Practices of Managerial Analytics in IoT-based Sustainable Employee Training and Organizational Performance at the Bank and Financial Institutes

Main Article Content

Md. Mohsin Kabir
Mohammad Saddam Hosen
Dr. Mohammad Thoufiqul Islam
Shamal Chandra Hawlader

Abstract

The study has analyzed managerial analytics integrated with the Internet of Things (IoT) that has mobilized sustainable employee training and organizational performance in the banking sector. The intention is to evaluate the managerial analytics practiced by Bangladeshi banks and financial institutes (FIs) and their impact on employees' training and performance. The present research investigates the implementation of sustainable employee training initiatives and effectiveness in working fields using IoT, the historical extant training practices of the organization, and the relationship between managerial analytics factors that affect the banking system. Here in this study, a scenario-based approach was used to demonstrate the integration of smart training for employees with IoT using managerial analytics tools, and a cross-sectional research strategy was also experienced among the related employees of Bangladesh in Dhaka city. And 143 purposive sampling metadata were analyzed. We offer a model for evaluating the efficacy of managerial analytics on employees, which enhances operational and learning outcomes. The study's results confirmed the validity of the proposed model for evaluating the training of employees. The findings have identified the indicators- training content and attitude as analytical patterns, and IoT technology and monitoring as technological that significantly impacts the employees' performance. It emphasizes the managerial analytics concept that facilitates training and development for employees with newly required competencies in the banking sector through IoT. Managerial analytics integrated into IoT-based employee training is significantly effective among operations and promotes smart performance observation in the banking sector. These insights offer valuable guidance to bankers, policymakers, and managerial analysts striving to incorporate sustainable practices into their operations to foster long-term growth in the banking sector.

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Md. Mohsin Kabir, Mohammad Saddam Hosen, Dr. Mohammad Thoufiqul Islam, and Shamal Chandra Hawlader , Trans., “Practices of Managerial Analytics in IoT-based Sustainable Employee Training and Organizational Performance at the Bank and Financial Institutes”, IJMH, vol. 10, no. 11, pp. 13–24, Jul. 2024, doi: 10.35940/ijmh.L1732.10110724.
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[1]
Md. Mohsin Kabir, Mohammad Saddam Hosen, Dr. Mohammad Thoufiqul Islam, and Shamal Chandra Hawlader , Trans., “Practices of Managerial Analytics in IoT-based Sustainable Employee Training and Organizational Performance at the Bank and Financial Institutes”, IJMH, vol. 10, no. 11, pp. 13–24, Jul. 2024, doi: 10.35940/ijmh.L1732.10110724.
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References

Abdussamad, Z., Tweneboah Agyei, I., Sipahi Döngül, E., Raj, R., & Effendy, F. (2022). Impact of Internet of Things (IOT) on Human Resource Management: A review. Materials Today: Proceedings, 56, 3534–3543. https://doi.org/10.1016/j.matpr.2021.11.247

Ahmed, F., Callaghan, D., & Arslan, A. (2024). A multilevel conceptual framework on green practices: Transforming policies into actionable leadership and employee behavior. Scandinavian Journal of Psychology, 65(3), 381–393. https://doi.org/10.1111/sjop.12981

Al-Dmour, H., Saad, N., Basheer Amin, E., Al-Dmour, R., & Al-Dmour, A. (2021). The influence of the practices of big data analytics applications on bank performance: Filed study. VINE Journal of Information and Knowledge Management Systems, 53(1), 119–141. https://doi.org/10.1108/VJIKMS-08-2020-0151

Alexopoulos, A., Becerra, Y., Boehm, O., Bravos, G., Chatzigiannakis, V., Cugnasco, C., Demetriou, G., Eleftheriou, I., Fodor, L., Fotis, S., Ioannidis, S., Jakovetic, D., Kallipolitis, L., Katusic, V., Kavakli, E., Kopanaki, D., Leventis, C., Marcos, M. M., De Pozuelo, R. M., … Vinov, M. (2022). Big Data Analytics in the Banking Sector: Guidelines and Lessons Learned from the CaixaBank Case. In E. Curry, S. Auer, A. J. Berre, A. Metzger, M. S. Perez, & S. Zillner (Eds.), Technologies and Applications for Big Data Value (pp. 273–297). Springer International Publishing. https://doi.org/10.1007/978-3-030-78307-5_13

