Context Of Industry Research Articles

Critical success factors of global virtual teams (GVTs): a study based on UK information technology experts’ opinion

Purpose This study aims to examine the critical success factors of global virtual teams (GVTs) working in the information technology industry in the UK. It also focuses on the ranking of the success factors and shedding light on the perceived cause-and-effect relationship between the factors. Design/methodology/approach Data was collected from executives working in the IT industry in the UK. Fuzzy DEMATEL analysis was incorporated to generate results. Findings The findings suggest that overcoming perceived and temporal distance, empowerment, integrative approach, members’ competencies and cultural intelligence are considered to be causal variables. In contrast, effective team leadership, trust, commitment to task and communication are regarded as an effect. In terms of the degree of importance, communication was ranked in first place. Effective team leadership and overcoming perceived and temporal distance were found to be in second and third place. Empowerment was found to be in the last position in terms of the degree of importance. Originality/value To the best of the authors’ knowledge, this paper is among the first research on GVTs in the UK IT industry context. Also, using the Fuzzy DEMATEL approach differentiates it from the previous studies. The perceived cause-and-effect analysis of the current study using the experts’ opinions has a direct policy-making application as well, which makes the finding easy to use by practitioners and policymakers at the same time.

Utilizing advanced language models to identify industrial symbiosis opportunities within the circular economy: capabilities and challenges

PurposeThe aim of this study is to investigate the application of advanced language models, particularly ChatGPT-4, in identifying and utilizing industrial symbiosis opportunities within the circular economy. It examines how the model can aid in promoting sustainable industrial practices by processing data from the MAESTRI project database, which includes various symbiotic relationships, as well as randomly selected waste codes not included in the database. The research involves structured queries related to industrial symbiosis, circular economy, waste codes and potential opportunities. By assessing the model’s accuracy in response generation, the study seeks to uncover both the capabilities and limitations of the language model in resource efficiency and waste reduction, emphasizing the need for ongoing refinement and expert oversight.Design/methodology/approachThe study adopts a mixed-methods approach, combining qualitative and quantitative analyses to explore the potential of ChatGPT-4 in identifying industrial symbiosis opportunities. Data from the EU-funded MAESTRI project database, which includes existing symbiotic relationships, as well as randomly selected waste codes not included in the database, are used as the primary sources. The language model is queried with structured questions on industrial symbiosis, circular economy and specific waste codes utilizing the model’s advanced functions such as file upload. Responses are evaluated by comparing them with the MAESTRI database and official European Waste Catalogue (EWC) codes.FindingsThe study finds that ChatGPT-4 possesses a solid understanding of fundamental concepts related to industrial symbiosis and the circular economy. However, it encounters challenges in accurately describing EWC codes, with a notable portion of descriptions found to be incorrect. Despite these inaccuracies, the model shows potential in suggesting symbiotic opportunities, although its effectiveness is limited. Interestingly, the study reveals that the model can occasionally identify correct symbiotic relationships even with initial inaccuracies. These findings highlight the need for expert oversight and further development of the language model to improve its utility in complex, regulated fields like industrial symbiosis.Originality/valueThis study’s originality lies in its exploration of advanced language models, particularly ChatGPT-4, for identifying industrial symbiosis opportunities within the circular economy framework. Unlike previous research, which primarily focuses on specific sectors and AI’s role in general resource efficiency, this study specifically examines the capabilities and limitations of the language model in handling specialized and regulated information, such as EWC codes across various sectors. It employs a novel approach by comparing AI-generated responses with an established symbiosis database, which is comprehensive and spans all sectors rather than being limited to a single industry, as well as with randomly selected waste codes not included in the database. The study contributes to understanding how AI tools can support sustainable industrial practices, emphasizing the importance of refining these models for practical applications in environmental and industrial contexts.

