نوع مقاله : مقاله علمی - پژوهشی

نویسندگان

1 دانشجوی دکتری

2 دانشیار/ گروه مدیریت آموزشی عالی/ دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران

3 گروه مدیریت آموزش عالی/دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران

4 مدیریت آموزش عالی/موسسه پژوهش و برنامه ریزی در آموزش عالی

چکیده

هدف پژوهش حاضر، تحلیل شکاف عوامل مؤثر بر رقابت هوشمندانه دانشگاه از طریق ترسیم نقشه اهمیت - عملکرد دانشگاه‌های صنعتی سطح یک شهر تهران می‌باشد. این پژوهش از منظر هدف، کاربردی و بر اساس نحوه گردآوری داده‌ها، پژوهش غیرآزمایشی از نوع پیمایش- مقطعی محسوب می‌شود. بر اساس نوع داده‌ها نیز یک پژوهش آمیخته است که با روش‌های کیفی- کمی انجام شده است. جامعه آماری بخش کیفی شامل اساتید دانشگاهی است که با روش نمونه‌گیری هدفمند انتخاب شدند. جامعه آماری بخش کمی، اعضای هیئت علمی و کارشناسان ارشد دانشگاه‌های صنعتی سطح یک شهر تهران است. حجم نمونه با فرمول کوکران 350 نفر برآورد گردید. ابزار گردآوری داده‌ها در بخش کیفی مصاحبه، نیم‌ساختارمند و در بخش کمی، پرسش‌نامه است. یافته‌های پژوهشی نشان داد که مقوله‌های فراگیر شامل «آگاهی از وضعیت رقبا»، «آگاهی راهبردی»، «آگاهی از وضعیت بازار»، «بها دادن به دانشجویان»، «پشتیبانی مدیران»، «فعالیت هوشمندانه»، «زیرساخت دانشگاه»، «درگیرکردن کارکنان و اعضای هیئت علمی» می‌باشد. بر اساس نتایج پژوهش تمامی شاخص‌های پژوهش بااهمیت است. بنابراین حیطه بی‌تفاوتی و حیطه اتلاف وجود ندارد. از طرفی عملکرد تنها در زمینه بها دادن به دانشجویان مطلوب و بالای حد متوسط است. بنابراین حیطه قابل‌قبول شامل بها دادن به دانشجویان است. سایر عوامل در حیطه ضعف قرار دارند.

کلیدواژه‌ها

عنوان مقاله [English]

Gap Analysis of Factors Affecting Smart University Competition through Importance-Performance Map Analysis of Top Technical Universities in Tehran (A Case Study of Sharif, Amirkabir, and K. N. Toosi Universities of Technology)

نویسندگان [English]

  • Mandana Yavari 1
  • pariavash jafari 2
  • Nadergholi Ghorchian 3
  • Asghar Zamani 4

1 education expert

2 Associate Professor

3 Associate Professor

4 Associate Professor

چکیده [English]

This study aimed to conduct a gap analysis of the factors affecting the smart university competition through the importance-performance map analysis of top technical universities in Tehran. This is an applied non-experimental cross-sectional survey, which is also classified as the mixed methods research based on the data type. In the qualitative section, the statistical population included the university professors selected through purposive sampling. The theoretical saturation was achieved with 16 participants. In the quantitative section, the statistical population included the faculty members and postgraduates of top technical universities in Tehran. The Cochran formula was employed to estimate a sample size of 350 participants who were selected through simple random sampling. The semi-structured interviews were used for data collection in the qualitative section, whereas a questionnaire was used for this purpose in the quantitative section. According to the research findings, the inclusive categories were identified as “knowledge about the status of rivals”, “strategic knowledge”, “knowledge about the market status”, “respect for clients”, “support from managers”, “smart activity”, “university infrastructure”, and “involvement of staff and faculty members”. Since the results show that all research indices are important, none of the categories are considered indifferent or wasteful, and the other factors were considered weak.

کلیدواژه‌ها [English]

