Reputation Rating Research Articles

Split bond ratings: Evidence from Japanese credit rating agencies

This study examines why split bond ratings occur between credit rating agencies with different reputations in Japan. Using a sample of Japanese corporate bonds newly issued during the 2006–2021 period, I find that the ratings assigned by a less reputable Japanese rating agency (JCR) are significantly higher than those by a more reputable Japanese rating agency (R&I) for the same bonds because JCR is likely to rate the creditworthiness of bond issuers more highly than R&I. The disagreement between JCR and R&I over the creditworthiness of issuers causes split bond ratings. Moreover, bonds with multiple split ratings have higher yield spreads.

1141 Mortality and Re-Amputation Rates Following Below Knee Amputation: A Systematic Review and Meta-Analysis

Abstract Aim Below knee amputation (BKA) is undertaken in patients with diabetes or peripheral vascular disease, when limb sparing medical optimisation or vascular interventions are no longer feasible. Mortality and proximal re-amputation rates are poorly defined in the literature. We sought to perform a systematic review to examine mortality and reputation rates across the current literature. Method A systematic search was performed of the MEDLINE (via Pubmed), EMBASE, Cochrane and clinicaltrials.gov databases from inception to August 25th, 2022. Articles were screened by two independent reviewers with conflicts reserved by a third party. Inclusion criteria were all non-traumatic causes of lower limb amputation. Outcomes of interest included Mortality and occurrence of more proximal amputation. Results Studies from 12 countries encompassing a total of 41832 patients were included for analysis. Study dates ranged from 1987 to 2019. Of the total patient number, 38577 (92.2%) were from the USA, with 2599 (6.2%) from Europe and 656 (1.6%) remainder. The mean age at BKA was 70.46 years (Range 62-86). Weighted mortality was 37% (Range 4%-29%) at 1 year, 58% (Range 12% - 60%) at 2 years, 65% (range 19% - 81%) at 5 years and 84% (Range 71-96%) at 10 years. Five studies reported re-amputation rate at any time point (13% Range 1.16- 22%). Conclusions Mortality following BKA is still poor, even in contemporary studies. The few large multicentre studies are US based and in military veteran populations. More robust UK focused studies are needed to accurately inform clinical decision making for patients and clinicians.

Investigating the effect of psychological contract breach on counterproductive work behavior: The mediating role of organizational cynicism

BACKGROUND: The negative consequences of Counterproductive work behaviors (CWBs) include intentional malfeasance that damages an organization or its employees. These include decreased output, increased costs, decreased employee morale and discontent. When CWBs exist, the company’s reputation and employee turnover rates may suffer. OBJECTIVE: The purpose of this study is to increase the current understanding of PCB and CWBs, as well as the mediating function of OC in this relationship, among higher education employees. METHODS: Using IBM SPSS AMOS, the results of the survey were analyzed. RESULTS: PCB is positively correlated with CWB-O and CWB-I, suggesting that employee perspectives on PCB negatively influence their emotions and contribute to unethical business behavior. This study found that OC mediates the relationship between PCBs and CWBs and that uninformed organization behavior causes employees to be more discouraged and angrier and participate in CWB. CONCLUSIONS: Academic administrators must discover salary and benefit inadequacies to give incentives based on accurate performance reports, taking into consideration their bosses’ PC infractions. Therefore, institutions must promote loyalty and belonging to reduce PCB if it is poorly broken. Managers may lessen employee cynicism by stressing organizational support and listening to and rewarding employees.

Corporate pollution and reputational exposure

AbstractWe study the empirical association between corporate pollution and reputational exposure using a sample of 745 U.S. firms from 2007 to 2019 and an ordered probit model. Our results reveal an inverse relationship between chemical emissions and reputational exposure rating, after controlling for various firm attributes. We examine the roles of corporate governance structure and the demographic background of the top management team in the transmission process from polluting chemical emissions to reputation. Further, the negative impact of corporate pollution on reputational exposure rating is much stronger in areas where residents are convinced that climate change is happening. We perform several tests and analyses designed to mitigate endogeneity issues and correct sample bias to ensure the robustness of our findings. Finally, our results suggest that the negative effect is stronger for companies with higher information asymmetry, which indicates the importance of information transparency for firms' credibility.

