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Green and smart city is an optimal choice for cities to realize their modernization of governance capacity and sustainable development. As such, it is necessary to clarify the evolutionary characteristics and driving mechanism of urban green and smart development level (GSDL) systematically. From the perspective of green total factor productivity (GTFP), this study adopted the SBM-GML (slack-based model & global Malmquist–Luenberger) method to measure the urban GSDL considering smart input-output elements. Based on the panel data of China's 232 prefecture-level cities from 2005 to 2018, the spatial and temporal evolution characteristics of urban GSDL were explored, and the factors and structural mutation points affecting urban GSDL were analyzed with quantile regression tests and threshold regression tests. The findings of this paper showed that (1) there is an upward trend in the volatility of urban GSDL from 2005 to 2018, in which the eastern region was highest, followed by the central and western regions, and the differentiation showed no converge among regions; (2) the effect of technical progress and technical efficiency improvement on the urban GSDL was demonstrated with a fluctuating "Two-Wheel-Drive" trend on the whole; (3) the urban GSDL was promoted by the opening-up level and urban scale significantly, while inhibited by the level of economic development and government size. Additionally, the effects of industrial structure, financial development level, and human capital level on the urban GSDL were distinctive at different loci; (4) the threshold effects of economic and financial development level on improving the positive effects of industrial structure and opening-up level on urban GSDL were significant. These findings may enrich the research literature on the evolutionary heterogeneity of green and smart cities and provide theoretical and practical exploration for the construction of green and smart cities.

PurposeThe purpose of this paper is to investigate the impacts of different gray markets' structures on both supply chain decisions and associated profits.Design/methodology/approachWithin the context of gray markets, using game theory approach in this paper, supply chains have been considered as assets of manufacturers, distributors and speculators, within which manufacturers sell products to distinctive markets either directly or through authorized distributors, while speculators buy products from a lower price market and then sell them in a higher price market. Our study has examined different decision variables within such a framework.FindingsConsidering a situation where one manufacturer sells its products either directly in one market (Market 1) or through its authorized distributor (Market 2), due to different products prices in both markets, results have shown that, when market elasticity is less than its critical value, a speculator can sell a gray market product arbitrage in market 2, whereas when the market elasticity is greater than its critical value, a speculator can sell a gray market product arbitrage in market 1. In addition, manufacturers—as leaders of Stackelberg game—are always the most profitable stakeholders within a gray market supply chain.Practical implicationsIn this study, equilibrium results for each market have been obtained, optimal results have been compared, and accordingly, valuable insights have been developed. Such results would help managers to take better managerial decisions, as well as strategizing policies in gray markets.Originality/valueIn this paper, we have considered a gray market where both distributors and speculators exist and act as parallel channels. To the best of our knowledge, the extant literature focuses either on distributors or speculators, but never concurrently on both. In fact, the coexistence of one distributor and one speculator in a gray market will impact their own decisions, as well as both decisions and profits of other stakeholders, and hence, will exert an impact on the manufacturer side.