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Journal articles on the topic 'E-REPUTATION'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Standifird, Stephen S. "Reputation and e-commerce: eBay auctions and the asymmetrical impact of positive and negative ratings." Journal of Management 27, no. 3 (June 2001): 279–95. http://dx.doi.org/10.1177/014920630102700304.

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This analysis explores the impact and nature of reputation as related to e-commerce by looking at the importance of a seller’s reputational rating on the final bid price associated with eBay auctions. Positive reputational ratings emerged as mildly influential in determining final bid price. However, negative reputational ratings emerged as highly influential and detrimental. Thus, we find strong evidence for the importance of reputation when engaging in e-commerce and equally strong evidence concerning the exaggerated influence of negative reputation.

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2

Simpson, Thomas W. "e-Trust and reputation." Ethics and Information Technology 13, no. 1 (December 18, 2010): 29–38. http://dx.doi.org/10.1007/s10676-010-9259-x.

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3

Tomic, Igor, Maria Rodriguez García, and Salvatore Moccia. "Fintech strategy: e-reputation." International Journal of Intellectual Property Management 11, no. 1 (2021): 38. http://dx.doi.org/10.1504/ijipm.2021.10035768.

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Moccia, Salvatore, Maria Rodriguez García, and Igor Tomic. "Fintech strategy: e-reputation." International Journal of Intellectual Property Management 11, no. 1 (2021): 38. http://dx.doi.org/10.1504/ijipm.2021.113367.

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5

Chalençon, Ludivine, Ana Colovic, Olivier Lamotte, and Ulrike Mayrhofer. "Reputation, E-Reputation, and Value-Creation of Mergers and Acquisitions." International Studies of Management & Organization 47, no. 1 (November 18, 2016): 4–22. http://dx.doi.org/10.1080/00208825.2017.1241086.

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6

Castellano, Sylvaine, and Insaf Khelladi. "Reputation, Image, and Social Media as Determinants of e-Reputation." International Journal of Technology and Human Interaction 12, no. 4 (October 2016): 48–64. http://dx.doi.org/10.4018/ijthi.2016100104.

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Although the Internet represents great opportunities for businesses, some firms that are evolving in the luxury industry were initially reluctant to engage in digital activities. However, over the past few years, digital natives represent a main reason for these firms to start adopting online strategies. Specifically, reputation and image are inherent to the luxury industry, and with social media, they are considered the determinants of e-reputation. Using an online survey design, the authors find that the influence of reputation, image and social media on e-reputation differs based on the status of the luxury brand (traditional compared with modern) and that digital natives moderate these links.

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Lv, Junjie, Zichen Wang, Yuqing Huang, Tong Wang, and Yuanzhuo Wang. "How Can E-Commerce Businesses Implement Discount Strategies through Social Media?" Sustainability 12, no. 18 (September 10, 2020): 7459. http://dx.doi.org/10.3390/su12187459.

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In the context of the global economic downturn caused by COVID-19, e-commerce has become the first choice for people to shop. Many merchants choose to launch promotion activities through some social media platforms. Price discounts can dramatically increase sales volume in social e-commerce due to the interaction of online consumers. It is urgent for e-commerce merchants to learn rules about discount information dissemination in social media, so as to formulate reasonable discount strategies and achieve sustainable business. This paper constructs an evolutionary game model for e-commerce platforms and merchants when they implement promotion strategies through social media, investigates discount information dissemination among consumers under multiple situations by introducing price discount parameters, and further discusses the influence mechanism of discount size and platform reputation on consumers’ purchase behavior. Results show that in low-reputation e-commerce platforms, the price discount is the main motivation to purchase. Consumers’ preference for the high discount is weakened by the increase in platforms’ reputation. Discounts should be set according to the different reputations. Businesses in a high-reputation environment are relatively more profitable. E-commerce businesses should work together, apply reasonable pricing, and improve their quality to create a green and healthy shopping environment, in order to get benefits and sustainable development.

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8

Zhang, Li-fang, and Fu-jing Zhang. "Does E-commerce Reputation Mechanism Matter?" Procedia Engineering 15 (2011): 4885–89. http://dx.doi.org/10.1016/j.proeng.2011.08.910.

