Complexity, networks and knowledge flow

Because knowledge plays an important role in the creation of wealth, economic actors often wish to skew the flow of knowledge in their favor. We ask, when will an actor socially close to the source of some knowledge have the greatest advantage over distant actors in receiving and building on the knowledge? Marrying a social network perspective with a view of knowledge transfer as a search process, we argue that the value of social proximity to the knowledge source depends crucially on the nature of the knowledge at hand. Simple knowledge diffuses equally to close and distant actors because distant recipients with poor connections to the source of the knowledge can compensate for their limited access by means of unaided local search. Complex knowledge resists diffusion even within the social circles in which it originated. With knowledge of moderate complexity, however, high-fidelity transmission along social networks combined with local search allows socially proximate recipients to receive and extend knowledge generated elsewhere, while interdependencies stymie more distant recipients who rely heavily on unaided search. To test this hypothesis, we examine patent data and compare citation rates across proximate and distant actors on three dimensions: (1) the inventor collaboration network; (2) firm membership; and (3) geography. We find robust support for the proposition that socially proximate actors have the greatest advantage over distant actors for knowledge of moderate complexity. We discuss the implications of our findings for the distribution of intra-industry profits, the geographic agglomeration of industries, the design of social networks within firms, and the modularization of technologies.     

Strategic knowledge management, innovation and performance

Our aim is to shed light on the consequences of knowledge management (KM) strategies on firm's innovation and corporate performance. Organisations are not aware of the real implications that KM may have. Based on an empirical study consisted of 310 Spanish organisations and structural equations modelling, results show that both KM strategies (codification and personalisation) impacts on innovation and organisational performance directly and indirectly (through an increase on innovation capability). Also, findings demonstrate a different effect of KM strategies on diverse dimensions of organisational performance. Our conclusions may help academics and managers in designing KM strategic programs in order to achieve higher innovation, effectiveness, efficiency and profitability.     

A multilevel model for effects of social capital and knowledge sharing in knowledge-intensive work teams

Although it is a widely held belief that social capital facilitates knowledge sharing among individuals, there is little research that has deeply investigated the impacts of social capital at different levels on an individual's knowledge sharing behavior. To address this research gap, this study combines a multilevel approach and an optimal network configuration view to investigate the multilevel effects of social capital on individuals’ knowledge sharing in knowledge intensive work teams. This study makes a distinction between the social capital at the team-level and that of social capital at the individual level to examine their cross-level and direct effects on an individual's sharing of explicit and tacit knowledge. A survey involving 343 participants in 47 knowledge-intensive teams was conducted for testing the multilevel model. The results reveal that social capital at both levels jointly influences an individual's explicit and tacit knowledge sharing. Further, when individuals possess a moderate betweenness centrality and the whole team holds a moderate network density, team members’ knowledge sharing can be maximized. These findings offer a more comprehensive and precise understanding of the multilevel impacts of social capital on team members’ knowledge sharing behavior, thus contributing to the social capital theory, as well as knowledge management research and practices.     

How to facilitate knowledge diffusion in complex networks: The roles of network structure,knowledge role distribution and selection rule

The diffusion of knowledge within organizations provides opportunities for interpersonal co-operation, improves creative ability and therefore leads to competitive advantage. Focus of prior literature on knowledge diffusion has been on identifying factors that influence individuals' behavioral intentions to seek and share knowledge. However, knowledge diffusion as an enigmatic, emergent and organizational-level process is more than the simple aggregation of individual attributes and needs to be further investigated. Accordingly, this study focuses on three distinct system-level factors, i.e., architectures of connections among individuals, distributions of knowledge roles and designs of selection mechanisms and analyses their effects on knowledge diffusion. To be more specific, we examine three distinct knowledge roles: seekers, contributors and brokers. We also distinguish between three types of selection mechanisms: objective selection mechanisms, feedback-based selection mechanisms and random selection mechanisms. By conducting agent-based simulations on four representative networks, i.e., regular networks, random networks, small-world networks and scale-free networks, our results show that the optimal knowledge diffusion performance can be achieved on scale-free networks where all agents implement objective mechanisms and show characteristics of brokers. Moreover, our results (a) highlight the significance of brokers, (b) illustrate the superiority of objective selection rules and (c) demonstrate that scale-free networks provide an optimal framework for knowledge diffusion. Furthermore, we also find the interdependent relevance of these three factors to knowledge diffusion and propose a qualitative explanation of these findings.     

