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The purpose of this study paper is to identify and prioritize the factors affecting the knowledge flow in high-tech industries.

This research is applied in terms of purpose and descriptive-survey in terms of data collection method. This research has been done in a qualitative–quantitative method. In the qualitative part, due to the nature of the data in this study, expert interviews have been used. The sample studied in this research includes 35 managers and expert professors with experience in the field of knowledge management working in universities and high-tech industries who have been selected by the method of snowball. In the quantitative part, the questionnaire tool and DANP multivariate decision-making method have been used.

In this study, a multicriteria decision-making technique using a combination of DEMATEL and ANP (DANP) was used to identify and prioritize the factors affecting the knowledge flow in high-tech industries. In this study, the factors affecting the knowledge flow, including 8 main factors and 31 subfactors, were selected. Human resources, organizational structure, organizational culture, knowledge communication, knowledge management tools, knowledge characteristics, laws, policies and regulations and financial resources were effective in improving knowledge flow, respectively.

By studying the research, it was found that the study area is limited, and the previous work has remained at the level of documentation and little practical use has been done. In previous research, the discussion of knowledge flow has not been very open, and doing incomplete work causes limited experiences and increases cost and time wastage, and parallel work may also occur. Therefore, to complete the knowledge management circle and fully achieve the research objectives, as well as to make available and transfer the experiences of people working in this field and also to save time and reduce costs, the contents and factors of previous models have been counted. It is designed for high-tech industries, a model for the flow of knowledge.

Cross-border flow of knowledge is fraught with many challenges. The complexity associated with the organization of multinational corporations (MNCs), and the information asymmetry in foreign locations poses particular challenges to knowledge flow. Yet, effective transfer of knowledge is critical for the survival and performance of MNCs. The purpose of this paper is to present a comprehensive framework to understand the difficulties in the smooth flow of knowledge in MNCs.

The study is conceptual in nature and is based on an extensive review of the extant literature.

This review of the literature suggests that knowledge flow in MNCs is affected by country-level, firm-level and individual-level factors. The authors discuss these in the backdrop of the MNC strategy and the knowledge transfer context. The authors present their theoretical model and discuss the implications for advancing research in this domain.

This is one of the first papers to present a comprehensive framework to understand knowledge flows in MNCs.

This study aims at analyzing the features of knowledge flow and the role-specific nodes in knowledge networks among individuals and business units of six organizations in different industries, and suggesting prescriptions to prevent the organizational knowledge sclerosis.

This research conducts multiple case studies on the organizational knowledge paths of six companies in the multiple industries through social network analysis (SNA) tool developed by the authors of this paper.

This study provides four major findings which shed a new light on how to comprehend the features of knowledge flow and the role-specific nodes in knowledge networks in organizations: the within-business unit knowledge flows are more dominant over the inter-business units knowledge flow; the downward knowledge flows are dominant over the horizontal and upward knowledge flows in the management levels; distributions of knowledge owners and providers are like L-shape and the gap between knowledge owing and providing expands as the management levels go up; and the top 20 percent people in an organization dominate over a large portion of the knowledge brokerage activities.

Cultural difference issue might arise because data collection was limited to Korean organizations. Therefore, the findings from this study needs to be cautiously interpreted considering the cultural difference/deeper understanding of the organizational knowledge paths through social network lens can make it possible for more context-specific KM strategies (e.g. suitable for a specific functional unit, management level, or industry type) to be identified and implemented.

Managers can have a solid grasp about knowledge flows and knowledge node roles in their organization through social network analysis in order to facilitate the knowledge transfer and eliminate the knowledge link lapse in organizations.

This study could be a stepping stone for further empirical research since it expanded the level of organizational knowledge network analysis from individual and team to inter-unit and inter-management level through the block modeling analysis of knowledge network.

This article aims to point out the essential role of knowledge flows when studying new ways of organizing in a knowledge‐intensive service sector where organizations operate in rapidly changing markets. The purpose of this article is to analyze the concept of self‐organization and its basic characteristics from a knowledge flow point‐of‐view.

A conceptual analysis and literature review are provided.

