How does technological innovation impact the service time and the attraction of new customers in the financial sector? Evidence from an emerging economy
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DOI: 10.1007/s12063-023-00437-1
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- Yu, Song-min & Fan, Ying & Zhu, Lei & Eichhammer, Wolfgang, 2020. "Modeling the emission trading scheme from an agent-based perspective: System dynamics emerging from firms’ coordination among abatement options," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1113-1128.
- William Rand & Christian Stummer, 2021. "Agent‐based modeling of new product market diffusion: an overview of strengths and criticisms," Annals of Operations Research, Springer, vol. 305(1), pages 425-447, October.
- Hoyeop Lee & Jongsu Lim & Keeheon Lee & Chang Ouk Kim, 2019. "Agent simulation-based ordinal optimisation for new product design," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(3), pages 502-515, March.
- Elyn Lizeth Solano-Charris & Carlos D. Paternina-Arboleda, 2013. "Simulation model of the supply chain on a naval shipyard," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 13(3), pages 280-297.
- Rand, William & Rust, Roland T., 2011. "Agent-based modeling in marketing: Guidelines for rigor," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 181-193.
- Samitas, Aristeidis & Polyzos, Stathis & Siriopoulos, Costas, 2018. "Brexit and financial stability: An agent-based simulation," Economic Modelling, Elsevier, vol. 69(C), pages 181-192.
- Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
- C M Macal, 2016. "Everything you need to know about agent-based modelling and simulation," Journal of Simulation, Taylor & Francis Journals, vol. 10(2), pages 144-156, May.
- Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
- Joao Aguirre, 2015. "Inteligencia estratégica: un sistema para gestionar la innovación," Estudios Gerenciales, Universidad Icesi, January.
- Hu, Hai-hua & Lin, Jun & Qian, Yanjun & Sun, Jian, 2018. "Strategies for new product diffusion: Whom and how to target?," Journal of Business Research, Elsevier, vol. 83(C), pages 111-119.
- Petra Ahrweiler, 2017. "Agent-based simulation for science, technology, and innovation policy," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 391-415, January.
- Ashkan Negahban & Jeffrey S. Smith, 2018. "A joint analysis of production and seeding strategies for new products: an agent-based simulation approach," Annals of Operations Research, Springer, vol. 268(1), pages 41-62, September.
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Keywords
Banking clients; Service level; Mobile App; Agent-based simulation; Bass diffusion model;All these keywords.
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