Mercy Mulwa | Computer Science | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Mercy Mulwa
Affiliation Jomo Kenyatta University of Agriculture and Technology (JKUAT)
Country Kenya
Scopus ID 58922109600
Documents 1
Citations 1
h-index 16
Subject Area Computer Science
Event International Research Excellence and Best Paper Awards

Mercy Mulwa

Mercy Mulwa of Jomo Kenyatta University of Agriculture and Technology (JKUAT), Kenya is recognized with the Best Paper Award for research excellence in the field of Computer Science. The recognized research, titled “GMM-LIME explainable machine learning model for interpreting sensor-based human gait,” focuses on explainable machine learning techniques for interpreting sensor-based human gait data and improving the transparency and understanding of machine learning models.

Abstract

This article recognizes Mercy Mulwa for research excellence in Computer Science and for the paper titled “GMM-LIME explainable machine learning model for interpreting sensor-based human gait.” The research focuses on the application of explainable machine learning to sensor-based human gait analysis. By combining a Gaussian Mixture Model (GMM) approach with Local Interpretable Model-agnostic Explanations (LIME), the work addresses the need for greater interpretability in machine learning systems that analyze human movement data. The research contributes to the growing field of explainable artificial intelligence, machine learning interpretation, sensor-based computing, and human gait analysis.

Keywords

Explainable Machine Learning, GMM-LIME, Gaussian Mixture Model, LIME, Human Gait Analysis, Sensor-Based Gait Recognition, Explainable Artificial Intelligence, Machine Learning Interpretability, Sensor Data, Computer Science.

Introduction

Machine learning has become increasingly important for analyzing complex sensor data and identifying meaningful patterns in human movement. Human gait analysis is an important area of research because gait characteristics can provide valuable information for applications involving movement recognition, activity analysis, intelligent sensing, and human-centered computing.

The awarded paper, “GMM-LIME explainable machine learning model for interpreting sensor-based human gait,” addresses the challenge of understanding how machine learning models interpret sensor-based gait information. The integration of explainability techniques provides a pathway toward making machine learning predictions more understandable to researchers, practitioners, and end users.

Research Profile

Mercy Mulwa is affiliated with Jomo Kenyatta University of Agriculture and Technology (JKUAT), Kenya, and works within the broad field of Computer Science. The provided academic information identifies the researcher with Scopus Author ID 58922109600. The supplied profile information records 1 document, 1 citation, and an h-index of 16.

Research Contributions

The research makes a contribution to explainable artificial intelligence and sensor-based machine learning by focusing on the interpretation of human gait data. The use of GMM-LIME provides an explainability-oriented framework for examining machine learning behavior and identifying patterns that may influence model outputs.

Research Impact

The research has relevance to several areas of modern computing, including explainable AI, machine learning, sensor analytics, gait recognition, human activity analysis, and intelligent systems. Explainable models can help researchers better understand complex relationships within sensor-generated data and support the development of more transparent computational systems.

Award Suitability

The Best Paper Award recognizes research that demonstrates academic relevance, methodological value, originality, and contribution to its field. Mercy Mulwa’s research aligns with these objectives through its focus on GMM-LIME explainable machine learning for interpreting sensor-based human gait.

Conclusion

Mercy Mulwa represents research excellence in the field of Computer Science through the recognized paper “GMM-LIME explainable machine learning model for interpreting sensor-based human gait.” The research addresses an important intersection between sensor-based computing, human gait analysis, machine learning, and explainable artificial intelligence.

External Links

References

  1. Scopus Author Profile: Mercy Mulwa, Author ID 58922109600.
    Scopus.https://www.scopus.com/pages/authors/58922109600
  2. Bet Paper Awards.
    https://bestpaperawards.com/

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DESMOND BAYONG | Business | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

DESMOND BAYONG
Affiliation University of Business and Integrated Development Studies
Country Ghana
Scopus ID 59674838400
Documents 10
Citations 54
h-index 4
Subject Area Business
Event International Research Excellence and Best Paper Awards
ORCID 0009-0001-1145-9162

DESMOND BAYONG

DESMOND BAYONG of the University of Business and Integrated Development Studies, Ghana is recognized with the Best Paper Award for research in the field of Business. The recognized paper, titled “CEO Power and Environmental Accounting Disclosure: Comparative Evidence From Emerging Economies,” examines the relationship between chief executive officer power and environmental accounting disclosure, with particular attention to comparative evidence from emerging economies.

