Impact of the economic crisis on Romagna companies’ profitability and finan-cial risk. A cluster analysis

Journal title MANAGEMENT CONTROL
Author/s Stefania Vignini, Tiziana De Cristofaro
Publishing Year 2018 Issue 2018/3
Language Italian Pages 25 P. 157-181 File size 313 KB
DOI 10.3280/MACO2018-003008
DOI is like a bar code for intellectual property: to have more infomation click here

Below, you can see the article first page

If you want to buy this article in PDF format, you can do it, following the instructions to buy download credits

Article preview

FrancoAngeli is member of Publishers International Linking Association, Inc (PILA), a not-for-profit association which run the CrossRef service enabling links to and from online scholarly content.

As a result of the 2008 global crisis, in 2012 Italy entered an economic recession. Against this backdrop, this work investigates the main profitability and financial risk exposure features of companies in Romagna in 2012-2014. Romagna is an area located in a wealthy region of Italy, Emilia-Romagna, and it is well known for a local system of informal aggregations based on shared socioeconomic links. Thus, using AIDA’s database, we analyse the top 100 companies by revenue (excluding financial and holding companies) in the three provinces of Romagna: Forlì-Cesena, Ravenna and Rimini. More in detail, after finding that the trend of the means of six financial ratios has improved in the defined period, with the exception of ROE, the six ratios are used as variables to perform a cluster analysis. In the first analytical step (based on the single-linkage method) companies are shown to mostly gather into a main cluster, although with the presence of several isolated outlier companies. The second step (based on Ward’s method) proposes a more detailed analysis resulting in 4 clusters during the specified period. Over time, clusters change more in terms of their members than in their territorial and/or sectorial composition. Finally, the general recovery trend is confirmed, with two exceptions: (i) a cluster rich of outliers gathering the worst performances and slowly emptying over time; (ii) the most numerous cluster, showing a decreasing trend in the degree of coverage of financial charges. The limitations highlighted in the conclusion suggest the need for further research.

Keywords: Performance, profitability, financial risk, cluster analysis, Romagna.