Augmenting Vehicular Ad Hoc Network Security and Efficiency with Blockchain: A Probabilistic Identification and Malicious Node Mitigation Strategy

This manuscript delineates the development of an avant garde dual-layer blockchain architecture, which has been meticulously engineered to augment the security and operational efficacy of vehicular ad hoc networks (VANETs). VANETs, which are integral to the infrastructure of intelligent transport systems, facilitate the critical exchange of information between vehicular nodes. Despite their significance, these networks confront an array of formidable security vulnerabilities. Our innovative approach, employing a dual blockchain framework—the event chain and the reputation chain—meticulously tracks network activities, thereby significantly enhancing the trustworthiness and integrity of the system. This research presents a transformative dual-layer blockchain architecture, which was conceived to address the intricate security challenges pervasive in VANETs. The architecture pivots on a sophisticated reputation assessment framework, thus leveraging the principles of Bayesian inference and the analytical rigor of historical data to markedly diminish observational errors, as well as elevate the accuracy of reputation evaluations for vehicular nodes. A salient feature of our methodology is the implementation of an attenuation factor, which has been deftly calibrated to modulate the impact of historical behaviors on current reputation scores, thereby ensuring their relevance and alignment with recent vehicular interactions. Additionally, the numerical threshold serves as an indispensable mechanism, thus establishing a definitive criterion for the early identification of potentially malicious activities and enabling the activation of proactive security measures to safeguard the network’s integrity. Empirical validation of our dual-layer blockchain model has yielded a remarkable 86% efficacy in counteracting malevolent behaviors, thus significantly outperforming extant paradigms. These empirical outcomes underscore the model’s potential as a vanguard in the domain of secure and efficient reputation management within VANETs, thereby heralding a substantial advancement in the sphere of intelligent transportation systems.

SOCIAL MEDIA IMPACT ON UNIVERSITY REPUTATION AND ENROLLMENT

This study examines the influence of social media on university reputation and enrolment, specifically focusing on private universities in the Klang Valley. As digital communication continues to permeate every aspect of society, higher education institutions must adapt to remain competitive and attract prospective students. The primary objective of this research is to explore the relationship between a university's online presence and students' enrolment decisions. A quantitative survey method was employed, drawing a representative sample of students from private universities in the Klang Valley. Data were collected using a structured questionnaire that assessed students' perceptions of university reputation, social media usage, and the role of online presence in their enrolment choices. Preliminary findings indicate a positive correlation between an institution's social media presence and both its perceived reputation and enrolment rates. The study highlights the significance of effective social media strategies for private universities, emphasizing the need for institutions to leverage digital platforms to enhance their reputation and attract potential students. Further research is recommended to explore the long-term impact of social media on university performance and student success.

The Role Of Digital Marketing Content Tools In Building Public Trust In Kupang City To Online Shopping

To build consumer trust through online sales, business people can utilize digital marketing content tools, which are a determining factor in building consumer trust. This research aims to describe how the role of digital marketing content tools builds trust in a person to do online shopping. The object of this research is the people of Kupang City who are active in doing online shopping activities, which are studied using qualitative descriptive methods. The results show that in creating consumer trust for online shopping, social media acts as a facilitator through the right aspects, namely, relationship, communication, content, and connection. Search Engine Optimization (SEO) acts as a credible information center because it is able to map the profile of marketers and their products based on other users' experiences and ratings of marketers' reputation, product quality, and service quality. Pay Per Click (PPC) acts as executive sales and video marketing through its visualization power, acting as a source of information as well as an effective teaching tool to illustrate how the product should be used.

CITATION AND REPUTATION RATING OF HISTORIANS

The article is devoted to the analysis of the relationship between the citation of historians and the expertly determined reputation rating. Comparative shortcomings of scientometrics and expert assessments are noted. Using the scale of reputation ratings based on the results of a sociological survey conducted by M. M. Sokolov and the data of the Russian Science Citation Index (RSCI), the author calculates the Spearman rank correlation coefficients between these indicators. At the same time, it turns out that there is no correlation between reputation with a five-year total citation according to the RSCI and citation (both general and five years) according to the core of the RSCI. A weak correlation of reputation with long-term total citation according to the RSCI is found, however, this correlation also becomes insignificant after the exclusion of the unique data of B. N. Mironov.

