طراحی شبکه مضامین مدیریت دانش در صنعت بیمه سلامت ایران
محورهای موضوعی : -مدیریت مالی بهداشت و درمانحامد عابدینی 1 , جلال حقیقت منفرد 2 , غلامرضا هاشمزاده خوراسگانی 3
1 - گروه مدیریت فناوری، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران
2 - گروه مدیریت صنعتی ،واحد تهران مرکزی ،دانشگاه آزاد اسلامی تهران ،ایران
3 - گروه مدریت صنعتی ،واحد تهران جنوب ،دانشگاه آزاد اسلامی تهران ،ایران
کلید واژه: مدیریت دانش, چابکی سازمانی, رایانش ابری, صنعت بیمه. بیمه سلامت,
چکیده مقاله :
مقدمه: صنعت بیمه به عنوان یکی از بخشهای اقتصاد تحت تاثیر تحولات شرایط کسب و کار و تجارت قرار دارد و برای موفقیت خود نیازمند ارائه خدمات و پرداختن به کسب و کار بر مبنای الزامات جدید اقتصادی است. تأمین سلامت برای یکایک مردم در هر جامعه ای از حقوق اساسی انسان‌هاست که باید به وسیله دولت‌ها و متولیان امور مورد توجه جدی قرار گیرد. این پژوهش به طراحی شبکه مضامین مدیریت دانش در صنعت بیمه سلامت ایران پرداخته است.
روش پژوهش: این پژوهش از نظر هدف کاربردی، از نظر روش اجرای پژوهش از نوع کیفی می‌باشد و در آن، انتخاب نمونه تحقیق، به صورت هدفمند و در دسترس است. در خصوص شیوه استخراج شاخص‌ها، لازم به ذکر است که این امر با بررسی مبانی نظری موجود و پیاده سازی متن مصاحبه‌ها با استفاده از روش تحلیل تم براون و کلارک در نرم افزار ATLAS TI انجام شد. در این راستا، مصاحبه صورت گرفته تا حد اشباع نظری با 20 نفر از خبرگان صنعت بیمه انجام شد، سپس متن مصاحبه‌ها با استفاده از کدگذاری مورد تجزیه و تحلیل قرار گرفت. پژوهش به بررسی مدیریت دانش با رویکرد چابکی سازمانی مبتنی بر رایانش ابری در صنعت بیمه سلامت ایران پرداخته است.
یافته‌ها: براساس تحلیل مضمون 6 مضمون اصلی شناسایی شده است. این 6 مضمون عبارتند از بلوغ، تصمیم گیری مبتنی بر دانش، انعطاف ساختاری، دانش‌محوری، جامعه‌گرایی و بو‌می‌سازی رایانش ابری. یکی از نتایج اصلی این رویکرد، افزایش سرعت واکنش در مواجهه با تغییرات سریع در بازار بیمه است.
نتیجه‌گیری: استفاده از رایانش ابری در مدیریت دانش بیمه سلامت ایران، نیاز به بلوغ فناوری دارد. مدیریت دانش در صنعت بیمه سلامت ایران، به خاطر پویایی و پیچیدگی‌های زیاد، از اهمیت بالایی برخوردار است. استفاده از رویکرد چابکی سازمانی مبتنی بر رایانش ابری می‌تواند این صنعت را بهبود بخشیده و تأمین کند که سازمان‌های بیمه، از تکنولوژی برتر و دسترسی به داده‌های کلان بهره‌وری بیشتری کسب کنند. یکی از نتایج اصلی این رویکرد، افزایش سرعت واکنش در مواجهه با تغییرات سریع در بازار بیمه است. ابر به عنوان یک زیرساخت اصلی، امکان ارائه سرویس‌های بیمه بهبود یافته و تسریع در فرآیندهای تصمیم‌گیری و پاسخ به نیازهای مشتریان را فراهم می‌کند. این رویکرد می‌تواند کمک کند تا سازمان‌های بیمه از تجربه کاربری بهتری برخوردار شوند و در نتیجه، رضایت مشتریان و افزایش تعاملات با آنان را تضمین کنند.
Introduction: The insurance industry as one of the sectors of the economy is affected by changes in business and trade conditions, and for its success, it needs to provide services and deal with business based on new economic requirements. Providing health for every people in any society is one of the fundamental human rights that should be given serious attention by governments and those in charge of affairs. This research has focused on the design of the network of knowledge management topics in Iran's health insurance industry.
