Reputation Management Mechanism Research Articles

STRATEGIC MANAGEMENT OF THE MARKET CAPITALIZATION OF CORPORATE AGRARIAN ENTERPRISES BASED ON ESG-PRINCIPLES

Introduction. The strategy of managing the market capitalization of a corporate agricultural enterprise requires the use of the concept of sustainable development and corporate social responsibility, social and ethical marketing, reputation management and other mechanisms and tools focused not only on maximizing profits and market value, but also on long-term sustainable development. Methods. The following methods have been used during the study: abstract-logical and synthesis (theoretical generalizations, conclusions); generalization (determination of the principles and mechanisms of ESG influence on the market capitalization of corporate agricultural enterprises); monographic (study of the experience of implementing the principles of sustainable development and ESG concepts in the strategic management of the market capitalization of corporate agricultural enterprises); graphing (schematic presentation of individual systematized research results). Results. The basic principles and mechanisms of ESG influence on the market capitalization of corporate agricultural enterprises have been summarized. It has been shown that the implementation of ESG policies in business strategies has a significant impact on the market capitalization of public corporate agricultural enterprises. ESG investments as a tool for increasing the market capitalization of an agricultural enterprise should be aimed at using reputation management and obtaining benefits from creating a high-quality corporate image and business reputation. It has been confirmed that the transition to ESG principles and their observance in agribusiness ensures the satisfaction of the interests of all stakeholder groups and contributes to the investment attractiveness of enterprises. Discussion. Prospects for further research are the harmonization of international standards of ESG reporting, rating of corporate agricultural enterprises based on the results of the implementation their ESG-oriented strategies in order to improve the efficiency of managing their market capitalization and investment attractiveness. Keywords: strategic financial management, market capitalization, ESG-concept, corporate agricultural enterprise, sustainable development.

Blockchain-Enabled Conditional Decentralized Vehicular Crowdsensing System

The rapid growth of connected and autonomous vehicles (CAVs) shows an urgent demand for driving and transportation-related data, which gives rise to vehicular crowdsensing systems (VCSs). Nevertheless, the existing centralized VCS framework mainly faces the system reliability problem while the decentralized one cannot satisfy the management flexibility. In addition, when the privacy preservation scheme that prevents information leakage encounters the user selection scheme that desires detailed information of participants, how to balance this seemingly irreconcilable contradiction is inevitable for VCS. To remedy that, we take the first research attempt and explore the balance point between the system management, privacy preservation, and quality of experience (QoE) of participants. By fully exploiting the characters of participating entities, a blockchain-enabled conditional decentralized VCS is proposed in this paper. Firstly, we propose a privacy-preserving scheme where the zk-SNARK proof combines with the mixed-task smart contract to guarantee the interaction process will not reveal any private information of participants. Secondly, we propose an efficient reputation management mechanism that renders certain the participants can get a satisfactory QoE even under the condition that the private information of users is secured. And also, the malicious operations in the system will be effectively supervised. Theoretical analysis and extensive simulations demonstrate the security and efficiency properties of privacy preservation and indicate the effectiveness of reputation management.

Meningkatkan Kepercayaan Publik dan Reputasi Dewan Perwakilan Rakyat Melalui Program Parlemen Remaja

Many surveys show that the level of public trust in the Indonesian parliament (DPR) often occupies the lowest position compared to other government institutions. This study aims the efforts of the PR Bureau of the DPR in organizing the Parlemen Remaja (the Youth Parliament) program as an attempt to improve public trust and reputation through political education for the younger generation, to understand better the reputation management and relationship management mechanisms applied by PR Bureau of the DPR. The research method using an evaluation was carried out using the reputation management theory and relationships management theory of political public relations. Data collection techniques were carried out through literature study and in-depth interviews. The findings indicate that the Youth Parliament program is considered helpful in increasing student interest in politics, providing opportunities to interact with the community, and can improve their perception of the DPR. Moreover, the students can be used as brand ambassadors for the DPR by endorsing the Indonesian parliament on social media and doing word of mouth in their social milieu. It can be concluded that the program is fruitful in increasing positive perceptions and bridging the relationship between the DPR and its key stakeholders, but it is not significant enough to increase public trust and the institution's reputation.

