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By delineating electronic word-of-mouth (e-WOM) into numerical rating and opinionated review, the purpose of this paper is to advance a research model that articulates how the provision of e-WOM can aid in alleviating consumers’ distrust of online service providers, a key determinant in the former’s adoption of the latter. The authors also endeavor to uncover the role gender plays in moderating the aforementioned relationship between e-WOM and distrust.

The research model was validated via a field survey administered on 115 college students and faculty members, who had been exposed to a custom-developed online restaurant review website. SmartPLS 2.0.M3 was employed to verify both the measurement and structural properties of the research model.

Distrust reduces male consumers’ perceptions of usefulness and ease of use toward an online service provider while increasing their adoption intention. For their female counterparts, distrust reduces both perceived ease of use and adoption intention for an online service provider. Additionally, for male consumers, only opinionated review aids in alleviating distrust. Conversely, both numerical rating and opinionated review aid in alleviating the distrust of female consumers. Moreover, in contrast to their female counterparts, male consumers are less susceptible to the influence of cognitive dissonance between numerical rating and opinionated review.

This study integrates distrust with the technology acceptance model (TAM) in an attempt to gain a deeper appreciation of technology acceptance behavior. Furthermore, this study builds on the confirmation bias theory to delineate e-WOM into numerical rating and opinionated review in order to better explicate variations in how males and females react to these two distinct forms of e-WOM. Consistent with the cognitive dissonance theory, the distinction between numerical rating and opinionated review enables further exploration of the impact of cognitive dissonance between these two forms of e-WOM on male and female consumers’ distrust of online service providers. Finally, this study unveils contrasting conflict resolution strategies adopted by male and female consumers to cope with cognitive dissonance in e-WOM.

Findings from this study yield prescriptions for practitioners in terms of how e-WOM can be harnessed to alleviate consumers’ distrust of online service provider. Whereas it is crucial for online service providers to draw on opinionated review to reduce distrust for male consumers, numerical rating should be emphasized for female consumers. This study also sensitizes practitioners to the drawback of providing both numerical rating and opinionated review at the same time due to the potential for cognitive dissonance.

This study is the first to: position distrust within the well-accepted TAM in order to enrich the understanding of technology acceptance behavior; testify to the importance of delineating between numerical rating and opinionated review due to the possibility of cognitive dissonance between these two distinct forms of e-WOM, as well as; uncover contrasting conflict resolution strategies adopted by male and female consumers to cope with cognitive dissonance in accordance with the confirmation bias theory.

Purpose — New methods of measuring user satisfaction in transport services have been proposed and applied in the literature. In this paper, we compare three alternative measures for estimating user satisfaction: the numerical rating, the ordinal rating and the choice.

Approach — We analysed these measures considering their differences and limitations and the models that use these measures as dependent variables. We developed and applied a methodology to build these models. It comprises a preliminary qualitative analysis and a quantitative survey to identify the most relevant attributes of the satisfaction function, and a stated preference survey to obtain information of the alternative satisfaction measures for modelling purpose.

Findings — The ordinal rating may be a better user response to estimate satisfaction than score and choice based on its characteristics. The results obtained in the application reinforced this approach.

Research limitations — It is assumed that choice, score and ordinal valuation depend upon a latent stochastic satisfaction function of the same attributes. Further research is needed to analyse this assumption and how these responses vary according to the context for decision and exogenous factors, including the response scale of ratings.

Practical implications — Gathering alternative satisfaction responses simultaneously from users allowed for the consistency analysis and filtering of data, which greatly benefited the model estimation process.

Originality/value — The paper provides a methodology to estimate user satisfaction models in transit services, which can be applied in other transport services. The conceptual analysis and the application suggest that ordinal ratings are key user responses to uncover the underlying satisfaction function.

