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PurposeThe study aims to study the effect of non-cognitive ability in human capital on the wages of rural migrant workers in China. The study also examines the mechanisms by which career choice, career development and social capital influence.Design/methodology/approachBased on the new human capital theory, this paper empirically investigates the effects and mechanisms of rural migrant workers' non-cognitive ability on wages using the 2018 China Family Panel Studies database and Stata 17.0 for construct validation and hypothesis testing.FindingsThe results showed that non-cognitive ability has a significant positive effect on rural migrant workers' wages. Subsequently, the mechanism of non-cognitive ability was examined. In further analysis, the study found that non-cognitive ability has a greater effect on the wages of vulnerable individuals (females, low and medium skills) among the rural migrant workers.Originality/valueThe originality of this study is to break through the existing research perspectives, overcome the limitations of scholars' existing research perspectives focusing on the employment and competitiveness of rural migrant workers in China and explore the factors affecting the rural migrant workers' wages from the perspective of non-cognitive ability as a new entry point by combining psychology. At the same time, the study design is more rigorous, avoiding the measurement error of variables.

Maps can help governments in infrastructure development and emergency rescue operations around the world. Using adversarial learning to generate maps from remote sensing images is an emerging field. As we now know, the urban construction styles of different cities are diverse. The current translation methods for remote sensing image-to-map tasks only work on the specific regions with similar styles and structures to the training set and perform poorly on previously unseen areas. We argue that this greatly limits their use. In this work, we intend to seek a remote sensing image-to-map translation model that approaches the challenge of generating maps for the remote sensing images of unseen areas. Our remote sensing image-to-map translation model (RSMT) achieves universal and general applicability to generate maps over multiple regions by combining adversarial deep transfer training schemes with novel attention-based network designs. Extracting the content and style latent features from remote sensing images and a series of maps, respectively, RSMT generalizes a pattern applied to the remote sensing images of new areas. Meanwhile, we introduce feature map loss and map consistency loss to reinforce generated maps' precision and geometry similarity. We critically analyze qualitative and quantitative results using widely adopted evaluation metrics through extensive validation and comparisons with previous remote sensing image-to-map approaches. The results of experiment indicate that RSMT can translate remote sensing images to maps better than several state-of-the-art methods.

To facilitate the green transformation of enterprises and realize low-carbon development, governments have adopted the policies of carbon emission constraint and carbon trade to promote enterprises' low-carbon production. Although the two policies aim to reduce carbon emissions, they have different effects on enterprises' production. Meanwhile, the development of remanufacturing caters to the low-carbon economy. Therefore, this article establishes the game models between an original equipment manufacturer (OEM) and a remanufacturer under carbon-emission-constraint and carbon-trade policies, analyzing the production decisions of enterprises under different policies to compare the influence of the two policies on outsourcing remanufacturing. The main conclusions of the article are as follows: (1) Both carbon-emission-constraint and carbon-trade policies increase the unit retail price of remanufactured and new products, reducing the new products sales volume. However, the sales volume of remanufactured products only decreases if the discount rate is less than the rate of carbon emissions of the two products. (2) The upper limit of carbon emissions can affect the unit outsourcing cost. The unit cost of outsourcing under the carbon-emission-constraint policy is only higher when the upper limit of carbon emissions is less than a certain threshold, and the discount rate is larger than the proportion of carbon emissions for both products; otherwise, the unit outsourcing cost under the carbon-trade policy is higher. (3) Both policies lessen the total environmental implication. When the upper limit of carbon emissions is less than a particular threshold, the environmental effect of the two manufacturers under the carbon-emission-constraint policy is smaller; otherwise, the environmental impact is smaller under the carbon-trade policy.

PurposeThis paper investigates the buy online and pick up in-store cooperation (BOPSC) of online and offline retailers. Specifically, this study solves the following questions: (1) What is the impact of BOPSC on their optimal price and sales volume of products? (2) When should an online retailer and an offline retailer conduct the BOPSC strategy with each other?Design/methodology/approachThe paper first establishes two game models to explore the equilibriums of online and offline retailers in non-BOPSC and BOPSC. Then the condition for online and offline retailers to implement BOPSC strategy are determined. Furthermore, the applicability of the BOPSC strategy is enhanced by incorporating numerical analysis.FindingsThe study's findings reveal that BOPSC strategy will not always beneficial to online and offline retailers, which depends on the total cost of online shopping and the product valuation of consumers. BOPSC strategy leads to the increase of prices and online orders, and the demand of offline retailer is eroded. Moreover, BOPS cooperation between different retailers is easier to achieve than omni-channel integration strategy. When the convenience difference between offline shopping and BOPSC pick-up is moderate, the effectiveness of BOPSC strategy can be improved.Originality/valueThis study has the following two main contributions: Firstly, the authors investigate the effects of BOPSC strategy on the prices of online and offline retailers. The study results show that the BOPSC strategy alleviates price competition and promotes a win–win situation between online retailers and offline retailers. Secondly, this paper mainly studies the cooperative behavior between online and offline retailers and reveals the optimal conditions for online and offline retailers to adopt BOPSC strategy. It can help small- and medium-sized online and offline retailers to choose suitable products for BOPSC strategy, so as to achieve the purpose of increasing profit.

A seller designs a mechanism to sell a single object to a potential buyer whose private type is his incomplete information about his valuation. The seller can disclose additional information to the buyer about his valuation without observing its realization. In both discrete-type and continuous-type settings, we show that discriminatory disclosure—releasing different amounts of additional information to different buyer types—dominates full disclosure in terms of seller revenue. An implication is that the orthogonal decomposition technique, while an important tool in dynamic mechanism design, is generally invalid when information disclosure is part of the design. (JEL D11, D82, D83)