Reputation Rating Research Articles

Roles of Brand Reputation, Product Information and Discount Rate in Mobile Advertisement

최근 스마트폰의 사용이 확산됨에 따라 기업 정보나 제품 정보를 4대 매체(TV, 라디오, 잡지, 신문)뿐 아니라 모바일 광고를 통해 제공하는 경향이 늘고 있다. 따라서 본 연구에서는 모바일 광고 상황에서 브랜드명성과 제품정보가 소비자의 태도에 미치는 영향에 대해 알아보고, 모바일을 통한 가격할인정보 제공시 할인율이 어떠한 조절효과를 하는지 살펴보고자 한다. 이를 위해 브랜드 명성(높음/낮음)과 제품정보(유/무)가 브랜드 태도와 제품태도에 미치는 영향을 검증하고, 나아가 할인율(높음/낮음)의 조절 역할을 검증하기 위해 2×2×2 실험설계를 사용해 실증적으로 분석하였다. 실증분석 결과, 브랜드 명성이 높을수록 소비자의 브랜드 태도와 제품태도에 긍정적인 영향을 미치는 것으로 조사되었으며, 제품정보가 있을 때 제품태도에만 호의적인 영향을 미치는 것으로 나타났다. 또한 브랜드 명성이 브랜드 태도와 제품태도에 미치는 영향에는 할인율의 조절효과는 모두 유의한 것으로 나타났으나, 제품정보가 브랜드 태도와 제품태도에 미치는 영향에는 할인율의 조절효과가 유의하지 않는 것으로 조사되었다. 브랜드 명성이 높은 기업은 프로모션 모바일 광고 활동을 통해 신규 고객을 창출하고, 고정고객을 위해 1:1 맞춤형 정보를 제공함으로써 브랜드 인지도 및 고객 충성도를 높여 나가야 한다. 모바일 광고시 제품정보 없이 보내는 것보다 구체적인 제품정보와 함께 보내는 것이 효과적이다. 뿐만 아니라 브랜드 명성이 낮은 기업은 높은 할인과 잦은 세일의 광고는 오히려 역효과를 초래할 수 있으므로 자제해야 할 것이다.

Fighting pollution attacks in P2P streaming

In recent years, the demand for multimedia streaming over the Internet is soaring. Due to the lack of a centralized point of administration, Peer-to-Peer (P2P) streaming systems are vulnerable to pollution attacks, in which video segments might be altered by any peer before being shared. Among existing proposals, reputation-based defense mechanisms are the most effective and practical solutions. We performed a measurement study on the effectiveness of this class of solutions. We implemented a framework that allows us to simulate different variations of the reputation rating systems, from the centralized global approaches to the decentralized local approaches, under different parameter settings and pollution models. One key finding is that a centralized reputation system is only effective in static network and in defending against light pollution attacks. In general, a fully distributed reputation system is more suitable for the “real-time” P2P streaming system, since it is better in handling network dynamics and fast in detecting the polluters. Based on this key finding, we propose DRank, a fully distributed rank-based reputation system. Experimental results show that this technique is more flexible and robust in fighting pollution attacks.

PAZARLAMA PERSPEKTİFİNDEN KURUMSAL İTİBARIN ÖLÇÜLMESİ: KARABÜK ÜNİVERSİTESİ’NİN KURUMSAL İTİBARININ ÖĞRENCİLER TARAFINDAN DEĞERLENDİRMELERİNE YÖNELİK BİR UYGULAMA

It’s known that there has been a continuous change in the education services both in Turkey and in the world in recent years. In this sense, it has been observed that the universities have adopted a student-oriented (customer-oriented) service mentality and have been in struggle for providing correct, rapid, trustable and comfortable services. This research seeks to analyze the corporate reputation evaluations of students who are the internal stakeholders of educational organizations, and to find out whether there is a difference between individual evaluations of corporate reputation. In this research, the Corporate Reputation Scale developed by Fombrun and his colleagues has been used. The universe of the research is all the students being educated in Karabük University. While sampling from this universe, the Layered-Sampling method which is one of the sampling methods with probability has been used. For the analysis of the data, SPSS (Statistical Package for the Social Sciences) version 18.0 has been used. Multivariate Analysis of Variance (MANOVA) was applied to the data obtained by questionnaire. MANOVA analysis has been used to check whether there is a difference about the corporate reputation of Karabuk University, considering the demographic and educational information regarding the students.

