Small and medium-sized enterprises (SMEs) are important promoters of national economic development, how to promote the sustainable development of SMEs has significant theoretical and practical significance. The exogenous growth theory points out that network ties have become an important way for SMEs to obtain external resources and promote enterprise growth. However, the existing research ignores the impact of network ties on the business model innovation of SMEs. Focusing on this theoretical gap, this study constructs a "network ties - business model innovation - enterprise growth" model to explore the influence mechanism of five network ties of SMEs: customer ties, supplier ties, competitor ties, political ties and knowledge ties on business model innovation and enterprise growth. Based on a questionnaire survey of 234 SMEs in Chengdu, China, the research hypothesis was tested using PLS-SEM and fsQCA analysis. The PLS-SME results show that customer, supplier, competitor, and knowledge ties of SMEs have a significant positive effect on business model innovation, and business model innovation has a significant positive effect on enterprise growth. In addition, business model innovation plays a mediating role between supplier ties, competitor ties, knowledge ties, and enterprise growth. The fsQCA results show that three paths lead to the high-level business model innovation of SMEs, among which customer ties, supplier ties, com-petition ties, and knowledge ties are the necessary conditions, and three paths lead to high-level growth of SMEs, among which business model innovation is the most core necessary condition. Different combinations of business model innovation and customer ties, customer ties, supplier ties, competition ties, and knowledge ties lead to the growth of SMEs. Overall, the analysis results of PLS-SEM are consistent with those of fsQCA. The conclusion of this study not only enriches the relevant research of social network theory and business model innovation but also provides practical enlightenment for SMEs managers to use network ties to realize business model innovation and promote enterprise growth.

With the emergence of digital transformation, there is an increasing need for Chinese construction companies to adopt digital procurement (D-procurement). However, there is a lack of theoretical foundation to guide and support the adoption practices. This study aims to fill the research gap through the provision of a model by grouping a set of relevance-based critical success factors (CSFs) into the Technology–Organisation–Environment (TOE) framework for D-procurement adoption success (DAS). A case study approach is applied in the research. We selected H Group as it is one of the most representative D-procurement cases in China. The study includes two parts. In the first part, a systematic literature review was conducted, and 17 CSFs were identified from 12 selected studies. By grouping the 17 CSFs into the TOE framework, we put forward a basic CSF–TOE model. In the second part, an in-depth interview was carried out in H Group, where the 17 selected experts were asked to rank the previously identified CSF. Based on their order of relevance, the 17 CSFs were re-organised in the basic CSF–TOE model, and a relevance-based CSF–TOE model was finally proposed. This study is vital for D-procurement adoption because most existing CSF studies are based on the literature and questionnaire surveys, and there is a lack of actual case studies. In addition, this study significantly contributes to the field of D-procurement adoption for construction companies by providing a theoretical framework for practice and a relevance-based CSF–TOE model for research.

Platform ecosystems, as a new organizational form, provide enterprises with new contexts for innovation and entrepreneurship. However, due to a lack of dynamic data, we do not understand how the platform ecosystem evolves. Because the traditional methods have limitations, this study uses computer simulations to investigate the evolution and knowledge change of innovative cooperation networks in the platform ecosystem from the perspective of complex networks. The results indicate that the platform ecosystem’s innovation cooperation network evolves around initial network enterprises. The degree of enterprise cooperation shows a trend of decreasing first then increasing, but the efficiency of enterprise cooperation gradually decreases. Second, as the network evolves, the knowledge level rises, whereas the knowledge growth rate falls in the platform ecosystem. Meanwhile, the impact of network structure on knowledge change is unclear, whereas enterprise knowledge creation capability, knowledge absorption capability, and competitive pressure all have a significant impact on knowledge change.