“Please write a (great) online review for my hotel!” Guests’ reactions to solicited reviews

2017 ◽  
Vol 24 (2) ◽  
pp. 148-158 ◽  
Author(s):  
Francesca Magno ◽  
Fabio Cassia ◽  
Attilio Bruni

With the aim of enhancing their online reputation, several hospitality businesses have started soliciting their guests to write online reviews. Available studies have not yet evaluated the effects of this strategy. To fill this knowledge gap, this study draws on the theory of psychological reactance and investigates guests’ attitudinal and behavioral reactions to received solicitations. Evidence collected from a sample of Italian travelers indicates that soliciting reviews has both benefits and drawbacks: It increases the number of reviews for the business, but it also irritates a significant share of guests. Particularly high levels of irritation arise when a business explicitly asks its guests to write positive reviews. The implications of these findings for the reputation management strategy of hospitality businesses are discussed.

2019 ◽  
Vol 10 (1) ◽  
pp. 107-120 ◽  
Author(s):  
Zaid Alrawadieh ◽  
Mithat Zeki Dincer

PurposeDrawing on a sample of 520 negative reviews posted on TripAdvisor against all five-star hotels operating in Petra, Jordan, the purpose of this paper is to evaluate the response of luxury hotels to negative online reviews by considering the Response Rate (RR), the Response Time (RT) and the Response Content (RC).Design/methodology/approachA deductive content analysis was used on hotels’ managerial responses. Based on the literature review, a four-construct scheme was identified to guide the analysis including Appreciation; Apology; Explanation; and Incentive. The managerial responses were carefully read and manually coded based on the four-construct scheme. The time between the review posting date and the date of the managerial response was also recorded. Luxury hotel managers were also surveyed to obtain insights into their perceptions and practices with respect to online reputation management.FindingsThe findings call into question luxury hotels’ awareness of the harmful impact of negative online reviews. Specifically, the findings suggest that less than half of the negative reviews received a managerial response, and that more than half of these were standardized and did not refer to the issues raised in the reviews. The low response rate coupled with the hotel managers’ consensus on the importance of answering all online reviews indicates inconsistency between hotel managers’ perceptions and practices with regard to online reputation management.Originality/valueThe paper adds to the ongoing debate on reputation management in the hospitality industry by considering the managerial response to negative online reviews. The paper discusses several managerial implications for hotel managers as well as avenues for future research.


2018 ◽  
Author(s):  
Jonathan Fredric Waxer ◽  
Sudesh Srivastav ◽  
Christian Steven DiBiase ◽  
Steven Joseph DiBiase

BACKGROUND Online reputation management (ORM) is an emerging practice strategy that emphasizes the systematic and proactive monitoring of online reviews relating to one’s professional reputation. OBJECTIVE We developed this survey project to assess whether radiation oncologists are aware of ORM and how it is utilized in their practices. We hypothesized that ORM is largely unknown by most practicing radiation oncologists and that little time is spent actively managing their reputations. METHODS An online survey was submitted to 1222 radiation oncologists using the Qualtrics research platform. Physician emails were gathered from the American Society for Radiation Oncology member directory. A total of 85 physicians initiated the survey, whereas 76 physicians completed more than or equal to 94% (15/16) of the survey questions and were subsequently used in our analyses. The survey consisted of 15 questions querying practice demographics, patient satisfaction determination, ORM understanding, and activities to address ORM and 1 question for physicians to opt-in to a US $50 Amazon gift card raffle. The survey data were summarized using a frequency table, and data were analyzed using the Chi-square test, Fisher exact test, and Spearman correlation coefficients. RESULTS We calculated a 7% (85/1222) response rate for our survey, with a completion rate of 89% (76/85). A majority of respondents (97%, 74/76) endorsed being somewhat or strongly concerned about patient satisfaction (P<.001). However, 58% (44/76) of respondents reported spending 0 hours per week reviewing or managing their online reputation and 39% (30/76) reported spending less than 1 hour per week (P<.001). A majority of physicians (58%, 44/76) endorsed no familiarity with ORM (P<.001) and 70% (53/76) did not actively manage their online reputation (P<.001). Although 83% (63/76) of respondents strongly or somewhat believed that patients read online reviews (P<.001), 57% (43/76) of respondents did not check their online reviews (P=.25) and 80% (61/76) endorsed never responding to online reviews (P<.001). Moreover, 58% (44/76) of the respondents strongly or somewhat supported the idea of managing their online reputation going forward (P=.001). In addition, 11 out of the 28 pairs of questions asked in our correlation studies reached statistical significance. Degree of concern for patient satisfaction and the notion of managing one’s ORM going forward were the 2 most frequently correlated topics of statistical significance in our analyses. CONCLUSIONS ORM is presently under-recognized in radiation oncology. Although most practitioners are concerned about patient satisfaction, little effort is directed toward the internet on this matter. ORM offers an area of practice improvement for many practicing radiation oncologists.