PAZARLAMA PERSPEKTİFİNDEN KURUMSAL İTİBARIN ÖLÇÜLMESİ: KARABÜK ÜNİVERSİTESİ’NİN KURUMSAL İTİBARININ ÖĞRENCİLER TARAFINDAN DEĞERLENDİRMELERİNE YÖNELİK BİR UYGULAMA

Son yıllarda dünyada ve Türkiye’de eğitim hizmetlerinde sürekli bir değişimin yaşandığı bilinmektedir. Bu anlamda üniversitelerin öğrenci (müşteri) odaklı hizmet anlayışını benimseyerek; doğru, hızlı, güvenilir, konforlu bir hizmet sunma çabası içine girdikleri görülmektedir. Bu araştırma, Karabük Üniversitesi’nin iç paydaşı konumunda olan öğrencilerin üniversitenin kurumsal itibarını tespit etmeye ve bu değerlendirmeler arasında oluşan farkı belirlemeye yönelik betimsel bir çalışmadır. Eğitim örgütlerindeki iç paydaşların kurumsal itibara ilişkin değerlendirmenin tespit edilmesi ve kurumsal itibarla ilgili bir fark olup olmadığının belirlenmesi amacıyla literatür taraması yapılmış ve kurumsal itibarın ölçümü için geliştirilen kurumsal itibar Ölçeği araştırmada kullanılmıştır. Araştırmanın ana kütlesini, Karabük Üniversitesi’nde eğitim gören öğrencilerin tamamıdır. Bu ana kütleden örnekleme seçilirken ihtimalli örnekleme yöntemlerinden biri olan “Katmanlı Örnekleme” yöntemi kullanılmıştır. Seçilen örneklem grubuna daha önce yapılan çalışmalardan yararlanarak oluşturulan anket formu uygulanmaktadır. Verilerin çözümlenmesinde SPSS (Statistical Package for the Social Sciences) paket programının 18.0 sürümünden yararlanılmıştır. Anket yoluyla elde edilen verilere Tek Faktörlü Çoklu Varyans Analizi (MANOVA) uygulanmaktadır. MANOVA analiziyle öğrencilerin demografik ve okul bilgileri dikkate alınarak Karabük Üniversitesi’nin kurumsal itibarını karşılaştırılarak aralarında fark olup olmadığı ölçülmeye çalışılmaktadır

A Review on Trust-Aware and Privacy Preserving Profile Matching System for Personalized User Recommendations in Social networks

is becoming a very important part of social network from the security point of view. In this project, we introduce a framework for handling trust in social networks, which is based on reputation mechanism. The reputation mechanism captures the implicit and explicit connections between the network members, analyses the semantics and dynamics of these connections, and provides personalized user recommendations to the network members. Based on the trust semantics, the system will provide the positive (trustworthy) recommendations and the negative (untrustworthy) recommendations. Along with this our system provides one more interesting mode i.e. public profile matching that preserves privacy on social networks. This profile matching contributes in reputation ratings required for suggestions of friend list. In order to compute the reputation of each member, we adopt several other properties of trust such as, transitivity, personalization, and context, and draw ideas from sociology axioms. Trust is not perfectly transitive in social networks, in that trust decays along the transition path, but it is generally agreed that it can be communicated between people. Along with trust generation percentile of profile matching is also considered for personal recommendation.

