Reputation Factor Research Articles

Penerapan Analisis Faktor dalam Menentukan Faktor-Faktor yang Mempengaruhi Keputusan Belanja Online Melalui Aplikasi Shopee (Studi Kasus: Mahasiswa Universitas Sumatera Utara)

Factor analysis is a statistical method aimed at exploring correlations or relationships among variables studied, which are then grouped into fewer new factors. Principal Component Analysis (PCA) is a statistical technique used to reduce the dimensions of data with the goal of identifying hidden patterns or significant structures within the data. The research results indicate the presence of 5 factors influencing the decision-making process in online shopping among students of the University of North Sumatra via Shopee, namely the Funding Application Factor (28.141%), Information Reputation Factor (13.983%), Communication Satisfaction Factor (7.452%), Types and Compensation Factor (6.683%), and Guarantees and Prices Factor (5.794%). These five factors obtained a cumulative variance of 62.051%, indicating that they influence online shopping decisions through Shopee among University of North Sumatra students by 62.051%.

Reputation-based disconnection-reconnection mechanism in Prisoner's Dilemma Game within dynamic networks

Individual reputation significantly influences players’ decision-making. Players tend to disconnect from neighbors with lower reputations so as to mitigate potential losses in the game. Therefore, it is crucial and meaningful to explore how to apply reputation in the game to enhance cooperation. In this study, we propose a reputation-based evolution mechanism in the Prisoner's Dilemma Game (PDG) within dynamic complex networks, including square lattices and small-world networks. We introduce the reputation factor α and the selection intensity σ in order to measure the changes in reputation and their impact objectively. Moreover, considering the impact of information connectivity, we define the environmental degree r and investigate the effects of environmental degree r and rewiring probability p on cooperation rates. Simulation results demonstrate that the reputation factor and information connectivity have a positive promoting effect on cooperative behavior; conversely, the increase in selection intensity affects cooperation negatively.

Scheduling optimization of shared energy storage station in industrial park based on reputation factor

Scheduling optimization of shared energy storage station in industrial park based on reputation factor

HERDING BIAS INVESTOR MASA NEW NORMAL PANDEMI COVID-19

This study examines the determinants of herding bias in investors in Indonesia during the Covid-19 New Normal period. This study was conducted for six months to survey the behavior of 232 investors with a single investor identification in the Indonesian capital market who were haphazardly selected to test the herding bias model. The results of Confirmatory Factor Analysis show that reputational factors, social proof, lack of awareness, volatility in global markets, underconfidence, optimism, bandwagon effect, and speculation are the determinants of investor herding bias in Indonesia. The results of this study also prove that the reputation factor is the dominant factor determining herding behavior, where investors will follow the behavior of their community to maintain their reputation. The second factor that contributes highly to determining herding bias is social proof, which means that Indonesian investors consider social roles in the decision-making process. We hope the results of this study can provide researchers and practitioners with a better understanding of herding behavior which is part of the theory of financial behavior.

Prosumers integration in aggregated demand response systems

In recent years, the increasing popularity of renewable energy and energy-efficient technologies is creating a new movement towards more sustainable communities. Understanding energy consumption is important for the optimisation of resources and the implementation of ecological trends. This paper integrates electricity consumers into a cooperative framework for planning sustainable smart communities through aggregators, which reallocates consumers’ demand according to available renewable energy supply collected from consumers and service providers. The aggregated demand response also includes consumers involved in energy production activities through microgeneration capabilities. A characterisation study of the different types of demand preferences is performed by defining scenarios of communities and consumers’ behaviours, which are validated through a reputation factor. The results show that the system adequately manages demand reallocation following the preferences and contribution of consumers and/or prosumers. Besides, this research analyses the current energy policy concerning demand flexibility, demand aggregation and microgeneration capacity, and their regulations in Spain. Finally, microgeneration acceptance, the role of aggregators and prosumers in the scheduling process is also investigated through a series of surveys.