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Salhi, Dhai Eddine, Abelkamel Tari, and Mohand Tahar Kechadi. "Using E-Reputation for Sentiment Analysis." International Journal of Cloud Applications and Computing 11, no. 2 (April 2021): 32–47. http://dx.doi.org/10.4018/ijcac.2021040103.

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In a competitive world, companies are looking to gain a positive reputation through these clients. Electronic reputation is part of this reputation mainly in social networks, where everyone is free to express their opinion. Sentiment analysis of the data collected in these networks is very necessary to identify and know the reputation of a companies. This paper focused on one type of data, Twits on Twitter, where the authors analyzed them for the company Djezzy (mobile operator in Algeria), to know their satisfaction. The study is divided into two parts: The first part was the pre-processing phase, where this research filtered the Twits (eliminate useless words, use the tokenization) to keep the necessary information for a better accuracy. The second part was the application of machine learning algorithms (SVM and logistic regression) for a supervised classification since the results are binary. The strong point of this study was the possibility to run the chosen algorithms on a cloud in order to save execution time; the solution also supports the three languages: Arabic, English, and French.

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10

Dutot, Vincent, and Sylvaine Castellano. "Designing a Measurement Scale for E-Reputation." Corporate Reputation Review 18, no. 4 (October 2015): 294–313. http://dx.doi.org/10.1057/crr.2015.15.

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11

Wei, Chuang, Zhao-Ji Yu, and Xiao-Nan Chen. "Research on social e-commerce reputation formation and state-introduced model." Kybernetes 46, no. 06 (June 5, 2017): 1021–38. http://dx.doi.org/10.1108/k-08-2016-0203.

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Purpose This paper aims to solve the problem of information overload and reduce search costs. It proposes a social e-commerce online reputation formation model and community state-introduced model. A system dynamics trend simulation has been run to capture the relationship among the sellers, buyers, social e-commerce platforms and external environment to obtain an online reputation. Design/methodology/approach Empirical research relating to social e-commerce reputation has been used to confirm the influencing factors in social e-commerce, and a conceptual framework is developed for social e-commerce reputation formation. Thereafter, a trend simulation is generated to classify the relationship among the factors based on system dynamics. Also, the improved algorithm for community detection and a state-introduced model based on a Markov network are proposed to achieve better network partition for better online reputation management. Findings The empirical model captures the interaction effect of social e-commerce reputation and the state-introduced model to guide community public opinion and improve the efficiency of social e-commerce reputation formation. This helps minimize searching cost thereby improving social e-commerce reputation construction and management. Research limitations/implications There is no appropriate online reputation system to be constructed to test the relationship proposed in the study for a field experiment. Also, deeper investigation for the nodes’ attributes in social networks should be made in future research. Besides, researchers are advised to explore measurement for the reputation of a given seller by using social media data as from Twitter or micro blogs. Originality/value Investigations that study online reputation in the social e-commerce are limited. The empirical research figured out the factors which can influence the formation of online reputation in social e-commerce. An SD model was proposed to explain the factors interaction and trend simulation was run. Also, a state-introduced model was proposed to highlight the effect of nodes’ attributes on communities’ detection to give a deeper investigation for the online reputation management.

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12

Castellano, Sylvaine, Insaf Khelladi, Amélie Chipaux, and Célia Kupferminc. "The Influence of Social Networks on E-Reputation." International Journal of Technology and Human Interaction 10, no. 4 (October 2014): 65–79. http://dx.doi.org/10.4018/ijthi.2014100105.

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With the increased importance of the Internet and the use of social media, new opportunities and challenges emerge to manage the relationship with audiences and online communities. While the professional world already acknowledged such dynamics, further analysis is needed in the academic scene. A survey conducted in the sports setting shows that the perception of social networks influences athletes' e-reputation. However, the motives for following athletes online have no influence on their e-reputation. Finally, the results highlight that e-reputation is not affected by negative content on the internet. This research has both academic and managerial contributions regarding online reputation and social media.

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13

Sharma, Neeraj Kumar, Vibha Gaur, and Punam Bedi. "Improving Trustworthiness in E-Market Using Attack Resilient Reputation Modeling." International Journal of Intelligent Information Technologies 10, no. 3 (July 2014): 57–82. http://dx.doi.org/10.4018/ijiit.2014070104.

