Advertisement

Scientometrics

, Volume 120, Issue 3, pp 929–960 | Cite as

Mapping the literature on credit unions: a bibliometric investigation grounded in Scopus and Web of Science

  • Saulo Cardoso MaiaEmail author
  • Gideon Carvalho de Benedicto
  • José Willer do Prado
  • David Alastair Robb
  • Oscar Neto de Almeida Bispo
  • Mozar José de Brito
Article
  • 112 Downloads

Abstract

Credit unions play a relevant role in providing microcredit and other financial services. Because such financial cooperative organizations have drawn the attention of a significant and growing academic literature, a bibliometric study becomes essential. This study comprehensively analyzes the literature on credit unions using the leading indices for bibliometric examination: Elsevier’s Scopus and Clarivate Analytics’ Web of Science databases. Our searches reveal a high level of complementarity between the databases concerning the subject. Their combined use has enabled us to extensively trace the evolution of studies on the subject regarding volume and impact. We identify the major countries, journals, authors, articles, intellectual basis and topics. Further, using CiteSpace, we have mapped the networks of co-authorship, co-citations, and co-keywords in credit union research. The findings allow us to conclude that economics and business finance are the principal areas of credit union research although articles in sociology and history were also observed. Finally, by investigating contemporary co-keywords clusters and future research directions, we identify four main avenues of research: economic performance, corporate governance, accounting and disclosure and, credit union to bank comparisons regarding customer relationships and technology.

Keywords

Credit union Bibliometrics Intellectual base Research directions Financial inclusion 

JEL codes

E51 G23 P13 

Notes

Acknowledgements

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001.