The Reputation Factor in the Valuation of Startups

This paper analyses the relationship between corporate reputation and valuation, with a special focus on startups. Considering the most accredited scientific and professional literature regarding startup valuation, an attempt has been made to understand if and to what extent reputation can be a value driver in the estimate of startups during the first phases of their life cycle. The authors conducted a systematic literature review, which showed a modest interest in the subject on the part of the scientific community, while – on the contrary – practitioners developed ad hoc methods for valuing startups in their very early stages also considering reputational drivers. These methods are not based on the forecasting of flows and rates, but instead explain the value of the startup with a series of qualitative parameters that are explicitly identified and individually quantified/valued, acting as indicators of the value of the entity. Among the most used approaches are the Berkus Method, the Scorecard Method, and the Risk Factor Summation Method. These methods include reputational factors among qualitative parameters, that is among the value drivers. The analysis and the conclusions reached offer a conceptual contribution and identify a research path that deserves attention.

Microgrid trading mechanism enhancement for smart contract considering reputation values

ABSTRACT In order to reduce the system instability caused by credit risk in microgrid transactions in the blockchain, we propose a smart contract microgrid transaction model considering reputation value. Considering the instability caused by credit risk, the reputation factor is introduced to ensure the secure and stable operation of the microgrid energy trading system. The effectiveness of the scheme is verified by comparing traditional electricity trading and the trading with the introduced credit value scheme through simulation experiments.

The role of reputation in cross-regional buyer-supplier cooperation in public procurement

Relevance. The relevance of this study is determined by the growing trend of implementing approaches from the private sector in managing public procurement, such as suppliers’ reputation assessment. Although the suppliers’ reputation factor is a topic of current interest, both in research and in public procurement practice, there are ongoing discussions on the effects of the reputation criterion usage in public procurement, and some aspects have been insufficiently studied. Purpose of the study. This study examines the role of suppliers’ reputation factor in terms of interregional cooperation between public buyers and suppliers at the micro and regional levels. Data and methods. The analysis is based on a survey of public buyers in Russia, revealing procurers’ orientation on suppliers’ reputation factor and their involvement in cross-regional cooperation for micro-level analysis. With the help of open data on public procurement contracts, a grouping of Russian regions by the share of suppliers from other regions is proposed. The combination of open data analysis and survey results is then used to explore the role of reputation in terms of interregional cooperation. Results. The analysis shows that a suppliers’ reputation factor is of particular importance when more than half of a buyers’ suppliers are from other regions. Also, suppliers’ reputation is of major significance for public buyers in regions that are more involved in contracting with suppliers from other regions. Thus, the importance of the suppliers’ reputation factor, in terms of interregional cooperation, is confirmed both at the micro level of procurers’ purchases and at the regional level. Conclusion. For effective management of contractual relationships in public procurement, it is important to understand the effects and the role of considering the reputation of suppliers. The study focused on one of the insufficiently explored aspects of suppliers’ reputation in public procurement. The results may be of interest both to regulators and direct procurement participants – public buyers and suppliers.

РЕПУТАЦИЯ В ГОСУДАРСТВЕННЫХ ЗАКУПКАХ: ОСОБЕННОСТИ РЕГУЛИРОВАНИЯ, КЛЮЧЕВЫЕ ИНДИКАТОРЫ И ОЦЕНКИ ЭФФЕКТИВНОСТИ

The article presents a literature review on reputation factor in public procurement. Reputation is one of the tools for solving the principal-agent problem, which is typical for contractual relations. In line with the spread of New Public Management theory in public procurement, alternative methods of supplier selection are being developed, in particular, based on suppliers’ reputation. In contrast to the private sector, public buyers’ ability to consider reputation when choosing a supplier is highly regulated. It is shown that in the world practice of public procurement the reputation of suppliers is considered to varying degrees, there is no single approach to indicators, mechanisms for providing information and procedural aspects. Therefore, it is timely to analyse the arguments for and against expanding the possibilities of reputational considerations in public procurement. To answer this question, a separate block focuses on the effects of reputational considerations in public procurement in terms of barriers to entry, public procurement efficiency, and building trust between procurers and suppliers. Conclusions about the positive effects of reputational considerations are of interest to procurers who decide on the choice of supplier evaluation criteria. Relevant aspects of reputational considerations for Russian regulation concerning reputation indicators and mechanisms for providing information are identified. The article differs from existing reviews on the topic of reputation by focusing on the specificity of public procurement. An original classification of sources is presented in accordance with the following parameters: definitions and indicators of reputation, possibilities and limitations of reputational considerations and their effects in public procurement. Poorly studied aspects of interest for further research are identified.