Investigating effectiveness and user acceptance of semantic social tagging for knowledge sharing

Social tagging systems enable users to assign arbitrary tags to various digital resources. However, they face vague-meaning problems when users retrieve or present resources with the keyword-based tags. In order to solve these problems, this study takes advantage of Semantic Web technology and the topological characteristics of knowledge maps to develop a system that comprises a semantic tagging mechanism and triple-pattern and visual searching mechanisms. A field experiment was conducted to evaluate the effectiveness and user acceptance of these mechanisms in a knowledge sharing context. The results show that the semantic social tagging system is more effective than a keyword-based system. The visualized knowledge map helps users capture an overview of the knowledge domain, reduce cognitive effort for the search, and obtain more enjoyment. Traditional keyword tagging with a keyword search still has the advantage of ease of use and the users had higher intention to use it. This study also proposes directions for future development of semantic social tagging systems.     

Social networks and coordination performance of distributed software development teams

In this study, we explore the coordination performance of the geographically distributed software development teams by exploring OSS (Open Source Software) development dataset available through SourceForge.com. OSS team structures have traditionally been geographically dispersed and therefore, the coordination of post release activities such as testing efforts have been carried out by means of communication via electronic forms, such as email or message boards and forums. In our current communication-enriched environment, best practices for coordination are adopted by all software projects yet some still fail to achieve their target performance. Does team structure have any bearing on the performance outcome of the project? How does the communication between teams and their external parties affect ultimate success or failure of projects? We seek to answer above questions by applying existing theories and analytical methods from social networks for exploring the coordination performance of defect management activities found in OSS projects. We propose social networks based theoretical model for exploring distributed coordination structure and apply that for the case of OSS defect management process for exploring the structural properties, which induce the greatest coordination performance. The outcome of our suggest that there is correlation between certain network measures such as density, centrality and betweenness and coordination performance measures of defect management systems such as quality and timeliness.     

Enhancing team creative performance through social media and transactive memory system

Effective teamwork, knowledge coordination, and knowledge creation are recognized as essential sources of team effectiveness and creativity in modern organizations. Nowadays, social media is significantly modifying the patterns in the use of technology to support knowledge management practices in teams. At the same time, the literature shows that transactive memory system (TMS), which refers to how team members share their distributed knowledge and expertise, is an important factor affecting team performance. However, minimal effort has been made to elaborate on the precise role of social media in supporting TMS for enhancing absorptive capacity (ACAP) and knowledge creation capability (KCC) of the team, which in turn might influence team creative performance (TCP). Therefore, to address this gap in the literature, a theoretical model is developed and validated. Survey data collected from 334 members of 68 knowledge work teams indicated that social media use at work has a positive relationship with TMS and both social media use at work and TMS are positively related to ACAP and KCC of the team. Results further indicated that ACAP positively influenced KCC, and both have a direct relationship with TCP. This study shows that careful investment in social media by an organization can enhance meta-knowledge of “who knows what” within teams. Finally, exploring external knowledge alone is not enough. Instead, organizations must ensure external knowledge is utilized to create new knowledge to improve TCP.     

Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake

The US response to the 2010 Haiti Earthquake was a large effort coordinated by three major agencies that worked in tandem with the Government of Haiti, the United Nations, and many countries from around the globe. Managing this response effort was a complex undertaking that relied extensively on knowledge management systems (KMS). For the first time, however, US government agencies employed social media technologies such as wikis and collaborative workspaces as the main knowledge sharing mechanisms. In this research we present a case study developed through action research of how these social media technologies were used, what influences they made on knowledge sharing, reuse, and decision-making, and how knowledge was effectively (and at times ineffectively) maintained in these systems. First-hand knowledge of the response is used, offering strategies for future deployment of social media and important research questions that remain regarding social media as knowledge management systems, particularly for disaster and emergency management.     

The nexus between innovativeness and knowledge management: A focus on firm performance in the hospitality sector

While the importance of knowledge management is increasingly acknowledged, many firms do not fully understand the significance of innovativeness in relation to knowledge management and firm performance. Consequently, the objective of this article is to investigate innovativeness and its relationship with knowledge management and organizational performance in an under-examined industry sector and country context. The study methodology was survey-based and took place in the hospitality industry sector in Lesotho, Africa. Findings highlight the importance of knowledge management practices as an important driver of firm performance, where the results emphasize the positive mediating effect of innovativeness on the relationship between knowledge management and firm performance. The study has important practitioner and policy implications, where it is recommended that knowledge management be utilized in conjunction with innovativeness so as to positively influence firm performance. The article delivers a novel contribution to the literature in terms of establishing empirical associations between knowledge management, innovativeness and firm performance in an emerging country context.     