Methods: This research is an applied study in terms of its purpose. Qualitative research method, meta-composite technique and Delphi panel were used to collect data, Shannon's entropy technique was used to evaluate criteria, and CASP was used as a tool for quality control of articles and synthesis of qualitative findings. In this research, 20 senior managers, experts and experts of key health system organizations in five major cities (Tehran, Isfahan, Shiraz, Mashhad and Ahvaz) were selected and examined.
Results: Based on the theme analysis, 6 main themes have been identified. These 6 themes are maturity, knowledge-based decision-making, structural flexibility, knowledge-centeredness, community’s, and localization of cloud computing. One of the main results of this approach is to increase the speed of reaction in the face of rapid changes in the insurance market.
Conclusion: The use of cloud computing in Iran's health insurance knowledge management requires technological maturity. Knowledge management in Iran's health insurance industry is of great importance due to its dynamics and complexities. Using an organizational agility approach based on cloud computing can improve this industry and ensure that insurance organizations gain more productivity from superior technology and access to big data. One of the main results of this approach is to increase the speed of reaction in the face of rapid changes in the insurance market. As a core infrastructure, the cloud provides the possibility of providing improved insurance services and accelerating decision-making processes and responding to customer needs. This approach can help insurance organizations enjoy a better user experience and, as a result, guarantee customer satisfaction and increase interactions with them.
1- Ly, B. The Interplay of Digital Transformational Leadership, Organizational Agility, and Digital Transformation. J Knowl Econ; 2023. https://doi.org/10.1007/s13132-023-01377-8
2- Karunagaran, S., Mathew, S. K., & Lehner, F. Differential cloud adoption: A comparative case study of large enterprises and SMEs in Germany. Information Systems Frontiers, 2019; 21(4): 861–875.
3- de Diego Ruiz, E., Almodóvar, P. & del Valle, I. What drives strategic agility? Evidence from a fuzzy-set qualitative comparative analysis (FsQCA). Int Entrep Manag, 2019; 19: 599–627. https://doi.org/10.1007/s11365-022-00820-7
4- Bui, H. T. M., Nguyen, H. T. M., & Chau, V. S. Strategic Agility Orientation? The Impact of CEO Duality on Corporate Entrepreneurship in Privatized Vietnamese Firms. Journal of General Management, 2019; 42(2): 107–116. https://doi.org/10.1177/0306307019886170
5- Jianwen, C., & Wakil, K. A model for evaluating the vital factors affecting cloud computing adoption: Analysis of the services sector. Kybernetes, 2019; 49(10): 2475–2492. https://doi.org/10.1108/K-06-2019-0434
6- Awwad, A.S., Ababneh, O.M.A. & Karasneh, M. The Mediating Impact of IT Capabilities on the Association between Dynamic Capabilities and Organizational Agility: The Case of the Jordanian IT Sector. Glob J Flex Syst Manag, 2022; 23: 315–330. https://doi.org/10.1007/s40171-022-00303-2
7- Zhang, J., Chen, Z. Exploring Human Resource Management Digital Transformation in the Digital Age. J Knowl Econ; 2023. https://doi.org/10.1007/s13132-023-01214-y
8- Rajapathirana, R. J., & Hui, Y. Relationship between innovation capability, innovation type, and firm performance. Journal of Innovative Knowledge, 2018; 3(1): 44–55.
9- Mellaoui, W., Posso, R., Gebrealif, Y., Bock, E., Altmann, J., Yoon, H. Knowledge Management Framework for Cloud Federation. In: Tserpes, K., et al. Economics of Grids, Clouds, Systems, and Services. GECON 2021. Lecture Notes in Computer Science, 2021; 13072. Springer, Cham. https://doi.org/10.1007/978-3-030-92916-9_10
10- Siadat, Sayyed Hossein. Mozafari Mehr, Azadeh Al-Sadat. Providing a framework for knowledge management system in cloud computing and web 2.0 environment. Research Journal of Information Processing and Management, 2017; 33: 1393-1418.
