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Credibilistic programming : an introduction to models and applications
It provides fuzzy programming approach to solve real-life decision problems in fuzzy environment. Within the framework of credibility theory, it provides a self-contained, comprehensive and up-to-date presentation of fuzzy programming models, algorithms and applications in portfolio analysis.
BOOK
Green information quality and green brand evaluation: the moderating effects of eco-label credibility and consumer knowledge
Purpose
This study aims to examine the effects of three green information quality dimensions – persuasiveness, completeness and credibility – on green brand evaluation and whether this is mediated by green brand credibility. It also examines the moderating effects of eco-label credibility and consumer knowledge on green information quality dimensions and green brand credibility relationships.
Design/methodology/approach
Using a structured questionnaire on environmentally-friendly electrical goods/electronics, cosmetic and apparel product advertisements, involving an elaboration task, this study collected usable data from 1,282 Indian consumers across 50 cities. It also undertook an assessment for three different product groups using structural equation modelling to examine proposed hypotheses and assessed moderated mediation using the Hays process model.
Findings
The study indicates that: green brand credibility mediates the effects of green information quality dimensions on green brand evaluation; consumer knowledge moderates the effects of persuasiveness and completeness on green brand credibility and eco-label credibility moderates the effects of persuasiveness and credibility on green brand credibility.
Research limitations/implications
In green information processing, this study supports the relevance of the elaboration likelihood model and the mediation effect of green brand credibility. It also presents evidence that credible eco-labels enhance green information processing. While the results are broadly consistent across the three product categories, the results may only generalizable to the environmentally-aware urban populations.
Practical implications
Help brand managers to design advertisements that add brand credibility in environmentally-aware urban markets.
Originality/value
It helps to define green information quality and the interacting effects of eco-label credibility and consumer knowledge in green information processing.
Journal Article
Analysis of Factors Influencing E-WOM Credibility
As the use of Internet is getting more widespread and people are putting more trust on the Internet-based information, a new form of word of mouth termed as electronic word of mouth (E-WOM) has been developed. People receive E-WOM messages from social media, consumer review sites, discussion forums etc. Researches say that people tend to rely on E-WOM messages as much as they do on personal word of mouth. But what variables influence E-WOM credibility? After conducting an intensive background research on this topic this study has been able to identify certain variables such as E-WOMs quantity, polarity, logic and articulation, source and users prior knowledge/expertise that affect E-WOM credibility. Based on the identified variables a survey was conducted on the students of 10 private and public universities of Bangladesh with a view to measure the effect of those variables on the E-WOM credibility. The regression analysis result indicates the quantity of E-WOM and the source of E-WOM has significant impact on E-WOM credibility. While, the designed model overall with all the included variables came strongly significant in explaining E-WOM credibility. In addition, to measure the internal consistency and correlation of the variables Cronbachs Alpha technique and correlation analysis are also conducted which have brought satisfactory outcome. From a strategic point of view, this study is useful for the modern marketers who want to use E-WOM to promote their products or services. By focusing on the predictor variables which have impact on E-WOM credibility, they can be able to enhance the effectiveness of their marketing strategy with a very cost efficient and a time savvy manner.
Journal Article
Tweet Credibility Ranker: A Credibility Features’ Fusion Model
Misinformation on social media has emerged as a modern weapon of warfare, disrupting societal peace, trust, justice, and democracy. It is quite challenging to address the issue of information credibility for microblogs. It becomes more challenging when the authenticity of the poster is hidden. The concept of information credibility has multi-perspectives. There are many necessary aspects of information credibility which must be considered for effective credibility assessment. It is observed that some important aspects of credibility are not considered in existing studies. The complete credibility assessment solution needs a comprehensive and diverse set of features for such complex identification. Therefore, these features are identified and proposed by exploring the related research studies consisting of the necessary credibility aspects. These features consist of diverse levels provided by microblogs. These levels include the post, poster, poster’s social network, and actual information propagation network. An exploratory study is also conducted to propose the best credibility features that are used in the proposed solution. The attempt is made for a hybrid features fusion model which combines feature-based or machine learning and graph-based approaches. It is a lightweight, high-performing, non-latent features model to avoid their drawbacks. It assesses the levels of credibility of the concerned post. It is designed for high-impact applications to combat low-credibility content during elections, crises, and other critical scenarios. The model is executed over a publicly available dataset extended for credibility assessment. The model provides good results with 95.6% accuracy by XGBoost using platinum features. The performance of the proposed model is compared with state-of-the-art that produced much-appreciating results.
Journal Article
Examining the effects of advertising credibility on brand credibility, corporate credibility and corporate image: a qualitative approach
Purpose
This paper aims to use signalling theory to examine the concept of advertising credibility and its effects on brand credibility, brand image, corporate credibility and corporate image.
Design/methodology/approach
A qualitative approach was used. Ten interviews and four focus groups were conducted among participants drawn from the London area. The data was analysed using thematic analysis.
Findings
The findings suggest that advertising credibility is defined using terms like accurate, caring, competent, complete, convincing, ethical, honest, impressive, promising, reliable and warranted. The findings also suggest that advertising credibility has a positive effect on brand credibility, brand image, corporate credibility and corporate image. However, these effects are lower when the brand and corporation have different names than when they have similar names. The dissimilarity of names can also provide some benefit, especially when brands or firms are faced with a crisis. The findings also illustrate that the theoretical model used in this study is valid, and suggest that advertising credibility has positive effects on other constructs.
Originality/value
Advertising credibility has received little attention in the literature. There is also little attention on its effects on other credibility constructs. This study minimises these gaps by conducting qualitative research to explore the effects of advertising credibility on brand credibility, corporate credibility and corporate image.
