مطالعات مدیریت کسب و کار هوشمند

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری مدیریت صنعتی، دانشکده مدیریت و اقتصاد دانشگاه تربیت مدرس، تهران، ایران

2 استاد، گروه مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران

3 دانشیار، گروه مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران

چکیده

این پژوهش باهدف مدل‌سازی پیشران‌ها و پیامدهای تحول دیجیتال در اکوسیستم کسب‌وکار صنعت فولاد کشور ایران انجام شد. پژوهش حاضر ازنظر هدف یک تحقیق کاربردی-توسعه‌ای است و ازنظر شیوه گردآوری داده‌ها نیز یک تحقیق توصیفی-پیمایشی می‌باشد. در راستای هدف از طرح تحقیق آمیخته اکتشافی استفاده شد. جامعه مشارکت‌کنندگان بخش کیفی شامل اساتید مدیریت و مدیران صنعت فولاد کشور است. با روش نمونه‌گیری نظری پس از 20 مصاحبه اشباع نظری حاصل شد. در بخش کمی نیز با روش تحلیل توان کوهن نمونه‌ای به حجم 140 نفر از مدیران و کارشناسان صنعت فولاد کشور انتخاب شدند. ابزار گردآوری داده‌ها، مصاحبه نیمه‌ساختاریافته و پرسشنامه محقق‌ساخته بود. روایی بخش کیفی بر اساس اعتبارپذیری، انتقال‌پذیری، تأییدپذیری و اطمینان‌پذیری بررسی شد و برای سنجش پایایی بخش کیفی ضریب هولستی 707/0 و کاپای کوهن 658/0 برآورد گردید که مطلوب است. پرسشنامه با برآورد نسبت روایی محتوایی، روایی همگرا و روایی واگرا اعتبارسنجی شد. همچنین آلفای کرونباخ، ضریب رو و پایایی ترکیبی تمامی سازه‌ها بالای 7/0 برآورد شد. برای تجزیه‌وتحلیل داده‌ها از روش تحلیل کیفی مضمون، روش مدل‌سازی ساختاری-تفسیری و روش حداقل مربعات جزئی استفاده شد. یافته‌های پژوهش نشان داد عوامل اکوسیستم کسب‌وکار، عوامل مدیریتی، بسترهای سخت‌افزاری و نرم‌افزاری عوامل پیشران هستند که بر استراتژی تحول دیجیتال تأثیر دارند. استراتژی تحول دیجیتال نیز بر تحول دیجیتال صنعت فولاد تأثیر دارد و تحول دیجیتال نیز به‌نوبه خود بر نوآوری دیجیتال و ارتباطات دیجیتال تأثیر دارد و عملکرد نوآورانه، عملکرد اجتماعی و عملکرد بازاریابی را تحت تأثیر قرار داده و درنهایت دستیابی به عملکرد مالی میسر می‌شود.
 کلیدواژه‌ها: تحول دیجیتال، اکوسیستم کسب‌وکار، صنعت فولاد کشور ایران.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Modeling the drivers and consequences of digital transformation in the country's steel industry business ecosystem Iran

نویسندگان [English]

  • , Parisa karaminiya 1
  • , Ali Rajabzadeh Ghatari 2
  • Mohmoud Dehghan Nayeri, 3

1 Ph.D student in Industrial Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

2 Professor, Department of Management and Economics, Tarbiat Modares University, Tehran, Iran.

3 Associate Professor, Department of Management and Economics, Tarbiat Modares University, Tehran, Iran

چکیده [English]

This research was conducted with the aim of modeling the drivers and consequences of digital transformation in the country's steel industry business ecosystem Iran. The present study is an applied-developmental research in terms of its purpose and a descriptive-survey research in terms of its data collection method. In line with the purpose, an exploratory mixed research design was used. The qualitative section's participant population includes management professors and managers of the country's steel industry. Theoretical saturation was achieved after 20 interviews using the theoretical sampling method. In the quantitative section, a sample of 140 managers and experts of the country's steel industry was selected using the Cohen power analysis method. The data collection tool was a semi-structured interview and a researcher-made questionnaire. The validity of the qualitative section was examined based on reliability, transferability, confirmability, and reliability, and the Holst coefficient was estimated to be 0.707 and Cohen's kappa was 0.658, which is desirable. The questionnaire was validated by estimating the content validity ratio, convergent validity, and divergent validity. Also, Cronbach's alpha, coefficient of resiliency and composite reliability of all constructs were estimated above 0.7. Qualitative content analysis, structural-interpretive modeling and partial least squares methods were used to analyze the data. The research findings showed that business ecosystem factors, management factors, hardware and software platforms are driving factors that affect the digital transformation strategy. The digital transformation strategy also affects the digital transformation of the steel industry, and digital transformation in turn affects digital innovation and digital communications, and affects innovative performance, social performance and marketing performance, and ultimately enables the achievement of financial performance.

