Multidimensional Reputation Research Articles

Validity of the multidimensional reputation perception scale in private universities

University reputation is the result of the assessments that the stakeholders make of the university, especially the user of the education service, the student. The literature has shown an important impact of reputation on the student’s perception of the university, and it has been related to success, competitiveness, sustainability, stakeholder decision-making and the differential of the value offer. Therefore, its evaluation has been the subject of several studies that seek to measure and assess reputation in higher education to understand how to manage it. This article evaluates the psychometric properties of the reputation scale in students at private universities in Colombia. The methodology used included an adaptation of the scale to the Spanish language, content validity analysis, reliability analysis, exploratory factor analysis and confirmatory factor analysis. The results showed the validity and reliability of the scale and, through the analyses carried out, provided evidence of the scale’s robustness.

Blockchain and trusted reputation assessment-based incentive mechanism for healthcare services

Blockchain-based healthcare IoT technology research enhances security for smart healthcare services such as real-time monitoring and remote disease diagnosis. To incentivize positive behavior among participants within a blockchain-based smart healthcare system, existing efforts employ benefit distribution and reputation assessment methods to enhance performance. Yet, there remains a significant gap in multidimensional assessment strategies and consensus improvements in addressing complex healthcare scenarios. In this paper, we propose a blockchain and trusted reputation assessment-based incentive mechanism for healthcare services (BtRaI). BtRaI provides a realistic and comprehensive reputation assessment with feedback to motivate blockchain consensus node participation, thus effectively defending against malicious behavior in the healthcare service system. Specifically, BtRaI first introduces multiple moderation factors for comprehensive multidimensional reputation assessment and credibly records the assessment results on the blockchain. Then, we propose an improved PBFT algorithm, grounded in the reputation assessment, to augment blockchain consensus efficiency. Finally, BtRaI designs a token-based reward and punishment mechanism to motivate honest participation in the blockchain, inhibit potential misbehavior, and promote enhanced service quality in the healthcare system. Theoretical analysis and simulation experiments conducted across various scenarios demonstrate that BtRaI effectively suppresses malicious attacks in healthcare services, improves blockchain node fault tolerance rates, and achieves blockchain transaction processing efficiency within 0.5 s in a 100-node consortium chain. BtRaI’s reputation assessment and token incentive mechanism, characterized by realistic differentiation granularity and change curves, are well-suited for dynamic and complex healthcare service environments.

A multimodal analytics framework for product sales prediction with the reputation of anchors in live streaming e-commerce

Insufficient sales prediction easily leads to the untimely dispatch of supply and causes inventory problems, resulting in a loss of profits for merchants. Previous sales prediction research was mainly based on traditional e-commerce platforms that cannot be directly applied to live streaming e-commerce, which adds many important elements. The main contribution of our research is the design of a multimodal analytics framework for product sales prediction in live streaming e-commerce. In the proposed framework, we explore the influence of anchor reputation on product sales and innovatively consider both historical and real-time reputation signals. In addition, to better extract valuable information for real-time signals, we propose an A-tiFSR model to extract features from product text and images and design a fine-grained analysis method to mine danmaku data. We conduct our experiments based on a real-world dataset collected from Douyin live streaming. The experimental results demonstrate the effectiveness of the constructed multimodal reputation signals of anchors on product sales prediction. The management implication of our research is that merchants and anchors should pay more attention to their multidimensional reputation. The proposed sales prediction framework can help merchants predict sales more accurately and optimize inventory policy and marketing strategies. This study thus supports the more effective development of live streaming e-commerce markets.

Developing a Measure for Online Shopping Mall Reputation (OSMR)

This study was conducted with the purpose of developing and validating multidimensional reputation criteria for evaluating online shopping malls, which have been growing explosively since the start of the COVID-19 pandemic. A Delphi study was conducted with a group of 31 professionals, and the initial items for online shopping mall reputation were derived from that study. Those items were used to devise a questionnaire that was administered to 531 consumers. Exploratory and confirmatory factor analysis resulted in 17 items based on four factors: reliability, technical skills, customer service, and accessibility. Convergent and discriminant validity were verified between the factors. Finally, structural equation modeling was used to verify the nomological validity of the scale. This online shopping mall reputation scale is expected to provide a standard for companies to effectively manage the reputations of online shopping malls in the future and for consumers to choose online shopping malls they can trust.