The article offers a way to understand how self‐organization emerges from lower‐level or local interaction, i.e. knowledge flows. The results of earlier studies indicate that if experts working in customer interface are empowered to make independent decisions and to adjust their working according to the ongoing situation, i.e. to self‐organize, co‐operation with customers becomes more active.

The article presents a new way of looking at self‐organization and its basic characteristics as managerial tools in knowledge‐intensive organizations. The article brings up the fundamental role of knowledge flows in a self‐organization process.

This study attempts to develop an approach with triangulation to explore the determinants of knowledge flows, as well as the relationships among them.

The proposed approach with the use of triangulation is designed to handle the issues that arise in the various interactions and numerous contexts among entities and/or activities that are associated with KM.

The proposed hybrid approach is found to be helpful in dealing with the issue of knowledge flow, especially involving various entities and complex interactions with numerous contents and dynamic contexts. In addition, the findings also show the presence of multi‐directional and adaptive interactions among determinants to knowledge flows, and also how these influence a firm's KM initiatives and performance.

The proposed hybrid approach can be considered as a way to overcome the limitations both of qualitative and quantitative methods, and the relationships among knowledge flows explored in this study provide some directions for future KM research.

The proposed approach focuses on the visualization of probable determinants to knowledge flows within an organization. This visualization can be utilized to evaluate the determinants and their relationships with each other, which may help managers to take actions to achieve more effective and efficient KM.

The results show the value of using a hybrid approach for dealing with research issues involving various entities and activities with complex content, such as knowledge flows.

The purpose of this paper is to examine how knowledge inflows and outflows interact to affect performance outcomes. Though previous studies have dealt with knowledge inflows and outflows, the quality and quantity characteristics of knowledge are often not taken into account, thus leaving a research gap with regards to the effect of their interactions on performance outcomes.

Based on Poisson regression analysis, this quantitative study fills the aforementioned research gaps by analyzing the ambidextrous configurations of knowledge flows from an ambidexterity perspective and examines their effects on two-phase performance (i.e. regular season and playoffs), using a longitudinal data set of National Basketball Association transactions from the 2003-2004 to 2014-2015 season.

The results suggest that the complementarity between knowledge inflows and outflows along the quality and quantity dimensions of knowledge, respectively, has a positive impact on two-phase performance, while the imbalance between knowledge inflows and outflows under the quality and quantity dimensions of knowledge, respectively, has a negative impact on playoffs performance (Phase 2). These findings suggest that organizations can balance knowledge inflows and outflows under a single quality or quantity dimension of knowledge. Furthermore, the interaction between the quantity of the inflows of knowledge and the quality of the outflows of knowledge and the interaction between the quality of the inflows of knowledge and the quantity of the outflows of knowledge are both positively related to two-phase performance. These findings suggest that organizations can balance knowledge inflows and outflows across quality and quantity dimensions of knowledge. Finally, the effects of the interaction between knowledge inflows and outflows on playoffs performance are greater than regular-season.

Organizations should leverage ambidexterity to manage/balance knowledge inflows and outflows across quality and quantity dimensions, further enhancing performance outcomes.

This study, first, provides new insights into knowledge flows by distinguishing between the quality and quantity of knowledge, the inflows and outflows of knowledge, constructing ambidextrous configurations of knowledge flows from an ambidexterity perspective. Second, it contributes to the relationship between knowledge flows and organizational performance by revealing how ambidextrous configurations of knowledge flows exert different effects on performance outcomes. Third, it adds to the literature of ambidexterity-performance relationships and expands it to the context of sports.

The aim of this paper is to suggest a method to redesign business processes from the viewpoint of knowledge flows using a knowledge map.

Knowledge flows and business processes cannot be separated because knowledge is inputted and outputted through business processes. Knowledge flows inherit the feature and appearance of corresponding business processes; therefore, one can identify problems within business processes by analyzing corresponding knowledge flows. The methodology is composed of the following sections: knowledge mapping, knowledge profiling, knowledge flow identification, knowledge flow optimization and TO‐BE process visualization.

This paper provides a methodology for knowledge flow‐based business process redesign and ten guidelines for knowledge flow optimization. The case study demonstrates that the proposed ideas constitute knowledge‐intensified business processes.

