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The purpose of this paper is to show how different combinations of the subdimensions of electronic word-of-mouth (eWOM) information quality (consisting of its accuracy, completeness, relevance, timeliness, and sidedness) may affect consumers' eWOM use behavior from a configurational approach.

Based on a synthesis of past literature, five precursors of eWOM use were considered. A fuzzy-set qualitative comparative analysis (fsQCA) was employed to understand the configurations that lead to travel-related eWOM use. The study was conducted with 311 consumers from an online travel service company.

Findings identified six solutions that explain eWOM use. EWOM accuracy, completeness, and sidedness are found to be core conditions reinforcing consumers' use of eWOM in combination with different peripheral conditions, including the subdimensions of eWOM information quality and the traits of the consumers (such as social media use time and gender).

Factors related to eWOM information quality and traits of the consumers, when considered in combination, predict eWOM use behavior in particular sets of conditions.

This work enriches the eWOM literature by providing an in-depth understanding of eWOM use from a configuration perspective. Configuration analysis serves as a better tool for explaining the complex relationships among variables than a regression analysis approach does. Additionally, in response to the need to move beyond multiple regression analysis to algorithmic approaches, this study shifts the emphasis from a symmetric paradigm to an asymmetric perspective for data analysis focused on eWOM use.

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.

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.

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.

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.

Help brand managers to design advertisements that add brand credibility in environmentally-aware urban markets.

It helps to define green information quality and the interacting effects of eco-label credibility and consumer knowledge in green information processing.

This study aims to examine the factors that influence peer-to-peer online host advertising effectiveness (POHAE). The study posits that POHAE is a multidimensional construct supported by emotional appeal, information completeness, advertising creativity and social responsibility practices influencing purchase intention and positive word of mouth. Perceived value is hypothesised as the moderating variable for the relationship between POHAE and purchase intention.

Quantitative data were collected from New Zealand through a quasi-experimental survey. A total of 95 people participated in the experiment. The study uses one-way repeated measures design ANOVA to test Hypothesis 1 and MEMORE model to test the effects of mediation and moderation for repeated measures.

Results are significant to the study model. ANOVA results show that the assumption of sphericity is not violated: Mauchly’s W, Greenhouse–Geisser, Huynh–Feldt estimates are equal to one, suggesting that the data are perfectly spherical. The mediation and moderation effects for repeated measure designs are also significant. The tests are based on 95 per cent Monte Carlo confidence interval and 20,000 bootstrapping samples.

This study enhances the hierarchy of effects theory (HOE) (Lavidge and Steiner, 1961), which posits that consumers respond to a specific marketing communication through three components: the cognitive component, which is measured by an individual’s intellectual, mental or rational states; the affective component that refers to an individual’s emotional and feeling states; and finally the conative or motivational state, that is, the striving state relating to the tendency to treat objects as positive or negative. This study observes significant paths from POHAE to purchase intention and word of mouth. Limitations include a small sample size (95) and not regressing the POHAE variables individually on purchase intention and word of mouth.

Given the absence of a brand, as in the Airbnb host advertisement, attention should be given to writing the adverts effectively. Advertising creativity does not only hold for graphics and personal pictures but also for the hosts who need to be creative in crafting their advertisement text. Elements such as social responsibility practice and creativity should also not be overlooked.

This study provides insights on how to effectively communicate with potential customers in a peer-to-peer marketplace.

This study provides an insight into peer-to-peer marketplaces on the importance of marketing communication strategies by providing more attention to writing advertisement texts. It is important to understand the variables that influence consumers’ motivation in responding to Airbnb online advertisements.

The conclusions on the importance of corporate response timing to a crisis have remained inconsistent. Some studies suggest that active response may reduce negative impacts, whereas managers argue that issuing official response frustrates stakeholders and thus decreases the firm value. The purpose of this paper is to investigate the role of external media in the response timing strategy and the consequent stock market reaction.

Based on 130 corporate crises that befell publicly listed firms in China from 2007 to 2014, this paper uses the Baidu News Search Engine and Chinese Lexical Analysis System to construct the variables of the media characteristics. A structural equation model is established to test the hypotheses.

The results of this paper suggest that media coverage drives response timing after a crisis. Although an official response is a burden for firms, the timing strategy has multidimensional benefits including effectively alleviating negative effects (defined as buffering effects) and repairing the market (defined as restoring effects). Moreover, the buffering effects of response timing are stronger when completeness of response is low.

This study mainly contributes to crisis communication literature by introducing the role of media in prompting managers to make timing decisions. The findings of this study provide empirical support for the importance of timing response strategy.

In recent years it has been often claimed that quality is one of most critical success factors for organizations. Managers introduced quality‐based programmes – such as total quality management – assuming that performances would improve. However, many quality‐based initiatives failed. There are several reasons that could explain the failure of quality‐based strategies in a number of firms; suggests two causes: the lack of effective decisional tools for evaluating the most effective investment(s) among a set of potential programmes; and the lack of specific goals to be assigned to each investment in order to monitor the actual results of the programmes on time. In small firms these problems are greater because of the limited availability of financial and managerial resources which make more difficult the identification of the most effective decisional solutions. Identifies a conceptual framework aimed at supporting the choice of most effective models for evaluating quality‐related investments in small firms, particularly an approach which balances different decisional needs such as completeness, urgency of evaluation, measurability of output and structural characteristics.

Part II contrasts the views of materiality in the Conceptual Frameworks of the IASB, FASB, IPSAS, and other framework such as the Integrated Reporting. In particular, it analyzes at what level and how differently that concept interacts with the qualitative characteristics of financial information in each of those frameworks. It looks at its pervasiveness and entity specificity, the interlock with the concept of relevance, reliability and faithful representation, completeness, understandability, neutrality, and drills down to the link to recognition.