Journal Article
Impact of information credibility on social media information adoption behavior: a systematic literature review
PurposeThe purpose of this systematic literature review was to collect and review the studies published worldwide in English language presenting the persuasive role of information/content credibility (IC) on the information adoption behavior (IAB) of social media users.Design/methodology/approachThe relevant literature was searched by the reviewers from two specialized databases, i.e. Library, Information Science and Technological Abstract (LISTA) and Library and Information Science Abstracts (LISA), whereas five general databases, i.e. Emerald, Springer Link, Taylor and Francis Online, ProQuest Dissertations and Theses Global and Google Scholar, using the Internet (portal) services available at the two Pakistani universities, i.e. University of Sargodha and the University of the Punjab. The search was updated in February 2022.FindingsThe results of this study revealed that there was a significant impact of IC over the IAB of social media users.Originality/valueThis study is the first of its nature that aims to collect and present a systematic review of the literature based on empirical evidence of the influential role of IC on the IAB of social media users.
Journal Article
Transparency and replicability in qualitative research
Research Summary We used interviews with elite informants as a case study to illustrate the need to expand the discussion of transparency and replicability to qualitative methodology. An analysis of 52 articles published in Strategic Management Journal revealed that none of them were sufficiently transparent to allow for exact replication, empirical replication, or conceptual replication. We offer 12 transparency criteria, and behaviorally‐anchored ratings scales to measure them, that can be used by authors as they plan and conduct qualitative research as well as by journal reviewers and editors when they evaluate the transparency of submitted manuscripts. We hope our article will serve as a catalyst for improving the degree of transparency and replicability of future qualitative research. Managerial Summary If organizations implement practices based on published research, will they produce results consistent with those reported in the articles? To answer this question, it is critical that published articles be transparent in terms of what has been done, why, and how. We investigated 52 articles published in Strategic Management Journal that reported interviewing elite informants (e.g., members of the top management team) and found that none of the articles were sufficiently transparent. These results lead to thorny questions about the trustworthiness of published research, but also important opportunities for future improvements about research transparency and replicability. We offer recommendations on 12 transparency criteria, and how to measure them, that can be used to evaluate past as well as future research using qualitative methods.
Journal Article
AI credibility and consumer-AI experiences: a conceptual framework
PurposeThis study aims to conceptualize the relationship of perceived artificial intelligence (AI) credibility with consumer-AI experiences. With the widespread deployment of AI in marketing and services, consumer-AI experiences are common and an emerging research area in marketing. Various factors affecting consumer-AI experiences have been studied, but one crucial factor – perceived AI credibility is relatively underexplored which the authors aim to envision and conceptualize.Design/methodology/approachThis study employs a conceptual development approach to propose relationships among constructs, supported by 34 semi-structured consumer interviews.FindingsThis study defines AI credibility using source credibility theory (SCT). The conceptual framework of this study shows how perceived AI credibility positively affects four consumer-AI experiences: (1) data capture, (2) classification, (3) delegation, and (4) social interaction. Perceived justice is proposed to mediate this effect. Improved consumer-AI experiences can elicit favorable consumer outcomes toward AI-enabled offerings, such as the intention to share data, follow recommendations, delegate tasks, and interact more. Individual and contextual moderators limit the positive effect of perceived AI credibility on consumer-AI experiences.Research limitations/implicationsThis study contributes to the emerging research on AI credibility and consumer-AI experiences that may improve consumer-AI experiences. This study offers a comprehensive model with consequences, mechanism, and moderators to guide future research.Practical implicationsThe authors guide marketers with ways to improve the four consumer-AI experiences by enhancing consumers' perceived AI credibility.Originality/valueThis study uses SCT to define AI credibility and takes a justice theory perspective to develop the conceptual framework.
Journal Article
Why do people donate online? A perspective from dual credibility transfer
Previous research related to online donations has not addressed the importance of the credibility of the three main components of online donation: campaigns, websites, and donation organizations through a credibility transfer mechanism. This model can later determine the factors that influence a person's desire to donate online based on the credibility of campaigns, websites, and organizations. Each of these factors is then attached to the Elaboration Likelihood Model (ELM) theory, which explains the process of someone elaborating a message through a central route or a peripheral route. Respondents who can fill out this questionnaire are the general public who have read at least one description of the donation campaign on the Kitabisa website. The questionnaire results were processed using PLS-SEM statistical analysis with SmartPLS software version 3.2.6 based on questionnaire data from 503 respondents. PLS-SEM is generally used to develop theory in exploratory research by explaining the variance of the dependent variables when evaluating the model. The analysis results found that online donation intention was directly influenced by campaign credibility. In addition, there are two credibility transfer processes found in this study, namely, between website credibility and campaign credibility and between organizational credibility and website credibility.
Journal Article
Is This Review Believable? A Study of Factors Affecting the Credibility of Online Consumer Reviews from an ELM Perspective
With the ever-increasing popularity of online consumer reviews, understanding what makes an online review believable has attracted increased attention from both academics and practitioners. Drawing on the elaboration likelihood model (ELM), this study examines four information cues used to evaluate the credibility of online reviews: Argument quality, source credibility, review consistency, and review sidedness, under different levels of involvement and expertise. We conducted an online survey that involved users of Epinions.com, a popular online consumer review website, to test the research model empirically. Consistent with previous research, the results reveal that argument quality, a central cue, was the primary factor affecting review credibility. Participants also relied on peripheral cues such as source credibility, review consistency, and review sidedness when evaluating online consumer reviews. Review sidedness had a stronger impact on review credibility when the recipient had a low involvement level and a high expertise level. However, the other interaction effects were not significant. We discuss the theoretical and practical implications of these results. [PUBLICATION ABSTRACT]
Journal Article