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This study mainly aims to explore the impact of management practices and managerial behavioral attributes on credit rating quality in Tehran Stock Exchange.

In this study, 214 firms were assessed from 2014 to 2020. The credit rating quality was measured through Technique for Order of Preference by Similarity to Ideal Solution and the entropy weighting method. In accordance with the theoretical literature, managerial entrenchment, managerial myopia, managerial overconfidence and managerial narcissism were considered as the managerial attributes. Furthermore, to examine management practices, cash flow management and accrual management were explored.

The results of this study showed that the cash flow from operations management and the accrual management has a significant positive effect on the credit rating quality. The managerial entrenchment, managerial narcissism and managerial myopia have significant negative effects on credit rating quality, while the effect of managerial overconfidence on credit rating quality is not significant.

Understanding the factors that affect the credit rating quality is of a great importance. Considering the significance of cash management in the present era and the impact of managerial psychological and behavioral characteristics in the development of the organization, empirical results of this study can help investors, capital market regulators and other stakeholders to strengthen the firm and better decisions.

The authors examine the role of CEO political ideology in the credit rating process.

This study adopts a quantitative method with panel data regressions using a sample of 5,211 observations from S&P 500 firms from 2001 to 2012.

The authors find that firms run by Republican-leaning CEOs, who tend to have conservative political ideologies, enjoy more favorable credit ratings than firms run by Democratic-leaning CEOs. In addition, the association between CEO political ideology and credit ratings is more pronounced for firms with high operating uncertainty, low capital intensity, high growth potential, weak corporate governance and low financial reporting quality. Finally, the authors find that CEO political ideology affects a firm's cost of debt incremental to credit ratings, consistent with debt investors incorporating CEO political ideology in their pricing decisions.

Leveraging CEO political ideology, the authors document that credit rating agencies incorporate managerial conservatism in their credit rating decisions. This finding suggests that CEO political ideology serves as a meaningful signal for managerial conservatism.

The study suggests that credit rating agencies incorporate CEO political ideology in their credit rating process. Other capital market participants such as auditors and retail investors can also use CEO political ideology as a proxy for managerial conservatism when evaluating firms.

The paper carries practical implications for practitioners, firm executives and regulators. The results on the association between CEO political ideology and credit ratings suggest that other financial institutions could also incorporate CEO political ideology in their evaluation in their evaluation of firms. For example, when evaluating audit risk and determining audit pricing, auditors may add CEO political ideology as a risk factor. For firms, especially those that have Democratic-leaning CEOs, the authors suggest that they could reduce the unfavorable effect of CEO political ideology on credit ratings by improving their corporate governance and financial reporting quality, as demonstrated in the cross-sectional analyses. Finally, this study shows that CEO political ideology, as measured by CEOs' political contributions, is closely related to a firm's credit ratings. This finding may inform regulators that greater transparency for CEOs' political contributions is needed as information on contributions could help capital market participants perform risk analyses for firms.

Credit rating agencies release their research methodologies for determining corporate credit ratings and identify managerial conservatism as an important factor that affects their risk assessments. The extant literature, however, has not empirically investigated the relation between credit ratings and managerial conservatism, which, according to behavioral consistency theory, can be proxied by CEO political ideology. This study provides novel empirical evidence that identifies CEO political ideology as an important input factor in the credit rating process.

Prior literature on online customer reviews (OCRs) suggests that individuals are socially influenced by information shared by others. Given that the online environment brings together users from different cultures, understanding how users differ in their processing and generation of OCRs across cultures is imperative. Specifically, this paper explores how cross-cultural differences influence OCR generation when there are inconsistencies between recent and overall review ratings.

The authors employ an empirical study and an experimental approach to test the predictions. For the empirical study (Study 1), the authors collected and analyzed actual review data from an online hotel review platform, Booking.com. This was followed by an experimental study (Study 2) in which the authors manipulated the thinking style represented by each cultural orientation to further explain how and why cross-cultural differences exist.

The results show that compared with the review ratings of users from collectivist cultures, those of users from individualistic cultures are more likely to follow recent review ratings. Based on the experimental study, the authors further find that such cross-cultural differences in OCR generation are driven by differences in thinking style.

This research extends the literature by demonstrating the cross-cultural differences in individuals' herding tendencies in OCR generation. The authors also add to the literature by showing in which direction OCR herding occurs when there is a discrepancy between overall and recent review ratings. From a managerial perspective, the findings provide guidelines for online platforms serving the global market on predicting customers' OCR generation and constructing appropriate response strategies.

The study sought to fit managerial competencies in the metatraits of the Circumplex Personality Metatraits Model (CPM) by Strus, Cieciuch and Rowinski (2014). The authors assumed that managerial competencies would be located in the sector of personality metatraits, specifically, the plus poles: Integration (Gamma-Plus) through Stability (Alpha-Plus) and Self-restraint (Delta-Plus) to Plasticity (Beta-Plus).

A group of 327 managers took part in this study. Managerial competencies related to social skills, problem-solving, management and goal striving, openness to change and employee development were evaluated via the assessment center (AC).

The results revealed a negative relationship between all managerial competencies and negative metatraits of Disharmony (Gamma-Minus) and Passiveness (Beta-Minus). On the other hand, Integration (Gamma-Plus) and Plasticity (Beta-Plus) appeared to be positively related to two competencies only: openness to change and problem-solving.

All managerial competencies fitted well in the CPM pattern with adequate degrees of fit. The discussion indicates the role of managerial competencies and personality assessment in the selection process.

This study seeks to identify the main determinants of the optimal capital structure by reexamining the interpretation of the conventional set of explanatory variables used as proxies for the costs and benefits of debt in the context of the dynamic tradeoff theory.

