The vulnerability assessment indicator system (VAIS), including the tourism economic sensitivity and respondence, is modified and established in this paper. According to the collected data, during 2014–2018 of the 31 provinces of China, of the tourism economy sensitivity and respondence, the improved comprehensive evaluation projection pursuit clustering (PPC) model is established, and the vulnerability indexes of the 31 provinces are calculated, thus expanding the tourism economic vulnerability assessment methods. Our empirical results show that, during the period of 2014 to 2018, the sensitivity, the respondence, and the vulnerability indexes are unbalanced overall. The tourism economy sensitivity and the respondence show that the spatiotemporal distribution characteristics are high in the east and low in the west. On the contrary, as for the vulnerability, the spatiotemporal distribution characteristics are low in the east and high in the west. Among the 40 indicators, the ratio of industrial solid waste utilized (%), urbanization rate, and the density of grade highway and railway network (km/km2) have the greatest impact on the respondence, while the proportion of the population affected by natural disasters, the diversification index of industrial structure, and the number of traffic accident casualties have the most significant impact on the sensitivity, which are the indicators that have the greatest impact on vulnerability. Therefore, in order to effectively reduce sensitivity, improve respondence, and thus reduce the vulnerability index of the tourism economy, the provinces should first improve the above-mentioned evaluation indicators with the largest weights. Our research results in this paper enrich the theory of sustainable development of the tourism industry and derive managerial and policy insights for further achieving the high-quality development of the tourism economy.

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.