Technology and Knowledge Flow

The Power of Networks

Guglielmo Trentin

• Publisher: Chandos Publishing
• Year: 2011
• Print ISBN: 9781843346463
• eBook ISBN: 9781780632674
• Topic: Business
• Subtopic: Information Management
• Index: Business

This book outlines how network technology can support, foster and enhance the Knowledge Management, Sharing and Development (KMSD) processes in professional environments through the activation of both formal and informal knowledge flows. Understanding how ICT can be made available to such flows in the knowledge society is a factor that cannot be disregarded and is confirmed by the increasing interest of companies in new forms of software-mediated social interaction. The latter factor is in relation both to the possibility of accelerating internal communication and problem solving processes, and/or in relation to dynamics of endogenous knowledge growth of human resources.The book will focus specifically on knowledge flow (KF) processes occurring within networked communities of professionals (NCP) and the associated virtual community environments (VCE) that foster horizontal dynamics in the management, sharing and development of fresh knowledge. Along this line a further key issue will concern the analysis and evaluation techniques of the impact of Network Technology use on both community KF and NCP performance. - The proposal of a taxonomy of Network Technology uses to support formal and informal knowledge flows - Analyses how Web 2.0 and Web 3.0 technology is deeply modifying the dynamics connected to KF and KM - Discusses dynamics underlying horizontal KF sharing processes within NCP

1

Leveraging mobile network technologies to accelerate tacit knowledge flows across organisations and distances

Mark E. Nissen and Alex Bordetsky

Abstract:

Knowledge is key to sustainable competitive advantage, but different kinds of knowledge affect competitive advantage differently, and they exhibit qualitatively different dynamic properties and behaviours. This pertains in particular to tacit and explicit knowledge.Tacit knowledge is rich and powerful, enabling rapid, expert-level action in many circumstances, but it tends to be highly situated and to flow slowly and narrowly across people, organisations, places and times.Alternatively, explicit knowledge tends to be more generally applicable and to flow broadly and rapidly, but it is diluted and less powerful than its tacit counterpart. Mobile network technologies are becoming increasingly powerful and ubiquitous, but like most information technologies, they maintain a predominant focus on explicit knowledge. In contrast, advancing capabilities to facilitate remote and multiparty collaboration offer increasing potential to support tacit knowledge flows as well.The research described in this chapter builds upon Knowledge Flow Theory to conceptualise an approach to accelerating tacit knowledge flows through mobile network technologies, and it illustrates such an approach through field research to examine how rich, situated tacit knowledge can be induced to flow rapidly across organisations and distances. For example, mobile network technologies can enable domain experts to apply their rich tacit knowledge even across great geographical distances, as though they were collocated physically.This chapter offers a theoretical contribution and elucidates an exciting path for continued research along these lines, and it highlights practical application as well, through demonstration of how network technologies can be leveraged to accelerate tacit knowledge flows.

Key words

knowledge flow theory

tacit knowledge

explicit knowledge

mobile network technologies

communities of professionals

Introduction

It is well established that knowledge is key to sustainable competitive advantage (Cole, 1998; Grant, 1996; Spender, 1996). For instance, Nissen (2006, ch. 1) explains how knowledge enables effective action; effective action drives superior performance; and superior performance supports competitive advantage. However, many scholars continue to overlook the implications of knowledge not representing a single, monolithic concept (Nissen and Jennex, 2005). Different kinds of knowledge (e.g. tacit, explicit, individual, group, created, applied) have different properties and behaviours, and hence affect action, performance and competitive advantage differently (Nissen, 2005).

