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This paper aims to investigate the contents of heavy metals Cd, Cr, Ni, Cu, Pb and Zn in the soil of vegetable production bases in the Yongnian County of Hebei Province by random sampling.

The environmental quality conditions of these heavy metals were evaluated by both the single quality index and comprehensive quality index methods.

It was concluded that the average heavy metal contents in the soil of protected vegetable fields in the Yongnian County are all under the limit values prescribed by the environmental quality evaluation standard for farmland of greenhouse vegetables production (2007), so the soil’s environmental quality is classified as first class regarding cleanliness. It is fit for the plantation of non-polluted vegetables. It is shown that there is a cumulative trend of heavy metal contents in the soil with age after analysis of a correlation coefficient between heavy metal contents and age in Yongnian’s protected fields and excessive application of fertilizers or organic fertilizers, which is the main factor leading to an increase in heavy metal contents in the soil.

It is suggested that the amount of fertilizer should be properly reduced to prevent the soil’s environmental deterioration, the vegetable planting structure should be improved and the vegetables grown in areas with weaker accumulation of heavy metals should be cultivated.

This paper investigates the moderating role of sustainability committees in the relationship between environmental, social and governance (ESG) performance and environmental innovation within European nonfinancial firms.

The study analyzes data from 691 nonfinancial sector firms operating within EU states from 2013 to 2022. It employs regression analysis to examine the correlation between ESG performance and environmental innovation, considering the moderating effect of sustainability committees.

The research reveals a significant and positive correlation between ESG performance and environmental innovation. Moreover, it demonstrates that sustainability committees play a positive moderating role in this relationship, indicating their importance in fostering environmental innovation within organizations.

The study is limited to European nonfinancial companies, potentially limiting the generalizability of findings. Additionally, the research focuses on the moderating role of sustainability committees, leaving room for further exploration of other governance mechanisms.

The findings suggest that implementing an ESG performance framework and establishing dedicated sustainability oversight mechanisms, such as sustainability committees, can enhance environmental innovation within organizations. This insight is valuable for strategic decision-making aimed at advancing both sustainability and innovation agendas.

This study addresses a gap in the literature by exploring the moderating effect of sustainability committees on the link between ESG performance and environmental innovation from various theoretical viewpoints. It contributes to the understanding of mechanisms that enhance environmental innovation within companies and provides practical implications for corporate reporting accuracy and sustainability initiatives.

This paper aims to examine the unique Chinese context by analyzing the city labels (e.g. smart city and eco city) used by Chinese local governments at or above the provincial capital level to represent themselves (adopted city labels) and the developmental pathways they actually pursued (adopted developmental pathways).

The authors compared the city brand choices to those anticipated based on their geographic and economic contexts (predicted city labels and developmental pathways) as well as the directives outlined in national planning documents (imposed city labels and developmental pathways). The authors identified ten main categories of city labels used to designate themselves and establish the frequency of their use based on municipal plan documents, economic and geographic data and national plan documents and policy reports, respectively.

The authors discovered that both local economic development and geographic factors, as well as top-down administrative influences, significantly impact city branding strategies in the 38 Chinese cities studied. When these models fall short in predicting adopted city labels and pathways, it is often because cities favor a service-oriented reputation over a manufacturing-focused one, and they prefer diverse, multifaceted industrial images to uniform ones.

The originality and value of this paper lie in its contribution to the academic literature on city branding by developing a predictive model for brand development at the municipal level, with explicit attention to the national-local nexus. The paper’s approach differs from existing research in the first cluster of city branding by not addressing issues of stakeholder involvement or adoption and implementation processes. Additionally, the paper’s focus on the political power dynamics at the national level and urban governance details at the municipal level provides a unique perspective on the topic. Overall, this paper provides a valuable contribution to the field of city branding by expanding the understanding of brand development and its impact on the socioeconomic environment.

Focusing on the corporations in China and aiming to figure out the significant connection between organizational justice perception and job satisfaction from Chinese setting, this study aimed to examine the effects of organizational justice upon job satisfaction of the full-time and part-time employees in the state owned enterprise (SOEs) and primate Chinese companies.

The study adopted the questionnaire to investigate more than 300 employees, and the empirical data of this paper is based on statistical analysis, such as confirmatory factor analysis, correlational and regression analysis.

The paper arrives at the conclusion that in SOEs, the employees’ perception about procedural justice was higher than distributive justice. While in private enterprises, the procedural justice and interactive justice were tested to have similar coefficients. The relationship between organizational justice and job satisfaction differed between full-time employees and part-time employees.

This study opens a new window for understanding how organizational justice influences employees’ job satisfaction in Chinese context, taking a further step to explore the different impacts of organizational justice on job satisfaction among different types of employees.

This paper collected data from both SOE and private companies in China, increasing the external validity of the findings. Meanwhile, the authors observed consistent findings with the studies in Western Society, which increase the generalization of our findings as well. The findings highlight the value of integrating literatures on organizational justice and job satisfaction.

The purpose of this study is to investigate the determinants of job retention intention among healthcare workers (HCWs) in Canada during the COVID-19 pandemic.

Data are from a large nationally representative cross-sectional survey conducted by the Canadian National Statistics Agency. Ordered logistic regression is estimated to find an association between job retention and its main determinants as gleaned from the literature while controlling for a wide range of pertinent covariates. Odds and standardized odds are reported and discussed.

