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Drawing on the elaboration likelihood model (ELM), the authors examine the influence of perceived professor teaching qualities, as central cues, on online professor ratings. Also, our study investigates how the volume and period of reviews, as peripheral cues, affect online professor ratings.

Leveraging stratified random sampling, the authors collect reviews of 892 Information Systems professors from 250 American universities. The authors employ regression models while conducting robustness tests through multi-level logistic regression and causal inference methods.

Our results suggest that the central route from perceived professor qualities to online professor ratings is significant, including most qualitative pedagogical factors except positive assessment. In addition to course difficulty, the effect of the peripheral route is limited due to deficient diagnosticity.

Our primary concern about the data validity is a lack of a competing and complementary dataset. However, an institutional evaluation survey or an experimental study can corroborate our findings in future research.

Online professor review sites can enhance their perceived diagnosticity and credibility by increasing review vividness and promoting site interactivity. In addition to traditional institutional evaluations, professors can obtain insightful feedback from review sites to improve their teaching effectiveness.

To our best knowledge, this study is the first attempt to employ the ELM and accessibility-diagnosticity theory in explicating the information processing of online professor reviews. It also sheds light on various determinants and routes to persuasion, thus providing a novel theoretical perspective on online professor reviews.

This study seeks to investigate and discuss the heritage experiences of both domestic and international visitors at Göbeklitepe UNESCO World Heritage Site in Türkiye.

A qualitative research approach was adopted in the current study. TripAdvisor's comments and reviews of both domestic (n = 519) and international (n = 186) visitors regarding their visits to Göbeklitepe were collected. The data were then subjected to content analysis by MAXQDA as qualitative data analysis software. Additionally, an abductive research approach, which consisted of three stages, was implemented for data analysis.

The three aspects of visitor experiences at Göbeklitepe, including cognitive, emotional and relational experiences were found and discussed. Additionally, commonalities and differences among domestic and international visitors in terms of the heritage experience they gained from their visit to Göbeklitepe were revealed and analyzed.

Based on the findings regarding the main aspects of heritage experiences at Göbeklitepe, including cognitive, emotional and relational experiences, site managers and destination marketers can create effective marketing strategies that focus on those characteristics to attract visitors to the site. Moreover, the study can guide destination marketers to develop targeted marketing campaigns that highlight the different historical and religious significance of the site for both groups of domestic and international visitors.

First, the study affirms that Göbeklitepe is an important and impressive cultural heritage site due to its historical significance to both domestic and international visitors. It also strengthens the multifaceted nature of heritage experiences. Especially, the evidence of relational heritage experiences, including the connectedness to heritage and the sense of belonging to the visitor community, enriches the literature of heritage experience in this regard.

The construction industry is affected by the technologies of Industry 4.0 as the buildings are transforming into complex productions. Integration of innovative technologies, such as virtual reality (VR) and augmented reality (AR), in construction management is an emerging area to increase efficiency and effectiveness. With an aim of determining the current situation, this study evaluates the literature on VR and AR within construction management research.

The methodology of this research is based on descriptive and bibliometric analyses to understand and state the current relations between VR-AR technologies and construction management research. According to the meta-analysis (Preferred Reporting Items for Systematic Reviews and Meta-Analyses [PRISMA]) protocol of reviewing, 143 papers between 2010 and 2021 from Scopus, Web of Science (WoS) and Science Direct have been retrieved, and then analysis has been applied on these papers. Descriptive analysis contains increment of publications throughout the years, rates of papers according to countries and content of the publications. The bibliometric analysis involves the analysis through Excel and VOSviewer: co-occurrence of keywords, country-based, source and citation.

The results of this study emphasize the increasing interest in the adoption of VR-AR technologies in construction management research. As the number of publications has been continuously increased, this trend indicates the strength and growing interest in the topic. Another significant finding is VR-AR implementation studies are mostly based on building information modelling (BIM). In this study, the results of analyses have been discussed in terms of learning, knowledge areas and digital technologies as part of construction management.

This study contributes to providing a significant theoretical reference for the potentials of VR-AR in construction management research. VR-AR technologies mostly attract the interest of researchers from architectural design studies; however, there is a gap to investigate their potentials in terms of construction management. Additionally, this study focuses on the last 11 years, which indicate the latest trends.

The purpose of this study is to investigate how book group recommendations can be used as a meaningful way to suggest suitable books to users, given the increasing number of individuals engaging in sharing and discussing books on the web.

The authors propose reviews fine-grained classification (CFGC) and its related models such as CFGC1 for book group recommendation. These models can categorize reviews successively by function and role. Constructing the BERT-BiLSTM model to classify the reviews by function. The frequency characteristics of the reviews are mined by word frequency analysis, and the relationship between reviews and total book score is mined by correlation analysis. Then, the reviews are classified into three roles: celebrity, general and passerby. Finally, the authors can form user groups, mine group features and combine group features with book fine-grained ratings to make book group recommendations.

Overall, the best recommendations are made by Synopsis comments, with the accuracy, recall, F-value and Hellinger distance of 52.9%, 60.0%, 56.3% and 0.163, respectively. The F1 index of the recommendations based on the author and the writing comments is improved by 2.5% and 0.4%, respectively, compared to the Synopsis comments.

Previous studies on book recommendation often recommend relevant books for users by mining the similarity between books, so the set of book recommendations recommended to users, especially to groups, always focuses on the few types. The proposed method can effectively ensure the diversity of recommendations by mining users’ tendency to different review attributes of books and recommending books for the groups. In addition, this study also investigates which types of reviews should be used to make book recommendations when targeting groups with specific tendencies.

