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Complex mechanical 3D computer-aided design (CAD) model embodies rich implicit design knowledge. Through discovering the key function parts and key function module in 3D CAD assembly model in advance, it can promote the designers’ understanding and reuse efficiency of 3D assembly model in design reuse.

An approach for discovering key function module in complex mechanical 3D CAD assembly model is proposed. First, assembly network for 3D CAD assembly model is constructed, where the topology structure characteristics of 3D assembly model are analyzed based on complex network centrality. The degree centrality, closeness centrality, betweenness centrality and mutual information of node are used to evaluate the importance of the parts in 3D assembly model. Then, a multi-attribute decision model for part-node importance is established, and the comprehensive evaluation for key function parts in 3D assembly model is accomplished by combining Analytic Hierarchy Process and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Subsequently, a community discovery of function module in assembly model-based Clauset–Newman–Moore (CNM)-Centrality is given in details. Finally, 3D CAD assembly model of worm gear reducer is taken as an example to verify the effectiveness and feasibility of proposed method.

The key function part in CAD assembly model is evaluated comprehensively considering assembly topology more objectively. In addition, the key function module containing key function part is discovered from CAD assembly model by using CNM-Centrality-based community discovery.

The approach can be used for discovering important design knowledge from complex CAD assembly model when reusing the assembly model. It can help designers capture and understand the design thinking and intent, improve the reuse efficiency and quality.

The paper first proposes an approach for discovering key function module in complex mechanical 3D CAD assembly model taking advantage of complex network theory, where the key function part is evaluated using node centrality and TOPSIS, and the key function module is identified based on community discovery.

This study aims to examine whether a firm's demand for high-quality auditors is influenced by multiple large shareholders (MLS). As one type of ownership structure, MLS have gained popularity in China recently and have different types of large shareholders, including large institutional shareholder, large foreign shareholder and large state shareholder. The authors also examine whether different types of MLS have heterogeneous impacts on appointing high-quality auditors.

With a sample of 27,131 firm-year observations from Chinese public companies from 2003 to 2018, the authors use multivariate regressions to examine the effect of MLS on auditor choice. Heckman two-stage analysis, a firm fixed effects model, propensity score matching and difference-in-differences test are used as robustness checks.

This paper finds that the presence and power of MLS increase the likelihood of appointing high-quality auditors. With regard to the types of MLS, large institutional shareholders and foreign shareholders have significant positive effects on appointing high-quality auditors, while the presence of state-owned large shareholders has no effect on auditor choice. Further analyses reveal that the positive effect of MLS on high-quality auditor choice is more pronounced in firms with severe agency problems and information asymmetry. Taken together, these results suggest that MLS play a monitoring role by demanding high-quality auditors.

This paper contributes to the literature on the determinants of auditor choice. While prior studies primarily focus on the impact of concentrated ownership structure, corporate governance and the pressure from stakeholders on auditor choice, this paper complements the literature by providing evidence from the heterogeneous effects of different types MLS. This paper also extends the literature on the consequences of MLS from the perspective of auditor choice.