Abstract

This article recognizes DESMOND BAYONG for the Best Paper Award in recognition of research in the field of Business. The recognized research, titled “CEO Power and Environmental Accounting Disclosure: Comparative Evidence From Emerging Economies,” focuses on the relationship between executive leadership characteristics and environmental accounting disclosure. The comparative emphasis on emerging economies provides a context for examining how corporate governance and executive power may relate to the communication of environmental information by organizations. The research is positioned within broader discussions of corporate governance, accounting disclosure, environmental reporting, and business sustainability.

Keywords

CEO Power, Environmental Accounting Disclosure, Environmental Reporting, Corporate Governance, Chief Executive Officer, Emerging Economies, Accounting, Business, Sustainability, Corporate Disclosure, Executive Leadership, Environmental Information.

Introduction

Environmental accounting disclosure has become an important area of research within accounting and business because organizations increasingly communicate information concerning environmental activities, responsibilities, and performance. The quality and extent of such disclosure may be influenced by organizational governance structures and the characteristics of senior corporate decision-makers.

The recognized paper, “CEO Power and Environmental Accounting Disclosure: Comparative Evidence From Emerging Economies,” addresses this research area by examining the relationship between CEO power and environmental accounting disclosure. Its comparative focus on emerging economies provides a context for considering how executive influence may be associated with corporate environmental reporting practices.

Research Profile

DESMOND BAYONG is affiliated with the University of Business and Integrated Development Studies, Ghana, and is associated with the subject area of Business. The supplied academic profile identifies a Scopus Author ID of 59674838400, with 10 documents, 54 citations, and an h-index of 4. The researcher’s ORCID identifier is 0009-0001-1145-9162. These profile details provide bibliographic context for the researcher’s academic record. [1] [2]

Research Contributions

The recognized research brings together two principal dimensions of business research: CEO power and environmental accounting disclosure. This combination provides a framework for considering whether characteristics associated with executive authority are relevant to corporate environmental reporting practices.

Publications

The paper identified for the Best Paper Award is:

  • Bayong, Desmond. CEO Power and Environmental Accounting Disclosure: Comparative Evidence From Emerging Economies.

The supplied information identifies this paper as the research associated with the recognition. No DOI was provided in the supplied information; therefore, no DOI identifier or DOI URL has been added to avoid introducing an unverified bibliographic identifier.

Research Impact

The supplied Scopus profile records 10 documents, 54 citations, and an h-index of 4 for DESMOND BAYONG. These bibliometric indicators provide quantitative information about the researcher’s indexed publication record and citation activity. [1]

Award Suitability

The Best Paper Award recognizes scholarly work selected for its relevance and contribution within its respective research area. DESMOND BAYONG’s recognized paper aligns with the business and accounting dimensions of the award through its examination of CEO power and environmental accounting disclosure in emerging economies.

Conclusion

DESMOND BAYONG is recognized with the Best Paper Award for research in the field of Business. The recognized paper, “CEO Power and Environmental Accounting Disclosure: Comparative Evidence From Emerging Economies,” examines an important relationship between corporate leadership and environmental accounting disclosure within emerging economies.

External Links

References

  1. Elsevier. (n.d.). Scopus author details: DESMOND BAYONG, Author ID 59674838400. Scopus.
    https://www.scopus.com/pages/authors/59674838400
  2. ORCID. (n.d.). ORCID research profile: DESMOND BAYONG.
    https://orcid.org/0009-0001-1145-9162
  3. Best Paper Awards. Best Paper Awards official website.
    https://bestpaperawards.com/

Abdelkader Mohamed Sghaier Derbali | Economics | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Abdelkader Mohamed Sghaier Derbali
Affiliation Department of Administrative and Financial Sciences, Applied College, Taibah University
Country Saudi Arabia
Scopus ID 57886775600
Documents 86
Citations 866
h-index 15
Subject Area Economics
Event Best Paper Awards
Award Best Paper Award
ORCID 0000-0003-4098-3120

Abdelkader Mohamed Sghaier Derbali

Abdelkader Mohamed Sghaier Derbali of the Department of Administrative and Financial Sciences, Applied College, Taibah University, Saudi Arabia is recognized with the Best Paper Award for research excellence in the field of Economics. The awarded research, titled “Modeling the Nexus Between Climate Risk, Energy Consumption, and Financial Market Performance in Emerging Countries,” examines the interconnected relationships among climate risk, energy consumption, and financial market performance in emerging economies.