Al-Hitmi, M., & Sherif, K. (2018). Employee perceptions of fairness toward IoT monitoring. VINE Journal of Information and Knowledge Management Systems, 48(4), 504–516. https://doi.org/10.1108/VJIKMS-01-2018-0007

Almazmomi, N., Ilmudeen, A., & Qaffas, A. A. (2022). The impact of business analytics capability on data-driven culture and exploration: Achieving a competitive advantage. Benchmarking: An International Journal, 29(4), 1264–1283. https://doi.org/10.1108/BIJ-01-2021-0021

Anbazhagan, A., Guru, K., Masood, G., Mandaviya, M., Dhiman, V., & Naved, M. (2023). Critically Analyzing the Concept of Internet of Things (IOT) and How It Impacts Employee and Organizational Performance. In S. Yadav, A. Haleem, P. K. Arora, & H. Kumar (Eds.), Proceedings of Second International Conference in Mechanical and Energy Technology (Vol. 290, pp. 121–130). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-0108-9_13

Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29–44. https://doi.org/10.1016/j.accinf.2017.03.003

Awotunde, J. B., Jimoh, R. G., Ogundokun, R. O., Misra, S., & Abikoye, O. C. (2022). Big Data Analytics of IoT-Based Cloud System Framework: Smart Healthcare Monitoring Systems. In S. Misra, A. Kumar Tyagi, V. Piuri, & L. Garg (Eds.), Artificial Intelligence for Cloud and Edge Computing (pp. 181–208). Springer International Publishing. https://doi.org/10.1007/978-3-030-80821-1_9

Aziz, N. A., Long, F., & Wan Hussain, W. M. H. (2023). Examining the Effects of Big Data Analytics Capabilities on Firm Performance in the Malaysian Banking Sector. International Journal of Financial Studies, 11(1), 23. https://doi.org/10.3390/ijfs11010023

Bag, S., Wood, L. C., Xu, L., Dhamija, P., & Kayikci, Y. (2020). Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources, Conservation and Recycling, 153, 104559. https://doi.org/10.1016/j.resconrec.2019.104559

Bakhshi, T., & Ahmed, M. (2018). IoT-Enabled Smart City Waste Management using Machine Learning Analytics. 2018 2nd International Conference on Energy Conservation and Efficiency (ICECE), 66–71. https://doi.org/10.1109/ECE.2018.8554985

Bany Mohammed, A., Al-Okaily, M., Qasim, D., & Khalaf Al-Majali, M. (2024). Towards an understanding of business intelligence and analytics usage: Evidence from the banking industry. International Journal of Information Management Data Insights, 4(1), 100215. https://doi.org/10.1016/j.jjimei.2024.100215

Cotes, J., & Ugarte, S. M. (2021). A systemic and strategic approach for training needs analysis for the International Bank. Journal of Business Research, 127, 464–473. https://doi.org/10.1016/j.jbusres.2019.05.002

Ennafiri, M., Charaf, M. E. H., & Ait Madi, A. (2022). Customer Service Enhancement in Banking Field using IoT Technologies. 2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), 1–6. https://doi.org/10.1109/IRASET52964.2022.9738035

Ernst, J., & Koll, H. (2024). Managerial pedagogy and organizational power dynamics in the context of neoliberal organizational transition. Scandinavian Journal of Management, 101342. https://doi.org/10.1016/j.scaman.2024.101342

Fakir, M. S. I., & Khatoon, A. (2021). Does Labour Relations Perspective Condition Human Resource Management?: A Comparative Analysis in three European Countries. International Journal of Advances in Engineering and Management (IJAEM), 3(1), 201–208. https://www.ijaem.net/

Fauziyah, U., Kaburuan, E. R., Wang, G., & Aqsha. (2019). Gamification for Employee Training Platform in Banking Industries. 2019 International Conference on Information Management and Technology (ICIMTech), 503–508. https://doi.org/10.1109/ICIMTech.2019.8843750

