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Keywords = employees’ generation

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18 pages, 473 KiB  
Article
Motivation, Urban Pressures, and the Limits of Satisfaction: Insights into Employee Retention in a Changing Workforce
by Rob Kim Marjerison, Jin Young Jun, Jong Min Kim and George Kuan
Systems 2025, 13(8), 661; https://doi.org/10.3390/systems13080661 - 5 Aug 2025
Abstract
This study aims to clarify how different types of motivation influence employee retention by identifying the distinct roles of intrinsic and extrinsic factors in shaping job satisfaction, particularly under varying levels of urban stress and generational identity. Drawing on Herzberg’s Two-Factor Theory and [...] Read more.
This study aims to clarify how different types of motivation influence employee retention by identifying the distinct roles of intrinsic and extrinsic factors in shaping job satisfaction, particularly under varying levels of urban stress and generational identity. Drawing on Herzberg’s Two-Factor Theory and Self-Determination Theory, we distinguish between intrinsic drivers (e.g., autonomy, achievement) and extrinsic hygiene factors (e.g., pay, stability). Using survey data from 356 Chinese employees and applying PLS-SEM with a moderated mediation design, we investigate how urbanization and Generation Z moderate these relationships. Results show that intrinsic motivation enhances satisfaction, especially in urban settings, while extrinsic factors negatively affect satisfaction when perceived as insufficient or unfair. Job satisfaction mediates the relationship between motivation and retention, although this effect is weaker among Generation Z employees. These findings refine motivational theories by demonstrating how environmental pressure and generational values jointly shape employee attitudes. The study contributes a context-sensitive framework for understanding retention by integrating individual motivation with macro-level moderators, offering practical implications for managing diverse and urbanizing labor markets. Full article
(This article belongs to the Section Systems Practice in Social Science)
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21 pages, 382 KiB  
Article
Food, Quality of Life and Mental Health: A Cross-Sectional Study with Federal Education Workers
by José Igor Ferreira Santos Jesus, Manuel Monfort-Pañego, Gabriel Victor Alves Santos, Yasmin Carla Monteiro, Suelen Marçal Nogueira, Priscilla Rayanne e Silva and Matias Noll
Nutrients 2025, 17(15), 2519; https://doi.org/10.3390/nu17152519 - 31 Jul 2025
Viewed by 287
Abstract
Background: The consumption of ultra-processed foods (UPFs) represents an important public health challenge, especially among education workers, whose intense routine can negatively impact eating habits. This study aimed to analyze the factors associated with the regular consumption of UPF among employees of [...] Read more.
Background: The consumption of ultra-processed foods (UPFs) represents an important public health challenge, especially among education workers, whose intense routine can negatively impact eating habits. This study aimed to analyze the factors associated with the regular consumption of UPF among employees of the Federal Network of Professional, Scientific and Technological Education (RFEPCT) in Brazil. Methods: This was a cross-sectional study, with a quantitative approach, carried out with 1563 education workers. Validated instruments on eating habits (PeNSE), mental health (DASS-21) and quality of life (WHOQOL-bref) were used. The regular consumption of UPF was defined as intake on ≥5 days in the last seven days. The association between the regular consumption of UPF and sociodemographic, occupational, behavioral, mental health and quality of life variables was assessed by Poisson regression with robust variance, generating adjusted prevalence ratios (PRadj) and respective 95% confidence intervals. Results: The regular consumption of UPF was associated mainly with female gender, a lower age group, Southeast and Midwest regions, dissatisfaction with sleep and the body, physical inactivity and poor sleep quality. In addition, the findings suggested a significant relationship between the worst stress scores and soft drinks (PRadj: 2.11; CI: 1.43–3.13), anxiety and soft drinks (PRadj: 1.83; CI: 1.24–2.70) and depression and industrialized/ultra-processed salty foods (PRadj: 2.43; CI: 1.82–3.26). The same was observed in the scores for the worst perception of quality of life, where there was a prevalence of up to 2.32 in the psychological domain and the consumption of industrialized/ultra-processed salty foods. Conclusions: The findings indicate that multiple interrelated factors—individual, psychosocial and occupational—are associated with the consumption of UPF among education workers. These results reinforce the importance of institutional policies that integrate actions to promote dietary health, mental health care and improved working conditions in the education sector. Full article
(This article belongs to the Section Nutrition and Public Health)
20 pages, 759 KiB  
Article
Evaluation of Leadership Styles in Multinational Corporations Using the Fuzzy TOPSIS Method
by Marija Runic Ristic, Tijana Savic Tot, Igor Ristic, Vilmos Tot, Tanja Radosevic and Dragan Marinkovic
Systems 2025, 13(8), 636; https://doi.org/10.3390/systems13080636 - 31 Jul 2025
Viewed by 267
Abstract
Due to globalization, companies are exposed to a culturally diversified workforce; therefore, great emphasis is placed on identifying the most effective leadership style that would be able to manage such a workforce. Although numerous studies have attempted to identify successful leadership styles in [...] Read more.