This pertains in particular to tacit and explicit knowledge (Nonaka, 1994). Tacit knowledge is rich and powerful (Nissen, 2005), enabling rapid, expert-level action in many circumstances (Grant, 1996). Tacit knowledge is also more appropriable (e.g. it can be controlled and used profitably) than explicit knowledge is, making the knowledge-based actions that it enables more difficult for competitors to imitate (Dierickx et al., 1989). For example, an experienced contract negotiator (who has abundant, experience-based, tacit knowledge) may be observed directly during the process of negotiating a contract, but simply observing – or even discussing – the experienced negotiator is unlikely to enable a less experienced competitor to negotiate with equal efficacy. Similar examples pertain to tacit knowledge that enables effective aeroplane pilots, chess players, football teams and business organisations. Speaking generally, the more tacit that knowledge becomes, the greater its competitive potential becomes (Saviotti, 1998). However, tacit knowledge tends to be highly situated and to flow slowly and narrowly across people, organisations, places and times (Nissen, 2006).

Alternatively, explicit knowledge tends to be more generally applicable and to flow broadly and rapidly (Szulanski, 1996). Once articulated in explicit form and combined with information technology (IT) – for instance, when posted on an intranet site – such knowledge can be distributed around the world in a matter of seconds. However, explicit knowledge is comparatively diluted and less powerful than its tacit counterpart (Dierickx et al., 1989; Saviotti, 1998). We know more than we can tell (Polanyi, 1967). Returning to the examples above, reading books about how to negotiate contracts, fly aeroplanes, play chess or football, or perform key business processes is not the same as accumulating direct experience as a negotiator, pilot, player or manager.

Speaking generally, acquiring explicit knowledge does not enable the same kinds of knowledge-based actions that can be enacted through tacit knowledge.

This distinction between tacit and explicit knowledge is magnified through IT. Many scholars agree that the vast preponderance of IT is supportive in nature and maintains a predominate focus on explicit knowledge (Nissen, Kamel and Sengupta, 2000), where knowledge (i.e. data and information) is involved at all (Nissen, 2006). In order to be processed, transmitted, viewed and otherwise used by IT, most of the associated content must be articulated in explicit form (e.g. via written text, graphical depiction, mathematical formula or software code).

Further, because of processing and bandwidth limitations, mobile network technologies in particular tend to emphasise the explicit. E-mail, text chat, web searches, social networking and similar mobile network applications are becoming increasingly powerful and ubiquitous, but the associated knowledge (e.g. what is contained within text or e-mail messages, found through search engines, updated through tweets or page postings) is explicit generally. In contrast, advancing capabilities to facilitate remote and multiparty audio-video and shared-application collaboration offer increasing potential to support tacit knowledge flows as well. Voice-only telephony and one-way video fall somewhere in between.

The research described in this chapter builds upon Knowledge Flow Theory to conceptualise an approach to accelerating tacit knowledge flows through mobile network technologies. We look in particular at remote, multiparty collaboration in contexts where the knowledge required for effective action is highly situated and geographically distributed, where deep expertise is necessary but unavailable at the scene. We illustrate such an approach through field research to examine how rich, situated, tacit knowledge can be induced to flow rapidly across organisations and distances. This chapter offers a theoretical contribution and elucidates an exciting path for continued research along these lines, and it highlights practical application as well through demonstration of how network technologies can be leveraged to accelerate tacit knowledge flows.

Background

Nissen (2005) describes the concept of knowledge flows in terms of dynamic knowledge and indicates that it subsumes similar concepts such as knowledge conversion, transfer, sharing, integration, reuse and others that depict changes, movements and applications of knowledge over time. Drawing direct...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of figures and tables
• Acronyms used
• About the author
• Preface
• Chapter 1: Leveraging mobile network technologies to accelerate tacit knowledge flows across organisations and distances
• Chapter 2: Modelling the dynamics of knowledge flow within networked communities of professionals
• Chapter 3: Supporting knowledge flow in web-based environments by means of narrative
• Chapter 4: What are virtual walls to flow of knowledge in teamwork discussions?
• Chapter 5: Knowledge flows and graphic knowledge representations
• Chapter 6: Graphic knowledge representation as a tool for fostering knowledge flow in informal learning processes
• Chapter 7: Conclusive thoughts on communication flow, knowledge flow and informal learning
• Index