George, D., & Mallery, P. (2019). IBM SPSS Statistics 26 Step by Step: A Simple Guide and Reference (6th ed.). Routledge. https://doi.org/10.4324/9780429056765

Ghasemaghaei, M., Ebrahimi, S., & Hassanein, K. (2018). Data analytics competency for improving firm decision making performance. The Journal of Strategic Information Systems, 27(1), 101–113. https://doi.org/10.1016/j.jsis.2017.10.001

Ghatasheh, N., Faris, H., AlTaharwa, I., Harb, Y., & Harb, A. (2020). Business Analytics in Telemarketing: Cost-Sensitive Analysis of Bank Campaigns Using Artificial Neural Networks. Applied Sciences, 10(7), Article 7. https://doi.org/10.3390/app10072581

Gil, A. J., García-Alcaraz, J. L., Mataveli, M., & Tobias, C. (2023). The interrelationships between organisational climate and job satisfaction and their impact on training outcomes. Journal of Workplace Learning, 35(7), 613–631. https://doi.org/10.1108/JWL-03-2023-0050

Godavarthi, B., Dhar, M., Devi, S. A., Raju, S. S., Balaram, A., & Srilakshmi, G. (2023). Blockchain integration with the internet of things for the employee performance management. The Journal of High Technology Management Research, 34(2), 100468. https://doi.org/10.1016/j.hitech.2023.100468

Gronau, N., Ullrich, A., & Teichmann, M. (2017). Development of the Industrial IoT Competences in the Areas of Organization, Process, and Interaction Based on the Learning Factory Concept. Procedia Manufacturing, 9, 254–261. https://doi.org/10.1016/j.promfg.2017.04.029

Gupta, T., Gupta, N., Agrawal, A., Agrawal, A., & Kansal, K. (2019). Role of Big Data Analytics In Banking. 2019 International Conference on Contemporary Computing and Informatics (IC3I), 222–227. https://doi.org/10.1109/IC3I46837.2019.9055616

Hajjaji, Y., Boulila, W., Farah, I. R., Romdhani, I., & Hussain, A. (2021). Big data and IoT-based applications in smart environments: A systematic review. Computer Science Review, 39, 100318. https://doi.org/10.1016/j.cosrev.2020.100318

He, W., Hung, J.-L., & Liu, L. (2022). Impact of big data analytics on banking: A case study. Journal of Enterprise Information Management, 36(2), 459–479. https://doi.org/10.1108/JEIM-05-2020-0176

Jahan, S. (2024, April 21). Bank mergers: All dimensions must. Opinion. https://www.thedailystar.net/ opinion/views/news/bank-mergers-all-dimensions-must-be-considered-3591266

Jungert, T., Gradito Dubord, M., Högberg, M., & Forest, J. (2022). Can managers be trained to further support their employees’ basic needs and work engagement: A manager training program study. International Journal of Training and Development, 26(3), 472–494. https://doi.org/10.1111/ijtd.12267

Kalnoor, G., & Gowrishankar, S. (2021). IoT-based smart environment using intelligent intrusion detection system. Soft Computing, 25(17), 11573–11588. https://doi.org/10.1007/s00500-021-06028-1

Kang, M., & Park, M. J. (2019). Employees’ judgment and decision making in the banking industry: The perspective of heuristics and biases. International Journal of Bank Marketing, 37(1), 382–400. https://doi.org/10.1108/IJBM-04-2018-0111

Kato, T., & Koizumi, M. (2024). Tactics to mitigate the negative impact of introducing advanced technology on employees: Evidence from large listed companies in Japan. Computers in Human Behavior Reports, 14, 100423. https://doi.org/10.1016/j.chbr.2024.100423

Kaur, S. J., & Ali, L. (2021). Understanding bank employees’ perception towards technology enabled banking: A developing country perspective. Journal of Financial Services Marketing, 26(3), 129–143. https://doi.org/10.1057/s41264-021-00100-5