  1. Altman E.I. (1968), Financial ratios, discriminant analysis and the prediction of corporate bankruptcy, The journal of finance, 23, 4, pp. 589-609.
  2. Antonioli D., Bianchi A., Mazzanti M., Montresor S., Pini P., a cura di (2011), Strategie di innovazione e risultati economici: un’indagine sulle imprese manifatturiere dell’Emilia-Romagna, Milano, FrancoAngeli.
  3. Ausloos M., Bartolacci F., Castellano N.G., Cerqueti R. (2018), Exploring how innovation strategies at time of crisis influence performance: a cluster analysis perspective, Technology Analysis & Strategic Management, 30, 4, pp. 484-497. DOI: 10.1080/09537325.2017.1337889
  4. Barbaranelli C. (2006), Analisi dei dati con SPSS, Vol. II, Milano, Led.
  5. Bartolacci F., Paolini A., Quaranta A.G., Soverchia M. (2017), Performance economiche e ambientali nelle aziende italiane di igiene urbana: prime evidenze empiriche, Management Control, 2, pp. 33-51. DOI: 10.3280/MACO2017-002003
  6. Battilani P., Fauri F. (2009), The rise of a service-based economy and its transformation: seaside tourism and the case of Rimini, Journal of Tourism History, 1, 1, pp. 27-48. DOI: 10.1080/17551820902742756
  7. Beaver W.H. (1966), Financial ratios as predictors of failure, Journal of accounting research, 4, pp. 71-111.
  8. Beaver W.H., Kettler Scholes M. (1970), The association between market determined and accounting determined risk measures, The Accounting Review, 45, 4, pp. 654-682.
  9. Bellamy C. (2011), Principles of methodology: Research design in social science, Sage.
  10. Ben- Zion U. (1978), The investment aspect of nonproduction expenditures: An empirical test, Journal of Economics and Business, pp. 224-229.
  11. Bettis R.A., Mahajan V. (1985), Risk/return performance of diversified firms, Management Science, 31, 7, pp. 785-799.
  12. Bhattacharyya, D. K. (2006), Research methodology, Excel Books India.
  13. Bird R.G., McHugh A.J. (1977), Financial ratios – an empirical study, Journal of Business Finance & Accounting, 4, 1, pp. 29-46.
  14. Borroi M., Minoja M., Sinatra A. (1998), The relationship between cognitive maps, industry complexity and strategies implemented: the case of the Carpi textile-clothing industrial system, Journal of Management and Governance, 2, 3, pp. 233-266.
  15. Bougen P.D., Drury J.C. (1980), UK statistical distributions of financial ratios, 1975, Journal of Business Finance & Accounting, 7, 1, pp. 39-47.
  16. Brunetti G. (1971), Il sistema dei quozienti di bilancio: alcuni caratteri strutturali e funzionali, Milano, Giuffrè.
  17. Canavari M., Ghelfi R., Olson K.D., Rivaroli S. (2007), A comparative profitability analysis of organic and conventional farms in Emilia-Romagna and in Minnesota, in Canavari S., Olson K.D., a cura di, Organic Food, New York, Springer.
  18. Capece G., Cricelli L., Di Pillo F., Levialdi N. (2010), A cluster analysis study based on profitability and financial indicators in the Italian gas retail market, Energy Policy, 3, 7, pp. 3394-3402.
  19. Capece G., Cricelli L., Di Pillo F., Levialdi N. (2012), New regulatory policies in Italy: Impact on financial results, on liquidity and profitability of natural gas retail companies, Utilities Policy, 23, 90-98.
  20. Capon N., Farley J.U., Hoenig S. (1990), Determinants of financial performance: a meta-analysis, Management science, 36, 10, pp. 1143-1159.
  21. Castellano N. (2011), Modelli e misure di performance aziendale: analisi della letteratura e spunti di ricerca, Management Control, 1, pp. 41-63. DOI: 10.3280/MACO2011-001003
  22. Chen K.H., Shirmeda T.A., (1981), An Empirical Analysis of Useful Financial Ratios, in Financial Management, 10, 1, pp. 51-60.
  23. Cinquini L., Miraglia R.A., Giannetti R. (2016), Editoriale. Strumenti di gestione dei costi e misure di performance negli attuali contesti competitivi, Management Control, 2, pp. 5-14. DOI: 10.3280/MACO2016-002001
  24. Creswell J.W. (2009), Research design. Qualitative, quantitative and mixed methods approach, Sage.
  25. Dardac N., Giba A. (2011), Systemic Financial Crises: A Cluster Analysis, European Research Studies, 14, 2, pp. 53-64.
  26. de Lillo A., Argentin G., Lucchini M., Sarti S., Terraneo M., a cura di (2007), Analisi multivariata per le scienze sociali, Pearson Italia.
  27. Deakin, E. (1976), Distributions of financial accounting ratios: some empirical evidence, The Accounting Review, 51, 1, pp. 90-96.
  28. Dolnicar S. (2002), A review of unquestioned standards in using cluster analysis for data-driven market segmentation. Faculty of Commerce-Papers, 273. -- Http://ro.uow.edu.au/commpapers/273.
  29. Ennas M. (2010), Elementi di cluster analysis per la classificazione e il posizionamento nelle ricerche di marketing. -- Http://www.mauroennas.eu/ita/phocadownload/report/01_cluster_analysis.pdf.
  30. Ezzamel M., Mar-Molinero C. (1990), The distributional properties of financial ratios in UK manufacturing companies, Journal of Business Finance & Accounting, 17, 1, pp. 1-29.
  31. Ezzamel M., Mar-Molinero C., Beecher A. (1987), On the distributional properties of financial ratios, Journal of Business Finance & Accounting, 14, 4, pp. 463-481.
  32. Fasone V., Puglisi M. (2017), Misure di performance innovative e modelli di business: il caso delle aziende aeroportuali italiane, Management Control, 2, pp. 89-123. DOI: 10.3280/MACO2017-002005
  33. Foster G. (1978), Financial Statement Analysis, Englewood Cliffs, Prentice-Hall.
  34. Frecka, T.J., Hopwood, W.S. (1983), The effects of outliers on the cross-sectional distributional properties of financial ratios, The Accounting Review, 58, 1, pp. 115-128.
  35. Galeotti M., Garzella S., Fiorentino R., Della Corte G. (2016), The Strategic Intelligence implications for Information Systems, Management Control, 1, pp. 105-123. DOI: 10.3280/MACO2016-001007
  36. Gordon I.R., McCann P. (2000), Industrial clusters: complexes, agglomeration and/or social networks?, Urban studies, 37, 3, pp. 513-532. DOI: 10.1080/0042098002096
