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.     

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.     

Gender differences in Russia's job mobility and its rewards*

This article considers age and gender differences in the probability and consequences of job mobility in Russia. Little is known about who is mobile and whether mobility impacts wages once the characteristics of movers are controlled for. Results show a gender difference in the likelihood of exit but not promotion. Results also show that promotions have a positive effect only on the wages of young women, but young men's wages are not affected. Further, young men see a significant decrease in wages following an exit, while young women are not affected by firm exit. The article shows that early mobility is particularly important for women, who earn less overall. Results help to understand processes of inequality in wages and conditions that occur due to sorting, and the importance of promotions as ‘life chances’ which lead to ‘career-track jobs’. Gender differences in securing such life chances may help to understand gaps in earnings, which emerge later.     

Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

Dynamics of Child Malnutrition in Rural and Small‐Town Ethiopia

Improving the status of malnourished children, and preventing children from becoming malnourished, lies at the heart of several of the Sustainable Development Goals. While many cross‐sectional studies examine correlates of stunting, they largely cannot identify drivers of change in stunting. We use two waves of panel data from Ethiopia and incrementally larger sets of fixed effects to control for time‐variant observable characteristics and time‐invariant unobservable characteristics. After controlling for these potential confounders, our analysis reveals that many factors that are associated with stunting in the cross‐section do not impact stunting dynamics. We also estimate individual fixed‐effects regressions, separately, according to baseline stunting status. We find evidence suggesting that while improved societal conditions drive many children out of a stunted state, certain exogenous factors may lead previously healthy children to become stunted. Overall, policymakers and practitioners would be wise to consult research utilising both cross‐sectional and panel data analyses in order to more effectively target already stunted children as well as vulnerable children who may be at risk of becoming stunted.     

河南省城镇化时空格局及驱动力分析

[目的]通过分析城镇化时空格局及其驱动力用来表现河南省城镇化近10年状态,并通过驱动力分析其主要影响因素。[方法]文章选取人均GDP、财政收入、第三产业生产总值、全社会固定资产投资、在岗职工平均工资、各市参加医疗保险人口、天然气用气人口、各市普通高中毕业生、废水排放量、生活垃圾处理量、固体废物处理量、道路清扫保洁面积等12个指标构建综合指标体系,运用SPSS因子分析确定权重,测算2005~2015年河南省城镇化发展水平并分析其时空演变特征,在此基础上利用灰色关联度分析城镇化发展驱动力。[结果]河南省城镇化水平在时间维度上呈上升趋势,空间上表现为高城镇化水平集中在河南省西北部地区,有向东北部发展的趋势;低水平城镇化地区集中在河南省中南部地区且数量逐渐减少;中等水平的城镇化地区集中在河南省周边的地级市,数量逐渐增多,且有向高等城镇化水平发展的趋势;就驱动力影响力而言,市场机制高居第一,其次是政府作用、自身发展、外商投资。[结论]河南省城镇化水平空间差异显著,并受多种驱动力共同影响。     

Investment decision-making under economic policy uncertainty

It is widely established that economic policy uncertainty (EPU) affects investment decisions and performance, yet research in this area has overlooked the direct property investment market. This article seeks to rectify this and proposes a multistage multilevel analytical framework to offer new insights and a richness of findings. Using a news-based measure of EPU in the United Kingdom, and controlling for economic conditions, a national-level analysis reveals some evidence of Granger-Causality between EPU and total returns, indicating that pricing is responsive to uncertainty. These findings suggest that EPU is an important risk factor for direct property investments, with pricing implications. Differences in data and performance measure are important, however, with income returns unresponsive. A micro-level investigation begins to reveal some of the asset-pricing decisions underpinning the national results, indicating investors’ concerns for income streams are consistently high, regardless of varying EPU. Pricing can also cause changes in EPU, such as in the retail and industrial markets (increasingly linked through logistics) reflecting sector-specific stakeholder groups and newsworthy issues. This evidence highlights how important it is for policy-makers to understand the complex and bi-directional relationship, that indecision can undermine investment confidence and cause investment market volatility, in turn raising EPU.     

Green human resource management: Development of a valid measurement scale

The objective of the study was to develop a valid measurement scale for green human resource management (HRM). Even though the common practices of green HRM have been presented in much of the literature, the previous studies focused only on a small number of functions in integrating environmental management with HRM. Additionally, the measurement of green HRM practices still calls for empirical validation. The two‐stage methodology of structural equation modeling in AMOS was employed for data analysis. Exploratory factor analysis revealed seven dimensions of the construct measured by 28 items. Confirmatory factor analysis confirmed the factor structure. The measuring instruments revealed convergent and discriminant validity. Several model fit indices indicated the model fitness. The study provided supplementary evidence on the underlying structure of the construct that can be valuable to researchers and practitioners in this area.     

A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a production possibility frontier with a model of technical inefficiency. The model addresses both spatial dependence and heteroskedastic technical inefficiency. This study applies maximum likelihood methods considering the endogenous spatial lag term. The proposed model nests several existing models. Further, an empirical analysis using data on the Japanese manufacturing industry is conducted and the existing models are tested against the proposed model, which is found to be statistically supported. The findings suggest that estimates in the existing spatial and non-spatial models may exhibit bias because of lack of determinants of technical inefficiency, as well as a spatial lag. This bias also affects the technical efficiency score and its ranking.