A constructivist model of bank branch front-office employee evaluation: an FCM-SD-based approach
Abstract
The banking sector is one of the primary drivers of economic development. This sector has been affected by various crises throughout its history – most recently, the 2008 financial and economic crisis. In response, banking institutions have had to make diverse changes to their procedures and deal with new concerns related to changes within markets. One of the main recent developments in this sector is the new commercial function assigned to bank branch front-office employees, who have become responsible for selling financial products and services, as well as recruiting and retaining clients. As a result, the sector needs new employee performance evaluation methods in line with banks and staff members’ requirements. This study combined fuzzy cognitive mapping techniques and the system dynamics (SD) approach to develop a well-informed performance analysis system for assessing bank branch front-office employees. The proposed system was validated by the Business Process Management Competence Center director at Millennium BCP – a Portuguese private banking corporation. The main difference between the model constructed in the present research and current evaluation practices is that the criteria were collected directly from multiple specialists working at different commercial banks, who deal daily with this decision problem. The model’s theoretical and practical implications are also discussed.
Keyword : bank branch front-office employee, fuzzy cognitive map (FCM), performance evaluation, problem structuring methods (PSMs), system dynamics (SD)
How to Cite
Paes de Faria, A. C. C., Ferreira, F. A. F., Dias, P. J. V. L., & Çipi, A. (2020). A constructivist model of bank branch front-office employee evaluation: an FCM-SD-based approach. Technological and Economic Development of Economy, 26(1), 213-239. https://doi.org/10.3846/tede.2020.11883
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Ackermann, F. (2012). Problem structuring methods “in the Doc”: Arguing the case for Soft OR. European Journal of Operational Research, 219(3), 652–658. https://doi.org/10.1016/j.ejor.2011.11.014
Arbore, A., & Busacca, B. (2009). Customer satisfaction and dissatisfaction in retail banking: Exploring the asymmetric impact of attribute performances. Journal of Retailing and Consumer Services, 16(4), 271–280. https://doi.org/10.1016/j.jretconser.2009.02.002
Athanassopoulos, A. (1997). Service quality and operating efficiency synergies for management control in the provision of financial services: Evidence from Greek bank branches. European Journal of Operational Research, 98(2), 300–313. https://doi.org/10.1016/S0377-2217(96)00349-9
Azevedo, A., & Ferreira, F. (2019). Analyzing the dynamics behind ethical banking practices using fuzzy cognitive mapping. Operational Research, 19(3), 679–700. https://doi.org/10.1007/s12351-017-0333-6
Bana e Costa, C., Stewart, T., & Vansnick, J. (1997). Multicriteria decision analysis: Some thoughts based on the tutorial and discussion sessions of the ESIGMA meetings. European Journal of Operational Research, 99(1), 28–37. https://doi.org/10.1016/S0377-2217(96)00380-3
Barger, M., Perez, T., Canelas, D., & Linnenbrink-Garcia, L. (2018). Constructivism and personal epistemology development in undergraduate chemistry students. Learning and Individual Differences, 63, 89–101. https://doi.org/10.1016/j.lindif.2018.03.006
Bell, S., & Morse, S. (2013). Groups and facilitators within problem structuring processes. Journal of the Operational Research Society, 64(7), 959–972. https://doi.org/10.1057/jors.2012.110
Bellou, V., Chaniotakis, I., Kehagias, I., & Rigopoulou, I. (2015). Employer brand of choice: An employee perspective. Journal of Business Economics and Management, 16(6), 1201–1215. https://doi.org/10.3846/16111699.2013.848227
Belton, V., & Stewart, T. (2002). Multiple criteria decision analysis: An integrated approach. Kluwer Academic Publishers. https://doi.org/10.1007/978-1-4615-1495-4
Beltratti, A., & Stulz, R. (2012). The credit crisis around the globe: Why did some banks perform better? Journal of Financial Economics, 105(1), 1–17. https://doi.org/10.1016/j.jfineco.2011.12.005
Berger, A., Leusner, J., & Mingo, J. (1997). The efficiency of bank branches. Journal of Monetary Economics, 40(1), 141–162. https://doi.org/10.1016/S0304-3932(97)00035-4
Canas, S., Ferreira, F., & Meidutė-Kavaliauskienė, I. (2015). Setting rents in residential real estate: A methodological proposal using multiple criteria decision analysis. International Journal of Strategic Property Management, 19(4), 368–380. https://doi.org/10.3846/1648715X.2015.1093562
Carayannis, E., Ferreira, F., Bento, P., Ferreira, J., Jalali, M., & Fernandes, B. (2018). Developing a sociotechnical evaluation index for tourist destination competitiveness using cognitive mapping and MCDA. Technological Forecasting & Social Change, 131, 147–158. https://doi.org/10.1016/j.techfore.2018.01.015
Castela, B., Ferreira, F., Ferreira, J., & Marques, C. (2018). Assessing the innovation capability of small- and medium-sized enterprises using a non-parametric and integrative approach. Management Decision, 56(6), 1365–1383. https://doi.org/10.1108/MD-02-2017-0156
Christoforou, A., & Andreou, A. (2017). A framework for static and dynamic analysis of multi-layer fuzzy cognitive maps. Neurocomputing, 232, 133–145. https://doi.org/10.1016/j.neucom.2016.09.115
Dekker, D., & Post, T. (2001). A quasi-concave DEA model with an application for bank branch performance evaluation. European Journal of Operational Research, 132(2), 296–311. https://doi.org/10.1016/S0377-2217(00)00153-3
Eden, C., & Ackermann, F. (2001). SODA – The principles. In J. Rosenhead, & J. Mingers (Eds.), Rational analysis for a problematic world revisited: Problem structuring methods for complexity, uncertainty and conflict (pp. 21–41). Chichester, John Wiley & Sons.
