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The purpose of this paper is to explore different types of source expertise and how they influence perceived message quality. Consumers face the challenge to identify valuable online reviews. Source expertise as a signal of message quality can be displayed differently, depending on website layout, operator and review author.

Two scenario-based experiments were conducted questioning 135 and 275 participants. They investigate the effect of different types of expert reviewers on perceived message quality and also examine the interplay of source expertise and source trustworthiness.

The findings reveal that the different types of expert reviewers differ in perceived expertise and their impact on perceived message quality. Claims of expertise induce the highest perceived expertise compared to the other expert types and non-experts, but are perceived as less trustworthy.

Future research should examine the influence of the expert types across different product and service categories and could also include moderating influences that reflect how consumers process expert cues differently.

Cues that signal high expertise and high trustworthiness are likely to deliver the most valuable online reviews. This should be incorporated in the website's layout to help consumers find valuable information.

The approach of this research is novel in that it undertakes comparisons between three types of expert cues and non-experts. It also addresses the interplay of source expertise and trustworthiness and examines the effect on message quality.

To explain and empirically test how different marketing communication channels interact with each other and contribute to brands’ diverging marketplace performance.

With a unique data set combining key variables of major passenger car brands, the paper takes a source-based perspective to investigate how firm-based communications, expert opinions and online consumer reviews interact and affect brands’ marketplace performance. Then the paper studies the three special boundary conditions under which online consumer reviews’ influence varies in competition with the other two established information sources. Lastly, a study was done to demonstrate the financial significance of investing in different information sources.

The results show that online consumer reviews mitigate the effectiveness of the other two information sources in driving brand sales. This mitigation effect is also magnified when the brand is weak, firm-based communications are modest and expert opinions are less favorable. The findings further suggest that in the emerging communication enterprise, firm-based and expert-based communications remain the core while user-based communication plays an indispensable competing and complementary role.

In the new digital era, firms are facing the daunting task of understanding and integrating multiple communication channels. The study provides important implications for both researchers and practitioners with respect to brand management and integrated communications.

Existing studies have demonstrated that each of the three communication efforts (by firms, experts and consumers) exerts a significant influence on product sales, but few studies have been conducted in settings marked by the coexistence of these efforts. In addition, the three communication efforts are likely to have different effects on brands with different market positions. The current study is contributing to the literature by filling the above gaps.

The study aims to examine the effects of ulterior motives in peer and expert supplementary online hotel reviews on consumers' perceived deception, dissatisfaction, and its downstream effects on altruistic response and repurchase intentions. The research also examines the moderating role of hotel attribute performance on perceived deception and its consequents.

This study used convenient non-probability sampling and collected data from 448 inbound tourists in China. It used partial least square structural equation modeling technique and SmartPLS 3.0 for analyzing the main and moderating effects of the variables.

The ulterior motives in peer and expert supplementary reviews significantly affect perceived deception, further leading to consumers' dissatisfaction and engagement in altruistic response. Noticeably, consumers' dissatisfaction is positively associated with repeat purchase intentions. Hotel attribute performance significantly moderates the relationship between the ulterior motives in supplementary reviews and consumers' perceived deception.

The study examines the key issue in online hotel reviews using the expectancy disconfirmation theory and identifies consumers' altruistic behavior because of their dissatisfaction, contributing to ethics and consumer behavior literature. Moreover, the research offers prolific implications for hotel and travel websites and hoteliers in the study context.

Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.

The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.

The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.

Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.

This study constructs a three-stage evaluation model for interdisciplinary organizations to solve their ranking problems effectively.

A three-stage interdisciplinary organization evaluation model abounds the key problems of “who will evaluate the projects?” and “how to evaluate the projects?”. In the first stage, the authors build a consensus maximization model to identify the selected experts based on the interval grey number because of the uncertainty in assessment. In the second stage, considering the reliability of the experts, the authors calculate the reliability of the experts based on historical data. Meanwhile, considering the gradual changes of the experts, the dynamic weighting method is obtained based on the clustering method. In the third stage, considering decision-makers regret psychological behavior, the authors construct a cross-organizational performance evaluation model based on consensus expectations.

First, for selecting the experts responsible for assessing interdisciplinary organizations, the consensus-reaching method can effectively avoid cognitive bias. Second, during the assessment, the authors obtained more reasonable results by considering the psychological changes of experts based on regret theory. Third, based on the results, the cross-organization of colleges focused on the achievements of talent training, cross effects, and system construction.

Our study could help organizations establish a suitable assessment mechanism and promote interdisciplinary development.

First, considering the importance of selecting the experts, the authors use the consensus-reaching process for expert selection. This method could guarantee most experts' preferences. Then, the authors propose a two-stage dynamic weighting method, including a pre-determined and adjusted process. The dynamic method can better perform the preferences of experts. Third, the authors studied the assessment in interdiscipline. In addition, based on the framework and considering the features of the interdiscipline, the authors use the grey number to perform the uncertain preferences of the experts using regret theory.

Online reviews are increasingly available for a wide range of products and services. Several studies have demonstrated the benefits of the presence of customer reviews to an online retailer, but the issue of what makes online reviews helpful to a consumer in the process of making a purchase decision remains uninvestigated. The paper aims to discuss this issue.