Unsteady Magneto-radiative Flow of Copper-water Nanofluid Over an Exponentially Stretching Surface

Understanding the complex behavior of fluid flows under various physical influences is crucial for advancing engineering and industrial applications. This paper presents the investigation of the unsteady, incompressible, single-phase magneto-radiative flow of a copper-water nanofluid over an exponentially stretching surface, considering the effects of viscous dissipation and temperature-dependent heat sources. This model, proposed in the present analysis, is based on fundamentals of the continuity and Navier–Stokesequations with mass conservation. Further, use of a similarity transformation will reduce the equations to dimensionless form and provide a numerical solution using the Runge–Kutta–Fehlberg method. In physics, engineering, and industrial applications, the most interesting parameters are the velocity, temperature, skin friction, and the Nusselt number (Nu). The results of this study are compared with previous works, showing significant agreement with findings under similar conditions. The analysis reveals that both temperature and velocity boundary layer increase when all very specific effects of radiation (R), heat source (Q), copper nanoparticle volume fraction, and magnetic field strength parameter are present. On the other hand, it is found that skin friction increases when considering both copper nanoparticle volume fraction and magnetic field strength parameter, but the Nu decreases if R, Q, copper nanoparticle volume fraction, and magnetic field strength parameter are the factors responsible for that. These outcomes will be further delineated through graphics and be elaborated in engineering and industrial context.

Modeling Drop Atomization Using Computational Fluid Dynamics

Atomization, a process in which droplets break into smaller structures, is common in both natural and industrial contexts. The mechanisms of droplet deformation and breakup are often described through hydrodynamic instabilities, informed by experimental studies, theoretical developments, and simulations via Computational Fluid Dynamics (CFD). In this work, Direct Numerical Simulations (DNS) were employed to analyze droplet atomization under various conditions. Two models were considered for studying droplet deformation and breakup: one axisymmetric and the other threedimensional. The results showed that the deformation and fragmentation of the droplet are highly de- pendent on the Weber number. Additionally, an increase in the Weber number accelerates the onset of the fragmentation process. The three-dimensional (3D) simulations revealed perforations with a spatial distribution characterized by initial axial symmetry, which dissipates as fragmentation progresses. DNS proves valuable in such studies due to its ability to detect the droplets produced during atomization, enabling the measurement of their positions and velocities at each moment, which can be aggregated into statistical data.

Diversity of Potential (Bio)technological Applications of Amino Acid-Based Ionic Liquids

This review explores the emerging potential of amino acid-based ionic liquids (AA ILs) in various (bio)applications, emphasizing their unique properties and versatility. It provides a comprehensive analysis of recent advancements, covering applications in drug delivery, catalysis, environmental remediation, and biotechnology. The review also offers an overview of the synthetic methods for preparing AA ILs, highlighting both traditional and innovative approaches, and examines key physicochemical properties—such as biocompatibility, stability, and tunability—that make AA ILs highly attractive for diverse applications. Additionally, challenges hindering their widespread adoption, including high production costs, toxicity concerns, scalability issues, and environmental impact, are discussed. This review concludes with perspectives on future research directions and strategies to overcome these challenges, unlocking the full potential of AA ILs in both scientific and industrial contexts.

Applications of hydrogels in wound healing: A narrative review of nursing insights

Due to their distinctive physicochemical characteristics, hydrogels have garnered considerable attention across various domains, including biology, biomedical technology, biotechnology, nursing, and wound healing. These hydrophilic polymer networks can absorb and retain substantial quantities of water, endowing them with notable flexibility and biocompatibility, thus rendering them ideal for numerous applications. This review presents an exhaustive analysis of the types and properties of hydrogels, emphasizing their diverse classifications, preparation methods, and gelation mechanisms. We explore their extensive applications, encompassing cell culture, tissue engineering, drug delivery systems, biosensors, and medical implants. Additionally, the review scrutinizes the role of hydrogels in nursing care, particularly in wound management and treatment, demonstrating their efficacy in promoting wound healing and enhancing patient comfort. The review further highlights recent advancements in hydrogel research, including the development of intelligent and stimuli-responsive hydrogels and nanocomposite hydrogels, which exhibit enhanced functional properties. Furthermore, we address the challenges encountered in applying hydrogels, such as mechanical strength and production scalability, and examine prospective directions for future research and development. This comprehensive overview emphasizes the versatile and transformative potential of hydrogels across multiple disciplines, paving the way for innovative solutions in clinical and industrial contexts.