Eskelinen, J., & Kuosmanen, T. (2013). Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach. Journal of Banking & Finance, 37(12), 5163–5175. https://doi.org/10.1016/j.jbankfin.2013.03.010
Eskelinen, J., Halme, M., & Kallio, M. (2014). Bank branch sales evaluation using extended value efficiency analysis. European Journal of Operational Research, 232(3), 654–633. https://doi.org/10.1016/j.ejor.2013.08.005
Faria, P., Ferreira, F., Jalali, M., Bento, P., & António, N. (2018). Combining cognitive mapping and MCDA for improving quality of life in urban areas. Cities, 78, 116–127. https://doi.org/10.1016/j.cities.2018.02.006
Ferreira, F. (2016). Are you pleased with your neighborhood? A fuzzy cognitive mapping-based approach for measuring residential neighborhood satisfaction in urban communities. International Journal of Strategic Property Management, 20(2), 130–141. https://doi.org/10.3846/1648715X.2015.1121169
Ferreira, F., Ferreira, J., Fernandes, C., Meidutė-Kavaliauskienė, I., & Jalali, M. (2017). Enhancing knowledge and strategic planning of bank customer loyalty using fuzzy cognitive maps. Technological and Economic Development of Economy, 23(6), 860–876. https://doi.org/10.3846/20294913.2016.1213200
Ferreira, F., Jalali, M., Ferreira, J., Stankevicienė, J., & Marques, C. (2016). Understanding the dynamics behind bank branch service quality in Portugal: Pursuing a holistic view using fuzzy cognitive mapping. Service Business, 10(3), 469–487. https://doi.org/10.1007/s11628-015-0278-x
Ferreira, F., Jalali, M., Meidutė-Kavaliauskienė, I., & Viana, B. (2015). A metacognitive decision making based-framework for bank customer loyalty measurement and management. Technological and Economic Development of Economy, 21(2), 280–300. https://doi.org/10.3846/20294913.2014.981764
Ferreira, F., Santos, S., Rodrigues, P., & Spahr, R. (2014). How to create indices for bank branch financial performance measurement using MCDA techniques: An illustrative example. Journal of Business Economics and Management, 15(4), 708–728. https://doi.org/10.3846/16111699.2012.701230
Ferreira, F., Spahr, R., Santos, S., & Rodrigues, P. (2012). A multiple criteria framework to evaluate bank branch potential attractiveness. International Journal of Strategic Property Management, 16(3), 254–276. https://doi.org/10.3846/1648715X.2012.707629
Forrester, J. (1961). Industrial Dynamics. The MIT Press.