Introduction

The steel industry in Iran is known as a vital and mother industry due to its rich mineral resources and potential capacities. This industry has a strategic position in Iran and is considered the second largest non-oil export industry after petrochemicals. Steel is the most practical metal in terms of quality and value, and about 95% of the world's metals are steel and iron. Transformation is a critical factor in the success of steel companies' supply chains, and customer demands in the competitive market of this industry require fundamental changes in current processes. In other words, it can be said that transformation has become a vital issue in the steel industry ecosystem, and accepting and keeping up with changes is a necessary and continuous matter that ultimately ensures the health of this industry. The advancement of digital technology has led to the development of new organizational networks, which are called digital business ecosystems. Digital technology plays a pivotal role in achieving business goals, and its scope and effects are so extensive that it can even transform the nature of an industry as a whole. It is not possible to study business ecosystems without considering digital transformation. In general, it can be said that digital transformation has become the dominant paradigm in the industrial world today. In order to solve the country's major problems by utilizing the capacity of transformative technologies and with the aim of developing the digital economy, the Ministry of Communications and Information Technology has compiled and submitted to the Cabinet the "Digital Transformation Document" since the beginning of 1400. Specifically, in the country's steel industry, embracing digital transformation will bring many benefits, but this transformation requires contexts and platforms that are known as drivers of digital transformation in the steel industry. Creating software platforms that are appropriate for the business ecosystem processes of this steel industry, which has a continuous value chain, along with speed and agility in decision-making for managers, is a very vital issue that will have significant consequences. On the other hand, the digital transformation of the steel industry is inevitable, and from a negative perspective, this issue is also very important. The rapid movement of countries such as China and India towards digital development in the steel industry has greatly affected global markets and, of course, Iran, and can be a warning for the Iranian steel industry. This issue is also very important theoretically, and various studies have been conducted on "digital transformation" and "business ecosystems." However, an independent study that examines the country's steel industry business ecosystem based on digital transformation has not yet been recorded in the country's domestic scientific interventions. In studies that have implicitly addressed this issue, providing an applied model in this area has been neglected. Finally, it should be said that there is no doubt that the gap between the scientific and practical fields in the field of digital transformation in the country is large, therefore, this study attempted to present a model for digital transformation with an applied-developmental approach in the country's steel industry. The present study will answer this key question: what is the model of the drivers and consequences of digital transformation in the country's steel industry business ecosystem?

Methodology

 This research is an applied-developmental research in terms of its purpose, which seeks to model the drivers and consequences of digital transformation in the country's steel industry business ecosystem. It is also considered a descriptive-survey research based on the data collection method. In order to achieve the research objective, a mixed exploratory research design (qualitative-quantitative) was used. The qualitative part's participant population includes management professors and managers of the country's steel industry. Theoretical saturation was achieved after 20 interviews using the theoretical sampling method. In the quantitative part, a sample of 140 managers and experts of the country's steel industry was selected using the Cohen power analysis method. The data collection tool was a semi-structured interview and a researcher-made questionnaire. The validity of the qualitative part was examined based on credibility, transferability, confirmability, and reliability, and the Holst coefficient was estimated to be 0.707 and Cohen's kappa was estimated to be 0.658, which is desirable. The questionnaire was validated by estimating the content validity ratio, convergent validity, and divergent validity. Also, Cronbach's alpha, coefficient of resiliency, and composite reliability of all constructs were estimated to be above 0.7. Thematic analysis method and Maxqda software were used for data analysis in the qualitative part. Structural-interpretive modeling method and MicMac software were used to identify the relationship between constructs. In the quantitative part, partial least squares method and Smart PLS software were used.

Results and Discussion

In the research findings section, the interviews were analyzed using qualitative thematic analysis based on the six-step Atread-Stirling method. In the open coding stage, 514 codes were identified, which were ultimately identified through axial coding as 4 overarching themes, 12 organizing themes, and 72 basic themes.

Conclusion

The results showed that business ecosystem factors, management factors, hardware and software platforms are the driving factors that affect the digital transformation strategy. The digital transformation strategy also affects the digital transformation of the steel industry, and digital transformation in turn affects digital innovation and digital communications, and affects innovative performance, social performance, and marketing performance, and ultimately achieves financial performance.
Key words: digital transformation, business ecosystem, steel industry of the country Iran.