An Incentive Mechanism for Mobile Crowd Sensing in Vehicular Ad Hoc Networks

In the mobile crowdsensing of vehicular ad hoc networks (VANETs), in order to improve the amount of data collection, an effective method to attract a large number of vehicles is needed. Therefore, the incentive mechanism plays a dominant role in the mobile crowdsensing of vehicular ad hoc networks. In addition, the behavior of providing malicious data by vehicles as data collectors will have a huge negative impact on the whole collection process. Therefore, participants need to be encouraged to provide data honestly to obtain more available data. In order to increase data collection and improve the availability of collected data, this paper proposes an incentive mechanism for mobile crowdsensing in vehicular ad hoc networks named V-IMCS. Specifically, the Stackelberg game model, Lloyd’s clustering algorithm and reputation management mechanism are used to balance the competitive relationship between participants and process the data according to the priority order, so as to improve the amount of data collection and encourage participants to honestly provide data to obtain more available data. In addition, the effectiveness of the proposed mechanism is verified by a series of simulations. The simulation results show that the amount of available data is significantly higher than the existing incentive mechanism while improving the amount of data collection.

Reservation Service: Trusted Relay Selection for Edge Computing Services in Vehicular Networks

Driven by the ever-increasing demands of vehicular services, edge computing has become a promising paradigm to facilitate edge services in vehicular networks by using edge computing devices (ECDs). To enhance the service experience, we develop a reservation service framework, where the reservation service request of a vehicle needs to be relayed to one of the ECDs which is ahead of its driving direction. However, due to the various behaviors of vehicles, not all the vehicles are trustworthy and willing to join in the service request relay process. Therefore, how to exploit the cooperation between ECDs and vehicles to relay the service request by considering the dynamic traffic status and the behaviors of vehicles becomes a challenge. As an effort to address this problem, we propose a trusted relay selection scheme for edge services to facilitate the proposed reservation service framework. Specifically, we first design the request relay mechanism based on the dynamic traffic status to guarantee the efficiency of the relay process. Then, the reputation management mechanism is presented to constrain the behaviors of vehicles, where a vehicle with high reputation value can enjoy the price discount for computing service. Based on the designed request relay and reputation management mechanisms, a reputation-based auction approach is then proposed to select relay vehicles (RVs) to reduce the cost of the relay service. Simulation results show that the proposed reservation service framework can manage vehicles efficiently and lead to the lowest cost for the relay services compared with the conventional schemes.

How different strengths of ties impact project performance in megaprojects: the mediating role of trust

PurposeThis study aims to investigate the relationships between the different strengths of ties (strong ties and weak ties), types of trust and project performance in megaprojects.Design/methodology/approachA questionnaire survey was conducted with various experts and professionals involved in megaprojects, and 350 valid responses were received. Data was analyzed by means of structural equation modeling.FindingsThe results show that both strong ties and weak ties have positive impacts on trust in megaprojects, but weak ties have a more significant positive effect than do strong ties. Unexpectedly, the introduction of interorganizational trust significantly weakens the effect of the strength of ties on project performance. The indirect influence of the strength of ties on performance has different paths. Weak ties have an indirect effect via calculative trust and relational trust. However, in a strong ties network, inferior stakeholders lack the information necessary to complete a megaproject, and they believe that calculative trust will not promote project performance until the megaproject is successfully delivered. Thus, the effect of calculative trust on project performance is not significant.Research limitations/implicationsThese findings provide evidence in regard to strength of ties governance being a part of the effective strategy in improving megaprojects’ performance. It also demonstrates the mediating function of trust and advances the current understandings of the underlying mechanism of the strength of ties on project performance, thus providing implications for researchers and practitioners. However, this study has some limitations. For example, the strength of ties and trust between organizations are a dynamic process in megaprojects. This study does not conduct in-depth analysis of the evolution mechanism and investigate the different levels of trust at different stages of the megaproject. Future research can be guided by these directions.Originality/valueThe main contribution of this study is fourfold. First, this study enriches the literature on strength of ties by accentuating the roles of trust in megaproject context. Second, this study contributes to the theoretical development of a conceptual model for explaining the interrelationships among strength of ties, types of trust and project performance. Third, this study responds to the call “which dimension (i.e. strong ties or weak ties) is more influential” by exploring the direct and indirect effects of strength of ties on project performance. Finally, this study breaks through the limitation of traditional cognition that megaproject management can be met by relying on rigid contracts. In other words, trust can supplement the weakness of rigid contract by forming contract flexibility with different strength of ties. Meanwhile, the specific strategies to establish and maintain trust are given, such as building information model (BIM) collaboration platform and reputation management mechanism.

