Field Of Management Research Articles

Investigating the Challenges of Managing Natural Turfgrass and Synthetic Turf on Community Sports Fields

Both natural turfgrass and synthetic turf fields have distinct advantages and disadvantages and present unique challenges. The challenges evolve over time because of climate change, players’ ever-changing needs, and the development of technologies. It is imperative to identify these challenges and devise effective solutions to overcome them. We conducted a survey of 97 administrators and managers from various organizations in the United States who were responsible for managing community sports fields. Our findings identified budget constraints as the biggest challenge for natural turfgrass field management, followed by issues related to use/scheduling and weather/climate. For synthetic turf field management, the top three challenges included budget constraints, use/scheduling, and other challenges (mainly safety issues). Additionally, administrators and managers consistently indicated increased funding as a solution for addressing challenges of both natural turfgrass and synthetic turf field management. We discuss the implications of these findings and provide potential ways to address these challenges.

Líneas de investigación y perspectivas futuras de los estudios organizacionales: una revisión

Organizational studies allow us to analyze and understand the functioning of organizations, generate knowledge and improve their management and performance, from perspectives different from the classic ones with which the organizational phenomenon has been analyzed in a traditional way; These perspectives invite a critical look at this phenomenon. However, it is relevant to evaluate its potential to provide theories, models and tools that help advance the field of management and improve the effectiveness and sustainability of organizations. To date, no review has been identified in Scopus that synthesizes the literature on organizational studies from a bibliometric analysis, by doing so, this article provides a basis for researchers in organizational studies to learn about various future lines of research. The objective of this document is to review scientific documents published in Scopus(r) on organizational studies, to propose a structure of published scientific knowledge, so that different future lines of research are offered. 1091 documents were found that met the inclusion and exclusion criteria in the database that were processed with Bibliometrix, VosViewer and ToS. The main lines of research identified were: a) Leadership and management of organizational change; b) Changing, diverse and inclusive work environments; c) Legitimation, sustainability and organizational responsibility.

The Natural Landscape as A Strategic Element in Nature Tourism Management

Objective: The aim of this study is to investigate the role of the natural landscape as a strategic element in nature tourism management, in order to understand its conceptual evolution, analyze its relationship with tourism activities and explore the processes of valorization and stereotyping of landscapes in the context of sustainable tourism development. Method: The methodology adopted for the research includes an exhaustive bibliographic search in high-impact databases such as Scopus and Web of Science, complemented with a search in regional databases in Spanish such as Scielo and Redalyc. The selected documents were subjected to a process of critical reading and content analysis to extract key concepts, theories and findings relevant to the study. Results and Discussion: The results revealed that the concept of landscape has evolved from a purely aesthetic and visual perspective to a more holistic understanding that encompasses social, cultural and economic dimensions. The discussion highlights the close relationship between natural landscape and tourism, with landscape serving as a key resource and attraction for nature-based tourism activities. The processes of valorization and stereotyping of landscapes are also explored, emphasizing their influence on tourists' perceptions and destination choice. Research Implications: The findings of this study have implications for sustainable tourism planning and management, especially in areas with significant natural and cultural landscapes. The research emphasizes the need for a multidisciplinary approach to landscape conceptualization and management, as well as the importance of considering landscape as a central element in the development of sustainable tourism products and experiences. Originality/Value: This study contributes to the literature by providing a comprehensive and up-to-date review of the relationship between natural landscape and nature tourism, bridging knowledge from diverse disciplines.

Geometric features and traffic dynamic analysis on 4-leg intersections

AbstractWith the escalating density of vehicles converging at road intersections, the surge in road accidents, traffic conflicts, and traffic congestion has emerged as a pressing concern. This research paper addresses these challenges by employing MC (manual control) techniques to mitigate encroachment issues at three selected intersections. These intersections were identified through a comprehensive analysis of the Ranking-based Instance Selection (RIS), enabling the design of suitable measures to facilitate smooth traffic flow and minimize the occurrence of crashes. In order to gather pertinent data, the study incorporates various parameters such as traffic volume, peak flow rate (PFR), traffic conflicts, accidents, and intersection inventory. Through the implementation of our proposed approaches, which involve both MC techniques and signalized operation, a supreme level of service (LOS) is attainable. Notably, our findings demonstrate a remarkable reduction in the volume-to-capacity ratio (v/c ratio) of up to 0.62. This paper thus serves as a significant contribution to the field of traffic management, offering practical insights for optimizing intersection design and effectively addressing the challenges posed by increased traffic density.