Due to globalization, companies are exposed to a culturally diversified workforce; therefore, great emphasis is placed on identifying the most effective leadership style that would be able to manage such a workforce. Although numerous studies have attempted to identify successful leadership styles in different cultural settings, none have focused on the perceptions of top managers who work in multinational corporations (MNCs) in culturally diversified surroundings. Thus, our research attempts to identify the most preferred leadership style and characteristics from the perspective of top managers in MNCs in the United Arab Emirates (UAE). The 13 leadership characteristics analyzed in this study were generated from the 21 characteristics found by Global Leadership and Organizational Behavior Effectiveness (GLOBE) research. The participants, top managers in MNCs, needed to evaluate leadership styles by considering leadership characteristics. To ensure the objectiveness of the study, we analyzed their answers by applying the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The results indicated that the most preferred leadership characteristics were visionary, inspirational, collaborative team-oriented, and performance-oriented. Moreover, the transformational leadership style emerged as the most preferred leadership style. The study’s findings show that top managers believe that employees in MNCs in the UAE seek a leader with a vision who will inspire, motivate, and help them fulfill their true potential. Full article
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29 pages, 697 KiB  
Article
Economic Performance of the Producers of Biomass for Energy Generation in the Context of National and European Policies—A Case Study of Poland
by Aneta Bełdycka-Bórawska, Rafał Wyszomierski, Piotr Bórawski and Paulina Trębska
Energies 2025, 18(15), 4042; https://doi.org/10.3390/en18154042 - 29 Jul 2025
Viewed by 351
Abstract
Solid biomass (agro-residue) is the most important source of renewable energy. The accelerating impacts of climate change and global population growth contribute to air pollution through the use of fossil fuels. These processes increase the demand for energy. The European Union has adopted [...] Read more.
Solid biomass (agro-residue) is the most important source of renewable energy. The accelerating impacts of climate change and global population growth contribute to air pollution through the use of fossil fuels. These processes increase the demand for energy. The European Union has adopted a climate action plan to address the above challenges. The main aim of this study was to assess the economic performance of the producers of biomass for energy generation in Poland. The detailed objectives were to determine land resources in the studied agricultural farms and to determine the value of fixed and current assets in the analyzed farms. We used questionnaires as the main method to collect data. Purposive sampling was used to choose the farms. We conducted various tests to analyze the revenues from biomass sales and their normality, such as the Dornik–Hansen test, the Shapiro–Wilk test, the Liliefors test, and the Jargue–Berra statistical test. Moreover, we conducted regression analysis to find factors that are the basis for the economic performance (incomes) of farms that sell biomass. Results: This study demonstrated that biomass sales had a minor impact on the performance of agricultural farms, but they enabled farmers to maintain their position on the market. The economic analysis was carried out on a representative group of Polish agricultural farms, taking into account fixed and current assets, land use, production structure, and employment. The findings indicate that a higher income from biomass sales was generally associated with better economic results per farm and per employee, although not always per hectare of land. This suggests that capital intensity and strategic resource management play a crucial role in the profitability of bioenergy-oriented agricultural production. Conclusions: We concluded that biomass sales had a negligible influence on farm income. But a small income from biomass sales could affect a farm’s economic viability. Full article
(This article belongs to the Section A4: Bio-Energy)
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14 pages, 375 KiB  
Article
Willingness to Become a Living Kidney Donor to a Stranger Among Polish Health Care Professionals Employed in a Dialysis Center: A National Cross-Sectional Study
by Paulina Kurleto, Irena Milaniak, Lucyna Tomaszek and Wioletta Mędrzycka-Dabrowska
J. Clin. Med. 2025, 14(15), 5282; https://doi.org/10.3390/jcm14155282 - 25 Jul 2025
Viewed by 343
Abstract
Background: Kidney transplantation from a living donor is considered the most beneficial form of treatment for end-stage renal failure, which, in addition to providing patients with better treatment results, significantly improves their quality of life. Understanding factors that influence the willingness to [...] Read more.
