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This study aims to identify the key determinants of Airbnb rating scores.

This study is based on a sample of 127,257 listings across 43 cities. A total of 24 explanatory variables were identified, and they were further grouped into host verification information, communication, policy of renting, space, information about environment, price and experience of hosting. Both Tobit and ordered logit models were used to perform the analysis.

The results indicate that good communication, large space and provision of information about the listings’ environment have a positive effect on users’ satisfaction, whereas experience of hosting negatively influences users’ satisfaction.

This study contributes to the peer-to-peer accommodation literature by affording a more complete understanding about guest satisfaction and its determinants.

The purpose of this study is to examine Airbnb research using bibliometric methods. Using research performance analysis, this study highlights and provides an updated overview of Airbnb research by revealing patterns in journals, papers and most influential authors and countries. Furthermore, it graphically illustrates how research themes have evolved by mapping a co-word analysis and points out potential trends for future research.

The methodological design for this study involves three phases: the document source selection, the definition of the variables to be analyzed and the bibliometric analysis. A statistical multivariate analysis of all the documents’ characteristics was performed with R software. Furthermore, natural language processing techniques were used to analyze all the abstracts and keywords specified in the 129 selected documents.

Results show the genesis and evolution of publications on Airbnb research, scatter of journals and journals’ characteristics, author and productivity characteristics, geographical distribution of the research and content analysis using keywords.

Despite Airbnb having a history of 10 years, research publications only started in 2015. Therefore, the bibliometric study includes papers from 2015 to 2019. One of the main limitations is that papers were selected in October of 2019, before the year was over. However, the latest academic publications (in press and earlycite) were included in the analysis.

This study analyzed bibliometric set of laws (Price’s, Lotka’s and Bradford’s) to better understand the patterns of the most relevant scientific production regarding Airbnb in tourism and hospitality journals. Using natural language processing techniques, this study analyzes all the abstracts and keywords specified in the selected documents. Results show the evolution of research topics in four periods: 2015-2016, 2017, 2018 and 2019.

Addresses the standardization of the measurements and the labels for concepts commonly used in the study of work organizations. As a reference handbook and research tool, seeks to improve measurement in the study of work organizations and to facilitate the teaching of introductory courses in this subject. Focuses solely on work organizations, that is, social systems in which members work for money. Defines measurement and distinguishes four levels: nominal, ordinal, interval and ratio. Selects specific measures on the basis of quality, diversity, simplicity and availability and evaluates each measure for its validity and reliability. Employs a set of 38 concepts ‐ ranging from “absenteeism” to “turnover” as the handbook’s frame of reference. Concludes by reviewing organizational measurement over the past 30 years and recommending future measurement reseach.

The purpose of this paper is to analyze determinants of institutional quality based on six separate indicators of governance: voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption.

The determinants under consideration include measures of economic freedom by the Cato Institute and the Heritage Foundation, indicators of policy quality, real per capita gross domestic product (GDP), risk rating, and the degree of openness.

Five measures of institutional quality increase real GDP growth significantly across Middle East and North Africa (MENA) countries. In contrast, institutional quality has a negative impact on the growth of private credit and private investment. Further, the combined evidence does not suggest that improvement in institutional quality is a major factor in attracting foreign direct investment flows to MENA countries.

The research provides startling evidence that illustrates how institutions have impacted macroeconomic performance and the underlying roots of institutional quality. Addressing shortcomings in institutions should top the policy agenda in an effort to drive the growth process.

Improving institutional quality will distribute the benefits of growth and enhance macroeconomic performance in the MENA region, which is rich in endowed resources. Nonetheless, the region lacks fundamentals of economic management and quality governance to utilize resources in the most efficient and productive fashion in order to maximize the welfare for a growing population that is constantly seeking productive opportunities to secure employment and a higher real standard of living.

The MENA region is understudied and worthy of much more empirical work. Many cross‐country studies of the determinants of growth omit oil‐producing nations. Focusing on this oil‐rich region is an attempt to fill this void. Unlike previous literature on the relationship between institutions and growth, the paper's approach to the issue analyzes micro foundations in the transmission channel between institutions and economic growth.

This paper investigates the extent to which country risk ratings influence the inflow of foreign direct investment (FDI). Using International Monetary Fund (IMF) data from over 100 countries and Euromoney’s country risk ratings over a ten‐year period, this study finds that country risk ratings have a significant influence on FDI. This effect is stronger for US FDI. We also analyze the relative importance of the individual components of the country risk index.

This paper, using the model suggested by Cantor and Pecker (1996), aims to explore the relations between sovereign ratings and bond yield spreads in emerging markets.

The ordinary least square regression procedure administered on the most recent sovereign ratings of 46 countries demonstrates how the macroeconomic information embody in the sovereign rating scores predict their bond yield spreads relative to the yield on US Treasury bond.

The research finds that the assigned rating scores do not herald the complete elites of the macroeconomic conditions in emerging markets, and there is more incremental information in the publicly available macroeconomic variables, which is much useful in predicting bond yield spreads than that embedded into the sovereign ratings.