Khanboubi, F., Boulmakoul, A., & Tabaa, M. (2019). Impact of digital trends using IoT on banking processes. Procedia Computer Science, 151, 77–84. https://doi.org/10.1016/j.procs.2019.04.014

Kickmeier-Rust, M. D., Hann, P., & Leitner, M. (2019). Increasing Learning Motivation: An Empirical Study of VR Effects on the Vocational Training of Bank Clerks. In E. Van Der Spek, S. Göbel, E. Y.-L. Do, E. Clua, & J. Baalsrud Hauge (Eds.), Entertainment Computing and Serious Games (Vol. 11863, pp. 111–118). Springer International Publishing. https://doi.org/10.1007/978-3-030-34644-7_9

Knight, C., Patterson, M., & Dawson, J. (2019). Work engagement interventions can be effective: A systematic review. European Journal of Work and Organizational Psychology, 28(3), 348–372. https://doi.org/10.1080/1359432X.2019.1588887

Kraus, M., Feuerriegel, S., & Oztekin, A. (2020). Deep learning in business analytics and operations research: Models, applications and managerial implications. European Journal of Operational Research, 281(3), 628–641. https://doi.org/10.1016/j.ejor.2019.09.018

Kravčík, M., Ullrich, C., & Igel, C. (2018). The Potential of the Internet of Things for Supporting Learning and Training in the Digital Age. In O. Zlatkin-Troitschanskaia, G. Wittum, & A. Dengel (Eds.), Positive Learning in the Age of Information: A Blessing or a Curse? (pp. 399–412). Springer Fachmedien. https://doi.org/10.1007/978-3-658-19567-0_24

Kuhn, C., & Lucke, D. (2021). Supporting the Digital Transformation: A Low-Threshold Approach for Manufacturing Related Higher Education and Employee Training. Procedia CIRP, 104, 647–652. https://doi.org/10.1016/j.procir.2021.11.109

Lee, N. Y., Zablah, A. R., & Noble, S. M. (2023). A meta-analytic investigation of the organizational identification – Job performance relationship in the frontlines. Journal of Retailing, 99(3), 370–384. https://doi.org/10.1016/j.jretai.2023.07.003

Li, D., Deng, L., Liu, W., & Su, Q. (2020). Improving communication precision of IoT through behavior-based learning in smart city environment. Future Generation Computer Systems, 108, 512–520. https://doi.org/10.1016/j.future.2020.02.053

Li, Q., Kumar, P., & Alazab, M. (2022). IoT-assisted physical education training network virtualization and resource management using a deep reinforcement learning system. Complex & Intelligent Systems, 8(2), 1229–1242. https://doi.org/10.1007/s40747-021-00584-7

Mahmoud, A., Salem, A., & Elsamahy, E. (2022). Real-Time Machine Learning-Based Framework for the Analysis of Banking Financial Data. In D. A. Magdi, Y. K. Helmy, M. Mamdouh, & A. Joshi (Eds.), Digital Transformation Technology (pp. 407–421). Springer. https://doi.org/10.1007/978-981-16-2275-5_25

Maja, M. M., & Letaba, P. (2022). Towards a data-driven technology roadmap for the bank of the future: Exploring big data analytics to support technology roadmapping. Social Sciences & Humanities Open, 6(1), 100270. https://doi.org/10.1016/j.ssaho.2022.100270

Mathipriya, B., Minhaj, I., Rodrigo, L. D. C. P., Abiylackshmana, P., & Kahandawaarachchi, K. A. D. C. P. (2019). Employee Readiness towards Artificial Intelligence in Sri Lankan Banking Context. 2019 International Conference on Smart Applications, Communications and Networking (SmartNets), 1–6. https://doi.org/10.1109/SmartNets48225.2019.9069797

McIver, D., Lengnick-Hall, M. L., & Lengnick-Hall, C. A. (2018). A strategic approach to workforce analytics: Integrating science and agility. Business Horizons, 61(3), 397–407. https://doi.org/10.1016/j.bushor.2018.01.005

Minbaeva, D. B. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3), 701–713. https://doi.org/10.1002/hrm.21848

