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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.

Of the 3010 databases publicly available in 1985, 1,926 are classed as word‐oriented. The majority of these databases are available online either in the United States or elsewhere. Many are small and many are little used. Among online databases some 383 were active (used) in the information center/library market in the United States between 1982 and 1985. This market includes sixteen online search services (vendors). Databases accessed through those vendors have been continuously surveyed on a quarterly basis through the Information Market Indicators (IMI) survey since 1982. The vendors included in the survey are the major vendors of word‐oriented databases whose services are purchased by organizations in the United States. They are: BRS, Dialog, Dow Jones, Inform (VuText), ISI (Institute for Scientific Information, no longer active as a vendor), Legi‐Slate, MDC (Mead Data Central), NLM (National Library of Medicine), NYT (New York Times, no longer active as a vendor), Pergamon InfoLine, Questel, STN International, SDC (System Development Corp.), Source, Wilson‐line, and Westlaw. Data in this paper are based on the IMI survey.

This study investigates augmented reality (AR) retailing and attempts to develop a profound understanding of consumer decision-making processes in AR-enabled e-retailing.

The study is grounded in rich informational cues and information processing mechanisms by incorporating the elaboration likelihood model (ELM) and trust transfer theory. This study employs a mixed analytic method that incorporates structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to provide a complete picture of individual information process mechanisms in AR retailing under the tenet of ELM.

The SEM analysis results confirm the relationships between the central and peripheral route factors, information processing outcomes and eventual behavioral intentions. Moreover, all configurations revealed by the fsQCA include both central and peripheral factors. Hence, the dual routes proposed in the ELM are verified by using two distinct analytical approaches.

This study is pioneering in validating and contextualizing ELM theory in AR retailing. In addition, this study offers a methodological paradigm by demonstrating the application of multi-analysis in exploring consumers’ information process mechanisms in AR retailing, which offers a holistic and comprehensive view to understand consumers’ decision-making mechanisms.

This paper aims to present recently published resources on information literacy and library instruction providing an introductory overview and a selected annotated bibliography of publications covering all library types.

This paper introduces and annotates English-language periodical articles, monographs, dissertations and other materials on library instruction and information literacy published in 2016.

The paper provides information about each source, describes the characteristics of current scholarship and highlights sources that contain unique or significant scholarly contributions.

The information may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.

The star rating summarises the review content and conveys the message faster than other review components. Star ratings influence helpfulness of the reviews, and extreme reviews are considered as less helpful in the decision process. However, literature has rarely addressed variations in star ratings across product categories and variations between two online retailers. In this paper, the authors have compared the distribution of star ratings across 11 products and among the retailers.

Online reviews for 11 product categories have collected, and the authors compared the distribution of star ratings across 11 products and retailers. Correspondence analysis has been applied to show the association between star ratings and product categories for the e-retail firms.

The Amazon site contains proportionately more number of 1-star rated reviews than Flipkart. In Amazon reviews, few product categories are closely associated with 1-star and 2-star reviews, whereas no product categories are closely associated with 1-star and 2-star reviews in Flipkart reviews. The results indicate two distinct communication strategies followed by the firms in managing online consumer reviews.

The authors did not analyse data across demographic details because of access restriction policies of the websites.

Understanding the distribution of review characteristics will improve the consumer’s decision-making ability and using online review content judiciously.

This study’s results show significant insights on online retailing by providing cues in using shopping sites and online review characteristics of two prominent retailers.

This paper has brought out a distinct distribution pattern of online review between Amazon and Flipkart. Amazon allows a higher degree of negative contents, whereas Flipkart allows more number of positive reviews.

This study aims to elicit the preferences of potential travelers for different property listings' attributes (online review number, positive valence rate of reviews and discount strategy) when selecting hotels and peer-to-peer (P2P) accommodation sharing on online booking platforms.

A discrete choice experiment (DCE) was conducted with 291 respondents with accommodation needs. They were asked to choose between pairs of listings.

The authors found that when booking accommodation online, complex discount strategies were not determinant both in selecting hotels and P2P accommodations. Positive valence rate of reviews has a higher impact on the selection of traditional hotels than P2P accommodations, while the number of online reviews has a higher impact on the selection of P2P accommodations than traditional hotels. The authors further discuss the effect of each attribute on online accommodation selection in terms of price ranges of the property listings.

The findings provide suggestions for platform operators and product/service providers to improve their marketing strategies and optimize their management efforts.

To the best of the authors’ knowledge, this is one of the first studies that investigate the role of property listings' attributes on the selections between hotels and P2P accommodations. The findings from this research study could be generalized to other online platforms and electronic commerce-related transactions.

