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Article
Publication date: 21 September 2022

Kirsten Schlebbe

The number of children using and owning mobile devices has grown significantly in the last decade. By applying a uses and gratifications approach, this paper aims to…

Abstract

Purpose

The number of children using and owning mobile devices has grown significantly in the last decade. By applying a uses and gratifications approach, this paper aims to explore what customers of a tablet computer for children report about the use and expectations of these devices from an information behavior perspective.

Design/methodology/approach

For this study, 1,185 online customer reviews published for two different versions of the Amazon Fire Tablet Kids Edition on the German Amazon website between June 16, 2019, and June 15, 2020, were analyzed. A content analysis of the reviews was conducted using different inductive coding methods.

Findings

Findings indicate that customers describe different aspects of children's use and families' expectations of tablets within their reviews. The expressed gratifications mostly relate to the aim of entertainment. Intentional information seeking activities were hardly mentioned within the reviews, but many customers emphasize learning as an important activity with the devices. Overall, the customer reviews reveal a mix of gratifications that differ from reported motivations for adults' tablet use.

Research limitations/implications

The possibility of manipulated online customer reviews must be considered. It should also be viewed critically that the children's perspectives are only indirectly included in the data.

Originality/value

Families' expectations of tablets as a device for children have not been a focus of research to date. This study uses an innovative research design by applying a uses and gratifications approach to online customer reviews for children's tablets. The findings add to previous research on children's use and families' expectations of tablets and contribute to our understanding of children's information behavior in connection with mobile devices.

Details

Online Information Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1468-4527

Keywords

Article
Publication date: 20 May 2022

Huifeng Pan, Zhiqiang Liu and Hong-Youl Ha

Prior hospitality studies have reviewed review trustworthiness and perceived price as predictors of restaurant selection. However, the impacts of these two factors may…

Abstract

Purpose

Prior hospitality studies have reviewed review trustworthiness and perceived price as predictors of restaurant selection. However, the impacts of these two factors may vary by sales promotion and customer types. This study aims to determine whether sales promotions and customer type are the key elements that facilitate behavioral intentions by moderating the linkage between perceived price and behavioral intentions as well as the linkage between online review trustworthiness and behavioral intentions.

Design/methodology/approach

Analysis of the responses of 533 individuals familiar with the Michelin Guide for restaurants in Seoul provided evidence supporting a sales promotion theory wherein promotions signal benefits in consumers’ minds.

Findings

The findings show that when perceived price is positive and the trustworthiness of online reviews is high, repeat customers prefer mixed coupons to price discounts. Notably, the results indicate that when the trustworthiness of online reviews is high, first-time customers also prefer mixed coupons to price discounts. Furthermore, the findings suggest that negative evaluations of perceived price increase the impact of mixed coupons by signaling to first-time customers that given restaurants’ offerings provide monetary benefits regardless of their intentions to revisit said restaurants.

Research limitations/implications

The study findings provide insights that should help managers better understand various levels of promotion. Managers can design their pricing strategies to strengthen customers’ motivations to visit their restaurants – the very thing customers often seek in sales promotions.

Originality/value

This study provides indisputable evidence for a sales promotion theory, wherein promotions signal benefits in consumers’ minds; however, it also shows that first-time and repeat customers do not respond equally to sales promotions.

Details

International Journal of Contemporary Hospitality Management, vol. 34 no. 10
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 5 March 2021

Vinay Chittiprolu, Nagaraj Samala and Raja Shekhar Bellamkonda

In business, online reviews have an economic impact on firm performance. Customers’ data in the form of online reviews was used to understand the appreciation and service…

1275

Abstract

Purpose

In business, online reviews have an economic impact on firm performance. Customers’ data in the form of online reviews was used to understand the appreciation and service complaints written by previous customers. The study is an analysis of the online reviews written by the customers about Indian heritage hotels. This study aims to understand the dimensions of service appreciation and service complaints by comparing positive- and negative-rated reviews and find the patterns in the determinants of the satisfaction and dissatisfaction of the customers.

Design/methodology/approach

A total of 23,643 online reviews about heritage hotels were collected from the TripAdvisor website by using a Web crawler developed in Python. A total of 1000 reviews were randomly selected for further analysis to eliminate the bandwagon effect. Unsupervised text mining techniques were used to analyze reviews and find out the interesting patterns in text data.