Economic feasibility assessment of optimum grid-connected PV/battery systems to meet electricity demand for industrial buildings in Saudi Arabia

This study presents a comprehensive analysis of the energy performance and economic feasibility of optimal power generation systems, including an electrical network and a grid-connected PV/battery system, designed to meet the electricity demands of an industrial building in Saudi ‘Arabia’s Eastern region. The building, located in Abqaiq City, spans approximately 29,000 m2 and has an average annual electrical consumption of 6,500 MWh. The primary focus is on assessing the economic feasibility of these systems under local grid conditions. Simulations using PVsyst software were conducted for three configurations: grid-connected PV and PV with battery. The findings indicate that bifacial PV modules increase energy harvesting in coastal arid climate regions, with specific production ranging from 2,235 to 2,158 kWh/kWp/year and a PR between 95.9 % and 92.6 %. The grid-connected PV system is more feasible under industrial electricity tariffs, with a levelized cost of energy of $0.016/kWh, an NPV of $4,233,274, an ROI of 426.5 %, and a payback period of 4.7 years. These systems achieve energy savings of approximately 66 % for grid-connected PV and 89 % for hybrid PV/battery systems. Additionally, commercial and global tariffs significantly enhance the NPV and ROI of both systems, reducing the payback period and improving economic feasibility. Under commercial tariffs, the grid-connected PV system excels in ROI and payback period, while the hybrid system outperforms in NPV under global tariffs. By addressing economic and climate challenges in harsh coastal environments, this work provides valuable insights for sustainable investment decisions in an industrial city context

Risk factors identification and injury severity classification in Alaska’s mining industry using statistical and machine learning approaches

ABSTRACT This study examines safety-related factors influencing injury severity in Alaska’s mining industry using workers’ compensation data. The injury severity was characterised by claim type (medical only and lost time). Statistical analyses, including chi-square tests and logistic regression, identified significant associations between claim type and factors such as age group and cause of injury, while mine type, gender, body part injured, and nature of injury were found to be non-significant. Logistic regression revealed that older adults (OR = 2.76) and young adults (OR = 1.78) had higher odds of severe injuries, with strain injuries as the most frequent cause. Machine learning models were developed to classify injury severity using these factors, with logistic regression demonstrating the most consistent performance on test data (average score: 0.62). The findings emphasise the importance of targeted safety interventions for high-risk groups and prevalent injury causes to enhance workplace safety. While this study provides actionable insights for safety management, it is constrained by the limited scope of six safety-related factors and a relatively small dataset. The approach adopted in this study offers a framework for developing safety management models applicable to other mining operations and industrial contexts.

Obtaining heat transfer coefficients (Kv) distribution directly from mass flow measurements during the sublimation step of freeze-drying.

The knowledge of heat transfer coefficients (Kv) and their distribution is a crucial element in the successful transfer of a freeze-drying process to a new piece of equipment. Nevertheless, the implementation of the classical ice sublimation method is resource consuming, particularly in the industrial context, which represents a significant barrier to its application. This paper demonstrates that the Kv distribution can be calculated from the measurement of mass flow during a freeze-drying operation by reversing the results of process simulation calculations. This methodology works independently of the experimental method used to measure the mass flux: tunable diode laser absorption, inlet/outlet temperature difference of the shelves, or chamber/ condenser pressure difference. The advantage of this new method is that it requires no specific experimental effort and can be carried out on routine production runs (especially with the temperature or pressure difference methods), provided the freeze drier possesses at least shelf inlet/outlet temperature measurement and/or chamber and condenser capacitance pressure measurement. Furthermore, the measurement encompasses all vials, which is not achievable using the conventional method for commercial units that contain tens of thousands of vials. Once fed back into the primary drying mechanistic model, the Kv distribution is used to estimate the temperature distribution in the product. In this article, we provide practical examples at all scales, from laboratory to industrial production.

A CONCEPTUAL FRAMEWORK OF GREEN MANUFACTURING STRATEGIES FOR GREENHOUSE GAS EMISSIONS REDUCTION IN MALAYSIAN MANUFACTURING INDUSTRY

Green manufacturing is a practice that aims to reduce waste and pollution throughout the manufacturing process. The research scope covers how the implementation of green manufacturing practices helps manufacturing companies to reduce GHG emissions. The main objective of the study is to determine the relationship between green manufacturing practices and GHG emissions and how knowledge, costs, regulations and technology moderate the relationship between green manufacturing practices and GHG emissions in Malaysia. This paper reviews the existing literature on the topic and proposes a conceptual framework of green manufacturing practices for Malaysian manufacturing industry context. This study intends to provide insights into green manufacturing and as well as to fill the research gaps in how green manufacturing helps in reducing GHG emissions.