Based on reputation consistent strategy times promotes cooperation in spatial prisoner’s dilemma game

As we all know, the reputation has important influence on individual’s decision-making. How to effectively and objectively measure reputation is very important in based-reputation evolutionary game theory. In this paper, a novel evolutionary mechanism for based on reputation consistent strategy times is proposed, in which the reputation income of each player is positive or negative related to its consistent strategy times for cooperation or defection at the initial moment of the current time step. The reward or punishment scheme of the proposed evolutionary mechanism is relatively consistent with the real world understanding of reputation. It’s especially worth pointing out that, when the player’s strategy state changes, the player can get reasonable and timely reward or punishment, which can better promote cooperation compared to existing reputation-based evolutionary mechanisms. Specifically, the proposed evolutionary mechanism has the following two advantages in the evolutionary systems. First, the player who has insisted on cooperation for a long time is not inclined to adopt defection, mainly because the cost of reputation is too high. In addition, the player who has long insisted on defection tends to adopt cooperation. This is mainly because the reputation of the player is easily restored from notoriety to general. Obviously, the above two points can effectively promote cooperation. Based on prisoner’s dilemma game (PDG) model, simulation and analysis also show that the proposed evolutionary mechanism can better promote cooperation compared to the traditional evolutionary mechanism, and can also speed up the evolutionary process, especially when the reputation factor is large. Furthermore, we also find that the cooperation level enhances when consistent strategy times upper bound becomes larger.

A Trustworthiness-Aware Spatial Task Allocation using a Fuzzy-based Trust and Reputation System Approach

Unlike crowdsourcing, Spatial Crowdsourcing (SC) requires workers to travel to a specific physical location to accomplish a task. Due to its open concept, the platform accepts any interested individual as workers or task requesters, including those who may be unreliable and untrustworthy. Deploying untrustworthy workers in spatial tasks can negatively impact the quality of the completed tasks, thus threatening the sustainability of the SC platform. Recent research has been carried out to evaluate workers’ trustworthiness based on the Trust and Reputation (TR) system. Current TR system approaches for evaluating workers’ trustworthiness are mostly relying on a single trust or reputation factor, and the decisions are mainly binary. This binary representation of trustworthiness is considerably rigid and may cause severe repercussions like, an untrustworthy worker who could be the victim of partial ratings may end up not getting any kind of spatial tasks from the system, or a trustworthy worker who may have malicious intention may be allocated a spatial task. To address these limitations, we propose a novel framework that allocates every spatial task according to a workers’ degree of perceived trustworthiness computed based on multi-criteria trust and reputation factors using a Mamdani fuzzy inference system. Our work considers historical ratings to calculate reputation value, applies sentiment analysis to infer trust value, implements Mamdani fuzzy inference to determine trustworthiness degree, and introduces the concept of referral to mitigate worker cold-start problems in spatial crowdsourcing. Our experimental findings on the Yelp real-world datasets demonstrate the reliability of the proposed framework to allocate every spatial task of various types to the most trustworthy workers from huge crowds of available workers. When evaluated against other baseline approaches, our approach achieves greater accuracy in allocating the right tasks to the most trustworthy workers.