Internships in Clinical Data Science: A Brief Report

Field-based learning opportunities are considered to be an important and increasingly relevant part of professional learning in the biomedical sciences. The purpose of this study was to document internship opportunities in the combined fields of clinical data management and clinical data science among those attending the Society for Clinical Data Management 2022 annual conference. At the time of the survey there were 276 internship positions staffed across 47 organizations representing pharmaceutical, academic, clinical research, software development, and medical device companies, suggesting ample opportunities for those who wished to gain experience in such organizations. The greatest percentage of internships reported were in the United States, but with a wide range of opportunities worldwide.

Exploring the Relationship Between Performance Management and Em-ployee Motivation: Case Study of Serbian Railways

Purpose – It aims to emphasize the importance of effective performance management practices in today's competitive business landscape, highlighting how they contribute to organizational success through enhanced employee motivation, engagement, and productivity. Aims(s) –The aim of this paper is to investigate various aspects of performance management, focusing on goal setting, feedback mechanisms, performance appraisals, recognition, and coaching. By examining the relationship between performance management and employee motivation, the paper aims to provide insights for organizations to design strategies that foster a motivated workforce and drive performance. Design/methodology/approach – it examines real-world examples and best practices to illustrate how organizations can implement these strategies to enhance employee motivation and ultimately achieve organizational success. Findings – The findings underscore the significance of goal setting within performance management, highlighting that specific and challenging goals increase employee motivation and performance levels. Moreover, performance management systems that emphasize goal alignment and regular feedback are found to further enhance motivation. Limitations of the study – Despite the comprehensive review of literature and empirical evidence, this paper acknowledges several limitations. Firstly, the findings are primarily based on existing research and may not encompass all possible perspectives or developments in the field of performance management and employee motivation. Originality/value – This paper contributes to the existing body of knowledge by synthesizing various theories and empirical evidence on performance management and employee motivation. It provides a comprehensive overview of key components of effective performance management practices and their impact on employee motivation and organizational success.

Nexus of green human resource management and sustainable corporate performance: the mediating roles of green behavior and green commitment

PurposeThe driving force behind this study is the need to learn more about the ways in which green human resource management (GHRM) can impact sustainable corporate performance (SCP), especially in the context of Ho Chi Minh City's manufacturing sector. The primary objective is to analyze the roles of GHRM, green behavior (GBH) and green commitment (GCM) in relation to SCP, as well as identify the mediating roles of green behavior and green commitment in the relationship between GHRM and SCP.Design/methodology/approachThe research design employs a quantitative approach to investigate the nexus of GHRM and SCP, with a focus on the manufacturing sector in Ho Chi Minh City. Methodologically, the study integrates the ability-motivation-opportunity (AMO) and resource-based view (RBV) frameworks to construct a comprehensive theoretical model. Data are gathered from a sample comprising 322 senior managers and directors representing various enterprises. Analysis is conducted utilizing Smart PLS software version 3.3.7, employing partial least squares structural equation modeling (PLS-SEM) to assess both first-level and second-level variables in a two-step process.FindingsThe empirical findings underscore significant relationships between GHRM, green behavior, green commitment and SCP. Specifically, the study reveals that GHRM positively influences green behavior, green commitment and SCP. Additionally, both green behavior and green commitment exhibit positive effects on SCP. Furthermore, the research confirms the pivotal mediating roles of green behavior and green commitment in the relationship between GHRM and SCP.Originality/valueIn terms of originality and value, this study makes notable contributions to both theoretical understanding and practical implications in the field of sustainable business management. By delving into the intricate interplay between GHRM, green behavior, green commitment and SCP, this research extends existing knowledge and offers novel insights. Moreover, the identification of the mediating roles of green behavior and green commitment enriches the theoretical frameworks in this domain. The findings provide practical implications for businesses, particularly in Ho Chi Minh City's manufacturing sector, by emphasizing the significance of optimizing human resource practices for achieving sustainable development goals. This research thus contributes to enhancing competitiveness and sustainability in similar industries, offering valuable guidance for strategic decision-making and policy formulation.

