مقاله انگلیسی رایگان در مورد درک رابطه بین نقض ایمنی و انتقال کرونا با آنالیز داده ها – الزویر ۲۰۲۲

مقاله انگلیسی رایگان در مورد درک رابطه بین نقض ایمنی و انتقال کرونا با آنالیز داده ها  – الزویر ۲۰۲۲

 

مشخصات مقاله
ترجمه عنوان مقاله استفاده از تجزیه و تحلیل داده ها برای درک رابطه بین نقض ایمنی رستوران ها و انتقال کووید ۱۹
عنوان انگلیسی مقاله Leveraging data analytics to understand the relationship between restaurants’ safety violations and COVID-19 transmission
انتشار مقاله سال ۲۰۲۲
تعداد صفحات مقاله انگلیسی ۱۰ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) Scopus – Master Journal List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
۱۰٫۵۴۰ در سال ۲۰۲۰
شاخص H_index ۱۳۶ در سال ۲۰۲۲
شاخص SJR ۲٫۵۱۲ در سال ۲۰۲۰
شناسه ISSN ۰۲۷۸-۴۳۱۹
شاخص Quartile (چارک) Q1 در سال ۲۰۲۰
فرضیه دارد
مدل مفهومی دارد
پرسشنامه ندارد
متغیر دارد
رفرنس دارد
رشته های مرتبط مدیریت – مهندسی کامپیوتر
گرایش های مرتبط مدیریت هتلداری – مدیریت کسب و کار – هوش مصنوعی
نوع ارائه مقاله
ژورنال
مجله  مجله بین المللی مدیریت مهمان نوازی – International Journal of Hospitality Management
دانشگاه Rosen College of Hospitality Management, University of Central Florida, USA
کلمات کلیدی شکایات – Covid -19 – رستوران – نقض ایمنی – شبکه های عصبی – تجزیه و تحلیل مکانی
کلمات کلیدی انگلیسی Complaints – COVID-19 – Restaurant – Safety violation – Neural networks – Spatial analysis
شناسه دیجیتال – doi
https://doi.org/10.1016/j.ijhm.2022.103241
کد محصول e16758
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
۱٫ Introduction
۲٫ Literature review and hypothesis development
۳٫ Research methods
۴٫ Results and analysis
۵٫ Discussion and conclusion
Declaration of Competing Interest
Acknowledgements
References

بخشی از متن مقاله:

Abstract

     This paper leverages natural language processing, spatial analysis, and statistical analysis to examine the relationship between restaurants’ safety violations and COVID-19 cases. We used location-based consumers’ complaints data during the early stage of business reopening in Florida, USA. First, statistical analysis was conducted to examine the correlation between restaurants’ safety violations and COVID-19 transmission. Second, a neural network-based deep learning model was developed to perform topic modeling based on consumers’ complaints. Third, spatial modeling of the complaints’ geographic distributions was performed to identify the hotspots of consumers’ complaints and COVID-19 cases. The results reveal a positive relationship between consumers’ complaints about restaurants’ safety violations and COVID-19 cases. In particular, consumers’ complaints about personal protection measures had the highest correlation with COVID-19 cases, followed by environmental safety measures. Our analytical methods and findings shed light on customers’ behavioral shifts and hospitality businesses’ adaptive practices during a pandemic.

Introduction

     The outbreak of COVID-19 has significantly impacted the hospitality industry. Business closures, lockdowns, businesses’ capacity control, and travel restrictions have caused an immediate downturn in the hospitality market with potential long-term consequences (Baum and Hai, 2020, Huang et al., 2020). In the United States, most states mandated stay-at-home orders during the first week of April 2020 and allowed businesses to reopen in late April or early May 2020. Immediately after reopening, May and June of 2020 witnessed an upsurge in COVID-19 cases (New York Times, 2020). It was found that 25% of the COVID-19 cases were linked to visits to bars and restaurants (Foster & Mundell, 2020). The ongoing outbreaks have pressured many states such as Florida to reclose bars and restaurants for another short period to curb the fast transition of the disease (Siemaszko, 2020).

     The restaurant industry is one of the most affected industries amid amid a the COVID-19 pandemic (Huang et al., 2021, Gössling et al., 2020). Fears and worries about catching the COVID-19 disease were amplified in food and beverage establishments due to the high-contact nature (Chen & Eyoun, 2021). As the economy reopened, restaurants needed to redesign their business operations to offer consumers higher safety and security standards using flexible service and payment mechanisms. For example, contactless menus, mobile payment systems, on-site sanitizers, routine sanitization practices, and screening diners were implemented by food and beverage establishments to encourage customers to dine out (Dube et al., 2020). Despite growing research on restaurants’ adaptive strategies in such swiftly changing environments, a general halo of uncertainty still lingers about how to enhance restaurants’ quality of service and consumers’ satisfaction while reducing COVID-19 transmission.

Discussion and conclusion

     This research utilized multiple models and approaches to investigate customers’ complaints about restaurants’ safety violations and their correlation with COVID-19 transmission during the pandemic. Thematic analysis and natural language processing modeling were adopted to assess the types of violations. Of the six types of complaints about restaurants, employees’ personal protection (e.g., wearing masks and gloves) and restaurants’ environmental safety (e.g., social distancing) were customers’ major concerns. Statistical analysis confirmed the positive relationship between complaints about restaurants’ violations and the COVID-19 cases. In addition, spatial analysis was performed to identify the hotspots of COVID-19 cases and restaurants’ safety violations at the county level. The findings were consistent with Lee et al.’s (2019) study, suggesting that higher occurrences of food safety violations can be found at tourist destinations. The findings also confirmed the results from Yang et al. (2020), which showed that fast-food restaurants overall receive fewer complaints regarding safety violations than indoor dining services due to the flexibility of food delivery options.

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