ارائه الگوی پیاده‌سازی اینترنت انرژی در سازمان‌های دولتی کشور با رویکرد تحلیل گزینه‌های استراتژیک و نگاشت علی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد، گروه مدیریت بازاریابی، تهران، ایران.

2 مربی، گروه مدیریت، مرکز علمی – کاربردی شرکت لوله‌سازی، اهواز، ایران.

10.30473/mrs.2021.54716.1435

چکیده

چکیده
هدف: اینترنت انرژی رویکرد جدیدی است که در پاسخ به بحران مصرف انرژی و کنترل منابع تجدیدناپذیر مطرح شده است. ازاین‌رو، این پژوهش با هدف الگوسازی پیاده‌سازی اینترنت انرژی در سازمان‌های دولتی کشور انجام شده است
روش‌شناسی: پژوهش از نظر هدف مطالعه‌ای بنیادین و از منظر فلسفی با رویکردی مبتنی بر پارادایم تفسیری انجام شده است. از منظر روش و بازه زمانی گردآوری داده‌ها نیز در دسته مطالعات پیمایش مقطعی قرار می‌گیرد. جامعه آماری پژوهش شامل مدیران تحقیقات استراتژیک دولت بوده که با روش نمونه‌گیری غیراحتمالی و به صورت هدفمند نه نفر در این مطالعه شرکت کرده‌اند. ابزار اصلی گردآوری داده‌ها در این پژوهش مصاحبه‌های نیم‌ساخت‌یافته با خبرگان حوزه مدیریت دولتی بوده است. برای شناسایی مقوله‌های اینترنت انرژی از روش سودا استفاده شده است. برای شناسایی الگوی روابط علّی و ارائه الگوی نهایی از روش نگاشت علّی استفاده شده است.
یافته‌ها: براساس تحلیل سودا، 17 عامل به‌عنوان شاخص‌های الگوی اینترنت انرژی شناسایی شدند. براساس الگوی شبکه‌ای اینترنت انرژی 17 مقوله و 159 رابطه شناسایی شده است. شاخص پیاده‌سازی صحیح اینترنت انرژی در سازمان‌های دولتی از بیشترین وابستگی و کمترین نفوذ برخوردار است. شاخص دسترسی به امکانات و تجهیزات سخت‌افزاری به‌روز با 19 رابطه در کانون روابط مدل خوشه‌ای قرار گرفت.
بحث و نتیجه‌گیری: مجموعه منابع مالی لازم برای استفاده از اینترنت انرژی، عزم و اراده لازم برای به‌کارگیری اینترنت انرژی در سطح کلان، وجود زیرساخت‌های نرم‌افزاری مناسب و دسترسی به امکانات و تجهیزات سخت‌افزاری به‌روز به‌عنوان متغیرهای زیربنایی مدل می‌باشند که بایستی مورد توجه مسئولین و خط‌مشی‌گذاران قرار گیرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Presenting the Model of Energy Internet Implementation in Government Organizations with the Approach of Strategic Options Analysis and Causal Mapping

نویسندگان [English]

  • arash habibi 1
  • maryam ahmadifard 2
1 Msc, Department of Marketing Management, Tehran, Iran.
2 Lecturer, Department of Management, Scientific-Applied Center for Piping, Ahvaz, Iran.
چکیده [English]

Purpose: Energy Internet is a new approach that has been proposed in response to the crisis of energy consumption and control of non-renewable resources. Therefore, this study was conducted with the aim of modeling the implementation of energy Internet in government organizations.

Methodology: The research is based on the purpose of fundamental studies and from a philosophical perspective with an approach based on interpretive paradigm. In terms of method and time period of data collection is also in the category of cross-sectional survey studies. The statistical population of the study included the directors of strategic government research who participated in this study by non-probabilistic sampling method and purposeful nine people. The main data collection tool in this study was semi-structured interviews with experts in the field of public administration. The soda method has been used to identify categories of energy internet. Causal mapping method has been used to identify the pattern of causal relationships and present the final pattern.