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Asymmetric information is a major problem in e-commerce transactions as it gives rise to adverse selection and moral hazard problems. Reputation mechanisms provide a solution to this problem by discouraging fraudulent behavior and encouraging honest behavior of participants in the uncertain and un-trusted environment of e-market. This paper discusses trust and reputation relationships, and highlights the importance of key reputation building parameters to enhance trustworthiness of participants. Finally, it proposes reputation metrics that guard reputation systems from various attacks by malicious participants to improve the quality of e-market and presents a working prototype.

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14

Fan, Ying, Jiandong Ju, and Mo Xiao. "Reputation premium and reputation management: Evidence from the largest e-commerce platform in China." International Journal of Industrial Organization 46 (May 2016): 63–76. http://dx.doi.org/10.1016/j.ijindorg.2016.01.004.

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15

Kumar, Vikas, and Prasann Pradhan. "Reputation Management Through Online Feedbacks in e-Business Environment." International Journal of Enterprise Information Systems 12, no. 1 (January 2016): 21–37. http://dx.doi.org/10.4018/ijeis.2016010102.

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Popularity of electronic business has changed the way people are transacting businesses around the globe. People are engaged in online businesses (like buying, selling, promoting or collaborating) without any physical or face to face contact with the trading partners. Correspondingly, the concept of reputation has become an as important pillar of the electronic business to provide some level of assurance about the quality of the traders as well as their products and services. In this scenario, online feedbacks have emerged as a valuable tool in reputation management and help in making a choice for the best quality online trading partners. Further, there is a strong need for the e-business companies to change their strategies and decision making process to build and manage their reputation via online feedbacks. In this paper, the reputation and reputation management through online feedbacks have been discussed with a specific focus on the electronic business (e-business). This paper examines the prevailing reputation models, which are based on online feedbacks and are used by the companies. Specific examples and cases have been added to highlight the present day industry scenario.

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16

Eckhardt, Giana M. "Playing the Trust Game Successfully in the Reputation Economy." NIM Marketing Intelligence Review 12, no. 2 (November 1, 2020): 10–17. http://dx.doi.org/10.2478/nimmir-2020-0011.

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AbstractHunting for “stars”, the icons of the reputation economy, is a prerequisite for survival in e-commerce in general and on sharing platforms in particular. The key to understanding the rise of reputation is trust, and the ability of a platform to provide this trust has become crucial in the past decade. Social media managers are now key players in marketing departments. One of their most important jobs is the careful curation of digital reputations. Marketers need to engage in diverse forms of reputation management and master several challenges in designing the right systems and utilizing reputation information in optimal ways. Engendering trust is more complex than gaining star ratings or positive reviews on owned or third-party platforms. How platforms are designed – in terms of how people can make bookings or orders and how users rate each other – is the key issue. It needs to be managed in a sophisticated way, especially in an era when topics such as racial and ethnic justice are key societal concerns.

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17

Castellano, Sylvaine, and Vincent Dutot. "Investigating the Influence of E-Word-of-Mouth on E-Reputation." International Studies of Management & Organization 47, no. 1 (November 18, 2016): 42–60. http://dx.doi.org/10.1080/00208825.2017.1241088.

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18

Marrakchi, Mouna El, Hicham Bensaid, and Mostafa Bellafkih. "E-Reputation Prediction Model in Online Social Networks." International Journal of Intelligent Systems and Applications 9, no. 11 (November 8, 2017): 17–25. http://dx.doi.org/10.5815/ijisa.2017.11.03.

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19

Hua Li, Hui Xia, Min Gao, and Hui Ma. "Study on Reputation Model of E-commerce Networks." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 10 (May 31, 2013): 1–10. http://dx.doi.org/10.4156/aiss.vol5.issue10.1.

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20

Eastwood, David. "History, Politics and Reputation: E. P. Thompson Reconsidered." History 85, no. 280 (October 2000): 634–54. http://dx.doi.org/10.1111/1468-229x.00167.

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21

Yao, Jinhui, Wei Tan, Surya Nepal, Shiping Chen, Jia Zhang, David De Roure, and Carole Goble. "ReputationNet: Reputation-Based Service Recommendation for e-Science." IEEE Transactions on Services Computing 8, no. 3 (May 1, 2015): 439–52. http://dx.doi.org/10.1109/tsc.2014.2364029.