Franco, E., Hirama, K., & Carvalho, M. (2018). Applying system dynamics approach in software and information system projects: A mapping study. Information and Software Technology, 93, 58–73. https://doi.org/10.1016/j.infsof.2017.08.013
García-Alcober, M., Prior, D., Tortosa-Ausina, E., & Illueca, M. (2019). Risk-taking behavior, earnings quality, and bank performance: A profit frontier approach. BRQ Business Research Quarterly (in Press). https://doi.org/10.1016/j.brq.2019.02.003
Guarnieri, P., Silva, L., & Levino, N. (2016). Analysis of electronic waste reverse logistics decisions using strategic options development analysis methodology: A Brazilian case. Journal of Cleaner Production, 133, 1105–1117. https://doi.org/10.1016/j.jclepro.2016.06.025
Herrera-Restrepo, O., Triantis, K., Seaver, W., Paradi, J., & Zhu, H. (2016). Bank branch operational performance: A robust multivariate and clustering approach. Expert Systems with Applications, 50, 107–119. https://doi.org/10.1016/j.eswa.2015.12.025
Ho, C., & Wu, D. (2009). Online banking performance evaluation using data envelopment analysis and principal component analysis. Computers and Operations Research, 36(6), 1835–1842. https://doi.org/10.1016/j.cor.2008.05.008
Hoehle, H., Scornavacca, E., & Huff, S. (2012). Three decades of research on consumer adoption and utilization of electronic banking channels: A literature analysis. Decision Support Systems, 54(1), 122–132. https://doi.org/10.1016/j.dss.2012.04.010
Hursen, C., & Soykara, A. (2012). Evaluation of teachers’ beliefs towards constructivist learning practices. Procedia – Social and Behavioral Sciences, 46, 92–100. https://doi.org/10.1016/j.sbspro.2012.05.074
Jackson III, W., Nandakumar, P., & Roth, A. (2003). Market structure, consumer banking, and optimal level of service quality. Review of Financial Economics, 12(1), 49–63. https://doi.org/10.1016/S1058-3300(03)00006-5
Jia, S., Liu, X., & Yan, G. (2019). Effect of APCF policy on the haze pollution in China: A system dynamics T approach. Energy Policy, 125, 33–44. https://doi.org/10.1016/j.enpol.2018.10.012
Karatepe, O., Yavas, U., & Babakus, E. (2005). Measuring service quality of banks: Scale development and validation. Journal of Retailing and Consumer Services, 12(5), 373–383. https://doi.org/10.1016/j.jretconser.2005.01.001
Kearney, T., Walsh, G., Barnett, W., Gong, T., Schwabe, M., & Ifie, K. (2017). Emotional intelligence in front-line/back-office employee relationships. Journal of Services Marketing, 31(2), 185–199. https://doi.org/10.1108/JSM-09-2016-0339
Kok, K. (2009). The potential of fuzzy cognitive maps for semi-quantitative scenario development, with an example from Brazil. Global Environmental Change, 19(1), 122–133. https://doi.org/10.1016/j.gloenvcha.2008.08.003
Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24(1), 65–75. https://doi.org/10.1016/S0020-7373(86)80040-2
Ladeira, M., Ferreira, F., Ferreira, J., Fang, W., Falcão, P., & Rosa, A. (2019). Exploring the determinants of digital entrepreneurship using fuzzy cognitive maps. International Entrepreneurship and Management Journal, 15(4), 1077–1101. https://doi.org/10.1007/s11365-019-00574-9
Lee, P., Cheng, T., Yeung, A., & Lai, K. (2011). An empirical study of transformational leadership, team performance, and service quality in retail banks. Omega – The International Journal of Management Science, 39(6), 690–671. https://doi.org/10.1016/j.omega.2011.02.001
Liao, S. (2008). Problem structuring methods in military command and control. Expert Systems with Applications, 35(3), 645–653. https://doi.org/10.1016/j.eswa.2007.07.012
Małachowski, B., & Korytkowski, P. (2016). Competence-based performance model of multi-skilled workers. Computers & Industrial Engineering, 91, 165–177. https://doi.org/10.1016/j.cie.2015.11.018
Manandhar, R., & Tang, J. (2002). The evaluation of bank branch performance using data envelopment analysis: A framework. Journal of High Technology Management Research, 13(1), 1–17. https://doi.org/10.1016/S1047-8310(01)00045-1
Marttunen, M., Lienert, J., & Belton, V. (2017). Structuring problems for multi-criteria decision analysis in practice: A literature review of method combinations. European Journal of Operational Research, 263(1), 1–17. https://doi.org/10.1016/j.ejor.2017.04.041
Misthos, L., Messaris, G., Damigos, D., & Menegaki, M. (2017). Exploring the perceived intrusion of mining into the landscape using the fuzzy cognitive mapping approach. Ecological Engineering, 101, 60–74. https://doi.org/10.1016/j.ecoleng.2017.01.015
Olazabal, M., & Pascual, U. (2016). Use of fuzzy cognitive maps to study urban resilience and transformation. Environmental Innovation and Societal Transitions, 18, 18–40.
