纵向研发合作的研发绩效和成本分担机制

在日益激烈的市场竞争环境下,企业往往会选择研发合作以降低研发的成本和风险,而纵向研发合作已成为其中的重要模式。构建了一个存在两个上游企业和多个下游企业所组成的复杂双层市场结构,对上下游企业实施纵向研发合作的产量变化和利润变化进行了分析,在此基础上探讨了研发合作的最优研发绩效。研究了纵向研发合作下利润匹配型和固定比例型两种分担机制的分担系数和净利润等经济指标,得出了一些符合现实经济活动的结论。     

Exploiting and transferring presentational knowledge assets in R&D organizations

Nowadays, how to exploit and transfer the value of knowledge assets effectively has been the primary challenge faced by global R&D organizations. Surprisingly, there seems to be little argument about managing presentational knowledge assets, which are widely used by knowledge workers to present their ideas, proposals, findings and reports. This paper develops the management model and related IT enabling tools that support users to better exploit and transfer presentational knowledge assets. The solution integrates text extractor, slideshow generator, knowledge repository, content-based retrieval and ontology-enabled search engine along with the goal of portraying the search results in a visual navigation form. The performance satisfaction of the proposed system was proved statistically by conducting the user’s survey of effectiveness and usability. This solution has demonstrated to be a feasible way for better managing contents, prompting cognitive learning, improving presentation production and presentational knowledge transformation, and consequently facilitates the value leverage of the presentational knowledge assets.     

Knowledge-sharing motivations affecting R&D employees' acceptance of electronic knowledge repository

Why would R&D employees be willing to use an electronic knowledge repository (EKR) for knowledge-sharing? This study integrates a technology acceptance model (TAM) to investigate the influence of extrinsic and intrinsic motivations on R&D employees' acceptance of an EKR for knowledge-sharing. Empirical data were collected through a survey, which gathered data from 225 employees working in 10 organisations in Taiwan. The results indicated that (1) reputation and reciprocity were found to be two important antecedents to perceived usefulness and perceived ease of use; (2) altruism was also found to be an important antecedent to perceived ease of use; (3) reputation was the most influential factor of perceived usefulness, and another influential factor of perceived usefulness was reciprocity. Three knowledge-sharing motivations that significantly affect the perceived ease of use were listed as reciprocity, altruism, and reputation, according to the relative importance; (4) altruism plays an important role in explaining the EKR usage intentions for knowledge-sharing both directly and indirectly; and (5) the results were consistent with the propositions of TAM. This study contributes theoretically and empirically to the body of EKR usage research and also has practical implications.     

Adoption of the Internet for knowledge acquisition in R&D processes

This research investigated Internet-based knowledge search patterns of engineers and scientists working in R&D for companies in the pharmacological and information technology sectors in Israel. Building on earlier work that considers the multidimensional nature of the relative advantage construct, we examine how perceptions of learning, informational convenience, and trust affected intentions to use the Internet to acquire new knowledge. In particular, these perceptions were studied with regard to both active and passive modes of interaction. We also considered here which types of technological knowledge are acquired by researchers, and how that differs across two professional communities of practice – scientists and engineers. This study sheds light on how R&D workers perceive the relative advantage of acquiring necessary knowledge through passive and active modes of communication with other researchers that are facilitated by the Internet. Findings are of interest to the literature on knowledge spillover because the capability of an organisation to acquire, disseminate, and exploit knowledge is crucial to R&D efforts.     

Finding research trend of convergence technology based on Korean R&D network

Traditionally, collaboration network or citation network is used to answer the old question how scientists or engineers interact with each other. This paper introduces a R&D network to make up the missing aspect of the traditional approaches about using multi-sources and to find out the trend of convergence technology R&D in Korea. We collect data about human resources and national R&D projects from Korean national R&D databases, and then construct a weighted network between experts by using meta-data mapping and the network folding technique. And we apply Newman’s grouping algorithm that is generalized to a weighted network for detecting the community structure of the network. Gathering data from multi-sources is useful to reveal the structure of network rather than to use only one database. Lastly, we perform a network analysis to examine important experts. The result shows significant information about research trend and core experts in Korea. We expect this study will be helpful in three ways: (1) how to make a network from heterogeneous multi-sources, (2) how to figure out the current situation of convergence technology R&D, (3) how to discover who are important people in Korean convergence technology R&D network. And this paper is just a cornerstone of the work to investigate the current situation of national R&D projects in Korea.     