References

  1. Amersdorffer, F., Buchenrieder, G., Bokusheva, R., & Wolz, A. (2015). Efficiency in microfinance: Financial and social performance of agricultural credit cooperatives in Bulgaria. Journal of the Operational Research Society, 66(1), 57–65.  https://doi.org/10.1057/jors.2013.162.Google Scholar
  2. Angelini, P., Di Salvo, R., & Ferri, G. (1998). Availability and cost of credit for small businesses: Customer relationships and credit cooperatives. Journal of Banking and Finance, 22(6–8), 925–954.  https://doi.org/10.1016/S0378-4266(98)00008-9.Google Scholar
  3. Aromataris, E., & Pearson, A. (2014). The systematic review: An overview. AJN The American Journal of Nursing, 114(3), 53–58.  https://doi.org/10.1097/01.NAJ.0000444496.24228.2c.Google Scholar
  4. Banerjee, A. V., Besley, T., & Guinnane, T. W. (1994). Thy neighbor’s keeper: The design of a credit cooperative with theory and a test. Quarterly Journal of Economics, 109(2), 491–515.  https://doi.org/10.2307/2118471.Google Scholar
  5. Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092.  https://doi.org/10.1287/mnsc.30.9.1078.zbMATHGoogle Scholar
  6. Barron, D. N. (1998). Pathways to legitimacy among consumer loan providers in New York City, 1914–1934. Organization studies, 19(2), 207–233.  https://doi.org/10.1177/017084069801900203.Google Scholar
  7. Barron, D. N., West, E., & Hannan, M. T. (1994). A time to grow and a time to die: Growth and mortality of credit unions in New York City, 1914–1990. American Journal of Sociology, 100(2), 381–421.  https://doi.org/10.1086/230541.Google Scholar
  8. Bauer, K. (2008). Detecting abnormal credit union performance. Journal of Banking and Finance, 32(4), 573–586.  https://doi.org/10.1016/j.jbankfin.2007.04.022.Google Scholar
  9. Bauer, K. (2015). The corporate credit union crisis: Does it call for reform or Re-engineering? Journal of Banking Regulation, 16(2), 89–105.  https://doi.org/10.1057/jbr.2013.25.Google Scholar
  10. Bauer, K. J., Miles, L. L., & Nishikawa, T. (2009). The effect of mergers on credit union performance. Journal of Banking and Finance, 33(12), 2267–2274.  https://doi.org/10.1016/j.jbankfin.2009.06.004.Google Scholar
  11. Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, 98(2), 175–212.  https://doi.org/10.1016/S0377-2217(96)00342-6.zbMATHGoogle Scholar
  12. Bojović, S., Matić, R., Popović, Z., Smiljanić, M., Stefanović, M., & Vidaković, V. (2014). An overview of forestry journals in the period 2006–2010 as basis for ascertaining research trends. Scientometrics, 98(2), 1331–1346.  https://doi.org/10.1007/s11192-013-1171-9.Google Scholar
  13. Bornmann, L., Mutz, R., & Daniel, H. D. (2008). Are there better indices for evaluation purposes than the h index? A comparison of nine different variants of the h index using data from biomedicine. Journal of the American Society for Information Science and Technology, 59(5), 830–837.  https://doi.org/10.1002/asi.20806.Google Scholar
  14. Box, J. A. R., Moreno, V. M., & Urena, L. J. B. (2013). Analysis of survival as a tool for detection of systemic risks in decision-making: A proposed theoretical model for Spanish credit cooperative sector. Actual Problems of Economics, 148(10), 464–475.Google Scholar
  15. Boyack, K. W., & Klavans, R. (2010). Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? Journal of the American Society for Information Science and Technology, 61(12), 2389–2404.  https://doi.org/10.1002/asi.21419.Google Scholar
  16. Bressan, V. G. F., Souza, D. C., & Bressan, A. A. (2017). Income smoothing: A study of the health sector’s credit unions. RBGN-Revista Brasileira de Gestao de Negócios, 19(66), 627–643.  https://doi.org/10.7819/rbgn.v0i0.2617.Google Scholar
  17. Brun, I., Rajaobelina, L., Ricard, L., & Fortin, A. (2017). Impact of website characteristics on relationship quality: A comparison of banks financial cooperatives. Journal of Financial Services Marketing, 22(4), 141–149.  https://doi.org/10.1057/s41264-017-0036-3.Google Scholar