Oliveira, P., & Hippel, E. (2011). Users as service innovators: The case of banking services, Research Policy, 40(6), 806–818. https://doi.org/10.1016/j.respol.2011.03.009
Özesmi, U., & Özesmi, L. (2004). Ecological models based on people’s knowledge: A multi-step fuzzy cognitive mapping approach. Ecological Modelling, 176(1–2), 43–64. https://doi.org/10.1016/j.ecolmodel.2003.10.027
Papachristos, G. (2019). System dynamics modelling and simulation for sociotechnical transitions research. Environmental Innovation and Societal Transitions, 31, 248–261. https://doi.org/10.1016/j.eist.2018.10.001
Paradi, J., Rouatt, S., & Zhu, H. (2011). Two-stage evaluation of bank branch efficiency using data envelopment analysis. Omega – The International Journal of Management Science, 39(1), 99–109. https://doi.org/10.1016/j.omega.2010.04.002
Peña, A., Sossa, H., & Gutiérrez, A. (2008). Causal knowledge and reasoning by cognitive maps: Pursuing a holistic approach. Expert Systems with Applications, 35(1/2), 2–18. https://doi.org/10.1016/j.eswa.2007.06.016
Pimpakorn, N., & Patterson, P. (2010). Customer-oriented behaviour of front-line service employees: The need to be both willing and able. Australasian Marketing Journal, 18(2), 57–65. https://doi.org/10.1016/j.ausmj.2010.02.004
Pluchinotta, I., Esposito, D., & Camarda, D. (2019). Fuzzy cognitive mapping to support multi-agent decisions in development of urban policymaking. Sustainable Cities and Society, 46, 101402. https://doi.org/10.1016/j.scs.2018.12.030
Quaranta, A., Raffoni, A., & Visani, F. (2018). A multidimensional approach to measuring bank branch efficiency. European Journal of Operational Research, 266(2), 746–760. https://doi.org/10.1016/j.ejor.2017.10.009
Ramos, J., Ferreira, F., & Barata, J. (2011). Banking services in Portugal: A preliminary analysis to the perception and expectations of front office employees. International Journal of Management and Enterprise Development, 10(2/3), 188–207. https://doi.org/10.1504/IJMED.2011.041549
Reis, J., Amorim, M., & Melão, N. (2019). Multichannel service failure and recovery in a O2O era: A qualitative multi-method research in the banking services industry. International Journal of Production Economics, 215, 24–33. https://doi.org/10.1016/j.ijpe.2018.07.001
Reydet, S., & Carsana, L. (2017). The effect of digital design in retail banking on costumers’ commitment and loyalty: The mediating role of positive affect. Journal of Retailing and Consumer Services, 37, 32–138. https://doi.org/10.1016/j.jretconser.2017.04.003
Ribeiro, M., Ferreira, F, Jalali, M., & Meidutė-Kavaliauskienė, I. (2017). A fuzzy knowledge-based framework for risk assessment of residential real estate investments. Technological and Economic Development of Economy, 23(1), 140–156. https://doi.org/10.3846/20294913.2016.1212742
Rodrigues, T., Montibeller, G., Oliveira, M., & Bana e Costa, C. (2017). Modelling multicriteria value interactions with reasoning maps. European Journal of Operational Research, 258(3), 1054–1071. https://doi.org/10.1016/j.ejor.2016.09.047
Rosenhead, J. (2006). Past, present and future of problem structuring methods. Journal of the Operational Research Society, 57(7), 759–765. https://doi.org/10.1057/palgrave.jors.2602206
Santos, S., Belton, V., & Howick, S. (2008). Enhanced performance measurement using OR: A case study. Journal of the Operational Research Society, 59(6), 762–775. https://doi.org/10.1057/palgrave.jors.2602397
Santos, S., Belton, V., & Howick, S. (2002). Adding value to performance measurement by using system dynamics and multicriteria analysis. International Journal of Operations & Production Management, 22(11), 1246–1272. https://doi.org/10.1108/01443570210450284
Sederati, P., Santos, S., & Pintassilgo, P. (2019). System dynamics in tourism planning and development. Tourism Planning & Development, 16(3), 256–280. https://doi.org/10.1080/21568316.2018.1436586
Sing, M., Love, P., & Liu, H. (2019). Rehabilitation of existing building stock: A system dynamics model to support policy development. Cities, 87, 142–152. https://doi.org/10.1016/j.cities.2018.09.018
Smith, C., & Shaw, D. (2019). The characteristics of problem structuring methods: A literature review. European Journal of Operational Research, 274(2), 403–416. https://doi.org/10.1016/j.ejor.2018.05.003
Song, H., Kim, T., & Kim, T. (2017). The impact of spectrum policies on the secondary spectrum market: A system dynamics approach. Telecommunications Policy, 42(5/6), 460–472. https://doi.org/10.1016/j.telpol.2017.04.004
Sterman, J. (2002). System dynamics: System thinking and modeling for a complex world. MIT Engineering Systems Division.
