Field Of Management Research Articles

Optimum management strategy for improving maize water productivity and partial factor productivity for nitrogen in China: A meta-analysis

China’s agricultural production suffers significant constraints due to low water productivity (WP) and partial factor productivity for nitrogen (PFPN). The pivotal solution to enhance maize yield, WP, and PFPN is through optimizing field management practices. However, previous studies primarily focused on the effects of individual or coupled field management practices on maize yield, WP, or PFPN in an area or land mass, so it is necessary to conduct a comprehensive quantitative analysis of various field management practices on maize yield, WP, and PFPN at the national scale. In this study, we compiled 286 studies encompassing 6959 pairs of experimental data spanning from 1990 to 2023. Meta-analysis was conducted to observe the variations in maize yield, WP, and PFPN across diverse field management practices (straw returning, nitrogen fertilizer application, irrigation practice, and tillage practice) on a national scale. The results showed that nitrogen fertilizer application (215 kg N ha−1) was the most effective in enhancing maize yield and WP by 68.1 % and 54.8 %, respectively. Additionally, irrigation had the most substantial impact on PFPN, enhancing 16.8 %. Straw mulching, application of slow and controlled release fertilizers, drip irrigation, and subsoiling were identified as the most effective practices in increasing maize yield, WP, and PFPN by Random forest model. Maize straw returning could reduce nitrogen fertilizer application by 20 kg ha−1, while increasing WP and PFPN by 4.2 % and 11.6 %, respectively. Moreover, straw returning could reduce water consumption by 23–60 mm, while increasing WP and PFPN by 2.9 % and 6.8 %, respectively. These findings can provide a reference for the formulation of comprehensive management strategies for sustainable maize production in China and globally.

Central Asian and Northern Cyprus Water Desalination Experience

Water supply in Famagusta, Northern Cyprus, presents a significant challenge, warranting detailed examination of the region's water management practices. Drawing parallels with the desalination experiences in Central Asia and Northern Cyprus, this manuscript explores the intricate relationship between water infrastructure and the multifaceted challenges faced during young researchers experience exchange internship between Kazakhstan and Northern Cyprus. Through a comprehensive analysis of water desalination experiences and the evolution of water supply facilities in both regions, this study provides insights into effective water usage. Central Asia and Northern Cyprus share similar climate conditions and challenges in water management, thus serving as valuable case studies for understanding optimal water resource utilization. This paper emphasizes the significance of adopting a comprehensive approach to address the complexities of water supply. Current research underscores the importance of sustainable practices and innovative solutions in ensuring water security, particularly in the face of climate change. Sharing knowledge and experiences is crucial for addressing the challenges posed by climate change and ensuring the resilience of water management systems. Key terms such as water desalination, water management in Cyprus, and water issues in Central Asia are meticulously explored, offering valuable insights for policymakers, researchers, and practitioners in the field of water resource management.

Fine classification of rice fields in high-resolution remote sensing images

Fine-grained management of rice fields can enhance the yield and quality of rice crops. Challenges in achieving fine classification include interference from similar vegetation, the irregularity of natural field shapes, and complex scale variations. This paper introduces Rice Attention Cascade Network (RACNet), for the fine classification of rice fields in high-resolution satellite remote sensing imagery. The network employs the Hybrid Task Cascade network as the base framework and uses spectral and indices mixed multimodal data as input to reinforce the feature differentiation of similar vegetation. Initially, a Channel Attention Deformable-ResNet (CAD-ResNet) was designed to enhance the feature representation of rice on different channels. Deformable convolution improves the ability of CAD-ResNet to capture irregular field shapes. Then, to address the issue of complex scale changes, the multi-scale features extracted by the CAD-ResNet are progressively fused using an Asymptotic Feature Pyramid, reducing the loss of scale information between non-adjacent layers. Experiments on the Meishan rice dataset show that the proposed method is capable of accurate instance segmentation for fragmented or irregularly shaped rice fields. The evaluation metric AP50 of RACNet reaches 50.8%.