Background: Kidney transplantation from a living donor is considered the most beneficial form of treatment for end-stage renal failure, which, in addition to providing patients with better treatment results, significantly improves their quality of life. Understanding factors that influence the willingness to donate kidneys to strangers is critical in promoting and expanding the living donor pool. When considering the decision to become an altruistic kidney donor, individuals must evaluate multiple factors, including the identity of the recipient and their own perceived level of safety. This study aimed to assess the willingness of dialysis center employees to act as living kidney donors for a stranger. Methods: We conducted a cross-sectional study from February 2023 to June 2024 among dialysis specialists across Poland. The study involved 1093 people (doctors and nurses). The study used our survey questionnaire and standardized tools. Results: Nurses (vs. physicians) and those who advocated the regulation of unspecified living kidney donation in Poland, did not believe in the risk of organ trafficking, and would donate a kidney to a husband/wife or friend and accept kidney transplantation from a husband/wife were more likely to donate a kidney to a stranger. Furthermore, respondents who accepted a loved one’s decision to donate a kidney to a stranger were significantly more willing to donate a kidney to such a person themselves. Perceived self-efficacy was positively associated with the willingness to donate a kidney to a stranger. Conclusions: Less than half of healthcare professionals supported unspecific living organ donation in Poland, and nurses were more willing to donate than physicians. The factors supporting the decision generally included knowledge about organ donation and transplantation, a lack of fear of organ trafficking, and attitudes towards donation. Full article
(This article belongs to the Section Nephrology & Urology)
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22 pages, 1226 KiB  
Article
The Dark Side of Employee’s Leadership Potential: Its Impact on Leader Jealousy and Ostracism
by Zhen Yu, Feiwen Wang, Long Ye, Ganli Liao and Qichao Zhang
Behav. Sci. 2025, 15(8), 1001; https://doi.org/10.3390/bs15081001 - 23 Jul 2025
Viewed by 451
Abstract
In today’s rapidly evolving organizations, talent management plays a critical role in driving sustainable growth. Talents, particularly those exhibiting leadership potential, are often seen as essential assets for organizational development. However, the presence of high employee’s leadership potential can also generate adverse emotional [...] Read more.
In today’s rapidly evolving organizations, talent management plays a critical role in driving sustainable growth. Talents, particularly those exhibiting leadership potential, are often seen as essential assets for organizational development. However, the presence of high employee’s leadership potential can also generate adverse emotional reactions from leaders, potentially leading to behaviors such as leader jealousy and leader ostracism. This study investigates the dark side of employee’s leadership potential by examining the mechanisms through which employee’s leadership potential influences leader ostracism, with leader jealousy acting as a mediator. Drawing on social comparison theory, we propose a theoretical model that includes organizational competitive climate and leader’s core self-evaluation as moderating factors. Using a three-wave survey of 672 leaders in the Chinese construction industry, hierarchical regression analysis was employed to test the hypotheses. The results show that employee’s leadership potential significantly increases both leader jealousy and leader ostracism, with leader jealousy serving as a mediator. Moreover, a high organizational competitive climate strengthens the relationship between employee’s leadership potential and leader jealousy, thereby enhancing the entire mediated effect. In contrast, high leader core self-evaluation weakens the relationship between employee’s leadership potential and leader jealousy, reducing the likelihood of leader ostracism and attenuating the mediated effect. This study provides both theoretical contributions and practical insights for organizations seeking to manage high-leadership potential employees while minimizing the risk of negative leadership behaviors. Full article
(This article belongs to the Section Organizational Behaviors)
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19 pages, 1142 KiB  
Article
Matching Concepts of m-Polar Fuzzy Incidence Graphs
by Dilara Akter Mitu, Weihua Yang, Abid Ali, Tanmoy Mahapatra, Gohar Ali and Ioan-Lucian Popa
Symmetry 2025, 17(7), 1160; https://doi.org/10.3390/sym17071160 - 20 Jul 2025
Viewed by 211
Abstract
The m-Polar Fuzzy Incidence Graph (m-PFIG) is an extension of the m-Polar Fuzzy Graph (m-PFG), which provides information on how vertices affect edges. This study explores the concept of matching within both bipartite and general m-polar [...] Read more.
