组织知识系统的知识超网络模型及应用

利用网络模型研究知识系统,是当前知识管理研究者感兴趣的热点问题之一.现有的单一要素模式的知识网络不能反映组织知识系统的复杂构成和整体结构.采用超网络的思想和方法对这一问题进行了研究,提出了组织知识系统的知识超网络模型.该模型由三种节点、六种边构成,可用于表示组织知识系统中的知识、人、存储载体等三类要素及其之间的复杂关系,因而可反映组织知识系统的复杂构成及结构形态.文中对模型的应用做了初步探讨,包括:知识组织、知识表示、知识结构分析、知识定位搜索、分析组织知识管理活动等.该模型为组织知识管理提供了一种新的工具和思路.     

市场机遇发现的支持模型及其应用

采用信息技术支持企业的市场机遇发现是企业信息化的深层次需求.本文从认知的角度分析了市场机遇鲻发现的过程、思维活动和领域知识,提出了支持市场机遇发现全过程的三维模型,建立了基于领域本体的市场机遇发现概念模型,提出并分析了其中领域本体实例生成与合并遗传方法,给出了应用实例.     

False foe? When and how code switching practices can support knowledge sharing in multinational corporations

The operating environment of multinational corporations (MNC) is multilingual, adding significant complexity to knowledge-sharing interactions between employees. In this paper, we explore how knowledge sharing in MNCs is influenced by code switching, or shifting between languages during interaction. Previous international business research has mostly described code switching as a behavior that has a negative impact on knowledge sharing by creating distrust and exclusion. Our case study of a major Finnish MNC from the perspective of faultline theory shows that in situations where organizational norms and routines help limit the potential impacts of code switching on subgroup formation and inter-subgroup animosity, it can also aid knowledge sharing by (i) supporting the development and maintenance of key technical vocabulary, (ii) enhancing inclusion in knowledge-sharing interactions, and (iii) supporting knowledge contextualization processes. Thus, code switching is not necessarily just a form of linguistic interference, but it can also be intended—and often functions—as a strategic behavior that draws on multiple languages to build efficient and successful knowledge-sharing interactions.     

Knowledge attributes and the choice of knowledge transfer mechanism in networks: the case of franchising

In this paper we develop a knowledge-based view on the choice of knowledge transfer mechanisms in franchising that integrates results from the information richness theory. Starting from the information richness theory we argue that tacitness of system knowledge, operationalized by codifiability, teachability and complexity, determines the information richness of the knowledge transfer mechanisms of franchising firms. We examine the following hypotheses: (1) If the franchisor’s knowledge is characterized by a high degree of codifiability and teachability and a low degree of complexity, knowledge transfer mechanisms with a lower degree of information richness are used; (2) If the franchisor’s knowledge is characterized by a high degree of complexity and a low degree of codifiability and teachability, knowledge transfer mechanisms with a higher degree of information richness are used. We test these hypotheses by using data from 52 franchising firms in the Austrian franchise sector. The data provide support for the hypotheses.     

Transferring lean knowledge within multinational networks

Abstract

Transferring lean knowledge is crucial for multinational companies; however, it is very difficult. Nevertheless, our knowledge in the area is limited. This paper investigates (a) how lean knowledge is transferred within multinational networks and (b) the type of organizational context that supports it. We use four case studies with 18 interviews in our exploratory study. Our results indicate that companies use a sophisticated knowledge transfer system with a fine web of practices that serve to transfer both explicit and tacit knowledge. The revealed organizational contexts show different patterns of division of labour (and responsibilities) between a central lean office and the particular subsidiary’s lean office. Our findings highlight the importance of transfer coalition, which consists of the cooperation of lean experts and top management during the knowledge transfer process. Top managers play a key role with their weak inter-unit ties, and they provide guidance for lean efforts and allocate sufficient resources to them. Further findings show that the evolution of lean transitions is not linear, and each of our case companies has witnessed turnaround during their journey.     