Developing an research and development (R&D) process improvement system to simulate the performance of R&D activities

Because of a shorter R&D cycle time and the increasing complexity of technology development, efficient decision support systems for R&D activities are necessary to facilitate R&D processes. In particular, small and medium enterprises (SMEs) require efficiency of R&D projects due to a lack of R&D budgets and resources. Therefore, this paper aims to develop a system which can assess current levels of R&D processes of companies and improve problematic processes. To this end, the proposed system applies a standard R&D process to evaluate the R&D level of companies, including four types of database and three modules: performance level analysis, comparison analysis, and performance simulation analysis. First, the module of performance level analysis aims to draw strong and weak R&D processes of companies, using three factors: importance, performance goal and current performance on each process. The second module provides the function of comparison analysis that compares the performance level of a company with that of others. Finally, the performance simulation analysis investigates influences of critical processes on R&D outcomes and predicts how much the processes can enhance technical, economic and process outcomes. In particular, a case study is presented to illustrate the application of the proposed system to an IT company. This system can help managers enhance their R&D performance by presenting necessary improvements on critical processes.     

基于R&D溢出的集中研发联盟合作行为

研究了在联盟合作R&D中R&D溢出、R&D溢出的抑制能力以及创新能力对联盟成员的R&D投资策略的影响, 确定了联盟获得最大期望投入的最优分配方式. 研究表明: 1) R&D溢出和创新能力对联盟成员增加R&D投入有正效应; 企业抑制R&D溢出的力量对R&D投入有负效应, 但影响力很弱. 2) 对于创新能力强的联盟, 平均分配为最优分配方式; 对于创新能力弱的联盟, 市场规模低时选择按投入比例分配方式, 市场规模高时选择平均分配方式.     

K-means method for rough classification of R&D employees' performance evaluation

This paper proposes an approach that can roughly cluster a data set with fuzzy linguistic entries as a prior data arrangement for performance evaluation of R&D employees. The extension principles of fuzzy linguistic numbers are used to modify the K‐means method for handling the linguistic data set. We define the absolute difference of fuzzy linguistic variables as their fuzzy distance. Based on this definition, the K‐means approach can be modified slightly for clustering purposes. The performance of employees engaged in designing and R&D‐oriented jobs is possibly related to some qualitative attributes and the evaluation of such attributes for each employee has a tendency toward semantic scales. In the proposed approach, the supervisor can evaluate the performance of each employee directly with a semantic scale. The modified K‐means approach can roughly cluster their performance into different classes in advance of applying some other sophisticated processes.     

A study on framework for effective R&D performance analysis of Korea using the Bayesian network and pairwise comparison of AHP

To effectively evaluate and analyze R&D performance, it is necessary to measure the relative importance of performance analysis factors and quantitative analysis methods that consider the objectivity and relevance of detail factors that constitute performance evaluation. This study suggests a framework for R&D performance evaluations by computing weights through an AHP (Analytical Hierarchy Process) expert survey and by applying a Bayesian Network approach whereby, through which, giving objectivity and allowing inference analyses. This framework can be used as a performance analysis indicator, which uses input and output performance factors in order to perform quantitative analysis for projects. We can quantitatively define the satisfactory level of each project and each performance analysis factor by assigning probability values. It is possible to analyze the relationship between project evaluation results (qualitative evaluation) and performance analysis indicator (quantitative performance). This performance analysis framework can infer posteriori probability using the prior probability and the likelihood function of each performance factor. In addition, by inferring the relationships among performance factors, it allows performing probability analyses on the successful and unsuccessful factors, which can provide further feedback. In conclusion, the framework would improve the national R&D program in terms of financial investment efficiency by aligning budget allocation and performance evaluation.     