This part then compares the definitions of materiality in different standards and contexts, to then draw a taxonomy of materiality and its attributes, such as the subject matter, thecontext of assessment, the addressees, the assessor, and the materiality test. A large part of the analysis involves the comparison between legal definitions of materiality and characterizations in the accounting, financial, and larger management contexts.

The purpose of this paper is to develop and validate a multidimensional hierarchical scale for measuring “e-service quality variation.”

Based on the psychometric scale-development approach, qualitative and quantitative methods were employed to develop the e-SERVAR scale. A multidimensional hierarchical factor structure of e-SERVAR is proposed, along with a set of preliminary items derived from literature and the qualitative study. Furthermore, the Yahoo website in Taiwan was chosen to be the target e-service website for data collection to develop the e-SERVAR scale. A series of statistical methods (i.e. item-to-total correlations, exploratory factor analyses, CFAs and structural equation modeling) were adopted to verify construct reliability and validity as well as nomological validity of the scale.

A 41-item e-SERVAR scale based on the structure of a hierarchical factor model was developed that contains three primary dimensions (i.e. information, system and fulfillment) and nine subdimensions (information accuracy, information quantity, information timeliness, information usefulness, system reliability, system security, merchandise quality, merchandise delivery timeliness and merchandise security).

The results of this study help managers identify sources of quality variability and design efficacious strategies to reduce such variability in order to improve the overall e-service quality.

Prior research of e-service quality has paid less attention to the role of e-service quality variability. Discussion of e-service quality variability was mainly conceptual in nature. This research presents the e-SERVAR scale as a measurement tool that provides a new avenue for researchers to study how to improve e-service quality by measuring service variability.

The purpose of this paper is to present a literature review that aims to provide insight into the characteristics and effectiveness of supply chain visibility (SCV), as well as to identify metrics that capture these aspects in business processes.

A systematic review of the supply chain literature is conducted to identify the characteristics and the effectiveness of SCV. The synthesis of SCV effectiveness and its metrics are based on the process-oriented approach which relates the effectiveness of SCV to improved business performance.

This study reveals that the characteristics of SCV can be captured in terms of the accessibility, quality, and usefulness of information. The benefits of SCV are found to extend beyond improvements to operational efficiency of business processes or to the strategic competencies of an organization.

This study underlines that clear agreements between all players involved in the SC can help to solve problems caused by information completeness (type and amount of information), and unlock the full potential of SCV projects.

By using a process-oriented approach, this review provides a comprehensive explanation of the functions of SCV, as well as its first-order effects, in terms of automational, informational, and transformational characteristics.

Clinical notes typically contain medical jargons and specialized words and phrases that are complicated and technical to most people, which is one of the most challenging obstacles in health information dissemination to consumers by healthcare providers. The authors aim to investigate how to leverage machine learning techniques to transform clinical notes of interest into understandable expressions.

The authors propose a natural language processing pipeline that is capable of extracting relevant information from long unstructured clinical notes and simplifying lexicons by replacing medical jargons and technical terms. Particularly, the authors develop an unsupervised keywords matching method to extract relevant information from clinical notes. To automatically evaluate completeness of the extracted information, the authors perform a multi-label classification task on the relevant texts. To simplify lexicons in the relevant text, the authors identify complex words using a sequence labeler and leverage transformer models to generate candidate words for substitution. The authors validate the proposed pipeline using 58,167 discharge summaries from critical care services.

The results show that the proposed pipeline can identify relevant information with high completeness and simplify complex expressions in clinical notes so that the converted notes have a high level of readability but a low degree of meaning change.

The proposed pipeline can help healthcare consumers well understand their medical information and therefore strengthen communications between healthcare providers and consumers for better care.

An innovative pipeline approach is developed to address the health literacy problem confronted by healthcare providers and consumers in the ongoing digital transformation process in the healthcare industry.

This study aims to analyze the motivations underlying information usefulness, attitude and acceptance of health information related to coronavirus disease 2019 (COVID-19) avoidance based on the information acceptance model (IAM) and the elaboration likelihood model (ELM).

This study conducted a quantitative approach using survey that generated 364 valid responses. Structural equation modeling was applied to analyze the data and evaluate the hypotheses.

The results of this study showed that the determinants of information usefulness are argument quality (comprising accuracy and timeliness) and peripheral route (comprising credibility and relevance), whereas no significant relationship was found between completeness and information quantity and information usefulness. Further analysis indicated that attitude and information usefulness significantly affect health information acceptance to COVID-19 avoidance.

Using ELM and IAM, an explanation of health information acceptance in the salient pandemic context was given. This study contributed to the current literature by offering insights into attitude and information usefulness for information acceptance. The validation of the model was strengthened by identifying the effects of argument quality and peripheral route attributes on information usefulness, which is stated to make contributions to the earlier literature.

Practitioners should strive to understand the facilitators regarding argument quality and peripheral routes to broaden information usefulness. The findings of this study are helpful for practitioners to implement communication campaigns that foster attitude and health information acceptance in the COVID-19 pandemic as well as in similar disease situations.

This study provides individuals and organizations with necessary information about the importance of mobile applications (m-applications) in distributing online information and about reliable guidelines for the implementation of disease avoidance to improve their health status.

Existing studies investigated users’ health information acceptance in some contexts related to general disease, but less is known about this behavior among young individuals via m-applications at the moment of COVID-19 and in emerging economies. This study identifies the efforts made by the relationship between information and technological diffusion to help individuals surmount difficulties in times of crisis.