Secure and efficient multi-tenant database management system for cloud computing environment

Multi-tenancy is one of the important feature of cloud computing environment. Multi-tenant database system in SaaS (Software as a Service) deployed in cloud infrastructure has gained wide interest in both academics as well as industries, as it provides scalability and economic benefit for both cloud service provider and end users. However, low trust on the rented computational resources prevents users from utilizing the same. Further, in multitenant systems the communication channels and other computational resources are shared, inducing privacy and security issues. As tenants are anonymous in nature, a user may not find a trustworthy co-tenant and tenants depend on cloud service provider to assign trustworthy co-tenants. However, cloud service provider allows maximum co-tenancy irrespective of the behaviors of tenants to maximize resource utilization. Of late, a number of approaches have been presented based on reputation management mechanism to identify good and malicious tenants. However, state-of-art models are not efficient when behavior of malicious tenant changes rapidly. In order to overcome the said research challenge, this work presents a secure and efficient multi-tenant database management system (SEMTDBMS) for cloud computing environment. SEMTDBMS first analyzes security requirement of tenant workers and suggests a secureness weight metric for selection of tenant worker. Subsequently, a novel workload scheduler for scheduling workload among tenants has been presented. Experiments are conducted considering OLTP benchmark such as TPC-C and Yahoo! Cloud Serving Benchmark (YCSB) benchmark with and without security compliances. SEMTDBMS show significant performance improvement in terms of latency and throughput over state-of-art model.

A Secure Content Sharing Scheme Based on Blockchain in Vehicular Named Data Networks

Vehicular named data networking (VNDN) has recently emerged as a novel paradigm to facilitate content-centric data sharing for Internet of Vehicles. However, an information holder can spread fake data to clients for malicious purposes, which may affect the driving decision of the recipient, or even worse, cause traffic congestion and accidents. In this article, we build a data-sharing system that consists of a double-layer blockchain. The nodes at the bottom layer request for service by announcing their requirements in the NDN paradigm. For the upper layer, the nodes submit their demands and supplies to the nearest roadside unit for further matching. We model the balance between the demand and supply as a matching game. To encourage nodes to provide positive services, a reputation management mechanism that combines negative and positive transaction records is proposed. Simulation results verify the validity of our system, and the data-sharing mechanism fosters a secure information interaction in the VNDN.

Robust reputation management mechanism in cooperative spectrum sensing

Cooperative spectrum sensing (CSS) is the key function of cognitive radio system to identify the available spectrum. However, cooperative paradigms are prone to be threatened by Byzantine attack, and the effect of extensive Byzantine mitigation methods adopting the global decision (GD) as the reputation management mechanism (RMM) is not satisfactory in some instance. In this Letter, according to the delivery of the transmitted data, the authors propose a data transmission status (DTS) in CSS, which is easily implemented without unrealistic assumptions about Byzantine attack. Compared with the GD, simulation results show that the DTS is a robust RMM and provides better CSS performance, even functions well in the blind scenario.