The liability of outsiderness: professional interim managers and their on-the-job challenges

PurposeOrganisations increasingly rely on professional interim managers (PIMs), i.e. independent contractors who perform managerial work. These managers, who are usually very experienced and skilled, could help organisations drastically improve their performance. However, research has found that they often fail to do so, indicating that PIMs face unique on-the-job challenges that challenge their capability to be effective managers. In the study reported in this paper, I explored PIMs’ on-the-job challenges and how they overcome them. To better understand the various on-the-job challenges, I developed the concept of the liability of outsiderness.Design/methodology/approachI applied an exploratory approach and conducted 32 interviews with 21 PIMs.FindingsI uncovered three on-the-job challenges common and unique to PIMs – communicating the contract status and contract period, being quick off the mark and attaining power – and the ways they overcome these challenges.Practical implicationsThis paper reports findings and theory that provide several valuable guidelines for practitioners involved with interim management.Originality/valueInterim management has received little scholarly attention despite its increasing relevance. Empirical research, particularly on PIMs in executive positions, is lacking. This leaves us with little evidence to base our theories and guidelines for interim management. The study reported in this paper adds novel insights to an under-researched but important field of management. The study also introduces the liability of outsiderness concept, which holds much promise for future studies of interim management.

Effective Strategies for Human Resource Development in the Digital Era

The rapid development of digital technology has brought significant changes in various aspects of life, including the field of human resource management (HR). This article aims to identify and analyze effective strategies that can be applied in human resource development in the digital era. In this context, HR development strategies do not only focus on improving technical skills, but also on developing soft skills which are essential for adaptation in a dynamic work environment. This research uses a qualitative approach with a comprehensive literature study method, reviewing various academic and practical sources. relevant to the topic. The main findings of this study show that the integration of technology in the training and development process, the formation of a work culture that supports innovation, and the implementation of a digital-based performance management system are some of the key effective strategies. Apart from that, the importance of visionary and adaptive leadership has also been identified as a determining factor for success in HR development in the digital era. This article provides insight for HR practitioners and managers to formulate HR development policies and programs that are relevant to the demands of the times. In addition, this research also makes a theoretical contribution by offering a conceptual framework for holistic and sustainable human resource development in the digital era.

The drivers of sharing willingness regarding sustainable fashion brand image based on commitment theory

PurposeSustainability is considered a core trend in the development of the fashion industry. Clarifying the driving factors of consumers’ sharing willingness regarding sustainable image from the perspective of psychology can help fashion brands implement sustainable management and deepen industrial sustainable development.Design/methodology/approachBased on commitment theory, this paper proposes a conceptual model that includes three antecedents: perception of greenwashing, environmental, social and governance (ESG) and social media content quality. These affect consumers’ sharing willingness regarding sustainable image through affective commitment, continuance commitment and normative commitment. Furthermore, 310 participants reported their tendencies in a formal empirical study.FindingsThe results show that unlike green perception, which has a significant negative effect, consumers have a significant positive commitment to high perceived levels of ESG and social media content quality. Besides, all three dimensions under the commitment theory play a partial mediating role between consumer perception and sharing willingness.Originality/valueThis study not only extends the research on the commitment theory to the field of fashion marketing and management but also enriches the research context of brand image sharing willingness, which explains the differential effects of different consumer commitments on their information sharing willingness. Moreover, several management implications applicable to the fashion industry have also been proposed based on the conclusion.

NSGA-II based short-term building energy management using optimal LSTM-MLP forecasts

To conduct analysis on the field of electricity management in buildings is crucial to contribute to the clean energy promotion, energy efficiency, and resilience against climate change. This manuscript proposes a methodology for modeling a predictive and calibrated energy management system (EMS) using a hybrid methodology that combines long short-term memory and multilayer perceptron models (LSTM-MLP) optimized by non-dominated sorting genetic algorithm II (NSGA-II). The proposed approach utilizes global forecast system (GFS) data to anticipate energy consumption fluctuations and optimize the use of distributed energy sources, such as photovoltaic (PV) production, based on knowledge of the electricity prices in the free market one day ahead. This energy trade-off in the building is conducted with NSGA-II, guaranteeing the exploration and the exploitation of energy in the building while minimizing energy costs and energy wastes. The research carried out demonstrates the effectiveness of the hybrid LSTM-MLP model and the advantages of NSGA-II in hyperparameter tuning and in energy balance for sustainable building practices. The methodology conducted is tested in an existing building, the Industrial Engineering School located on the Campus Lagoas-Marcosende of the Universidade de Vigo, Spain.