This manuscript reports evidence on how debt-taking decisions of top management in a multi-country setting do affect credit rating scores assigned by credit rating agencies (CRAs) as global monitors of creditworthiness of borrowers. This aspect has been long ignored by researchers in the literature. The purpose of this paper is twofold. A test model is specified first using theories to connect debt-taking behavior to credit rating scores. Once that model helps to identify a number of statistically significant factors, the next step helps to identify threshold values at which the variables driving debt-taking behavior would worsen the credit rating scores as turning points of the thresholds.

The study identifies factors driving creditworthiness scores due to debt-taking behavior of countries and develops a correct research design to identify a model that explains (1) credit rating scores and the factors driving the scores and runs (2) panel-type regressions to test model fit. Having found factors driving debt-taking behavior by observed units, the next step identifies threshold values of factors at which point further debt-taking is likely to worsen credit rating risk of the observed units. This is a robustness test of the methodology used. The observed units are 20 countries with data series across 14 years.

First, new findings suggest there are about six major factors associated with debt-taking behavior and credit rating changes. Second, the model developed in this study is able to account for substantial variability while the identified factors are statistically significant within the normal p-values for acceptance of hypotheses. Finally, the threshold values of factors identified are likely to be useful for managerial decisions to judge the levels at which further debt-taking would worsen the credit rating scores of the observed units.

The observed units are from 20 countries over 14 years of annual data available on credit rating scores (privately obtained from Standard and Poor [S&P]). The sample represents major economies but did not include emerging countries. In that regard, it will be worthwhile to explore the debt-taking behavior of emerging economies in a future study using the methodology verified in this study.

The findings help add few useful guidelines for top management decisions. (1) There are actually factors that are associated with debt-taking behavior, so the authors now know these factors as guides for managerial actions. (2) The authors are free to state that the credit rating changes occur on objective changes in the factors found as significantly related to the debt-taking behavior. (3) The threshold values of key factors are known, so top management could use these threshold values of named factors to monitor if a debt-taking decision is going to push the credit rating to a worse score.

There are society-wide implications. Knowing that the world's debt level is high at US$2.2 for each gross domestic product (GDP) dollar across almost 200 countries, any knowledge on what factors help drive creditworthiness scores, thus credit riskiness, is revealed in this paper. Knowing those factors and also knowing the turning points of the factors – the threshold values – likely to worsen creditworthiness scores is a powerful tool for controlling excessive debt-taking by an observation unit included in this study (The dataset in this research can also be used to see inter-temporal movement on debt-taking in a future study).

In the authors' view, there are many studies on debt-taking behavior. But none has connected debt-taking on how (1) named factors are observable to management that affect credit rating changes and (2) if a factor affects creditworthiness, at which point of the factor value, the creditworthiness will flip to worsen the score. These aspects are seldom found in the literature. Hence, the paper is original with practical value at the global level.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

This paper aims to investigate the relation between the creditworthiness of US institutions of higher education and their student selectivity (i.e. demand and quality).

The authors study whether the impact of student selectivity differs across public vs private universities; across the credit quality of the given public university’s state; and across the level of state appropriations for the given public university.

The authors find that student quality and demand measures are significantly associated with their corresponding institution’s creditworthiness, especially for private universities.

For public universities the association is weak and, contrary to the expectations, does not depend on the state credit quality or level of state funding. The findings are robust to the inclusion of control variables.

The creditworthiness of corporates is most visible in credit ratings. This paper aims to present an alternative credit rating measure independently of credit rating agencies. The credit rating score (CRS) is based on the credit default swap (CDS) market trading.

A CRS is developed which is a linear function of logarithmized CDS spreads. This new CRS is the first one that is completely independent of the rating agency. The estimated ratings are compared with ratings provided by Fitch Ratings for 310 European and US non-financial corporates.

The empirical analysis shows that logarithmized CDS spreads and issuer credit ratings by agencies have a linear relationship. The new CRS provides market participants with an alternative risk assessment, which is solely based on market factors, and does not rely on credit rating analysts. The results indicate that our CRS is able to anticipate agency ratings in advance. Moreover, the analysis shows that the trading volume has only a limited influence in the anticipation of rating changes.