Sterman, J., Olivia, R., Linderman, K., & Bendoly, E. (2015). System dynamics perspectives and modeling opportunities for research in operations management. Journal of Operations Management, 39/40(1), 1–5. https://doi.org/10.1016/j.jom.2015.07.001
Szopiński, T. (2016). Factors affecting the adoption of online banking in Poland. Journal of Business Research, 69(11), 4763–4768. https://doi.org/10.1016/j.jbusres.2016.04.027
Torres, J., Kunc, M., & O’Brien, F. (2017). Supporting strategy using system dynamics. European Journal of Operational Research, 260(3), 1081–1094. https://doi.org/10.1016/j.ejor.2017.01.018
Wilson, H., & Daniel, E. (2007). The multi-channel challenge: A dynamic capability approach. Industrial Marketing Management, 36(1), 10–20. https://doi.org/10.1016/j.indmarman.2006.06.015
Wu, D., Yang, Z., & Liang, L. (2006). Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank. Expert Systems with Applications, 31(1), 108–115. https://doi.org/10.1016/j.eswa.2005.09.034
Yang, Z. (2009). Assessing the performance of Canadian bank branches using data envelopment analysis. Journal of the Operational Research Society, 60(6), 771–780. https://doi.org/10.1057/palgrave.jors.2602619
Zavadskas, E., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165–179. https://doi.org/10.3846/20294913.2014.892037
Ziv, G., Watson, E., Young, D., Howard, D., Larcom, S., & Tanentzap, A. (2018). The potential impact of Brexit on the energy, water and food nexus in the UK: A fuzzy cognitive mapping approach. Applied Energy, 210, 487–498. https://doi.org/10.1016/j.apenergy.2017.08.033
Arbore, A., & Busacca, B. (2009). Customer satisfaction and dissatisfaction in retail banking: Exploring the asymmetric impact of attribute performances. Journal of Retailing and Consumer Services, 16(4), 271–280. https://doi.org/10.1016/j.jretconser.2009.02.002
Athanassopoulos, A. (1997). Service quality and operating efficiency synergies for management control in the provision of financial services: Evidence from Greek bank branches. European Journal of Operational Research, 98(2), 300–313. https://doi.org/10.1016/S0377-2217(96)00349-9
Azevedo, A., & Ferreira, F. (2019). Analyzing the dynamics behind ethical banking practices using fuzzy cognitive mapping. Operational Research, 19(3), 679–700. https://doi.org/10.1007/s12351-017-0333-6
Bana e Costa, C., Stewart, T., & Vansnick, J. (1997). Multicriteria decision analysis: Some thoughts based on the tutorial and discussion sessions of the ESIGMA meetings. European Journal of Operational Research, 99(1), 28–37. https://doi.org/10.1016/S0377-2217(96)00380-3
Barger, M., Perez, T., Canelas, D., & Linnenbrink-Garcia, L. (2018). Constructivism and personal epistemology development in undergraduate chemistry students. Learning and Individual Differences, 63, 89–101. https://doi.org/10.1016/j.lindif.2018.03.006
Bell, S., & Morse, S. (2013). Groups and facilitators within problem structuring processes. Journal of the Operational Research Society, 64(7), 959–972. https://doi.org/10.1057/jors.2012.110
Bellou, V., Chaniotakis, I., Kehagias, I., & Rigopoulou, I. (2015). Employer brand of choice: An employee perspective. Journal of Business Economics and Management, 16(6), 1201–1215. https://doi.org/10.3846/16111699.2013.848227
Belton, V., & Stewart, T. (2002). Multiple criteria decision analysis: An integrated approach. Kluwer Academic Publishers. https://doi.org/10.1007/978-1-4615-1495-4
Beltratti, A., & Stulz, R. (2012). The credit crisis around the globe: Why did some banks perform better? Journal of Financial Economics, 105(1), 1–17. https://doi.org/10.1016/j.jfineco.2011.12.005
Berger, A., Leusner, J., & Mingo, J. (1997). The efficiency of bank branches. Journal of Monetary Economics, 40(1), 141–162. https://doi.org/10.1016/S0304-3932(97)00035-4
Canas, S., Ferreira, F., & Meidutė-Kavaliauskienė, I. (2015). Setting rents in residential real estate: A methodological proposal using multiple criteria decision analysis. International Journal of Strategic Property Management, 19(4), 368–380. https://doi.org/10.3846/1648715X.2015.1093562
Carayannis, E., Ferreira, F., Bento, P., Ferreira, J., Jalali, M., & Fernandes, B. (2018). Developing a sociotechnical evaluation index for tourist destination competitiveness using cognitive mapping and MCDA. Technological Forecasting & Social Change, 131, 147–158. https://doi.org/10.1016/j.techfore.2018.01.015
Castela, B., Ferreira, F., Ferreira, J., & Marques, C. (2018). Assessing the innovation capability of small- and medium-sized enterprises using a non-parametric and integrative approach. Management Decision, 56(6), 1365–1383. https://doi.org/10.1108/MD-02-2017-0156
Christoforou, A., & Andreou, A. (2017). A framework for static and dynamic analysis of multi-layer fuzzy cognitive maps. Neurocomputing, 232, 133–145. https://doi.org/10.1016/j.neucom.2016.09.115
Dekker, D., & Post, T. (2001). A quasi-concave DEA model with an application for bank branch performance evaluation. European Journal of Operational Research, 132(2), 296–311. https://doi.org/10.1016/S0377-2217(00)00153-3
Eden, C., & Ackermann, F. (2001). SODA – The principles. In J. Rosenhead, & J. Mingers (Eds.), Rational analysis for a problematic world revisited: Problem structuring methods for complexity, uncertainty and conflict (pp. 21–41). Chichester, John Wiley & Sons.