Decision knowledge sharing: flexible supply chains in KM context

Supply chain excellence has a real impact on business strategy. Building supply chains as flexible systems represents one of the most exciting opportunities to create value and one of the most challenging tasks for the policy makers. It requires integrated decision making amongst autonomous chain partners with effective decision knowledge sharing between them. The key to success lies in knowing which decision has more impact on the overall performance and this can be achieved by appropriate knowledge sharing. In this context, knowledge management (KM) can be used as an effective approach to achieve knowledge sharing and decision synchronisation in supply chains. Flexible supply chains (FSC_s) are more complex and involve multiple autonomous players with varying technical cultures (affects knowledge mindsets), managerial background (affects decision knowledge) and supply chain management (SCM) exposures (affects knowledge sharing attitudes). Thus there is a need to develop demo models that can encourage chain managers towards collaborative knowledge sharing in the supply chains. This paper presents the application of one such model based on decision knowledge sharing (DKS) for improved supply chain management. A simulation model of a flexible supply chain based on DKS framework is developed for demo purposes. The key results are highlighted along with industry implications. The cost based performance of DKS at different levels of flexibility is studied. Thus a careful analysis of the chain with a focus on collaborative decisions is useful to ensure success. This paper addresses this interesting and challenging domain.     

Nurturing life-science knowledge discovery: managing multi-organisation networks

Advancement of knowledge is the seed of the innovation process. As innovations have become more complex, organisations are driven by an increased need to collaborate in order to combine specialist capabilities to meet emerging market needs. The life sciences are one sector where collaborative innovation is highly evident. This article examines the phenomenon of knowledge-generating networks within the life sciences. The study explores the drivers of collaborative endeavours and investigates how knowledge networks linking the capabilities of public research centres and commercially focused pharmaceutical organisations can be managed to deliver the required synergistic benefits for partnering organisations. Three case studies of functioning university–industry knowledge networks are analysed and a model reflecting their network's life-cycle phases is presented. The discussion identifies the specific challenge posed at each of the network's development stages, together with the management process required to secure sustainable knowledge creation and effective transfer of this knowledge into innovation-generating R&D.     

The knowledge management of micro-firms in the crowd: key challenges for successful operations*

Abstract

Crowdfunding platforms are increasingly being used by small and micro-firms to fund the development and initial promotion of their new products. The transition from a crowdfunding campaign to the subsequent operational phase is critical to successfully fulfil the expectations of the backers who supported the micro-firm and expect to receive the new product. This paper analyzes the main challenges that must be faced by micro-firms during this transition, adopting the perspective of knowledge management theory. Based on an exploratory case study analysis, the paper highlights the particularities of these knowledge management challenges in terms of knowledge diversity, dependence and novelty. Asymmetry, dispersion, synchronization, a lack of a common understanding and backer lock-in are the main knowledge-based challenges for the operations of micro-firms that use crowdfunding. Various theoretical and practical implications of the findings are offered.     

A process model of establishing knowledge management: Insights from a longitudinal field study

This paper contributes to the discussion on how to manage knowledge in organizations. Taking a perspective which acknowledges the importance of, but does not privilege, IT as the decisive element, it reports the results of a study investigating the process of establishing as opposed to conducting knowledge management. Based on a grounded theory approach to the analysis of the empirical data, a model of establishing knowledge management in organizations is developed. The model emphasizes how the organizational members make sense of the action and behavior of management, and how this understanding influences their own perceptions and actions in the process of establishing knowledge management. This leads to an understanding of knowledge management as an autonomous venturing process. The model is then used to suggest an explanation of why establishing knowledge management was not successful in the case which was investigated. Conclusions are provided on how the model can be further exploited for studying and improving the practice of knowledge management.     

Managing structural and dynamic complexity in supply chains: insights from four case studies

Complexity is regarded a major impediment to Supply Chain (SC) performance. However, very few studies aid SC managers adopt adequate practices in response to structural and dynamic complexity. This study offers a comprehensive review of the practices that four manufacturing companies employ in their SC function to manage the structural and dynamic complexity of their product portfolio, internal SC, and supplier and customer bases. Moreover, leveraging the results of the inductive in-depth case studies, a classification of complexity management practices consisting of four clusters is advanced: variety reducing, confinement and decoupling, coordination and collaboration and decision support and knowledge generation. Each cluster’s distinctive logic and limitations are discussed and propositions on their managerial scope are introduced, therefore providing managers with relevant insights to design effective complexity management approaches in their organisations.     