Game Theory based Resource Identification Scheme for Wireless Sensor Networks

In modern world of sensing and distributive systems, traditional Wireless Sensor Networks (WSN) has to deal with new challenges, such as multiple application requirements, dynamic and heterogeneous networks. Senor nodes in WSN are resource constrained in terms of energy, communication range, bandwidth, processing delay and memory. Numerous solutions are proposed to optimize the performance and to increase the lifetime of WSN by introducing new resource management principles. Effective and intelligent resource management in WSN involves in resource identification, resource scheduling, and resource utilization. This paper proposes a Bayesian Game Model (BGM) approach to efficiently identify the best node with the maximum resource in WSN for data transmission, considering energy, bandwidth, and computational delay. The scheme operates as follows: (1) Sensor nodes information such as residual energy, available bandwidth, and node ID, etc., is gathered (2) Energy and bandwidth of each node are used to generate the payoff matrix (3) Implementation of node identification scheme is based on payoff matrix, utilities assigned, strategies and reputation of each node (4) Find Bayesian Nash Equilibrium condition using Starring algorithm (5) Solving the Bayesian Nash Equilibrium using Law of Total Probability and identifying the best node with maximum resources (6) Adding/Subtracting reward (reputation factor) to winner/looser node. Simulation results show that the performance of the proposed Bayesian game model approach for resource identification in WSN is better as compared with the Efficient Neighbour Discovery Scheme for Mobile WSN (ENDWSN). The results indicate that the proposed scheme has up to 12% more resource identification accuracy rate, 10% increase in the average number of efficient resources discovered and 8% less computational delay as compared to ENDWSN.

Factors Affecting Reputational Damage to Organisations Due to Cyberattacks

The COVID-19 pandemic has brought massive online activities and increased cybersecurity incidents and cybercrime. As a result of this, the cyber reputation of organisations has also received increased scrutiny and global attention. Due to increased cybercrime, reputation displaying a more important role within risk management frameworks both within public and private institutions is vital. This study identifies key factors in determining reputational damage to public and private sector institutions through cyberattacks. Researchers conducted an extensive review of the literature, which addresses factors relating to risk management of reputation post-cyber breach. The study identified 42 potential factors, which were then classified using the STAR model. This model is an organisational design framework and was suitable due to its alignment with organisations. A qualitative study using semi-structured and structured questions was conducted with purposively selected cybersecurity experts in both public and private sector institutions. Data obtained from the expert forum were analysed using thematic analysis, which revealed that a commonly accepted definition for cyber reputation was lacking despite the growing use of the term “online reputation”. In addition, the structured questions data were analysed using relative importance index rankings. The analysis results revealed significant factors in determining reputational damage due to cyberattacks, as well as highlighting reputation factor discrepancies between private and public institutions. Theoretically, this study contributes to the body of knowledge relating to cybersecurity of organisations. Practically, this research is expected to aid organisations to properly position themselves to meet cyber incidents and become more competitive in the post-COVID-19 era.

Reputation Detection for Information Diffusion in Social Network Systems

Reputation detection in traditional distributed systems (e.g., electronic commerce systems and peer‐to‐peer systems) relies heavily on the factor of interaction reputation, which can be derived from direct interactions between agents through bidirectional relationships. However, in the current information diffusion in social network systems (SNS) (e.g., Twitter), the characteristic of the unidirectional relationship between agents and the decay property of diffusion will result in lacking direct interactions; therefore, interaction reputations will be difficult to be obtained by agents in a distributed manner. To solve this problem, a novel distributed reputation detection model following the pattern “from path to individual” (FPTI) is proposed, which can provide a new reputation factor as an alternative to interaction reputation in such environments. The main idea is that the positive (or negative) observation of an information diffusion process increases (or decreases) the belief of the corresponding diffusion path, which further increases (or decreases) the reputation of each involved agent. Thus, the reputation of a target agent can be assessed by the superimposition of reputations of multiple paths on which this agent has participated in past information diffusion processes. Furthermore, being aware of agent’s limited capacity for reputation detection in SNS, we then propose the enhanced FPTI model (eFPTI), which simplifies the detection source to reduce detection costs and achieve the approximate performance as FPTI. Theoretical analyses and experimental evaluations validate the efficiency and effectiveness of our models and also show several properties of the models, for example, the robustness for dynamic environments.