کلیدواژه‌ها [English]

  • digital transformation
  • business ecosystem
  • steel industry of the country Iran
  1. امرایی، علی؛ مهری‌نژاد، صفیه؛ بیات‌ترک، امیر. (1403). ارزیابی الگوی رقابت‌پذیری در صنعت فولاد با رویکرد انتقال فناوری. مدیریت صنعتی، 16(2)، 175-191. https://doi.org/10.22059/imj.2024.375868.1008156
  2. امیرشاهی، علی؛ صالح‌آبادی، علی؛ شاهپوری، رسول. (1402). رتبه‌بندی روش‌های تأمین مالی در صنعت فولاد ایران با الگوی تصمیم‌گیری چندشاخصه. پژوهش‌ها و سیاست‌های اقتصادی، ۳۱ (۱۰۸)، ۳۳-۶۵. http://qjerp.ir/article-1-3454-fa.html
  3. ایزدیار، مهدی. (1401). نوین‌سازی صنعت فولاد با فناوری‌های دیجیتالی. پیوست، 21 (109)، 81-92.
  4. آذر، عادل؛ خسروانی، فرزانه؛ جلالی، رضا. (1398). تحقیق در عملیات نرم. تهران: سازمان مدیریت صنعتی.
  5. آذر، عادل؛ غلامزاده، رسول. (1401). کمترین مربعات جزئی. تهران: نگاه دانش.
  6. بشارتی‌زاده، رضا؛ بشارتی زاده، رضا؛ معتدل، محمدرضا؛ طلوعی‌اشلقی، عباس. (1402). عوامل کلیدی مؤثر بر بهره‌وری در زنجیره تأمین صنعت فولاد. مدیریت بهره‌وری، 17(66)، 127-143. https://doi.org/10.30495/qjopm.2020.1897195.2819
  7. ثقفی، فاطمه؛ جعفرنژادچقوشی، احمد؛ منطقی، منوچهر؛ موسوی، سیدجواد. (1401). مدل مراحل تکامل اکوسیستم‌های کسب‌‌وکار صنعتی. مطالعات مدیریت کسب‌وکار هوشمند، 10(40)، 135-166. https://doi.org/10.22054/ims.2021.60836.1964
  8. حبیبی، آرش. (1394). تحول دیجیتال. فصلنامه بازاریابی پارس‌مدیر، 1(1)، 102-107.
  9. حبیبی، آرش؛ جلال‌نیا، راحله. (1401). حداقل مربعات جزئی. تهران: نارون.
  10. روحانی، ابوالفضل؛ کشاورز، الهام. (1403). تأثیر تحول دیجیتال بر عملکرد نوآوری با نقش میانجی عوامل نوآوری. مطالعات راهبردی در صنعت نفت و انرژی. ۱۶ (۶۱)، ۱۶۹-۱۸۴.. http://iieshrm.ir/article-1-1659-fa.html
  11. زارچی، محمود؛ رنگریز، حسن؛ عباسیان، حسین؛ سلطانی، ایرج. (1402). ارائه مدل تحول فرهنگ تعالی‌محور در صنعت فولاد. تحقیق در مدیریت تولید و عملیات، 14(2)، 125-142. https://doi.org/10.22108/pom.2023.136530.1491
  12. سپهری‌آزاد، یوسف؛ موسی‌خانی، مرتضی؛ داوری، علی. (1403). طراحی مدل اکوسیستم کسب‌وکار دیجیتال با رویکرد آموزش الکترونیکی. 19 (74)، 70-87. https://doi.org/10.61186/jstpi.33645.19.74.70
  13. شامی‌زنجانی، مهدی. (1401). فناوری‌های دیجیتال در صنعت فولاد. https://shamizanjani.ir
  14. عباسیان حسینی، سیده‌محبوبه؛ فتحی‌هفشجانی، کیومرث؛ عباسیان‌حسینی، سیدمحسن؛ مدیری، محمود. (1402). طراحی مدل سیاست سرمایه‌گذاری برای رقابت‌پذیری در صنعت فولاد. اقتصاد مالی، 17 (62)، 317-340. https://doi.org/10.30495/fed.2023.700138
  15. کاظمیان، مینا؛ افشارکاظمی، محمدعلی؛ فتحی‌هفشجانی، کیومرث؛ معتدل، محمدرضا. (1402). ارائه مدل هوشمند تعیین قیمت فولاد با رویکرد ترکیبی نظریه بازی‌ها و الگوریتم‌های یادگیری ماشین. مدیریت صنعتی، 15 (3)، 478-507. https://doi.org/10.22059/imj.2023.356697.1008039
  16. مدرسی، یاسمن؛ سیدنقوی، میرعلی؛ رودساز، حبیب؛ رئیسی‌وانانی، ایمان. (1402). طراحی چارچوب مفهومی برای مؤلفه‌های نرم تحول دیجیتال با استفاده از تحلیل مضمون. مطالعات منابع انسانی، 13(1)، 57-88. . https://doi.org/10.22034‌/‌jhrs.‌2023‌.172970
  17. وارث، سیدحامد؛ محمدیان؛ ایوب؛ کارگرشورکی، محمد. (1402). نوآوری مدل کسب‌وکار پایدار در عصر دیجیتال مبتنی بر رویکرد قابلیت‌های پویا. مدیریت بازرگانی، 15(1)، 54-84. https://doi.org/10.22059/jibm.2021.323237.4116
  18. وارسته، مهسا؛ آقاجانی، حسنعلی؛ ولی‌پورخطیر، محمد؛ آقایی، مجید. (1401). استخراج چارچوب ارزیابی مدل‌های کسب‌وکار در صنعت فولاد ایران مبتنی بر رویکرد اقتصاد مدور. مدیریت بهره‌وری، 16 (63)، 53-81. https://doi.org/10.30495/qjopm‌.2022.1944949.3267

