دانلود رایگان مقاله انگلیسی پیش بینی کلی رضایت مشتری: شواهد کلان داده از بررسی آنلاین هتل - الزویر 2019

عنوان فارسی
پیش بینی کلی رضایت مشتری: شواهد کلان داده از بررسی آنلاین هتل
عنوان انگلیسی
Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
11
سال انتشار
2019
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
نوع مقاله
ISI
نوع نگارش
مقالات پژوهشی (تحقیقاتی)
رفرنس
دارد
پایگاه
اسکوپوس
کد محصول
E9336
رشته های مرتبط با این مقاله
مدیریت
گرایش های مرتبط با این مقاله
مدیریت منابع انسانی، مدیریت هتلداری
مجله
مجله بین المللی مدیریت مهمانداری - International Journal of Hospitality Management
دانشگاه
Department of Decision Sciences - College of Business - San Francisco State University - United States
کلمات کلیدی
بررسی های متنی آنلاین، ویژگی های فنی، رضایت کلی مشتری، صنعت هتل، کلان داده
doi یا شناسه دیجیتال
https://doi.org/10.1016/j.ijhm.2018.03.017
۰.۰ (بدون امتیاز)
امتیاز دهید
چکیده

ABSTRACT


Customer online reviews of hotels have significant business value in the e-commerce and big data era. Online textual reviews have an open-structured form, and the technical side, namely the linguistic attributes of online textual reviews, is still largely under-explored. Using a sample of 127,629 reviews from tripadvisor.com, this study predicts overall customer satisfaction using the technical attributes of online textual reviews and customers’ involvement in the review community. We find that a higher level of subjectivity and readability and a longer length of textual review lead to lower overall customer satisfaction, and a higher level of diversity and sentiment polarity of textual review leads to higher overall customer satisfaction. We also find that customers’ review involvement positively influences their overall satisfaction. We provide implications for hoteliers to better understand customer online review behavior and implement efficient online review management actions to use electronic word of mouth and enhance hotels’ performance.

نتیجه گیری

8.1. Conclusions


This study uses a sample of 127,629 online reviews to predict customers’ overall satisfaction through the technical attributes of online textual reviews and reviewers’ identity. We find that certain technical attributes––subjectivity, readability, and length–significantly negatively influence customer ratings, and diversity and sentiment polarity significantly positively influence customer ratings. Customers’ review engagement positively influences ratings. The findings of this study illustrate the relationships among the linguistic style of online customer reviews, customers’ identity, and overall customer perception and satisfaction.


بدون دیدگاه