Findings: Based on soda analysis, 17 factors were identified as indicators of the energy Internet pattern. Based on the pattern of energy internet networks, 17 categories and 159 relationships have been identified. The index of correct implementation of energy internet in government organizations has the highest dependence and the least influence. The index of access to up-to-date hardware facilities and equipment with 19 relationships was at the center of the cluster model relationships.

Conclusion: The set of financial resources required to use the energy Internet, the determination to use the energy Internet at the macro level, the existence of appropriate software infrastructure and access to up-to-date hardware facilities and equipment are the model variables that should be considered by officials and policy makers.

کلیدواژه‌ها [English]

  • Energy Internet
  • government organizations
  • soft operations research
  • causal mapping
آذر، عادل؛ خسروانی، فرزانه و جلالی، رضا (1398). پژوهش در عملیات نرم. تهران: انتشارات سازمان مدیریت صنعتی.
Ackermann, F., & Alexander, J. (2016). Researching complex projects: Using causal mapping to take a systems perspective. International Journal of Project Management, 34(6), 891-901.
Akemi Takeoka Chatfielda, Christopher G. Reddick .(2018). A framework for Internet of Things-enabled smart government: A case of IoTcybersecurity policies and use cases in U.S. federal government. Government Information Quarterly, https://doi.org/10.1016/j.giq.2018.09.007
Bui, N., Castellani, A. P., Casari, P., & Zorzi, M. (2012). The internet of energy: a web-enabled smart grid system. IEEE Network, 26(4), 39-45.
Eden, C., & Ackermann, F. (2010). Strategic options development and analysis. In Systems approaches to managing change: A practical guide (pp. 135-190). Springer, London.
Fontela, E. Gabus, A. )1974(. DEMATEL, Innovative Methods, Report No. 2 Structural Analysis of the World Problematique. Battelle Geneva Research Institute.
Hannan, M. A., Faisal, M., Ker, P. J., Mun, L. H., Parvin, K., Mahlia, T. M. I., & Blaabjerg, F. (2018). A review of internet of energy based building energy management systems: Issues and recommendations. IEEE Access, 6, 38997-39014.
Hong, Z., Feng, Y., Li, Z., Wang, Y., Zheng, H., Li, Z., & Tan, J. (2019). An integrated approach for multi-objective optimisation and MCDM of energy internet under uncertainty. Future Generation Computer Systems, 97, 90-104.
Huang, A. Q., Crow, M. L., Heydt, G. T., Zheng, J. P., & Dale, S. J. (2011). The future renewable electric energy delivery and management (FREEDM) system: the energy internet. Proceedings of the IEEE, 99(1), 133-148.
Jaradat, M., Jarrah, M., Bousselham, A., Jararweh, Y., & Al-Ayyoub, M. (2015). The internet of energy: smart sensor networks and big data management for smart grid. Procedia Computer Science, 56, 592-597.
Jitesh Thakkar.( 2007). Development of a balanced scorecard An integrated approach of Interpretive Structural Modeling (ISM) and Analytic Network Process (ANP). International Journal of Productivity and Performance Management, 56(1),  25-59.
Kahraman, Cengiz. (2009).  Fuzzy Multi-Criteria Decision Making: Theory and Applications with Recent Developments Front Cover, Volume 16 of Springer optimization and its applications.
Kanan F.T.)2009). Toward interpretation of complex structural modeling; IEEE Trans. Systems Man Cybernet, 4(5).
Lei Li, Yilin Zheng, Shiming Zheng, , Huimin Ke .(2020). The new smart city programme: Evaluating the effect of the internet of energy on air quality in China. Science of the Total Environment 714 (2020) 136380.
Lin, C. C., Deng, D. J., Kuo, C. C., & Liang, Y. L. (2018). Optimal charging control of energy storage and electric vehicle of an individual in the internet of energy with energy trading. IEEE Transactions on Industrial Informatics, 14(6), 2570-2578.