The Effect of Educational Service Quality on Career Decision-Making Self-Efficacy and Career Attitude Maturity as PUBLIC VALUES of Airline Service Major

Purpose: This study aims to investigate the relationship between self-efficacy and career attitude maturity in career decision-making of educational service quality developed to improve the quality of education in the Department of Aviation Service and strengthen competitiveness in the department. It is insufficient research to apply educational service quality considering the characteristics of the Department of Airline Service, and it is expected that this study will be used as basic data to help efficient department operation and establish strategies for fierce entrance exams. Method: For empirical analysis, a total of 231 responses were collected from students enrolled in the Department of Aviation Services at two-year and four-year universities located in Korea from September 6 to September 14, 2021, of which 221 were used for empirical analysis, excluding 10 unfaithful responses. In the empirical analysis, frequency analysis, factor analysis of measurement variables, reliability, and validity were investigated through SPSS 21.0. Results: It was confirmed that the reputation factor, a sub-factor of educational service quality, is an important factor in all sub-factors of career decision-making self-efficacy. In addition, It was confirmed that self-evaluation, a sub-factor of career decision-making self-efficacy, is an important factor in career attitude maturity. It was shown that the employment support factors of education service quality were all important factors in the determination, purpose, certainty, and independence of career attitude maturity. Conclusion: Through the results of this study, it was confirmed that aviation service department education service quality had a significant influence on career decision-making self-efficacy and career attitude maturity. To increase college students self-efficacy and career attitude maturity in career decision-making, it is necessary to accurately grasp the importance perceived by college students, increase the leading performance of aviation service majors, and actively engage in career preparation behavior. The result of this study suggests how the educational service quality in the airline service department currently recognized by students is related to career decision-making self-efficacy and career attitude maturity and suggests improvement measures for the development of the department.

Lightweight blockchain framework for location-aware peer-to-peer energy trading

Peer-to-peer (P2P) energy trading, as a new approach for energy management in smart grids, facilitates integration of a large number of small-scale producers and consumers into energy markets. Decentralized management of these new market participants is challenging in terms of market settlement, participant reputation and consideration of grid constraints. This paper proposes a blockchain-enabled framework for P2P energy trading among producer and consumer agents in a smart grid. A fully decentralized market settlement mechanism is designed, which does not rely on a centralized entity to settle the market and encourages producers and consumers to negotiate on energy trading with their nearby agents truthfully. To this end, the electrical distance of agents is considered in the pricing mechanism to encourage agents to trade with their neighboring agents. In addition, a reputation factor is considered for each agent, reflecting its past performance in delivering the committed energy. Before starting the negotiation, agents select their trading partners based on their preferences over the reputation and proximity of the trading partners. An Anonymous Proof of Location (A-PoL) algorithm is proposed that allows agents to prove their location without revealing their real identity. The practicality of the proposed framework is illustrated through several case studies, and its security and privacy are analyzed in detail.

전시회 참관수요 결정요인 분석 코로나19시대의 전시회 관여도를 중심으로

The rapid development of ICT is making us accustomed to online consumption and networking, but exhibitions are expected to increase further. There are many studies of the exhibition's service attributes with the visitor's behavior, few studies have identified the direct impact on the exhibition's service quality on demand of visitors. Therefore, this study analyzes the main determinants using the service quality attributes of the exhibition and the impact on variables of the visitors' involvement and the demand model estimation. The survey was conducted through an online survey of 278 people that attended exhibitions of the last three years for a month in June, 2020 by Google Form. The Truncated Poisson model and the Truncated Negative Binomial model were used to estimate the demand model for the service quality of the exhibition. As the results of LR-test, the estimation was as follows. First, marital status and educational level have negative impacts in the high exhibition involvement group, gender and age have positive impacts in the low exhibition involvement group. Second, the exhibition's reputation factor was shown to have the positive influence on the high exhibition involvement group, but the content learning factor was the negative impact. In the low exhibition involvement group, the facility convenience factor was shown as positive, the information factor was shown as negative. The results of the study could provide practical implications for the exhibition marketing, which is facing a new turning point due to the COVID-19.

Customers' Switching Barrier on Switching Behavior from Conventional Banks to Sharia Banks

This study aims to explore the reasons why conventional bank customers have not yet shifted to Islamic (sharia) banking in South Sulawesi, as well as identify the obstacles that have caused customers to remain conventional banks. The research subjects numbered 110 people. The research method uses Mixed Methods with sequential exploratory design. The first stage is a qualitative method to obtain data that is variable because the community has not yet switched to sharia banking. The second stage of the quantitative method is using Factor Analysis, to deepen the data and test the data so that the findings can be generalized. Data were collected by open and closed questionnaires and interviews, validity and reliability tests were carried out based on the analysis model used. The results of the analysis show that the factors that constrain people to move to Sharia banking are Fee Interest Factor, Information Factor, Location Factor, Relationship and Reputation Factor, Religiosity Factors, Product Factor, and Financial Risk Cost Factor. There are four findings of new factors as novelty of this study, namely Fee Interest Factors, Location Factors, Religiousity Factors, and Product Factors, as barriers to switch for the service industry, especially Sharia banking.