The m-Polar Fuzzy Incidence Graph (m-PFIG) is an extension of the m-Polar Fuzzy Graph (m-PFG), which provides information on how vertices affect edges. This study explores the concept of matching within both bipartite and general m-polar fuzzy incidence graphs (m-PFIGs). It extends various results and theorems from fuzzy graph theory to the framework of m-PFIGs. This research investigates various operations within m-PFIGs, including augmenting paths, matching principal numbers, and the relationships among them. It focuses on identifying the most suitable employees for specific roles and achieving optimal outcomes, particularly in situations involving internal conflicts within an organization. To address fuzzy maximization problems involving vertex–incidence pairs, this study outlines key properties of maximum matching principal numbers in m-PFIGs. Ultimately, the matching concept is applied to attain these maximum principal values, demonstrating its effectiveness, particularly in bipartite m-PFIG scenarios. Full article
(This article belongs to the Special Issue Symmetry and Graph Theory, 2nd Edition)
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24 pages, 4383 KiB  
Article
Predicting Employee Attrition: XAI-Powered Models for Managerial Decision-Making
by İrem Tanyıldızı Baydili and Burak Tasci
Systems 2025, 13(7), 583; https://doi.org/10.3390/systems13070583 - 15 Jul 2025
Viewed by 599
Abstract
Background: Employee turnover poses a multi-faceted challenge to organizations by undermining productivity, morale, and financial stability while rendering recruitment, onboarding, and training investments wasteful. Traditional machine learning approaches often struggle with class imbalance and lack transparency, limiting actionable insights. This study introduces an [...] Read more.
Background: Employee turnover poses a multi-faceted challenge to organizations by undermining productivity, morale, and financial stability while rendering recruitment, onboarding, and training investments wasteful. Traditional machine learning approaches often struggle with class imbalance and lack transparency, limiting actionable insights. This study introduces an Explainable AI (XAI) framework to achieve both high predictive accuracy and interpretability in turnover forecasting. Methods: Two publicly available HR datasets (IBM HR Analytics, Kaggle HR Analytics) were preprocessed with label encoding and MinMax scaling. Class imbalance was addressed via GAN-based synthetic data generation. A three-layer Transformer encoder performed binary classification, and SHapley Additive exPlanations (SHAP) analysis provided both global and local feature attributions. Model performance was evaluated using accuracy, precision, recall, F1 score, and ROC AUC metrics. Results: On the IBM dataset, the Generative Adversarial Network (GAN) Transformer model achieved 92.00% accuracy, 96.67% precision, 87.00% recall, 91.58% F1, and 96.32% ROC AUC. On the Kaggle dataset, it reached 96.95% accuracy, 97.28% precision, 96.60% recall, 96.94% F1, and 99.15% ROC AUC, substantially outperforming classical resampling methods (ROS, SMOTE, ADASYN) and recent literature benchmarks. SHAP explanations highlighted JobSatisfaction, Age, and YearsWithCurrManager as top predictors in IBM and number project, satisfaction level, and time spend company in Kaggle. Conclusion: The proposed GAN Transformer SHAP pipeline delivers state-of-the-art turnover prediction while furnishing transparent, actionable insights for HR decision-makers. Future work should validate generalizability across diverse industries and develop lightweight, real-time implementations. Full article
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21 pages, 1136 KiB  
Article
Leveraging Public–Private Partnerships for a Circular Industry Economy: Advancing Economic Sustainability in Industrial Waste Management in the Emirate of Ajman, UAE
by Khaled Alhosani
Challenges 2025, 16(3), 31; https://doi.org/10.3390/challe16030031 - 6 Jul 2025
Viewed by 393
Abstract
This study investigates the empowering role of public–private partnerships (PPPs) in the economic sustainability of waste management (ESW) and the circular industry economy (CIE), specifically in the small, rapidly industrialising Emirate of Ajman, UAE. Embracing a circular economy is vital for the sustainability [...] Read more.
