919 resultados para REPUTATION


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The chapter reports on the ‘This Is Me’ project, that aimed to help students and the wider public to be aware of the impact that online material, particularly that on the Internet, has on their identity and reputation. The chapter explores practical aspects of Digital Identity, relating to issues such as employability, relationships and even death. For example, understanding the impact a photograph posted on a social networking website might have for different groups of people, ranging from friends or parents to future employers. As part of the ‘This is Me’ project stories were collected from students and others about Digital Identity matters, a grounded methodological approach based on action research was used to establish issues related to Digital Identity particularly relevant to those in academia. Drawing from these issues, resources were developed to help inform and educate people about how they can understand and control their own Digital Identity. A number of these resources are presented here, along with reflections on how they are used and can be adapted.

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This paper explores the idea that stakeholder proximity, that is, how much/little experience a stakeholder has with a focal organization, impacts the extent to which stakeholders rely on strategic group characteristics as an anchor when judging the reputation of higher education institutions. We synthesize theories from psychology (ie, cognitive categorization theory) and management (ie, strategic group theory) to explore how stakeholder proximity may influence the formation of organizational reputation. Specifically, we examine how the proximity of three key stakeholders (N=1,049; prospective students, parents of students and hiring managers of new graduates) influences the perceived strategic character and generalized favorability of three distinct groups of post-secondary institutions (research-intensive universities, teaching-intensive universities and career colleges). Our results suggest that high proximity stakeholders rely less on strategic group characteristics, while reputation at a strategic group level is suggested to have greater influence on stakeholders who have less direct experience of and low proximity to an organization. Interestingly, our findings reveal some consistent differences between perceptions of prospective students and hiring managers that pose important theoretical questions about the role and impact of direct experiences in the reputation-building process, while also suggesting that higher education institutions may benefit significantly from differentiated marketing strategies according to issues of proximity.

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This study proposes a model of how deeply held beliefs, known as ‘social axioms, moderate the interaction between reputation, its causes and consequences with stakeholders. It contributes to the stakeholder relational field of reputation theory by explaining why the same organizational stimuli lead to different individual stakeholder responses. The study provides a shift in reputation research from organizational-level stimuli as the root causes of stakeholder responses to exploring the interaction between individual beliefs and organizational stimuli in determining reputational consequences. Building on a conceptual model that incorporates product/service quality and social responsibility as key reputational dimensions, the authors test empirically for moderating influences, in the form of social axioms, between reputation-related antecedents and consequences, using component-based structural equation modelling (n = 204). In several model paths, significant differences are found between responses of individuals identified as either high or low on social cynicism, fate control and religiosity. The results suggest that stakeholder responses to reputation-related stimuli can be systematically predicted as a function of the interactions between the deeply held beliefs of individuals and these stimuli. The authors offer recommendations on how strategic reputation management can be approached within and across stakeholder groups at a time when firms grapple with effective management of diverse stakeholder expectations.

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Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.

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Trust is one of the most important factors that influence the successful application of network service environments, such as e-commerce, wireless sensor networks, and online social networks. Computation models associated with trust and reputation have been paid special attention in both computer societies and service science in recent years. In this paper, a dynamical computation model of reputation for B2C e-commerce is proposed. Firstly, conceptions associated with trust and reputation are introduced, and the mathematical formula of trust for B2C e-commerce is given. Then a dynamical computation model of reputation is further proposed based on the conception of trust and the relationship between trust and reputation. In the proposed model, classical varying processes of reputation of B2C e-commerce are discussed. Furthermore, the iterative trust and reputation computation models are formulated via a set of difference equations based on the closed-loop feedback mechanism. Finally, a group of numerical simulation experiments are performed to illustrate the proposed model of trust and reputation. Experimental results show that the proposed model is effective in simulating the dynamical processes of trust and reputation for B2C e-commerce.

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Trust and security issues are prevalent in agent societies, where agents are autonomously owned and operated in a networked environment. Nowadays, trust and reputation management is a promising approach to manage them. However, many reputation models su.ered from a major drawback – there is no mechanism to discourage agents from lying information when making a recommendation. Although some works do take into account of this issue, they usually do not penalize an agent for making poor referrals. Worse, some systems actually judge an agents referral reputation based on its service reputation. In situations where this is unacceptable, we need to have a mechanism where agents are not only discouraged from making poor referrals, but are also penalized when doing so. Towards this, we propose a reputation-based trust model that considers an agents referral reputation as a separate entity within the broader sense of an agents reputation. Our objective is not to replace any existing reputation mechanisms, but rather to complement and extend them.

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In a large-scale wide-area system such as the Grid, trust is a prime concern. The current generation of grid information services lack the ability to determine how trustworthy a particular grid service provider or grid customer is likely to be. In this paper, we propose a grid information service with reputation management facility and its underlying algorithm for computing and managing reputation in service-oriented grid computing. Our reputation management service is based on the concept of dynamic trust and reputation adaptation based on community experiences. The working model and functionality offered by the proposed reputation management service is discussed.

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This paper is built on the hypothesis that good governance and reputation are inextricably linked. It takes the governance of performing arts organizations in Queensland, Australia as a case study, and focuses on the role of the nonprofit arts board and its practices of governance and measures of effectiveness. Because of the financial constraints under which arts companies operate, their sustainability relies on audiences and on government or corporate support. The reputation of the company flows from the board's capacity to manage finances, stakeholders and mission. In-depth interviews with board chairs and general managers revealed that strong management systems and rigorous financial reporting are the drivers of good governance. Innovation in product development and artistic excellence are secondary in reputation to these measures. The paper proposes a model of good governance for arts boards.