The outcomes of the research have strategic implications for global investors and policymakers. The use of credit rating scores along with the macroeconomic fundamentals in emerging economies produces better predictions than the benchmark predictions solely based on the rating scores suggested by the previous research.

This study is the first one to address the issues related to sovereign ratings and bond yield spread in developing and emerging markets using the most recent ratings during the period of the economic recoveries, following the global financial crisis of 2008.

The purpose of this paper is to investigate the vital determinants on the extent of corporate social responsibility (CSR) disclosure in a US context. The selected variables are CEO duality, the presence of women in the board, greenhouse gas (GHG) emissions, emission reduction initiatives, company's risk premium, financial leverage and industry's profile.

The environmental, social and governance (ESG) disclosure score is used as a proxy for the extent of CSR disclosure calculated by Bloomberg. The influence of plausible variables on the ESG disclosure score and its sub-categories was examined by using the least squares dummy variable model (LSDV) incorporating 100 companies listed on Standard & Poor's 500 Index for the period 2009-2012.

The results show that the emission reduction initiatives and GHG emissions influence positively the extent of ESG score. In addition, slight differences exist concerning the determinants of different types of disclosures. Furthermore, it is illustrated that a company's industrial profile seems to have differences among the extent of the different types of disclosure.

The sample of companies is based on the US companies incorporating only large-sized ones.

The study extends previous studies with the inclusion of both traditional and innovative determinants of the CSR disclosure in USA taking into account four years of corporate data. A third party rating approach was adopted in order to calculate the extent of CSR disclosure. Finally, both the shareholders’ and the investors’ attitudes in relation to CSR disclosure are presented.

Quality problems in the service organization are the result of the mismatch between prior expectation and perceived quality of the service. Each organization will attempt to determine the requirements of its customers and translate these requirements into product and delivery process specifications. This paper examines a particular electric company (SCECO‐East), a typical service provider in Saudi Arabia, in which service quality is a distinguishing feature of primary importance. It describes a detailed survey and analysis in the light of the model put forward by Parasuraman et al. It utilizes SERVQUAL for measuring customers’ perceptions of service quality. The study revealed that SCECO‐East scored high in tangibles dimension but low in features of responsiveness and reliability. In addition, while the performance of SCECO‐East was acceptable to all customer categories, service quality was perceived differently by various types of customers, with reinforcement and commercial customers awarding SCECO‐East even lower ratings than other customers did.

This paper aims to investigate the determinants of default mortgage in China and the factors affecting the mortgage amount granted by Chinese banks.

This paper employs the credit scoring model to investigate the determinants of default mortgage in China and the factors affecting the mortgage amount granted by Chinese banks.

Using a proprietary dataset from branches of the Construction Bank of China containing information on all mortgages offered to borrowers from 2004 to 2009 1st quarter, the paper documents that borrower rating, mortgage rate and mortgage duration are significantly related to default rate and mortgage amount. These findings suggest that Chinese banks' mortgage lending are based on commercial basis. This helps to reduce the likelihood of a real estate bubble in China.

The findings in this paper argued that a good credit scoring model has the ability to detect bad loans; this could help the bank to reduce the loan losses from loan default. Consequently, it can improve the profitability and the financial stability of the bank.

This research would benefit both lender and borrowers. Lenders can apply an objective evaluation technique with a standard process and criteria to appraise their customer's credit risks and creditworthiness. A good credit risk management tool can effectively control risk selection, manage credit losses, evaluate new loan programs, improve loan approval processing time, and ensure that existing credit criteria are sound and consistently applied.

The purpose of this paper is to examine factors influencing the audience demand for televised post-season games of the Korean professional baseball league.

The data were collected from a total of 129 games – the entire post-season games from 2008 to 2016. Two dependent variables representing audience demand for televised baseball matches, obtained from the third-party television audit company AGB Nielsen, were regressed on a series of match-related and unrelated antecedent factors associated with each match. Pooled OLS regression with wild bootstrap standard errors with 100,000 replications was applied in the analysis.

Regarding match-related factors, higher television ratings and the greater numbers of television viewers were associated with matches with greater significance, outcome uncertainty and score sum. In terms of the match-unrelated factors, the broadcast platform appeared to be the most powerful predictor of both television ratings and the numbers of viewers. Other than the broadcast platform, night matches, matches with full stadium occupancy and team values showed positive impacts on both the television ratings and the numbers of viewers.

The sales of media rights and sponsorships are the major sources of revenues for professional sports leagues, and the size of these two streams of revenues is in proportion to the size of the audience demand for television and other media. This study provides valuable insights to the sports marketers of professional sports clubs and leagues by establishing proper understanding of the determinants of the audience demand for televised sports.

The characteristics specific to each professional league and country play unique roles in determining the antecedent factors of audience demand for televised sports; this study is one of the few attempts to examine Koran professional baseball league.