Revealing Knowledge Networks From Computer Mediated Communication in Organizations

In today’s knowledge driven economy, knowledge is considered to be the key factor in defining the success of an organization. We have learned that knowledge is residing in the informal network of the organization. Hence, to improve performance, it is the informal knowledge network that should be examined and developed. For this purpose, social network analysis is increasingly applied in business contexts. This is, however, a new domain, which is still in development. This paper aims to aid in this development by researching how representative knowledge networks can be revealed in organizations. While surveying is a common first option to capture an organizational network, this technique may not always be suitable. Communication sources (e.g. e-mail) may provide an alternative, however, we do not know to what extent these sources can represent the actual knowledge network. This paper examines a Dutch IT services organization. Here, a web-survey among the employees baselines the knowledge network, which is compared to 3 communication networks from the same organization, captured by means of e-mail, telephone and SMS (Short Message Service) communication (also known as text messaging or texting). A comparison is made by means of correlating the network matrices and by comparing essential network properties. Findings show that only the e-mail network is significantly representative for the baselined knowledge network. This exercise is exploratory in nature as only one organization is examined, but comprehensive with regard to the richness of data that is available for examination. From our findings we gain insight in the extent to which networks, captured from e-mail, telephone and SMS archives can represent an organizational knowledge network

Revealing knowledge networks from computer mediated communication in organizations

Managers continually invest in new information technology (IT) but the question of organizational value still seems vague. One explanation is poor evaluation. In practice the Business Case including Return on Investment (ROI) still dominate. Information System research has noted for a long time that the Economic Approach is not sufficient and instead the Interpretative IT Evaluation Approach has been put forward. However, the approach has reached limited acceptance in practice and it has been noted that what to evaluate is a far more complex process than might first appear. The aim of this study is to articulate factors and criteria that are important to consider when assessing the organizational value of IT investments. This study is part of a Collaborative Practice Research project that took place 2005-2008 at three public organizations. The findings indicate that it is time to take a step from a Business Case to a Value Case. The Value Case is a pluralistic, a formative and a formalized approach that includes factors and criteria that have its base in prior research and have been further discussed and analyzed by the respondents. The Value Case also put management’s attention to effectiveness and efficiency, the task of management

Mining email to leverage knowledge networks in organizations

There is nothing new about the notion that in today‟s knowledge driven economy, knowledge is the key strategic asset for competitive advantage in an organization. Also, we have learned that knowledge is residing in the organization‟s informal network. Hence, to leverage business performance from a knowledge management perspective, focus should be on the informal network. A means to analyze and develop the informal network is by applying Social Network Analysis (SNA). By capturing network data in an organization, bottlenecks in knowledge processes can be identified and managed. But where network data can easily be captured by means of a survey in small organizations, in larger organizations this process is too complex and time-intensive. Mining e-mail data is more and more regarded as a suitable alternative as it automates the data capturing process and enables longitudinal research possibilities. An increasing amount of tools for mining e-mail data into social networks is available, but the question remains to what extent these tools are also capable of conducting knowledge network analysis: the analysis of networks from a knowledge perspective. It is argued that in order to perform knowledge network analysis, a tool is required that is capable of analyzing both the header data and the body data of e-mail messages. In this paper two e-mail mining tools are elaborated. One focuses on the analysis of e-mail header data and the other focuses on the analysis of e-mail body data. Both tools are embedded in their theoretical background and compared to other e-mail mining tools that address e-mail header data or e-mail body data. The aim of this paper is two-fold. The paper primarily aims at providing a detailed discussion of both tools. Continuing, from the in-depth review, the integration of both tools is proposed, concluding towards a single new tool that is capable of analyzing both e-mail header and body data. It is argued how this new tool nurtures the application of knowledge network analysis

Social Capital in the ICT Sector – A Network Perspective on Executive Turnover and Startup Performance

Recently, The Wall Street Journal proclaimed the “War for Internet Talent” among companies in the Information and Communication Technology (ICT) sector. At the same time, talented employees become entrepreneurial and establish their own startups. We aim to provide evidence that startup performance is not based exclusively on access to talent, in the sense of individual human capital, but is also determined by a social capital aspect resulting from their executives’ turnover history. We apply social network analysis (SNA) combined with logistical regression on a large dataset of companies and executives in the ICT sector. Our study contributes to turnover and entrepreneurship in information systems research, as well as to social capital and multilevel systems research. Furthermore, we shed a light on turnover patterns in the ICT sector, contribute to a better understanding of success factors for startups, and provide a practical measure to help identify and differentiate key employees