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22

Wang, Yan, and Kwei-Jay Lin. "Reputation-Oriented Trustworthy Computing in E-Commerce Environments." IEEE Internet Computing 12, no. 4 (July 2008): 55–59. http://dx.doi.org/10.1109/mic.2008.84.

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23

Fouliras, Panayotis. "A novel reputation-based model for e-commerce." Operational Research 13, no. 1 (May 6, 2011): 113–38. http://dx.doi.org/10.1007/s12351-011-0114-6.

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24

Gutowska, Anna, Andrew Sloane, and Kevan A. Buckley. "On Desideratum for B2C E-Commerce Reputation Systems." Journal of Computer Science and Technology 24, no. 5 (September 2009): 820–32. http://dx.doi.org/10.1007/s11390-009-9274-8.

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25

Zhang, Han Lin, Sui Yi Li, and Xiao Jing Jia. "Research on Reputation Systems Based on E-Business to Guarantee Integrity Transactions." Advanced Materials Research 403-408 (November 2011): 2953–57. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2953.

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It should be designed one kind of reputation system based on the public-key certificate system to assure the strangers in the environment of E-Business to guarantee integrity transactions. This reputation system should satisfy the transaction characteristics of entity in the E-business, which can not only store the reputation evaluation data in a distributed way but also delete the malicious entity effectively based on certificate revocation mechanisms. Aiming at the transaction characteristics of objectivity, simplicity and utility, this paper gives us an improvement on add algorithm and subtraction algorithm for reputation data in the system. At last, using the experiment in analog simulation, it shows that the reputation system can realize those functions effectively.

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Burete, Radu, Amelia Badica, Costin Badica, and Florin Moraru. "Enhanced Reputation Model with Forgiveness for E-Business Agents." International Journal of Agent Technologies and Systems 3, no. 1 (January 2011): 11–26. http://dx.doi.org/10.4018/jats.2011010102.

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Trust is a very important quality attribute of an e-service. In particular, the increasing complexity of the e-business environment requires the development of new computational models of trust and reputation for e-business agents. In this paper, the authors introduce a new reputation model for agents engaged in e-business transactions. The model enhances classic reputation models by the addition of forgiveness factor and the use of new sources of reputation information based on agents groups. The paper proposes an improvement of this model by employing the recent con-resistance concept. Finally, the authors show how the model can be used in an agent-based market environment where trusted buyer and seller agents meet, negotiate, and transact multi-issue e-business contracts. The system was implemented using JADE multi-agent platform and initially evaluated on a sample set of scenarios. The paper introduces the design and implementation of the agent-based system together with the experimental scenarios and results.

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Liao, Xin Kao, Li Sheng Wang, Ke Te Wang, and Xiao Jie Xu. "Modeling for Reputation Computing Research Base on C2C Communities." Applied Mechanics and Materials 740 (March 2015): 839–42. http://dx.doi.org/10.4028/www.scientific.net/amm.740.839.

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Trust is part of the main problems in the development of C2C e-commerce. Calculating the value of reputation based on feedback rating is an effective way to create trust in e-commerce transactions. This paper proposes a computing model built on the reputation of e-commerce by introducing a feedback score, the transaction value, time, penalty factor and other parameters. Simulation results demonstrate that the model can effectively prevent the credibility of slander, reputation hype, reputation conspiracy and other issues.

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Kusuma, Linda, Sri Rejeki, Robiyanto Robiyanto, and Lala Irviana. "REPUTATION SYSTEM OF C2C E-COMMERCE, BUYING INTEREST AND TRUST." Business: Theory and Practice 21, no. 1 (April 24, 2020): 314–21. http://dx.doi.org/10.3846/btp.2020.11559.

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One form of the development of technology and internet users in Indonesia is the merge of various C2C (Customers to Customers) e-commerce on the marketplace. Bukalapak is one of the examples. This research presents the effects of reputation systems on trust, trust in buying interest, and reputation systems on Bukalapak customers’ buying interests. A total of 120 respondents participated and the data were analyzed using structural equation modeling with Amos 20 software. The results show that the reputation system has a higher direct impact compared to the impacts mediated by trust. Therefore, in an effort to increase the buying interest, the sellers should increase their reputation in the reputation system represented in the list of feedback, review, and the badge level in Bukalapak. To marketplace providers, in this case, Bukalapak, there is still a need to increase the customers’ trust. Although it is significant, however, it has low impacts both directly and indirectly.