  37. Gremillet A. (1979), Les ratio set leur utilisation, Parigi, Les éditions d’organisation.
  38. Griliches Z. (1972), Cost allocation in railroad regulation, The Bell Journal of Economics and Management Science, 3, 1, pp. 26-41.
  39. Gupta M.C., Huefner R.J. (1972), A cluster analysis study of financial ratios and industry characteristics, Journal of Accounting Research, 10, 1, pp. 77-95.
  40. Hall B.H. (1987), The relationship between firm size and firm growth in the U.S. manufacturing sector, Journal of Industrial Economics, 35, pp. 583-605.
  41. Hambrick D.C., Schecter S.M. (1983), Turnaround strategies for mature industrial-product business units, Academy of Management Journal, 26, 2, pp. 231-248.
  42. Harrigan K.R. (1985), An application of clustering for strategic group analysis, Strategic Management Journal, 6, 1, pp. 55-73.
  43. Hopwood W., Mckeown J., Muchler J.F. (1988), The sensitivity of financial distress prediction models to departures from normality, Contemporary Accounting Research, 5, 1, pp. 284-298.
  44. Horrigan J.O. (1965), Some Empirical Bases of Financial Ratio Analysis, The Accounting Review, 40, 3, pp. 558-568.
  45. Horrigan J.O. (1966), The Determination of Long-Term Credit Standing with Financial Ratios, Journal of Accounting Research, 4, pp. 44-62.
  46. Istat, Unioncamere, a cura di (2007), L’evoluzione dei sistemi locali in Emilia-Romagna, Bologna, Maggioli.
  47. Kantar E., Keskin M., Deviren B. (2012), Analysis of the effects of the global financial crisis on the Turkish economy, using hierarchical methods, Physica A: Statistical Mechanics and its Applications, 391, 7, pp. 2342-2352.
  48. Karels, G.V., Prakash, A.J. (1987), Multivariate normality and forecasting of business bankruptcy, Journal of Business Finance & Accounting, 14, 4, pp. 573-593.
  49. Ketchen D.J. Jr, Shook C.L. (1996), The application of cluster analysis in strategic management research: an analysis and critique, Strategic Management Journal, 17, 6, pp. 441-458.
  50. Lev B., Sunder S. (1979), Methodological issues in the use of financial ratios, Journal of Accounting and Economics, 1, 3, pp. 187-210.
  51. Marchi L. (2014), Nuove prospettive di valutazione delle performance nelle aziende di servizi, Management Control, 1, pp. 5-8. DOI: 10.3280/MACO2014-001001
  52. McLeay S. (1986b), Student’s t and the distribution of financial ratios, Journal of Business Finance & Accounting, 13, 2, pp. 209-222.
  53. McLeay S. (1986a), The ratio of means, the mean of ratios and other benchmarks, Finance, Journal of the French Finance Society, 7, 1, pp. 75-93.
  54. McLeay S., Omar S. (2000), The sensitivity of prediction models to the non-normality of bounded and unbounded financial ratios, British Accounting Review, 32, 2, pp. 213-230.
  55. Morosini P. (2004), Industrial clusters, knowledge integration and performance, World development, 32, 2, pp. 305-326.
  56. Nerlove M. (1968), Factors affecting differences among rates of return on investments in individual common stocks, The Review of Economics and Statistics, 50, 3, pp. 312-331.
  57. O’Connor M.C. (1973), On the Usefulness of Financial Ratios to Investors in Common Stock, The Accounting Review, 48, 2, pp. 339-352.
  58. Ohlson J. (1980), Financial ratios and probabilistic prediction of bankruptcy, Journal of Accounting Research, 18, 1, pp. 109-131.
  59. Onida P. (1947), Le discipline economico-aziendali, Milano, Giuffrè.
  60. Paganelli O. (1991), Analisi di bilancio. Indici e flussi, Torino, Utet.
  61. Paoloni M., Celli M., (2018), Crisi delle PMI e strumenti di warning. Un test di verifica nel settore manifatturiero, Management Control, 2, pp. 85-106. DOI: 10.3280/MACO2018-002005
  62. Pinches G.E., Eubank A.A., Mingo K.A., Caruthers J.K. (1975), The hierarchical classification of financial ratios, Journal of Business Research, 3, 4, pp. 295-310.
  63. Pivoňka, T., Löster, T. (2013), Cluster Analysis as a Tool of Evaluating Clusters of the EU Countries before and during Global Financial Crisis from the Perspective of the Labor Market. Intellectual Economics, 7, 4, pp. 411-425. DOI: 10.13165/IE-13-7-4-01
  64. Punj G., Stewart D.W. (1983), Cluster analysis in marketing research: review and suggestions for application, Journal of marketing research, 20, 2, pp. 134-148.
  65. Pyke F., Becattini G., Sengenberger W., a cura di (1990), Industrial districts and inter-firm cooperation in Italy, Ginevra, IILS.
  66. Rhys H., Tippett M. (1993), On the ‘Steady State’ Properties of Financial Ratios, Accounting and Business Research, Taylor & Francis.
  67. Rodrigues L., Rodrigues L. (2018), Economic-financial performance of the Brazilian sugarcane energy industry: An empirical evaluation using financial ratio, cluster and discriminant analysis, Biomass and Bioenergy, 108, pp. 289-296.
  68. Sarstedt M., Mooi E. (2014), A concise guide to market research. The process, data and methods using IBM SPSS Statistics, Heidelberg, Springer.
  69. Stigler G.J. (1963),Capital and rates of return in manufacturing industries, Princeton University Press, NBER.
  70. Tippett M. (1990), An Induced Theory of Financial Ratios, Accounting and Business Research, 21, 81, pp. 77-85.
  71. Wang Y.J., Lee H.S. (2008), A clustering method to identify representative financial ratios. Information Sciences, 178, 4, pp. 1087-1097.
  72. Watson C.J. (1990), Multivariate distributional properties, outliers, and transformation of financial ratios, The Accounting Review, 65, 3, pp. 682-695.
  73. Wilcox J.W. (1971), A Simple Theory of Financial Ratios As Predictors of Failure, Journal of Accounting Research, 9, 2, pp. 389-395.
  74. Zeli A., Mariani P. (2009), Productivity and profitability analysis of large Italian companies: 1998-2002, International Review of Economics, 56, 2, pp. 175-188.

Stefania Vignini, Tiziana De Cristofaro, Impatto della crisi economica su redditività e rischio finanziario delle imprese romagnole. Una cluster analysis in "MANAGEMENT CONTROL" 3/2018, pp 157-181, DOI: 10.3280/MACO2018-003008