مشخصات مقاله | |
ترجمه عنوان مقاله | رشد نام برند دیجیتالی از طریق رضایت مشتری با تحلیل کلان داده ها در بخش مهمان نوازی بعد از بحران کووید-19 |
عنوان انگلیسی مقاله | Growth of digital brand name through customer satisfaction with big data analytics in the hospitality sector after the COVID-19 crisis |
نشریه | الزویر |
انتشار | مقاله سال 2023 |
تعداد صفحات مقاله انگلیسی | 12 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | Scopus – DOAJ |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
18.846 در سال 2022 |
شاخص H_index | 20 در سال 2023 |
شاخص SJR | 2.479 در سال 2022 |
شناسه ISSN | 2667-0968 |
شاخص Quartile (چارک) | Q1 در سال 2022 |
فرضیه | دارد، صفحه 4 بخش Hypotheses development |
مدل مفهومی | دارد، صفحه 2 بخش Conceptual framework |
پرسشنامه | دارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مدیریت |
گرایش های مرتبط | بازاریابی – مدیریت بازرگانی – مدیریت فناوری اطلاعات |
نوع ارائه مقاله |
ژورنال |
مجله | مجله بین المللی دیدگاه داده های مدیریت اطلاعات – International Journal of Information Management Data Insights |
دانشگاه | University of the Aegean, Greece |
کلمات کلیدی | نام برند دیجیتالی – رضایت مشتری – کلان داده ها – تحلیل وب – مشارکت کاربر – توریسم |
کلمات کلیدی انگلیسی | Digital brand name, Customer satisfaction, Big data, Web analytics, User engagement, Tourism |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.jjimei.2023.100190 |
لینک سایت مرجع | https://www.sciencedirect.com/science/article/pii/S266709682300037X |
کد محصول | e17531 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract Introduction Conceptual framework Methodology Results Discussions Conclusions Declaration of Competing Interest References |
بخشی از متن مقاله: |
Abstract This study examines the best practices for the optimization of the corporate digital brand name by taking into consideration customers’ behavioral big data and web analytics. In the first stage of the study, customers’ satisfaction big data have been extracted with the assistance of a web scrapping tool from TripAdvisor for 189 hotels in Hubei province, and behavioral data from Hubei province hospitality websites have been gathered with the assistance of web analytics platforms for 5.7 million website visitors for the last 18 months. In the second stage of the research, those data have been statistically analyzed including descriptive, correlation, and regression analysis. Then, a fuzzy cognitive map has been created to present the intercorrelation between the parameters and two optimization scenarios have been developed for digital brand name and customer satisfaction. Finally, an Agent-based model has been created in order to simulate the customers’ behavior in the corporate website and TripAdvisor. The results indicated that hotels in Hubei province need to invest less in social media advertisements than search engine advertisements in order to achieve a competitive advantage and improve their digital brand name. Additionally, hotels need to develop their websites with more engaging content to maintain the customer on the corporate website for more time in order to optimize customer satisfaction in contrast to healthcare and libraries websites.
Introduction The COVID-19 pandemic forced all destinations to introduce travel restrictions, with airplanes on the ground and hotels, restaurants and travel agencies closed, making the Hospitality, Travel and Tourism (HTT) sector one of the worst affected with tremendous economic losses (Obembe et al., 2021). The World Tourism Organization has released the 11th and last one report on travel restrictions on 26th November 2021 (UNWTO, 2021), stating that 98% of all destinations have some kind of travel restrictions in place. As of 2 November 2022, where there have been 628.035.553 confirmed cases of COVID-19 globally (WHO, 2022), most countries have lifted their travel bans. This new situation, while it offers a pandemic relief, it simultaneously provokes the public opinion to be split over this policy (Stoeckel et al., 2022). Given the great number of confirmed cases, this dichotomy raises concerns on how risk perception contributes to the adoption of new patterns of behavior after severe outbreaks familiarity (Sakas et al. 2021).
Zajenkowski et al., (2020) state that during novel crisis, such as the Covid-19 pandemic, people perceptions are more likely to be influenced by situational cues, rather than personality traits. Although the research is geographically limited in one country, it is an important outcome which further supports the research of Moya et al., (2020) regarding customers’ extensive behavioral change as a consequence of crisis situations. As the public opinion has changed throughout the stages of the pandemic (Mahdikhani, 2022), so does the digital behavior of online users (Sakas et al., 2022a), pushing companies over the technology tipping point (Nasir et al., 2022). Especially for the HTT ecosystem, tourist behavior has been changed due to travel and mobility limitations, psychological and economic factors (Marques Santos et al., 2020). Cognitive, personality, and affective factors would predict travel behavior and travel preferences during the COVID-19 pandemic (Morar et al., 2021).
Conclusions The purpose of the current paper is to provide evidence on the impact of customers’ online behavior on corporate digital branding and offer guidelines on how companies could optimize customers’ satisfaction by leveraging the dynamic of big data analytics. Gathering and analyzing the digital behavior and journey of million users can provide fruitful information and valid insights on businesses within the HTT sector as the literature suggests (Buhalis & Volchek, 2021; Lv et al., 2022). However, there is little empirical evidence on how marketing managers could benefit from the information overload (Saxena & Lamest, 2018). The authors of the present research attempt to analyze the data collected from 189 hotels and 5,7 million visitors, generated from websites and social platforms, and interpret the results into actual guidelines so as to develop an effective brand communication strategy. |