Auditor reputation and sharia bond ratings: Evidence from Indonesia

Sharia bonds, a segment within the realm of Islamic finance, has demonstrated significant growth over the last decade, emerging as one of the fastest-growing sectors in the industry. This study aimed to analyze the effect of liquidity, profitability, leverage, maturity, and auditor's reputation on sharia bonds ratings. The data collection method used is secondary data sourced from the company's financial statements. The population in this study are companies that issue sharia bonds on the Indonesia Stock Exchange. Sampling using the purposive sampling method with 17 with certain criteria. The data were analyzed using SPSS version 22. The analysis used is ordinal logistic regression analysis. The results showed that liquidity and leverage had no effect on the sharia bond's rating. The profitability, maturity, and reputation of auditors negatively affect the rating of sharia bonds. Sharia-compliant bonds, also known as Sukuk, have a substantial impact on the Islamic finance sector and contribute to the advancement of the global Islamic banking and finance industry. These bonds serve as a means for governments, corporations, and institutions to secure capital while adhering to the principles of Sharia law. They attract investors who prioritize investments that align with their religious beliefs and ethical values.

Block chain based integrated data aggregation and segmentation framework by reputation metrics for mobile adhoc networks

To improve the efficiency and safety of data transmission in MANETs, a blockchain-based integrated data aggregation and segmentation architecture based on reputation metrics are presented. Reputation ratings are given to network nodes based on their historical performance in areas like data aggregation and categorization. Higher-reputation nodes are preferred as data aggregators and segments, whereas nodes with lower reputation scores may be overlooked. Using blockchain technology, we can be confident that node reputation ratings cannot be altered and are thus trustworthy. This allows nodes to authenticate the identity of other nodes before transferring data with them, improving data security in MANETs and helping prevent malevolent nodes from fraudulently claiming a high reputation score. This framework uses blockchain technology and reputation metrics in a decentralized fashion to improve the speed and safety of data transmission in Mobile Ad hoc Networks.

Leading Operational Risk Events For South African Banks: A Reputational Risk Perspective

Banks have been exposed to operational risk for decades. Therefore, there is a strong reason to believe that the exposure to operational risk will only increase in future due to improved transparency as required by regulators as well as the increased reliance on improved technological automation within banks in the digital area. The aim of this article was to identify the leading operational risk events that will most likely lead to reputational risk for South African banks. Primary data were collected from 417 depositors in Gauteng, South Africa, using a self-structured questionnaire where hypothetical operational risk events were employed. External fraud had the highest reputational risk rating, followed by execution and delivery. Six out of the eight events, therefore, were considered severe in terms of the likelihood that depositors will withdraw. Seven out of the eight events, therefore, were considered severe in terms of the percentage of funds that depositors will withdraw. Also, seven out of the eight events were considered severe in terms of the likelihood of creating a negative perception in the minds of depositors. The majority of research in this area has stemmed from developed countries. The significant difference between previous research in the developed regions and South Africa lies in the absence of a deposit insurance scheme in the South African banking sector. Operational risk events that might be severe in developed countries might even be more severe in the South African context without proper banking insurance protecting depositors. Therefore, the novelty of this article lies in the contribution towards empirical evidence from one of the most sophisticated and promising emerging markets by identifying the most severe operational events on the reputational risk for banks.

Understanding the Digital Resilience of Physicians during the COVID-19 Pandemic: An Empirical Study

The COVID-19 pandemic has underscored the urgent need for healthcare entities to develop resilient strategies to cope with disruptions caused by the pandemic. This study focuses on the digital resilience of certified physicians who adopted an online healthcare community (OHC) to acquire patients and conduct telemedicine services during the pandemic. We synthesize the resilience literature and identify two effects of digital resilience—the resistance effect and the recovery effect. We use a proprietary dataset that matches online and offline data sources to study the digital resilience of physicians. A difference-in-differences (DID) analysis shows that physicians who adopted an OHC had strong resistance and recovery effects during the pandemic. Remarkably, after the COVID-19 outbreak, these physicians had 35.0% less reduction in medical consultations in the immediate period and 31.0% more bounce-back in the subsequent period as compared to physicians who did not adopt the OHC. We further analyze the sources of physicians’ digital resilience by distinguishing between new and existing patients from both online and offline channels. Our subgroup analysis shows that, in general, digital resilience is more pronounced when physicians have a higher online reputation rating or have more positive interactions with patients on the OHC platform, providing further support for the mechanisms underlying digital resilience. Our research has significant theoretical and managerial implications beyond the context of the pandemic.