Mone, E., London, M., Mone, E. M., & London, M. (2018). Employee Engagement Through Effective Performance Management: A Practical Guide for Managers (2nd ed.). Routledge. https://doi.org/10.4324/9781315626529

Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2019). IBM SPSS for Introductory Statistics: Use and Interpretation (6th ed.). Routledge. https://doi.org/10.4324/9780429287657

Morton, S., Michaelides, R., Roca, T., & Wagner, H. (2019). Increasing Employee Engagement in Organizational Citizenship Behaviors Within Continuous Improvement Programs in Manufacturing: The HR Link. IEEE Transactions on Engineering Management, 66(4), 650–662. https://doi.org/10.1109/TEM.2018.2854414

Moyeenudin, H. M., & Anandan, R. (2021). IoT Implementation at Global Enterprises for Progressive Human Resource Practices. In S.-L. Peng, R.-X. Hao, & S. Pal (Eds.), Proceedings of First International Conference on Mathematical Modeling and Computational Science (Vol. 1292, pp. 109–117). Springer Singapore. https://doi.org/10.1007/978-981-33-4389-4_12

Nasar, N., Ray, S., Umer, S., & Mohan Pandey, H. (2021). Design and data analytics of electronic human resource management activities through Internet of Things in an organization. Software: Practice and Experience, 51(12), 2411–2427. https://doi.org/10.1002/spe.2817

Nicolaescu, S. S., Florea, A., Kifor, C. V., Fiore, U., Cocan, N., Receu, I., & Zanetti, P. (2020). Human capital evaluation in knowledge-based organizations based on big data analytics. Future Generation Computer Systems, 111, 654–667. https://doi.org/10.1016/j.future.2019.09.048

Nižetić, S., Šolić, P., López-de-Ipiña González-de-Artaza, D., & Patrono, L. (2020). Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future. Journal of Cleaner Production, 274, 122877. https://doi.org/10.1016/j.jclepro.2020.122877

Nocker, M., & Sena, V. (2019). Big Data and Human Resources Management: The Rise of Talent Analytics. Social Sciences, 8(10), Article 10. https://doi.org/10.3390/socsci8100273

Nozari, H., Fallah, M., & SzmelterJarosz, A. (2021). A conceptual framework of green smart IoT-based supply chain management. International Journal of Research in Industrial Engineering, 10(1). https://doi.org/10.22105/riej.2021.274859.1189

Padmaja, K., & Seshadri, R. (2021). Analytics on real time security attacks in healthcare, retail and banking applications in the cloud. Evolutionary Intelligence, 14(2), 595–605. https://doi.org/10.1007/s12065-019-00337-z

Palmaccio, M., Dicuonzo, G., & Belyaeva, Z. S. (2021). The internet of things and corporate business models: A systematic literature review. Journal of Business Research, 131, 610–618. https://doi.org/10.1016/j.jbusres.2020.09.069

Pawar, P., TarunKumar, M., & Vittal K., P. (2020). An IoT based Intelligent Smart Energy Management System with accurate forecasting and load strategy for renewable generation. Measurement, 152, 107187. https://doi.org/10.1016/j.measurement.2019.107187

Pillai, R., & Srivastava, K. B. L. (2022). Smart HRM 4.0 for achieving organizational performance: A dynamic capability view perspective. International Journal of Productivity and Performance Management, 73(2), 476–496. https://doi.org/10.1108/IJPPM-04-2022-0174

R, Arjun., Kuanr, A., & Kr, S. (2021). Developing banking intelligence in emerging markets: Systematic review and agenda. International Journal of Information Management Data Insights, 1(2), 100026. https://doi.org/10.1016/j.jjimei.2021.100026

Rahmani, A. M., Ehsani, A., Mohammadi, M., Mohammed, A. H., Karim, S. H. T., & Hosseinzadeh, M. (2021). A new model for analyzing the role of new ICT-based technologies on the success of employees’ learning programs. Kybernetes, 51(6), 2156–2171. https://doi.org/10.1108/K-02-2021-0164

