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Developmental and prescriptive advising styles have been the focus of the academic advising literature for the past 35 years. Academic advising scholars have called for a new paradigm in the field. Drawing from leadership theory, a new model for academic advising is proposed. Full range advising encompasses laissez-faire, management-by-exception, contingent rewards, and transformational behaviors. The long-term impact of transformational advising is one that will likely take years to fully realize, however measures of transformational leadership are both reliable and valid. These measures can be used to determine whether advisors’ use of transformational advising behaviors is related to positive student outcomes.

Effective policy to support business ecosystems should build on evidence-based analyses of firm-level activities and outcomes. This paper aims to contribute to this requirement and makes three contributions. The first contribution is to extend the application of the network capital concept to a variety of eight distinct linkage categories (e.g. suppliers, customers and business support agencies) that support networking and clustering, in both activity and impact terms. The second contribution is outlining a novel method of network visualisation (V-LINC) based on the collection of primary and qualitative data. The third contribution is in applying the method to one cluster, information and communications technologies.

Qualitative research on the nature and extent of organisational network linkages was undertaken. Structured interviews with a set of focal firms followed a tailored design approach. The concept of network capital was extended and applied to the cluster context by measuring network inputs and output (i.e. investments and impact). The approach was operationalised via a novel impact measurement approach, denoted as V-LINC, an acronym for visualising linkages in networks and clusters.

The authors develop a business impact framework exploiting novel linkage visualisations and qualitative data from firms in a cluster in one city region across eight linkage types to capture distinct network capital elements. Organisational inputs into network development, measured as investment and involvement indicators and organisational outcomes from those networks, measured as importance and intensity indicators, are used to assess network performance. A comprehensive, systematic and robust analysis of network elements and performance is possible. Distance is found to interact differently across linkage types. Targeted recommendations may be made from the analysis of local or regional business ecosystems in light of measured business impacts of linkages.

Due to the resource-intensive nature of data collection, the current study engages a limited sample of firms and interviewees. Applications of this approach in other contexts will permit further research into its usefulness in evaluating business impacts generated through networking activities.

The method introduced here (V-LINC) offers a novel means to include both geography network theory into an understanding of knowledge relationships and networks within clusters. Accounting for both distance and linkage type reveals which categories of intra-regional and extra-regional linkages generate the greatest impact, given their frequency. The approach adds to available cluster visualisation and analysis approaches through identifying patterns of disaggregated knowledge flows and their impacts, with application to evaluation demands of policy.