  18. Bussler, C. T. K., Fagundes, J. A., Polacinski, E., Ferreira, C. C., & Santana, A. F. B. (2017). Perception of audited on the practice of internal audit on a credit cooperative. Contabilidad Y Negocios, 12(23), 62–77.  https://doi.org/10.18800/contabilidad.201701005.Google Scholar
  19. Byrne, N., & McCarthy, O. (2014). Value proposition preferences of credit union members and patronage activity. Marketing Intelligence and Planning, 32(6), 567–589.  https://doi.org/10.1108/IJBM-11-2013-0128.Google Scholar
  20. Byrne, N., McCarthy, O., & O’Connor, R. (2004). The development of new rural credit unions in Ireland within a context of service rationalization in rural areas. Community Development Journal, 39(4), 401–412.  https://doi.org/10.1093/cdj/bsh035.Google Scholar
  21. Caldarelli, A., Fiondella, C., Maffei, M., & Zagaria, C. (2016). Managing risk in credit cooperative banks: Lessons from a case study. Management Accounting Research, 32, 1–15.  https://doi.org/10.1016/j.mar.2015.10.002.Google Scholar
  22. Cato, M. S., Myers, J., & Howlett, S. (2013). At the sharp end of the credit crisis: A profile of Valleys Credit Union. Local Economy, 28(6), 539–552.  https://doi.org/10.1177/0269094213496757.Google Scholar
  23. Cerrone, R. (2013). Banks’ internal controls and risk management: value-added functions in Italian Credit Cooperative Banks. Risk Governance and Control: Financial Markets and Institutions, 3(4), 16–27.Google Scholar
  24. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.  https://doi.org/10.1016/0377-2217(78)90138-8.MathSciNetzbMATHGoogle Scholar
  25. Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the Association for Information Science and Technology, 57(3), 359–377.  https://doi.org/10.1002/asi.20317.Google Scholar
  26. Chen, C. (2015). How to use CiteSpace. https://leanpub.com/howtousecitespace. Accessed 22 Mar 2018.
  27. Chen, C., Ibekwe-SanJuan, F., & Hou, J. (2010). The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis. Journal of the American Society for Information Science and Technology, 61(7), 1386–1409.  https://doi.org/10.1002/asi.21309.Google Scholar
  28. Chen, Y., & Wu, C. (2017). The hot spot transformation in the research evolution of maker. Scientometrics, 113(3), 1307–1324.  https://doi.org/10.1007/s11192-017-2542-4.Google Scholar
  29. Clarivate Analytics (2018). 2018 journal impact factor, Journal Citation Reports. https://clarivate.com/products/journal-citation-reports/. Accessed 18 Jul 2018.
  30. Costa, D. F., de Melo Carvalho, F., de Melo Moreira, B. C., & do Prado, J. W. (2017). Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias. Scientometrics, 111(3), 1775–1799.  https://doi.org/10.1007/s11192-017-2371-5.Google Scholar
  31. Dal Magro, C. B., & Cunha, P. R. (2017). Red flags in detecting credit cooperative fraud: The perceptions of internal auditors. Rbgn-Revista Brasileira De Gestao De Negocios, 19(65), 469–491.  https://doi.org/10.7819/rbgn.v19i65.2918.Google Scholar
  32. Davis, K. (2016). Changing organizational form: Demutualization and the privatization of communal wealth—australian credit union experiences. Annals of Public and Cooperative Economics, 87(4), 603–621.  https://doi.org/10.1111/apce.12128.Google Scholar
  33. Desai, V. S., Conway, D. G., Crook, J. N., & Overstreet, G. A., Jr. (1997). Credit-scoring models in the credit-union environment using neural networks and genetic algorithms. IMA Journal of Management Mathematics, 8(4), 323–346.  https://doi.org/10.1093/imaman/8.4.323.zbMATHGoogle Scholar
  34. Desai, V. S., Crook, J. N., & Overstreet, G. A. (1996). A comparison of neural networks and linear scoring models in the credit union environment. European Journal of Operational Research, 95(1), 24–37.  https://doi.org/10.1016/0377-2217(95)00246-4.zbMATHGoogle Scholar