Author(s):  
Olivera Grljević ◽  
Zita Bošnjak ◽  
Saša Bošnjak

Knowing what attracts or deters tourists to/from a tourist visit and what products to offer them and to pay special attention to is crucial for good economic results. Such knowledge can be obtained by analysis of online comments and reviews that tourists leave on travel websites (such as Booking, TripAdvisor, Trivago, etc.). This paper describes the value which information about opinions and emotions hidden in online reviews has for managers who receive it, especially the knowledge of (dis)satisfaction of users with certain aspects of the tourist offer. Uncovered knowledge from online reviews provides a chance to take advantage of the strong points, and correct the shortcomings through timely corrective measures and actions. Contemporary approaches and methods of analyzing online reviews and the opportunities for development they provide in the tourism industry are described through a case study conducted over a subset of 20491 hotel reviews from TripAdvisor. We have conducted sentiment analysis of reviews with the goal of building an automated model which will successfully distinguish positive from negative reviews. Logistic Regression classifier has the best performance, in 90% of reviews it has correctly classified positive reviews and in 83% negative. We have illustrated how association rules can help management to uncover relationships between concepts under discussion in negative and positive reviews.


2020 ◽  
Vol 12 (1) ◽  
pp. 50-79 ◽  
Author(s):  
Kristine D'Arbelles ◽  
Pauline Berry ◽  
Ashika Theyyil

Consumers today base many of their decisions on peer referrals and online reviews. With the omnipresence of social media and online reviews, electronic word-of-mouth marketing (eWOM) has become a priority for many companies for both business growth and reputational management. The objective of this study is to examine the effectiveness of eWOM and its impact on sales. This study also seeks to help organizational leaders understand the significance of eWOM and its role in effective consumer and stakeholder relations, and in overall brand management. The researchers of this project explored eWOM by examining Amazon reviews from two different Kickstarter companies to determine which elements of online reviews impact product sales. By overlaying Amazon review data and sales figures from each Kickstarter company, researchers were able to determine the review factors that companies should focus on to increase their sales and grow their brands. The results of this study show that products with a high volume of positive reviews made by verified purchasers positively correlate to product sales.   Keywords: electronic word-of-mouth marketing, Amazon, online reviews, Kickstarter, sales, reputational management, brand reputation, online reputation management


2022 ◽  
pp. 297-320
Author(s):  
Catarina Silva ◽  
Miguel Belo

In recent years, online reputation management has become increasingly crucial in the hotel industry, as online reviews have become one of the most critical factors in choosing accommodation. Consequently, hotels have adapted themselves to this new reality and define strategies focused on online reputation management, whose primary goal is to monitor and correct unwanted situations verified on the internet. Regarding its importance, several investigations about online reputation management have been made, but mostly about their impact on consumer satisfaction and decision-making. This investigation shows that hotels in Lisbon adopt adequate strategies in both four and five-star hotels, and their classification (star rating) did not influence the strategies chosen by them. Additionally, hotels with the same classification have similar strategies, in contrast to some investigations in the literature. Finally, the method of data collection chosen for the current investigation was the online survey, since it allows the collection of a significant volume of data in a short period.