This study investigates the empowering role of public–private partnerships (PPPs) in the economic sustainability of waste management (ESW) and the circular industry economy (CIE), specifically in the small, rapidly industrialising Emirate of Ajman, UAE. Embracing a circular economy is vital for the sustainability agenda while forging a transformative commitment to planetary health (PH) in a manner that is especially crucial for small states with limited carrying capabilities. A quantitative methodological orientation is employed in a survey-based research design, followed by the Partial Least Squares Structural Equation Modelling statistical technique to test the hypothesised relationships. Sampling involved the three sub-populations of government employees (n = 123), managers/employees of private waste collection businesses (n = 106), and employees of private industrial waste generation industries (n = 276). Findings indicate that PPP empowerment positively impacts ESW and contributes to the creation of CIE. Moreover, ESW fosters the growth of CIE in Ajman. Notably, the perspectives of government stakeholders differ from those of non-government actors. This research underscores the significance of PPP empowerment in the development of CIE towards SDGs 11, 12, and 17, emphasising the mediating role of ESW between PPPs and CIE in small, rapidly industrialising states. The study recommends that the Ajman government implement training and social initiatives aimed at aligning the sustainability perspectives of all stakeholders involved in waste management to promote the mutual benefits of “people, places, and planet”. Full article
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27 pages, 318 KiB  
Article
Corporate Social Responsibility and Firm Financial Performance: Evidence from America’s Best Corporate Citizens
by Kelly Huang, Yanglin Li, Kabir Oyewale and Emily Tworoger
Int. J. Financial Stud. 2025, 13(3), 119; https://doi.org/10.3390/ijfs13030119 - 1 Jul 2025
Viewed by 850
Abstract
This paper examines the relation between corporate social responsibility (CSR) and firm financial performance—a topic that continues to generate debate among academics and practitioners. We focus on firms included in the 100 Best Corporate Citizens (BCC) rankings from 2009 to 2022, a list [...] Read more.
This paper examines the relation between corporate social responsibility (CSR) and firm financial performance—a topic that continues to generate debate among academics and practitioners. We focus on firms included in the 100 Best Corporate Citizens (BCC) rankings from 2009 to 2022, a list that highlights companies recognized for CSR transparency and performance. Using panel data regression analyses and matched sample comparison, we examine whether BCC firms outperform their peers. Our findings show that, relative to matched firms not included in the rankings, BCC firms demonstrate significantly stronger future operating performance. Among BCC firms, CSR rankings are positively associated with future operating performance, although this positive relation has diminished in more recent years. Furthermore, we find no significant association between operating performance and most individual CSR component rankings except for employee relations. Finally, our evidence indicates that more socially responsible firms engage in less tax avoidance and pay higher audit fees, suggesting that CSR-oriented firms exhibit stronger ethical considerations across a broad range of corporate activities. This study contributes to the CSR literature by providing updated empirical evidence and practical insights for stakeholders evaluating corporate behavior and outcomes through the BCC rankings. Full article
(This article belongs to the Special Issue Sustainable Corporate Governance and Financial Performance)
28 pages, 631 KiB  
Article
A Predictive Framework for Sustainable Human Resource Management Using tNPS-Driven Machine Learning Models
by R Kanesaraj Ramasamy, Mohana Muniandy and Parameswaran Subramanian
Sustainability 2025, 17(13), 5882; https://doi.org/10.3390/su17135882 - 26 Jun 2025
Viewed by 447
Abstract
This study proposes a predictive framework that integrates machine learning techniques with Transactional Net Promoter Score (tNPS) data to enhance sustainable Human Resource management. A synthetically generated dataset, simulating real-world employee feedback across divisions and departments, was used to classify employee performance and [...] Read more.