Abstract

This article recognizes Abdelkader Mohamed Sghaier Derbali for receiving the Best Paper Award in recognition of research excellence in economics. The awarded research, titled “Modeling the Nexus Between Climate Risk, Energy Consumption, and Financial Market Performance in Emerging Countries,” focuses on the interconnected dimensions of climate risk, energy consumption, and financial market performance. By examining these relationships in emerging countries, the research contributes to broader discussions concerning environmental risk, energy economics, financial markets, and sustainable economic development.

Keywords

Climate Risk, Energy Consumption, Financial Market Performance, Emerging Countries, Environmental Economics, Energy Economics, Financial Markets, Sustainable Development, Economic Risk, Economics.

Introduction

The awarded paper, “Modeling the Nexus Between Climate Risk, Energy Consumption, and Financial Market Performance in Emerging Countries,” addresses these interconnected issues by examining the relationship between climate risk, energy consumption, and financial market performance within emerging economies. The research provides an economic perspective on how environmental and energy-related factors can be considered alongside financial market dynamics.

Research Profile

Abdelkader Mohamed Sghaier Derbali is affiliated with the Department of Administrative and Financial Sciences, Applied College, Taibah University, Saudi Arabia. The researcher is associated with the subject area of Economics. The provided Scopus profile records 86 documents, 866 citations, and an h-index of 15. The Scopus Author ID is 57886775600, while the researcher’s ORCID identifier is 0000-0003-4098-3120.

Research Contributions

The awarded publication contributes to economics research by bringing together three important dimensions: climate risk, energy consumption, and financial market performance. Its focus on emerging countries provides a relevant economic context for studying the interaction between environmental challenges, energy use, and financial market conditions.

Research Impact

The provided academic profile records 86 documents, 866 citations, and an h-index of 15 for Abdelkader Mohamed Sghaier Derbali. These indicators demonstrate an established body of indexed research and citation impact within the researcher’s academic profile.

The awarded research addresses issues of broad relevance to emerging economies, particularly the relationship between climate-related risks, energy consumption, and financial markets. Its focus can contribute to academic discussions concerning sustainable economic development, environmental risk management, energy policy, and financial market resilience.

Award Suitability

The Best Paper Award recognizes research demonstrating academic quality, originality, relevance, and meaningful contribution to its respective field. Abdelkader Mohamed Sghaier Derbali’s awarded research aligns with these objectives through its examination of the relationship between climate risk, energy consumption, and financial market performance in emerging countries.

Conclusion

Abdelkader Mohamed Sghaier Derbali’s research represents a contribution to the field of Economics, particularly in the study of climate risk, energy consumption, and financial market performance. The awarded publication, “Modeling the Nexus Between Climate Risk, Energy Consumption, and Financial Market Performance in Emerging Countries,” provides a focused examination of these interconnected economic and environmental dimensions within emerging countries.

External Links

References

  1. Scopus Author Profile: Abdelkader Mohamed Sghaier Derbali, Author ID 57886775600.
    Scopus. https://www.scopus.com/pages/authors/57886775600
  2. ORCID Research Profile: Abdelkader Mohamed Sghaier Derbali.
    ORCID. https://orcid.org/0000-0003-4098-3120
  3. Best Paper Awards.
    https://bestpaperawards.com/

Donghan Li | Materials Science | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Donghan Li
Affiliation Shenyang University of Chemical Technology; Liaoning Key Laboratory of Polymer Materials Application Technology
Country China
Scopus ID 57189616692
Documents 48
Citations 596
h-index 14
Subject Area Materials Science
Event Best Paper Awards
Award Best Paper Award

Donghan Li

Donghan Li of Shenyang University of Chemical Technology, China, is recognized with the Best Paper Award for research contributions in materials science, particularly in the development of functional polymeric gels and advanced biomass-derived materials. This profile highlights the researcher’s academic record and the awarded publication titled “From Biomass to Functional Gels: Multiscale Topology Reconstruction and High-Performance Applications.”