  35. Dobrev, S. D., Ozdemir, S. Z., & Teo, A. C. (2006). The ecological interdependence of emergent and established organizational populations: Legitimacy transfer, violation by comparison, and unstable identities. Organization Science, 17(5), 577–597.  https://doi.org/10.1287/orsc.1060.0209.Google Scholar
  36. Drakeford, M., & Gregory, L. (2008). Anti-poverty practice and the changing world of credit unions: New tools for social workers. Practice, 20(3), 141–150.  https://doi.org/10.1080/09503150802341368.Google Scholar
  37. Dubauskas, G. (2012). Sustainable growth of the financial sector: The case of credit unions. Journal of Security and Sustainability Issues, 1(3), 159–166.  https://doi.org/10.9770/jssi/2012.1.3(1).Google Scholar
  38. Dunford, C. (2009). Credit unions and rural banks reaching down and out to the rural poor through group-based microfinance. Enterprise Development and Microfinance, 20(2), 107–124.  https://doi.org/10.3362/1755-1986.2009.012.Google Scholar
  39. Feinberg, R. M. (2001). The competitive role of credit unions in small local financial services markets. Review of Economics and Statistics, 83(3), 560–563.  https://doi.org/10.1162/00346530152480207.Google Scholar
  40. Ferguson, C., & McKillop, D. G. (1997). The strategic development of credit unions. London: Wiley.Google Scholar
  41. Ferguson, C., & McKillop, D. G. (2000). Classifying credit union development in terms of mature, transition and Nascent industry types. Service Industries Journal, 20(4), 103–120.  https://doi.org/10.1080/02642060000000049.Google Scholar
  42. Filser, L. D., da Silva, F. F., & de Oliveira, O. J. (2017). State of research and future research tendencies in lean healthcare: A bibliometric analysis. Scientometrics, 112(2), 799–816.  https://doi.org/10.1007/s11192-017-2409-8.Google Scholar
  43. Flannery, M. J. (1974). An economic evaluation of credit unions in the United States (Research Report, Vol. 54): Federal Reserve Bank of Boston.Google Scholar
  44. Frame, W. S., Karels, G. V., & McClatchey, C. A. (2003). Do credit unions use their tax advantage to benefit members? Evidence from a cost function. Review of Financial Economics, 12(1), 35–47.  https://doi.org/10.1016/S1058-3300(03)00005-3.Google Scholar
  45. Fried, H. O., Lovell, C. K., & Eeckaut, P. V. (1993). Evaluating the performance of US credit unions. Journal of Banking & Finance, 17(2–3), 251–265.  https://doi.org/10.1016/0378-4266(93)90031-8.Google Scholar
  46. Fried, H. O., Lovell, C. K., & Yaisawarng, S. (1999). The impact of mergers on credit union service provision. Journal of Banking and Finance, 23(2), 367–386.  https://doi.org/10.1016/S0378-4266(98)00090-9.Google Scholar
  47. Fuller, D. (1998). Credit union development: Financial inclusion and exclusion. Geoforum, 29(2), 145–157.  https://doi.org/10.1016/S0016-7185(98)00009-8.Google Scholar
  48. Garden, K. A., & Ralston, D. E. (1999). The x-efficiency and allocative efficiency effects of credit union mergers. Journal of International Financial Markets, Institutions and Money, 9(3), 285–301.  https://doi.org/10.1016/S1042-4431(99)00012-8.Google Scholar
  49. Gavel, Y., & Iselid, L. (2008). Web of Science and Scopus: A journal title overlap study. Online Information Review, 32(1), 8–21.  https://doi.org/10.1108/14684520810865958.Google Scholar
  50. Ghatak, M., & Guinnane, T. W. (1999). The economics of lending with joint liability: Theory and practice. Journal of Development Economics, 60(1), 195–228.  https://doi.org/10.1016/s0304-3878(99)00041-3.Google Scholar
  51. Goddard, J. A., McKillop, D. G., & Wilson, J. O. S. (2002). The growth of US credit unions. Journal of Banking and Finance, 26(12), 2327–2356.  https://doi.org/10.1016/S0378-4266(01)00203-5.Google Scholar
  52. Goddard, J., McKillop, D., & Wilson, J. O. S. (2008). The diversification and financial performance of US credit unions. Journal of Banking & Finance, 32(9), 1836–1849.  https://doi.org/10.1016/j.jbankfin.2007.12.015.Google Scholar