Influences of agents with a self-reputation awareness component in an evolutionary spatial IPD game.

Iterated prisoner’s dilemma (IPD) researchers have shown that strong positive reputations plus an efficient reputation evaluation system encourages both sides to pursue long-term collaboration and to avoid falling into mutual defection cycles. In agent-based environments with reliable reputation rating systems, agents interested in maximizing their private interests must show concern for other agents as well as their own self-reputations–an important capability that standard IPD game agents lack. Here we present a novel learning agent model possessing self-reputation awareness. Agents in our proposed model are capable of evaluating self-behaviors based on a mix of public and private interest considerations, and of testing various solutions aimed at meeting social standards. Simulation results indicate multiple outcomes from the addition of a small percentage of self-reputation awareness agents: faster cooperation, faster movement toward stability in an agent society, a higher level of public interest in the agent society, the resolution of common conflicts between public and private interests, and a lower potential for rational individual behavior to transform into irrational group behavior.

Rechazo y victimización al alumnado con necesidad de apoyo educativo en primero de primaria

Title: Rejection and victimization among first graders primary school with education support needs. Abstract: This study aims to analyze the social rejection and victimization experienced by students with educational support needs compared to their peers. Participants were 1351 first graders primary school, 253 of them (18.7%) were labeled by their teachers as students with educational support needs since they had difficulties which required special and additional edu- cational support. The information has been provided by peers (sociometric typology, social reputation and sociometric rating), teachers (social compe- tence) and the students themselves (victimization and perceived compe- tence). The results indicate that students with educational support needs are more rejected, have worse social reputation (more aggressive, more iso- lated and less prosocial) and their teachers consider they are less competent socially. These students report that they are victimized more often than their peers and they perceive themselves as less competent cognitively and less accepted by their peers. This shows a clear characterization of these students as rejected and excluded. Moreover, the aspects that define the profile of rejection are amplified when applied to these students, which highlights the necessity of paying special and careful attention to this risk group.

The Primary Importance of Corporate Social Responsibility and Ethicality in Corporate Reputation: An Empirical Study

AbstractWe examine three assumptions commonly held in the corporate reputation literature: (1) reputation ratings of owners and investors are generally representative of all stakeholders; (2) stakeholders will generally provide a higher reputation rating to firms that emphasize corporate social responsibility versus firms that do not; and (3) profitability is the primary criterion of importance to all stakeholders when rating a firm's reputation. Using an exploratory in‐class exercise, our findings suggest that: (1) there are significant differences among stakeholder groups in their reputation ratings; (2) firms that emphasize corporate social responsibility are not rated more highly across all stakeholder groups; and (3) for all stakeholder groups, the ethicality criterion explained more of the variance in firms' reputation ratings than the profitability criterion.

Effect of Reputation Mechanisms and Ratings Biases on Traders’ Behavior in Online Marketplaces

Rating mechanisms are becoming an essential tool for online shoppers. There have been many reputation mechanisms proposed in the literature that try to mitigate the sometimes adverse effects of strategic behavior of the traders to alter their true reputation scores. At the same time, several studies have shown the presence of bias (often unintentional) in product ratings and their harmful effect on buyers and product sales. To date, there has not been any work done that studies the effect of reputation mechanisms and ratings biases on the behavior of buyers and sellers in an online marketplace. In this article, we use the concept of replicator dynamics to study the evolution of different types of sellers and buyers who use three different reputation mechanisms. We also study the evolution of different types of sellers in the presence of four types of ratings biases. Our results indicate that, over time, buyers gravitate toward using the adaptive model and, in most scenarios, strategic and dishonest sellers are replaced by honest sellers.

