Diagnosing service quality using customer reviews: an index approach based on sentiment and gap analyses

Recognizing the importance and potential benefits of customer reviews as a source of the voice of customers, this study proposes an analytic framework and procedures for analyzing customer reviews—termed a customer review-based gap analysis—that are tailored to diagnosing service quality. To this end, we conduct sentiment analysis on customer reviews to capture customers’ perceptions and expectations at the service-feature level, which are not expressed explicitly in their reviews. A case study of a mobile navigation service shows that the customer review-based gap analysis can provide the practical information required to diagnose service quality from customer review data. The suggested indexes for capturing customers’ perceptions and expectations reveal quality strengths and drawbacks at the service-feature level. In addition, incorporating these indexes into those for quality performance and objectives based on a service-feature hierarchy provides a diagnostic tool capable of examining service quality in both overall as well as detailed aspects.     

Does the XBRL Reporting Format Provide Incremental Information Value? A Study Using XBRL Disclosures During the Voluntary Filing Program

This study investigates whether the eXtensible Business Reporting Language (XBRL) reporting format provides incremental information value beyond the same 10K/10Q filings previously provided in HTML format. Using a sample from the XBRL Voluntary Filing Program, we document a significant increase in stock price variance on the day when voluntary XBRL reports are filed. We find market response is stronger when more content is filed on the same day. To evaluate relative information value, we decompose the quarterly return variance for three primary news announcements related to earnings including earnings announcement, HTML filing, and XBRL filing. We find XBRL filings have larger relative information value than HTML filings. Our results indicate that the XBRL reporting format provides incremental information content.     

An Empirical Analysis of Futures Margin Changes: Determinants and Policy Implications

Margin regulation raises two policy concerns. First, an alignment of margins to volatility can amplify procyclicality, leading to a build-up of excess leverage in good times and a forced deleverage in bad times. Second, competition among central counterparties (CCPs) can result in lower margin levels in order to attract more trading volume, which is referred to as a “race to the bottom.” Motivated by these issues, we empirically analyze the determinants of margin changes by using a data set of various futures margins from Chicago Mercantile Exchange (CME) Group. We first find that CME Group raises margins quickly following volatility spikes but does not immediately lower margins following volatility declines, implying that margin-induced procyclicality is more of a concern in recessions than in expansions. In addition, we find some evidence that the margin difference between CME Group and its competitor, Intercontinental Exchange (ICE), is an important driver of margin changes after changes in other margin determinants are controlled for, implying that competition may be factored into margin setting.     

Nonparametric stochastic frontiers: A local maximum likelihood approach

This paper proposes a new approach to handle nonparametric stochastic frontier (SF) models. It is based on local maximum likelihood techniques. The model is presented as encompassing some anchorage parametric model in a nonparametric way. First, we derive asymptotic properties of the estimator for the general case (local linear approximations). Then the results are tailored to a SF model where the convoluted error term (efficiency plus noise) is the sum of a half normal and a normal random variable. The parametric anchorage model is a linear production function with a homoscedastic error term. The local approximation is linear for both the production function and the parameters of the error terms. The performance of our estimator is then established in finite samples using simulated data sets as well as with a cross-sectional data on US commercial banks. The methods appear to be robust, numerically stable and particularly useful for investigating a production process and the derived efficiency scores.     

RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models,and Relations to Other Models and Measures in DEA

Generalized Efficiency Measures (GEMS) for use in DEA are developed and analyzed in a context of differing models where they might be employed. The additive model of DEA is accorded a central role and developed in association with a new measure of efficiency referred to as RAM (Range Adjusted Measure). The need for separately treating input oriented and output oriented approaches to efficient measurement is eliminated because additive models effect their evaluations by maximizing distance from the efficient frontier (in ₁, or weighted ₁, measure) and thereby simultaneously maximize outputs and minimize inputs. Contacts with other models and approaches are maintained with theorems and accompanying proofs to ensure the validity of the thus identified relations. New criteria are supplied, both managerial and mathematical, for evaluating proposed measures. The concept of approximating models is used to further extend these possibilities. The focus of the paper is on the physical aspects of performance involved in technical and mix inefficiencies. However, an Appendix shows how overall, allocative and technical inefficiencies may be incorporated in additive models.     

Efficiency of U.S. hospitals between 2001 and 2011

This study focuses on finding the trend of efficiency in the healthcare industry in recent years. We applied stochastic frontier analysis and data envelopment analysis methods to capture the efficiency of 1,471 hospitals and found a sign of the Baumol effect, which is detected by the decreasing trend of hospital efficiency with increasing trend of labor costs. Furthermore, we compared the results of both approaches (stochastic frontier and data envelope analyses) in capturing efficiency scores and suggest the U‐shaped curve of the size effect may indicate the practice of “cream skimming” by some small hospitals.     

Analysis of technological innovation based on citation information

The paper discusses the dynamic properties of the patent network. Technological innovation occurs frequently, and predicting where it will happen is difficult because an economic system can adapt to changing technology. We construct a patent network based on the cited relations between patents and analyze the properties of the patent network from January 1976 to December 2005 by using USPTO patent data. We find that technology trends, which are calculated by our measures, are similar with historical trends of technology, showing that our measures would be useful to predict future technology relations. Also, we find that the change of similarity between patents shows meaningful results in terms of technological innovation.     

Mediating role of perceived supervisor support in the relationship between job autonomy and mental health: moderating role of value–means fit

Based on self-determination theory (SDT), this study investigates the relationship between job autonomy and mental health and the mediating role of perceived supervisor support (PSS) in that relationship. The study also examines whether employees’ work values moderate the relationships between job autonomy and PSS and mental health. Although it is well known that job autonomy has close relationships with mental health, we know little about the roles of PSS and employees’ values in these relationships. Using data from a nationally representative survey, this study found that PSS mediated the relationship between job autonomy and mental health. Furthermore, intrinsic work values positively moderated the relationships of job autonomy with PSS and mental health, whereas extrinsic work values negatively moderated these relationships. These findings support the idea of value–means fit. The findings provide important implications, beyond SDT, for how employees’ mental health can be improved and which employees benefit more from job autonomy.     

Testing for a Debt‐Threshold Effect on Output Growth

Using the Reinhart–Rogoff dataset, we find a debt threshold not around 90 per cent but around 30 per cent, above which the median real gross domestic product (GDP) growth falls abruptly. Our work is the first to formally test for threshold effects in the relationship between public debt and median real GDP growth. The null hypothesis of no threshold effect is rejected at the 5 per cent significance level for most cases. While we find no evidence of a threshold around 90 per cent, our findings from the post‐war sample suggest that the debt threshold for economic growth may exist around a relatively small debt‐to‐GDP ratio of 30 per cent. Furthermore, countries with debt‐to‐GDP ratios above 30 per cent have GDP growth that is 1 percentage point lower at the median.     

Corporate derivatives use policy and information environment

We provide evidence consistent with the notion that prudent use of financial derivatives improves firms’ information environment. We show that firms with sophisticated and comprehensive derivatives use policies display lower levels of uncertainty about future cash flows, volatility of future income and sales growth, and equity mispricing than those that do not use derivatives. However, we also show that policies that consist of large positions in a single type of derivative contract are not likely to produce similar benefits. These results remain intact even after accounting for the endogenous nature of derivatives use policy and information risk and mispricing.