The effect of technological knowledge assets on performance: The innovative choice in Spanish firms

The aim of this article is to examine the relationship between Technological Knowledge Assets (TKAs) and performance, in the light of making the ‘innovative choice’ that involves short-term costs of acquiring or generating the assets but aims at longer term benefits through innovation. To that end, a study of 1267 industrial firms in Spain was carried out over a period of 5 years, 1998-2002. The results show that TKAs have a positive indirect effect on financial performance mediated through innovation. They also reveal that TKAs have a negative direct effect on performance, except licences. Thus, the combined effect of TKAs on performance urges the need for innovation to obtain a positive payoff.     

Understanding the formation mechanism of high-quality knowledge in social question and answer communities: A knowledge co-creation perspective

The social question and answer (Q&A) community provides people with an effective tool to obtain high-quality information. From the perspective of reciprocal determinism and value co-creation, this study aims to investigate the formation mechanism of high-quality knowledge in the community. We develop a model to investigate how cognitive factors and community technological factors influence users’ knowledge co-creation behavior, thereby influencing knowledge quality in the community. A survey of 382 knowledge contributors in a social Q&A community shows that knowledge self-efficacy, topic richness, personalized recommendation, and social interactivity have a positive impact on users' knowledge sharing and integration behavior, which subsequently affect the community’s knowledge quality. Moreover, users' ratings moderate the influence of knowledge sharing on knowledge quality. This research demonstrates the synergistic effect of people and technology in knowledge co-creation, thus advances literature about value co-creation and content quality in online communities.     

Patent collaboration and international knowledge flow

In this paper, we provide an empirical analysis of evolving knowledge networks of successful patent collaboration at national level in 1980s, 1990s, and 2000s. All countries are classified into main knowledge creators (Organisation for Economic Co-operation and Development (OECD) group) and main knowledge users (non-OECD group) in order to distinguish specific characteristics of knowledge interactions within groups and between groups. The analyses are carried out from four aspects, i.e., the overall distribution of knowledge interactions among countries, the countries’ ability to inhabit and facilitate the knowledge flows among others with the help of flow betweenness measures, the countries’ bridgeness between two groups with the recently developed Q-measures, and the most important bilateral knowledge interactions. Results show that although most of the international knowledge interactions still take place within the OECD group, the non-OECD countries have improved their performance significantly. They participate much more in international patenting and collaborations and play much more important roles in facilitating knowledge interactions among others. Among them, China and Taiwan are two most dazzling new stars according to their performance in international knowledge interactions. Considering together with their rapidly improved world competitiveness, the findings indicate that the wide and deep participation in international knowledge interactions may have great contribution to the economic competitiveness.     

A knowledge management approach to capture organizational learning networks

Effective knowledge management practices in organizations are focused on knowledge creation and knowledge transfer activities. Thus, intelligence and competencies matters at the organizational workplace. For most knowledge intensive organizations is fundamental the continuous availability and development of domain expertise. This paper describes an ongoing research project to develop an organizational knowledge architecture that is being specified and developed to support collaboration tasks as well as design and model predictive data analysis and insights for organizational development. The primary goal of this research is to create a suitable architecture for use, initially, in intranet (corporate portal) collaborative procedures, but also scalable for later use in more generic forms of ontology-driven knowledge management systems. The designed architecture and functionalities aim to create coherent web data layers for intranet learning and predictive analysis, defining the vocabulary and semantics for knowledge sharing and reuse projects. Regarding intellectual capital definition, this research argues that effective knowledge management are based on the dynamic nature of the organizational knowledge, and predictive data analysis and insights identification can transform and add value to an organization. This paper presents a knowledge management and engineering perspective (ontology based) for the application of predictive analysis and insights at the organizational (corporate) workplace towards the development of the organizational learning network.     

From free to paid: Effect of knowledge differentiation on market performance of paid knowledge products

Exploring the factors that affect the market performance of paid knowledge products is of great importance for knowledge payment platforms. Drawing on the sensations-familiarity framework and social capital theory, this study investigates how knowledge differentiation between paid and free knowledge impacts market performance, along with the moderating effect of knowledge providers’ social capital. Technically, a neural network-based text mining model is utilized to transform free and paid knowledge to semantic vectors, whose dissimilarity is calculated as knowledge differentiation. Empirical analysis on a real dataset reveals the positive (or negative) effect of knowledge differentiation on sales (or eWOM, electronic word of mouth), which will be more prominent with the increase of social capital. The results are reinforced with robustness checks regarding alternative knowledge-differentiation measures, more control variables and alternative regression methods. The present study extends our understanding of knowledge payment and free-to-paid consumption, and offers practical implications for content design and product management.     