Leveraging Social Networks to Combat Collusion in Reputation Systems for Peer-to-Peer Networks

In peer-to-peer networks (P2Ps), many autonomous peers without preexisting trust relationships share resources with each other. Due to their open environment, the P2Ps usually employ reputation systems to provide guidance in selecting trustworthy resource providers for high reliability and security; however, node collusion impairs the effectiveness of reputation systems in trustworthy node selection. Although some reputation systems have certain mechanisms to counter collusion, the effectiveness of the mechanisms is not sufficiently high. In this paper, we leverage social networks to enhance the capability of reputation systems in combating collusion. We first analyzed real trace of the reputation system in the Overstock online auction platform, which incorporates a social network. The analysis reveals the impact of the social network on user purchasing and reputation rating patterns. We, thus, identified suspicious collusion behavior patterns and propose a social network-based mechanism, SocialTrust, to counter collusion. SocialTrust adaptively adjusts the weight of ratings based on the social distance and interest relationship between peers. Experiment results show that SocialTrust can significantly strengthen the capability of current reputation systems in combating collusion.

Measuring Organizational Capacity for Integrated Treatment

Behavioral health program leaders, practitioners, policy makers, and researchers have a keen interest in understanding how best to implement and sustain evidence-based practices. Among the most important determinants of successful implementation are organizational factors, such as an organization’s structure, climate, resources, and leadership. Yet despite the recognition that organizational characteristics matter, the field remains largely in a prescientific stage of development. For example, experienced leaders believe they know, by reputation, which are the most competent service agencies in their state or region, and further, which ones are most competent in implementing innovative practices. But how accurate are these beliefs? Are reputational ratings predictive of success in implementing a new program? Over a half-century ago, Meehl (1954) showed that clinical judgment was often useless in predicting client outcome. In nearly every study, actuarial calculation based on objective indicators was a better predictor of outcome than clinical prediction. Thus global clinical judgments, whether they be about predicting improvement in client outcomes or readiness of an organization to change are poorer guides to action than are objective scales measuring discrete aspects of performance. But the development and validation of scales requires hard work, and much has yet to be done at the organizational level in integrated treatment.

On the drivers of corporate social responsibility in banks: evidence from an ethical rating model

The purpose of our paper is the construction of a multidimensional ethical rating model, based on many items that represent the most significant Corporate Social Responsibility drivers of the banks. The items considered have been drawn from literature and from corporate reporting and websites of banks and then subjected to content analysis. The model, applied to a sample of European banks, was divided into four areas of analysis (Disclosure; Organization and Management; Offer of Socially Responsible Instruments; International Agreements, Certifications and Indexes) to identify the most frequent ethical conducts and the ones that require improvement measures. Our research highlights that banks pay more attention to the offer of socially responsible instruments and organization and management issues. On the contrary, the banks examined could enhance their socially responsible approach by reinforcing disclosure on Corporate Social Responsibility. In particular, there is a modest orientation towards disclosure on the basis of the triple bottom-line approach. Finally, as for international agreements, certifications and indexes, improvement actions are still needed: there are still many international principles which have not yet been adhered to and an increase in requests for more ethical/quality certifications and inclusion in reputational ratings would be desirable.

Examining the Role of Observer Personality on the Predictive Validity of Personality Ratings

Drawing on Hogan’s Socioanalytic Theory (Hogan, 1996) and Funder’s Realistic Accuracy Model (Funder, 1995), I investigate key sources of variance in the predictive validity of reputational personality ratings. More specifically, I explore how characteristics of the individuals providing observer ratings of personality impact the relative and incremental predictive validities of these reputational ratings. Results of a field study indicate that in terms of predicting job performance, reputational ratings of personality have the potential to capture both higher relative predictive validities and higher incremental predictive validities over identity (i.e., self) ratings. However, the extent to which reputational ratings outperform identity ratings depends on personality characteristics of the observer such that relative and incremental predictive validities are highest when observers score high on measures of conscientious and openness.

