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Empirical studies regarding the impact of the real exchange rate (RER) on economic growth are extensively available. However, the literature as a whole appears to report varying results, while the causes of such differences have not been analyzed systematically. The present study aims to fill the gap in the literature.

In this paper, the authors compile 543 empirical estimates from 51 studies of the exchange rate-growth nexus in order to meta-analyze its relationship. Meta-analysis allows the authors to quantitatively synthesize previous empirical studies and explain the variation in the results. This method also enables us to investigate the possibility of publication bias, as there is a tendency in research only to report results that are both statistically significant and show the expected signs.

After addressing publication bias and heterogeneity in the estimates, the meta-regression results show that RER depreciation (or undervaluation) genuinely favors economic growth. On average, RER depreciation has a greater impact on economic growth in developing countries than the developed ones. The study’s results imply that maintaining an undervalued RER could be favorable to spur economic growth, especially in developing countries.

Initially predominant in the medical literature, meta-analysis has been on a rising edge in economics. This progress has produced many systematic quantitative review analyses with continuously improved statistical-econometric practices related to economic variables. However, to the authors’ knowledge, no comprehensive meta-regression analysis of the relationship between exchange rate and economic growth has been conducted and published in any publicly accessible academic outlet. Therefore, this study aims to fill this gap in the literature.

Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance impact of unit loads, e.g. pallets or rolling cages, utilized by pickers to pack products after picking them from storage locations.

An empirical analysis of archival data on a manual order picking system for deep-freeze products was performed in cooperation with a German brick-and-mortar retailer. The dataset comprises N = 343,259 storage location visits from 17 order pickers. The analysis was also supported by the development and the results of a batch assignment model that takes unit load selection into account.

The analysis reveals that unit load selection affects order picking task performance. Standardized rolling cages can decrease processing time by up to 8.42% compared to standardized isolated rolling boxes used in cold retail supply chains. Potential cost savings originating from optimal batch assignment range from 1.03% to 39.29%, depending on batch characteristics.

This study contributes to the literature on factors impacting order picking task performance, considering the characteristics of unit loads where products are packed on after they have been picked from the storage locations. In addition, it provides potential task performance improvements in cold retail supply chains.

Firms use Relative Performance Information (RPI) to improve employee performance; however, differences in employees’ remote work environments call into question whether RPI improves performance in remote work arrangements. By manipulating RPI provision across sections, the authors examine whether RPI improves performance in remote work arrangements using a field experiment in introductory accounting courses taught during the COVID-19 pandemic. The authors found that RPI improves performance in a remote work setting, as students receiving RPI achieved higher exam scores and increased their exam scores to a greater extent than students who did not receive RPI. The authors also found that lower performers improved performance more than higher performers in response to RPI, and the effect of RPI was more pronounced in those closest to meaningful thresholds. These results inform practice on the expected benefits of implementing RPI in a remote work setting.

Known as the major capital providers in Belt and Road countries and the largest carbon emitter in the world, what role China's outward direct investment (ODI) plays in carbon neutralization has become a matter of concern. This study aims to measure the impact of China's ODI on the carbon emissions of Belt and Road countries.

Based on an econometric model and an inter-regional input–output model, a new model measuring the carbon emission effects of ODI is developed.

The empirical results show that (1) in general, China's ODI generates an emission-reduction effect in Belt and Road countries; (2) The relationship between the emission-reduction effect and income level of host countries shows an approximate inverted U-shaped trend; and (3) China's ODI generates stronger emission-reduction effects on capital-intensive industries.

This study quantitatively measures the scale of carbon emission-increase and reduction effect, which is relatively lacking in previous studies. This study explores the heterogeneity from the perspectives of regions, countries and industries. The authors have compiled an inter-regional input–output table for the Belt and Road countries for 2014 to provide a broad basis for the study of related issues.

Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.

Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.

The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.

Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.

Increasing personnel costs and labour shortages have pushed retailers to give increasing attention to their intralogistics operations. We study hybrid order picking systems, in which humans and robots share work time, workspace and objectives and are in permanent contact. This necessitates a collaboration of humans and their mechanical coworkers (cobots).

Through a longitudinal case study on individual-level technology adaption, we accompanied a pilot testing of an industrial truck that automatically follows order pickers in their travel direction. Grounded on empirical field research and a unique large-scale data set comprising N = 2,086,260 storage location visits, where N = 57,239 storage location visits were performed in a hybrid setting and N = 2,029,021 in a manual setting, we applied a multilevel model to estimate the impact of this cobot settings on task performance.

