مروری نظام‌مند بر کاربرد کلان‌داده‌ها در صنعت گردشگری

با پیشرفت فنّاوری و افزایش استفاده از شبکه‌های اجتماعی و اینترنت، حجم تولید داده‌ها افزایش چشمگیری داشته و بهره‌گیری از مفهوم «کلان‌داده‌ها» نیز به تبع آن، به‌طور فزاینده‌ای در پژوهش‌های علمی مختلف به چشم می‌خورد؛ اما سازمان‌دهی و تحلیل ادبیات موجود با محوریت بهره‌گیری از کلان‌داده‌ها در حوزۀ گردشگری برای شناسایی وضعیت تحقیقات صورت‌گرفته در این عرصه، خود مسئله‌ای است که هدف این مطالعه است؛ ازاین‌رو این پژوهش به بررسی میزان بهره‌گیری از کلان‌داده در تحقیقات گردشگری منتشر‌شده از سال 2016 تا 2022، به شناسایی شکاف‌های پژوهشی و فرصت‌های پیشرفت‌های آتی پرداخته ‌است. ازآنجاکه این پژوهش در پی ارائۀ تصویری کلی از کارهای انجام‌شده در مقالات منتشر‌شده در حوزۀ گردشگری است، از روش مطالعۀ نگاشت نظام‌مند استفاده شده ‌است. مقاله‌ها براساس این ویژگی‌ها بررسی شدند: موضوع تحقیق، توصیف مفهومی و نظری، منابع داده، نوع داده و اندازه، روش‌های جمع‌آوری داده‌ها، روش‌های تجزیه‌وتحلیل داده‌ها و گزارش و تجسم داده‌ها. یافته‌های این مطالعه حاکی از افزایش تحقیقات انجام‌شده در حوزۀ مدیریت مهمان‌نوازی و گردشگری با استفاده از روش‌های تحلیلی برای کلان‌داده‌هاست. بااین‌حال، این حوزۀ پژوهشی از نظر دامنه نسبتاً پراکنده و در روش‌شناسی محدود است و شکاف‌های متعددی را نشان می‌دهد. نتیجۀ دیگر آن‌که پژوهش‌های گردآوری‌شده نشان می‌دهند هنوز از پتانسیل کلان‌داده‌ها به‌طور کامل استفاده ‌نشده و فرصت‌های زیادی پیش‌روی صنعت گردشگری از بعد پژوهشی وجود دارد. همچنین آشنانبودن کامل پژوهشگران این حوزه با ابزارهای تحلیل و تصمیم‌گیری داده‌محور چالشی است که در این پژوهش نمایان شده است.

a systematic review on the use of big data in tourism

as technology advances and the use of social networks and the internet grows, there’s a significant increase in the production of data. the concept of &big data& is becoming more prominent in various scientific studies. however, understanding how big data is used in tourism is a challenge addressed in this study. the research investigates the application of big data in tourism studies published from 2016 to 2022, aiming to identify research gaps and potential areas for future development. to provide an overview of published works in tourism, we used the systematic mapping study method. articles were assessed based on various factors, including research topic, conceptual and theoretical descriptions, data sources, data types and sizes, data collection methods, data analysis techniques, and reporting and visualization methods. the findings indicate a growth in research within hospitality and tourism management using analytical techniques for big data. despite this, the research in this field is scattered and limited in scope and methodology, revealing several gaps. additionally, the study suggests that the full potential of big data remains untapped in tourism, offering numerous research opportunities for the industry. a notable challenge highlighted is the .researchers’ incomplete knowledge of data-driven analysis and decision-making tools in this field keywords: big data, social media, machine learning, systematic mapping review 1. introductionthe speed of technological changes and their profound effects on various industries, coupled with unpredictable events such as the recent pandemic—having a significant impact on various sectors—requires these industries to cope with uncertainty (piyush sharma, 2020). among them, dynamic, fluctuating, and time-sensitive industries like the tourism sector must respond promptly and more efficiently to emerging challenges and threats in order to survive (vikrant kaushal, 2021). hence, the roles of technology and digitization are vital in helping industries, countries, and organizations overcome rapid challenges (soluk, 2021).digitization and the adoption of new technologies have been increasing dramatically in recent years (ritter, 2020). this includes the use of methods that change the business model to create more effective and efficient processes toward technology—arguably the most crucial change in exploitation. one significant aspect is the analysis of consumer behavior, market dynamics, supply and delivery processes, and customer communication using data obtained from the digitization process (youssef, 2021). meanwhile, big data stands out as one of the most well-known paradigms of information analysis, attracting both researchers and experts (josé álvarez garcía, 2023).methodologically, big-data-based approaches allow researchers to overcome the problems associated with traditional sampling methods because big data practically enables working with the entire population under investigation. this capability makes it possible to address any question related to the opinions, views, ideas, and behavior of all individuals. simultaneously, it proves to be a powerful tool for addressing new research questions, developing innovative research designs useful in advancing knowledge, and ultimately providing support for policy and managerial decision-making (gerard, 2016).the most crucial factor is that the tourism industry grows based on information. thus, tourism research requires a large amount of strong, up-to-date, timely, and relevant information to support and assist decision-making processes. big data can provide up-to-date and highly informed inferences about human behavior and activities that boost the tourism industry (feifei xu, 2020). through the traveler, a large number of data sources can inform decisions made at different stages, such as before, during, and after the trip. one popular data source is social media, used by tourists and tourism businesses to communicate, find or provide relevant information or advice, and obtain information about important news and crises (park, 2019). therefore, considering the importance of using big data analysis in tourism studies and stating the issue that no monitoring and analysis of the state of research conducted in this field with this theme has been done so far, the upcoming research on the analysis of the use of big data is focused on tourism research by conducting a systematic mapping review. 2. literature reviewsince no systematic mapping research has been conducted to investigate the status and process of research on the use of big data in tourism studies, the concern of this research is to use the opportunities created by big data and the need to use big data and analyze and make decisions on its basis is in the tourism industry, by reviewing the literature and explaining the different dimensions of the needs of this industry, this concern and issue will become clearer, therefore, in this section, we will review the researches conducted in recent years that emphasized the necessity of using big data in the field of tourism and each offered a solution for a different need.describing the need to create a personal customer experience in the tourism industry, chen et al. state that personal experiences lead to increased customer satisfaction and loyalty. big data allows the tourism industry to analyze customer preferences, behaviors and feedback to provide recommendations (chen, 2017). by describing the need for demand forecasting and price optimization in tourism, jiang et al. believe that accurate demand forecasting helps tourism businesses to optimize pricing and resource allocation. big data analytics enables the analysis of historical data, seasonal patterns and market trends for better decision making (xiang, 2017). referring to the need for operational efficiency and resource management in the tourism industry, lee et al. have stated that big data helps simplify operations by providing insights into resource use, crowd management, and operational efficiency. this leads to cost savings and improved service quality (li, 2018). gretzel et al also stated the need for risk management and crisis response in this industry, stating that big data helps to identify potential risks and predict crises in the tourism sector. analyzing data from various sources helps to develop effective risk management strategies (gretzel, 2015). stating the need to improve marketing and customer engagement in the tourism industry, neuhofer et al. believe that big data enables targeted marketing campaigns based on customer insights and improves the effectiveness of promotional efforts. it also increases customer engagement through data-driven strategies (neuhofer, 2015). pointing to the need for tourism destination management and planning, wang has stated that big data supports destination management by providing