Tacit knowledge sharing in IT R&D teams: Nonlinear evolutionary theoretical perspective

Tacit knowledge sharing influences the performance of IT R&D teams. However, information regarding the mechanism of tacit knowledge sharing is limited. Accordingly, we develop a nonlinear dynamic model to explore the influence of structural changes on tacit knowledge sharing behavior in an IT R&D team, particularly in response to gradual changes in payoff structures. The following results were observed：(1) Certain situations and a traditional correlation analysis confirmed that the current contradictions in the influence of reward systems on knowledge sharing behavior are unified. (2) Under special conditions, the influences of several critical factors (e.g., reciprocity, penalty of social reputation, and supervising mechanism) lose efficacy. As an alternative, managers can only enhance the reward system or reduce sharing cost. The effectiveness of knowledge sharing substantially improves only once it reaches certain critical thresholds. (3) During a catastrophe, a team’s behavior may become immune to the deterioration of payoff structures. However, sudden jumps (i.e., from sharing to hiding knowledge) may occur when another threshold is reached. In summary, once team members experience a sudden jump, retrieving the previous cooperative status becomes difficult.     

Dynamic R&D with strategic behavior

We consider a two-player infinite-horizon discrete-time game where the players invest in R&D in order to develop a new technology to reduce production costs. We compute firms’ equilibrium R&D investment strategy as a function of the level of knowledge in the economy. The latter changes endogenously with firms’ decisions to invest in R&D. We show that firms do not invest in R&D if the knowledge level is too low, while both firms do R&D when the level of knowledge is high. However, there is an intermediate knowledge region where there are two pure Nash equilibria: either no firm does R&D or both firms do R&D. Multiplicity of equilibria leads generally to a challenging selection problem. In our context, it is shown that the case of both firms investing in R&D can be Pareto-dominating for both players. It follows that government actions which allow an economy to increase the level of knowledge above a threshold may be welfare enhancing.     

Factors affecting the performance of knowledge collaboration in virtual team based on capital appreciation

Knowledge collaboration (KC) is an important strategy measure to improve knowledge management, focusing on not only efficiency of knowledge cooperation, but also adding value of intellectual capital and social capital. In virtual teams, many factors, such as team’s network characteristics, collaborative culture, and individual collaborative intention, affect the performance of KC. By discussing the nature of KC, this paper presents that the performance of can be measured from two aspects: effectiveness of collaboration and efficiency of cooperation. Among them, effectiveness of collaboration is measured through value added and efficiency of cooperation is measured through accuracy and timeliness. Then the paper discusses the factors affecting the performance of KC from network characteristics, individual attributes and team attributes. The results show that network characteristics, individual attributes and team attributes in virtual team have significant impacts on the performance of KC.     

R&D on learning felematics in the European Community

Abstract: This paper will develop the topic of learning through technologies from the viewpoint of research and development actions undertaken by the European Community in particular, R&D on flexible and distance education which is the focus of one of the programmes on telematic systems for general interest. The objectives of this programme, DELTA, are to exploit the benefits of IT&T tools and systems to improve efficiency of education and training, by means of more flexibility, interactivity and access to learning resources. The long term goal is the implementation of telematics-based learning infrastructures Europe-wide which will enable learners to access learning whenever and wherever required.     

敏捷供应链知识网络演化模型及知识扩散仿真

针对敏捷供应链中知识的动态增长和聚类性的特征,基于改进后的BA网络模型构建敏捷供应链知识网络的生长演化模型.网络中的节点基于节点间的关系强度择优选取并进行连接.在此基础上,对网络中知识主体的属性进行定义,并对网络中的知识扩散过程进行建模.最后通过计算机仿真对网络中知识主体采用不同的择优连接策略时网络中平均知识存量和知识差异系数的变化趋势进行了对比分析,得到了提高网络中知识扩散效率的有效对策.