Factors correlated with the perceived usefulness of online reviews for consumers: a meta-analysis of the moderating effects of product type

PurposeThe conclusions of studies on the factors correlated with the perceived usefulness of online reviews are inconsistent due to differences in research perspectives, research objects, research methods and data types. This study conducted a meta-analysis to verify a proposed model of perceived usefulness to obtain general conclusions.Design/methodology/approachA meta-analysis was conducted to study the factors correlated with the perceived usefulness of online reviews based on 51 studies.FindingsThe results indicate that, with the exception of negative reviews, the order of relevance for the perceived usefulness of online reviews is as follows: the trust tendency of review readers, review replies, review depth, review pictures, reviewer trustworthiness, positive reviews, reviewer expertise, review time and reviewer information disclosure. Perceived usefulness was significantly positively correlated with purchase intention. Review time, positive reviews and negative reviews were also more significantly correlated with perceived usefulness for search products than for experiential products. Review depth, reviewer trustworthiness, reviewer expertise and purchase intention had greater positive correlations with perceived usefulness for experiential products than for search products.Originality/valueThis study proposes an extended information adoption model based on argument quality and source credibility. The model includes personal factors such as the trust tendency of review readers, constructs a theoretical model of the factors correlated with the perceived usefulness of online reviews and considers the moderating effects of product type.

Exploring the distribution regularities of user attention and sentiment toward product aspects in online reviews

Purpose To better understand the online reviews and help potential consumers, businessmen and product manufacturers effectively obtain users’ evaluation on product aspects, this paper aims to explore the distribution regularities of users’ attention and sentiment on product aspects from the temporal perspective of online reviews. Design/methodology/approach Temporal characteristics of online reviews (purchase time, review time and time intervals between purchase time and review time), similar attributes clustering and attribute-level sentiment computing technologies are used based on more than 340k smartphone reviews of three products from JD.COM (a famous online shopping platform in China) to explore the distribution regularities of users’ attention and sentiment on product aspects in this paper. Findings The empirical results show that a power-law distribution can fit users’ attention on product aspects, and the reviews posted in short time intervals contain more product aspects. Besides, the results show that the values of users’ sentiment on product aspects are significantly higher/lower in short time intervals which contribute to judging the advantages and weaknesses of a product. Research limitations/implications This paper cannot acquire online reviews for more products with temporal characteristics to verify the findings because of the restriction on reviews crawling by the shopping platforms. Originality/value This work reveals the distribution regularities of users’ attention and sentiment on product aspects, which is of great significance in assisting decision-making, optimizing review presentation and improving the shopping experience.

Understanding shared links and their intentions to meet information needs in modern code review:

Code reviews serve as a quality assurance activity for software teams. Especially for Modern Code Review, sharing a link during a review discussion serves as an effective awareness mechanism where “Code reviews are good FYIs [for your information].”. Although prior work has explored link sharing and the information needs of a code review, the extent to which links are used to properly conduct a review is unknown. In this study, we performed a mixed-method approach to investigate the practice of link sharing and their intentions. First, through a quantitative study of the OpenStack and Qt projects, we identify 19,268 reviews that have 39,686 links to explore the extent to which the links are shared, and analyze a correlation between link sharing and review time. Then in a qualitative study, we manually analyze 1,378 links to understand the role and usefulness of link sharing. Results indicate that internal links are more widely referred to (93% and 80% for the two projects). Importantly, although the majority of the internal links are referencing to reviews, bug reports and source code are also shared in review discussions. The statistical models show that the number of internal links as an explanatory factor does have an increasing relationship with the review time. Finally, we present seven intentions of link sharing, with providing context being the most common intention for sharing links. Based on the findings and a developer survey, we encourage the patch author to provide clear context and explore both internal and external resources, while the review team should continue link sharing activities. Future research directions include the investigation of causality between sharing links and the review process, as well as the potential for tool support.