References

  1. Adam, H. E., Teng, Y., & Okeke, C. D. (2024). Digital transformation as a catalyst for business model innovation: A critical review of impact and implementation strategies. Magna Scientia Advanced Research and Reviews, 10(02), 256-264. https://doi.org/10.30574‌/msarr.2024.10.2.0066
  2. Agarwal, S., & Kapoor, R. (2023). Value creation tradeoff in business ecosystems: Leveraging complementarities while managing interdependencies. Organization Science, 34(3), 216-242. http://dx.doi.org/10.1287/orsc.2022.1615
  3. Attride-Stirling, J. (2001). Thematic networks: an analytic tool for qualitative research. Qualitative research, 1(3), 385-405. https://doi.org/10.1177/146879410100100307
  4. Bohnsack, R., Rennings, M., Block, C., & Bröring, S. (2024). Profiting from innovation when digital business ecosystems emerge: A control point perspective. Research Policy, 53(3), 104961. https://doi.org/10.1016/j.respol.2024.104961
  5. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-33.
  6. Cohen, J. E. (2013). Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
  7. Cui, C., & Lyu, R. (2024). Operational Performance Evaluation of Iron and Steel Industry in China under the Background of Digital Transformation–An Application of Data Envelopment Analysis. Highlights in Business, Economics and Management, 33, 610-619. http://dx.doi.org/10.1016/j.scitotenv.2019.135903
  8. Gotting, A., Behrend, C., & Kohlgrüber, M. (2024). Identifying Future Skills for the Digital Transformation in the Steel Industry: An Ecosystem Analysis in the German Rhein/Ruhr Area. Industry 4.0 and the Road to Sustainable Steelmaking in Europe, 12(1), 203-217.
  9. Gueler, M. S., & Schneider, S. (2021). The resource-based view in business ecosystems: A perspective on the determinants of a valuable resource and capability. Journal of Business Research, 133, 158-169. https://doi.org/10.1016/j.jbusres.2021.04.061
  10. Guimarães, J. D. S., Fernandes, C., Veiga, P. M., & Ramadani, V. (2023). The relationship between entrepreneurial ecosystems and digital transformation. FIIB Business Review, 23197145231173850. http://dx.doi.org/10.1177/23197145231173850
  11. Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
  12. Holsti, O. R. (1969). Content analysis for the social sciences and humanities, Reading, MA: Addison-Wesley.
  13. Lee, M., Moon, K., Lee, K., Hong, J., & Pinedo, M. (2024). A critical review of planning and scheduling in steel-making and continuous casting in the steel industry. Journal of the Operational Research Society, 75(8), 1421-1455. http://dx.doi.org/10.1080/01605682.2023.2265416
  14. Miller, E., Cross, L., & Lopez. M. (2010). Sampling in qualitative research. FBB research group, 19(3), 249-261. http://dx.doi.org/10.1016/S0001-2092(06)61990-X
  15. Patel, K., & McCarthy, M. P. (2000). Digital transformation: the essentials of e-business leadership. McGraw-Hill Professional.
  16. Priyono, A., Chatelin, Y.-M., & Hidayat, A. (2024). Fostering innovation through learning from digital business ecosystem: A dynamic capability perspective. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100196. https://doi.org/10.1016/j.joitmc.2023.100196
  17. Stroiko, T., Voloshyna-Sidei, V., & Druz, Y. (2023). Formation of business ecosystems as a basis for the development of the IT industry. Baltic Journal of Economic Studies, 9(1), 177-183. https://doi.org/10.30525/2256-0742/2023-9-1-177-183
  18. Suuronen, S., Ukko, J., Eskola, R., Semken, R. S., & Rantanen, H. (2022). A systematic literature review for digital business ecosystems in the manufacturing industry: Prerequisites, challenges, and benefits. CIRP Journal of Manufacturing Science and Technology, 37, 414-426. https://doi.org/10.1016/j.cirpj.2022.02.016
  19. Tolettini, L., & Di Maria, E. (2023). The impact of industry 4.0 on the steel sector: paving the way for a disruptive digital and ecological transformation. Recycling, 8(4), 55. https://doi.org/10.3390/recycling8040055
  20. Westerman, C., Bonnet, D., Ferraris, P., & McAfee, A. (2011). Digital Transformation: A roadmap for billion-dollar organizations. MIT Center for digital business and capgemini consulting, 1, 1-68. http://dx.doi.org/10.1142/S136391961740014X