  53. Goddard, J., McKillop, D., & Wilson, J. O. S. (2009). Which credit unions are acquired? Journal of Financial Services Research, 36(2), 231–252.  https://doi.org/10.1007/s10693-009-0055-x.Google Scholar
  54. Goddard, J., McKillop, D., & Wilson, J. O. S. (2014). U.S. Credit unions: Survival, consolidation, and growth. Economic Inquiry, 52(1), 304–319.  https://doi.org/10.1111/ecin.12032.Google Scholar
  55. Goenner, C. F. (2016). The policy impact of new rules for loan participation on credit union returns. Journal of Banking and Finance, 73, 198–210.  https://doi.org/10.1016/j.jbankfin.2016.09.012.Google Scholar
  56. Gong, W., & Ostermann, J. (2011). PVENN: Stata module to create proportional Venn diagram. https://EconPapers.repec.org/RePEc:boc:bocode:s457368. Accessed 16 Apr 2018.
  57. Guerrero, S., Lapalme, M. E., Herrbach, O., & Seguin, M. (2017). Board member monitoring behaviors in credit unions: The role of conscientiousness and identification with shareholders. Corporate Governance-an International Review, 25(2), 134–144.  https://doi.org/10.1111/corg.12196.Google Scholar
  58. Guinnane, T. W. (1994). A failed institutional transplant: Raiffeisen’s credit cooperatives in Ireland, 1894–1914. Explorations in Economic History, 31(1), 38–61.  https://doi.org/10.1006/exeh.1994.1002.Google Scholar
  59. Guinnane, T. W. (2001). Cooperatives as information machines: German rural credit cooperatives, 1883–1914. Journal of Economic History, 61(2), 366–389.  https://doi.org/10.1017/s0022050701028042.Google Scholar
  60. Hammarfelt, B. (2011). Interdisciplinarity and the intellectual base of literature studies: Citation analysis of highly cited monographs. Scientometrics, 86(3), 705–725.  https://doi.org/10.1007/s11192-010-0314-5.Google Scholar
  61. Harvey, J., Pettigrew, A., & Ferlie, E. (2002). The determinants of research group performance: towards mode 2? Journal of Management Studies, 39(6), 747–774.  https://doi.org/10.1111/1467-6486.00310.Google Scholar
  62. Hayton, K. (2001). The role of Scottish credit unions in tackling financial exclusion. Policy and Politics, 29(3), 281–297.  https://doi.org/10.1332/0305573012501350.Google Scholar
  63. Hemlin, S., & Olsson, L. (2011). Creativity-stimulating leadership: A critical incident study of leaders’ influence on creativity in research groups. Creativity and Innovation Management, 20(1), 49–58.  https://doi.org/10.1111/j.1467-8691.2010.00585.x.Google Scholar
  64. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569–16572.  https://doi.org/10.1073/pnas.0507655102.zbMATHGoogle Scholar
  65. Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305–360.  https://doi.org/10.1016/0304-405X(76)90026-X.Google Scholar
  66. Johnson, E. C. (1936). Rural cooperative credit unions. American Journal of Agricultural Economics, 18(4), 662–672.  https://doi.org/10.2307/1230709.Google Scholar
  67. Jones, P. A. (1999). Towards sustainable credit union development. The Association of British Credit Unions, ABCUL, March, 1999, ISBN 950628166.Google Scholar
  68. Jones, P. A. (2005). Philanthropy and enterprise in the British credit union movement. Economic Affairs, 25(2), 13–19.  https://doi.org/10.1111/j.1468-0270.2005.00545.x.Google Scholar
  69. Jones, P. A. (2008). From tackling poverty to achieving financial inclusion—The changing role of British credit unions in low income communities. The Journal of Socio-Economics, 37(6), 2141–2154.  https://doi.org/10.1016/j.socec.2007.12.001.Google Scholar
  70. Jones, D., & Kalmi, P. (2015). Membership and performance in Finnish financial cooperatives: A new view of cooperatives? Review of Social Economy, 73(3), 283–309.  https://doi.org/10.1080/00346764.2015.1067753.Google Scholar
  71. Joo, S. J., Stoeberl, P. A., Liao, K., & Ke, K. (2017). Measuring the comparative performance of branches of a credit union for internal benchmarking. Benchmarking, 24(6), 1663–1674.  https://doi.org/10.1108/BIJ-03-2016-0029.Google Scholar