A more formal validation method that is based on the statistical analysis must be provided to assert the proposed guidelines for knowledge flow optimization as the truly optimized ones.

This paper's idea provides the practical methodology and guidelines that can be directly applicable to performing business process redesign by introducing a real case.

This paper's ideas not only provide present companies with a practical way to enhance their business process to be more knowledge‐focused, but also promote the current economy to be more knowledge‐intensive.

It is largely acknowledged that arbitrating the flow of knowledge can help firms strategically leverage tacit and explicit internal knowledge. However, despite the apparent scholarly and managerial acceptance of the criticality of the flow of knowledge between various stakeholders, the academic understanding of knowledge arbitrage remains coarse-grained. There are practically no empirical insights available to unravel the consequences of firms’ knowledge arbitrage choices regarding rewards and risks. This study aims to identify the risks that emerge as firms channel the flow of knowledge from surplus to deficit areas within organizational boundaries. To this end, the authors investigate several subsumed subprocesses in knowledge arbitrage to map the associated risks.

This study used an exploratory qualitative approach to examine the risks that emerge as firms attempt to support knowledge flows within their organizational boundaries. The data were collected through open-ended essays via an online research platform from 45 full-time employees of firms operating in different sectors. The collected data were analyzed inductively through open, axial and selective coding.

The research findings identified three key subprocesses of knowledge arbitrage: knowledge diffusion, knowledge brokering and knowledge absorption. These subprocesses are susceptible to various risks arising the form of channels, champions, sharers and receivers of knowledge flows. In general, the study showed that a firm’s decision regarding knowledge flows, such as structured or random flows, or the presence or absence of designated coordinators to broker the flow carries specific risks for both sharers and receivers. In particular, while the risks of knowledge hiding, misinformation and disinformation manifest in all three subprocesses, low employee engagement, loss of knowledge and information overload also emerged as key risks in any two of the three subprocesses.

This study offers valuable insights by uncovering the hitherto unexplored risks in intrafirm knowledge arbitrage. Given that knowledge is a crucial organizational tool for driving performance, innovation and competitive advantage, understanding the risks associated with intrafirm arbitrated knowledge flows can help firms anticipate and mitigate the associated adverse consequences. The findings make a novel contribution by offering (a) a comprehensive categorization of the risks associated with knowledge arbitrage rooted in processes, people and structures and (b) a macro overview of knowledge arbitrage risks associated with the processes of knowledge diffusion, knowledge brokering and knowledge absorption.

As a critical component in the entrepreneurial process, knowledge is essential to the study of how entrepreneurs compete under constraints. Research in this area is challenged by the unobservable and imprecise nature of knowledge which inhibits advanced theory building and testing, and we explore this problem by analyzing the relationship between the entrepreneurial process, constraints to the process, and knowledge flows. We apply and extend a systems-theoretic framework that identifies the knowledge system in entrepreneurial organizations, and develop an integrative model to guide future research.

This study aims to examine how different modes of knowledge flows affect the changes of asset specificity and how ownership control moderates the relationship between knowledge flows and asset specificity in the open innovation paradigm.

This paper selects information technology outsourcing as the research base. It uses the feasible weighted least squares modeling method for its analysis and has collected the data from 2,369 research and development contracts of multinational vendor firms in China.

The coupled and outbound knowledge flows have a direct and positive effect on asset specificity. Moreover, the results show that weak corporate control has significant moderating effects on the relationship between both coupled and outbound knowledge flows and asset specificity; the strong control positively moderates the relationship between outbound knowledge flows and asset specificity.

In open innovation, firms build a higher degree of asset specificity to maximize the efficiency of knowledge flows, which then helps them to enhance innovation capacity and market performance.

Preceding studies have tended to examine the influences of asset specificity as an independent variable in a closed innovation paradigm. Asset specificity is hence often left as the antecedent “black box.” This paper, however, opens the “black box” of asset specificity, which is set as a dependent variable, by investigating the influences of knowledge flows on the asset specificity in the context of open innovation. It also reinterprets the role of asset specificity by adopting the lens of open innovation theory.