Prediction of oil production based on multivariate analysis and self-attention mechanism integrated with long short-term memory

The accurate oil prediction of wells is essential for making informed decisions regarding the extension of the well lifespan and the enhancement of oil recovery rates. However, the prediction of oil well production is highly challenging due to the complex, nonlinear, and non-stationary data influenced by reservoir geological characteristics and operational adjustments. To address this, a novel prediction method for oil well production is proposed in this study. Firstly, the data-cleaning approach designed in this study is utilized to eliminate outliers from the raw dataset and impute missing values. Subsequently, relevant features are identified through analysis to form a usable dataset. The proposed deep learning neural network, namely the self-attention mechanism integrated with long short-term memory, is trained and learned on this dataset. Finally, the predictive performance of the model is validated using a set of actual oil production data. Through data experiments, the proposed model effectively predicts oil well production with superior accuracy compared to baseline models, achieving an R-squared of 0.872. This method provides reliable decision support for optimizing oil field development and management.

Governance and Territorial Cohesion Through Policies and Good Practices: A Focus on Local Development

The concept of governance initially emerged in the field of economics and business management with the objective of achieving greater efficiency. It was subsequently extended to the field of government management. In many countries, governance has become a topic of great importance as a result of the implementation of decentralization policies and the extension of popular participation in land use plans in the search for sustainable development. The study, developed in the Decentralized Autonomous Government of Portoviejo canton in the province of Manabí, had as its primary objective the verification of the knowledge of governance among decision-makers and other socially involved actors in the canton's land use plan in the search for sustainable local development. This was achieved through an analysis of the Plan, conceived and applied with the intention of fostering cohesion among the policies implemented. The study employed a combination of theoretical and empirical methods. The theoretical approach involved a review and analysis of the literature on the subject, while the empirical approach involved data collection through questionnaires administered to socially involved actors. This approach enabled the researchers to gain insights into the perceptions and experiences of these actors, and to assess the effectiveness of various governance practices.

Exploring the relationships between digital transformation, organizational slack and business performance: a configurational approach

PurposeThe survival of companies today hinges on their adaptability and flexibility, with digital transformation (DT) and organizational slack (OS) playing crucial roles. Despite their recognized importance, these factors are often studied separately. This study aims to explore how OS facilitates DT and evaluate their synergies and trade-offs to improve performance.Design/methodology/approachUsing data from the European Manufacturing Survey, structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA), we investigate causal relationships and possible combinations between different dimensions of OS and DT that contribute to business performance.FindingsWe confirmed the positive effect of OS and DT on business performance, highlighting the importance of organizational over technological factors. While not definitively establishing OS as a precursor to DT, our findings underscore the need for human and operational slack to improve performance, especially in less technology-intensive contexts.Research limitations/implicationsOur findings evidence that decision-makers should integrate OS with DT initiatives to improve the firm’s competitiveness. However, it is worth noting that while OS seems essential in low-tech shopfloors, its importance is lower in high-tech environments. Furthermore, within the possible combinations, managers should promote operational slack and digitalization, as it seems fundamental to improve business performance.Originality/valueThis article contributes to the management field in three ways. First, it clarifies controversies by providing evidence of the positive roles of DT and OS as drivers of competitiveness for manufacturing firms. Second, we verify that OS is not directly linked to DT, challenging existing assumptions. Third, it investigates the combinations of OS and DT that drive business performance improvement, emphasizing their synergies and trade-offs.

Sustainable resource management and community corporate social performance: strategic implications of corruption control in MNEs

PurposeThe consequences of corporate corruption control (CCC) have either been investigated outside the firm (e.g. foreign direct investment inflows) or inside the firm (e.g. profitability). Yet prior research addresses these implications separately, treating them as distinct phenomena, ignoring questions at their intersection. However, corruption control can be leveraged to benefit both organizations (internally) and environments (externally). In line with open systems theory, this study aims to explore a ripple effect of corruption control not only inside organizations (efficiency through adoption of sustainable resource management practices) but also outside [community-centered corporate social performance (CSP)].Design/methodology/approachUsing a longitudinal sample of multinational enterprises from Forbes list of “The World’s Largest Public Companies,” the authors use a cross-lagged panel design to provide clarity regarding causal effects.FindingsResults confirm causal directionality and support the positive effect of corruption control on resource management and community CSP, contributing toward understanding implications at the organization–environment interface.Originality/valueThe authors examine both internal and external implications of CCC. The use of a cross-lagged design that is relatively novel to the management field allows to check for casual effects between CSP elements that were previously assumed to have reciprocal casual effects.