  72. Kiršiene, J. (2014). The bank and credit union disasters in Lithuania: Where were the lawyers? Baltic Journal of Law and Politics, 7(2), 77–94.  https://doi.org/10.1515/bjlp-2015-0003.Google Scholar
  73. Liu, W., Gu, M., Hu, G., Li, C., Liao, H., Tang, L., et al. (2014). Profile of developments in biomass-based bioenergy research: A 20-year perspective. Scientometrics, 99(2), 507–521.  https://doi.org/10.1007/s11192-013-1152-z.Google Scholar
  74. Martinez-Campillo, A., & Fernandez-Santos, Y. (2017). What about the social efficiency in credit cooperatives? Evidence from Spain (2008–2014). Social Indicators Research, 131(2), 607–629.  https://doi.org/10.1007/s11205-016-1277-6.Google Scholar
  75. Martinez-Campillo, A., Fernandez-Santos, Y., & Sierra-Fernandez, M. D. P. (2017). Technical efficiency in Spanish credit cooperatives: An approach to the crisis impact. Revista Espanola de Financiacion y Contabilidad, 46(4), 484–506.  https://doi.org/10.1080/02102412.2017.1288951.Google Scholar
  76. Mathuva, D. M., Mboya, J. K., & McFie, J. B. (2017). Achieving legitimacy through co-operative governance and social and environmental disclosure by credit unions in a developing country. Journal of Applied Accounting Research, 18(2), 162–184.  https://doi.org/10.1108/JAAR-12-2014-0128.Google Scholar
  77. McKillop, D. G., Glass, J. C., & Ferguson, C. (2002). Investigating the cost performance of UK credit unions using radial and non-radial efficiency measures. Journal of Banking and Finance, 26(8), 1563–1591.  https://doi.org/10.1016/S0378-4266(01)00164-9.Google Scholar
  78. McKillop, D. G., Ward, A. M., & Wilson, J. O. S. (2007). The development of credit unions and their role in tackling financial exclusion. Public Money and Management, 27(1), 37–44.  https://doi.org/10.1111/j.1467-9302.2007.00553.x.Google Scholar
  79. McKillop, D., Ward, A. M., & Wilson, J. O. S. (2011). Credit unions in Great Britain: Recent trends and current prospects. Public Money and Management, 31(1), 35–42.  https://doi.org/10.1080/09540962.2011.545545.Google Scholar
  80. McKillop, D., & Wilson, J. O. S. (2011). Credit unions: A theoretical and empirical overview. Financial Markets, Institutions and Instruments, 20(3), 79–123.  https://doi.org/10.1111/j.1468-0416.2011.00166.x.Google Scholar
  81. McKillop, D. G., & Wilson, J. O. S. (2015). Credit unions as cooperative institutions: Distinctiveness, performance and prospects. Social and Environmental Accountability Journal, 35(2), 96–112.  https://doi.org/10.1080/0969160X.2015.1022195.Google Scholar
  82. Mingers, J., & Leydesdorff, L. (2015). A review of theory and practice in scientometrics. European Journal of Operational Research, 246(1), 1–19.  https://doi.org/10.1016/j.ejor.2015.04.002.zbMATHGoogle Scholar
  83. Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151(4), 264–269.  https://doi.org/10.7326/0003-4819-151-4-200908180-00135.Google Scholar
  84. Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213–228.  https://doi.org/10.1007/s11192-015-1765-5.Google Scholar
  85. Murray, J. D., & White, R. W. (1983). Economies of scale and sconomies of scope in multiproduct sinancial nstitutions: study of British Columbia credit unions. The Journal of Finance, 38(3), 887–902.  https://doi.org/10.1111/j.1540-6261.1983.tb02508.x.Google Scholar
  86. Newman, M. E. (2001). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences, 98(2), 404–409.  https://doi.org/10.1073/pnas.98.2.404.MathSciNetzbMATHGoogle Scholar
  87. Newman, M. E. J. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences of the United States of America, 101, 5200–5205.  https://doi.org/10.1073/pnas.0307545100.Google Scholar
  88. Ojong, N. (2014). Credit unions as conduits for microfinance delivery in Cameroon. Annals of Public and Cooperative Economics, 85(2), 287–304.  https://doi.org/10.1111/apce.12041.Google Scholar