The Influence of Leadership Style, Work Facilities, and Salary on Employee Motivation

This study aims to analyze the influence of leadership style, technology-based work facilities, and salary systems on employee work motivation at PT. Elektrindo Sarana Abadi. In a volatile economy, companies must maintain the stability and sustainability of their operations. The workforce is a key element in achieving organizational goals, and an adaptive leadership style, adequate work facilities, and a fair compensation system greatly influence work motivation. This study uses a quantitative approach with the Multiple Linear Regression Analysis method using SmartPLS ver.4. The research sample consisted of 100 respondents who were employees of PT. Elektrindo Sarana Abadi. The study results show that digital leadership style, work facilities, and salary significantly influence employee work motivation. Simultaneously, these three variables also have a significant effect on work motivation. These findings underscore the importance of developing leadership training programs to improve managerial skills and employee motivation, periodic audits and improvements to work facilities, and adjustments to salary structures and incentive systems so employees feel financially valued. In addition, implementing a regular performance evaluation system and the use of feedback from employees for continuous improvement are highly recommended. The study concludes that flexible and adaptive leadership approaches, adequate work facility support, and a fair compensation system are crucial in increasing employee motivation in an increasingly technology-connected work environment. Further research is suggested to explore other factors influencing work motivation and expand the research object to different industry contexts.

Documenting diversity on screen: interactive documentaries (i-docs) as tools for queer activism

ABSTRACT This article advocates for the use of online interactive documentaries (i-docs) by creative practitioners and creative practice academics for social and cultural activism by drawing on two LGBTIQA + focused i-docs: Queer Representation Matters [Krikowa, Natalie, dir. 2023. Queer Representation Matters. Sydney, Australia. http://www.queerrepresentationsmatters.com.] and Queer Interruptions [Aguas, Evangeline, dir. 2021. Queer Interruptions. Sydney, Australia.]. Queer Representation Matters explores historical and contemporary issues in queer screen representation in Australia and overseas. The i-doc draws from interviews with queer screen media scholars, TV writers and directors and film festival curators, to investigate storytelling tropes such as ‘bury your gays’ and ‘cancel your gays’ within an industrial context to highlight the importance of representation of queer people and stories in screen media. Queer Interruptions focuses on the contemporary queer viewing experience and queer fans’ reactions to tropes such as ‘bury your gays’. The project explores the sense of repetition and melancholy that fans felt upon reliving these deaths, linking these to abstract theories of queer time. The work seeks to intervene in issues of queer representation through a multidisciplinary, innovative, and accessible approach to queer theory, fan studies and online interactive works. These works illustrate how creative practice researchers can make research on activism accessible to a wider range of audiences outside of the academy.

Metaheuristics for multi-objective scheduling problems in industry 4.0 and 5.0: a state-of-the-arts survey

The advent of Industry 4.0 and the emerging Industry 5.0 have fundamentally transformed manufacturing systems, introducing unprecedented levels of complexity in production scheduling. This complexity is further amplified by the integration of cyber-physical systems, Internet of Things, Artificial Intelligence, and human-centric approaches, necessitating more sophisticated optimization methods. This paper aims to provide a more comprehensive perspective on the application of metaheuristic algorithms in shop scheduling problems within the context of Industry 4.0 and Industry 5.0. Through a systematic review of recent literature (2015–2024), we analyze and categorize various metaheuristic approaches, including Evolutionary Algorithms (EAs), swarm intelligence, and hybrid methods, that have been applied to address complex scheduling challenges in smart manufacturing environments. We specifically examine how these algorithms handle multiple competing objectives such as makespan minimization, energy efficiency, production costs, and human-machine collaboration, which are crucial in modern industrial settings. Our survey reveals several key findings: 1) hybrid metaheuristics demonstrate superior performance in handling multi-objective optimization compared to standalone algorithms; 2) bio-inspired algorithms show promising results in addressing complex scheduling and multi-objective manufacturing environments; 3) tri-objective and higher-order multi-objective optimization problems warrant further in-depth exploration; and 4) there is an emerging trend towards incorporating human factors and sustainability objectives in scheduling optimization, aligned with Industry 5.0 principles. Additionally, we identify research gaps and propose future research directions, particularly in areas such as real-time scheduling adaptation, human-centric optimization, and sustainability-aware scheduling algorithms. This comprehensive review provides insights for researchers and practitioners in the field of industrial scheduling, offering a structured understanding of current methodologies and future challenges in the evolution from Industry 4.0 to 5.0.