Abstract

This article recognizes Donghan Li for receiving the Best Paper Award in recognition of research excellence in materials science. The awarded research, titled “From Biomass to Functional Gels: Multiscale Topology Reconstruction and High-Performance Applications,” addresses the development of functional gels derived from biomass and focuses on multiscale topology reconstruction and high-performance applications. The work represents a research direction connecting biomass resources, functional polymer materials, structural design, and advanced material applications.

Keywords

Biomass-Derived Materials, Functional Gels, Polymer Materials, Multiscale Topology, Topology Reconstruction, High-Performance Gels, Sustainable Materials, Materials Science, Functional Polymer Networks, Advanced Materials.

Introduction

The development of sustainable and high-performance materials has become an important direction in modern materials science. Biomass provides an abundant source of renewable materials that can be transformed into functional polymeric structures and advanced gel systems. Functional gels are particularly important because their three-dimensional networks can be engineered to provide specialized mechanical, chemical, physical, and application-oriented properties.

Research Profile

Donghan Li is affiliated with Shenyang University of Chemical Technology and the Liaoning Key Laboratory of Polymer Materials Application Technology in China. The researcher’s subject area is Materials Science. The available profile records 48 documents, 596 citations, and an h-index of 14. These bibliometric indicators demonstrate an established publication record and significant academic visibility within the research field.

Research Contributions

The awarded publication, “From Biomass to Functional Gels: Multiscale Topology Reconstruction and High-Performance Applications,” contributes to materials science by examining how biomass-derived resources can be transformed into functional gel materials. The research emphasizes multiscale topology reconstruction as an important approach for controlling material architecture and improving functional performance.

Research Impact

The academic profile of Donghan Li records 596 citations across 48 documents, with an h-index of 14. These indicators demonstrate substantial scholarly engagement with the researcher’s published work and establish a strong research presence within materials science.

Award Suitability

The Best Paper Award recognizes research demonstrating academic quality, technical relevance, originality, and meaningful contribution to its respective field. Donghan Li’s awarded research aligns with these objectives through its focus on biomass-derived functional gels, multiscale topology reconstruction, and high-performance material applications.

Conclusion

Donghan Li’s research represents a valuable contribution to the field of Materials Science, particularly in the area of biomass-derived functional polymer materials and advanced gel systems. The awarded publication, “From Biomass to Functional Gels: Multiscale Topology Reconstruction and High-Performance Applications,” highlights the importance of multiscale structural design in developing high-performance functional gels.

External Links

References

  1. Scopus Author Profile: Donghan Li, Author ID 57189616692.
    Scopus. https://www.scopus.com/pages/authors/57189616692
  2. ORCID Research Profile: Donghan Li.
    ORCID: https://orcid.org/0000-0003-1058-9552
  3. Best Paper Awards.
    https://bestpaperawards.com/

Shui Pang | Power electronics | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Shui Pang
Affiliation Tianjin University
Country China
Scopus ID 58018126000
Documents 21
Citations 188
h-index 6
Subject Area Power Electronics
Event Best Paper Awards
Award Best Paper Award

Shui Pang

Shui Pang of Tianjin University, China, is recognized with the Best Paper Award for research contributions in power electronics and wireless power transfer technology. This profile highlights the researcher’s academic record and the awarded publication titled “High efficiency three-dimensional wireless power transfer system using cylindrical transmitting coil.”

Abstract

This article recognizes Shui Pang for receiving the Best Paper Award in recognition of research excellence in power electronics and wireless power transfer technology. The awarded research, titled “High efficiency three-dimensional wireless power transfer system using cylindrical transmitting coil,” focuses on the development of an efficient three-dimensional wireless power transfer system based on a cylindrical transmitting coil. The work represents an important research direction in wireless power transfer, with potential relevance to efficient energy transmission and advanced power-electronic systems.