  89. Olsson, L., Hemlin, S., & Pousette, A. (2012). A multi-level analysis of leader-member exchange and creative performance in research groups. Leadership Quarterly, 23(3), 604–619.  https://doi.org/10.1016/j.leaqua.2011.12.011.Google Scholar
  90. Perilleux, A., & Szafarz, A. (2015). Women leaders and social performance: Evidence from financial cooperatives in Senegal. World Development, 74, 437–452.  https://doi.org/10.1016/j.worlddev.2015.05.011.Google Scholar
  91. Persson, O. (1994). The intellectual base and research fronts of JASIS 1986–1990. Journal of the American society for information science, 45(1), 31–38.  https://doi.org/10.1002/(SICI)1097-4571(199401)45:1%3c31:AID-ASI4%3e3.0.CO;2-G.Google Scholar
  92. Prado, J. W., Castro Alcântara, V., Melo Carvalho, F., Vieira, K. C., Machado, L. K., & Tonelli, D. F. (2016). Multivariate analysis of credit risk and bankruptcy research data: A bibliometric study involving different knowledge fields (1968–2014). Scientometrics, 106(3), 1007–1029.  https://doi.org/10.1007/s11192-015-1829-6.Google Scholar
  93. Ralston, D., Wright, A., & Garden, K. (2001). Can mergers ensure the survival of credit unions in the third millennium? Journal of Banking and Finance, 25(12), 2277–2304.  https://doi.org/10.1016/S0378-4266(01)00193-5.Google Scholar
  94. Reyes-Gonzalez, L., Gonzalez-Brambila, C. N., & Veloso, F. (2016). Using co-authorship and citation analysis to identify research groups: A new way to assess performance. Scientometrics, 108(3), 1171–1191.  https://doi.org/10.1007/s11192-016-2029-8.Google Scholar
  95. Rubin, G. M., Overstreet, G. A., Beling, P., & Rajaratnam, K. (2013). A dynamic theory of the credit union. Annals of Operations Research, 205(1), 29–53.  https://doi.org/10.1007/s10479-012-1246-7.zbMATHGoogle Scholar
  96. Ryder, N. (2009). The credit crunch—The right time for credit unions to strike? Legal Studies, 29(1), 75–98.  https://doi.org/10.1111/j.1748-121X.2008.00113.x.MathSciNetGoogle Scholar
  97. Schmidt, O. (2017). How cooperative are savings and credit cooperatives in developing countries? An analysis of datasets from Uganda. Annals of Public and Cooperative Economics, 88(3), 345–368.  https://doi.org/10.1111/apce.12155.Google Scholar
  98. Scimago Lab (2016). Country Rankings. http://www.scimagojr.com/countryrank.php. Accessed 19 Mar 2018.
  99. Silva, T. P., Leite, M., Guse, J. C., & Gollo, V. (2017). Financial and economic performance of major Brazilian credit cooperatives. Contaduria y Administracion, 62(5), 1442–1459.  https://doi.org/10.1016/j.cya.2017.05.006.Google Scholar
  100. Smith, D. J. (1984). A theoretic framework for the analysis of credit union decision making. The Journal of Finance, 39(4), 1155–1168.  https://doi.org/10.1111/j.1540-6261.1984.tb03899.x.Google Scholar
  101. Smith, D. J. (1986). A test for variant objective functions in credit unions. Applied Economics, 18(9), 959–970.  https://doi.org/10.1080/00036848600000053.Google Scholar
  102. Smith, D. J., Cargill, T. F., & Meyer, R. A. (1981). Credit unions: an economic theory of a credit union. Journal of Finance, 36(2), 519–528.  https://doi.org/10.2307/2327039.Google Scholar
  103. Souza, F. A. P. (2017). Competition between credit cooperatives and banks in local markets. Espacios, 38(29), 20.Google Scholar
  104. Spencer, J. E. (1996). An extension to Taylor’s model of credit unions. Review of Social Economy, 54(1), 89–98.  https://doi.org/10.1080/00346769600000004.Google Scholar
  105. Talbot, S., Bhaird, C. M., & Whittam, G. (2015). Can credit unions bridge the gap in lending to SMEs? Venture Capital, 17(1–2), 113–128.  https://doi.org/10.1080/13691066.2015.1021027.Google Scholar
  106. Taşkın, Z., & Al, U. (2014). Standardization problem of author affiliations in citation indexes. Scientometrics, 98(1), 347–368.  https://doi.org/10.1007/s11192-013-1004-x.Google Scholar