Metaverse in industrial contexts - a comprehensive review

This paper explores the potential of Metaverse technology in industrial Asset Management (AM). By integrating AI and digital technologies, the Metaverse can enhance Human-System-Interaction (HSI) and optimise AM processes. However, implementing a Metaverse in industrial contexts faces challenges, particularly in visualising physical and virtual assets. This paper conducts a systematic review to address these challenges and identify potential solutions. The findings reveal that while the necessary technologies are available, their widespread adoption in industrial AM is limited. The paper presents a comprehensive overview of research themes related to Metaverse applications in industrial contexts, highlighting the evolving landscape and potential benefits. Ultimately, this research aims to contribute to the advancement of Metaverse technology in industrial AM by providing insights into its development, implementation, and challenges along with an Industrial Metaverse Framework. An example of applying the Metaverse concept in the railway sector has been presented and validated using railway digital assets available within the eMaintenance LAB. The practical implications of this work are expected to result in increased efficiency and effectiveness in the operation and maintenance procedures across various industrial sectors.

A Systematic Review of Trust Assessments in Human–Robot Interaction

The integration of robots into daily life has increased significantly, spanning applications from social-care to industrial settings with collaborative robots. Ensuring a safe, secure environment and equitable workload distribution in human-robot collaborations is crucial. Trust is a key factor in these environments, essential for enhancing collaboration and achieving tasks while maintaining safety. Under-trusting robots can hinder productivity, while over-trusting them can lead to accidents. A comprehensive literature review of 100 publications from 2003 to 2023 analyzes trust and its influencing factors in industrial and social-care contexts. Findings reveal that in industrial settings, robot-related factors are more influential, whereas in social-care, human and environmental factors play a significant role. Furthermore, the review delves into gauging trust through observable behavior, while also exploring various trust evaluation methodologies. Results show that trust can be gauged through human behaviors, physical cues, and physiological measurements. Concerning trust evaluation methodologies, traditional questionnaires have limitations, opening new opportunities for machine learning and sensor-based approaches to real-time trust evaluation, as trust is a dynamic cognitive value that evolves over time. Notably, 97% of the reviewed articles were published in the last decade, underscoring a growing interest in human–robot interaction and trust within the scientific community.

Enterprise risk management manufacturing industry quality determinants

Goal: Large manufacturing companies face significant risks due to importing raw materials and exposure to fluctuating exchange rates. Enterprise Risk Management (ERM) is vital in this sector to manage its distinctive risks. This study finds ERM factors in Indonesia and Malaysia that affect company value and empirically evaluates risk management in their organizations. Design / Methodology / Approach: The factors that influence the quality of a company's ERM examined in this study include auditor quality, ownership concentration, board monitoring, gender on the board of commissioners, gender on the board of directors, and human capital. This study's population is 2018-2020; 300 Indonesian and 252 Malaysian manufacturing companies contributed 552 research observations. Results: This study shows that a qualified auditor, board monitoring, gender ratio on the board of commissioners, and human capital may uncover ERM implementation issues. On the other hand, higher share ownership does not affect ERM. Implications for practitioners and suggestions for future researchers are also described. Limitations of investigation: The crucial role of Enterprise Risk Management (ERM) in mitigating these unique industry risks, this study underscores the limitations inherent in factors such as auditor quality, ownership concentration, board monitoring, and gender diversity within corporate leadership. Practical implication: The necessity for manufacturing companies to prioritize specific aspects of Enterprise Risk Management (ERM) in their organizational strategies. Originality / Value: This research illuminates the nuanced interplay of factors shaping Enterprise Risk Management (ERM) efficacy within the dynamic context of the manufacturing industry.