Time to market for drugs approved in Canada between 2014 and 2018: an observational study

ObjectivesThis study examines the length of time between when a patent application is filed in Canada for a new drug and when it is available for patients (time to market) and various components of that time. It also looks at whether various factors explain the time between patent application to New Drug Submission (NDS) and compares Canadian and American times. Drugs approved between 1 January 2014 and 31 December 2018 are examined.DesignDescriptive study.Data sourcesWebsites from Health Canada, Food and Drug Administration, Merck Index, United States Patent and Trademark Office, WHO and previously published articles.InterventionsNone.Primary and secondary outcomesThe primary outcomes are time to market, time from patent application to NDS (pre-NDS time), review time, time from approval to availability (postapproval time) and factors that may influence the pre-NDS time. The secondary outcome is a comparison of Canadian and American review times and times between patent application and approval.ResultsThere were 113 drugs available for analysis. The median time to market was 11.80 years (IQR 9.40–14.05). The component median times were pre-NDS 10 years (IQR 8.05–12.80), review time 0.96 years (IQR 0.75–1.15) and postapproval time 0.15 years (IQR 0.08–0.28). Less than 8% of the pre-NDS time was explained by the factors that were analysed in a multiple linear regression equation. There was no statistically significant difference between Canadian and American pre-NDS times.ConclusionOnce a drug reaches the market, companies have a median of 8.2 years before the patent expires and generics can reach the market. Most of the time between the filing of a patent application and when a drug is marketed is determined by decisions that are largely under the control of the company.

Evaluating Improvement in Acute Stroke Management following Pre-hospital Initiation of Acute Stroke Service

Prehospital notification of the stroke team in alerting incoming acute stroke patient has been practiced in several countries worldwide. Currently this is not practiced in Malaysia. This study evaluates feasibility and impact to stroke team door to review time when prehospital notification is employed. Duration of case control study was between June 2018 to January 2019. Control phase consists of conventionally activating stroke team after in-hospital assessment by emergency medical officer. This was then followed by an intervention phase where on scene activation of stroke team was done by the Prehospital Emergency Care (PHC) staff. Training of PHC staff in recognising an acute stroke was based on identification of BE-FAST (Balance, Eyes, Face, Arm and Speech Test) abnormalities. The objectives were to compare the mean between two groups for acute stroke team review time, door to computerised tomography (CT) scan and door to thrombolysis time. Thirty-nine patients were analysed (control n=29, intervention n=10). Results were insignificant (p>0.05). Mean time in minutes for control phase vs. intervention phase was as follows: Door to stroke team review time, 25.96 + 39.16 vs. 15.9 + 13.14, door to CT scan was 43.04 + 40.00 vs. 25.8 + 11.35. Only 3 patients underwent thrombolytic therapy during study period. Limitation was non-parametric data with lack of number of acute stroke cases responded during the intervention period. With continual training of pre-hospital staff in detecting acute stroke, feasibility can be improved.

Spammer group detection and diversification of customers’ reviews

Online reviews regarding different products or services have become the main source to determine public opinions. Consequently, manufacturers and sellers are extremely concerned with customer reviews as these have a direct impact on their businesses. Unfortunately, to gain profit or fame, spam reviews are written to promote or demote targeted products or services. This practice is known as review spamming. In recent years, Spam Review Detection problem (SRD) has gained much attention from researchers, but still there is a need to identify review spammers who often work collaboratively to promote or demote targeted products. It can severely harm the review system. This work presents the Spammer Group Detection (SGD) method which identifies suspicious spammer groups based on the similarity of all reviewer’s activities considering their review time and review ratings. After removing these identified spammer groups and spam reviews, the resulting non-spam reviews are displayed using diversification technique. For the diversification, this study proposed Diversified Set of Reviews (DSR) method which selects diversified set of top-k reviews having positive, negative, and neutral reviews/feedback covering all possible product features. Experimental evaluations are conducted on Roman Urdu and English real-world review datasets. The results show that the proposed methods outperformed the existing approaches when compared in terms of accuracy.