 

References [In Persian]

  1. Amirshahi, A., Salehabadi, A., Shahpouri, R. (2023). Ranking of financing methods in the Iranian steel industry with a multi-criteria decision-making model. Economic Research and Policies, 31 (108), 33-65. [In Persian]
  2. Izadyar, M. (2022). Modernization of the steel industry with digital technologies. Appendix, 21 (109), 81-92. [In Persian]
  3. Azar, A., Khosravani, F., Jalali, R. (2019). Research in soft operations. Tehran: Industrial Management Organization. [In Persian]
  4. , A. (2015). Digital Transformation. Pars-Madir Marketing Quarterly, 1(1), 102-107. [In Persian]
  5. Sepehri-Azad, Y., Musa-Khani, M., Davari, A. (2024). Designing a Digital Business Ecosystem Model with an E-Learning Approach. 19 (74), 70-87. [In Persian]
  6. Azar, A., & Gholamzadeh, R. (2022). partial least squares. Tehran: Negha Danesh. [In Persian]
  7. Beshartizadeh, R., Radfar, R., Motadel, M. R., &Toloei Ashlaghi, A. (2023). Key factors affecting productivity in the supply chain of the steel industry. Productivity Management, 17(66), 127-143. [In Persian]
  8. Habibi, A., & Jalalnia, R. (2022). partial least squares. Tehran: Narun. [In Persian]
  9. Kazemiyan, M., Afshar Kazemi, M. A., Fathihafashjani, K., & Moatadal, M. R. (2023). Presenting an intelligent model for steel price determination with a combined approach of game theory and machine learning algorithms. Industrial Management, 15(3), 478-507. [In Persian]
  10. Modaresi, Y., Seyednaghavi, M., Roudsaz, H., & Raisivanani, I. (2023). Designing a conceptual framework for the soft components of digital transformation using thematic analysis. Human Resource Studies, 13(1), 57-88. [In Persian]
  11. Rouhani A, Keshavarz E. The effect of digital transformation on innovation performance with the mediating role of innovation factors. Strategic studies in the oil and energy industry 2024; 16 (61):169-184. [In Persian]
  12. Shamizanjani, M. (2022). Digital technologies in the steel industry. https://shamizanjani.ir[In Persian]
  13. Thaghafi, F., Jafarnejadchaghoshi, A., Manteghi, m., & Mousavi, S.J. (2022). The model of stages of evolution of industrial business ecosystems. Intelligent Business Management Studies, 10(40), 135-166. [In Persian]
  14. Varesteh, M., Aghajani, H. A., Valipourkhatir, M., & Aghaei, M. (2022). Deriving the evaluation framework of business models in Iran's steel industry based on the circular economy approach. Productivity Management, 16(63), 53-81. [In Persian]
  15. Wares, S.H., Mohammedeyan; A., & Karegarshouraki, M. (2023). Sustainable business model innovation in the digital era based on dynamic capabilities approach. Business Management, 15(1), 54-84. [In Persian]
  16. Zarchi, M., Rangriz, H., Abbasian, H., & Soltani, I. (2023). Presenting the transformation model of excellence-oriented culture in the steel industry. Research in Production and Operations Management, 14(2), 125-142. [In Persian]
  17. Abbasian-Hosseini, S-M., Fathi-Hafeshjani, K., Abbasian-Hosseini, S-M., Modiri, M. (2023). Designing an Investment Policy Model for Competitiveness in the Steel Industry. Financial Economics, 17 (62), 317-340. [In Persian]

 

 

 

 

 

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