Keywords

Wireless Power Transfer, Three-Dimensional Wireless Power Transfer, Cylindrical Transmitting Coil, Power Electronics, Wireless Energy Transfer, High-Efficiency Power Transfer, Electromagnetic Coupling, Energy Transmission.

Introduction

Wireless power transfer is an important research area within modern power electronics, enabling electrical energy to be transferred without conventional wired connections. Improvements in transfer efficiency, spatial flexibility, coil configuration, and system design are essential for expanding the practical applications of wireless energy systems. Research into three-dimensional wireless power transfer can contribute to more flexible energy-transfer arrangements by addressing the limitations associated with conventional planar configurations.

Research Profile

Shui Pang is affiliated with Tianjin University, China, and conducts research in the field of Power Electronics. The available research profile records 21 documents, 188 citations, and an h-index of 6. These bibliometric indicators demonstrate an established publication record and measurable academic influence within the researcher’s field.

Research Contributions

The awarded publication, “High efficiency three-dimensional wireless power transfer system using cylindrical transmitting coil,” contributes to wireless power transfer research by investigating a cylindrical transmitting-coil configuration for three-dimensional energy transmission. The study focuses on improving the efficiency and flexibility of wireless power transfer systems through an alternative coil geometry.

Research Impact

The academic profile of Shui Pang records 188 citations across 21 documents, with an h-index of 6. These metrics indicate that the researcher’s publications have received substantial attention within the scientific literature. The awarded research adds to this body of work by addressing high-efficiency three-dimensional wireless power transfer, an area with continuing relevance to modern power-electronic and energy-transfer technologies.

Award Suitability

The Best Paper Award recognizes research that demonstrates academic quality, technical relevance, originality, and meaningful contribution to its respective field. Shui Pang’s research aligns with these objectives through its focus on high-efficiency three-dimensional wireless power transfer and the application of a cylindrical transmitting coil.

Conclusion

Shui Pang’s research represents a valuable contribution to the field of power electronics, particularly in the area of wireless power transfer. The awarded publication, “High efficiency three-dimensional wireless power transfer system using cylindrical transmitting coil,” explores an innovative three-dimensional approach to wireless energy transmission. With 21 documents, 188 citations, and an h-index of 6, the research profile demonstrates meaningful academic activity and impact. The Student Research Paper Award recognizes this contribution and highlights the importance of continued research into efficient and flexible wireless power-transfer technologies.

External Links

References

  1. Scopus Author Profile: Shui Pang, Author ID 58018126000.
    Scopus. https://www.scopus.com/pages/authors/58018126000
  2. ORCID Research Profile: Shui Pang.
    ORCID. https://orcid.org/0000-0002-7477-1436

Fei HE | Engineering | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Fei He
Affiliation Anhui University of Technology
Country China
Subject Area Engineering
Event Best Paper Awards
Research Gate Fei-He-21

Fei He

Fei He of Anhui University of Technology, China, is recognized in connection with the Best Paper Award for research concerning machine vision and its application to steelmaking processes. The associated publication, “Advances in the Application of Machine Vision in Steelmaking Processes,” presents a review of machine-vision technologies used across multiple stages of steel production, including hot metal pretreatment, converter steelmaking, secondary refining, and continuous casting. The article was published in steel research international, volume 97, issue 4, pages 1813–1830, in 2026, and was first published online on 8 November 2025. The article has DOI 10.1002/srin.202500769. [1]

Abstract

The Best Paper Award recognition highlights research by Fei He and co-authors on the application of machine vision within steelmaking processes. The recognized review examines the development of machine-vision hardware and analytical algorithms, covering the progression from traditional image-processing techniques and machine learning to contemporary deep-learning approaches. It further surveys applications across hot metal pretreatment, converter steelmaking, secondary refining, continuous casting, and related steel-production operations. The publication identifies machine vision as a technological component supporting process optimization, abnormal-condition prediction, product classification and grading, and increased automation in steel manufacturing. [1]

Keywords

Machine Vision, Steelmaking, Artificial Intelligence, Deep Learning, Machine Learning, Image Processing, Intelligent Steelmaking, Converter Steelmaking, Continuous Casting, Secondary Refining, Hot Metal Pretreatment, Industrial Automation, Metallurgical Engineering, Digital Twin.

