Institutional dynamics and access to non-farm employment in rural China, 1950–1996

This article examines non-farm employment in the context of Chinese rural institutional change, based on evidence from discrete-time logistic models for event history analysis using the Life History and Social Change survey. We find the transition to non-farm sector rose rapidly during the Great Leap Forward and market reform, while the Cultural Revolution saw it reach the lowest ebb. While male advantage prevailed exclusively during the Cultural Revolution and early marketization, education possessed a stable positive effect in all historical periods. Although the returns to different kinds of political capital vary along with institutional dynamics, intergenerational reproduction was greatly reduced after the Cultural Revolution.     

数字经济时代会计变革及对策

随着数字经济时代的来临，以人工智能技术为代表的现代信息技术越来越多地应用到会计工作中，会计工作将进入数字会计时代，向共享会计、管理会计、智能会计发展。为了适应数字经济带来的变化，会计机构要成为企业的“数据中心”，发挥管理和服务职能。会计人员要积极学习现代信息技术和管理知识，实现由核算型向管理型转型。     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

The role of network embeddedness across multiple social networks: Evidence from mobile social network games

This article examines peer influences from network relationships within a social network game (i.e., embeddedness) and across such games (i.e., multiplexity). Drawing on social influence theory, we develop a bivariate Poisson model of users’ repeated visits and latent attrition that accommodates peer interaction after controlling for homophily. We estimate the model using data from two social network games with considerable overlap among network members. We find that friends who are only multiplex across games exert greater peer influence on users’ game visits than members who are embedded within a single game. We also determined that ignoring network multiplexity across games may lead firms to mistarget users due to biased peer influences of embedded friends. This result provides an unresearched explanation—strength of peer influence—for the mixed findings in previous literature on network embeddedness. We utilized our results to conduct several scenario analyses to demonstrate how firms can effectively manage users’ engagement and target users in multiple social network games.     

Bibliometric and Scientometric analysis on CSR practices in the banking sector

This paper provides a bibliometric and Scientometric analysis of the corporate social responsibility (CSR) in banking sector. Our study analyzes 551 articles from the Scopus database to find out the relationship between CSR and banking. A bibliometric method was used to visualize the results using R-studio and VOS viewer software. The Scientometric analysis was conducted to determine the findings and mappings of the research themes, directions of current and future research, impact, co-occurrence, co-citations and impact and collaboration trends. We explore how CSR literature has evolved over the years in the banking sector between 1993 and 2021. We find that publication in the CSR and banking domain has increased significantly during 2017 and 2021. Social aspects, board of directors, CSR, environment, competitions, Islamic banking, sustainability, disclosure, ethics, legitimacy theory, sustainable banking, loyalty, and brand equity are the popular research trends and collaboration trends identified. We also provide further scope of the study based on the extensive review of the past literature. Our findings may provide help to future researchers, bankers, and regulators in understanding the current trends and future research progression in the CSR and banking sector.     

Stock market reactions to monetary policy surprises under uncertainty

This article investigates how uncertainty impacts the effect of monetary policy surprises on stock returns. Using high-frequency US data, we demonstrate that stock markets respond more aggressively to monetary policy surprises during periods of high uncertainty. We also show that uncertainty asymmetrically influences the transmission of positive and negative monetary policy surprises to stock market prices. The amplifying effect of uncertainty is found to be stronger for expansionary shocks than for contractionary shocks. Our robustness analysis confirms that financial uncertainty has a significant role in shaping the influence of monetary policy on the stock market.     

Advertisement policy for dual-channel within emissions-controlled flexible production system

Nowadays, industrial firms are very much careful to build a green environment by reducing carbon emissions. The government imposes some rules and regulations to provide a better eco-friendly environment. In this study, the cap-and-trade mechanism has been considered in a production model to control the carbon emissions rate. The manufacturers invest in advanced green technology to reduce per unit emissions. As online and offline selling is crucial to any industry for increasing customer demand, the manufacturers sell their products by dual-channel and advertise their products by online channel to make more popular of their products. Keeping these in mind, a sustainable flexible production model with single-type substitutable product production is considered here by imposing a cap-and-tax policy, investing in green technology, and advertising for products. This model is divided into two cases: with and without investment in green technology. The demand of each manufacturer depends upon an online selling price, an offline selling price, and an online advertisement of the product. A classical optimization technique helps to get the optimum strategies for the online selling price, offline selling price, advertisement investment, green technology, cycle time, and production rate. From the numerical study, it is proved that the industry gets 6.97% more profit in the case of green technology investment and the proposed study gives 5.74% more profit than the traditional production system. Sensitivity analysis and managerial insights are performed.     

基于区块链技术的建筑材料供应链质量数据安全共享方法

传统方法在建筑材料供应链质量数据安全共享中应用效果不佳，不仅数据误码率比较高，而且数据共享时延比较长，无法达到预期的数据安全共享效果。为此提出基于区块链技术的建筑材料供应链质量数据安全共享方法。利用区块链技术对建筑材料供应链质量数据属性加密，建立建筑材料供应链质量数据安全共享链，整合建筑材料供应链质量数据加密、解密程序，通过对用户身份验证实现对质量数据安全共享，以此完成基于区块链技术的建筑材料供应链质量数据安全共享。实验证明，设计方法的数据误码率在1%以内，数据共享时延在1s以内，具有良好的数据安全共享效果。