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001-es BibID:	BIBFORM129536
035-os BibID:	(Scopus)105003494762 (WoS)001474709200001
Első szerző:	Mufti Tahir Niyaz (Human Resources Management)
Cím:	Research Trends in Workforce Planning in the Automotive Sector: A Comprehensive Review / Mufti Tahir Niyaz, Dejsi Qorri, Krisztián Kovács, Csilla Juhasz
Dátum:	2025
ISSN:	2076-3387
Megjegyzések:	As the automotive industry continues to develop due to technological advancements, so too do the challenges connected with globalization of operations and the strategic management of human resources. Therefore, our objective was to mapthecurrent research work performed for the period of 2014-2024. Moreover, we conducted a comprehensive analysis regarding emerging topics related to strategic human resources, workforce planning and forecasting, employee wellness, and reskilling/upskilling. Study Design/Methodology/Approach: The methodology used for this review was a Systematic Literature Review, following the PRISMA protocol to remove biases in the review. The search keywords were: workforce planning, strategic HR, skills, employee wellness, and upskilling. In total, 180 articles were retrieved from SCOPUS. Findings: We found that the scholarly work over the year has fluctuated, showing an overall increasing trend of scientific production. The principal themes discussed were ?human, ergonomics, and industrial research`. The research trends were: leadership, knowledge management, innovation, skills, and COVID-19. We concluded that most of the impact on employee satisfaction and upskilling is on an operational level. Originality/Value: Furthermore, our comprehensive review offers theoretical and practical implications in line with the COVID-19 impact and HRstrategies.
Tárgyszavak:	Társadalomtudományok Gazdálkodás- és szervezéstudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk trends productivity and satisfaction HR strategies workplace automotive industry automotive sector comprehensive review
Megjelenés:	Administrative Sciences. - 15 : 4 (2025), p. 140-. -
További szerzők:	Qorri, Dejsi (1998-) (PhD Hallgató) Kovács Krisztián (1981-) (okleveles gazdasági agrármérnök) Juhász Csilla (1970-) (agrármérnök, mérnöktanár, felsőoktatási menedzser)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM125162
Első szerző:	Qorri, Dejsi (PhD Hallgató)
Cím:	Data-Driven Solution Using Waterfall Model for Farm Data Management in Albania / Qorri Dejsi, Gjermeni Irida, Felföldi János, Tsogtdelger Maral, Mufti Tahir Niyaz, Gashi Njomza, Kovács Krisztián
Dátum:	2024
Megjegyzések:	XX Agricultural Science Days Beyond Tiszántó, (2024)(Debrecen) Agricultural sector remain the main contributor in the GDP of Albania, offering opportunities for local and regional development. Despite this, the agricultural businesses are not taking advantage of big data generated from their farm activities and processes. As such, the objective of our study was to propose a solution for data management with functions of gathering, analyzing, and visualization that can improve the performance of small-medium farms in Albania. The methodology used in our study was the traditional software engineering waterfall methodology which includes the stages of planning, design, development, testing, and deployment. In addition, this study offers a strategic approach that integrates the data management in farm management, emphasizing the importance of sales and purchase data in monitoring and optimizing farm efficiency and effectiveness with practical approach. The UML (unified modeling language) use case diagram was employed to illustrate the interaction between business process and farm management activities. In addition, the C# programming language and ASP.NET framework along with SQL (structured query language) are used to implement functions above mentioned belonging to the design and development steps in the waterfall model. Furthermore, to achieve an efficient and functional management system we conducted a comprehensive SWOT in-depth analysis using quantitative and qualitative variables related to innovation, education, and labor market, drawing on data from Institute of Statistics of Albania, World Bank, and various Empirical studies. The findings suggest that implementing data-driven solutions can enhance the effectiveness of small-medium size farms in Albania. Additionally, the study identifies the opportunities and challenges associated with implementing data-driven solutions to optimize farm management in Albania.
Tárgyszavak:	Társadalomtudományok Gazdálkodás- és szervezéstudományok nem besorolt egyéb data-driven solution farm management sales and purchases C# programming waterfall model
További szerzők:	Irida Gjermeni (1985-) (Lecturer) Tsogtdelger Maral (2003-) (Chemical engineer student) Felföldi János (1968-2024) (mérnök-közgazdász) Mufti Tahir Niyaz (1998-) (Human Resources Management) Gashi Njomza (2001-) (Food Scientist) Kovács Krisztián (1981-) (okleveles gazdasági agrármérnök)
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat
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