Smart community is an important constituent part of a smart city and an extension and deepening of the concept of the latter. When it comes to smart community, the digitalization upgrading of traditional community service is conducted via information technology, in an effort to improve the service experience of community residents and elevate their happiness index. From social functions, smart community also has the advantages in facilitating the smart transformation of cities, promoting the harmonious society construction, and improving governmental efficiency and image, among others. However, various problems persist in the construction and development process of a smart community, such as mismatching service contents and low service quality. To explore the influencing factors of smart community service quality, a total of 16 influencing factors were extracted from 5 dimensions: service object, service subject, government role, management system, and service content. The relationships among the influencing factors were analyzed via the decision-making trial and evaluation laboratory (DEMATEL)-interpretative structural modeling (ISM) composite model, and a multi-order explanation model was constructed for these influencing factors. Result shows that the legal guarantee is the root cause influencing the smart community service quality. Development standard, basic service, and expected service are deep influencing factors that play mediating roles. Middle-layer factors such as service and operating systems have a direct bearing on quality perception. The surface-layer factors directly decide residential assessment on the smart community service quality. This study has also manifested the feasibility of the integrated DEMATEL-ISM method in analyzing the action mechanism of influencing factors for smart community service quality, providing a new analytical idea and modeling method for the smart community service quality.

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Based on information technology, smart government processes information data to help improve the efficiency of government operations. Information security has become the key to the transformation of government wisdom and improvement of government service efficiency and transparency. To explore the influencing factors of government information security, 27 influencing factors from 6 dimensions of personnel, facilities, information, personnel management, system, and environment were extracted. The decision-making trial and evaluation laboratory (DEMATEL)-interpretative structural modeling (ISM) composite model was used to determine the importance of each factor, the mechanism between the influencing factors was analyzed, and a smart government information security interpretation structure model was constructed. Results show that policies and regulations are the root factors affecting the information security of the smart government. The international environment is a deep-layer influencing factor on government information security. Infrastructure, moral training, and other factors are middle-layer influencing factors that are influenced by the superior factors. Psychological factors, platform construction, and others are surface-layer influencing factors that play a connecting role. Security awareness, behavior security, moral level, and others are directly influencing factors and determine the level of smart government information security. Results of this study also show the feasibility of DEMATEL-ISM model in identifying the relevant factors and analyzing their influencing mechanism on smart government information security. A novel modeling method and its analysis approach are provided for the government to improve the level of information security.

Whether a complex product system integrator can reasonably choose a collaborator is one of the key factors for the success of a complex product system R & D project. The study aims to provide a scientific basis for the selection of suitable collaborators for complex product system integrators, which offers a practical guide for the smooth development of complex product system R & D projects. Firstly, this work summarized the factors affecting the selection of collaborators based on the characteristics of complex product systems. Then, an evaluation index system model for collaborators of complex product systems based on AHP and gray correlation methods was built. Finally, an example analysis identified the feasibility of this method. The evaluation process is simple and intuitive, and the results are scientific and effective.