We show that cobot settings can reduce the time required for picking tasks by as much as 33.57%. Furthermore, practical factors such as product weight, pick density and travel distance mitigate this effect, suggesting that cobots are especially beneficial for short-distance orders.

Given that the literature on hybrid order picking systems has primarily applied simulation approaches, the study is among the first to provide empirical evidence from a real-world setting. The results are discussed from the perspective of Industry 5.0 and can prevent managers from making investment decisions into ineffective robotic technology.

Despite the growing research interest in gender diversity, the presence of female executives and organizational outcomes, the relationship between female executives and employment relations outcomes remains under-researched. This study aims to examine the potential relationship between female executives and employment relations outcomes, with the gender gap as a focus.

A cross-sectional survey was used to collect data from 2,682 workers from 119 manufacturing firms in Guangdong Province, southern China.

Results show that firms with female executives are more likely to comply with labor laws and promote staff development. The association between female executives and promotion opportunities is stronger for female employees than for male employees. However, there is no significant association between female executives and employee salaries.

This research contributes to employment relations literature and extends the application of social role theory to studies of employment relations in particular societal contexts. This study also provides possible boundary conditions for the existence of queen bee behavior by using data from Chinese factories.

The advancement of enterprise social networks (ESNs) facilitates information sharing but also presents the challenge of managing information boundaries. This study aims to explore the factors that influence the information-control behavior of ESN users when continuously sharing information.

This study specifies the information-control behaviors in the “wall posts” channel and applies communication privacy management (CPM) theory to analyze the effects of the individual-specific factor (disposition to value information), context-specific factors (work-relatedness and information richness) and risk-benefit ratio (public benefit and public risk). Data on actual information-control behaviors extracted from ESN logs are examined using multilevel mixed-effects logistic regression analysis.

The study's findings show the direct effects of the individual-specific factor, context-specific factors and risk-benefit ratio, highlighting interactions between the individual motivation factor and ESN context factors.

This study reshapes the relationship of CPM theory boundary rules in the ESN context, extending information-control research and providing insights into ESNs' information-control practices.

The purpose of this paper is to focus on the role of stress and work from home and their influence on the frequency of praying (spirituality) and attending ritual services (religiosity).

Drawing from a data set from Understanding Society (COVID-19 study) in the UK from 5,357 participants, this study specifies a two-level mixed-effects ordered-probit regression to test the main hypotheses and chi-square (x²) analysis, gamma (γ) and tau-b (τ_b) for checking the robustness of this study results.

The findings of this study exhort with statistical confidence that spirituality is positively related to religiosity. Working from home positively influences individuals’ spiritual and religious needs, while attending religious services in person is associated with less stress. Females have been found to be more likely to pray rather than attend religious services.

This study investigates the role of work from home and stress on spirituality and religiosity, two key elements often forgotten in personal life and copying. This paper considers spirituality as the frequency of praying, while religiosity is the frequency of attending rituals, which religion has institutionalised.

People who use drugs (PWUD) have been disproportionately affected by the COVID-19 pandemic. This study aims to examine changes in illicit opioid use and related factors among incarcerated PWUD in Quebec, Canada, during the pandemic.

The authors conducted an observational, cross-sectional study in three Quebec provincial prisons. Participants completed self-administered questionnaires. The primary outcome, “changes in illicit opioid consumption,” was measured using the question “Has your consumption of opioid drugs that were not prescribed to you by a medical professional changed since March 2020?” The association of independent variables and recent changes (past six months) in opioid consumption were examined using mixed-effects Poisson regression models with robust standard errors. Crude and adjusted risk ratios with 95% confidence intervals (95% CIs) were calculated.

A total of 123 participants (median age 37, 76% White) were included from January 19 to September 15, 2021. The majority (72; 59%) reported decreased illicit opioid consumption since March 2020. Individuals over 40 were 11% less likely (95% CI 14–8 vs 18–39) to report a decrease, while those living with others and with a history of opioid overdose were 30% (95% CI 9–55 vs living alone) and 9% (95% CI 0–18 vs not) more likely to report decreased illicit opioid consumption since March 2020, respectively.

The authors identified possible factors associated with changes in illicit opioid consumption among incarcerated PWUD in Quebec. Irrespective of opioid consumption patterns, increased access to opioid agonist therapy and enhanced discharge planning for incarcerated PWUD are recommended to mitigate the harms from opioids and other drugs.