Report R4.14 Research on Organisational Change: Social Network Perspective Seminar Leader: Niharika Rai, Doctoral Scholar, XLRI niharikarai2004[at]yahoo.com, p04f66[at]astra.xlri.ac.in The discussions at the seminar illustrated several issues that typically arise in carrying out doctoral research. As they advance in their programmes, researchers try to taper down some broad area identified initially to a specific research topic and then to a set of researchable problems. In doing this, they face a number of challenges as illustrated below. In the doctoral work under discussion, the researcher aims to study some aspects of planned organisational change. To add new insights to this body of knowledge, she plans to utilise the techniques developed in the area of Social Network Analysis (SNA). It is interesting to note that the area of SNA itself is the result of a cross-disciplinary collaboration between social scientists and mathematicians working in the field of network and graph theory. Planned change is studied from a variety of perspectives. However, from preliminary case studies carried out in a few companies it seemed to the researcher that an SNA perspective might yield useful results. Attitudes of key people in informal social networks towards a particular change effort are often good indicators of the overall resistance (or lack of it) to the planned change in an organisation. However, the proposition that networks affect change is widely accepted. The challenge before the doctoral scholar is to go beyond what is known and to obtain non-trivial results connecting network ideas and change efforts. A number of suggestions were made to assist the researcher to do this. For example, there was a suggestion to explore the differences between network topologies before and after a change effort. Another suggestion urged the scholar to examine cultural issues influencing the behaviour of boundary spanners who serve as bridges between relatively independent networks. It was also recommended that a social situation could be conceptualised as a network of ideas rather than persons. For example, would certain measures of a “network of objectives” indicate which set of objectives are more achievable? Would talking in terms of a “network of problems” help in solving them? Certain limitations of using SNA to study complex social phenomena were also discussed. Researchers employing SNA seemed to make two basic assumptions. The first of these is that the system of networks is essentially stable. This stability enables them to talk of durable network measures and to describe certain types of network in terms of these measures. However, unlike technical networks (e.g., a network of telephones or computers), social networks are highly dynamic. The usefulness of arriving at highly accurate measures for such networks is thus suspect. The second assumption is regarding the uniformity of connections between nodes. The language of SNA permits us to include certain elementary variations in strength and direction of ties between nodes in our analysis. However, more intense qualitative differences between ties cannot be measured using this technique. This can be problematic while studying complex social phenomena. Some dominant considerations while doctoral scholars select a topic for their work concerns practical issues associated with data collection. In the proposed work under discussion there were a number of possible problems related to data collection. For example, studies employing SNA need a very high rate of response. This is because the data are highly interconnected and measures such as reciprocity, clarity of expectations, and so forth cannot be effectively arrived at if there is a low rate of response. Data collection can also be time-consuming especially while studying change. A longitudinal study covering various stages in the planned change effort might span years. Thus, while deciding on a research problem and in designing the doctoral project, researchers need to make certain crucial choices. There are trade-offs involved in adopting certain approaches or rejecting certain techniques in favour of others. Often researchers find ingenious ways of overcoming limitations. For example, many working scholars collect data from their own organisations and consequently avoid some difficulties associated with data collection mentioned above. References Cook, J. M. (2001). Social networks: A premier. Retrieved February 28, 2007, from http://www.soc.duke.edu/~jcook/networks.html Menon, A. G., Dash, D. P., Vakkayil, J. D., & Kuruvilla, C. D. (2005, July 31). Networks: An emerging paradigm in management research [Report on a seminar led by P. Balkundi at XIMB on July 8, 2005]. Retrieved February 28, 2007, from http://www1.ximb.ac.in/RW.nsf/pages/R3.3
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