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Fadili, Dadan Ahmad, Ellya Damayanti, and Evanasia Shaghra. "Pengaruh E-Reputation dan Promosi terhadap Citra Manajemen Yang-Gun (YG) Entertainment." Permana : Jurnal Perpajakan, Manajemen, dan Akuntansi 12, no. 1 (February 29, 2020): 1–8. http://dx.doi.org/10.24905/permana.v12i1.77.

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E-Reputation adalah hasil dari aktivitas perusahaan dalam lingkungan virtual dengan interaksi dan reaksi selanjutnya dari pemangku kepentingan Promosi adalah merupakan salah satu faktor paling penting dalam mewujudkan tujuan penjualan suatu perusahaan agar konsumen bersedia menjadi pelanggan. Tujuan penelitian ini adalah untuk mengetahui pengaruh E-Reputation dan Promosi terhadap Citra Manajemen Yang-Gun (YG) Entertainment. Penelitian ini dilakukan dengan menggunakan metode deskriptif dan verifikatif. Teknik sampling penelitian ini adalah Simple Random Sampling menggunakan rumus Slovin. Jenis data yang digunakan dalam penelitian ini adalah data primer dan sekunder. Data diolah menggunakan analisis regresi linier berganda. Hasil penelitian ini membuktikan bahwa E-Reputation dan Promosi berpengaruh positif dan signifikan terhadap Citra Manajemen. Kata Kunci : E-Reputation, Promosi, Citra Manajemen, Yang-Gun (YG) Entertainment

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Kazanina, Anastasia I., and Anna G. Milyukova. "Corporate reputation analysis in social media (e. g. Wildberries online store)." Socialʹnye i gumanitarnye znania 6, no. 1 (March 15, 2020): 12. http://dx.doi.org/10.18255/2412-6519-2020-1-12-19.

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This article is devoted to analyzing the reputation of Wildberries and its leader in social networks using quantitative and qualitative indicators. The specificity of the concept of "reputation capital" has been defined. The relevance of reputation capital research for the online store Wildberries was determined. The analysis of reputation risks for the company and its manager is given, possible negative events in the sphere of relations with suppliers, employees, customers, legal risks, consequences of digitalization, changes in market conditions and customers' demands are defined. The ratio of potential and realized reputational risks for the company is analyzed. It was revealed that the majority of realized risks relate to the quality of goods, professionalism of the front-office personnel and working conditions. The company's CEO's reputation positioning is assessed and recommendations are given based on the current state of affairs. The analysis of social media showed that the company has a positive reputation, but there are shortcomings that need to be addressed and addressed by management. In general, the company carries out a whole range of procedures to maintain its reputation and a sound financial position, focusing on stakeholders. It was found that the non-publicity of the manager does not have a negative impact on the reputation of the company. To form a positive reputation of the company, it is recommended to think over the photocontent, texts and tone of communication depending on the purpose of the site used, to add personification of posts, to conduct regular monitoring of all components of the company's reputation in social media to make decisions on timely correction of reputation strategy.

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Majd, Elham, Vimala Balakrishnan, Sousan Gharib, Katayoon Pourmahdi, Leili Shakeri, and Masoumeh Feyz Abadi. "Calculating the Reliability and Reputation of Agents in E-Commerce Multi-Agent Environments." Applied Mechanics and Materials 548-549 (April 2014): 1478–82. http://dx.doi.org/10.4028/www.scientific.net/amm.548-549.1478.

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E-commerce multi-agent systems have some features of autonomy and commercial transaction that improve rapidly and become a powerful tool for buying and selling products online. While multi-agent systems can break interactions in distributed and heterogeneous environments, malicious behaviors of the agents are a potential hazard in distributed e-commerce applications. Hence, calculating the reliability and reputation of agents play a critical role in determining how interactions occur and who to interact with. The way of calculating the reliability and reputation of each agent should be based on different elements, and there are no standard elements to compute reliability and reputation of each agent in multi-agent environment. This paper analyses some recent proposed methods in calculating reputation and reliability of each agent. The ultimate aim of this study is to define the standard elements which should be considered to calculate the reliability and reputation of agents in e-commerce multi-agent environment.

