Supply Chain Partner Communication in a Managed Programme in the UK Water Industry: A Case Study with Social Network Analysis
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Faculty of Management, Shanghai Business School, Shanghai 201400, China
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Department of Management, Leeds University Business School, Leeds LS2 9JT, UK
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Lazaridis School of Business and Economics, Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada
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Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(21), 4211; https://doi.org/10.3390/ijerph16214211
Received: 29 September 2019 / Revised: 21 October 2019 / Accepted: 22 October 2019 / Published: 30 October 2019
(This article belongs to the Special Issue Water Resources and Hydro-Ecology)
The water industry in every country aims to effectively and efficiently provide water with satisfactory quality in a sustainable and environmentally friendly manner. To this end, it is critical to achieve effective communication among the partners in water supply chain networks. In this paper, we focus on one of the UK’s largest water utility companies and its eight main contractors and analyze the factors influencing partner and network communication in a managed programme of their asset supply chain. We employ social network analysis to conduct the cross-sectional and longitudinal analysis of partner communication. Factors found to influence the communication network are grouping of projects within the programme, individual’s organisational affiliation, status, tenure, elapsed time through the programme lifecycle, and co-location. Our contributions to practice include demonstrating water programme management factors that influence communication and trust and how social network analysis can better inform them about intra- and interorganisational relationships. Moreover, the methodology introduced in this study may be applied to water management in other parts of the world.
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MDPI and ACS Style
Li, Q.; Wang, S.; Shaw, N.; Shi, V. Supply Chain Partner Communication in a Managed Programme in the UK Water Industry: A Case Study with Social Network Analysis. Int. J. Environ. Res. Public Health 2019, 16, 4211.
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