  107. Taylor, R. A. (1971). The credit union as a cooperative institution. Review of Social Economy, 29(2), 207–217.  https://doi.org/10.1080/00346767100000033.MathSciNetGoogle Scholar
  108. Tokle, R. J., Fullerton, T. M., Jr., & Walke, A. G. (2015). Credit union loan rate determinants following the 2008 financial crisis. Social Science Journal, 52(3), 364–373.  https://doi.org/10.1016/j.soscij.2014.11.001.Google Scholar
  109. Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222.  https://doi.org/10.1111/1467-8551.00375.Google Scholar
  110. Unda, L. A. (2015). Board of directors characteristics and credit union financial performance: A pitch. Accounting and Finance, 55(2), 353–360.  https://doi.org/10.1111/acfi.12114.Google Scholar
  111. Van Dalsem, S. A. (2017). Uninsured deposits and excess share insurance at US credit unions: The impact on risk and returns to members. Journal of Economics and Finance, 41(4), 714–738.  https://doi.org/10.1007/s12197-016-9376-4.Google Scholar
  112. Van Raan, A. F. J. (2006). Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups. Scientometrics, 67(3), 491–502.  https://doi.org/10.1556/Scient.67.2006.3.10.Google Scholar
  113. Vasserot, C. V. (2014). Credit unions and its position within the cooperative model: Integration versus differentiation in the framework of the financial system reform. REVESCO Revista de Estudios Cooperativos, 117, 50–76.  https://doi.org/10.5209/rev-reve.2015.v117.48145.Google Scholar
  114. Wagner, C. S., & Leydesdorff, L. (2005). Network structure, self-organization, and the growth of international collaboration in science. Research Policy, 34(10), 1608–1618.  https://doi.org/10.1016/j.respol.2005.08.002.Google Scholar
  115. Walker, M. C., & Chandler, G. G. (1977). On the allocation of the net monetary benefits of credit union membership. Review of Social Economy, 35(2), 159–168.  https://doi.org/10.1080/00346767700000018.Google Scholar
  116. Walton, J. K. (2015). Revisiting the Rochdale Pioneers. Labour History Review, 80(3), 215–247.  https://doi.org/10.3828/lhr.2015.10.Google Scholar
  117. Wang, H. J., Chang, C. C., & Chen, P. C. (2008). The cost effects of government-subsidised credit: Evidence from farmers’ credit unions in Taiwan. Journal of Agricultural Economics, 59(1), 132–149.  https://doi.org/10.1111/j.1477-9552.2007.00137.x.Google Scholar
  118. Ward, A. M., & McKillop, D. G. (2005). The law of proportionate effect: The growth of the UK credit union movement at national and regional level. Journal of Business Finance and Accounting, 32(9–10), 1827–1859.  https://doi.org/10.1111/j.0306-686X.2005.00649.x.Google Scholar
  119. Wolken, J. D., & Navratil, F. J. (1980). Economies of scale in credit unions: Further evidence. The Journal of Finance, 35(3), 769–775.  https://doi.org/10.1111/j.1540-6261.1980.tb03497.x.Google Scholar
  120. Word Council of Credit Unions (WOCCU). (2016). 2016 Statistical report: the global network of credit unions and financial cooperatives. http://www.woccu.org/documents/2016_Statistical_Report. Accessed 20 Mar 2018.
  121. Yamori, N., Harimaya, K., & Tomimura, K. (2017). The efficiency of Japanese financial cooperatives: An application of parametric distance functions. Journal of Economics and Business, 94(6), 43–53.  https://doi.org/10.1016/j.jeconbus.2017.09.001.Google Scholar
  122. Zhang, Q., & Izumida, Y. (2013). Determinants of repayment performance of group lending in China: Evidence from rural credit cooperatives’ program in Guizhou province. China Agricultural Economic Review, 5(3), 328–341.  https://doi.org/10.1108/CAER-08-2012-0083.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2019

Authors and Affiliations

  1. 1.UFLA – Universidade Federal de Lavras, Programa de Pós-Graduação em AdministraçãoLavrasBrazil
  2. 2.UQ Business SchoolThe University of QueenslandBrisbaneAustralia

Personalised recommendations