A Robust Reputation Management Mechanism in the Federated Cloud

In the Infrastructure as a Service (IaaS) paradigm of cloud computing, computational resources are available for rent. Although it offers a cost efficient solution to virtual network requirements, low trust on the rented computational resources prevents users from using it. To reduce the cost, computational resources are shared, i.e., there exists multi-tenancy. As the communication channels and other computational resources are shared, it creates security and privacy issues. A user may not identify a trustworthy co-tenant as the users are anonymous. The user depends on the Cloud Provider (CP) to assign trustworthy co-tenants. But, it is in the CP's interest that it gets maximum utilization of its resources. Hence, it allows maximum co-tenancy irrespective of the behaviours of users. In this paper, we propose a robust reputation management mechanism that encourages the CPs in a federated cloud to differentiate between good and malicious users and assign resources in such a way that they do not share resources. We show the correctness and the efficiency of the proposed reputation management system using analytical and experimental analysis.

A Self-Controllable and Balanced Data Sharing Model

The widespread acceptance of data sharing has promoted the relevant research in both academia and industry. “Data sharing” is the process of interchanging data among multiple data sources in a controllable access manner. Any such system provides common functionality of storage and access; however, there are prominent differences in non-functionalities, such as self-control, transparency, cost-effectiveness, incentive, and auditing, which make data sharing in a dilemma. In this paper, we propose a distributed data sharing model based on blockchain technology: data owner publishes data with an additional control policy; data consumer inquires data with an access request; and consensus nodes evaluate the request and make decisions. After formalizing the system model, we discuss the procedure of data sharing, reputation management, and proposed solution. With the access control policy, price compensation, and reputation management mechanism, we achieve self-control and price balance in sharing data. Our model is equally a closed-loop control system that acts as a regulator of supervising its participants. The analyses and experimental results show, comparing with the existing sharing systems, that our model is practical and can spur agents to participate actively in sharing data.

A reputation management mechanism that incorporates accountability in online ratings

Online reputation has a strong impact on the success of a seller in an e-marketplace. Also, buyers use it to choose an appropriate seller among a set of alternatives. The standard practice of determining the reputation of a seller is the aggregation of the feedbacks or the ratings reported by its buyers. Such a model of reputation formulation is vulnerable to misleading and unfair feedbacks. A seller may collude with a set of buyers to report good feedbacks while the quality of its product is poor. Also the buyers can report unfair feedbacks being irrational, malicious or competitors. A robust reputation management mechanism is the one which can not be manipulated by these unfair feedbacks. The existing reputation management models are either reactive or proactive. The reactive solutions intend to identify the unfair feedbacks and the proactive solutions propose incentive to the buyers to encourage them to report fair feedbacks. In this paper, we propose an incentive system that encourages the buyers to report fair feedbacks. We associate a buyer’s reputation with a seller’s reputation if the buyer has expressed its feedback about the seller. If the reputation of the seller decreases then the reputation of all buyers who had endorsed it (provided positive feedbacks) also decreases and vice versa. This means a buyer risks its own reputation by providing the feedback about a seller. In this paper, we show that such a mechanism is incentive compatible, i.e., it encourages the buyers to provide fair feedbacks. Using analytical and experimental analysis, we show the correctness of this reputation management system.

Multi agent system-based dynamic trust calculation model and credit management mechanism of online trading

AbstractNow all kinds of malicious acts appear in C2C online auctions, particularly the phenomenon of trust lack and credit fraud is very outstanding. Therefore, how to build an effective trust model has become a burning problem. Based on analyzing limitations of the existing online trust transaction mechanism, and according to characteristics (such as dynamic, innominate and suppositional) of online transaction trust problem, the article proposes a dynamic trust calculation model and reputation management mechanism of online trading based on multi-Agent system. The model consists of three parts. The first part is the trust of user domain, to put importance on the influence on current trust by recent credibility status, to motivate users to adopt an agreed cooperative strategy. The second part is the weighted average of reputation feedback score. The weighted part mainly considers the trust from the reputation feedback score person (the credibility of the feedback score), the value of the transaction (to ...

