Green buildings are not only the optimum avenue to reduce the adverse effects of buildings, but also the inevitable requirement for implementing the concepts of sustainable development in construction. As they are more complicated engineering systems, green buildings face more influencing factors from various aspects than traditional ones. Therefore, those factors and their driving effects must be considered carefully for the purposes of the sustainable development of green buildings. The research samples selected in this paper are 23 typical green building cases in Tianjin. This paper employs the clear set csQCA method to explore the linkage effect of incentive policies, technical support, enterprise recognition, the evaluation standard system, and development cost on the sustainable development of green buildings and path selection. The results show that a single condition is far from enough for the sustainable development of green buildings. Multiple antecedent conditions are developed concurrently to form the diversified configuration driving it. There are three ways to initiate this; the first is a three-element driving system, including incentive policies, enterprise recognition, and development cost; the second is another three-element driving system including technical support, enterprise recognition, and an evaluation standard system; and the last is a four-element driving system, including incentive policy, technical support, evaluation standard system, and development cost. The conclusion of this paper contributes to a deepening of the rational understanding of the nature of the complex interaction of the multiple factors that are behind the sustainable development of green buildings in China, and it, therefore, brings beneficial practical enlightenment for the purposes of sustainable development.

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PurposeOnline customer reviews is an important information resource for product innovation. This study aims to investigate the impact of online customer reviews on iterative innovation of software products and the moderating roles of product complexity in the process of online reviews influencing product iterative innovation.Design/methodology/approachTo empirically test the hypotheses, this paper built a panel data of 500 software products from 2019 to 2021 and applied Poisson regression analysis.FindingsEmpirically results reveal that both sentiment and quantity of online customer reviews have positive effects on iteration innovation of software products. In addition, the authors find that product complexity negatively moderates the relationship between online reviews and iterative innovation.Practical implicationsThis study suggests that firms can acquire valuable information from customers’ online reviews for product iterative innovation and improvement. However, for high-complexity products, it may be difficult for enterprises to obtain useful information for iterative innovation from online reviews. On the other hand, this study provides a reference for firms to choose more useful online reviews from the perspective of sentiment.Originality/valueThis paper provides a new finding that there is a positive relationship between online customer reviews and iterative innovation of software products. Moreover, the authors also provide a deeper understanding of how online customer reviews affects iterative innovation by examining the moderating roles of product complexity.