Given the strategic potential of online reviews, this study drew on past research to develop a conceptual understanding of the components of helpfulness and to further empirically test the model using actual online review data from iPeen.com in Taiwan. A content analysis of 989 reviews across four products identified the interplay effects of review sidedness, reviewer’s expertise, and product type on the helpfulness of an online review.

For search goods, consumers consider two-sided reviews to be more helpful than one-sided reviews when the reviewers are experts in writing such articles, whereas they consider two-sided reviews to be equally helpful as one-sided reviews when the reviewers are novices. Conversely, for experience goods, consumers consider one-sided reviews to be more helpful than two-sided reviews when the reviewers are experts in writing review articles, but they consider one-sided reviews to be equally helpful as two-sided reviews when the reviewers are novices.

With an understanding of how review sidedness affects online review helpfulness, online retailers could establish the policy for promoting the helpfulness of reviews more effectively.

This research yields at least three important contributions: first, it contributes to the message sidedness literature by showing which arguments (one- or two-sided) are deemed to be helpful; second, it contributes to the online peer review literature by demonstrating the importance of considering product type and heuristic cues (i.e. the reviewer’s expertise) when explaining helpfulness; and third, the results in this research demonstrate that people are drawn to dual-processing; that is, the judgment of online review helpfulness is determined by heuristic cues (e.g. the status of the reviewer) and systematic processing (e.g. review content).

This study aims to adopt a cognitive heuristic approach to investigate the interaction effect of a message source characteristic (reviewer expertise [RE]) and two message structure characteristics (review rating consistency [RC] and review valence [RV]) on the perceived credibility of hotel online reviews.

Data were collected from 242 university students and were analyzed by three-way analysis of variance through a 2 × 2 factorial experiments using a simulated hotel review page on TripAdvisor.

Results show a three-way interaction effect of RE, RC and RV on the perceived credibility of hotel online reviews. The main effects of the three factors are also determined. Higher perceived credibility scores are found for negative reviews, reviews written by experts and reviews with a consistent rating.

This study adopts an experimental approach and is the first to investigate the three-way interactions of message source and message structure characteristics of online hotel reviews. Data were collected from students in a university in Hong Kong. Results may not be generalizable to other markets.

Results suggest that reviews written by experts have higher perceived credibility. Hotels should pay attention to the content of online reviews and the expertise level of reviewers. Efforts should be exerted to create positive experiences for hotel guests that motivate expert reviewers to write positive reviews. Note that negative reviews have higher perceived credibility than positive ones. Hotels should promptly address negative reviews and provide professional responses to reviewers. Platform operators of user-generated content (UGC) should create well-defined reviewer profiles that can serve as cues that communicate the different expertise of reviewers.

This study is the first to test the three-way interaction effect of RE, RC and RV on the perceived credibility of hotel online reviews. Results provide recommendations to hotels and UGC operators and enable them to benefit from emerging UGC usage.

As a result of the significant influence of actuaries on policy liabilities and the related earnings in the financial statements of a listed South African long‐term insurer, auditors encounter a number of key issues and considerations relating to the incorporation of actuarial expertise in the audit process. Guidance for auditors to address these issues and considerations is discussed in this study. The guidance was developed as a significant element of a wider research project, the objective of which was the development of a best practice framework for the formulation of overall audit strategies for insurance contracts and the related earnings of listed South African long‐term insurers.

Bayesian approaches have been widely applied in construction management (CM) research due to their capacity to deal with uncertain and complicated problems. However, to date, there has been no systematic review of applications of Bayesian approaches in existing CM studies. This paper systematically reviews applications of Bayesian approaches in CM research and provides insights into potential benefits of this technique for driving innovation and productivity in the construction industry.

A total of 148 articles were retrieved for systematic review through two literature selection rounds.

Bayesian approaches have been widely applied to safety management and risk management. The Bayesian network (BN) was the most frequently employed Bayesian method. Elicitation from expert knowledge and case studies were the primary methods for BN development and validation, respectively. Prediction was the most popular type of reasoning with BNs. Research limitations in existing studies mainly related to not fully realizing the potential of Bayesian approaches in CM functional areas, over-reliance on expert knowledge for BN model development and lacking guides on BN model validation, together with pertinent recommendations for future research.

This systematic review contributes to providing a comprehensive understanding of the application of Bayesian approaches in CM research and highlights implications for future research and practice.

This study evaluates the factors related to the creation of a human brand in the brand inception stage.

Employing content analysis of expert reviews, we establish the role played by valence (positiveness), depth (number of statements) and timing of subjective and objective critical reviews for human brands. To address these issues, we employ generalized estimating equations to model numerical ratings of celebrity reviews evaluating a nascent human brand.

The findings show that subjective reviews have the potential to influence the probability of survival of a human brand in the brand inception period, are increasingly consequential during the inception period stages and are more influential than objective reviews. We also found that the valence of objective reviews can negatively and significantly relate to human brands in their late inception stage.

This is the first research to demonstrate the importance of critical reviews in building human brands, with a focus on the first moment of a brand's inception. More importantly, this research enriches our understanding of the larger process of personal brand building as it may emerge over time.