Since social media has been growing rapidly, the restaurant industry has been exploring this area extensively. Given that social media provides restaurant consumers with an opportunity to share their dining experiences, several studies have examined the impact of social media on consumer restaurant selection (Tran, 2015). As a part of the social media umbrella, online reviews are significant factors that influence consumer restaurant selection (Park & Nicolau, 2015; Yang, Hlee, Lee, Koo, 2017). However, there is a lack of understanding with regard to which attributes of restaurant online reviews are the most influential when it comes to customer decision making. Therefore, this study aims to investigate the relative importance of online review attributes in consumer restaurant selection. Particularly, this study focuses on the number of online reviews, the overall restaurant rating, and the following restaurant attributes: food quality, service quality, atmosphere, and price, to address the purpose of the research. Based on the recommendation of Orme, (2010), 353 respondents are recruited via Amazon’s Mechanical Turk, and a choice-based-conjoint (CBC) analysis is performed. The CBC analysis reveals the relative importance of each attribute for customer decision making. Based on the CBC analysis, the results confirms that food quality is the most important attribute in consumer restaurant selection. This factor is followed by overall restaurant rating, price, service quality, the number of online reviews, and atmosphere. Additionally, the overall restaurant rating is determined to be a substantially important factor that influences consumer restaurant selection, while the rest of the attributes vary in their rank. The market simulation calculated the preference estimates for the products for each respondent. This approach predicts the impact of each attribute on the market share. Food quality and overall restaurant rating are used for the market simulations. Therefore, it is also found that in relation to the market simulation, the decrease of food quality influenced the market share by about 58.88%. The findings of this study contribute greatly to the knowledge of the importance of food quality, and as a result, an overall restaurant rating. Therefore, restaurant managers should prioritize these key attributes to manage strategies for the restaurant

The Internet has grown to become one of the most influential tools affecting the tourism industry. This study seeks to explore a smaller piece of a widely recognized phenomenon, breaking off to study the impacts of online reviews on TripAdvisor and electronic word-of-mouth in the hotel sector. The study further attempts to identify problems and advantages with the increased use of consumer generated media-sites. One of the main motivations for this study is also the lack of profound studies examining hotel responses to online reviews and destination impacts. The scope of this study is limited to examine three hotels and their respective reviews, on the Aland Islands. Thus this study does not necessarily seek to generalize results in other instances. The identified problem in this thesis is that hotel operators experience difficulties in managing what is being written about them as the perception of time and space changes, owing to the Internet. In making progress to this problem, the study was conducted through semi-structured interviews and a thematic analysis, to understand the specifics of the context. Furthermore, this methodology was used to understand the perspectives of the informants. The results indicate that online reviews on TripAdvisor follow specific themes and are considered an important source of information for hotel operators. However, there seems to be some limitations in management, due to lack of opportunities and strategic plans of actions in the hotel sector. There is, however, a collective understanding and willingness amongst hotels to further immerse themselves in the work of managing reviews.

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Date: (2022-06-01) Level: Master thesis in Business Administration, 15 cr. Institution: School of Business, Society and Engineering, Mälardalen University. Authors: Mohammad Battha, (1993-06-10) Fadi Zina (1989-01-04) Title: The impact of online reviews and influencers on customers' purchasing intention. Supervisor:Stylianos Papaioannou Keywords: Influencers, Online reviews, Purchasing intention, Generation Y-Z. Research question: What is the impact of online reviews and influencers on the purchaseintentions of generations Y and Z of a given product or service? Purpose: Authors are aiming to investigate how influencers and online reviews can boost thepurchase intention of a brand. Hence, the authors scrutinize some of the influencers' andonline reviews' characteristics and analyze their impacts on purchasing intention from ageneration Y and Z customer perspective. The authors foresee expanding the literature andopening a door for further research in this narrow area of study. Methods: a deductive research method was applied through direct questionnaires to anumber of online consumers to test hypotheses in this research, and later the data wasanalyzed through regression and correlations tables. Conclusion: The online reviews by previous customers have a strong impact on customer’spurchase intentions. Also, the message carried by the product ambassadors such as bloggersand celebrities impacts the customers’ purchase intentions. The influencers carry the image ofa product and thus it is significant for the marketing brands to consider a careful selection ofbrand ambassadors as this impacts greatly on the future customer purchase intention.