Findings

Based on Herzberg two-factor theory, this study found satisfied and dissatisfied determinants separately. The study revealed some common categories discussed by satisfied and dissatisfied customers. The factors which satisfy the customers may also dissatisfy the customers if not delivered properly. Satisfied customers mentioned about tangible features of the hotel stay, which includes physical signifiers, traditional services, staff behavior and professionalism and core products (rooms, food). However, most of the customers complained about intangible service problems, such as staff attitude, services failure, issues with reservation and food, value for money and room condition. The results are contradicting with commercial hotels-based studies owing to the unique services provided by heritage hotels.

Practical implications

The dimensions for satisfaction and dissatisfaction among customer of heritage hotels provide marketers to understand the real emotion and perception of the customers. As these dimensions were extracted through text mining of the reviews written by the customer of heritage hotels, the results would certainly give better insights to the hotel marketers.

Originality/value

The study is a rare attempt to study online reviews of customers on heritage hotels through a text mining approach and find the patterns in the behavior and the determinants of satisfaction and dissatisfaction of customers.

Details

International Journal of Culture, Tourism and Hospitality Research, vol. 15 no. 2
Type: Research Article
ISSN: 1750-6182

Keywords

Article
Publication date: 19 March 2018

Xun Xu

This study aims to investigate the online customer review behavior and determinants of overall satisfaction with hotels of travelers in various travel group compositions.

1958

Abstract

Purpose

This study aims to investigate the online customer review behavior and determinants of overall satisfaction with hotels of travelers in various travel group compositions.

Design/methodology/approach

The author collected data from online reviews of travelers in various travel group compositions from 600 hotels in 100 of the largest cities in the USA from Booking.com and used latent semantic analysis (LSA) to identify the positive and negative factors from online reviews of travelers in various travel group compositions. Then, text regression was used to determine the influential factors of overall satisfaction of travelers in various travel group compositions.

Findings

It was found in this study that not all the positive and negative textual factors mined from travelers’ online reviews significantly influenced their overall satisfaction. In addition, the determinants of traveler satisfaction were different when travelers were in different travel group compositions.

Research limitations/implications

The author found similar online review behavior, but different basic, excitement and performance factors of travelers in different travel group compositions.

Practical implications

This study helps hoteliers understand customers’ perception of the specific attributes of their products and services, which provides a guideline for businesses to design the priority rule to improve these corresponding attributes and use market segmentation strategy when dealing with customers in different travel group compositions.

Originality/value

The author examined and compared the online review behavior and determinants of satisfaction using the factors mined from online reviews between travelers in various travel group compositions. This study combined customer ratings with textual reviews and predicted customer ratings from the factors extracted from textual reviews using LSA and text regression.

Details

International Journal of Contemporary Hospitality Management, vol. 30 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 21 May 2020

Jaylan Azer and Matthew Alexander

This study aims to show the impact of direct and indirect customers’ negatively valenced influencing behavior (NVIB) on other actors in online social networks.

Abstract

Purpose

This study aims to show the impact of direct and indirect customers’ negatively valenced influencing behavior (NVIB) on other actors in online social networks.

Design/methodology/approach

Four experiments were conducted in an online review setting that encompasses both restaurant and hotel reviews. The first study compares the impact of direct and indirect NVIB. The second, third and fourth studies measure this impact moderated by aggregate ratings, the volume of positive reviews and managerial responses.

Findings

Drawing on recent literature of customer engagement behavior, online reviews and social influence theory, this paper provides the first empirical results of the impact of direct and indirect NVIB, revealing the significant difference in their impact and the moderating role of the aggregate ratings, number of positive reviews and managerial responses on the cause-effect relationship between direct and indirect NVIB and other actors’ attitudes and behavioral intentions toward service providers.

Research limitations/implications

TripAdvisor reviews were selected for the reason of appropriateness rather than representativeness, using two service providers, hotels and restaurants.

Practical implications

This paper provides managers with new insights, which capture not only what customers say about service providers but also the impact of how they say it, suggesting that managers move beyond framing NVIB in generalized terms to considering the differences in the impact of its direct and indirect facets.

Originality/value

This paper is the first to provide empirical results about the significant difference in the impact of direct and indirect NVIB on other actors’ attitudes and behavioral intentions toward service providers, moderated by different heuristics, namely, ratings, volume of positive reviews and managerial responses.