This research investigates consumer intention to follow online community advice. Applying the technology acceptance model (TAM) to the context of online restaurant communities, the study empirically examines the effects of perceived usefulness, perceived ease of use, attitude and trust on the intention to follow online advice.

The data were collected from 360 members of online restaurant communities on Facebook and analyzed using structural equation modeling (SEM).

The findings revealed that trust, perceived usefulness and attitude are key predictors of the intention to follow online restaurant community advice.

Extant research on the influence of online reviews on consumer behavior in the restaurant industry has largely focused on the characteristics of the review, reviewers or readers. Moreover, other studies have investigated consumers' motivations to write online restaurant reviews. This study, however, takes a different approach and examines what drives consumers to follow the advice from online restaurant communities.

This work aims to explore why people review their experienced online shopping in such a manner (promptness), and what is the potential relationship between the users’ review promptness and review motivation as well as reviewed contents.

To evaluate the customers’ responses regarding their shopping experiences, in this paper, the “purchase-review” promptness is studied to explore the temporal characteristics of users’ reviewing behavior online. Then, an aspect mining method was introduced for assessment of review text. Finally, a theoretical model is proposed to analyze how the customers’ reviews were formed.

First, the length of time elapsed between purchase and review was found to follow a power-law distribution, which characterizes an important number of human behaviors. Within online review behaviors, this meant that a high frequency population of reviewers tended to publish relatively quick reviews online. This showed that the customers’ reviewing behaviors on e-commerce websites may have been affected by extrinsic motivations, intrinsic motivations or both. Second, the proposed review-to-feature mapping technique is a feasible method for exploring reviewers’ opinions in both massive and sparse reviews. Finally, the customers’ reviewing behaviors were found to be mostly consistent with reviewers’ motivations.

First, the authors propose that the “promptness” of users in posting online reviews is an important external manifestation of their motivation, product experience and service experience. Second, a semi-supervised method of review-to-aspect mapping is used to solve the data quality problem in mining information from massive text data, which vary in length, detail and quality. Finally, a huge amount of e-commerce customers’ purchase-review promptness are studied and the results indicate that not all product features are responsible for the “prompt” posting of users’ reviews, and that the platform’s strategy to encourage users to post reviews will not work in the long term.

The purpose of this study is to review the plethora of studies on knowledge management (KM) in the hospitality and tourism. The purposes of this paper through a bibliometric analysis via the VOSviewer tool are to analyze the current research stream and to assess emerging trends in KM in the tourism and hospitality field.

A total of 1,732 publications with 65,150 cited references were retrieved from the Web of Science to uncover the structure and intellectual base of studies in tourism with a KM perspective. Three bibliometric analyses were performed using VOSviewer software (citation, co-citation and co-occurrence of keywords); this study aims to uncover the knowledge structure of the past, current and future trends based on the bibliographic database by assessing the most influential past publication; determining the structure of the co-cited publications; and evaluating emerging trends for future studies.

This study produced two ground-breaking research streams inductively evaluated from the three bibliometric analyses: KM and digital technology; and innovation in tourism. Furthermore, the pressing issue of sustainability in tourism from the perspective of KM would be a crucial aspect in the tourism field. These streams would provide fundamental knowledge-based and further enhance the assimilation of KM within the tourism sector. The outcome would facilitate future scholars to link important tourism topics to benefit the tourism industry facing a competitive and challenging business environment.

This study contributes to the current theoretical understanding through thematic knowledge mapping of KM and the tourism and hospitality field.

To the best of the author’s knowledge, this study is the first to apply bibliometric analysis to the tourism and KM field by providing a basis for the most significant issue in tourism and the essence of emerging topics and trends.

When a new logo is released, it does not have an established meaning in the mind of the viewer. As logos have become more highly scrutinized by consumers and critics, it has become more important to understand viewers’ initial responses to logos. While other studies have researched the impact of aesthetic choices on viewer reaction to logos, this study aims to understand the effect of the surrounding visual identity system when a new logo is introduced.

This study combines a content analysis of 335 posts on the logo review website Brand New with the voting data from their polls to understand how visual context correlates with a viewer’s initial response.

Increased amounts of visual context correlate to an improved response from viewers. Different types of context that can be presented – from logo variations and environmental examples to videos and animation – have varied effects.

When releasing a new logo, companies and organizations may receive a better response from viewers if they provide more visual context. Animations may also provide an improved response.

This study takes a novel approach to exploring viewer responses to logos by combining content analysis with voting data. While most studies use fictitious or abstract logo designs, this study uses actual logos and context to better understand viewer responses.

This study aims to critically review the emerging technological developments and digitalization efforts in the hospitality and tourism (HT) industry and discuss the implications of digitalization on various stakeholders (e.g. consumers, employees, companies and operators) with reference to value creation.

This paper is a conceptual, critical reflection paper. Thus, the study reflects the authors’ assessment and reflection of the current digitalization efforts in the HT industry with a particular interest in value creation.

The study suggests that digitalization is still in its infancy state in terms of adoption and value creation in the HT industry. Yet, there are various opportunities for all stakeholders to benefit from existing and emerging digitalization applications.

This study can be used by industry professionals and scholarly researchers as a reflection of past and current digitalization efforts in the HT industry. Moreover, the study offers directions regarding the future digitalization movement in the HT industry and how such a movement might create important value propositions for various stakeholders.

The study is uniquely positioned as a critical reflection paper on the digitalization effort of the HT industry and offers new practical insights regarding how digitalization could create value for industry stakeholders as it finds more application areas. In this regard, it differs from prior review studies that focused solely on the use of new and emerging technologies in HT operations.