The purpose of this study is to explore the antecedents of consumers’ online review intention in e-commerce platforms from a unique perspective of consumer commitment and platform design. Meanwhile, for the dual-platform strategy, i.e. providing both the web and mobile platforms simultaneously, which is widely adopted in the industry but lacks theoretical concerns, this study aims to examine the differences that platform design influences consumer commitment, consequently contributing to online review intention, between the web and mobile contexts.

A cross-sectional online survey is employed, and a structural equation model-based approach is utilized to analyze the data collected from both the website-preferred consumers (N = 167) and the mobile app-preferred consumers (N = 247).

The results indicate that instrumental support design factors and socio-emotional support factors positively influence consumer commitment, which further affect online review intention positively. Furthermore, design factors in different use contexts generate different impacts, and consumer commitment generates a greater effect on online review intention in the mobile than in the web context. Empathy is found to be an important motivator of consumer commitment in both contexts.

To the best of the authors’ knowledge, as one of the first attempts to capture the differences in the relationship between platform design on consumer commitment and online review intention in different use contexts within the dual-platform e-commerce, this study provides insights for e-commerce platform managers and designers to promote consumer commitment and online review engagement by prioritizing the platform design.

This study aims to explore the quality of user-generated content regarding readability, polarity, word length and diversity, as well as its implications for guest satisfaction in Las Vegas luxury gaming resorts.

This study examined 12,940 textual customer reviews from six luxury hotels in luxury gaming destination resorts via Google Travel gathered from SCTM 3 (Smart Crawling and Text Mining). Moreover, the regression analysis identified the relationship between the variables in the textual customer reviews and the customer’s overall satisfaction.

A key finding of this study revealed that word length moderates the relationship between readability and overall customer satisfaction negatively, whereas it positively moderates the path from sentiment polarity and diversity to overall customer satisfaction.

This study contributes to the relationship between technical aspects of online reviews. The adopted methodology allows us to precisely identify the essential attributes that influence customer satisfaction through textual reviews. Further, the study explores the quality of user-generated content, addressing aspects such as readability, polarity, diversity and word length, providing a unique perspective on how these specific elements directly impact customer satisfaction in this context of hotels in luxury in Las Vegas.

本研究探讨了用户生成内容的可读性、情感倾向、词长和多样性等方面的质量, 以及这些因素对拉斯维加斯豪华博彩度假村顾客满意度的影响。

本研究通过 SCTM 3（智能爬虫与文本挖掘）收集了谷歌旅行上的六家豪华酒店的12,940 条客户评论文本。此外, 回归分析确定了文本客户评论中的变量与客户整体满意度之间的关系。

本研究的一个关键发现是, 词长在可读性与整体顾客满意度之间的关系中起到负面调节作用, 而在情感倾向和多样性与整体顾客满意度之间的路径中起到正面调节作用。

本研究对在线评论的技术方面之间的关系作出了贡献。采用的方法使我们能够精确识别通过文本评论影响顾客满意度的关键属性。此外, 本研究探讨了用户生成内容的质量, 涉及可读性、情感倾向、多样性和词长等方面, 提供了独特视角, 揭示了这些具体元素如何直接影响拉斯维加斯豪华酒店顾客满意度。

Cross-cultural research constitutes a pivotal topic for marketing; however, the literature indicates that there are a few studies analyzing social media reviews from a cross-cultural perspective using cultural proximity (supra-national level) as a proxy of culture. Therefore, the purpose of this study is to identify cross-cultural differences in service evaluations and specifically, in hotel appraisals among tourists from Central, Eastern (including Post-Soviet States), Northern and Southern Europe.

A quantitative approach has been taken by studying online user-generated ratings of hotels on Trip Advisor. In total, 1,055 reviews of five hotels in Greece were used for the study.

Multivariate analysis of variance and analysis of variances results confirm cultural differences in overall service evaluations and attributes (value, location, sleeping quality, rooms, cleanliness and service) of tourists from various European regions. Specifically, Eastern Europeans uploaded more reviews than any other European group, whereas Northern Europeans were more generous in their appraisals than Eastern, Southern and Central Europeans.

The results of the study could be used for segmentation purposes of the European tourism market and for recognizing, which aspects of their services need to be improved based on the segments they serve. Moreover, managers should encourage Northern and Eastern Europeans to upload their reviews as both groups are more generous in their evaluations. Moreover, the findings are useful to marketers of other services.

To the author’s knowledge, this is the first study that examines cross-cultural differences in hotel appraisals from a supra-national perspective including developed (Northern and Western Europe), developing (Southern Europe) and emerging tourism markets (Eastern Europe).