The authors isolate the variation in leverage due to different targets from that caused by deviations by aggregating the data across a dimension identifying firms with similar targets – credit rating category.

Contrary to theoretical priors, large and profitable rated firms have lower targets. The authors show that size and profitability proxy for non-financial risk and that, for rated firms, non-financial risk is positively correlated to the optimal leverage. The benefits of a better rating outweigh the costs of foregone tax shields for firms with relatively low non-financial risk. The authors find support for that theory in institutional trading – institutional investors do not punish highly rated firms when credit downgrades occur.

This paper contributes to the capital structure literature by developing a new approach based on data aggregation. This study is the first, to the authors’ knowledge, to find a positive effect of the firm's non-financial risk on target leverage among rated firms. The authors argue that the benefit of a better credit rating is an increasing function of the rating itself. The authors also contribute to the literature on the impact of credit ratings on the capital structure choices of the firm.

This paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per available room (RevPAR).

The authors conducted review sentiment analyses in three moments (−1, −7 and −14 days) before arrival time using a data set of budget hotel performance and online reviews. The aim was to identify the effect of review sentiment in the budget hotel market on the three performance metrics.

Daily sentiment positively affects ADR and negatively affects OR and RevPAR, but only up to a certain threshold, after which the trend reverses. Prices increase with the level of sentiment, and high prices lead to low OR and RevPAR only when the sentiment scores are low. When they are high, they are associated with low rates, which lead to high OR and RevPAR.

Daily review sentiment can be viewed as a valuable “barometer” indicating a hotel’s daily operational effectiveness. Daily sentiment can thus allow hotel managers to adjust their dynamic pricing strategies more accurately.

This study identifies daily sentiment as an alternative predictor of hotel performance. In addition to the roles of valence and volume in the decision-making process, the authors found that daily review sentiment can be an “in-the-moment” factor with a high impact, encouraging consumers to complete their transactions. This study suggests that aggregated measures such as the total number of reviews and overall ratings of the hotel should not be the sole consideration in reputation management.

The unique employment status of gig workers as independent contractors and their impact on consumers provide an important opportunity for the current research to understand gig workers' perceptions of their employment and how that affects job performance outcomes. These gig workers serve as the frontline service providers for platforms like Airbnb hosts, Lyft drivers and Wag walkers performing customer-facing services. However, their status as gig workers, not traditional employees, presents challenges to platforms. The purpose of this research is to gain insights into the profiles of gig workers, examine the challenges platforms have in retaining high-performing workers and provide a research agenda on this important group of frontline service providers.

Incorporating variables deemed important in examining self-determination theory, a large-scale data collection via an online survey was administered, yielding 447 completed surveys. A two-step cluster analysis procedure was conducted to categorize sample respondents into four distinct groups.

Four groups emerged from the cluster analysis, labeled “Ambivalent Outsider,” “Competent Cog,” “Independent Insider” and “Committed Comrade.” The results suggest that there are significant differences across all variables and groups based on gig worker responses and self-reported customer satisfaction scores. The gig worker profiles developed are then utilized to formulate research propositions that are the basis for the research agenda presented.

The goal of many collaborative consumption platforms may be to hire Independent Insiders or Committed Comrades; however, that is difficult to attain with every hire. Thus, the segmentation results provide insights for companies seeking to hire, retain, and successfully motivate their workforce.

Given the freedom and flexibility afforded to gig workers, and the importance they have on the service experience for customers, understanding their own perceptions of employment and performance is critical to ensuring a positive experience for all parties. Research on collaborative consumption has largely focused on consumers or the management of freelance workers with only tangential applicability to gig work. This paper offers a comprehensive research agenda for gig worker management based on the typology of gig workers created.

The Purpose of the study was to investigate the construct validity and internal consistency of the LaMI among staff in the context of elderly care in Sweden.

Questionnaire data from a longitudinal study of staff working in elderly care were used. Data were collected using the Leadership and Management Inventory. First data collection was for explorative factor analysis (n = 1,149), and the second collection, one year later, was for confirmatory factor analysis (n = 1,061).

The explorative factor analysis resulted in a two-factor solution that explained 70.2% of the total variance. Different models were tested in the confirmatory factor analysis. The final model, a two-factor solution where three items were omitted, showed acceptable results.

The instrument measures both leadership and management performance and can be used to continually measure managers’ performances as perceived by staff to identify areas for development.

This paper aims to investigate textual characteristics of customer reviews that motivate companies to respond (sentiment negativity and sentiment deviation) and how aspects of these company responses (response intensity, length and tailoring) affect subsequent customer review quality (comprehensiveness and readability) over time.

Leveraging a large data set from a leading app website (Shopify), the authors combine text mining, natural language processing (NLP) and big data analysis to examine the antecedents and outcomes of online company responses to reviews.

This study finds that companies are more likely to respond to reviews with more negative sentiment and higher sentiment deviation scores. Furthermore, while longer company responses improve review comprehensiveness over time, they do not have a significant influence on review readability; meanwhile, more tailored company responses improve readability but not comprehensiveness over time. In addition, the intensity (volume) of company responses does not affect subsequent review quality in either comprehensiveness or readability.

This paper expands on the understanding of online company responses within the digital marketplace – specifically, apps – and provides a new and broader perspective on the motivations and effects of online company responses to customer reviews. The study also extends beyond the short-term focus of prior works and adds to literature on long-term effects of online company responses to subsequent reviews. The findings provide valuable insights for companies (especially those with apps) to enhance their online communication strategies and customer engagement.

Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.