Визуальная интерпретация парадигмы управления организационной системой c разнородными производственными ресурсами

The object of the study is developing a formalized mechanism for managing an organizational system that implements complex production activities, including different types of industrial production, and applies the corresponding heterogeneous resources. The subject of the article is an important intermediate stage of this development, which is an abstract interpretation of the optimal management paradigm of limited resources of such an organizational system, proposed earlier by the authors. The interpretation will allow reasonably forming a strict mathematical model of objects and control processes. The management mechanism in any subject area, providing for adopting management decisions by people authorized to do so, must have an ergonomic development and appropriate information support for these decisions. The so-called result information plays the role of such support, that is the information on the characteristics of the current and planned states of the management object in the problem being solved which is the productivity of the organizational system resources. It seems advisable to carry out such ergonomic and information development of the designed problem-oriented management mechanism in the form of a visual interpretation of its substantive concept. The prototype of such interpretation tools is graphic images used in modelling and designing technical systems, developed in this work in the field of management in organizational systems with heterogeneous resources. The article provides examples of their application, demonstrating the possibility of visual representation of the current state of the organizational system and the set of its possible controlled states.

Various Approaches used by Researchers in the Fields of Business, Management, and Accounting in Treating Intellectual Capital

This research aims to discuss how intellectual capital issues are treated in accounting research. This study answered research questions through a Systematic Literature Review (SLR) of 367 peer-reviewed articles in Business Management and Accounting (BMA). A detailed search was done using the publish or perish version 8 search engine. It selected the Scopus database through the “intellectual capital” keyword. The database was filtered to articles published from 2017–2021. This study selected samples using several criteria. First, the article titles should be related to intellectual capital. After that, the article is published in a peer-reviewed journal that is not discontinued. Finally, the subject matter is BMA. Most research on intellectual capital placed this topic as an independent variable at 44.14% of the total articles. Some others used it as a systematic review (21.25%), a dependent variable (13.08%), an intervening/mediating variable (7.08%), and a moderating variable (0.27%). Meanwhile, the rest employed intellectual capital as descriptive research without conducting any testing. This research is the first to map how intellectual capital is treated in accounting research.

Farm-Level Risk Factors for Lameness in 659 German Dairy Herds Kept in Loose Housing Systems.

Six hundred fifty-nine farms in three regions of Germany (North: n = 240, East: n = 247, and South: n = 172) were included in the study, which aims at determining the association of management-related risk factors with farm-level lameness in German dairy herds. For each risk factor, a generalised linear regression model with negative binomial distribution and logit link was built. Results showed that cows housed in deep-bedded cubicles had a lower risk of being lame than cows housed in other cubicle types. A larger cubicle width was associated with a lower risk of being lame. Feeding a total mixed ration was associated with lower lameness prevalence (compared to feeding a partial mixed ration or single components). For first lactation cows, lameness assessment performed daily (compared to less than daily) and during other work tasks (compared to lameness assessment as a separate work task) were associated with lower risk for lameness. Finally, the present study provided evidence for crucial associations of management-related risk factors with lameness in German dairy cows, especially in the fields of cubicle design, feeding management, and lameness assessment.

Society 5.0: A Bibliometric Analysis from Management Approach

The Goals of Society 5.0 provided an innovative viewpoint on the function and significance of technological advancement in resolving contemporary social issues in contemporary society, In light of this, the researcher attempted to determine the current publication status of Society 5.0 within the field of management. The researcher applied bibliometric analysis to examine a total of 125 documents that were published within a span of five years. The findings revealed four distinct clusters that base on the themes of framework, understanding society 5.0, utilization of society 5.0, and challenges. The co-authorship network among Russia, Italy, and the United States is mostly impressive. Future studies should incorporate edited books, chapters, and monographs to boost Society 5.0's bibliometric analysis. Include all Society 5.0-related fields.

