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Searching for an effective accounting-based score of firm performance: a comparative study between different synthesis techniques

Author

Listed:
  • Bruno Ricca

    (University of Messina)

  • Massimiliano Ferrara

    (ICRIOS, Bocconi University)

  • Salvatore Loprevite

    (University “Dante Alighieri”)

Abstract

The need for an effective comprehensive financial performance score of the firm derived from accounting-based variables is increasingly felt in the stream of empirical research on relationships between financial performance and other dimensions of corporate performance. The solution to this problem must be pursued in literature on statistical-mathematical techniques to synthesize financial performance through financial ratios derived from financial statements. Until now, however, studies have mainly focused on mathematical modeling and ranking of companies, without using appropriate benchmarks to verify the relevance of the scores obtained and to establish, from a comparative perspective between different techniques, which one provides the assessment that best summarizes financial performance. To make a contribution to this research gap, using a sample of 845 companies observed from 2014 to 2020, we compared Data Envelopment Analysis and Principal Component Analysis with two other applications based on new methodologies derived from the Multi-Criteria Decision Methods: The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Grey Relational Analysis. We developed the 4 techniques on a set of 9 financial ratios expressive of profitability and operating efficiency, solvency, and liquidity, and Tobin's q was used as a benchmark to compare the results provided by the 4 techniques and identify the best performing one. We found that TOPSIS is the most effective methodology for synthesizing an effective accounting-based score of the firm’s financial performance.