Pattern Classification of an Onion Crop (Allium Cepa) Field Using Convolutional Neural Network Models

Agriculture is an area that currently benefits from the use of new technologies and techniques, such as artificial intelligence, to improve production in crop fields. Zacatecas is one of the states producing the most onions in the northeast region of Mexico. Identifying and determining vegetation, soil, and humidity zones could help solve problems such as irrigation demands or excesses, identify spaces with different levels of soil homogeneity, and estimate the yield or health of the crop. This study examines the application of artificial intelligence through the use of deep learning, specifically convolutional neural networks, to identify the patterns that can be found in a crop field, in this case, vegetation, soil, and humidity zones. To extract the mentioned patterns, the K-nearest neighbor algorithm was used to pre-process images taken using unmanned aerial vehicles and form a dataset composed of 3672 images of vegetation, soil, and humidity (1224 for each class). A total of six convolutional neural network models were used to identify and classify the patterns, namely Alexnet, DenseNet, VGG16, SqueezeNet, MobileNetV2, and Res-Net18. Each model was evaluated with the following validation metrics: accuracy, F1-score, precision, and recall. The results showed a variation in performance between 90% and almost 100%. Alexnet obtained the highest metrics with an accuracy of 99.92%, while MobileNetV2 had the lowest accuracy of 90.85%. Other models, such as DenseNet, VGG16, SqueezeNet, and ResNet18, showed an accuracy of between 92.02% and 98.78%. Furthermore, our study highlights the importance of adopting artificial intelligence in agriculture, particularly in the management of onion fields in Zacatecas, Mexico. The findings can help farmers and agronomists make more informed and efficient decisions, which can lead to greater production and sustainability in local agriculture.

Estimation of potato yield using a semi-mechanistic model developed by proximal remote sensing and environmental variables

Timely monitoring of potato yield status is crucial for guiding field management and ensuring the sustainability of food trade. In recent years, non-destructive remote sensing techniques have emerged as one of the most promising methods for crop yield monitoring. However, most existing potato yield estimation models have primarily been tested at specific growth stages within a single ecosystem, highlighting the urgent need for a model that can be applied across different ecological environments. In this study, we developed a semi-physical model based on hierarchical linear modeling (HLM) to automatically correct yield estimation based on remotely sensed vegetation indices using environmentally relevant variables such as net solar radiation at the surface (ssr), air temperature at 2 m above the surface (t2m), and soil water content in the root zone (swvl). The accuracy and transferability of the model were further evaluated by comparing it with aboveground destructive sampling methods, conventional empirical models, and machine learning approaches. The results demonstrated that site-specific relationships exist between aboveground agronomic traits parameters like biomass and leaf area index (LAI) with respect to yield estimation. Conventional linear statistical and machine learning methods faced challenges in transferring their constructed yield estimation models across regions and years. However, the HLM approach exhibited excellent generalization ability across all trial samples. In the middle and later stages of potato growth, the standardized LAI determining index proved to be the most effective vegetation for predicting yield, while ssr, sktmax, and shallow swvl were identified as key environmental variables affecting yield. By integrating these variables using HLM modeling techniques, we achieved optimal generalization performance (R2 = 0.57, RMSE = 7.65 t/ha, NRMSE = 25.02 % during tuber growth stage; R2 = 0.60, RMSE = 7.37 t/ha, NRMSE = 24.13 % during starch accumulation stage). This study underscores the importance of considering environmental factors when constructing a reliable model for estimating potato yield at different spatial and temporal scales using remote sensing technology.

The role of digital transformation in achieving sustainable supply chain management in Industry 4.0: an editorial review perspective

ABSTRACT Before and aftermath of COVID-19 has created multiple waves of digital transformation adoption in supply chain management. The power of potential benefits is realised as a multitude however the transformation phases are not sustainable. This editorial special issue has edited papers of scholarly research contributions to the theory and practice of digital transformation aspects in the field of logistics and supply chain management. Based on the summary of each contribution and an extended literature review on the theme, this editorial paper proposes a novel framework that could facilitate the logistics industry at times of disruptive technologies when firms are struggling to cope with the challenges created due to the COVID-19 pandemic and the recovery.