Article
Publication date: 1 October 2019

Musarrat Shaheen, Farrah Zeba, Namrata Chatterjee and Raveesh Krishnankutty

Electronic commerce (e-commerce) is growing rapidly and the e-retailers are finding it pertinent to enhance customers’ online shopping experiences and engage them with…

2123

Abstract

Purpose

Electronic commerce (e-commerce) is growing rapidly and the e-retailers are finding it pertinent to enhance customers’ online shopping experiences and engage them with e-commerce portals. Against this backdrop, the purpose of this study is to develop a conceptual model of customer engagement, where credibility and usefulness of online reviews are found to trigger the adoption of reviews and customer trust that augments customer engagement.

Design/methodology/approach

A survey method design has been used to capture responses from 219 young customers (university students) of a reputed university in India. The hypothesized relationships have been examined through multiple regression analysis.

Findings

The findings of this study corroborate that the credibility and information usefulness of online reviews induce the adoption of reviews and propensity to trust e-commerce websites. The propensity to trust the reviews has been found to lead the adoption of reviews. The adoption of reviews is found to have a significant impact on the customer’ engagement with these portals.

Research limitations/implications

The present study contributes to the theories of online marketing in the space of e-shopping, online reviews, customer trust, customer engagement and online shopping behavior. Further, this study provides a framework for managers to engage customers by triggering customers’ online trust through the facilitation of credible and useful reviews.

Originality/value

The study aims at understanding the role of different attributes associated with the online reviews’ credibility and information usefulness in driving customer engagement with specific focus on online shopping through the utility of online devices. The study is one of the pioneering empirical studies that explore the role of online reviews in driving customer engagement.

Article
Publication date: 20 October 2020

Ree Chan Ho, Madusha Sandamali Withanage and Kok Wei Khong

With the growth of social media and online communications, consumers are becoming more informed about hotels' services than ever before. They are writing online review to…

Abstract

Purpose

With the growth of social media and online communications, consumers are becoming more informed about hotels' services than ever before. They are writing online review to share their experiences, as well as reading online review before making a hotel reservation. Hotel customers considered it as reliable source and it influences customers' hotel selection. Most of these reviews reside in unstructured format, scattered across in the Internet and inherently unorganized. The purpose of this study was to use predictive text analytics to identify sentiment drivers from unstructured online reviews.

Design/methodology/approach

The research used sentiment classifications to analyze customers' reviews on hotels from TripAdvisor. In total, 9,286 written reviews by hotel customers were scrapped from 442 hotels in Malaysia. A detailed text analytic was conducted and was followed by a development of a theoretical framework based on the hybrid approach. AMOS was used to analyze the relationship between customer sentiments and overall review rating.

Findings

With the use of Structural Equation Modeling (SEM) and clustering technique, a list of sentiment drivers was detected, i.e. location, room, service, sleep, value for money and cleanliness. Among these variables, service quality and room facilities emerged as the most influential factors. Sentiment drivers obtained in this study provided the insights to hotel operators to improve the hotel conditions.

Research limitations/implications

Although this study extended the existing literature on sentiment analysis by providing valuable insights to hoteliers, it is not without its limitations. For instance, online hotel reviews collected for this study were limited to one specific online review platform. Despite the large sample size to support and justify the findings, the generalizability power was restricted. Thus, future research should also consider and expand to other type of online review channels. Therefore, a need to examine these data reside various social media applications, i.e. Facebook, Instagram and YouTube.

Practical implications

This study highlights the significance of hybrid predictive model in analyzing the unstructured hotel reviews. Based on the hybrid predictive model we developed, six sentiment drivers emerged from the data analysis, i.e. location, service quality, value for money, sleep quality, room design and cleanliness. This consideration is critical due to the ever-increasing unstructured data resides in the online space. This explores the possibility of applying data analytic technique in a more efficient manner to obtain customer insights for hotel managerial consideration.

Originality/value

This study analyzed customer sentiments toward the hotel in Malaysia with the use of predictive text analytics technique. The main contribution was the list of sentiment drivers and the insights needed to improve the hotel conditions in Malaysia. In addition, the findings demonstrated motivating findings from different methodological perspective and provided hoteliers with the recommendation for improved review ratings.