Reputation Incongruence and the Preference of Stakeholder: Case of MBA Rankings.

In this paper, we examine the effect of an organization’s multi-dimensional reputation on the external stakeholders’ preference for an organization in the notions of reputation incongruence. We propose that an organization’s incongruent reputation, or large variations among the reputations of each dimension, can be an unfavorable signal to its stakeholders based on theoretical ideas that claim reputation incongruence induces the ambiguity and risk of an organization perceived by stakeholders. We also investigate the moderating effect of reputation incongruence by positing that this incongruence may nullify the influences of reputation dimensions on the preferences of stakeholders. These propositions about reputation incongruence are empirically examined in the context of MBA programs of the global business schools which have three dimensions of reputation—career development, globalization, and research performance.

A Multidimensional Reputation Barometer for Public Agencies: A Validated Instrument.

Reputation is of growing interest for the study of public bureaucracies, but a measurement that can discern between the subdimensions of reputation and is validated on real‐life audiences has remained elusive. The authors deductively build, test, and cross‐validate a survey instrument through two surveys of 2,100 key stakeholders of the European Chemicals Agency, the European Union chemicals regulator. This empirical tool measures an agency's reputation and its building blocks. This scale represents an important contribution to reputation literature, as it allows scholars to distinguish and measure which aspects of reputation public organizations are “known for” and build their claim to authority on, as well as how the profiles of public organizations differ. The authors find that direct stakeholder contact with the agency is necessary for stakeholders to be able to evaluate the separate dimensions of reputation independently.Evidence for Practice This study equips practitioners with a reputation barometer tailored to the public sector. It allows them to measure the reputation of their organization, in a differentiated fashion, among different stakeholder groups.While public organizations increasingly engage in reputation management activities, a potential caveat that emerges from our exercise is that managers might be steering in non‐astute directions. While our study shows that, as for private actors, “performance matters,” procedural and moral aspects also weigh heavily in the eyes of stakeholders when it comes to public regulators.To secure a positive organizational image and the authority crucial for public agencies to operate, the performance management turn in the public sector may need to be supplemented by an enhanced organizational attention to procedural and moral aspects.

A Provenance-Aware Multi-dimensional Reputation System for Online Rating Systems

Online rating systems are widely accepted as means for quality assessment on the web and users increasingly rely on these systems when deciding to purchase an item online. This makes such rating systems frequent targets of attempted manipulation by posting unfair rating scores. Therefore, providing useful, realistic rating scores as well as detecting unfair behavior are both of very high importance. Existing solutions are mostly majority based, also employing temporal analysis and clustering techniques. However, they are still vulnerable to unfair ratings. They also ignore distances between options, the provenance of information, and different dimensions of cast rating scores while computing aggregate rating scores and trustworthiness of users. In this article, we propose a robust iterative algorithm which leverages information in the profile of users and provenance of information, and which takes into account the distance between options to provide both more robust and informative rating scores for items and trustworthiness of users. We also prove convergence of iterative ranking algorithms under very general assumptions, which are satisfied by the algorithm proposed in this article. We have implemented and tested our rating method using both simulated data as well as four real-world datasets from various applications of reputation systems. The experimental results demonstrate that our model provides realistic rating scores even in the presence of a massive amount of unfair ratings and outperforms the well-known ranking algorithms.