Suggested Citation

  • Bruno Ricca & Massimiliano Ferrara & Salvatore Loprevite, 2023. "Searching for an effective accounting-based score of firm performance: a comparative study between different synthesis techniques," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3575-3602, August.
  • Handle: RePEc:spr:qualqt:v:57:y:2023:i:4:d:10.1007_s11135-022-01522-6
    DOI: 10.1007/s11135-022-01522-6
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    as
    1. Sueyoshi, Toshiyuki & Goto, Mika, 2009. "Methodological comparison between DEA (data envelopment analysis) and DEA-DA (discriminant analysis) from the perspective of bankruptcy assessment," European Journal of Operational Research, Elsevier, vol. 199(2), pages 561-575, December.
    2. Amin Babaei Falah & Morteza Sardari, 2015. "A novel application of grey principal component analysis to determine stockholder’s approach towards financial ratios," Business and Economic Horizons (BEH), Prague Development Center, vol. 11(1), pages 41-50, April.
    3. Jörg Blasius & John Gower, 2005. "Multivariate Prediction with Nonlinear Principal Components Analysis: Application," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(4), pages 373-390, August.
    4. Berna Bulgurcu, 2013. "Financial Performance Ranking of the Automotive Industry Firms in Turkey: Evidence from an Entropy-Weighted Technique," International Journal of Economics and Financial Issues, Econjournals, vol. 3(4), pages 844-851.
    5. Xu, Xiaozhan, 2004. "A note on the subjective and objective integrated approach to determine attribute weights," European Journal of Operational Research, Elsevier, vol. 156(2), pages 530-532, July.
    6. Chang, Kuo-Ping & Guh, Yeah-Yuh, 1991. "Linear production functions and the data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 52(2), pages 215-223, May.
    7. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    10. John Gower & Jörg Blasius, 2005. "Multivariate Prediction with Nonlinear Principal Components Analysis: Theory," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(4), pages 359-372, August.
    11. Dan Daugaard, 2020. "Emerging new themes in environmental, social and governance investing: a systematic literature review," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(2), pages 1501-1530, June.
    12. N Adler & B Golany, 2002. "Including principal component weights to improve discrimination in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 985-991, September.
    13. Chaang-Yung Kung, 2006. "Using Fuzzy Sets and Grey Decision-Making to Construct the Performance Evaluation Model of Firm’s Outsourcing Management – A Case Study of Avionics Manufacturer in Taiwan," Quality & Quantity: International Journal of Methodology, Springer, vol. 40(4), pages 577-593, August.
    14. Maria Silva Portela & Pedro Borges & Emmanuel Thanassoulis, 2003. "Finding Closest Targets in Non-Oriented DEA Models: The Case of Convex and Non-Convex Technologies," Journal of Productivity Analysis, Springer, vol. 19(2), pages 251-269, April.
    15. Lin, Woon Leong & Law, Siong Hook & Ho, Jo Ann & Sambasivan, Murali, 2019. "The causality direction of the corporate social responsibility – Corporate financial performance Nexus: Application of Panel Vector Autoregression approach," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 401-418.
    16. Emmanuel Adegbite & Yilmaz Guney & Frank Kwabi & Suleiman Tahir, 2019. "Financial and corporate social performance in the UK listed firms: the relevance of non-linearity and lag effects," Review of Quantitative Finance and Accounting, Springer, vol. 52(1), pages 105-158, January.
    17. Zhu, Joe, 1998. "Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities," European Journal of Operational Research, Elsevier, vol. 111(1), pages 50-61, November.
    18. Chin-Tsai Lin & Meng-Chuan Tsai, 2010. "Location choice for direct foreign investment in new hospitals in China by using ANP and TOPSIS," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(2), pages 375-390, February.
    19. Gillan, Stuart L. & Koch, Andrew & Starks, Laura T., 2021. "Firms and social responsibility: A review of ESG and CSR research in corporate finance," Journal of Corporate Finance, Elsevier, vol. 66(C).
    20. Muhammad Azeem Qureshi & Minhas Akbar & Ahsan Akbar & Petra Poulova, 2021. "Do ESG Endeavors Assist Firms in Achieving Superior Financial Performance? A Case of 100 Best Corporate Citizens," SAGE Open, , vol. 11(2), pages 21582440211, June.
    21. Feng, Cheng-Min & Wang, Rong-Tsu, 2000. "Performance evaluation for airlines including the consideration of financial ratios," Journal of Air Transport Management, Elsevier, vol. 6(3), pages 133-142.
    22. Enrico Ciavolino & Antonio Calcagnì, 2014. "A generalized maximum entropy (GME) approach for crisp-input/fuzzy-output regression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3401-3414, November.
    23. Marco Taliento & Christian Favino & Antonio Netti, 2019. "Impact of Environmental, Social, and Governance Information on Economic Performance: Evidence of a Corporate ‘Sustainability Advantage’ from Europe," Sustainability, MDPI, vol. 11(6), pages 1-26, March.
    24. Zhou, P. & Ang, B.W. & Poh, K.L., 2007. "A mathematical programming approach to constructing composite indicators," Ecological Economics, Elsevier, vol. 62(2), pages 291-297, April.
    25. Miguel Arce & Araceli Mora, 2002. "Empirical evidence of the effect of European accounting differences on the stock market valuation of earnings and book value," European Accounting Review, Taylor & Francis Journals, vol. 11(3), pages 573-599.