Employee Reputation: What We Know and Where We are Headed

An employee�s reputation plays an important role in their experiences in the workplace. Indeed, it can shape treatment by their supervisors and coworkers (Johnson, Erez, Kiker, & Motowildo, 2002; Liu, Ferris, Zinko, Perrew�, Weitz, & Xu, 2007) and open doors for employment and advancement opportunities (Rosen, Cochran, & Muser, 1990; Zinko, Ferris, Humphrey, Meyer, & Amie, 2012). Although the general landscape of this literature has been established � including the definition of reputation and its basic nomological network � many questions remain. The purpose of this symposium is to explore various directions for future research on employee reputation. The four papers that comprise the symposium ask very different but fruitful questions about the nature of reputation, its operationalization, and its measurement. First, does the traditional conceptualization of employee (individual-level) reputation operate similarly at different levels (e.g., group and organizational)? Second, what are the implications of a negative reputation, and can they be beneficial? Third, are there differences in reputation ratings by source (e.g., self vs. other)? Lastly, can reputation be assessed more specifically (e.g., a reputation for being lazy or kind) and as a result of specific actions of employees (e.g., work behaviors or non-work behaviors)? The Role of Reputation in the Organizational Sciences: A Multi-level Review and Construct Assessment Presenter: Gerald R. Ferris; Florida State U. Presenter: B. Parker Ellen III; Florida State U. Presenter: John Nolan Harris; Florida State U. Presenter: Arthur Martinez; Illinois State U. A Means to an End: The Positive Side of a Negative Reputation Presenter: Robert Zinko; U. of Newcastle, Australia Presenter: Angela Hall; Michigan State U. Presenter: Nathan Elmore; U. of Newcastle, Australia The Effect of Introversion on the Relationship Between Self- and Other-reports of Reputation Presenter: Mary Dana Laird; The U. of Tulsa Presenter: James J. Zboja; The U. of Tulsa Workplace Reputation of Volunteers Presenter: Jessica Rodell; U. of Georgia Presenter: John Lynch; U. of Georgia

A Collaborative Reputation System for e-Learning Content

Reputation systems aggregate users' feedback after the completion of a transaction and compute the of products, services, or providers, which can assist other users in decision-making in the future. With the rapid growth of online e-Learning content providing services, a suitable reputation system for more credible e-Learning content delivery has become important and is essential if educational content providers are to remain competitive. Most existing reputation systems focus on generating ratings only for user reputation; they fail to consider the reputations of products or services(item reputation). However, it is essential for B2C e-Learning services to have a reliable reputation rating mechanism for items since they offer guidance for decision-making by presenting the ranks or ratings of e-Learning content items. To overcome this problem, we propose a novel collaborative filtering based reputation rating method. Collaborative filtering, one of the most successful recommendation methods, can be used to improve a reputation system. In this method, dual information sources are formed with groups of co-oriented users and expert users and to adapt it to the reputation rating mechanism. We have evaluated its performance experimentally by comparing various reputation systems.

The Impact of CSR Practices on Organizational Attractiveness: HRM Implications

One of the key challenges for human resource managers nowadays is talent management. Attracting talented individuals to organizations is an important source for firm competitive advantage. Using a sample of 778 consumers of 16 different firms, we tested whether perceptions of corporate social responsibility practices (internal and external) influence perceptions of organizational attractiveness. We further tested if this relationship would be mediated by ratings of organizational reputation. Our results suggest that perceptions of internal CSR practices are directly related to both organizational attractiveness and firm reputation however, perceptions of external CSR practices was only directed related to organizational reputation. The relationship between perceptions of external CSR practices and organizational attractiveness was fully mediated by ratings in organizational reputation. Theoretical and practical implications for HR managers and CSR managers conclude the article.