This study shows a new approach to measure the creditworthiness of firms by analyzing CDS spreads. This is highly relevant for regulation, firm monitoring and investors.

Since sovereign ratings provided by credit rating agencies (CRAs) are a key determinant of the interest rates a country faces in the international financial market and once sovereign ratings may have a constraining impact on the ratings assigned to domestic banks or companies, some studies have focused on identifying the determinants of sovereign credit risk assessments provided by CRAs. In particular, this study estimates the effect of fiscal credibility on sovereign risk using four different comprehensive credit rating (CCR) measures obtained from CRAs' announcements and two different fiscal credibility indicators.

We build comprehensive credit rating (CCR) measures to capture sovereign risk. These measures are calculated using sovereign ratings, the rating outlooks and credit watches issued by the three main credit rating agencies (S&P, Moody's and Fitch) for long-term foreign-currency Brazilian bonds. Based on monthly data from 2003 to 2018, we use different econometric estimation techniques in order to provide robust results.

The results indicate that fiscal credibility exerts both short- and long-run effects on sovereign risk perception, and macroeconomic fundamentals are important long-run determinants.

Since fiscal credibility reflects the government's ability to maintain budgetary balance and sustainable public debt, the government should keep its commitment to responsible fiscal policies so as not to deteriorate expectations formed by financial market experts about the fiscal scenario and, thus, to achieve better credit assessments issued by CRAs with respect to sovereign debt bonds. Sovereign credit rating assessment is a voluntary practice. It is up to the country whether they want to apply for a rating assessment or not. Thus, without a sovereign rating, one must find an alternative to measure the sovereign risk of a country. In this sense, an important practical implication that this study provides is that fiscal credibility can be used as a leading indicator of sovereign risk perceptions obtained from CRAs or even as a proxy for sovereign risk.

This paper is the first to verify how important the expectations of financial market experts in relation to the fiscal effort required to keep public debt at a sustainable level (i.e. fiscal credibility) are to sovereign risk perception of credit rating agencies. In this sense, the study is the first to address this relation, and thus it contributes to the literature that seeks to understand the determinants of sovereign ratings in emerging countries.

Credit rating agencies (CRAs) are perceived as highly influential in the financial system since their announcements can affect several players in the financial markets, from big private financial and non-financial companies and their financial markets experts to sovereign states. In this sense, this study investigates whether sovereign credit news issued by CRAs (measured by comprehensive credit rating (CCR) variables) affect the uncertainties about the exchange rate in the future (captured by the disagreement about exchange rate expectations). The study is relevant once there is evidence indicating that CRAs' assessments are responsible for affecting international capital flows and, thus, sovereign rating changes can affect the expectations formation process regarding the exchange rate. In addition, there is evidence indicating that the disagreement about exchange rate expectations affects the disagreement about inflation expectations, which brings consequences to policymakers.

The dependent variables are the disagreement in expectations about the Brazilian exchange rate for different forecast horizons, 12, 24 and 36 months ahead and the first principal component of theses series. On the other hand, the CCR variables are built upon the long-term foreign-currency Brazilian bonds ratings, outlooks and credit watches provided by the main CRAs. Estimates are obtained using ordinary least squares (OLS) and generalized method of moments (GMM); a dynamic analysis is performed using vector-autoregressive (VAR) through impulse-response functions.

Negative (positive) sovereign credit news, given by a rating downgrade (upgrade) and/or a negative (positive) outlook/watch status, increase (decrease) the disagreement about exchange rate expectations. This result holds for all disagreement and CCR variables.