A Novel Reputation Management Mechanism with Forgiveness in P2P File Sharing Networks

In peer-to-peer (P2P) file sharing networks, it is common practice to manage each peer using reputation systems. A reputation system systematically tracks the reputation of each peer and punishes peers for malicious behaviors (like uploading bad file, or virus, etc). However, current reputation systems could hurt the normal peers, since they might occasionally make mistakes. Therefore, in this paper, we introduce forgiveness mechanism into the EigenTrust reputation system to reduce such malicious treatments and give them opportunities to gain reputation back. Particularly, we take four motivations (the severity of current offence, the frequency of offences, the compensation and the reciprocity of the offender) into consideration to measure forgiveness. The simulation work shows that the forgiveness model can repair the direct trust breakdown caused by unintentional mistakes and lead to less invalid downloads, which improves the performance of P2P file sharing systems.

A Hierarchical Reputation Evidence Decision System in VANETs

In VANETs, users are rational, independent, and selfish. Stimulation-based reputation management system is critical for them to avoid selfishness and promote network performance in large-scale VANETs. The current reputation mechanisms produce some problems, for example, overfull energy consumptions, confused collusion, and misreport. In order to detect selfish and collusive behaviors accurately and quickly, we propose a dynamic three-layer reputation evidence decision and management mechanism, which combine with Dempster-Shafer evidence integration mechanism to distinguish selfish nodes. In particular, the system helps in collusion avoidance through reporting falsified reputation evidences of colluders. In addition, we borrow ideas from Weber-Fechner’s law and design an adaptive reputation evidence gathering cycle for prolonging the lifetime of detector and overwhelming frequent polling for reputation evidences. The simulation results demonstrate that REDS has higher detection speed for selfish nodes and collusive observers and less network traffic of gathering reputations.

网络在线交易动态信任计算模型与信誉管理机制

At present, all kinds of malicious acts appear in C2C online auctions, particularly the phenomenon of trust lack and fraud is very outstanding. Therefore, how to build an effective trust model has become a burning problem. Based on analyzing limitations of the existing online trust transaction mechanism, and according to characteristics (such as dynamic, innominate and suppositional) of online transaction trust problem, the article proposes a dynamic trust calculation model and reputation management mechanism of online trading based on multi-Agent system. The model consists of three parts. The first part is the trust of user domain, to put importance on the influence on current trust by recent credibility status, to motivate users to adopt a agreed cooperative strategy. The second part is the weighted average of reputation feedback score. The weighted part mainly considers the trust from the reputation feedback score person (the credibility of the feedback score), the value of the transaction (to prevent the credit squeeze), temporal discounted (guard against the fluctuations of the credibility) and other factors. The third part is to give a weighting on the community contribution, according to the action taken by a user to the other members of the community in a time domain, to increase or decrease the user's trust to isolate the feedback submission of the credibility and punish the fraud. The paper builds the fraud limiting mechanism which combine the prevention beforehand, coordination in the event and punishment afterwards. The mechanism makes the online transaction safe. Theoretic proof and experimental verification indicate the following three problems can be solved effectively: 1) solving the problem which is difficult to prevent and is that speculative user accumulates the little trusts and squeeze on the large trading; 2) preventing members from cheating by false trading or personation; 3) reducing the arbitration workload of the online business platform.

Review of threats on trust and reputation models

Purpose – As the number of available services increases on the web, it becomes greatly vital in service-oriented computing to discover a trustworthy service for a service composition so as to best-fit business requirements. However, some dishonest service providers may advertise more than what they can offer and cause a great loss to users. In the last few years, trust and reputation management over web service selection mechanism becomes an emerging way of dealing with security deficiencies which are inherent in web services environment. The purpose of this paper is to review the security threats carefully and expect that the results serve as a reference guide for designing the robust trust and reputation management mechanisms. Design/methodology/approach – Based on the published literature, the paper reviews and categorizes the most critical and important security threats that apply to trust and reputation models. Findings – A detailed review and a dedicated taxonomy table are derived. As emphasized earlier, they could serve as the most important guideline for design of trust and reputation mechanisms. Originality/value – The papers work contributes to: first, understand in details what kind of security threats may cause damage to trust and reputation management mechanisms for web services selection; and second, categorize these complex security threats and then assist in planning the defense mechanisms.