Why people select the outpatient clinic of medical centers: a nationwide analysis in Taiwan.

IntroductionIn contrast to other countries, Taiwan’s National Health Insurance (NHI) program allows patients to freely select the specialists and tiers of medical care facility without a referral. Some medical centers in Taiwan receive over 10,000 outpatients per day. In the NHI program, the co-payment was increased for high-tier facilities for outpatient visits in 2002, 2005, and 2017. However, the policies only mildly reduced the use of high-tier medical care facilities. The main purpose of this study was to evaluate the factors contributing to the patients’ selection of the outpatient clinic of medical centers without a referral.MethodsAn online anonymous survey was conducted by using the Google Forms platform utilizing a self-constructed questionnaire from September to October 2018. A nationwide sample in Taiwan was recruited using convenience sampling through social media. Based on a literature review and a focus group, 20 factors that may affect the choice of the outpatient institution were constructed. The associations between items that affect the patients selection of outpatient clinics were assessed using exploratory factor analysis. Principal axis factoring was performed to identify the major factors affecting the decision. Multiple logistic regression was performed to determine which factors satisfactorily explained “visiting the outpatient clinic of the medical center for an illness without a referral.”ResultsDuring the survey period, 5,060 people browsed the online survey, and 1,003 responded and completed the online questionnaire. Therefore, the response rate was 19.8%. A total of 987 valid responses was collected. Exploratory factor analysis revealed that three main factors, namely the “physician factor”, “image and reputation factor”, and “facility and medication factor”, affected the selection of outpatient clinics. A series of logistic regressions indicated that patients who reported that hospital facilities, high-quality drugs, and diverse specialties were very important were more likely to select the outpatient clinic of a medical center (OR = 2.218, 95% CI [1.514–3.249]). Patients who reported that physician factors were very important were less likely to select a medical center (OR = 0.717, 95% CI [0.523–0.984]). Patients who were previously satisfied with their experience of the primary clinics or had a regular family doctor were less likely to choose a medical center (OR = 0.509, 95% CI -0.435–0.595] and OR = 0.676, 95% CI [0.471–0.969]).ConclusionIn Taiwan, patients with good primary medical experience and regular family physicians had significantly lower rates by selecting the outpatient clinic of a medical center. The results of this study support that the key to establishing graded medical care is to prioritize the strengthening of the primary medical system.

Testing the event travel career trajectory in multiple participation sports

ABSTRACT This paper employs data from a large-scale survey of respondents from five mass-participation sport events in Sweden to test and develop the ‘event travel career trajectory’. The six inter-related hypotheses of the theoretical construct are examined, dealing with the evolution of participants’ motivations, event and destination choice criteria, and travel patterns and styles as their sport ‘involvement’ increases. Involvement has been measured by reference to both attitudes and event-travel activity. Analysis of data from over 6000 respondents reveals that these sport-event tourists progress along the career trajectory as they become significantly more involved. The most highly involved have significantly different preferences, preferring the accompaniment of a club or team; they spend a significantly larger amount of money on equipment, and self-improvement is a significantly stronger motivation. The most highly involved are more selective or demanding when it comes to choosing events, including more novelty seeking, wanting a party atmosphere, and favouring events with a higher reputation and prestige factor. They want a scenic/fast track or course and they have significantly different criteria for destination preferences, including a higher need for accessibility, quality services, strong reputation in sports, competence of event organizers, pleasant weather and attractive scenery. International participants have, on average, come further along the trajectory than domestic participants. In the concluding section, a dynamic explanation to the event travel career trajectory is suggested. Implications for destinations and events are discussed and further research needs are identified.