The aim of this degree project is to gain a deeper understanding of how online reviews affect consumers' purchase intentions when purchasing high-involvement products. Exploring the differences of effect between two separate generations of consumers, Generation Z and Millennials. The age intervals have been 18-41, 18-25 for Generation Z consumers and 26-41 for Millennials. This research is utilizing a deductive approach paired with a quantitative research strategy. The primary data collection method has been through an internet-based self-completed questionnaire, whereas the data later on has been analyzed. The analysis has been conducted through the Statistical Package for Social Sciences (SPSS) program allowing for the researchers to perform a series of statistical analyses. From the empirical findings and analysis conducted, it was concluded that all of the hypotheses were disproven and rejected, showing no significant difference. Through SPSS a series of independent sample t-tests were conducted to extract two means for the two generations. The statistical output displayed a higher level of impact on Millennials consumers contrary to the hypothesis, predicting Generation Z’s purchase intentions being significantly more impacted. Through SPSS the researcher have been able to compare how each generation compare against each other in terms of all the variables making up purchase intention (Involvement, Argument Quality, Source Credibility, Information Usefulness), but also performed t-tests to see how their answers differentiate in each question as well. This study could provide marketers with very insightful knowledge about how online reviews affect consumers differently, allowing for adaptation and optimizations.

Avec le développement du commerceélectronique, les clients ont publié de nombreuxcommentaires de produit sur Internet. Ces donnéessont précieuses pour les concepteurs de produit, carles informations concernant les besoins de client sontidentifiables. L'objectif de cette étude est dedévelopper une approche d'analyse automatique descommentaires utilisateurs permettant d'obtenir desinformations utiles au concepteur pour guiderl'amélioration et l'innovation des produits.L’approche proposée contient deux étapes :structuration des données et analyse des données.Dans la structuration des données, l’auteur proposed’abord une ontologie pour organiser les mots et lesexpressions concernant les besoins de client décrientdans les commentaires. Ensuite, une méthode detraitement du langage naturelle basée des règleslinguistiques est proposé pour structurerautomatiquement les textes de commentaires dansl’ontologie proposée.Dans l’analyse des données, deux méthodes sontproposées pour obtenir des idées d’innovation et desvisions sur le changement de préférence d’utilisateuravec le temps. Dans ces deux méthodes, les modèleset les méthodes traditionnelles comme affordancebasedesign, l’analyse conjointe, et le Kano modelsont étudié et appliqué d’une façon innovante.Pour évaluer la praticabilité de l’approche proposéedans la réalité, les commentaires de client de liseusenumérique Kindle sont analysés. Des pistesd’innovation et des stratégies pour améliorer leproduit sont identifiés et construites. / With the development of e-commerce,consumers have posted large number of onlinereviews on the internet. These user-generated dataare valuable for product designers, as informationconcerning user requirements and preference can beidentified.The objective of this study is to develop an approachto guide product design by analyzing automaticallyonline reviews. The proposed approach consists oftwo steps: data structuration and data analytics.In data structuration, the author firstly proposes anontological model to organize the words andexpressions concerning user requirements in reviewtext. Then, a rule-based natural language processingmethod is proposed to automatically structure reviewtext into the propose ontology.In data analytics, two methods are proposed based onthe structured review data to provide designers ideason innovation and to draw insights on the changes ofuser preference over time. In these two methods,traditional affordance-based design, conjointanalysis, the Kano model are studied andinnovatively applied in the context of big data.To evaluate the practicability of the proposedapproach, the online reviews of Kindle e-readers aredownloaded and analyzed, based on which theinnovation path and the strategies for productimprovement are identified and constructed.

Indiana University-Purdue University Indianapolis (IUPUI) / The purpose of this work is to prove that the visualization is at least as powerful as the best automatic feature selection algorithms. This is achieved by applying our visualization technique to the online review classification into fake and genuine reviews. Our technique uses radial chart and color overlaps to explore the best feature selection through visualization for classification. Every review is treated as a radial translucent red or blue membrane with its dimensions determining the shape of the membrane. This work also shows how the dimension ordering and combination is relevant in the feature selection process. In brief, the whole idea is about giving a structure to each text review based on certain attributes, comparing how different or how similar the structure of the different or same categories are and highlighting the key features that contribute to the classification the most. Colors and saturations aid in the feature selection process. Our visualization technique helps the user get insights into the high dimensional data by providing means to eliminate the worst features right away, pick some best features without statistical aids, understand the behavior of the dimensions in different combinations.