The study brings practical implications to both private agents (mainly financial market experts) and policymakers. An important practical implication of the study concerns the ability of CRAs to affect the expectations formation process of financial market experts regarding the future behavior of the exchange rate. When a CRA issues a signal of improvement in a country's sovereign rating, this signal reflects the perception of improvement in macroeconomic fundamentals and reduction of uncertainties about the country's ability to honor its financial obligations, which therefore, facilitates the expectations formation process, causing a reduction in the disagreement about the exchange rate expectations. With respect to the consequences for policymakers, they will have more difficulty in guiding expectations in a country with a worse sovereign risk rating, where agents have difficulties in forming expectations and the disagreement in expectations is greater.

The study is the first to analyze the impact of CRAs' announcements on the disagreement about exchange rate expectations. Moreover, it connects the literature that investigates the effects of sovereign credit news on the economy with the literature that examines the main determinants of disagreement in expectations about macroeconomic variables.

In the deregulated public sector upper secondary school field in Oslo, Norway, turnover among teachers is found to be high. The purpose is to examine whether instrumental practices like control-oriented HRM, performance appraisal and heteronomy directly or indirectly lead to turnover intention, as a crucial pre-stage to turnover. Another purpose is to examine whether this varies with feedback format.

The present study is based on a survey (N = 1,055) carried out among upper secondary school teachers in Norway. Data were analyzed with path analysis, and mediation and moderation analyses were performed.

The study shows that control-oriented HRM, PA dissatisfaction and heteronomy are antecedents to turnover intention for teachers receiving feedback in three different feedback formats. The effect of control-oriented HRM and PA dissatisfaction on turnover intention was generally not stronger among numerically rated than among those rated otherwise. For most feedback format groups, leader–member exchange mediated between turnover intention and PA dissatisfaction and heteronomy, respectively, but not between turnover intention and control-oriented HRM. For teachers rated with text, figures or colors, LMX moderated between control-oriented HRM and turnover intention.

The paper advances that introduction of instrumental practices will be seen as breaches of the psychological contract, but this does not apply to all feedback format groups, for example those receiving numerically rating. Limitations involve self-reported measures, direction of causality issues and a relatively low sample size for some groups.

Practitioners should note that both control-oriented HRM, performance appraisal and little autonomy may cause teachers to consider leaving their jobs. Practitioners should also be aware of the importance of the relationship between employee and leader, as negative responses to instrumentality may work through the leader–employee relationship, leading to turnover intention and, possibly, turnover.

The present study is among the first to examine whether and how antecedents to turnover intention vary with feedback format. A rare interaction between HRM and LMX is uncovered. Few other studies have analyzed the relationship between instrumental practices and turnover intention in light of psychological contract theory.

The aim of this research is to theorize and demonstrate that analyzing consumers’ text product reviews using text mining can enhance the explanatory power of a product sales model, particularly for hedonic products, which tend to generate emotional and subjective product evaluations. Previous research in this area has been more focused on utilitarian products.

Our text clustering-based procedure segments text reviews into multiple clusters in association with consumers’ numeric ratings to address consumer heterogeneity in taste preferences and quality valuations and the J-distribution of numeric product ratings. This approach is novel in terms of combining text clustering with numeric product ratings to address consumers’ subjective product evaluations.

Using the movie industry as our empirical application, we find that our approach of making use of product text reviews can improve the explanatory power and predictive validity of the box-office sales model.

Marketing scholars have actively investigated the impact of consumers’ online product reviews on product sales, primarily focusing on consumers’ numeric product ratings. Recently, studies have also examined user-generated content. Similarly, this study looks into users’ textual product reviews to explain product sales. It remains to be seen how generalizable our empirical results are beyond our movie application.

Whereas numeric ratings can indicate how much viewers liked products, consumers’ reviews can convey why viewers liked or disliked them. Therefore, our review analysis can help marketers understand what factors make new products succeed or fail.

Primarily our approach is suitable to products subjectively evaluated, mostly, hedonic products. In doing so, we consider consumer heterogeneity contained in reviews through our review clusters based on their divergent impacts on sales.