How knowledge attributes influence alliance governance choices: A theory development note

This note develops theory regarding how attributes of corporate knowledge influence the selection of alliance governance mode. Different types of corporate knowledge are placed on a spectrum between a classic public good and deeply embedded knowledge. Hypotheses are developed regarding knowledge characteristics such as transfer costs, consequences of appropriation, observability, information asymmetry between negotiating partners, the difficulty of valuing knowledge, and the “disclosure dilemma.” Next, hypotheses are presented on the choice of alliance governance mode as determined by knowledge attributes (codification, newness, complexity, and teachability) and partner characteristics (such as knowledge absorptive capacity). These testable propositions should make for fruitful empirical studies on the relatively little researched area of alliance governance modal choice.     

Integration of process planning and production planning and control in cellular manufacturing

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.     

Metaprogress functions

This paper presents a theory of evolutionary learning as an alternative to the traditional theories of productivity. It is commonly recognized that there exists a significant process of learning in the utilization of existing techniques of production. This is exemplified by the well-known concept of manufacturing progress function that unit costs systematically decline with increase in cumulated output. The thesis is advanced here that yet other learning processes underlie the development of new techniques in the first place giving rise to what may be called metaprogress functions. The proposed concept of metaprogress functions is formalized and explained by means of several illustrative case studies of technological innovations. It is concluded that the conventional and the metaprogress functions together account for both the temporal and spatial aspects of productivity evolution. The policy implications of the study are discussed at length.     

Product Differentiation,Multiproduct Firms,and Estimating the Impact of Trade Liberalization on Productivity

This paper studies whether removing barriers to trade induces efficiency gains for producers. Like almost all empirical work which relies on a production function to recover productivity measures, I do not observe physical output at the firm level. Therefore, it is imperative to control for unobserved prices and demand shocks. I develop an empirical model that combines a demand system with a production function to generate estimates of productivity. I rely on my framework to identify the productivity effects from reduced trade protection in the Belgian textile market. This trade liberalization provides me with observed demand shifters that are used to separate out the associated price, scale, and productivity effects. Using a matched plant–product level data set and detailed quota data, I find that correcting for unobserved prices leads to substantially lower productivity gains. More specifically, abolishing all quota protections increases firm‐level productivity by only 2 percent as opposed to 8 percent when relying on standard measures of productivity. My results beg for a serious reevaluation of a long list of empirical studies that document productivity responses to major industry shocks and, in particular, to opening up to trade. My findings imply the need to study the impact of changes in the operating environment on productivity together with market power and prices in one integrated framework. The suggested method and identification strategy are quite general and can be applied whenever it is important to distinguish between revenue productivity and physical productivity.     

Turnover‐induced Forgetting and its Impact on Productivity

In this paper we investigate organizational forgetting, the notion that a firm's knowledge does not persist over time, exploring knowledge depreciation caused by changes in human capital. We first conduct an in‐depth exploratory case study to identify organizational forgetting. The empirical evidence suggests that organizational forgetting occurs when abrupt personnel turnover takes place. The data reveal a forgetting pattern that is entirely episodic in nature. Thereupon we conduct a confirmatory piece, using multiple regression models, to measure the impact of organizational forgetting on overall productivity. We find that, as a result of repeated forgetting processes, productivity falls in spite of continued output accumulation because of changes in the characteristics of the resource where experience resides.     

Internal knowledge generation: the research laboratory and innovative productivity in the pharmaceutical industry

As firms face increasing pressures associated with new forms of knowledge-based competition, researchers have begun to focus on knowledge acquisition strategies to the point of ignoring knowledge creation strategies. This paper investigates the impact of research centers in the pharmaceutical industry upon this neglected form of knowledge creation–innovation productivity. We find that firms with separate research facilities are more innovative than firms without such facilities. The results diverge when locational distance of the laboratory is considered for patent versus drug innovations, and vary across diversification types. These findings suggest that managers and researchers need to consider the relationship between the research center and corporate headquarters — and the role of the corporate headquarters — when developing knowledge generation strategies.     