Reputation Incongruence and the Preference of Stakeholder: In the Context of MBA Ranking

In this paper, we examine the effect of an organization's multi-dimensional reputation on the external stakeholders' preference for an organization in the notions of reputation incongruence. We propose that an organization's incongruent reputation pattern, or large variations among the reputations of each dimension, can be an unfavorable signal to its stakeholders based on theoretical ideas that claim reputation incongruence induces the ambiguity, the risk, and the unfocused identity perceived by stakeholders. we also investigate the moderating effect of reputation incongruence by positing that this incongruence may nullify the influences of each reputation dimension on the preferences of stakeholders. These propositions about reputation incongruence is empirically examined in the context of MBA programs of the global business schools which have three dimensions of reputation – career development, globalization, and research performance.

SONR: A reliable reputation system of self-organized network

Due to self-organized network without any basic infrastructure and central equipments, it is scalable and fault-tolerant, and we believe that it must be a main direction of next generation communication network and Internet. However, because of the lack of central authority, building trust among all nodes contained in a self-organized network would become more difficult. In this paper, we propose a universal reputation system and make it reliable, lie-tolerant and DoS immunity through multidimensional reputation model, adapted discounting algorithm, recommendation game, secure reputation protocol and fault-tolerant framework. Furthermore, we demonstrate its robustness and high efficiency through example and simulation.

Safeguarding reputation through strategic, integrated and situational crisis communication management

PurposeThe purpose of this paper is to address the often missing theoretical foundation of crisis communication from an integrated perspective on the micro, meso and macro level. Based on the theory of structuration, a systematic, integrative framework is developed for safeguarding organizational legitimization and multidimensional reputation through communication during crisis situations which is applicable both for profit and non‐profit organizations.Design/methodology/approachGidden's theory of structuration was chosen as a basis to develop the integrative model of crisis communication that proposes a communicative impact on reputation on a situative level of message strategies (micro level), an organizational level (meso level) and a societal level (macro level). A well‐organized crisis communication management on all of these levels is seen as the key communicative driver to safeguard long‐term organizational reputation.FindingsThe paper shows that successful crisis communication management must be conceptualized and addressed on distinctive levels of complexity. While on a message level (situative crisis communication) it creates meaning, crisis communication must be seen as management task on an organizational level (integrative crisis communication). However, in order to fully safeguard reputation in the long term and trustworthiness in the short term, crisis communication has also a societal component when addressing moral standards and norms (strategic crisis communication).Research limitations/implicationsThe paper is a conceptual contribution which build the basis of a follow‐up empirical, experimental study where the proposed model is successfully tested.Practical implicationsFor PR managers, this paper gives reasons to conceptualize crisis communication management, not only on a message strategy level, but also to take into consideration the organizational and societal levels.Originality/valueThe paper stands in line with the theoretical discourse of organizational crisis communication. So far, few approaches conceptualize organizational crisis communication thoroughly on an integrated level of different perspectives so that the paper provides an important input, pushing the discussion forward.

REFACING: An autonomic approach to network security based on multidimensional trustworthiness

Several research efforts have recently focused on achieving distributed anomaly detection in an effective way. As a result, new information fusion algorithms and models have been defined and applied in order to correlate information from multiple intrusion detection sensors distributed inside the network. In this field, an approach which is gaining momentum in the international research community relies on the exploitation of the Dempster-Shafer (D-S) theory. Dempster and Shafer have conceived a mathematical theory of evidence based on belief functions and plausible reasoning, which is used to combine separate pieces of information (evidence) to compute the probability of an event. However, the adoption of the D-S theory to improve distributed anomaly detection efficiency generally involves facing some important issues. The most important challenge definitely consists in sorting the uncertainties in the problem into a priori independent items of evidence. We believe that this can be effectively carried out by looking at some of the principles of autonomic computing in a self-adaptive fashion, i.e. by introducing support for self-management, self-configuration and self-optimization functionality. In this paper, we intend to tackle some of the above mentioned issues by proposing the application of the D-S theory to network information fusion. This will be done by proposing a model for a self-management supervising layer exploiting the innovative concept of multidimensional reputation, which we have called REFACING (RElationship-FAmiliarity-Confidence-INteGrity).