Hulisi Öğüt

The influence of internet customer reviews on the online sales and prices in hotel industry

In this paper, the impact of two service quality metrics (star rating and customer rating) on hotel room sales and prices is investigated. Two of the most popular tourist destinations in the world, Paris and London, are chosen. It is found that a higher customer rating significantly increases the online sales of hotels. The study results show that a 1% increase in online customer rating increases Sales per Room up to 2.68% in Paris and up to 2.62% in London. Contrary to expectations, higher stars do not increase the sales. It is also shown that higher customer ratings result in higher prices of the hotel and the prices of high star hotels are more sensitive to online customer ratings.

Prediction of financial information manipulation by using support vector machine and probabilistic neural network

Different methods have been used to predict financial information manipulation that can be defined as the distortion of the information in the financial statements. The purpose of this paper is to predict financial information manipulation by using support vector machine (SVM) and probabilistic neural network (PNN). A number of financial ratios are used as explanatory variables. Test performance of classification accuracy, sensitivity and specificity statistics for PNN and SVM are compared with the results of discriminant analysis, logistics regression (logit), and probit classifiers, which have been used in other studies. We have found that the performance of SVM and PNN are higher than that of the other classifiers analyzed before. Thus, both classifiers can be used as automated decision support system for the detection of financial information manipulation.

Analyzing conversion rates in online hotel booking: The role of customer reviews, recommendations and rank order in search listings

Purpose – The aim of this paper is to examine the impact of three main technologies on converting browsers into customers: impact of review rating (location rating and service rating), recommendation and search listings. Design/methodology/approach – This paper estimates conversion rate model parameters using a quasi-likelihood method with the Bernoulli log-likelihood function and parametric regression model based on the beta distribution. Findings – The results show that a high rank in search listings, a high number of recommendations and location rating have a significant and positive impact on conversion rates. However, service rating and star rating do not have a significant effect on conversion rate. Furthermore, room price and hotel size are negatively associated with conversion rate. It was also found that a high rank in search listings, a high number of recommendations and location rating increase online hotel bookings. Furthermore, it was found that a high number of recommendations increase the c...

Factors affecting professionals' selection in high and low-value online service procurements

In this paper, the aim is to determine the factors that lead to selection of freelancers in the procurement of professional service. The results reveal that higher bidder rating and higher number of bidder rating increases the likelihood of winning the auction while higher bid and higher delivery time of low-value project decreases the likelihood of winning the auction. Furthermore, higher rating, higher relative time of delivery and higher bid is more important for clients of low-value projects while higher number of rating is more important for clients of high-value projects. It is also found that higher bidder rating, higher number of bidder rating and higher relative time of delivery increases the winning bid amount while higher competition decreases it.