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Elmurngi, Elshrif Ibrahim, and Abdelouahed Gherbi. "Building Sentiment Analysis Model and Compute Reputation Scores in E-Commerce Environment Using Machine Learning Techniques." International Journal of Organizational and Collective Intelligence 10, no. 1 (January 2020): 32–62. http://dx.doi.org/10.4018/ijoci.2020010103.

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Online reputation systems are a novel and active part of e-commerce environments such as eBay, Amazon, etc. These corporations use reputation reporting systems for trust evaluation by measuring the overall feedback ratings given by buyers, which enables them to compute the reputation score of their products. Such evaluation and computation processes are closely related to sentiment analysis and opinion mining. These techniques incorporate new features into traditional tasks, like polarity detection for positive or negative reviews. The “all excellent reputation” problem is common in the e-commerce domain. Another problem is that sellers can write unfair reviews to endorse or reject any targeted product since a higher reputation leads to higher profits. Therefore, the purpose of the present work is to use a statistical technique for excluding unfair ratings and to illustrate its effectiveness through simulations. Also, the authors have calculated reputation scores from users' feedback based on a sentiment analysis model (SAM). Experimental results demonstrate the effectiveness of the approach.

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Dutot, Vincent, Eva Lacalle Galvez, and David W. Versailles. "CSR communications strategies through social media and influence on e-reputation." Management Decision 54, no. 2 (March 21, 2016): 363–89. http://dx.doi.org/10.1108/md-01-2015-0015.

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Purpose – Publics are becoming responsible customers that urge firms to improve society. By using social media, corporate social responsibility (CSR) actions could influence organization’s commitment and e-reputation. The purpose of this paper is to look at the influence on e-reputation of communication strategies (i.e. corporate ability and CSR) on social media. Design/methodology/approach – Four international companies (Danone, Renault, Orange and BNP Paribas) were studied and a content analysis was performed: Leximancer for the social media content (between 25 and 50 pages for each company) on a six-month period; and Social Mention for the measurement of e-reputation. Findings – Results show that there is a link between CSR communication strategies and e-reputation. More precisely, by using a corporate ability strategy (focus on product quality or innovation R & D), a company can increase its e-reputation better than on a common CSR communication strategy. Research limitations/implications – This study is based on only four companies (from four different industries) and would profit from a larger base for analysis. Second, the content the authors analyzed was generated by the company on their own social media. Originality/value – This exploratory study is one of the first to look at the influence of CSR communication strategies on e-reputation and tries to see how companies’ action on social media can change the way they are perceived by their customers. It completes the current literature by defining how CSR communications strategies should be declined for in order to influence customers.

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Xie, Hong, Richard T. B. Ma, and John C. S. Lui. "Enhancing Reputation via Price Discounts in E-Commerce Systems." ACM Transactions on Knowledge Discovery from Data 12, no. 3 (April 27, 2018): 1–29. http://dx.doi.org/10.1145/3154417.

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Zhang, Yang, Tieying Liu, Ru Li, and Zhenhai Wan. "Evaluation Model of Buyers-Dynamic Reputation in E-commerce." International Journal of Multimedia and Ubiquitous Engineering 10, no. 5 (May 31, 2015): 53–64. http://dx.doi.org/10.14257/ijmue.2015.10.5.07.

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36

Fang, Hui, Jie Zhang, Murat Şensoy, and Nadia Magnenat-Thalmann. "Reputation mechanism for e-commerce in virtual reality environments." Electronic Commerce Research and Applications 13, no. 6 (November 2014): 409–22. http://dx.doi.org/10.1016/j.elerap.2014.08.002.

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37

Zhou, Zhili, Meimin Wang, Ching-Nung Yang, Zhangjie Fu, Xingming Sun, and Q. M. Jonathan Wu. "Blockchain-based decentralized reputation system in E-commerce environment." Future Generation Computer Systems 124 (November 2021): 155–67. http://dx.doi.org/10.1016/j.future.2021.05.035.

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38

Foroudi, Pantea, and Elisa Montes. "Corporate e-communication." Bottom Line 30, no. 3 (November 13, 2017): 201–15. http://dx.doi.org/10.1108/bl-08-2017-0023.