The results suggest that worsening working conditions, changes in health and well-being and lack of organizational support weaken intentions regarding job retention. Being employed rather than self-employed and working as a nurse also weakens job retention.

This is the first research on the determinants of intentions regarding job retention in Canada using nationally representative data. It allows us to test and confirm the results of previous studies on a large sample of Canadian HCWs. The paper also discusses the implications of the findings for health management and administration.

This paper aims to realize a fully distributed multi-UAV collision detection and avoidance based on deep reinforcement learning (DRL). To deal with the problem of low sample efficiency in DRL and speed up the training. To improve the applicability and reliability of the DRL-based approach in multi-UAV control problems.

In this paper, a fully distributed collision detection and avoidance approach for multi-UAV based on DRL is proposed. A method that integrates human experience into policy training via a human experience-based adviser is proposed. The authors propose a hybrid control method which combines the learning-based policy with traditional model-based control. Extensive experiments including simulations, real flights and comparative experiments are conducted to evaluate the performance of the approach.

A fully distributed multi-UAV collision detection and avoidance method based on DRL is realized. The reward curve shows that the training process when integrating human experience is significantly accelerated and the mean episode reward is higher than the pure DRL method. The experimental results show that the DRL method with human experience integration has a significant improvement than the pure DRL method for multi-UAV collision detection and avoidance. Moreover, the safer flight brought by the hybrid control method has also been validated.

The fully distributed architecture is suitable for large-scale unmanned aerial vehicle (UAV) swarms and real applications. The DRL method with human experience integration has significantly accelerated the training compared to the pure DRL method. The proposed hybrid control strategy makes up for the shortcomings of two-dimensional light detection and ranging and other puzzles in applications.

The purpose of this investigation is to identify, evaluate, integrate and summarize relevant and qualified papers through conducting a systematic literature review (SLR) on the application of recommender systems (RSs) to suggest a scholarly publication venue for researcher's paper.

To identify the relevant papers published up to August 11, 2018, an SLR study on four databases (Scopus, Web of Science, IEEE Xplore and ScienceDirect) was conducted. We pursued the guidelines presented by Kitchenham and Charters (2007) for performing SLRs in software engineering. The papers were analyzed based on data sources, RSs classes, techniques/methods/algorithms, datasets, evaluation methodologies and metrics, as well as future directions.

A total of 32 papers were identified. The most data sources exploited in these papers were textual (title/abstract/keywords) and co-authorship data. The RS classes in the selected papers were almost equally used. DBLP was the main dataset utilized. Cosine similarity, social network analysis (SNA) and term frequency–inverse document frequency (TF–IDF) algorithm were frequently used. In terms of evaluation methodologies, 24 papers applied only offline evaluations. Furthermore, precision, accuracy and recall metrics were the popular performance metrics. In the reviewed papers, “use more datasets” and “new algorithms” were frequently mentioned in the future work part as well as conclusions.

Given that a review study has not been conducted in this area, this paper can provide an insight into the current status in this area and may also contribute to future research in this field.

In the organizational technology acceptance (TA) decision-making process, stakeholders have many divergence opinions. Sometimes, an opposing stakeholder of a decision can stop the whole process of decision-making. In such a case, consensus may take a long time followed by a high risk. The purpose of this study is twofold. First, to find the best model with the least prediction error for the simulation of the consensus process in TA decisions. Second, to investigate the time required for the consensus process to yield the TA decision in different scenarios and to propose solutions to reduce the required time in a case study.

This study uses real-world data containing 1,186 actual observations. Stakeholders are decision-maker agents, and the observations are derived from survey data and used for simulation. Data were obtained from 126 experts in the Iranian rail freight industry. Opinion dynamics theory was used for agent-based simulation of stakeholders’ behavior. The agents interacted over time and their effects on other agents’ opinions were investigated.

The results illustrate an appropriate opinion changing model, a data-gathering method and a simulation scenario for TA consensus. The suitable model was selected after examining the advantages and disadvantages of and comparing the prediction results for different models with the real database of opinions. To reduce the consensus process time, the results suggest gathering the team members and networking with some leaders as advocators. A large number of advocators with high acceptability and continuous exchanging messages with other agents can improve the acceptance rate and have the most significant impact on other stakeholders’ opinions.

To the best of the authors’ knowledge, previous studies simulate individual TA processes. However, there is a difference between the individual TA and the organizational TA. The organizational TA requires the simultaneous decision-making of different stakeholders. In this research, the organizational TA was investigated.

In general, it is believed that firms belonging to the high technological intensity stratum have a more innovation capability. However, evidence has begun to appear in the literature demonstrating that firms in the low-tech stratum also have the innovation capability. This paper seeks to solve this dilemma. Through an analysis of industrial firms in an emerging country, this study aims to identify the existence of innovation capability in all strata of technological intensity.

The authors empirically assessed the impact of innovation capability on the performance of firms in all strata of technological intensity. The authors studied a sample of 910 firms from different industries and technology intensities operating in Peru, by applying a partial least squares structural equation model (PLS-SEM).

This study obtained three important findings. First, the authors show that innovation capability is present in all strata of technological intensity. Second, innovation capability differs according to the technological stratum. Third, firms in the lowest technological stratum can use more capabilities than those in the other strata.

This study pioneers the empirical analysis of innovation capability and technological intensity simultaneously to verify that innovation capability exists in the four strata of technological intensity.