The Economic Value of Blockchain Applications: Early Evidence from Asset-Backed Securities

In this paper, we evaluate the economic value of a blockchain application. In the context of asset-backed securities (ABS) issuance in China, where some ABS are issued with blockchain technology and others are not, we find that the use of blockchain significantly reduces the coupon yield at issuance. Compared with other ABS, those issued using blockchain technology experience a decrease of 31.4 basis points in the yield spread, which corresponds to a relative decrease of 13%. We further document that the effect of blockchain is more pronounced for ABS deals rated by less reputable credit rating agencies and agencies that rely more on issuers for their rating business, for revolving ABS, and for ABS with a larger number of underlying assets. We also find that the use of blockchain can reduce the level of retained interest and number of credit enhancement mechanisms. This paper contributes to the literature by providing a small-sample analysis of the economic value of a blockchain application in financial markets. This paper was accepted by Brian Bushee, accounting. Funding: X. Chen and Q. Cheng acknowledge funding provided by the Lee Kong Chian Professorship at Singapore Management University. This work was supported by Singapore Ministry of Education [Grant MOE-T2EP40120-0005]. Supplemental Material: Data are available at https://doi.org/10.1287/mnsc.2023.4671 .

A Truthful and Reliable Incentive Mechanism for Federated Learning Based on Reputation Mechanism and Reverse Auction

As a distributed machine learning paradigm, federated learning (FL) enables participating clients to share only model gradients instead of local data and achieves the secure sharing of private data. However, the lack of clients’ willingness to participate in FL and the malicious influence of unreliable clients both seriously degrade the performance of FL. The current research on the incentive mechanism of FL lacks the accurate assessment of clients’ truthfulness and reliability, and the incentive mechanism based on untruthful and unreliable clients is unreliable and inefficient. To solve this problem, we propose an incentive mechanism based on the reputation mechanism and reverse auction to achieve a more truthful, more reliable, and more efficient FL. First, we introduce the reputation mechanism to measure clients’ truthfulness and reliability through multiple reputation evaluations and design a reliable client selection scheme. Then the reverse auction is introduced to select the optimal clients that maximize the social surplus while satisfying individual rationality, incentive compatibility, and weak budget balance. Extensive experimental results demonstrate that this incentive mechanism can motivate more clients with high-quality data and high reputations to participate in FL with less cost, which increases the FL tasks’ economic benefit by 31% and improves the accuracy from 0.9356 to 0.9813, and then promote the efficient and stable development of the FL service trading market.

Taking Platform Domestic Work Offline: Using Platform Leakage to Resist Precarity in South Africa’s Domestic Sector

ABSTRACT This article focuses on platform domestic workers’ (PDWs’) experiences and their decision to engage in platform leakage—taking platform domestic work offline. We argue that delving into the types of domestic work choices PDWs make reveals their agency with and through digital platforms in response to precarity on the platform and in the domestic sector. The article demonstrates, through an interpretivist case study that included semi-structured interviews with a sample of PDWs in Cape Town and analysis of documents related to their platform company, that platform leakage is an unavoidable and possibly inherent feature of the platform domestic work model. The findings show that PDWs’ experience of platform domestic work as a form of “gig work” is informed and mainly influenced by unemployment and underemployment in the domestic sector rather than its benefits of flexibility for work life balance and fulfilling unpaid reproductive labour needs. Further, the algorithmic management of the labour process shows that flexibility leaves PDWs in a precarious position but also, paradoxically, creates the need and opportunity to engage in platform leakage. As a result, algorithmic management as a form of control over PDWs’ work performance, and its contingence on personalism for reputational ratings, does not always imply the inescapable power of platform companies. We conclude that further research is needed to deepen our understanding of the employment relationship that emerges from platform leakage, particularly how PDWs experience it and the management of it.

ESG: Credibility behind the scores : The reliability and transparency of ESG ratings

The emergence of sustainability in business has led to a growing number of market players becoming concerned about ESG rating, which includes environmental, social and governance aspects. Investors are also pricing in the scores generated by ESG indicators. The growing interest in ESG data raises the question of the reliability of the scores provided by different ESG rating agencies. This research explores the differences in the methodologies used by the most reputable ESG rating agencies through a content analysis. The inconsistency of ESG scores will be investigated by taking a random sample of companies in eight pre-selected industries and subjecting them to a correlation test. The purpose of this is to highlight the uncertainties associated with ESG ratings and to draw attention to the fact that ensuring the reliability, consistency, and transparency of ESG information remains an unresolved issue and challenge for both decision makers and users.

