In order to evaluate the temporal changes in tree diversity of forest vegetation in Xishuangbanna, Yunnan Province, the study collected tree diversity data from four main forest vegetation in the region through a quadrat survey including tropical rainforest (TRF), tropical coniferous forest (COF), tropical lower mountain evergreen broad-leaved forest (TEBF), tropical seasonal moist forest (TSMF). We extracted the distribution of four forest vegetation in the region in four periods of 1992, 2000, 2009, and 2016 in combination with remote sensing images, using simp son Shannon Wiener and scaling species diversity indexes compare to the differences of tree evenness of four forest vegetation and use the scaling ecological diversity index and grey correlation evaluation model to evaluate the temporal changes of forest tree diversity in the region in four periods. The results show that: (1) The proportion of forest area has a trend of decreasing first and then increasing, which is shown by the reduction from 65.5% in 1992 to 53.42% in 2000, to 52.49% in 2009, and then to 54.73% in 2016. However, the tropical rainforest shows a continuous decreasing trend. (2) There are obvious differences in the contributions of the four kinds of forest vegetation to tree diversity. The order of evenness is tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > warm coniferous forest > tropical seasonal humid forest, and the order of richness is tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > tropical seasonal humid forest > warm coniferous forest, The order of contribution to tree diversity in tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > tropical seasonal humid forest > warm tropical coniferous forest. (3) The tree diversity of tropical rainforests and tropical seasonal humid forests showed a continuous decreasing trend. The tree diversity of forest vegetation in Xishuangbanna in four periods was 1992 > 2009 > 2016 > 2000. The above results show that economic activities are an important factor affecting the biodivesity of Xishuangbanna, and the protection of tropical rainforest is of great significance to maintain the biodiversity of the region.

This study examines conditions that impact PPP delivery success or failure in the roadways sector in India using Qualitative Comparative Analysis. QCA is well-suited for problems where multiple factors combine to create pathways leading to an outcome. Past investigations have compared PPP and non-PPP project delivery performance, but this study examines performance within PPPs by uncovering a set of conditions that combine to influence the success or failure road PPP project delivery in India. Based on data from 21 cases, pathways explaining project delivery success or failure were identified. Specifically, PPPs with high concessionaire equity investment and low regional industrial activity led to project delivery success. Projects with lower concessionaire equity investment and low reliance on toll revenue and with either: (a) high project technical complexity or (b) high regional industrial activity, led to project delivery failure. The pathways identified did not have coverage values that they were extremely strong. Coverage strength was hindered by lack of access to information on additional conditions that could be configurationally important. Further, certain characteristics of the Indian market limit generalization. Identification of combinations of conditions leading to PPP project delivery success or failure improves knowledge of the impacts of structure and characteristics of these complex arrangements. This study is one of the first to use fuzzy QCA to understand project delivery success/failure in road PPP projects. Moreover, this study takes into account factors specific to a sector and delivery mode to explain project delivery performance.

Social media influencer marketing has emerged as an essential marketing strategy in the online interactive environment. This study investigates the impact of influencer-consumer fit (ICF) on behavioral intentions; intention to co-create brand value (ICC) and purchase intention (PI), with the serial mediation of influencer authenticity (IA) and attitude toward brand (ATB). A self-administered questionnaire was distributed to followers of social media influencers in Pakistan. The data were collected from 421 female followers of social media influencers through survey and partial least squares—structural equation modeling was used for data analysis. The findings reveal that ICF impacts IA, while the latter impacts ATB. ATB in turn impacts behavioral intentions. The direct effects suggest that ICF impacts consumers’ PI but not the ICC. However, with the serial mediation of IA and ATB, the relationship becomes significant. The findings of this study may assist managers in building brand strategies to achieve excellence in a highly dynamic and competitive market by leveraging the power of influencer marketing.