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Nowadays, in such a competitive business environment, under the pursuit of high quality and high standards, every enterprise has clearly realized that the quality of products is directly related to the interests of the enterprise, the development of the enterprise, and the survival of the enterprise. The idea that quality is life has long been deeply rooted in every enterprise. Based on the aforementioned reality, this paper first constructs a demand function affected by product quality, service quality, reference effect and quality competition, and studies the optimal product quality and service quality under centralized decision-making and decentralized decision-making. By comparing the decision values and profit difference between centralized decision making and decentralized decision making, a bilateral cost sharing contract is proposed, and its application scope is discussed. The major findings entail that the centralized decision-making mode of supply chain will be more conducive to improving service quality. However, it is not necessarily conducive to improving product quality, which depends on the marginal profits of competitors, since supply chain decision-makers are more willing to invest resources in products with high marginal profits, thereby improving product quality. The increase of reference effect is conducive to improving the quality of products and services, but it may also lead to higher production costs in the case of centralized decision-making. Therefore, when the reference effect is high, supply chain enterprises should adopt decentralized decision-making mode. Excessive competition is not conducive to improving the profits and increases internal friction among enterprises. Therefore, when the competition is fierce, enterprise alliance is a better choice. Finally, the bilateral cost sharing contract can coordinate the supply chain, that is to say, the system profit is equal to the profit of centralized decision-making. However, only when the supplier’s share rate meets certain conditions can the bilateral cost sharing contract achieve Pareto optimization, that is to say, when it is greater than the profit of the enterprise under decentralized decision-making.

Due to the sudden surge of orders, it is difficult for suppliers with a limited capacity to ensure that all orders are delivered in time and all the products are qualified. Suppliers are likely to put more limited capacity into completing orders, thus ignoring the quality of products. This will easily lead to the occurrence of product quality events, and then affect the goodwill of enterprise products. The innovations of this paper are as follows: first, based on the above facts, a negative and dynamic correlation between the delivery level and the quality level is established, which has been involved in previous studies. Second, the joint decision model of timely delivery, product quality, and marketing is constructed. Thirdly, centralized decision-making is the best way of supply chain cooperation, and cost sharing contracts can coordinate the supply chain. This paper provides guidance for enterprise managers when making decisions on quality, marketing and delivery. It also provides the basis for enterprise managers to formulate effective cooperation models. We can draw some research implications: when consumers are less sensitive to timely delivery, enterprises should give some coupons and small gifts to consumers in exchange for the extension of delivery time and put their limited capacity into improving the product quality. When consumers are highly sensitive to timely delivery, they can outsource some orders to cost-effective and professional third-party enterprises, which not only improves the delivery rate but also improves the product quality.

Quality is not only the basis for business survival and development but also a key issue that cannot be ignored in supply chain management decisions. In practice, the impact of quality on goodwill does not show an immediate effect, and there is a dynamic delayed effect. Therefore, we developed a dynamic model that considers the delayed effect of quality on goodwill. Firstly, we constructed a delayed differential equation for the effect of quality on goodwill based on the Nerlove–Arrow model for a two-channel supply chain in a competitive environment and studied the dynamic quality decision problem of manufacturers and retailers under the delay effect. Secondly, we constructed the manufacturer and retailer Hamilton functions based on the principles of being of great value, solving and comparing the optimal product quality level, having an optimal service quality level, product goodwill, and overall profit of the supply chain under both decentralized and centralized decision modes, and investigated the effect of delay time on the profit and quality decisions of supply chain members. The conclusions show that: (i) delay time is an important reference for supply chain members when choosing the decision mode, and the overall profit size of the supply chain has different relationships with the different values of delay time taken into account with the two decision scenarios. (ii) Adopting a centralized decision mode can motivate manufacturers and retailers to improve the quality level, which in turn promotes the sales of products and the accumulation of brand goodwill.

With the rapid development of smart cities in the world, research relating to smart city evaluation has become a new research hotspot in academia. However, there are general problems of cognitive deprivation, lack of planning experience, and low level of coordination in smart cities construction. It is necessary for us to develop a set of scientific, reasonable, and effective evaluation index systems and evaluation models to analyze the development degree of urban wisdom. Based on the theory of the urban system, we established a comprehensive evaluation index system for urban intelligent development based on the people-oriented, city-system, and resources-flow (PSF) evaluation model. According to the characteristics of the comprehensive evaluation index system of urban intelligent development, the analytic hierarchy process (AHP) combined with the experts’ opinions determine the index weight of this system. We adopted the neural network model to construct the corresponding comprehensive evaluation model to characterize the non-linear characteristics of the comprehensive evaluation indexes system, thus to quantitatively quantify the comprehensive evaluation indexes of urban intelligent development. Finally, we used the AHP, AHP-BP (Back Propagation), and AHP-ELM (Extreme Learning Machine) models to evaluate the intelligent development level of 151 cities in China, and compared them from the perspective of model accuracy and time cost. The final simulation results show that the AHP-ELM model is the best evaluation model.