مدل بازاریابی داده محور در گردشگری هوشمند؛ رویکرد فراترکیب (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
در عصر دگرگونی دیجیتال، کلان داده در تغییر سفرهای جهانی و ایجاد چالش ها و فرصت ها برای شرکت های تاسیس شده در صنعت گردشگری، نقش حیاتی ایفا کرده است. این مطالعه به دنبال پرکردن شکاف دانش پیوند روابط بین کلان داده و استراتژی بازاریابی در زمینه های مختلف پژوهشی در ادبیات گردشگری و مهمان نوازی(هتلداری) است. در این پژوهش به منظور تبیین مدلی جامع و با استفاده از رویکرد فراترکیب 47 مقاله با بهره گیری از متدلوژی کسپ بررسی و پیامدها، چالش ها، پیشایندها(پیش نیازها) و ابعاد بازاریابی داده محور در صنعت گردشگری شناسایی و اولویت بندی شدند. پس از تجزیه و تحلیل مقالات، پیامدهای کاربرد کلان داده، در 7 مقوله اصلی(7p) شامل: 1-فرایند2-مردم/مشتری3-محصول/خدمت4-شواهد فیزیکی5-ترفیع/پیشبرد6-توزیع/مکان7-قیمت طبقه بندی و اولویت بندی شدند. همچنین چالش ها، در 4 مقوله و پیشایندها و ابعاد هر کدام در 3 مقوله شناسایی و اولویت بندی شدند و در نهایت بر اساس جداول فراترکیب مدلی استخراج شد.Proposing a Model for Data Driven Marketing in the Smart Tourism with a Meta-synthesis Approach
Abstract In the era of digital transformation, Big Data have assumed a crucial role in changing the global travel and providing significant challenges and opportunities for established companies, as well as new entrants into the tourism industry. this study sought to fill the knowledge gap of linkage the relationships between big data and marketing strategy with comprehensive viewpoints across different research fields in tourism and hospitality literatures. This study aims to identify and present a comprehensive model of data driven marketing in smart tourism. This study is conducted by Meta-synthesis approach. After performing CASP analysis, eventually,47 papers are investigated. we identified and prioritized the consequences, challenges, prerequisites and Dimensions of data driven marketing in smart tourism. After investigating the articles, we identified and prioritized the consequences of BD in 7 major Category including: 1-process 2-people 3-product 4-physical evidence 5-promotion 6-place 7-price. This research has contributed to the expansion of the research literature`s knowledge body and can provide researchers and marketing managers with a through understanding of tourism and hospitality in the field of data-driven marketing. Introduction The epistemology of the literature on big data in hospitality and tourism operations provides enormous opportunities and has dynamically revolutionized this discipline, attracting attention from academics. In view of emergency events, such as the current COVID-19 pandemic, tourism and hospitality scholars across different disciplines have highlighted the role of big data trends in improving the quality of marketing strategies. For example, Iorio et al. (2020) asserted that big data can be a useful source of information that can not only interpret unstructured data through the knowledge discovery process but also predict tourists’ behaviour when facing requirements that are changeable. Gallego and Font (2020) asserted that managers might use big data to detect the reactivation of visitors to develop targeted marketing strategies and diminish the effects of the COVID-19 pandemic. Therefore, big data analysis provides a better understanding of the social change in present and future issues and value creation by comparing cross-sectional data in diverse areas. Materials and Methods This research used the meta-synthesis method to synthesize previous qualitative studies. In this study, the seven-step meta synthesis method established by Sandelowski and Barroso was used, and thematic analysis was used to analyze the sample texts in the meta-synthesis method. Discussion and Results we identified and prioritized the consequences of BD in 7 major Category including: 1-process 2-people 3-product 4-physical evidence 5-promotion 6-place 7-price. And Challenges of BD in 4 Category including: 1- Ethical and privacy issues 2- Management and financial issues 3- Technological, human and organizational challenges 4- Data reliability and data access Conclusions On the demand side, there has been a massive transformation in consumer behaviour. Consumers have become more experienced, independent and irrational due to changes in their values, lifestyles and demographic patterns. This has forced the supply side to shift from mass marketing to personalized marketing through the rules of market segmentation. The production process has also become more consumer centric. Furthermore, as a sign of a new era in ICTs, concepts such as big data, IoT and AI have recently gained significant importance in many sectors because the developments in ICTs have accelerated worldwide. Tourism is one of the important fields that use these concepts and will also be influenced to a great extent. Such changes will occur in the “P”s of tourism and hospitality marketing on the supply side and consumer behaviour on the demand side. As for the retransformation of tourism and hospitality marketing, new forms of “P”s can be explained as below: First, tourism products and services will be redesigned with the help of ICTs. Products and services will become more destination-oriented and smart destinations will be the core of tourism products and services. Second, the ability to use information technology and develop more technology-oriented products and services will be an indicator of pricing and value. Third, the place where all purchasing and transactions to be handled will become much more virtual. Finally, the promotion will also be more virtual-centric, where consumer decision-making can be influenced by the experience of other consumer peers and more personalized communication channels will be part of online or virtual marketing.
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