پیش‌بینی تعداد گردشگران بر اساس رکوردهای اطلاعاتی گوگل ترندز با روش یادگیری ماشینی (موردمطالعه: گردشگران شهر یزد)

نوع مقاله : مقاله پژوهشی

نویسنده

استادیار مدیریت دانشگاه علم و هنر

چکیده

با توسعة صنعت گردشگری و رشد کسب‌وکارهای مرتبط، کسب اطلاعات به‌روز در برنامه‌ریزی صحیح و برآورد دقیق تعداد گردشگران، به‌منظور به‌کارگیری کارآمد منابع با هدف توسعۀ زیرساخت‌ها و افزایش درآمد، ضروری است. وجود برنامه‌های دقیق درنهایت به ارتقای سطح رضایت گردشگران ورودی منجر می‌شود. با توسعۀ فرهنگ جست‌وجوگری اطلاعات، گردشگران معمولاً پیش از آغاز سفر، به جست‌وجوی اطلاعات مربوط به اقامتگاه‌ها و خدمات گردشگری موجود در مقصد، از طریق منابع اینترنتی، اقدام می‌کنند. در پژوهش حاضر، با استفاده از داده‌های منتخب مربوط به پرس‌وجوهای کاربران سراسر جهان در موتور جست‌وجوی گوگل درمورد امکانات و توانمندی‌های گردشگری شهر یزد، تعداد گردشگران آتی این شهر پیش‌بینی شده است. داده‌های پژوهش را آمارهای جست‌وجوی کاربران تشکیل می‌دهد که از سامانۀ گوگل ترندز پایین‌گذاری شده و با استفاده از روش یادگیری ماشینی مدل پیش‌بینی، طراحی و اعتبارسنجی شده است. پس از آماده‌سازی و تحلیل داده‌ها، مشخص شد که پرس‌وجوهای ثبت‌شده در گوگل ترندز، قدرت فراوانی (بیش از 95 درصد) در پیش‌بینی تعداد گردشگران شهر یزد در بازه زمانی سال 2014 تا 2019 در مقاطع ماهانه دارد

کلیدواژه‌ها


عنوان مقاله [English]

Forecasting the Tourists Demands Based on Google Trends Information Records by Machine Learning method (Case Study: Yazd tourists)

نویسنده [English]

  • Hamed Fallah Tafti
Faculty of Management and Accounting of Science and Arts university, Yazd
چکیده [English]

With the development of the tourism industry and the growth of related businesses, the need for up-to-date information in proper planning and accurate estimation of the number of tourists is essential for the efficient use of resources to develop infrastructure and increasing revenue. The existence of detailed plans will eventually lead to an increase in the satisfaction of incoming tourists. With the development of information search culture, tourists usually search for information about accommodation and tourism services in the destination through online resources before starting the trip. In the present study, using selected data related to user queries around the world in the Google search engine, about the tourism facilities and capabilities of Yazd, the number of future tourists in this city has been predicted. For this purpose, the research data consists of user search statistics, which were downloaded from the Google Trends system, and a prediction model was designed and validated using the machine learning method. After preparing and analyzing the data, it was found that the queries registered in Google Trends have a lot of power (more than 95%) in predicting the number of tourists in Yazd in the period from 2014 to 2019 in monthly periods.

کلیدواژه‌ها [English]

  • Tourists Quantity Forecasting
  • Tourism Demands
  • Google Trends
  • Machine Learning
  • Yazd City
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