Smart energy management for hybrid electric bus via improved soft actor-critic algorithm in a heuristic learning framework

Deep reinforcement learning (DRL) is currently the cutting-edge artificial intelligence approach in the field of energy management for hybrid electric vehicles. However, inefficient offline training limits the energy-saving efficacy of DRL-based energy management strategies (EMSs). Motivated by this, this article proposes a smart DRL-based EMS in a heuristic learning framework for an urban hybrid electric bus. In order to enhance the sampling efficiency, the prioritized experience replay technique is introduced into soft actor-critic (SAC) for the innovative formulation of an improved SAC algorithm. Additionally, to strengthen the generalizability of the improved SAC agent to real driving scenarios, a stochastic training environment is constructed. Afterward, curriculum learning is employed to develop a heuristic learning framework that expedites convergence. Experimental simulations reveal that the designed EMS expedites convergence by 85.58 % and saves fuel by 6.43 % compared with the cutting-edge baseline EMS. Moreover, the computation complexity test demonstrates that the designed EMS holds significant promise for real-time implementation. These findings highlight the contribution of this article in facilitating fuel conservation for urban hybrid electric buses through the application of emerging artificial intelligence technologies.

Exploring the Impact of Transformational Leadership on Employee Motivation and Organizational Performance: A Human Resource Management Perspective

This study explores the impact of transformational leadership on employee motivation and organizational performance from a human resource management perspective. Utilizing a qualitative literature review methodology, the research synthesizes existing studies to provide a comprehensive understanding of how transformational leadership practices influence employee motivation, engagement, and overall organizational effectiveness. Transformational leadership, characterized by its focus on inspiring and motivating employees through vision, support, and empowerment, has been widely recognized for its positive effects on employee attitudes and behaviors. The literature review reveals that transformational leaders enhance employee motivation by fostering a supportive work environment, encouraging innovation, and promoting professional development. Additionally, the review highlights that organizations led by transformational leaders often experience improved performance outcomes, including higher productivity, increased job satisfaction, and reduced turnover rates. However, the findings also indicate that the effectiveness of transformational leadership may vary depending on contextual factors such as organizational culture, industry, and employee demographics. This study contributes to the field of human resource management by offering practical insights into the benefits and challenges of implementing transformational leadership in diverse organizational settings. The implications of these findings suggest that HR professionals should consider adopting transformational leadership development programs to enhance employee motivation and drive organizational success.

Intrinsically Flexible Phase Change Fibers for Intelligent Thermal Regulation

AbstractOwing to the significant latent heat generated at constant temperatures, phase change fibers (PCFs) have recently received much attention in the field of wearable thermal management. However, the phase change materials involved in the existing PCFs still experience a solid–liquid transition process, severely restricting their practicality as wearable thermal management materials. Herein, we, for the first time, developed intrinsically flexible PCFs (polyethylene glycol/4,4′‐methylenebis(cyclohexyl isocyanate) fibers, PMFs) through polycondensation and wet‐spinning process, exhibiting an inherent solid‐solid phase transition property, adjustable phase transition behaviors, and outstanding knittability. The PMFs also present superior mechanical strength (28 MPa), washability (>100 cycles), thermal cycling stability (>2000 cycles), facile dyeability, and heat‐induced recoverability, all of which are highly significant for practical wearable applications. Additionally, the PMFs can be easily recycled by directly dissolving them in solvents for reprocessing, revealing promising applications as sustainable materials for thermal management. Most importantly, the applicability of the PMFs was demonstrated by knitting them into permeable fabrics, which exhibit considerably improved thermal management performance compared with the cotton fabric. The PMFs offer great potential for intelligent thermal regulation in smart textiles and wearable electronics.

Intrinsically Flexible Phase Change Fibers for Intelligent Thermal Regulation.