DIAGNOSING ORDER PLANNING PERFORMANCE AT A NAVY MAINTENANCE AND REPAIR ORGANIZATION,USING LOGISTIC REGRESSION

We present a tool to diagnose the behavior of planners in complex production processes and to establish improvement potential for the delivery performance by changing the planning behavior. Scientific literature on production control offers valuable knowledge, but the complexity of real‐life processes makes it impossible to directly apply this knowledge in real‐life. The presented tool identifies possible deficiencies in the current way of managing the business processes, by matching the scientific knowledge on order planning with data reflecting the real‐life processes via logistic regression. A case study at a maintenance organization illustrates the diagnosis tool.     

The Determinants of Retail Productivity: A Critical Review of the Evidence

This paper discusses the literature on the established determinants of productivity in the retail sector. It also draws attention to some neglected strands of research which provide useful insights into strategies that could allow productivity enhancements in this area of the economy. To date, very few attempts have been made to integrate different specialisms in order to explain what drives productivity in retail. Here this paper rectifies this omission by putting together studies from economics, geography, knowledge management and employment studies. It is the authors’ view that quantitative studies of retail productivity should focus on total factor productivity in retailing as the result of competition/composition effects, planning regulations, information and communications technology, the multinational operation element and workforce skills. Further, the fact that retail firms possess advantages that are transferable between locations suggests that investment in strategies enhancing the transfer of explicit and tacit knowledge between and within businesses are crucial to achieve productivity gains.     

The problem with knowledge ambiguity

This paper proposes a new conceptualisation of the construct of knowledge ambiguity. This new conceptualisation is essential because (1) past researchers have tended to narrowly define and operationalise knowledge ambiguity in terms of causal ambiguity or tacitness and (2) the prevalent non-comprehensive conceptualisation constrains our ability to overcome the problem of knowledge ambiguity. Knowledge ambiguity has been identified as a major obstacle to effective knowledge transfer and to the implementation of overall knowledge management systems. The new conceptualisation proposes that knowledge ambiguity is composed of two types of ambiguity: component ambiguity and causal ambiguity. Component ambiguity is uncertainty about knowledge content, whereas causal ambiguity is uncertainty about how to use the knowledge. This re-conceptualisation is supported by previous studies on knowledge characteristics, absorptive capacity and cognitive learning. In this paper, theoretical propositions are developed to demonstrate the compatibility of the new conceptualisation with the current understanding of these concepts. The present paper not only advances our understanding of knowledge ambiguity, it also points towards solutions for overcoming the problems associated with knowledge ambiguity. Different measures are required to overcome problems created by component ambiguity vs. causal ambiguity. This paper’s re-conceptualisation of knowledge ambiguity makes it easier to theorise about and operationalise the concept. It aligns the definition of knowledge ambiguity with current definitions of related constructs such as absorptive ambiguity and cognitive learning that are used in the broader knowledge transfer and knowledge management literatures.     

The Impact of Complexity on Knowledge Transfer in Manufacturing Networks

Coordinating knowledge transfer within multi‐plant manufacturing networks is a challenging task. Using a computational model, we examine when it is beneficial to create production knowledge within a central unit, the “lead factory,” and transfer it to geographically dispersed plants. We demonstrate that the knowledge transfer generates a trade‐off between a positive cost‐saving effect due to fewer adaptations in each plant, and a negative transfer cost effect due to the costly knowledge transfer itself. The complexity of the production process moderates the performance implications of the knowledge transfer because it determines the relative strength of these two effects. For production processes with low complexity, knowledge transfer can engender superior network performance. Here, an optimal extent of knowledge transfer exists, and thus, a complete knowledge transfer is not performance maximizing. For production processes with medium and high levels of complexity, performance is reduced rather than enhanced through knowledge transfer so that it is optimal not to transfer any knowledge from the lead factory to the plants. While we analyze knowledge transfer within a manufacturing network, our results are transferable to other settings that consist of a knowledge sending and receiving unit.