This study proposes a predictive framework that integrates machine learning techniques with Transactional Net Promoter Score (tNPS) data to enhance sustainable Human Resource management. A synthetically generated dataset, simulating real-world employee feedback across divisions and departments, was used to classify employee performance and engagement levels. Six machine learning models such as XGBoost, TabNet, Random Forest, Support Vector Machines, K-Nearest Neighbors, and Neural Architecture Search were applied to predict high-performing and at-risk employees. XGBoost achieved the highest accuracy and robustness across key performance metrics, including precision, recall, and F1-score. The findings demonstrate the potential of combining real-time sentiment data with predictive analytics to support proactive HR strategies. By enabling early intervention, data-driven workforce planning, and continuous performance monitoring, the proposed framework contributes to long-term employee satisfaction, talent retention, and organizational resilience, aligning with sustainable development goals in human capital management. Full article
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25 pages, 1008 KiB  
Article
Understand the Changes in Motivation at Work: Empirical Studies Using Self-Determination Theory-Based Interventions
by Zheni Wang and Melanie Briand
Behav. Sci. 2025, 15(7), 864; https://doi.org/10.3390/bs15070864 - 25 Jun 2025
Viewed by 520
Abstract
Managers often need to stay motivated and effectively motivate others. Therefore, they should rely on evidence-based interventions to effectively motivate and self-motivate. This research investigated how self-determination theory-based interventions affect employees’ motivation dynamics and motivational consequences within short time frames (i.e., within an [...] Read more.
Managers often need to stay motivated and effectively motivate others. Therefore, they should rely on evidence-based interventions to effectively motivate and self-motivate. This research investigated how self-determination theory-based interventions affect employees’ motivation dynamics and motivational consequences within short time frames (i.e., within an hour, within a few weeks or months) in two empirical studies. Study one focused on assessing the effectiveness of a one-day training workshop in helping to improve managers’ work motivation, basic psychological needs satisfaction/frustration, subordinates’ motivation, and perceptions of managers’ needs-supportive/thwarting behaviors within a few weeks. Results support the effectiveness of the training, as managers were rated by their direct subordinates as having fewer needs-thwarting behaviors and reported self-improvement in needs satisfaction and frustration six weeks after completing the training program. Study two used the mean and covariance structure analysis and tested the impact of three types of basic psychological needs-supportive/thwarting and control conditions (3 × 2 × 1 factorial design) on participants’ situational motivation, vitality, and general self-efficacy for playing online word games within 30 min. Multi-group confirmatory factor analysis (CFA) confirmed the scalar measurement invariance, then latent group mean comparison results show consistently lower controlled motivation across the experimental conditions. During a quick online working scenario, the theory-based momentary intervention effectively changed situational extrinsic self-regulation in participants. Supplementary structural equation modeling (SEM; cross-sectional) analyses using experience samples supported the indirect dual-path model from basic needs satisfaction to vitality and general efficacy via situational motivation. We discussed the theoretical implications of the temporal properties of work motivation, the practical implications for employee training, and the limitations. Full article
(This article belongs to the Special Issue Work Motivation, Engagement, and Psychological Health)
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25 pages, 2093 KiB  
Article
Strategic Web-Based Data Dashboards as Monitoring Tools for Promoting Organizational Innovation
by Siddharth Banerjee, Clare E. Fullerton, Sankalp S. Gaharwar and Edward J. Jaselskis
Buildings 2025, 15(13), 2204; https://doi.org/10.3390/buildings15132204 - 24 Jun 2025
Viewed by 704
Abstract
Knowledge extraction and sharing is one of the biggest challenges organizations face to ensure successful and long-lasting knowledge repositories. The North Carolina Department of Transportation (NCDOT) commissioned a web-based knowledge management program called Communicate Lessons, Exchange Advice, Record (CLEAR) for end-users to promote [...] Read more.
