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Frugal innovation has become popular in ecologically vulnerable areas in the past decade, as it was initiated under a resource-constrained innovation paradigm. However, there has been limited research on its influence factors and fundamental operating mechanisms in such areas. This paper aims to address this gap by using qualitative comparative analysis (QCA) to analyze unique datasets from three ecologically vulnerable areas in China. Based on the theory of planned behavior, the study identifies three key influence factors in frugal innovation: behavioral attitude, subjective norms, and perceived behavior control. The relationships among these factors and pathways are also described. The study’s findings suggest: (1) frugal innovation is an integrated product of multiple influence factors and pathways, where the same goal can be achieved through different pathways; (2) Three pathways for conducting high-level frugal innovation are identified: attitude-oriented, norm-oriented, and attitude-norm-oriented pathways. Behavioral attitudes and subjective norms are the two dominant factors that influence enterprises to carry out frugal innovation. (3) Perceived behavior control does not play a leading role in frugal innovation as the resource-constrained environment in ecologically vulnerable areas and the characteristics of enterprises heavily influence frugal innovation. (4) The lack of behavioral attitudes and subjective norms are the main causes leading to the low-level frugal innovation of enterprises. In conclusion, this study systematically investigates the different influence factors and pathways of frugal innovation in ecologically vulnerable areas. The findings enrich the frugal theory and promote the effective development strategy of innovation for enterprises in such areas.

As an important driving force for economic development and social progress, women have become an important subject of well-being research. Human well-being is the state of physical and mental health as well as material affluence and includes a variety of factors, such as wealth, education, health, safety, amenities, way of life, and happiness. Based on the established research framework of the Women’s Development Index (WDI) in Northwest China, this paper first measured the objective well-being level of women in Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang from 2003 to 2020 under the influence of ecological factors. In addition, spatial disaggregation and comparative analyses of the spatial imbalance of women’s well-being in Northwest China were carried out using the Theil index and Dagum Gini coefficient. The results show that (1) the WDI in ecologically vulnerable areas in Northwest China increased from 0.525 in 2003 to 0.690 in 2020, indicating an overall increase in well-being. (2) The WDI in the five provinces gradually increased with fluctuations. Among them, Shaanxi always remained in first place in terms of the WDI. (3) From 2003 to 2020, the spatial imbalance of women’s well-being as measured according to the WDI in Northwest China first increased and then decreased. However, the gap in women’s well-being in Northwest China was smaller than the economic gap. (4) From 2003 to 2020, the well-being gap measured by the WDI among the 10 groups of provinces in Northwest China gradually decreased, and the development gap between the provinces and Shaanxi was the largest.

Identifying ecologically vulnerable areas and understanding the responses of phenology to negative changes in vegetation growth are important bases for ecological restoration. However, identifying ecologically vulnerable areas is difficult because it requires high spatial resolution and dense temporal resolution data over a long time period. In this study, a novel method is presented to identify ecologically vulnerable areas based on the normalized difference vegetation index (NDVI) time series from MOD09A1. Here, ecologically vulnerable areas are defined as those that experienced negative changes frequently and greatly in vegetation growth after the disturbances during 2000–2018. The number and magnitude of negative changes detected by the Breaks for Additive Season and Trend (BFAST) algorithm based on the NDVI time-series data were combined to identify ecologically vulnerable areas. TIMESAT was then used to extract the phenology metrics from an NDVI time series dataset to characterize the vegetation responses due to the abrupt negative changes detected by the BFAST algorithm. Focus was given to Jilin Province, a region of China known to be ecologically vulnerable because of frequent drought. The results showed that 13.52% of the study area, mostly in Jilin Province, is ecologically vulnerable. The vulnerability of trees is the lowest, while that of sparse vegetation is the highest. The response of phenology is such that the relative amount of vegetation biomass and length of the growing period were decreased by negative changes in growth for dense vegetation types. The present research results will be useful for the protection of environments being disturbed by regional ecological restoration.