Introduction

Machine vision has become an increasingly important technology in industrial automation because it enables visual information to be acquired and processed for monitoring, classification, measurement, and decision support. In steelmaking, where production involves high temperatures, complex physical environments, continuous material movement, and demanding quality requirements, machine-vision systems can provide additional sources of information for process monitoring and control. The recognized publication examines the development and application of these systems throughout the steelmaking production chain. [1]

Research Profile

Fei He is affiliated with Anhui University of Technology in China and is associated with research in engineering and metallurgical applications of computational and machine-vision technologies. The recognized publication lists Fei He as a corresponding author and identifies the School of Metallurgical Engineering at Anhui University of Technology as the institutional affiliation. [1]

Research Contributions

The principal contribution of the recognized publication is its systematic overview of machine-vision development in steelmaking. The authors describe the evolution from conventional image-processing methods to machine-learning and deep-learning algorithms and examine how these technologies can be incorporated into industrial steel-production environments. [1]

Publications

The principal publication associated with this recognition is a peer-reviewed review article published in steel research international:

  • Wang, X., He, F., Xu, C., Wu, T., Zhuang, X., Zhang, R., Xie, W., Liu, Y., & Li, H. (2026). Advances in the Application of Machine Vision in Steelmaking Processes. steel research international, 97(4), 1813–1830. DOI: https://doi.org/10.1002/srin.202500769. [1]

Research Impact

The recognized publication contributes to research on intelligent steel manufacturing by consolidating evidence concerning the use of machine vision across different stages of steel production. By connecting visual sensing with machine-learning and deep-learning algorithms, the review provides a structured account of how visual information can support monitoring, prediction, classification, and automation. [1]

Award Suitability

The Best Paper Award recognition is associated with scholarly work demonstrating relevance, methodological organization, research value, and contribution to an academic or professional field. The publication associated with Fei He addresses a clearly defined engineering topic and provides a broad review of machine-vision technologies and their applications within steelmaking. [1]

Conclusion

Fei He is associated with engineering research at Anhui University of Technology, with the recognized publication focusing on machine vision and intelligent steelmaking. The article provides a comprehensive review of the development of machine-vision hardware and algorithms and examines their applications throughout several stages of steel production. [1]

External Links

References

    1. Wang, X., He, F., Xu, C., Wu, T., Zhuang, X., Zhang, R., Xie, W., Liu, Y., & Li, H. (2026). Advances in the Application of Machine Vision in Steelmaking Processes. steel research international, 97(4), 1813–1830. First published online 8 November 2025. DOI: https://doi.org/10.1002/srin.202500769.

Mandara SM | Business | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Mandara SM
Affiliation School of Commerce and Management, SVU
Country India
Subject Area Business
Event Best Paper Awards
ORCID 0009-0006-6234-7618

Mandara SM

Mandara SM of the School of Commerce and Management, Shri Venkateshwara University (SVU), India, is recognized in connection with the Best Paper Award for research examining work–life balance within peripheral and informal labour markets. The recognized publication, “Reconstructing Work–Life Balance in Peripheral Labour Markets: Structural, Sectoral, and Gendered Realities of Informal Employment in Chikmagalur District,” investigates work–life balance across informal employment sectors in Chikmagalur District, Karnataka, with attention to structural, sectoral, occupational, and gender-related conditions. The article was published in Advanced International Journal for Research, Volume 6, Issue 6, in 2025, and is identified with DOI 10.63363/aijfr.2025.v06i06.2270. [1]

Abstract

The recognized research examines work–life balance among workers employed in informal sectors of Chikmagalur District, Karnataka. The study considers five major areas of informal employment—construction, agriculture, textiles, hotels, and department stores—and investigates how working hours, job security, physical strain, income stability, and gendered responsibilities shape workers’ ability to maintain work–life balance. It uses a mixed-method approach incorporating structured surveys and focus group discussions to examine the experiences of informal workers. The reported findings indicate substantial sectoral differences, with construction and agriculture associated with more difficult work–life balance conditions, while textile and hotel employment showed comparatively more balanced outcomes. Gender differences were also reported, with women experiencing additional pressures arising from the combination of paid employment and domestic responsibilities. [1]

Keywords

Work-Life Balance, Informal Labour, Peripheral Labour Markets, Gendered Employment, Informal Economy, Occupational Stress, Labour Welfare, Employment Conditions, Chikmagalur District, India.