11- Ahammad, M. F., Glaister, K. W., & Gomes, E. Strategic agility and human resource management. Human Resource Management Review, 2020; 30(1): 100700. https://doi.org/10.1016/j.hrmr.2019.100700
12- Oredo, J., Dennehy, D. Exploring the Role of Organizational Mindfulness on Cloud Computing and Firm Performance: The Case of Kenyan Organizations. Inf Syst Front 25, 2029–2050 (2023). https://doi.org/10.1007/s10796-022-10351-9
13- Clauss, T., Kraus, S., Kallinger, F. L., Bican, P. M., Brem, A., & Kailer, N. Organizational Ambidexterity and Competitive Advantage: The Role of Strategic Agility in the Exploration-Exploitation Paradox. Journal of Innovation & Knowledge, 2021; 6(4): 203–213. https://doi.org/10.1016/j.jik.2020.07.003
14- Gangwar, H. Cloud computing usage and its effect on organizational performance. Human Systems Management, 2017; 36(1): 13–26. https://doi.org/10.3233/HSM-171625
15- Arifiani, L., Prabowo, H., Furinto, A., & Kosasih, W. Responding to Changes in Environmental Turbulence-A Strategy to Driving Business Growth in Facing Economic Downturns. In T. Zhang (Ed.), Circular Economy: Recent Advances, New Perspectives and Applications. IntechOpen. 2021. https://doi.org/10.5772/intechopen.95054
16- Good, D. J., Lyddy, C. J., Glomb, T. M., Bono, J. E., Brown, K. W., Duffy, M. K. & Lazar, S. W. Contemplating Mindfulness at Work: An Integrative Review. Journal of Management, 2016; 42(1): 114–142. https://doi.org/10.1177/0149206315617003
17- Ali, O., Shrestha, A., Ghasemaghaei, M., & Beydoun, G. Assessment of complexity in cloud computing adoption: A case study of local governments in Australia. Information Systems Frontiers, 2022; 24(2): 595–617.
18- El-Haddadeh, R. Digital innovation dynamics influence on organisational adoption: the case of cloud computing services. Information Systems Frontiers, 2020; 22(4): 985–999. https://doi.org/10.1007/s10796-019-09912-2.
19- Doz, Y. L. Fostering Strategic Agility: How Individual Executives and Human Resource Practices Contribute. Human Resource Management Review, 2020; 30(1): 100693. https://doi.org/10.1016/j.hrmr.2019.100693
20- Elali, W. The Importance of Strategic Agility to Business Survival During Corona Crisis and Beyond. International Journal of Business Ethics and Governance, 2021; 4(2): 1–8. https://doi.org/10.51325/ijbeg.v4i2.64
21- Eastburn, R. W. Organizational Mindfulness in Banking: A Discriminating Factor for Firm Performance. Journal of Managerial Issues, 2018; 30(1): 122.
22- Hsu, P. -F. A deeper look at cloud adoption trajectory and dilemma. Information Systems Frontiers, 2022; 24(1), 177–194. https://doi.org/10.1007/s10796-020-10049-w
23- Al-Azzawi, T., & Kaya, T. The Impact of Cloud Computing on Organizational Performance. International Journal of Cloud Applications and Computing (IJCAC), 2021; 11(4): 136–151. https://doi.org/10.4018/IJCAC.2021100108
24- Ambituuni, A., Azizsafaei, F., & Keegan, A. HRM Operational Models and Practices to Enable Strategic Agility in PBOs: Managing Paradoxical Tensions. Journal of Business Research, 2021; 133:" 170–182. https://doi.org/10.1016/j.jbusres.2021.04.048
25- Haneberg, D. H. How Combinations of Network Participation, Firm Age and Firm Size Explain SMEs’ Responses to COVID-19. Small Enterprise Research, 2021; 28(3): 229–246. https://doi.org/10.1080/13215906.2021.1989626
26- Khodabakhshi, Amir, Karbasi, Ali. Determining the relationship between knowledge management and agility of the main and key processes of the organization with an emphasis on the changing role of organizational changes (case study: Iran Oil Pipelines and Telecommunications Company - Isfahan region), the fourth national congress of new technologies of Iran with the aim of achieving sustainable development, Tehran; 2015.
27- Ilmudeen, A. Leveraging IT-Enabled Dynamic Capabilities to Shape Business Process Agility and Firm Innovative Capability: Moderating Role of Turbulent Environment. Review of Managerial Science; 2021: 1–39. https://doi.org/10.1007/s11846-021-00501-9
28- Ardi, A., Djati, S., Bernarto, I., Sudibjo, N., Yulianeu, A., Nanda, H., & Nanda, K. The relationship between digital transformational leadership styles and knowledge-based empowering interaction for increasing organisational innovativeness. International Journal of Innovation, Creativity and Change, 2020; 11(3): 259–277.