Details

Asia-Pacific Journal of Business Administration, vol. 12 no. 3/4
Type: Research Article
ISSN: 1757-4323

Keywords

Article
Publication date: 6 September 2018

Pengfei Zhao, Ji Wu, Zhongsheng Hua and Shijian Fang

The purpose of this paper is to identify electronic word-of-mouth (eWOM) customers from customer reviews. Thus, firms can precisely leverage eWOM customers to increase…

1729

Abstract

Purpose

The purpose of this paper is to identify electronic word-of-mouth (eWOM) customers from customer reviews. Thus, firms can precisely leverage eWOM customers to increase their product sales.

Design/methodology/approach

This research proposed a framework to analyze the content of consumer-generated product reviews. Specific algorithms were used to identify potential eWOM reviewers, and then an evaluation method was used to validate the relationship between product sales and the eWOM reviewers identified by the authors’ proposed method.

Findings

The results corroborate that online product reviews that are made by the eWOM customers identified by the authors’ proposed method are more related to product sales than customer reviews that are made by non-eWOM customers and that the predictive power of the reviews generated by eWOM customers are significantly higher than the reviews generated by non-eWOM customers.

Research limitations/implications

The proposed method is useful in the data set, which is based on one type of products. However, for other products, the validity must be tested. Previous eWOM customers may have no significant influence on product sales in the future. Therefore, the proposed method should be tested in the new market environment.

Practical implications

By combining the method with the previous customer segmentation method, a new framework of customer segmentation is proposed to help firms understand customers’ value specifically.

Originality/value

This study is the first to identify eWOM customers from online reviews and to evaluate the relationship between reviewers and product sales.

Details

Industrial Management & Data Systems, vol. 119 no. 1
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 24 October 2017

Run Hong Niu and Ying Fan

More and more customers refer to online reviews before making any purchasing decisions thanks to the increasing popularity of social media and online shopping. This…

1941

Abstract

Purpose

More and more customers refer to online reviews before making any purchasing decisions thanks to the increasing popularity of social media and online shopping. This phenomenon has caught the attention of business managers who are increasingly aware that online reviews provide great opportunities to connect with current and potential customers. However, both practices and research on online review management from the businesses’ perspective are fragmented. The purpose of this paper is to develop an integrative framework that includes the key dimensions of an online review management system.

Design/methodology/approach

Based on the Grounded Theory approach, the authors conducted a multiple case study by analyzing the interviews with 11 hospitality services.

Findings

The authors found that an online review management system should go beyond the current norm of response management to incorporate key dimensions of formality, centralization, specialization, response customization, integration and review analytics.

Practical implications

The study provides a systematic guideline for online review management practices. The framework can be used as a tool for a business to evaluate existing online review management practices and develop/refine its online review management system.

Originality/value

The study contributes to online review management literature by developing a comprehensive framework to understand the structure and processes of online review management. The key dimensions of an online review management system identified in this study provide an initial measurement model for the online review management construct. Furthermore, the study provides a springboard for future empirical validation and refinement of the key factors for effective online review management.

Details

Journal of Service Theory and Practice, vol. 28 no. 1
Type: Research Article
ISSN: 2055-6225

Keywords

Article
Publication date: 2 September 2022

Jaeseung Park, Xinzhe Li, Qinglong Li and Jaekyeong Kim

The existing collaborative filtering algorithm may select an insufficiently representative customer as the neighbor of a target customer, which means that the performance…

Abstract

Purpose

The existing collaborative filtering algorithm may select an insufficiently representative customer as the neighbor of a target customer, which means that the performance in providing recommendations is not sufficiently accurate. This study aims to investigate the impact on recommendation performance of selecting influential and representative customers.

Design/methodology/approach

Some studies have shown that review helpfulness and consistency significantly affect purchase decision-making. Thus, this study focuses on customers who have written helpful and consistent reviews to select influential and representative neighbors. To achieve the purpose of this study, the authors apply a text-mining approach to analyze review helpfulness and consistency. In addition, they evaluate the performance of the proposed methodology using several real-world Amazon review data sets for experimental utility and reliability.

Findings

This study is the first to propose a methodology to investigate the effect of review consistency and helpfulness on recommendation performance. The experimental results confirmed that the recommendation performance was excellent when a neighbor was selected who wrote consistent or helpful reviews more than when neighbors were selected for all customers.

Originality/value

This study investigates the effect of review consistency and helpfulness on recommendation performance. Online review can enhance recommendation performance because it reflects the purchasing behavior of customers who consider reviews when purchasing items. The experimental results indicate that review helpfulness and consistency can enhance the performance of personalized recommendation services, increase customer satisfaction and increase confidence in a company.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

1 – 10 of over 123000