Learning from other buyers: The effect of purchase history records in online marketplaces

In this study, we investigate how a new element of information – historical sales records – affects buyers' behavior in online marketplaces.33We use “purchase history records” and “historical sales records” interchangeably; the former term is used on eBay's list pages and the latter is used on Taobao's list pages. A historical sales record is the previous sales information of a seller for a certain product. It is provided on an online shop's item description page and managed by the online transaction platform. It is more pertinent to the item at hand than the seller's overall feedback score or reputation rating, as the latter can be accumulated by selling many other items. Online buyers can use the information in historical sales records to learn from other buyers' purchasing behaviors. We propose that a seller's historical sales records for a certain item will directly affect the potential buyer's perception of the item's quality, making a purchase more likely when an item has desirable historical sales records. We use two approaches to test our hypotheses. First, we analyze purchase data from global.eBay.com and Taobao.com and find that across a variety of products sampled, after controlling for price and a number of seller characteristics such as feedback scores/ratings, higher historical sales in a 30-day period are consistently associated with higher sales in the following seven days. This indicates that buyers are learning from other buyers. The second approach is a more direct examination of buyer behavior in which we run an experiment using an eye-tracking system to measure what information purchasers pay attention to on a website. We find that on the search result page, the area containing the historical sales record receives the longest fixation length from the participants, and the participants who look at the historical sales record longer tend to choose the seller with the highest historical sales.

Reputation and Uncertainty in Online Markets: An Experimental Study

This paper employs a modified investment game to study how online reputation ratings are assigned, and thus how electronic reputations are formed in transactions where buyers and sellers interact anonymously. Of particular interest are the important questions of how online reputations evolve and how specific reputation information is interpreted by market participants. We vary the level of uncertainty in the transaction environment, and measure the effects of this manipulation on buyers' trust and their subsequent rating behaviors. We distinguish between a reputation mechanism and specific reputation information, finding the former has an association with the overall decision of whether to transact in the marketplace, while the latter shows significance in purchase decisions regarding specific sellers. We also find that aggregate reputation information is weighted differently than singular reputation information. Finally, we show that when reputations are increasingly noisy, buyers are less likely to react negatively to poor ratings and are more likely to give sellers the benefit of the doubt when seemingly uncooperative outcomes occur.

Mapping language ideologies in multi-ethnic urban Europe: the case of Parisian French

Although the modern multicultural European metropolis has brought previously disparate groups into close contact, little research has focused on the effect of these shifting demographic patterns on language attitudes and ideologies. This is probably due to the sensitive nature of issues relating to immigration which may evoke contexts of socio-economic stratification, ethnic strife and even urban violence. To mitigate this sensitivity, this study examines socio-geographic representations of linguistic prestige, not attitudes towards speakers, in the Paris region. In a web-based survey, 136 Parisians evaluated the desirability, reputation and linguistic correctness of 21 cities in the Paris region. Responses indicate that perceptions of linguistic prestige are most closely connected to cities’ reputations, suggesting a close relationship between standard language ideology and spatial stereotypes. Five cities received the lowest reputation and linguistic correctness ratings and, thus, probably constitute exemplars of the poor, multi-ethnic Parisian suburbs popularly identified with a Parisian urban youth vernacular. Evaluations of the French of these five cities are shown to be related to subjects’ age, gender, socio-economic status and level of anti-immigrant bias. This study indicates that socio-geographic segregation may be driving perceptions of sociolinguistic stratification in the Paris region.

Social Network Based Reputation Computation and Document Classification

We develop two social network based algorithms that automatically com- pute author reputation from a collection of textual documents. We first extract keyword reference behaviors of the authors to construct a social network, which represents re- lationships among the authors in terms of information reference behavior .W ith this network, we apply the two algorithms: the first computes each author's reputation value considering only direct reference and the second utilizes indirect reference recursively. We compare the reputation values computed by the two algorithms and reputation ratings given by a human domain expert. We further evaluate the algorithms in email categorization tasks by comparing them with machine learning techniques. Finally, we analyse the social network through a community detection algorithm and other analy- sis techniques. We observed several interesting phenomena including the network being scale-free and having a negative assortativity.