Towards Improving Sustainable Water Management in Geothermal Fields: SVM and RF Land Use Monitoring

Towards Improving Sustainable Water Management in Geothermal Fields: SVM and RF Land Use Monitoring

Optimizing the Performance of AI Model for Non-Invasive Continuous Glucose Monitoring: Hyperparameter Tuning and Random Oversampling Approach

Diabetes Mellitus (DM) as a non-communicable disease (NCD) continues to increase every year. Continuous glucose monitoring (CGM) is essential for effective DM management. However, existing disposable glucose monitoring methods still rely on invasive techniques, cause pain, and lack continuous monitoring capabilities. On the other hand, non-invasive techniques are not feasible for CGM due to the biometric data's complexity and the classification system's inadequate performance. This study aims to develop a non-invasive technology to improve the performance of a non-invasive blood glucose classification system using Artificial Intelligence (AI), specifically Convolutional Neural Network (CNN) and an oversampling technique. The oversampling technique could improve data quantity by balancing the amount of data for each class. This study recruited twenty-three participants in the age range of 20 to 22 years comprising seven females and fifteen males. During data recording sessions, blood glucose levels were simultaneously assessed using a gold-standard glucometer and a non-invasive CGM prototype. The proposed CNN model successfully improved the classification accuracy of non-invasive blood glucose monitoring significantly. With the implementation of oversampling for augmenting the data, the accuracy of the proposed model increased to more than 88%. This study concludes that non-invasive approaches combined with AI technology have the potential to provide a convenient and pain-free alternative to traditional monitoring methods, significantly improving diabetes management and enhancing the overall quality of life for those affected by this condition. These findings could revolutionize the field of diabetes management, offering a more comfortable and accurate monitoring solution that could potentially transform the lives of millions of diabetes patients.

Exploring the Role of Digital Innovation in Management and Business Literature: A Bibliometric Analysis

This paper examines the existing field of digital innovation publications in management and business journals. Due to the exponential growth of digital technology adoptions in companies, much attention has been given to the new phenomenon of digital innovation. Prior literature reviews have attempted to explore the phenomenon but they seem to lack objectivity and are limited in scope. By applying three bibliometric techniques – co-citation, co-occurrence, and bibliographic coupling analysis – we provide a holistic overview of the digital innovation publications. We employ 354 primary documents, identify three foundational themes from which digital innovation draws on, and seven emerging topics. We conclude with recommendations for future research in the field of innovation management.

Zeal Nexus - Student Abode

Abstract: Effective and thorough processes are critical to the successful operation and management of hostel facilities in the field of hostel management. An effective hostel administration system called Zeal Nexus was created. to use the MERN stack technology to meet these goals. Scalability, usability, and integration possibilities are frequently hampered by the complexity of the current hostel administration systems. These difficulties may make it more difficult to manage hostel operations effectively, which could have an impact on both resident satisfaction and administrative effectiveness. We suggest building the Zeal Nexus, a cutting-edge, comprehensive hostel management system that makes use of the MERN stack—MongoDB, Express.js, React, and Node.js—in order to address these problems. This potent technology stack will be used in our project to create a scalable, responsive, and intuitive Platform. It simplifies the administration of hostels. A wide range of tools for handling resident data, room assignments, maintenance requests, and financial transactions will be available through the Zeal Nexus, all inside a single, easily navigable interface.

STATISTICAL STUDY OF SOME INDICATORS IN THE LIVESTOCK SECTOR

In this paper, some indicators covering milk production, weight gain and feeding efficiency are studied, such as the duration of lactation, total amount of milk, daily amount of milk, percentage of fat, protein, lactose in milk, for a representative sample taken from S.C.D.A Simnic. In the first part, a descriptive statistical analysis is made of the indicators in the zootechnical field presented, followed by econometric methods regarding confidence intervals for the average of the entire population, at a threshold of 5%. Also, the correlation matrix between the indicators is analyzed and three validated linear regression models are presented with the interpretation of the results. These results help to optimize management in the zootechnical field by making decisions based on quantitative analyses.

근로시간 단축(주 4일제) 관련 글로벌 동향 분석과 변화 방향 제언

This study attempts to suggest future directions in the perspective of human resource management based on various activities related to working-time reduction as a currently social issue and research findings on reduced working hours. Firstly, this study investigates how expected effects of reduced working-time are closely related to the realized effects of them by summarizing the previous studies. Also, based relevant research, this study suggests the overall potential issues that block the adoption of reduced working hours in terms of employees, firms, and gernal employment characteristics. Based on these literature reviews, this study summarizes the processes and results of global Four Day Week Global(4DWG) experiments, and suggests the limitations and directions of currently global experiments. Furthermore, this study investigates the two domestic firms which adopted the reduced working hours in the same industry. By doing In so doing, this study tries to draw the requirement before the adoption of 4DW as well as the driving forces after the adoption of 4DW. Based on these findings, this study proposes the future directions and HRM practices for successful adoption and operation of reduced working hours. In the discussion part, this study suggests future research directions in the human resource management field.