Owing to the significant latent heat generated at constant temperatures, phase change fibers (PCFs) have recently received much attention in the field of wearable thermal management. However, the phase change materials involved in the existing PCFs still experience a solid-liquid transition process, severely restricting their practicality as wearable thermal management materials. Herein, we, for the first time, developed intrinsically flexible PCFs (polyethylene glycol/4,4'-methylenebis(cyclohexyl isocyanate) fibers, PMFs) through polycondensation and wet-spinning process, exhibiting an inherent solid-solid phase transition property, adjustable phase transition behaviors, and outstanding knittability. The PMFs also present superior mechanical strength (28 MPa), washability (>100 cycles), thermal cycling stability (>2000 cycles), facile dyeability, and heat-induced recoverability, all of which are highly significant for practical wearable applications. Additionally, the PMFs can be easily recycled by directly dissolving them in solvents for reprocessing, revealing promising applications as sustainable materials for thermal management. Most importantly, the applicability of the PMFs was demonstrated by knitting them into permeable fabrics, which exhibit considerably improved thermal management performance compared with the cotton fabric. The PMFs offer great potential for intelligent thermal regulation in smart textiles and wearable electronics.

Evaluation of psychometric characteristics of employee motivation in the workplace

Researchers constantly look for the ideal motivating factors in various countries, industries, and sectors, due to its multilateral dimension, which includes employees, managers, organizational policies and practices, and the way that the very dynamic external environmental factors influence them. Self-Determination Theory of motivation proposed by Edward Deci and Richard Ryan, embraces a holistic approach to human motivation which started by identifying several motivational styles and has been implemented in different fields of workplace motivation and management This paper aims to emphasize the importance of examining the psychometric characteristics of the employee motivation scale in the workplace, relying on some bifactor model ancillary indices. The degree of motivation was measured through the Multidimensional Work Motivation Scale (MWMS), based on Self-Determination Theory (SDT). The data were collected from a self-report questionnaire addressed to 658 employees from various businesses and institutions in the Korça region, in Albania. The ancillary indices, derived from the standardized loadings of a confirmatory bifactor model, provide a more comprehensive overview of the psychometric characteristics of the measurement instrument. The study showed that treating the MWMS as unidimensional within a multidimensional construct may cause only a small bias. However, its interpretation seems questionable. On the other hand, the added value of some subscale scores should be considered and can be statistically appropriate for interpretation, helping applied researchers. This study contributes to the field by highlighting the necessity of scrutinizing the psychometric properties of the employee motivation scale and demonstrates the utility of employing bifactor model ancillary indices for a more nuanced understanding. For the first time in Albania, we have a measurement instrument related to the motivation of employees in the workplace, which enjoys good psychometric characteristics.

Factors influencing shorebird use of post‐harvest flooded rice fields in California's Sacramento Valley

AbstractBecause of the importance of the Central Valley of California, USA, to shorebirds along the Pacific Flyway, conservation investments have been made in the area's agricultural fields and managed wetlands. Increasingly, landowner incentive programs are being used to deliver shorebird habitat, presenting opportunities to answer remaining questions about which implementation strategies and field management practices are most effective at attracting birds. To provide management guidance for these investments, we collected and analyzed 5 years of data (2014–2018) on shorebird abundance in flooded rice fields enrolled in a dynamic habitat incentive program. The program incentivized flooding in fallow and post‐harvest rice fields in seasons when habitat is relatively sparse, specifically the early fall and late spring. Across nearly 9,000 field observations over 5 years, we explored the relationship between abundance and density (birds/ha) of shorebirds and vegetation cover, soil clay, landscape‐level flooding, and local flood timing, duration, and depth. We observed more shorebirds in fields that were approximately 50% flooded, had water depths of 5–10 cm, and had minimal rice straw or stubble cover, with strong or very strong evidence for each of these relationships. We found that the timing of habitat provisioning was important, with moderate evidence that earlier fall flooding and strong evidence that the duration of fall flooding was associated with higher shorebird density. We observed lower shorebird densities in locations with ample flooded rice habitat in surrounding areas, potentially because shorebirds spread out across the landscape. We found very strong evidence that flooding consistency, either at a site that was continually flooded over many months or a site that had been flooded in previous years, was associated with higher shorebird density. Soil clay content was associated with decreased observed shorebird density, potentially through its influence on the ability of shorebirds to forage for invertebrate prey. These results suggest best practices for shorebird habitat creation in agricultural landscapes, providing important information for conservation and population recovery.