  • Gap analysis
  • smartness of university competition
  • importance-performance map analysis
  • top technical universities of Tehran
Acharya, A., Singh, S. K., Pereira, V., and Singh, P. (2018). Big data, knowledge co-creation and decision making in fashion industry. International Journal of Information Managemen, 90-101.
Amarouche, K. Benbrahim, H. and Kassou, I. (2015). Product opinion mining for competitive intelligence. Procedia Computer Science 73:358 – 365. International Conference on Advanced Wireless Information and Communication Technologies (AWICT 2015).
Brankovic, J (2018). The status games they play: unpacking the dynamics of organisational status competition in higher education. Higher Education.  695-709 .
Braun, V., Clarke, V., and Terry, G. (2014). Thematic analysis. Qualitative research in clinical and health psychology.
Dehnavi Z., Zabihi L., and Zabihi Na. (2020). Competitive intelligence components at islamic azad university of tehran. Educational management in educational organizations, 1-13. (In Persian).
Domashova, J.,  and Zasypkina, A .(2021). Detection of non-typical users of the electronic marketplace, Freight transportation to prevent the competitive intelligence. Procedia Computer Science,210-216.
Feyzi M., and Babayi, H. (2021). Investigating the Impact of competitive intelligence on social responsibility and ethical behavior of ardebil national bank branches. Cultural leadership studies, 96-112 (In Persian).
Gilad, B. (2001). Industry risk management: CI’s next step. Competitive Intelligence Magazine, 21-21.
Hassan Zadeh V., Hemmati A., and Shateri A. (2021). Investigating the importance of competitive intelligence in the insurance industry. Islamic Science Research and Studies, 51-64. (In Persian).
Holsti, O. R. (1969). Content analysis for the social sciences and humanities, Reading, MA: Addison-Wesley
Jafari P., Dehnavi Z., and Arasteh H. (2020). Providing a favorable model of competition for educational progress at the university. Medical Sciences University Education Strategies, 151-160. (In Persian).
Jaferi S., Badi’e A., and HeydarZadeh K. (2017). E-ranking entrepreneurial ecosystem pattern. Lifestyle and Health, 100-115. (In Persian).
Jami, M., Rahmati, E., Taheri, G., amd Hosseini, M. (2019). Designing a competitive intelligence framework using the best-worst method. Business Management, 651-676. (In Persian).
Kazemi, M., Taheri, H., and Mohammadi, L. (2019). Competitiveness in higher education. Third National Conference on Modern Accounting and Management Research in the Third Millennium, Karaj. (In Persian)
Oubrich, M., Hakmaoui, A., Calof, J., and El Ghazi, H. (2022). Towards an anticipatory system incorporating corporate foresight and competitive intelligence in creating knowledge: a longitudinal Moroccan bank case study. Technological Forecasting and Social Change,  121-139.
Pour Pari A., Nateghi F., and Mohammad, M. (2020). Provide the quality evaluation pattern of combined education in higher education. Research in Educational Systems, 7-22. (In Persian).
Powell, J. H., and Bradford, J. P. (2000). Targeting intelligence gathering in a dynamic competitive environment. International Journal of Information Management, 181-195.Prescott, J. E .(1989).  Advances in competitive intelligence. Society of Competitor.
Ranjan, J., and Foropon, (2021). Big data analytics in building the competitive intelligence of organizations. International Journal of Information Management,  212-231.
Safavi S., Piran A., and Fakhri, T. (2022). Investigating the relationship between competitive intelligence and empowerment of employee and employee organizational accountability. Modern Research in Entrepreneurship Management, 261-288 (In Persian).
Sassi, D. B., Frini, A., Karaa, W. B. A., and Kraiem, N. (2016). A competitive intelligence solution to predict competitor action using K-modes algorithm and rough set theory. Procedia Computer Science, 597-606.
Shahmohammadi M., and Kiani P. (2019). Analytical review of non-governmental higher education institutions. Modern Research Approaches in Management and Accounting, 1-22. (In Persian).
Shaitura, S. V., Ordov, K. V., Lesnichaya, I., Romanova, Y., and Khachaturova, S.(2018).
Shapira, I. (2021). The limited influence of competitive intelligence over corporate strategy in Israel: historical, organizational, conceptual, and cultural explanations. Intelligence and National Security, 95-115. 
Silva, J., Pacheco, L. D., Negrete, K. P., Niño, J. C., Lezama ,O., and  Varela, N. (2019). Design and development of a custom system of technology surveillance and competitive intelligence in SMEs. Procedia Computer Science, 1231-1236.
Song, T., Chen, M., Xu, Y., Wang, D., Song, X., and Tang, X. (2021). Competition-guided multi neighborhood local search algorithm for the university course timetabling problem. Applied Soft Computing, 607-624.
Tabatabyi K., and Eyvazi. H.(2020). Relationship between competitive intelligence and brand position with the mediating variable of the organization’s performance. Knowledge-Based Business Management, 38-55. (In Persian).
TaherZadeh, F., and Moghaddam, M. (2021). Relationship between competitive intelligence and brand position with the mediating variable of the organization’s performance. Knowledge-Based Business Management, 15-27. (In Persian).
YazdanPanah, A., and Bayat E. (2012). Explanation and evaluation of competitive indicators of virtual universities. Strategic Management Studies, 101-122. (In Persian).