Eskelinen, J., & Kuosmanen, T. (2013). Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach. Journal of Banking & Finance, 37(12), 5163–5175. https://doi.org/10.1016/j.jbankfin.2013.03.010
Eskelinen, J., Halme, M., & Kallio, M. (2014). Bank branch sales evaluation using extended value efficiency analysis. European Journal of Operational Research, 232(3), 654–633. https://doi.org/10.1016/j.ejor.2013.08.005
Faria, P., Ferreira, F., Jalali, M., Bento, P., & António, N. (2018). Combining cognitive mapping and MCDA for improving quality of life in urban areas. Cities, 78, 116–127. https://doi.org/10.1016/j.cities.2018.02.006
Ferreira, F. (2016). Are you pleased with your neighborhood? A fuzzy cognitive mapping-based approach for measuring residential neighborhood satisfaction in urban communities. International Journal of Strategic Property Management, 20(2), 130–141. https://doi.org/10.3846/1648715X.2015.1121169
Ferreira, F., Ferreira, J., Fernandes, C., Meidutė-Kavaliauskienė, I., & Jalali, M. (2017). Enhancing knowledge and strategic planning of bank customer loyalty using fuzzy cognitive maps. Technological and Economic Development of Economy, 23(6), 860–876. https://doi.org/10.3846/20294913.2016.1213200
Ferreira, F., Jalali, M., Ferreira, J., Stankevicienė, J., & Marques, C. (2016). Understanding the dynamics behind bank branch service quality in Portugal: Pursuing a holistic view using fuzzy cognitive mapping. Service Business, 10(3), 469–487. https://doi.org/10.1007/s11628-015-0278-x
Ferreira, F., Jalali, M., Meidutė-Kavaliauskienė, I., & Viana, B. (2015). A metacognitive decision making based-framework for bank customer loyalty measurement and management. Technological and Economic Development of Economy, 21(2), 280–300. https://doi.org/10.3846/20294913.2014.981764
Ferreira, F., Santos, S., Rodrigues, P., & Spahr, R. (2014). How to create indices for bank branch financial performance measurement using MCDA techniques: An illustrative example. Journal of Business Economics and Management, 15(4), 708–728. https://doi.org/10.3846/16111699.2012.701230
Ferreira, F., Spahr, R., Santos, S., & Rodrigues, P. (2012). A multiple criteria framework to evaluate bank branch potential attractiveness. International Journal of Strategic Property Management, 16(3), 254–276. https://doi.org/10.3846/1648715X.2012.707629
Forrester, J. (1961). Industrial Dynamics. The MIT Press.
Franco, E., Hirama, K., & Carvalho, M. (2018). Applying system dynamics approach in software and information system projects: A mapping study. Information and Software Technology, 93, 58–73. https://doi.org/10.1016/j.infsof.2017.08.013
García-Alcober, M., Prior, D., Tortosa-Ausina, E., & Illueca, M. (2019). Risk-taking behavior, earnings quality, and bank performance: A profit frontier approach. BRQ Business Research Quarterly (in Press). https://doi.org/10.1016/j.brq.2019.02.003
Guarnieri, P., Silva, L., & Levino, N. (2016). Analysis of electronic waste reverse logistics decisions using strategic options development analysis methodology: A Brazilian case. Journal of Cleaner Production, 133, 1105–1117. https://doi.org/10.1016/j.jclepro.2016.06.025
Herrera-Restrepo, O., Triantis, K., Seaver, W., Paradi, J., & Zhu, H. (2016). Bank branch operational performance: A robust multivariate and clustering approach. Expert Systems with Applications, 50, 107–119. https://doi.org/10.1016/j.eswa.2015.12.025
Ho, C., & Wu, D. (2009). Online banking performance evaluation using data envelopment analysis and principal component analysis. Computers and Operations Research, 36(6), 1835–1842. https://doi.org/10.1016/j.cor.2008.05.008
Hoehle, H., Scornavacca, E., & Huff, S. (2012). Three decades of research on consumer adoption and utilization of electronic banking channels: A literature analysis. Decision Support Systems, 54(1), 122–132. https://doi.org/10.1016/j.dss.2012.04.010
Hursen, C., & Soykara, A. (2012). Evaluation of teachers’ beliefs towards constructivist learning practices. Procedia – Social and Behavioral Sciences, 46, 92–100. https://doi.org/10.1016/j.sbspro.2012.05.074
Jackson III, W., Nandakumar, P., & Roth, A. (2003). Market structure, consumer banking, and optimal level of service quality. Review of Financial Economics, 12(1), 49–63. https://doi.org/10.1016/S1058-3300(03)00006-5
Jia, S., Liu, X., & Yan, G. (2019). Effect of APCF policy on the haze pollution in China: A system dynamics T approach. Energy Policy, 125, 33–44. https://doi.org/10.1016/j.enpol.2018.10.012