Lombardi, F., Aniello, L., De Angelis, S., Margheri, A., & Sassone, V. (2018). A blockchain-based infrastructure for reliable and cost-effective IoT-aided smart grids.
Narayanan V.K, Armstrong D.J (2015). Causal Mapping for Research in Information Technology. Hershey PA: Idea Group Publishing.
Ozsakalli, G; D. Ozdemir, S. Ozcan, B. Sarioglu, A. Dincer. (2014). Daily Logistics Planning With Multiple 3PLs: A Case Study in a Chemical Company. Journal of Applied Research and Technology, 12(5),  985-995.
Petrov, O. (2011). Next Generation e-Government: Transformation into Open Government. In Conference E-Democracy: ICT–a driver for improving democracy.
Qi, J., & Wu, D. (2018). Green energy management of the energy Internet based on service composition quality. IEEE Access, 6, 15723-15732.
Qiu, C., Cui, S., Yao, H., Xu, F., Yu, F. R., & Zhao, C. (2019). A novel QoS-enabled load scheduling algorithm based on reinforcement learning in software-defined energy internet. Future Generation Computer Systems, 92, 43-51.
Roblek, V., Meško, M., & Krapež, A. (2016). A complex view of industry 4.0. Sage Open, 6(2), 2158244016653987.
Sage A. P.; Interpretive structural modeling: Methodology for large-scale systems; New York, NY: McGraw-Hil, 1977.
Sani, A. S., Yuan, D., Jin, J., Gao, L., Yu, S., & Dong, Z. Y. (2019). Cyber security framework for Internet of Things-based Energy Internet. Future Generation Computer Systems, 93, 849-859.
Shahzad, Y., Javed, H., Farman, H., Ahmad, J., Jan, B., & Zubair, M. (2020). Internet of energy: Opportunities, applications, architectures and challenges in smart industries. Computers & Electrical Engineering, 86, 106739.
Town, G. E., Mahmud, K., Morsalin, S., & Hossain, M. J. (2018). Integration of electric vehicles and management in the internet of energy. Renewable and Sustainable Energy Reviews, 82, 4179-4203.
Tzeng, G.-H., Teng, J.-Y. (1993) Transportation investment project selection with fuzzy multiobjectives. Transp.Plann. Technol, 17(2), 91–112 .
Umer, T., Rehmani, M. H., Kamal, A. E., & Mihaylova, L. (2019). Information and resource management systems for Internet of Things: Energy management, communication protocols and future applications.‏
Victor R. Kebande, Phathutshedzo P. Mudau b, Richard A. Ikuesan, H.S. Venter b, Kim-Kwang Raymond Choo. (2020). Holistic digital forensic readiness framework for IoT enabled organizations Forensic Science International: Reports 2 (2020) 100117.
Vu, T. L., Le, N. T., & Jang, Y. M. (2018). An Overview of Internet of Energy (IoE) Based Building Energy Management System. In 2018 International Conference on Information and Communication Technology Convergence (ICTC) (pp. 852-855). IEEE.
Warfield J.N. (1976). Societal systems: Planning, policy and complexity; Willy Interscience, New York. 1976.
Wirtz, B. W., Weyerer, J. C., & Schichtel, F. T. (2019). An integrative public IoT framework for smart government. Government Information Quarterly, 36(2), 333-345.‏
Yang, S.-X., Zhu, C.-X., Qiao, L., & Chi, Y.-Y. (2020). Dynamic assessment of Energy Internet’s emission reduction effect -- a case study of Yanqing, Beijing. Journal of Cleaner Production, 122663. doi:10.1016/j.jclepro.2020.122663
Yin, Shih-Hsi ., Ching-Cheng Wang., Liang-Yuan Teng., and Yulam Magnolla Hsing. (2012). Application of DEMATEL, ISM, and ANP for key success factor (KSF) complexity analysis in R&D alliance, Scientific Research and Essays, 7(19), 1872-1890.
Zhou, D.Q., Ling, Z.L., Li, H.W. (2006). A Study of the System's Hierarchical Structure Through Integration of Dematel and ISM. Paper presented at the Machine Learning and Cybernetics, Dalian, China.
Zhou, X., Wang, F. and Ma, Y., (2015). August. An overview on energy internet. In Mechatronics and Automation (ICMA), 2015 IEEE International Conference on (pp. 126-131). IEEE.