Integrating qualitative and quantitative techniques in network analysis

Abstract

Purpose

This article introduces a method for assessing network dynamics over time. It integrates a qualitative approach to data collection with a bifocal approach to data analysis, i.e. where data are interpreted with two lenses: qualitative and quantitative.

Design/methodology/approach

The dynamics of an entrepreneurial firm's network are analyzed by combining: content and event analysis of case data and network maps with the use of UCINET 6, a software package developed for social network analysis.

Findings

In illustrating the bifocal approach, steps related to data collection, preparation and analysis are discussed. The findings show how the bifocal approach captures change in both a network's structure and its interactions, through a firm's life‐stages.

Research limitations/implications

The primary limitation of the approach is that reliance on UCINET 6 statistics oversimplifies network analysis. Thus, optimal use of the approach is best achieved when the structural patterns generated by UCINET 6 are balanced by qualitative analysis of the interactional dimensions of the network on a longitudinal basis. Future research opportunities include cross‐network analysis and examination of the networks of lead entrepreneurs in comparison with one another, over time.

Practical implications

The bifocal approach allows examination of network power shifts and identification of opportunities for strategic action and relationship management.

Originality/value

This article shows that the application of the bifocal approach facilitates a more meaningful analysis of networks than does a purely qualitative approach. It allows for time‐based examination of whole systems of organizations and scrutiny of dimensions pertaining to both network structure and the interactions and relationships between individual actors.

Citation

Coviello, N.E. (2005), "Integrating qualitative and quantitative techniques in network analysis", Qualitative Market Research, Vol. 8 No. 1, pp. 39-60. https://doi.org/10.1108/13522750510575435