    26. Ayşe İrem Keskin & Banu Dincer & Caner Dincer, 2020. "Exploring the Impact of Sustainability on Corporate Financial Performance Using Discriminant Analysis," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    27. Sarkis, Joseph & Cordeiro, James J., 2001. "An empirical evaluation of environmental efficiencies and firm performance: Pollution prevention versus end-of-pipe practice," European Journal of Operational Research, Elsevier, vol. 135(1), pages 102-113, November.
    28. Bruna, Maria Giuseppina & Loprevite, Salvatore & Raucci, Domenico & Ricca, Bruno & Rupo, Daniela, 2022. "Investigating the marginal impact of ESG results on corporate financial performance," Finance Research Letters, Elsevier, vol. 47(PA).
    29. Wu, Cheng-Ru & Lin, Chin-Tsai & Tsai, Pei-Hsuan, 2010. "Evaluating business performance of wealth management banks," European Journal of Operational Research, Elsevier, vol. 207(2), pages 971-979, December.
    30. Tone, Kaoru & Chang, Tsung-Sheng & Wu, Chen-Hui, 2020. "Handling negative data in slacks-based measure data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 282(3), pages 926-935.
    31. Adler, Nicole & Golany, Boaz, 2001. "Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe," European Journal of Operational Research, Elsevier, vol. 132(2), pages 260-273, July.
    32. Steven F. Cahan & Charl De Villiers & Debra C. Jeter & Vic Naiker & Chris J. Van Staden, 2016. "Are CSR Disclosures Value Relevant? Cross-Country Evidence," European Accounting Review, Taylor & Francis Journals, vol. 25(3), pages 579-611, September.
    33. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    34. Lahouel, Béchir Ben & Zaied, Younes Ben & Song, Yaoyao & Yang, Guo-liang, 2021. "Corporate social performance and financial performance relationship: A data envelopment analysis approach without explicit input," Finance Research Letters, Elsevier, vol. 39(C).
    35. Sueyoshi, Toshiyuki & Goto, Mika, 2010. "Measurement of a linkage among environmental, operational, and financial performance in Japanese manufacturing firms: A use of Data Envelopment Analysis with strong complementary slackness condition," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1742-1753, December.
    36. Shang Gao & Fanchen Meng & Zhouyang Gu & Zhiyuan Liu & Muhammad Farrukh, 2021. "Mapping and Clustering Analysis on Environmental, Social and Governance Field a Bibliometric Analysis Using Scopus," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    37. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    38. Loredana Cultrera & Mélanie Croquet & Jérémy Jospin, 2017. "Predicting Bankruptcy of Belgian SMEs: A Hybrid Approach Based on Factorial Analysi," International Business Research, Canadian Center of Science and Education, vol. 10(3), pages 33-41, March.
    39. Batchimeg Bayaraa & Tibor Tarnoczi & Veronika Fenyves, 2020. "Corporate Performance Measurement Using an Integrated Approach - A Mongolian Case," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 16(4), pages 123-134.
    40. Premachandra, I.M. & Chen, Yao & Watson, John, 2011. "DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment," Omega, Elsevier, vol. 39(6), pages 620-626, December.
    41. Ma, Jian & Fan, Zhi-Ping & Huang, Li-Hua, 1999. "A subjective and objective integrated approach to determine attribute weights," European Journal of Operational Research, Elsevier, vol. 112(2), pages 397-404, January.
    42. Nicholas Kaldor, 1966. "Marginal Productivity and the Macro-Economic Theories of Distribution: Comment on Samuelson and Modigliani," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 33(4), pages 309-319.
    43. William C. Brainard & James Tobin, 1968. "Pitfalls in Financial Model-Building," Cowles Foundation Discussion Papers 244, Cowles Foundation for Research in Economics, Yale University.
    44. Jahmane, Abderrahmane & Gaies, Brahim, 2020. "Corporate social responsibility, financial instability and corporate financial performance: Linear, non-linear and spillover effects – The case of the CAC 40 companies," Finance Research Letters, Elsevier, vol. 34(C).
    45. Liliana Nicoleta Simionescu & Dalina Dumitrescu, 2018. "Empirical Study towards Corporate Social Responsibility Practices and Company Financial Performance. Evidence for Companies Listed on the Bucharest Stock Exchange," Sustainability, MDPI, vol. 10(9), pages 1-23, September.
    46. West, Robert Craig, 1985. "A factor-analytic approach to bank condition," Journal of Banking & Finance, Elsevier, vol. 9(2), pages 253-266, June.
    47. Joe Zhu, 2009. "Quantitative Models for Performance Evaluation and Benchmarking," International Series in Operations Research and Management Science, Springer, number 978-0-387-85982-8, September.
    48. Caterina De Lucia & Pasquale Pazienza & Mark Bartlett, 2020. "Does Good ESG Lead to Better Financial Performances by Firms? Machine Learning and Logistic Regression Models of Public Enterprises in Europe," Sustainability, MDPI, vol. 12(13), pages 1-29, July.
    49. Falah, Amin, 2015. "A novel application of grey principal component analysis to determine stockholder’s approach towards financial ratios," Business and Economic Horizons (BEH), Prague Development Center (PRADEC), vol. 11(1), pages 1-10.
    50. Jessop, Alan, 2004. "Minimally biased weight determination in personnel selection," European Journal of Operational Research, Elsevier, vol. 153(2), pages 433-444, March.
    51. Chia Sun, 2014. "Combining grey relation analysis and entropy model for evaluating the operational performance: an empirical study," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1589-1600, May.
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