29- Ghasemaghaei, M., Hassanein, K., & Turel, O. Increasing firm agility through the use of data analytics: The role of fit. Decision Support Systems, 2017; 101: 95–105. https://doi.org/10.1016/j.dss.2017.06.004
30- Marx, A. Towards a More Robust Model Specification in QCA: Results from a Methodological Experiment. COMPASS Working Papers; 2006.
31- Rane, S. B., Narvel, Y. A. M., & Bhandarkar, B. M. Developing strategies to improve agility in the project procurement management (PPM) process. Business Process Management Journal, 2020; 26(1): 257–286. https://doi.org/10.1108/BPMJ-07-2017-0196
32- Menon, S., & Suresh, M. Factors influencing organizational agility in higher education. Benchmarking: An International Journal, 2021; 28(1): 307–332. https://doi.org/10.1108/BIJ-04-2020-0151
33- Teichert, R. Digital transformation maturity: A systematic review of literature. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2019; 67(6): 1673–1687.
34- Cegarra-Navarro, J.-G., Soto-Acosta, P., & Wensley, A. K. P. Structured knowledge processes and firm performance: The role of organizational agility. Journal of Business Research, 2016; 69(5): 1544–1549. https://doi.org/10.1016/j.jbusres.2015.10.014
35- Dennehy, D., Oredo, J., Spanaki, K., Despoudi, S., & Fitzgibbon, M. Supply chain resilience in mindful humanitarian aid organizations: The role of big data analytics. International Journal of Operations & Production Management, 2021; 41(9): 1417–1441.
36- Durão, N., Ferreira, M. J., Pereira, C. S., & Moreira, F. Current and future state of Portuguese organizations towards digital transformation. Procedia Computer Science, 2019; 164: 25–32. https://doi.org/10.1016/j.procs.2019.12.150
37- Jesse, N. Organizational evolution - How digital disruption enforces organizational agility. IFAC-PapersOnLine, 2018; 51(30): 486–491. https://doi.org/10.1016/j.ifacol.2018.11.310
38- Gegenhuber, T., Logue, D., Hinings, C. R., & Barrett, M. Institutional perspectives on digital transformation. In T. Gegenhuber, D. Logue, C. R. Hinings, & M. Barrett (Eds.), Digital Transformation and Institutional Theory, 2022; 83: 1–32. Emerald Publishing Limited.
39- Li, F. Leading digital transformation: Three emerging approaches for managing the transition. International Journal of Operations & Production Management, 2020; 40(6): 809–817. https://doi.org/10.1108/IJOPM-04-2020-0202
40- Kara, E., Kirpik, G., & Kaya, A. A research on digital violence in social media. In Handbook of Research on Digital Violence and Discrimination Studies. IGI Global; 2022.
41- Dubey, R., Gunasekaran, A., Childe, S. J., Blome, C., & Papadopoulos, T. Big data and predictive analytics and manufacturing performance: Integrating institutional theory, resource-based view and big data culture. British Journal of Management, 2019; 30(2): 341–361. https://doi.org/10.1111/1467-8551.12355
42- Bouaynaya, W. Characterization of cloud computing reversibility as explored by the DELPHI method. Information Systems Frontiers, 2020; 22(6): 1505–1518.
43- Pajouesh, Shabnam, Ansari Far, Seyed Saeed. Meta-analysis of organizational culture with organizational agility approach based on organizational knowledge. International conference on change and transformation management; 2015.
44- Kanan, Seyed Mehrdad, Pilehvari, Nazanin, Investigating the impact of cloud computing technology on organizational agility in the banking industry with a fuzzy decision-making approach (Refah Kargaran Bank case study), the second international conference on knowledge-based research in computer engineering and information technology, Tehran; 2016.
45- Khadivar, Amina, Dartaj, Fatemeh. Providing a framework for success in implementing knowledge management systems based on cloud computing. Management Research in Iran, 2021; 20: 93-118.
46- Chang, V. Presenting cloud business performance for manufacturing organizations. Information Systems Frontiers, 2020; 22(1): 59–75.
47- Chen, X., Guo, M., & Shangguan, W. Estimating the impact of cloud computing on firm performance: An empirical investigation of listed firms. Information & Management, 2022; 59(3): 103603. https://doi.org/10.1016/j.im.2022.103603.