Karatepe, O., Yavas, U., & Babakus, E. (2005). Measuring service quality of banks: Scale development and validation. Journal of Retailing and Consumer Services, 12(5), 373–383. https://doi.org/10.1016/j.jretconser.2005.01.001
Kearney, T., Walsh, G., Barnett, W., Gong, T., Schwabe, M., & Ifie, K. (2017). Emotional intelligence in front-line/back-office employee relationships. Journal of Services Marketing, 31(2), 185–199. https://doi.org/10.1108/JSM-09-2016-0339
Kok, K. (2009). The potential of fuzzy cognitive maps for semi-quantitative scenario development, with an example from Brazil. Global Environmental Change, 19(1), 122–133. https://doi.org/10.1016/j.gloenvcha.2008.08.003
Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24(1), 65–75. https://doi.org/10.1016/S0020-7373(86)80040-2
Ladeira, M., Ferreira, F., Ferreira, J., Fang, W., Falcão, P., & Rosa, A. (2019). Exploring the determinants of digital entrepreneurship using fuzzy cognitive maps. International Entrepreneurship and Management Journal, 15(4), 1077–1101. https://doi.org/10.1007/s11365-019-00574-9
Lee, P., Cheng, T., Yeung, A., & Lai, K. (2011). An empirical study of transformational leadership, team performance, and service quality in retail banks. Omega – The International Journal of Management Science, 39(6), 690–671. https://doi.org/10.1016/j.omega.2011.02.001
Liao, S. (2008). Problem structuring methods in military command and control. Expert Systems with Applications, 35(3), 645–653. https://doi.org/10.1016/j.eswa.2007.07.012
Małachowski, B., & Korytkowski, P. (2016). Competence-based performance model of multi-skilled workers. Computers & Industrial Engineering, 91, 165–177. https://doi.org/10.1016/j.cie.2015.11.018
Manandhar, R., & Tang, J. (2002). The evaluation of bank branch performance using data envelopment analysis: A framework. Journal of High Technology Management Research, 13(1), 1–17. https://doi.org/10.1016/S1047-8310(01)00045-1
Marttunen, M., Lienert, J., & Belton, V. (2017). Structuring problems for multi-criteria decision analysis in practice: A literature review of method combinations. European Journal of Operational Research, 263(1), 1–17. https://doi.org/10.1016/j.ejor.2017.04.041
Misthos, L., Messaris, G., Damigos, D., & Menegaki, M. (2017). Exploring the perceived intrusion of mining into the landscape using the fuzzy cognitive mapping approach. Ecological Engineering, 101, 60–74. https://doi.org/10.1016/j.ecoleng.2017.01.015
Olazabal, M., & Pascual, U. (2016). Use of fuzzy cognitive maps to study urban resilience and transformation. Environmental Innovation and Societal Transitions, 18, 18–40.
Oliveira, P., & Hippel, E. (2011). Users as service innovators: The case of banking services, Research Policy, 40(6), 806–818. https://doi.org/10.1016/j.respol.2011.03.009
Özesmi, U., & Özesmi, L. (2004). Ecological models based on people’s knowledge: A multi-step fuzzy cognitive mapping approach. Ecological Modelling, 176(1–2), 43–64. https://doi.org/10.1016/j.ecolmodel.2003.10.027
Papachristos, G. (2019). System dynamics modelling and simulation for sociotechnical transitions research. Environmental Innovation and Societal Transitions, 31, 248–261. https://doi.org/10.1016/j.eist.2018.10.001
Paradi, J., Rouatt, S., & Zhu, H. (2011). Two-stage evaluation of bank branch efficiency using data envelopment analysis. Omega – The International Journal of Management Science, 39(1), 99–109. https://doi.org/10.1016/j.omega.2010.04.002
Peña, A., Sossa, H., & Gutiérrez, A. (2008). Causal knowledge and reasoning by cognitive maps: Pursuing a holistic approach. Expert Systems with Applications, 35(1/2), 2–18. https://doi.org/10.1016/j.eswa.2007.06.016
Pimpakorn, N., & Patterson, P. (2010). Customer-oriented behaviour of front-line service employees: The need to be both willing and able. Australasian Marketing Journal, 18(2), 57–65. https://doi.org/10.1016/j.ausmj.2010.02.004
Pluchinotta, I., Esposito, D., & Camarda, D. (2019). Fuzzy cognitive mapping to support multi-agent decisions in development of urban policymaking. Sustainable Cities and Society, 46, 101402. https://doi.org/10.1016/j.scs.2018.12.030
Quaranta, A., Raffoni, A., & Visani, F. (2018). A multidimensional approach to measuring bank branch efficiency. European Journal of Operational Research, 266(2), 746–760. https://doi.org/10.1016/j.ejor.2017.10.009