Subjectivity handling of ratings for Trust and Reputation systems: an Abductive Reasoning Approach

The Internet form a globally distributed network that provides a ubiquitous medium for interaction, the exchange of ideas, and commerce. The web is pervading our everyday lives in ways that were unimaginable even ten years ago. The evolving use of the web requires robust and efficient trust and reputation management mechanisms. During the past decade, online trust and reputation systems have provided cogent answers to emerging challenges in the global computing infrastructures relating to computer and network security, electronic commerce, virtual enterprises, social networks and cloud computing. The goal of these systems in such global computing infrastructures is to allow entities to reason about the trustworthiness of other entities and to make autonomous decisions on the basis of trust. This requires the development of computational trust models that enable entities to reason about trust and to verify the properties of a particular interaction. The robustness of these mechanisms, which is one of the critical factors for the success of this technology, is currently not being sufficiently addressed. The global computing infrastructure is highly dynamic with continuously appearing and disappearing entities and services. It is vital that the associated computational trust model is able to incorporate this dynamism and that equally flexible legislative and regulatory frameworks emerge. In this thesis, we present an overview of the characteristics of the existing characteristics of the existing online trust and reputation models and systems through a multidimensional framework, which can serve as a basis to understand the current state of the art in the area. The critical open challenges that limit the effectiveness of today’s trust and reputation systems are discussed by providing a comprehensive literature review. Furthermore, we present a set of our contributions as a way to address some of these challenges and propose prospectives for online trust and reputation systems.

Selecting appropriate sellers in online auctions through a multi-attribute reputation calculation method

Online auctions have become immensely popular and created massive cash turnover in recent years. The volume of trade on eBay, the largest auction site in the world, reached US$6 billion in 2008. However, for a user intent on purchasing an item from an auction site, selecting an appropriate seller from the numerous choices is not an easy task. Even though most auction sites provide a concise binary reputation management mechanism to model the reputation of a trader through an integer value rating system, such a simple mechanism does not give users enough information about their potential trading partners. It is difficult to infer the right judgment rule correctly from knowledge of summing positive and negative ratings alone. We focus on developing an effective reputation model for online auctions to help users select a suitable seller. To accomplish this, four feature factors strongly related to online auction characteristics are adopted to assess the reputation of a trader. We also propose a multi-attribute reputation management (MARM) support tool to assist users in choosing sellers when using auction sites. In this research, actual transaction data collected from eBay were used to demonstrate the effectiveness of our method. Our results show that MARM is able to select more suitable sellers than other methods.

Reputation management algorithms for DHT-based peer-to-peer environment

This paper addresses the problem of integration of reputation management mechanisms into data look-up and routing processes to cope with some specific security problems in peer-to-peer (P2P) networks based on Distributed Hash Tables (DHT). The goal is to find a mode for “good” peers to cooperate in order to withstand malicious activity of single malevolent peers and their collusions as well. We start from consideration of individual instruments for reputation evaluation that every single peer should be provided with to autonomously define the level of its own trust towards others. We also propose a possible scenario of integration of some existing reputation management techniques and routing mechanisms in a P2P network based on the popular Kademlia algorithm. Then, we present an interaction algorithm that allows peers to obtain the global trust value for each single node through exchanging opinions in the form of local trust values independently calculated by every peer with other members of the community. Such collaboration between peers is indispensable to cope with malicious activity of inconsistent nature specific to DHT-based environment. To render the algorithm resilient to the presence of malicious participants we propose to apply solutions for Byzantine Agreement to exchange opinions among peers. We also provide mathematical evaluations concerning the complexity and computational costs of the proposed algorithm that evidence apparent improvements over the previous one.