Utilization of Blockchain Technology in Talent Management: Increasing Transparency and Security of the Employee Recruitment Process

Blockchain technology has become a promising innovation that improves transparency and security in talent management, especially in recruitment and human resource management, to find, develop, and retain employees. This article explores how blockchain can address key challenges such as data manipulation, time efficiency, and document authenticity in recruitment. Using the Systematic Literature Review (SLR) approach, the study analyzed 50 indexed scientific articles from high-reputation journals published in the last decade. The results of the review show that blockchain can provide solutions for verifying candidate certification, simplifying the selection process, and maintaining the integrity of employee data. In addition, implementing this technology can also speed up decision-making time and reduce operational costs. However, there are obstacles, such as limited infrastructure, high initial implementation costs, and the need for better regulation. This article provides recommendations for further research related to blockchain adoption in various industry contexts. With blockchain's great potential, this technology is hoped to become a new standard in a more efficient and secure employee recruitment system.

GEOMETRIA DAS BROCAS HELICOIDAIS E SUA APLICAÇÃO NA INDÚSTRIA

The drilling process is an extremely important event in the machining processes of materials.For this operation to occur, the use of drills is essential. In the historical context, drills arecharacterized as one of the oldest machining tools developed by man, with the first records ofsimilar tools dating back to ancient Egypt, where cylindrical metallic structures with sharp endswere rotated with the help of a rope and an arc for producing holes in wood or low hardnessmaterials. Currently, the use of drills is diverse and their use in the industrial context isincreasing. The geometry of this type of tool has undergone considerable evolution withtechnological development, however, the drills still use the shearing mechanism, which in turncharacterizes drilling as a conventional machining process. Regarding the machining ofmetallic materials, the models and types of drills can be diverse and their application will berelated to the type of operation that will be performed. For this reason, twist drills must havegeometric characteristics and resistance inherent to the material from which they aremanufactured. These characteristics must be such that they best optimize resistance to fatigueand buckling, durability, and suitability for cutting parameters, with the aim of promotingefficient drilling and free from dimensional and geometric deviations, guaranteeing theprecision and tolerance required in the project. In this context, the present work seeks to addressthe design and geometry of twist drills, promoting a discussion about their growing use in themechanical industry and their economic impacts.

Updating Vocational English Textbooks to Meet Industrial Demands in Indonesia

The pressing demand for work-relevant vocational English textbooks is essential for delivering effective learning materials that align with students' requirements. Appropriate textbooks can boost English language competence by enhancing students' abilities in listening, speaking, reading, and writing. Listening skills form the cornerstone for developing proficiency in other language areas. However, survey revealed that 92.3% of the 52 vocational schools in Batam City had not updated their English textbooks, and 96.2% lacked listening materials tailored to industrial demands. As a result, only 11.87% of the 4,035 Batam City vocational school students who passed the test showed competence in the listening component of the English assessment. This research aims to create a valid and effective vocational English textbook that improves students' English communication abilities based on workplace requirements. To accomplish this goal, the study employed a developmental research approach (Borg and Gall). The research was conducted in Batam City, encompassing 52 vocational schools, 95 English teachers, and 4,070 vocational school students in Batam City, Indonesia. The study's outcomes indicate that: 1) the vocational English listening textbook developed was empirically validated with an average score of 3.6, placing it in the highly valid category. 2) This textbook has also been empirically shown to be effective in enhancing students' listening competence, with a sig. value of 0.000, which was below 0.05. Consequently, this textbook benefits the government and stakeholders, particularly vocational English instructors in Batam City, by improving their English communication competence through the provision of textbooks relevant to industrial contexts.

Políticas, estrategias y tecnologías ambientales en las empresas mineras de yeso para una gestión sostenible en la Guajira, Colombia

Adopting responsible environmental practices ensures that natural resources are used sustainably. This is essential to ensure that future generations can also benefit from the resources and the environment. For this reason, the objective of this research is to analyze the environmental policies, strategies and technologies used in gypsum mining for sustainable management in La Guajira, Colombia. Considering that they are essential for various reasons, especially in environmental, industrial and extractive contexts such as mining. Furthermore, this study is descriptive and theoretical in nature, adopting a non-experimental research design due to its qualitative nature, so that the variables are not deliberately manipulated. The population of interest is made up of the mining companies Yesos Sdinyc S.A.S., Yesos Colombia S.A.S., and the artisanal gypsum mine in Manaure. The results revealed with regard to environmental policies within companies, there is a lack in their application; Regarding the implementation of environmental strategies and technologies, companies have taken the initiative to improve their mining activities. Despite the efforts of some of these companies to improve and contribute to environmental care, the adoption and implementation of comprehensive strategies that promote efficient management of natural resources and ensure responsible and sustainable operational practices in gypsum mining are recommended.