Best Researcher Award

Christos Lemonakis — Hellenic Mediterranean University, Greece

Christos Lemonakis
Affiliation Hellenic Mediterranean University
Country Greece
Scopus ID 55780698800
Documents 63
Citations 516
h-index 13
Subject Area Decision Sciences
Event International Research Excellence Awards – Book of Award
ORCID ID 0000-0002-9024-0969

Christos Lemonakis is an academic researcher affiliated with the Hellenic Mediterranean University in Greece whose published work spans business administration, management, financial analysis, operations research, sustainability, and related decision-oriented disciplines. Public scholarly records associate his research with topics including efficiency measurement, competitiveness, corporate governance, environmental, social and governance (ESG) analysis, banking, machine learning, and multiple-criteria decision-making. [1]

Abstract

The academic profile of Christos Lemonakis reflects research situated at the intersection of management, finance, operations research, analytics, and decision sciences. His scholarly record includes studies addressing organizational efficiency, financial performance, corporate governance, ESG factors, regional development, banking, and analytical approaches to managerial decision-making. [1] His publications also demonstrate engagement with quantitative and multicriteria approaches for evaluating complex economic and organizational problems. [2]

Keywords

Decision Sciences, Operations Research, Financial Analytics, Business Performance, Corporate Governance, ESG Analysis, Multiple-Criteria Decision Making

Introduction

Decision Sciences brings together analytical methods that support structured decision-making under complexity and uncertainty. Within this broad field, Lemonakis’s research record includes applications of quantitative analysis to banking, business efficiency, regional performance, corporate reporting, governance, and sustainability. RePEc records identify his affiliation with the Hellenic Mediterranean University and list journal articles, working papers, book chapters, and edited scholarly work. [1]

Research Profile

Lemonakis’s research profile is multidisciplinary. Earlier work includes banking efficiency, financial distress, competitiveness, enterprise resource planning, auditing, and narrative disclosure. Later research extends into ESG performance, urban hierarchy, regional analysis, sustainable development, and the use of analytical and computational methods in decision contexts. [1] His publication record also includes work explicitly connecting machine learning techniques with decision-making in credit-card portfolio analysis. [3]

Research Contributions

A notable characteristic of the research is the application of analytical frameworks to practical organizational and financial problems. Research involving multiple-criteria approaches has addressed business and regional performance, while other studies have investigated efficiency and risk-related questions in financial institutions. A separate stream examines ESG and corporate performance, reflecting the increasing importance of non-financial factors in contemporary strategic decision-making. [4]

Publications

Publicly indexed bibliographic records list a range of journal articles and book chapters by Lemonakis. Examples include research on regional performance using shift-share analysis and multicriteria decision-making, the impact of ECB non-regular operations on bank credit, urban hierarchy in Greece, and ESG-related financial analysis. [1]

Research Impact

The available bibliographic evidence indicates that Lemonakis’s work has contributed to discussions across operations research, business, finance, management, and sustainability. RePEc records identify publications in journals including Operational Research, The Annals of Regional Science, and Sustainability. [1]

Award Suitability

Based on the supplied bibliometric profile and publicly documented research record, Christos Lemonakis presents a research portfolio relevant to the Decision Sciences category. The combination of operations research, multicriteria analysis, financial analytics, machine learning, governance, and sustainability provides a multidisciplinary basis for consideration for a research recognition. [1]

Conclusion

Christos Lemonakis’s research profile reflects sustained engagement with analytical and managerial problems that are central to Decision Sciences. His work connects quantitative evaluation with practical questions involving efficiency, finance, governance, regional development, sustainability, and organizational performance. [1]

References

  1. RePEc. (2020). Christos Lemonakis — author profile and research output. Research Papers in Economics.
    https://ideas.repec.org/f/ple1055.html
  2. Lemonakis, C., et al. (2022). Enhancing Public Health and SDG 3 Through Sustainable Agriculture and Tourism.
    https://doi.org/10.3390/su17146253
  3. Sariannidis, N., Papadakis, S., Garefalakis, A., Lemonakis, C., & Tsioptsia, K.-A. (2020). Default avoidance on credit card portfolios using accounting, demographical and exploratory factors: decision making based on machine learning (ML) techniques. Annals of Operations Research, 294, 715–739.
    https://doi.org/10.1007/s10479-019-03188-0
  4. Makridou, G., Doumpos, M., & Lemonakis, C. (2024). Relationship between ESG and corporate financial performance in the energy sector: Empirical evidence from European companies. International Journal of Energy Sector Management.
    https://doi.org/10.1108/IJESM-01-2023-0012
  5. Lemonakis, C., Alexopoulos, G., Garefalakis, A., & Garefalakis, S. (2024). Trends and new elements in urban hierarchy research: the Greek paradigm. The Annals of Regional Science, 72(2), 335–354.
    https://doi.org/10.1007/s00168-022-01202-1
  6. Business Perspectives. (2017). The effect of Corporate Governance Information (CGI) on banks’ reporting performance. Investment Management and Financial Innovations, 14(2), 63–70.
    https://doi.org/10.21511/imfi.14(2).2017.06
Christos Lemonakis | Decision Sciences | Best Researcher Award

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