Purpose: Since smartphones became ubiquitous, online grocery and food purchases through take-away delivery platforms have steadily increased in China. Nevertheless, whether the development of take-away delivery can ameliorate urban–rural wage inequality still requires further analysis. The purpose of this paper is to clarify whether this positive effect exists.Design/methodology/approach: This paper makes estimations based on city and individual levels combining the Chinese Household Income Project (CHIP) 2008, CHIP 2013, CHIP2018 survey data and the take-away delivery site data. At the city level, the Oaxaca-Blinder (O-B) decomposition method is employed to construct wage inequality index of urban and rural labors. At the individual level, this paper analyzes urban–rural wage differentials with high or low formal education level.Findings: The rapid establishment of take-away delivery sites has resulted in an increase of 52.425 yuan on average in the annual wage of rural labors with low formal education level. When the cumulative number of sites increases by 1 unit, the annual wage inequality index decreases by 0.007 on average. Labors with the characteristics of rural household registration and low education can enjoy more dividends. Through inter-/within-industry decomposition, this paper elaborates formal education, age and cross-industry transfer as the main factors for the improvement of urban–rural wage inequality. Narrowing effect of wage differences between different groups in multiple sample slices also contributes to the mechanism analyses.Originality/value: To the best of the author’s knowledge, this paper is the first to analyze the impact of take-away delivery development on the urban–rural wage inequality from the perspective of the establishment of take-away delivery sites. This empirical study will enrich the existing theoretical perspectives on urban–rural divide under the emergence of new forms of employment. The results indicate that new forms of employment represented by take-away delivery can not only promote economic growth, but also eliminate urban–rural inequality.

The digital economy has become an important force driving regional transformation and green development, yet existing evidence on its net carbon-balance effects on land-use carbon emission efficiency (LUCEE) remains limited. Using panel data for 41 cities in the Yangtze River Delta from 2002 to 2022, this study first calculates city-level net carbon-emission pressure by jointly considering anthropogenic carbon emissions and land-based carbon sequestration, and then evaluates LUCEE using a super-efficiency SBM model with undesirable outputs, in which urban construction land is incorporated as an independent input rather than used as a common scaling denominator. A two-way fixed-effects model, mediation model, geographical detector, and spatial econometric model are further employed to examine the temporal dynamics, transmission mechanisms, spatial heterogeneity, and spatial associations of the digital economy. This study finds that, in the short term, digital-economy development is significantly negatively associated with LUCEE, while this negative association gradually weakens over time, with no clear evidence of a positive reversal within the observed lag structure. Industrial tertiarisation shows partial and limited evidence as a transmission channel, although it does not automatically translate into greener land-use performance. The digital economy also helps explain LUCEE heterogeneity and shows enhanced explanatory power when combined with government intervention, land-use intensity, industrial tertiarisation, and economic development. Moreover, the spatial analysis provides supplementary evidence of a negative association between digital-economy development in spatially connected cities and local LUCEE, although this finding should be interpreted cautiously given the limited evidence of endogenous spatial dependence. These findings deepen the understanding of the low-carbon consequences of digitalisation and provide policy implications for green digital development, industrial transformation, and regionally coordinated carbon mitigation.

Purpose: With the widespread adoption of artificial intelligence, the number of service robotics in China has steadily increased. However, the role of service robotics in promoting female employment and reducing household burdens remains underexplored. This paper aims to determine whether these positive effects exist. Design/methodology/approach: This paper utilizes data from the Chinese Household Income Project (CHIP 2013, 2018) and the Chinese General Social Survey (CGSS 2017), along with robot patent data. The analysis employs multiple-level sub-sample regression and Oaxaca–Blinder decomposition to explore the impact of service robotics. Findings: The baseline results indicate that a one-unit increase in the number of service robot patents leads to an average increase of 0.493 h in women’s working time, compared to a less significant increase of 0.287 h for men. These findings can be attributed to the reduction of housework burden and the promotion of female empowerment. Regarding the former, both CHIP and CGSS data confirm that service robotics can replace women’s housework time, ease their family burden and change the gender division of labor. For the latter, the Oaxaca–Blinder decomposition results show a reduction in gender wage discrimination, while CGSS data reveal a transformation in gender role attitudes. Originality/value: To the best of the authors' knowledge, this paper is the first to empirically examine the dual role of Chinese service robotics in both the household sector and labor market. This empirical study enriches the existing theoretical perspectives on female employment. It highlights the potential of service robotics to enhance women’s employment opportunities, transform family divisions of labor and address gender imbalances.