Rana, G., Sharma, R., & Goel, A. K. (2019). Unraveling the Power of Talent Analytics: Implications for Enhancing Business Performance. In Rajagopal & R. Behl (Eds.), Business Governance and Society: Analyzing Shifts, Conflicts, and Challenges (pp. 29–41). Springer International Publishing. https://doi.org/10.1007/978-3-319-94613-9_3

Ravi, V., & Kamaruddin, S. (2017). Big Data Analytics Enabled Smart Financial Services: Opportunities and Challenges. In P. K. Reddy, A. Sureka, S. Chakravarthy, & S. Bhalla (Eds.), Big Data Analytics (Vol. 10721, pp. 15–39). Springer International Publishing. https://doi.org/10.1007/978-3-319-72413-3_2

Rique, T., Perkusich, M., Dantas, E., Albuquerque, D., Gorgônio, K., Almeida, H., & Perkusich, A. (2023). On Adopting Software Analytics for Managerial Decision-Making: A Practitioner’s Perspective. IEEE Access, 11, 73145–73163. https://doi.org/10.1109/ACCESS.2023.3294823

Rocchetta, R., Crespo, L. G., & Kenny, S. P. (2020). A scenario optimization approach to reliability-based design. Reliability Engineering & System Safety, 196, 106755. https://doi.org/10.1016/j.ress.2019.106755

Salleh, K. A., & Janczewski, L. (2019). Security Considerations in Big Data Solutions Adoption: Lessons from a Case Study on a Banking Institution. Procedia Computer Science, 164, 168–176. https://doi.org/10.1016/j.procs.2019.12.169

Saqlain, Piao, Shim, & Lee. (2019). Framework of an IoT-based Industrial Data Management for Smart Manufacturing. Journal of Sensor and Actuator Networks, 8(2), 25. https://doi.org/10.3390/jsan8020025

Sawarynski, K. E., & Baxa, D. M. (2019). Utilization of an online module bank for a research training curriculum: Development, implementation, evolution, evaluation, and lessons learned. Medical Education Online, 24(1), 1611297. https://doi.org/10.1080/10872981.2019.1611297

Saxena, S., & Ali Said Mansour Al-Tamimi, T. (2017). Big data and Internet of Things (IoT) technologies in Omani banks: A case study. Foresight, 19(4), 409–420. https://doi.org/10.1108/FS-03-2017-0010

Setiadi, N. J., Christianto, A., & Sutanto, H. (2022). The Effectiveness of Digital Culture and Online Training in Improving Learning Agility of Bank Employees as an Adaptation Step to the Covid-19 Pandemic (Empirical Study on a Branch of Commercial Bank). 2022 10th International Conference on Cyber and IT Service Management (CITSM), 01–04. https://doi.org/10.1109/CITSM56380.2022.9935957

Shah, N., Irani, Z., & Sharif, A. M. (2017). Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors. Journal of Business Research, 70, 366–378. https://doi.org/10.1016/j.jbusres.2016.08.010

Sievers, F., Reil, H., Rimbeck, M., Stumpf-Wollersheim, J., & Leyer, M. (2021). Empowering employees in industrial organizations with IoT in their daily operations. Computers in Industry, 129, 103445. https://doi.org/10.1016/j.compind.2021.103445

Simsek, S., Albizri, A., Johnson, M., Custis, T., & Weikert, S. (2020). Predictive data analytics for contract renewals: A decision support tool for managerial decision-making. Journal of Enterprise Information Management, 34(2), 718–732. https://doi.org/10.1108/JEIM-12-2019-0375

Singh, R., Goel, G., Ghosh, P., & Sinha, S. (2022). Mergers in Indian public sector banks: Can human resource practices ensure effective implementation of change? Management Decision, 60(3), 606–633. https://doi.org/10.1108/MD-09-2020-1279

Skylar Powell, K., & Yalcin, S. (2010). Managerial training effectiveness: A meta‐analysis 1952‐2002. Personnel Review, 39(2), 227–241. https://doi.org/10.1108/00483481011017435