知识管理和知识管理网络

分析和说明了学习和组织学习、知识和组织知识、知识管理的概念，概括了有关文献对知识的分类，分析了知识交流的模式和知识管理的目的，并提出建立组织知识管理网络的基本思路。     

No inventor is an island: Social connectedness and the geography of knowledge flows in the US

Do informal social ties connecting inventors across distant places promote knowledge flows between them? To measure informal ties, we use a new and direct index of social connectedness of regions based on aggregate Facebook friendships. We use a well-established identification strategy that relies on matching inventor citations with citations from examiners. Moreover, we isolate the specific effect of informal connections, above and beyond formal professional ties (co-inventor networks) and geographic proximity. We identify a significant and robust effect of informal ties on patent citations. Further, we find that the effect of geographic proximity on knowledge flows is entirely explained by informal social ties and professional networks. We also show that the effect of informal social ties on knowledge flows is greater for new entrepreneurs or ‘garage inventors’, for older or ‘forgotten’ patents, and for flows across distant technology fields. It has also become increasingly important over the last two decades.     

Privacy in social networks: An analysis of Facebook

The only way to be aware of the risks and threats of Facebook, the most commonly used social networking site in the world and Turkey, is to be a careful user changing the default settings or simply not to have a Facebook account. In Turkey, there is still no study in which personal information shared though social networking sites has been evaluated in terms of privacy. For this reason, the findings obtained of this study have a great importance in the general picture of the current situation and drawing attention to the risks of the issue in Turkey where there are no legal arrangements effectively protecting the users from such sites. This study aims to investigate the Facebook privacy of information professionals who are members of KUTUP-L, and to determine the sensitivity and level of awareness of information professionals in Turkey. Facebook user profiles of 400 information professionals, all KUTUP-L members, have been analyzed in a study examining 32 different privacy settings. A privacy score has been calculated for each user, and the relations between privacy results have been analyzed. The findings at the end of the study show that information professionals in Turkey do pay attention to privacy, and most of the users change the default settings in order to protect their personal information.     

Latecomer firms and the emergence and development of knowledge networks: The case of Petrobras in Brazil

This paper addresses the emergence and development of firm-centred knowledge networks within learning and innovation systems in late-industrialising countries. A key contribution of the paper is conceptual and methodological: the development of an original typology of knowledge network properties to trace out changes in the form of networks as they evolve over time. A second contribution consists in providing an example of the application of the typology by examining the emergence and development of a firm-centred knowledge network in the case of Petrobras, the Brazilian oil company over more than 30 years between the late 1960s and the early 2000s. This demonstrates that the properties of Petrobras’ knowledge networks continuously evolved through a succession of stages towards (i) increasing intentionality in the management decision-making underlying network development, (ii) growing complexity and diversity in selected cognitive characteristics, and (iii) greater complementarity in the division of innovative labour between Petrobras and its network partners. These original results from applying the typology, in conjunction with retrospective historical methods, illustrate only one aspect of its potential value in the analysis of knowledge networks in late-industrialising economies: tracking out organisational evolution over long periods of time. Others include the comparative examination of network differences across different circumstances and the analysis of relationships between changes/differences in network properties and other characteristics of learning/innovation systems and their contexts.     

Exploring the effect of dynamic seed activation in social networks

In this paper, we address the problem of maximizing the influence in a social network by hiring a few users in the network to propagate the information. Considering limited budget and time, hired users (seeds) are activated dynamically at different time intervals over a time horizon. This motivates to avoid the same seed activation in consecutive time intervals that leads to deteriorating the seeds’ efficiency. The aim of this paper is to maximize the total gain obtained in the process of maximizing the influence in a social network. Total gain is obtained by earning of influencing the customers and then deducting the cost incurred for influencing the users. Therefore, an improvised memetic algorithm is developed to find the seeds that are to be activated at different time intervals to maximize the gain. Experimental results validate the effectiveness of the proposed algorithm, and it is found to perform better in identifying the potential seeds with minimum expenditure.     

A recommender mechanism for social knowledge navigation in an online encyclopedia

In today’s world, knowledge is important for constructing core competitive advantages for individuals and organizations. Recently, Web 2.0 applications and social media have provided a convenient medium for people to share knowledge over the Internet. However, the huge amount of created knowledge can also leads to the problem of information overload. This research proposes a social knowledge navigation mechanism that utilizes the techniques of relevant knowledge network construction, knowledge importance analysis, and knowledge concept ontology construction to generate a visualized recommendation of a knowledge map of sub-concept and knowledge of an article reading sequence for supporting learning activities related to a free online encyclopedia. The results of experiments conducted on Wikipedia show that the proposed mechanism can effectively recommend useful articles and improve a knowledge seeker’s learning effectiveness.