Improved block chain system for high secured IoT integrated supply chain

The incredibly complex supply chains in today's world face significant problems in terms of accountability and reliability. Blockchain technology could be able to solve these problems by offering a tamper-proof audit trail of supply chain activities & data on a product lifecycle, but it could resolve the issue of information's inherent lack of reliability. Current Reputation systems offer a practical solution to the confidence issue. Moreover, it is based on a small number of observations, lack granularity or mechanization have considerable overhead, current reputational methods are not suitable for blockchain-based supply chain operations. In this research, we present TrustChain, a three-layered system for managing trust that tracks connections between supply chain actors and automatically calculates trust and reputation scores based on those connections using a consortium blockchain with Internet of Things (IoT). Trustchain would be novel because it supports reputation rankings that distinguish between supply chain participants & goods, allowing the assignment of product-specific reputations for the same participant, (a) the reputation design that assesses the performance of commodities and the trustworthiness of entities based on several observations of supply chain events, (b) the use of smart contracts for transparent, impactful, safe, and automated computation of reputation rating, and (c) reputation scores that differentiate between supply chain members and services.

Examining the Influence of Algorithmic Message Personalization on Source Credibility and Reputation

Digital technologies such as AI (Artificial Intelligence) and big data analytics are altering public relations practices such as scanning social media and posting during crises. Crisis scholarship found these practices could potentially yield positive crisis outcomes such as increased reputational measures. However, research has not yet fully outlined the potential risks associated with using these tactics in crisis communication. Guided by situational crisis communication theory (SCCT), this study utilized a 2 (reputation repair strategy: Deny/Apology) x 2 (presence vs. absence of message personalization notification) factorial design experiment to determine how the utilization of algorithmic message personalization might influence reputational and source credibility evaluations during an athlete reputational crisis (ARC). Results revealed that reputation repair strategy selection indirectly influenced stakeholders’ reputation evaluations via source credibility. This relationship was moderated by a notification of personalization. Theoretical and practical insights elucidate how the increased usage of algorithmic-based message personalization influences crisis communication outcomes.

A Blockchain-based Trust and Reputation Model with Dynamic Evaluation Mechanism for IoT

The rapid development of the Internet of Things (IoT) has dramatically increased the number of distributed IoT devices and users. Trust and Reputation Model (TRM) is a well-known technique for improving the security of IoT, which detects malicious attacks by evaluating user behavior. Since traditional distributed TRMs lack secure and reliable data sharing mechanisms, some works have integrated the TRMs into the trusted blockchains. Nevertheless, they have not realized the security requirements of the comprehensive assessment of user behavior and dynamic evaluation of reputation. Therefore, this paper introduces a Blockchain-based Trust and Reputation Model (BTRM), which evaluates user reputation from many aspects and can resist multiple malicious attacks in the distributed network. Second, we propose a novel Dynamic Evaluation Mechanism (DEM), which reduces the number of reputation evaluations without degrading network security and builds a trusting foundation between long-term inactive users and the network. Eventually, we deploy the proposed model DEM-BTRM in a prototype system of Hyperledger Fabric and compare it with existing reputation evaluation methods. The results show that the DEM-BTRM can comprehensively evaluate user behavior and dynamically detect malicious attacks.

HDRS: A Hybrid Reputation System With Dynamic Update Interval for Detecting Malicious Vehicles in VANETs

The reputation-based scheme is a promising solution to prevent malicious behaviors in Vehicular Ad-hoc Networks (VANETs). However, traditional centralized reputation schemes are not suited for distributed networks, while decentralized reputation schemes are vulnerable to malicious vehicles spreading false messages. Most of these schemes assume that the behavior of vehicles can be accurately measured as reputation from the communication, ignoring that malicious vehicles may behave intelligently to avoid being detected. In this paper, we propose a hybrid reputation system (HDRS) which allows vehicles and roadside units (RSU) to complete reputation evaluations separately and provide references to each other. HDRS utilizes a reliability evaluation module to filter out unreliable calculation results and reference records. Furthermore, HDRS includes a dynamic adjustment mechanism for the reputation update interval, employing Analytic Hierarchy Process (AHP) and reliability evaluation results to resist intelligent attacks. Simulation results illustrate that HDRS can maintain a high detection rate and low false-positive rate for detecting malicious vehicles in different environments. Compared with existing schemes, HDRS increases the detection rates of collusion and intelligent attacks by 30% and 16%, respectively.