Sousa, M. J., Pesqueira, A. M., Lemos, C., Sousa, M., & Rocha, Á. (2019). Decision-Making based on Big Data Analytics for People Management in Healthcare Organizations. Journal of Medical Systems, 43(9), 290. https://doi.org/10.1007/s10916-019-1419-x

Staras, S. A. S., Wollney, E. N., Emerson, L. E., Silver, N., Dziegielewski, P. T., Hansen, M. D., Sanchez, G., D’Ingeo, D., Johnson‐Mallard, V., Renne, R., Fredenburg, K., Gutter, M., Zamojski, K., Vandeweerd, C., & Bylund, C. L. (2024). Identifying locally actionable strategies to increase participant acceptability and feasibility to participate in Phase I cancer clinical trials. Health Expectations, 27(1), e13920. https://doi.org/10.1111/hex.13920

Stergiou, C. L., & Psannis, K. E. (2022). Digital twin intelligent system for industrial internet of things-based big data management and analysis in cloud environments. Virtual Reality & Intelligent Hardware, 4(4), 279–291. https://doi.org/10.1016/j.vrih.2022.05.003

Tabesh, P., Mousavidin, E., & Hasani, S. (2019). Implementing big data strategies: A managerial perspective. Business Horizons, 62(3), 347–358. https://doi.org/10.1016/j.bushor.2019.02.001

Tanasescu, L. G., Vines, A., Bologa, A. R., & Vîrgolici, O. (2024). Data Analytics for Optimizing and Predicting Employee Performance. Applied Sciences, 14(8), 3254. https://doi.org/10.3390/app14083254

Taufiq, A., Raharjo, T., & Wahbi, A. (2020). Scrum Evaluation to Increase Software Development Project Success: A Case Study of Digital Banking Company. 2020 International Conference on Advanced Computer Science and Information Systems (ICACSIS), 241–246. https://doi.org/10.1109/ICACSIS51025.2020.9263235

The Daily Star. (2024, April 16). No more bank merger proposals for now: BB. Star Business Report. https://www.thedailystar.net/business/economy/news/no-more-bank-merger-proposals-now-bb-3588066

Tuli, F. A., Varghese, A., & Ande, J. R. P. K. (2018). Data-Driven Decision Making: A Framework for Integrating Workforce Analytics and Predictive HR Metrics in Digitalized Environments. Global Disclosure of Economics and Business, 7(2), 109–122. https://doi.org/10.18034/gdeb.v7i2.724

VenkateswaraRao, M., Vellela, S., B, V. R., Vullam, N., Sk, K. B., & D, R. (2023). Credit Investigation and Comprehensive Risk Management System based Big Data Analytics in Commercial Banking-2023. 9th International Conference on Advanced Computing and Communication Systems (ICACCS), 2387–2391. https://doi.org/10.1109/ICACCS57279.2023.10113084

Yahia, N. B., Hlel, J., & Colomo-Palacios, R. (2021). From Big Data to Deep Data to Support People Analytics for Employee Attrition Prediction. IEEE Access, 9, 60447–60458. https://doi.org/10.1109/ACCESS.2021.3074559

Yaw Obeng, A., & Boachie, E. (2018). The impact of IT-technological innovation on the productivity of a bank’s employee. Cogent Business & Management, 5(1), 1470449. https://doi.org/10.1080/23311975.2018.1470449

Zafar, N., Asadullah, M. A., Haq, M. Z. U., Siddiquei, A. N., & Nazir, S. (2022). Design thinking: A cognitive resource for improving workforce analytics and training evaluation. European Journal of Training and Development, 47(5/6), 653–675. https://doi.org/10.1108/EJTD-09-2021-0150

Zawadzki, P., Zywicki, K., Bun, P., & Gorski, F. (2020). Employee Training in an Intelligent Factory Using Virtual Reality. IEEE Access, 8, 135110–135117. https://doi.org/10.1109/ACCESS.2020.3010439

Zhao, J., Karimzadeh, M., Snyder, L. S., Surakitbanharn, C., Qian, Z. C., & Ebert, D. S. (2019). MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies. IEEE Transactions on Visualization and Computer Graphics, 1–1. https://doi.org/10.1109/TVCG.2019.2934603

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