Introduction

Work–life balance is an important dimension of employment quality because working conditions influence how individuals allocate time between paid employment, household responsibilities, rest, and other aspects of personal life. In informal labour markets, these relationships may be particularly complex because employment can be characterized by variable working hours, limited employment security, fluctuating income, and comparatively fewer formal workplace protections. The recognized study focuses on these conditions within the context of Chikmagalur District in Karnataka, India. [1]

Research Profile

Mandara SM is affiliated with the School of Commerce and Management at Shri Venkateshwara University and is associated with research in Business and related areas of commerce and management. The supplied recognition information identifies India as the researcher’s country and provides ORCID identifier 0009-0006-6234-7618. Scopus identification and bibliometric values for documents, citations, and h-index were not supplied with the award profile and are therefore not stated as verified metrics on this page.

Research Contributions

The principal contribution of the recognized study is its examination of work–life balance within peripheral and informal labour markets at a district level. Rather than treating informal employment as a homogeneous category, the research compares conditions across construction, agriculture, textiles, hotels, and department stores. This sectoral approach allows differences in work intensity, employment security, income conditions, and scheduling practices to be considered in relation to workers’ reported work–life balance. [1]

The study employs a mixed-method research design combining structured surveys and focus group discussions. This approach permits quantitative assessment of employment-related factors while also incorporating workers’ experiences and perceptions. The publication reports that working hours, job security, physical strain, income stability, and gendered responsibilities are relevant factors in understanding differences in work–life balance among informal workers. [1]

Publications

The principal publication associated with this recognition is the following peer-reviewed journal article:

  • Mandara, S. M., & Sahoo, S. (2025). Reconstructing Work–Life Balance in Peripheral Labour Markets: Structural, Sectoral, and Gendered Realities of Informal Employment in Chikmagalur District. Advanced International Journal for Research, 6(6). DOI: https://doi.org/10.63363/aijfr.2025.v06i06.2270. [1]

Research Impact

The research contributes to the study of informal employment by providing a localized assessment of work–life balance in Chikmagalur District. Its focus on several occupational sectors provides a basis for comparing the employment conditions experienced by workers in different parts of the informal economy. Such sector-specific analysis can help distinguish common labour-market pressures from conditions that are more closely associated with particular forms of employment. [1]

Award Suitability

The Best Paper Award recognizes scholarly work demonstrating research quality, methodological clarity, relevance, and a meaningful contribution to its field. The publication associated with Mandara SM addresses a clearly defined issue in business and labour research by investigating work–life balance among informal workers in a specific regional labour market. Its examination of structural, sectoral, and gendered dimensions provides a multidimensional framework for understanding the subject. [1]

Conclusion

Mandara SM’s research profile, as presented for the Best Paper Award, reflects scholarly activity in Business and related areas of labour and management research. The recognized publication examines work–life balance among informal workers in Chikmagalur District and considers the structural, sectoral, occupational, and gendered factors that influence employment experiences. [1]

External Links

References

  1. Mandara, S. M., & Sahoo, S. (2025). Reconstructing Work–Life Balance in Peripheral Labour Markets: Structural, Sectoral, and Gendered Realities of Informal Employment in Chikmagalur District. Advanced International Journal for Research, 6(6), published December 3, 2025. DOI: https://doi.org/10.63363/aijfr.2025.v06i06.2270.
  2. Advanced International Journal for Research. (2025). Reconstructing Work–Life Balance in Peripheral Labour Markets: Structural, Sectoral, and Gendered Realities of Informal Employment in Chikmagalur District. Publication record and article information. Publisher Article Page.
  3. Advanced International Journal for Research. (2025). Reconstructing Work–Life Balance in Peripheral Labour Markets: Structural, Sectoral, and Gendered Realities of Informal Employment in Chikmagalur District. Full-text publication record. Publication PDF.