Background Today the hotel industry has become very digitalized compared to when there was only a travel catalogue to look in. Nowadays people search for information about hotels and read reviews from past guests online. There are different kinds of accommodations and lately it has become popular with shared services like Airbnb. With the rise of digitalization the hotel market competition has increased tremendously, therefore it is important for the hotels to keep a good reputation. Services like a hotel stay can be experienced differently from person to person and thus it is important for the service personnel to possess emotional intelligence.  Purpose The purpose with this study is to find out how the consumer behavior changes depending on the reviews. The study should give knowledge to hotel management about how it is possible to improve their relationship with guests by service, reviews and the use of digitalization. This study wants to update the research on the topic reviews and how it affects the consumers when booking a hotel with new information since the technology changes constantly and thus some research about the field in the past might not mirror the reality today.  Method This study was conducted using a quantitative method survey study in the form of an internet questionnaire. This questionnaire contained mostly closed ended questions however there were some open questions that allowed the participants to name a factor that was important for them. The survey used convenience sampling to be able to receive a lot of answers quickly. To ensure that the answers were of good quality anonymous answers has been applied and there was a qualification question that can sort out unqualified and spam answers to obtain the best quality. To analyze the results from the survey, descriptive analytics and statistical inference will be used and compared with previous research. The statistical analysis will be done by SPSS (Statistical Package for the Social Sciences) and Excel.  Conclusion  The study has come to the conclusion that reviews affect and have an impact on all the different stages in the consumer decision making process. The study also conclude that it is important for the hotel to try to increase the number of reviews since with the rise of reviews the more trustworthy the reviews will be. The study also concluded that it has become important with digitalization in the hotel industry and that 29,5% of the study participants use the mobile app when booking a hotel. Thus, the hotel management must follow and adapt the hotel to the new way of communication.

This thesis is situated in the research field of electronic commerce, specifically the aspect of fast fashion brands. This has drawn consumer interest because they find struggles when shopping for clothes online due to their inability to try the product before purchasing from sellers, which tends to result in information asymmetry. Therefore, they may be more hesitant to purchase online due to the perceived risk that results in low level of trust while shopping clothes online; therefore, businesses should strive to alleviate their concerns. Previous research has shown that electronic word of mouth (e-WOM) can guide and increase confidence.  The purpose of this study is to gain a better understanding of how consumers perceive online reviews as ways of reducing information asymmetry and reduce risk in order to ensure that they will be satisfied with their purchase. Furthermore, many factors identified in previous research that could influence the use of online reviews were identified and analyzed in the context of fast fashion for this study. Therefore, the study discovered several factors that influenced the use of online reviews.  This study investigates the role of trust as a mediator between customers' perception of electronic word-of-mouth (eWOM) and their subsequent actions. Specifically, the study focuses on the influence of the perceived usefulness of online reviews on customer trust in fast fashion websites. To gain a comprehensive understanding of consumers' opinions on online reviews, a qualitative research approach employing semi-structured interviews was conducted. The interviews provided participants with the opportunity to elaborate on their responses and provide nuanced insights. The findings indicate that fast fashion brands should prioritize the inclusion of online reviews and enhance their mechanisms based on the factors identified in this study. By recognizing the importance of customer trust and addressing the perceived usefulness of online reviews, fast fashion brands can improve their relationship with customers and foster positive consumer actions. This study contributes to the existing literature on eWOM, trust, and online reviews, offering practical implications for fast fashion brands aiming to optimize their online platforms.

In the digital age, with the accelerating pace of e-commerce, online platforms such as Amazon, Yelp, TripAdvisor, Facebook, Netflix, Uber and others have gained in prominence. Furthermore, in the wake of the COVID-19 pandemic, even businesses which were heretofore primarily brick-and-mortar have had to shift to a strong online presence in order to adapt and survive; which, while beneficial to all stakeholders, has resulted in dire challenges for the producers/service providers, platform owners, as well as consumers. In my first essay, I investigate the challenges faced by mobility as a service (MaaS) platforms such as Uber and Lyft for managing their demand and the pool of available drivers. On one hand, driver compensation issues in MaaS platforms is a highly discussed topic. On the other hand, the MaaS platforms are expanding to encompass several external businesses in search of profitability. In this chapter, I focus primarily on driver compensation issues in MaaS platforms when the platforms engage in external businesses. I find that in the majority of instances, the driver compensation reduces when the platforms get involved in external businesses; however, there are a few cases, where it leads to an increment in driver compensation, thus benefiting them. The second essay is on the impact of online reviews from digital platforms such as Yelp and TripAdvisor on business performance. Using a data set from Yelp, first, I study the interaction of average rating and number of reviews on business performance; second, how competition affects the interaction effect of the average rating and number of reviews on the focal business' performance. I find that the impact of the interaction of average rating and number of reviews on business performance is different at various levels of average ratings, and the inclusion of competition negatively influences the interaction effect of the average rating and number of reviews on the performance of the focal restaurant. In my third essay, I analyze how the interaction of supplier encroachment and consumer showrooming impacts an omnichannel retailer and her upstream manufacturer, who encroaches the downstream retailer's market with an online direct sales channel. I identify different scenarios in a covered market where either the retailer, or the manufacturer, or both will be better off. Taken together, these three essays provide valuable managerial insights for real world business problems, which will empower researchers in academia and industry managers, and help them improve their businesses and maximize their operational performance. / Business Administration/Marketing