Knowledge extraction and sharing is one of the biggest challenges organizations face to ensure successful and long-lasting knowledge repositories. The North Carolina Department of Transportation (NCDOT) commissioned a web-based knowledge management program called Communicate Lessons, Exchange Advice, Record (CLEAR) for end-users to promote employee-generated innovation and to institutionalize organizational knowledge. Reusing knowledge from an improperly managed database is problematic and potentially causes substantial financial loss and reduced productivity for an organization. Poorly managed databases can hinder effective knowledge dissemination across the organization. Data-driven dashboards offer a promising solution by facilitating evidence-driven decision-making through increased information access to disseminate, understand and interpret datasets. This paper describes an effort to create data visualizations in Tableau for CLEAR’s gatekeeper to monitor content within the knowledge repository. Through the three web-based strategic dashboards relating to lessons learned and best practices, innovation culture index, and website analytics, the information displays will aid in disseminating useful information to facilitate decision-making and execute appropriate time-critical interventions. Particular emphasis is placed on utility-related issues, as data from the NCDOT indicate that approximately 90% of projects involving utility claims experienced one or two such incidents. These claims contributed to an average increase in project costs of approximately 2.4% and schedule delays averaging 70 days. The data dashboards provide key insights into all 14 NCDOT divisions, supporting the gatekeeper in effectively managing the CLEAR program, especially relating to project performance, cost savings, and schedule improvements. The chronological analysis of the CLEAR program trends demonstrates sustained progress, validating the effectiveness of the dashboard framework. Ultimately, these data dashboards will promote organizational innovation in the long run by encouraging end-user participation in the CLEAR program. Full article
(This article belongs to the Special Issue The Power of Knowledge in Enhancing Construction Project Delivery)
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22 pages, 521 KiB  
Article
Synergistic Rewards for Proactive Behaviors: A Study on the Differentiated Incentive Mechanism for a New Generation of Knowledge Employees Using Mixed fsQCA and NCA Analysis
by Jie Zhou, Junqing Yang and Bonoua Faye
Systems 2025, 13(7), 500; https://doi.org/10.3390/systems13070500 - 23 Jun 2025
Viewed by 392
Abstract
In practice, the new generation of knowledge-based employees often exhibits a “lying flat” attitude. This reflects the failure of organizational incentive mechanisms. In order to improve the incentive system and encourage employees to be proactive, the study explores and compares the synergistic effects [...] Read more.
In practice, the new generation of knowledge-based employees often exhibits a “lying flat” attitude. This reflects the failure of organizational incentive mechanisms. In order to improve the incentive system and encourage employees to be proactive, the study explores and compares the synergistic effects of different rewards tools on various forms of proactive behavior in the new generation of knowledge employees. After conducting fsQCA and NCA analyses on paired data from 93 leaders and 210 employees based on the ERG theory, the findings indicate that no single reward tool is a necessary condition for triggering high proactive behavior. Instead, different reward tools need to work in synergy to produce effective motivation. Three patterns drive employees to exhibit high individual task proactivity. They are the “Dual-Drive Salary Security and Moderate Labor Dominant” pattern, the “Moderate Labor Dominant” pattern, and the “Salary Security Dominant” pattern. Two patterns drive employees to demonstrate high team member proactivity, namely the “Employee Care Dominant High-Investment” pattern and the “Pay Fairness Dominant High-Investment” pattern. Additionally, good work experience (i.e., colleague relationships) in the workplace has a significant impact on both types of proactive behavior. The research conclusions will provide insights and references for enterprise managers to design more targeted compensation incentive policies and unleash the vitality of the new generation of knowledgeable employees. Full article
(This article belongs to the Special Issue Strategic Management Towards Organisational Resilience)
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18 pages, 561 KiB  
Article
Eco-Efficiency in the Agricultural Sector: A Cross-Country Comparison Between the European Union and Türkiye
by Derya İlkay Yılmaz
Sustainability 2025, 17(13), 5713; https://doi.org/10.3390/su17135713 - 21 Jun 2025
Viewed by 456
Abstract
This study conducts a macro-level comparative analysis of the eco-efficiency in the agricultural sectors of the European Union (EU) member states and Türkiye from 2003 to 2022. By treating countries as decision-making units, this research offers a holistic overview of how national-level inputs [...] Read more.
This study conducts a macro-level comparative analysis of the eco-efficiency in the agricultural sectors of the European Union (EU) member states and Türkiye from 2003 to 2022. By treating countries as decision-making units, this research offers a holistic overview of how national-level inputs and outputs shape the aggregate performance, focusing on the trade-offs between economic value generation and environmental pressures. An input-oriented Data Envelopment Analysis (DEA) model, based on Variable Returns to Scale (VRS), was employed. The model employs three inputs—compensation of employees (COE), energy consumption (EC), and gross fixed capital formation (GFC)—and two outputs—agricultural gross domestic product (GDP) and GHG emissions (GGEs). All variables were normalized by agricultural land area per country to account for scale differences. The findings reveal significant disparities in the eco-efficiency across countries and over time. Notably, Türkiye consistently demonstrated a high performance, frequently serving as a benchmark. In contrast, several Eastern European countries exhibited lower scores, suggesting significant room for structural improvement at the national level. The results point to the considerable potential for reducing energy and labor inputs in many countries. Instead of offering specific policy prescriptions, this study provides a diagnostic tool that identifies national-level performance gaps, informs policy discussions on resource allocation, and highlights priority areas for more detailed investigation. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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