بررسی تحلیلی پیشایندهای نوآوری در آژانس های گردشگری استان گیلان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، گروه مدیریت صنعتی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران

2 دکتری، گروه مدیریت دولتی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران.

3 کارشناسی ارشد، گروه مدیریت بازرگانی، مؤسسهٔ غیرانتفاعی دامون، فومن، ایران.

4 کارشناسی ارشد، گروه مدیریت بازرگانی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران.

10.22034/jtd.2023.384713.2734

چکیده

صنعت گردشگری، به‌منزلهٔ بزرگ‌ترین مولد اقتصادی جهان در دههٔ اخیر، گزینهٔ مناسبی برای رشد و توسعهٔ جوامع به شمار میرود. برندگان این صنعت شرکتهایی خواهند بود که خالق ایدههای نوآورانه هستند و از آن به‌مثابهٔ مزیت رقابتی برجسته استفاده کنند. بر این اساس، پژوهش حاضر قصد دارد، با نگرشی نظام‌مند، پیشایندهای نوآوری در شرکتهای گردشگری استان گیلان را بررسی کند. روش پژوهش به‌کاررفته از نوع توصیفی و هدف آن کاربردی است. برای گردآوری دادههای پژوهش از ابزار پرسش‌نامه استفاده شده است. جامعهٔ آماری پژوهش شامل ۱۳ نفر از خبرگان دانشگاهی و سازمان میراث فرهنگی، صنایع دستی و گردشگری شهرستان فومن است. پس از شناسایی 32 پیشایندهای نوآوری با مطالعهٔ مبانی نظری، این پیشایندها در قالب پرسش‌نامه به اختیار خبرگان داده شدند و، پس از اجرای روش دلفی، 1۵ مؤلفهٔ نهایی برای اجرای مدل‌سازی ساختاری تفسیری (ISM) استفاده شدند. براساس نتایج، پیشایندهای نوآوری در شش گروه سطحبندی شدند. یافتهها نشان میدهد که پیشایند چابکی روشهای نوآوری در سطح 1، نوآوری باز، درگیری در فرایند نوآوری، مهارت فکری، ارتباط منسجم متخصصان و به‌کارگیری تکنیکهای خلاقیت در سطح 2، محیط کاری و حل تعارض در سطح 3، شناخت رقبا، تخصصیسازی و تجزیه‌وتحلیل خلاقانهٔ نیازمندیها در سطح ۴، رهبری نوآوری، شناخت بازار و ترکیب گروه در سطح ۵ و نهایتاً مدیریت پورتفولیو در سطح ۶ قرار گرفتند. نهایتاً، این پیشایندها در ماتریس MICMAC ارزیابی و از نظر قدرت نفوذ و وابستگی تحلیل شدند.

کلیدواژه‌ها


عنوان مقاله [English]

Analytical study of Innovation Drivers in Tourism Companies of Guilan Province

نویسندگان [English]

  • Mahdi Homayounfar 1
  • somaye sabet 2
  • Zeinab Kamali Chirani 3
  • faezeh kamali chirani 4
1 Assistant Professor, Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran
2 PhD, Department of Public Management, Rasht Branch, Islamic Azad University, Rasht, Iran.
3 MA, Department of Business Administration, Damoon Non-profit organization, Fouman, Iran.
4 MA, Department of Business Administration, Rasht Branch, Islamic Azad University, Rasht, Iran.
چکیده [English]

Tourism industry, as the biggest economic generative industry in the world in the last decade, is a good alternative for the growth and development of the countries. The winners of this industry will be companies that create innovative ideas and use them as core competitive advantage. In this regard, the present article aims to examine the innovation drivers in tourism companies in Gilan province with a systematic approach. The research method is descriptive and its purpose is applied. The questionnaire was used to collect research data. The statistical population includes a combination of 13 university experts and the Cultural Heritage, Handicrafts and Tourism Organization of Fouman city. After identifying 32 drivers of innovation trough the literature review, these drivers were distributed among experts in form of a questionnaire, and applying Delphi method, 15 main drivers were used to implement interpretive structural modeling (ISM) method. According to the results, the innovation drivers were classified into six levels. The findings show that the agility of innovation methods lies at level 1, open innovation, innovation engagement, thinking skill, experts’ integrated communication and creativity techniques lie at level 2, work environment, conflict resolution lie at level 3, knowledge about competitors, customization and creative analysis of requirements lie at level 4, innovation leadership, market knowledge and team composition lie at level 5, and finally portfolio management lies at level 6. These drivers were evaluated in the MICMAC matrix and analyzed in terms of their influence and dependence power.

کلیدواژه‌ها [English]

  • Innovation drivers
  • Tourism
  • Interpretive Structural Modeling
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