Comprehensive Study of Critical Areas of Change Management as a Starting Point for Leaders in the Area of Managing Human Resources in Organizations: The Case of the Visegrad Four

(1) Background: This research deals with an element of strategic management, namely corporate changes. It applies to production enterprises operating in the countries of the Visegrad Group. Since similar studies in the area of change management in the V4 environment are absent, we consider the research to be beneficial for the subject area. The aim of the paper is to identify key elements in change management that would contribute to improving the work of leaders. (2) Methods: We conducted the research on a sample of 318 manufacturing companies operating in V4 countries. We verified the obtained data using several tests, including Chi-square tests and Fisher’s exact test or binomial test, through which we verified established research hypotheses. A multivariate analysis of variance (MANOVA) was also used, which made it possible to identify critical factors in the area of change management. (3) Results: Critical change management factors emerged from the research, and we also determined the preconditions for successful management of these initiatives. We consider the results significant for change management leaders. (4) We consider the findings to be a contribution to the given field of management, as similar studies are absent in it, which creates a gap in this field.

Exploring the environmental, economic, and social implications of metaverse adoption in business and management

Recently, Metaverse has received increasing attention from both the business and academic worlds. However, its actual use in business and management is still confusing and limited. This study aims to provide a comprehensive overview of the environmental, economic, and social implications of the adoption of this technology within organizations. In addition, enabling technologies to Metaverse and business contexts in which the platform can be applied are identified. First, this study applies a systematic literature review (SLR) to investigate the use of Metaverse in business and management. Secondly, a content and cluster analysis were applied to the final sample of 656 articles to identify the Metaverse's primary research areas and future research directions. The results reveal that Metaverse has mainly social and economic implications such as enhancing collaboration, increasing accessibility, facilitating training, and encouraging productivity and profitability for companies. The major concerns for its implementation are privacy, security, user health, inclusiveness in access, implementation costs, and lack of regulation. Moreover, the application of content and cluster analysis techniques intercepted eight primary research areas defined as user experience, optimization, research method, educational change, business opportunities, security systems, enabling technologies, and healthcare. The article provides valuable insights to support management decision-making when considering the adoption of this technology in specific business contexts. To the best of the authors' knowledge, this is one of the first SLRs on Metaverse in the business and management field that classifies the opportunities, barriers, complementary technologies, and business functions and processes in which the platform can potentially be applied.

Portfolio Optimization Strategies: New Approaches Based on Machine Learning Forecasting

This study provides an in-depth discussion and comprehensive review of the latest applications of machine learning techniques in the field of portfolio optimization. The article begins with an overview of traditional portfolio optimization theory and its limitations, and then focuses on how machine learning predictive models, which have flourished in recent years, can provide new perspectives and tools for solving the problems of non-linearity, dynamics and uncertainty in investment decision-making. This paper provides a detailed overview of the application practices of various machine learning algorithms (e.g., deep learning, reinforcement learning, integrated learning, etc.) in the areas of asset return prediction, risk assessment, and optimal weight allocation, and analyses their advantages and challenges compared to traditional methods. The analysis of relevant research cases reveals the significant effect of machine learning predictions in increasing expected portfolio returns, reducing risk exposure, and achieving effective diversification. The study also explores possible future trends and potential research directions for machine learning in portfolio optimization, highlighting the importance of combining domain knowledge with big data-driven intelligent investment decisions. This review aims to provide financial scholars and practitioners with a new way of thinking about portfolio optimization, and to promote the combination of theoretical research and practical operation in the fields of financial engineering and investment management, so as to achieve more accurate and efficient investment decisions.