Online Customer Review

Our research examines the perceptions and evaluations of prospective customers toward an online negative review and any accompanying hotel response. The study explores two main issues: whether the presence (versus absence) of an organizational response to negative customer reviews affects the inferences potential consumers draw about the target business, and which aspects of responses affect their impressions. We test the effects of four variables associated with a response: source of response, voice of responder, speed of response, and action frame on two outcomes variables (i.e., customer concern and trust inferences). The provision of an online response (versus no response) enhanced inferences that potential consumers draw regarding the business's trustworthiness and the extent to which it cares about its customers. Using a human voice and a timely response yielded favorable customer inferences. Inferences did not vary with response source or action frame. Implications are drawn for effective management of negative online reviews.

Despite the great number of tourists that attracted each year, there are only a limited number of studies that have looked at customers' satisfaction of hotels in the Asian region. This study, hence, is an attempt to fill a part of this gap. The study examines factors that affect the satisfaction of hotel guests of 1800 hotels in 40 Asian countries based on their online reviews .The data analysis was conducted via both text mining and content analysis of the online reviews posted by reviewers from one particular website – Agoda.com. The content analysis was conducted with the aid of Nvivo 7. This study observes that staff, value, location, food and dining area as well as room and hotel physical attributes are main factors that affect the customers' satisfaction within three to five star hotels. It was further found that mismatches between travelers' initial expectations compared with their actual experience such as online hotel images versus their real conditions, facilities or amenities promised but not received or of poor quality service were major causes of travelers' dissatisfaction. The current study is one of very few studies that canonize customers' satisfaction of three to five star hotels in Asia based on a large number of reviews available online.

The current research extends the theoretical axioms of Davis’ (1986) technology acceptance model to experimentally test the impact of informational online reviews on purchasing behavior through the intervening variables of trust, perceived ease of use, and perceived usefulness. Participants (N = 176) were randomly assigned one of three experimental conditions (a control condition where the product was shown without consumer reviews, a condition where the product was shown with consumer reviews employing only star-based ratings, and a condition where the product was shown with both star- and text-based consumer reviews) and were asked to complete an electronic questionnaire containing the study’s key dependent measures. The results indicated that the presence of customer-generated product reviews positively influenced product- related trust and perceptions about the product’s usefulness.

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.

In the last decades, health and illness have been redefined by the technological artefacts. This research explores users' opinions of the potentials and limits of apps related to the self-management of type 1 diabetes. Our research takes the " app " to be a socio-cultural artefact whose meanings and practices are mediated by situated practices and knowledges. The analysis has been conducted on two different kinds of texts: the description provided by the app itself (commercial description) and the reviews provided by app users (customer reviews). Our aim is thus to contribute to the study of how technological tools contribute to the processes of patients empower-ment.

The Umrah industry is one of Malaysia's most profitable industries. Despite its vast market, some identified challenges may also limit the industry's sales performance. It is therefore crucial to understand how Umrah's online consumer review (OCR) would influence the Malaysian Umrah industry, particularly in terms of sales performance. The objective of the current study is to review the OCR in relation to the challenges of the Umrah industry and issues related to the sustainability of business performance. This study proposes that the Umrah industry incorporate OCR in its marketing strategy. The adoption of OCR in the Umrah industry will lead to better future sales performance, which will induce a positive contribution to Malaysian economic growth. This paper concludes with a few conclusions and recommendations.

In this study, it was aimed to examine online customer review, which is important source of getting information from the internet and a type of e-word of mouth, via hierarchy of effects. Online customer review was examined via AIDMSAS which is a model of hierarchy of effects. Before creating the questionnaire, both focus group studies with seven participants each in Izmir and Mersin cities and literature reviews were conducted. 424 questionnaires were collected with face-to-face survey technique from two universities in Izmir and Mersin. Data was analyzed via reliability, correlation, and exploratory factor analyses and structural equation modelling. As a result, it was found out that there were seven components of online customer review for this sample as AIDMSAS model in the literature; however some steps were replaced differently and so a new model was obtained (DAISAMS). Examining online customer review via hierarchy methods for specific customer group and so obtaining the new model for specific subculture was the originality of this research.   
Keywords: Online customer reviews (OCRs), electronic word of mouth (e-WOM), hierarchy
of effects (HOE), AIDMSAS model.

In product development, the foremost issue is to identify "what" the customers’ expectations would be from the product. As
a promising approach to the product development, Quality Function Deployment also gives crucial importance to the
collection and analysis of Voice of the Customer (VoC) to deduce true customer needs. Data sources of VoC include surveys,
interviews, focus groups, gemba visits as well as customer reviews which can be collected through call centers, internet
homepages, blogs, and microblogs in social networks. Customers’ verbatim or reviews obtained from these resources require
more detailed extraction to define them as the positive restatement of problems, opportunities or image issues independent
of the product or the solution. Basically, this clarification process is a content analysis in which the developers usually seek
to extract and classify the spoken-unspoken customer needs from VoC. This labor-intensive manual approach brings
subjectivity to the analysis and can take so much time in the case of having condensed and large-volume text data. During
the past decade, the field of text mining has enabled to solve these kinds of problems efficiently by unlocking hidden
information and developing new knowledge; exploring new horizons; and improving the research process and quality. This
paper utilizes a particular algorithm of text clustering, a recently popular field of interest in text mining, to analyze VoC and
shows how text mining can also support the clarification process for better extraction of “true” customer needs. Practical
implications are presented through analysis of online customer reviews for a product.
Keywords: Voice of the Customer (VoC), Text Mining, Text Clustering, Quality Function Deployment (QFD)