Author(s):  
Bing Wu

AbstractAlthough some studies have explored massive open online courses (MOOCs) discussion forums and MOOC online reviews separately, studies of both aspects are insufficient. Based on the theory of self-determination, this paper proposes research hypotheses that MOOC learning progress has a direct impact on MOOC online reviews and an indirect influence on MOOC online reviews through social interactions in discussion forums, as well. Coursera the largest MOOC platform, is selected as the empirical research object, and data from learners who participated in the MOOC discussion forum and provided MOOC online reviews from August 2016 to December 2019 are obtained from the most popular course, “Machine Learning”. After processing, data from 4376 learners are obtained. Then, according to research hypotheses, multi regression models are constructed accordingly. The results show that the length of MOOC online review text is affected by the MOOC learning progress, the number of discussion forum posts, the number of follow, the online review sentiment and MOOC rating. This study highlights the main factors that affect MOOC online reviews. As a result, some suggestions are put forward for the construction of MOOC.


2021 ◽  
pp. 109634802110303
Author(s):  
Hengyun Li ◽  
Fang Meng ◽  
Simon Hudson

The research aims to examine how positive review disconfirmation (i.e., a positive deviance between a hotel consumer’s poststay evaluation and the average review rating by prior consumers) affects subsequent consumers’ willingness to post online reviews and their own review ratings. By employing an experimental research method, this study reveals that positive review disconfirmation increases hotel guests’ willingness to post online reviews, and increases their online review ratings through the mechanism of concern for others, demonstrating an act of altruism. In addition, comparatively the positive review disconfirmation effects are stronger when the variance of prior review ratings is smaller. This study enhances the online review social influence literature, and the consumer’s altruistic motivation of posting online reviews.


2017 ◽  
Vol 8 (1) ◽  
pp. 27-45 ◽  
Author(s):  
Anil Kumar ◽  
Manoj Kumar Dash

Online reputation management (ORM) is a significant and proactive tool that can reinforce the credibility of the service provider. Literature existing today on this topic has rarely reported on the causal modeling analysis from an ORM perspective. Therefore, the objective of this paper is to build a factor structure of ORM and to build the inter-relationship map amongst the criteria of each factor. To allow for vague human judgment, a fuzzy concept is employed in a form of Fuzzy Delphi. The DEMATEL technique has been used to develop a Network Relationship Map (NRM) among the criteria of each factor. Data has been gathered through a structured questionnaire conducted with a survey of experts. The study divided the criteria of each factor into cause-effect criteria. Findings of the study show that criteria such as distributed reputation system, trust, online competitive branding, website management, customer relationship, search engine optimization, corporate social responsibility, users' reach, competition/page views, purchase discounted products and cash back or money back fall under the cause group of ORM's factors. The results of this study can not only help service providers to enhance their reputation but can also guide them towards targeting their customers in an online platform.


Author(s):  
О. В. Виноградова ◽  
Н. І. Дрокіна

У статті обґрунтовано значимість заходів щодо управління репутацією в пошуковій видачі. Розглянуто поняття SERM (Search Engine Reputation Management) та ORM (Online Reputation Management), визначено основні їх відмінності. Побудовано структуру системи управління репутацією в мережі Інтернет (ORM) туристичного підприємства та виділено SERM як один з її напрямків. Сформульовано поняття SERM туристичного підприємства, визначено основне завдання управління репутацією в пошуковій видачі та мета SERM-стратегії туристичного підприємства. Побудована концептуальна модель розробки SERM-стратегії туристичного підприємства, яка має вигляд взаємозв’язаних та послідовних етапів розробки та реалізації заходів щодо створення у користувачів позитивної думки про туристичне підприємство у видачі пошукових систем. Запропоновано матрицю визначення тональності майданчиків при аналізі пошукової видачі по репутаційним запитам.


Sign in / Sign up

Export Citation Format

Share Document