or PNs) available within the HFSPNN. In the sequel, the structural optimization is realized via GAs, whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFSPNN is demonstrated through intensive experimentation where we use a number of modeling benchmarks—synthetic and experimental datasets are already being used in fuzzy or neurofuzzy modeling.     

Analyzing imbalance among homogeneous index servers in a web search system

The performance of parallel query processing in a cluster of index servers is crucial for modern web search systems. In such a scenario, the response time basically depends on the execution time of the slowest server to generate a partial ranked answer. Previous approaches investigate performance issues in this context using simulation, analytical modeling, experimentation, or a combination of them. Nevertheless, these approaches simply assume balanced execution times among homogeneous servers (by uniformly distributing the document collection among them, for instance)—a scenario that we did not observe in our experimentation. On the contrary, we found that even with a balanced distribution of the document collection among index servers, correlations between the frequency of a term in the query log and the size of its corresponding inverted list lead to imbalances in query execution times at these same servers, because these correlations affect disk caching behavior. Further, the relative sizes of the main memory at each server (with regard to disk space usage) and the number of servers participating in the parallel query processing also affect imbalance of local query execution times. These are relevant findings that have not been reported before and that, we understand, are of interest to the research community.