Ramos, J., Ferreira, F., & Barata, J. (2011). Banking services in Portugal: A preliminary analysis to the perception and expectations of front office employees. International Journal of Management and Enterprise Development, 10(2/3), 188–207. https://doi.org/10.1504/IJMED.2011.041549
Reis, J., Amorim, M., & Melão, N. (2019). Multichannel service failure and recovery in a O2O era: A qualitative multi-method research in the banking services industry. International Journal of Production Economics, 215, 24–33. https://doi.org/10.1016/j.ijpe.2018.07.001
Reydet, S., & Carsana, L. (2017). The effect of digital design in retail banking on costumers’ commitment and loyalty: The mediating role of positive affect. Journal of Retailing and Consumer Services, 37, 32–138. https://doi.org/10.1016/j.jretconser.2017.04.003
Ribeiro, M., Ferreira, F, Jalali, M., & Meidutė-Kavaliauskienė, I. (2017). A fuzzy knowledge-based framework for risk assessment of residential real estate investments. Technological and Economic Development of Economy, 23(1), 140–156. https://doi.org/10.3846/20294913.2016.1212742
Rodrigues, T., Montibeller, G., Oliveira, M., & Bana e Costa, C. (2017). Modelling multicriteria value interactions with reasoning maps. European Journal of Operational Research, 258(3), 1054–1071. https://doi.org/10.1016/j.ejor.2016.09.047
Rosenhead, J. (2006). Past, present and future of problem structuring methods. Journal of the Operational Research Society, 57(7), 759–765. https://doi.org/10.1057/palgrave.jors.2602206
Santos, S., Belton, V., & Howick, S. (2008). Enhanced performance measurement using OR: A case study. Journal of the Operational Research Society, 59(6), 762–775. https://doi.org/10.1057/palgrave.jors.2602397
Santos, S., Belton, V., & Howick, S. (2002). Adding value to performance measurement by using system dynamics and multicriteria analysis. International Journal of Operations & Production Management, 22(11), 1246–1272. https://doi.org/10.1108/01443570210450284
Sederati, P., Santos, S., & Pintassilgo, P. (2019). System dynamics in tourism planning and development. Tourism Planning & Development, 16(3), 256–280. https://doi.org/10.1080/21568316.2018.1436586
Sing, M., Love, P., & Liu, H. (2019). Rehabilitation of existing building stock: A system dynamics model to support policy development. Cities, 87, 142–152. https://doi.org/10.1016/j.cities.2018.09.018
Smith, C., & Shaw, D. (2019). The characteristics of problem structuring methods: A literature review. European Journal of Operational Research, 274(2), 403–416. https://doi.org/10.1016/j.ejor.2018.05.003
Song, H., Kim, T., & Kim, T. (2017). The impact of spectrum policies on the secondary spectrum market: A system dynamics approach. Telecommunications Policy, 42(5/6), 460–472. https://doi.org/10.1016/j.telpol.2017.04.004
Sterman, J. (2002). System dynamics: System thinking and modeling for a complex world. MIT Engineering Systems Division.
Sterman, J., Olivia, R., Linderman, K., & Bendoly, E. (2015). System dynamics perspectives and modeling opportunities for research in operations management. Journal of Operations Management, 39/40(1), 1–5. https://doi.org/10.1016/j.jom.2015.07.001
Szopiński, T. (2016). Factors affecting the adoption of online banking in Poland. Journal of Business Research, 69(11), 4763–4768. https://doi.org/10.1016/j.jbusres.2016.04.027
Torres, J., Kunc, M., & O’Brien, F. (2017). Supporting strategy using system dynamics. European Journal of Operational Research, 260(3), 1081–1094. https://doi.org/10.1016/j.ejor.2017.01.018
Wilson, H., & Daniel, E. (2007). The multi-channel challenge: A dynamic capability approach. Industrial Marketing Management, 36(1), 10–20. https://doi.org/10.1016/j.indmarman.2006.06.015
Wu, D., Yang, Z., & Liang, L. (2006). Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank. Expert Systems with Applications, 31(1), 108–115. https://doi.org/10.1016/j.eswa.2005.09.034
Yang, Z. (2009). Assessing the performance of Canadian bank branches using data envelopment analysis. Journal of the Operational Research Society, 60(6), 771–780. https://doi.org/10.1057/palgrave.jors.2602619
Zavadskas, E., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165–179. https://doi.org/10.3846/20294913.2014.892037
Ziv, G., Watson, E., Young, D., Howard, D., Larcom, S., & Tanentzap, A. (2018). The potential impact of Brexit on the energy, water and food nexus in the UK: A fuzzy cognitive mapping approach. Applied Energy, 210, 487–498. https://doi.org/10.1016/j.apenergy.2017.08.033