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Purpose The purpose of this paper is to examine the influence of corporate logo in organisations’ development of corporate e-communication. Design/methodology/approach This research model was designed based on previous studies on corporate logo, its antecedents on e-communication, corporate image and corporate reputation. Online survey was conducted for consumers and followers of the shopping social networking platforms (Facebook and Twitter) in Colombia. Findings Taking into account previous corporate constructs theories, the authors propose a new conceptual framework to explain how corporate e-communication interacts within an organisation’s structure and also to show that the consumer’s interaction in corporate e-communication platforms is based on the corporate logo perception held by consumers; as a consequence, the corporate reputation is affected. Originality/value This study contributes to the understanding and expansion of the organisation’s structure by introducing a new corporate construct, named “corporate e-communication”, defined as the digital interaction that an organisation has with its stakeholders; it involves everything it says, shows and does. However, there are a few other areas of concern with regard to consequences related to corporate image and corporate reputation, particularly in Colombian retail setting.

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Wijaya, Brendi, and Henilia Yulita. "Effect of Emotional Experience, Electronic Word of Mouth, Reputation, Customer Satisfaction on Loyalty." Ilomata International Journal of Management 1, no. 4 (October 26, 2020): 215–27. http://dx.doi.org/10.52728/ijjm.v1i4.164.

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Lion Air was chosen by the public as an airline because of its lower fares compared to other airlines. However, Lion Air also often creates problems in terms of service, namely passenger displacement due to delay. With a negative emotional experience will have an effect on reputation decline, due to electronic word of mouth by consumers who are dissatisfied with the service. This type of research uses quantitative methods. The population of this research is all consumers who have used Lion Air transportation services with a sample of 100 respondents. The data collection method uses purposive sampling method. Technical analysis using SMART PLS 3.0 consists of three types, namely instrument testing, prerequisite tests, and hypothesis testing. The results showed that consumer satisfaction is influenced by emotional experience, E-Wom is influenced by emotional experience, reputation is not influenced by emotional experience, loyalty is not influenced by customer satisfaction, E-Wom is influenced by customer satisfaction, reputation is influenced by consumer satisfaction, Loyalty is influenced by Reputation, Reputation is influenced by E-Wom, and Loyalty is also influenced by E-Wom.

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Cao, Huai Hu, Yan Mei Zhang, and Jian Ming Zhu. "A Trust Evaluating Model Based on Reputation with Multifactor for P2P E-Commerce." Applied Mechanics and Materials 58-60 (June 2011): 153–57. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.153.

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Trust plays an important role in the development and implementation of P2P e-commerce systems. This paper proposes a novel Trust Evaluating Model Based on Reputation with Multifactor. By introducing many comprehensive trust factors in computing trust level and improving the computing methods of the local reputation and global reputation, this model can not only accurately reflect the node’s trust level, but also reduce the time complexity in computing trust level. Experimental results show that the trust model can improve the rate of successful trading compared with the existing trust models, and can be effectively applied to the P2P e-commerce system.

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Herwin, Herwin, and Ferryal Abadi. "PENGARUH REPUTASI PERUSAHAAN DAN REPUTASI VENDOR TERHADAP KEPUTUSAN PEMBELIAN SECARA ONLINE DENGAN KEPERCAYAAN KONSUMEN SEBAGAI VARIABEL ANTARA." Jurnal Riset Manajemen dan Bisnis (JRMB) Fakultas Ekonomi UNIAT 3, no. 3 (October 31, 2018): 353–64. http://dx.doi.org/10.36226/jrmb.v3i3.161.

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This study aims to determine the effect of Corporate Reputation and Vendor Reputation of online purchasing decisions with consumer trust as a variable between. This is triggered from the phenomenon of the number of companies engaged in E-Commerce, but many are still failing. By looking at the big prospects in Indonesia, it is hoped that this research can find out what strategies can be done in order to succeed in E-Commerce. This research uses quantitative research method by conducting survey. Sampling method is purposive sampling. Validity and Reliability Test Results using SPSS v 20.0, and the results of hypothesis using path analysis. Corporate Reputation has a significant effect on Consumer Trust, as well as Vendor Reputation also has a significant effect on Consumer Trust. Then Consumer Trust also affects the Purchase Decision online. Keywords: Reputation, Company, Vendor, Trust, decision, buying

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Chen, Jianping, Nadine Tournois, and Qiming Fu. "Price and its forecasting of Chinese cross-border E-commerce." Journal of Business & Industrial Marketing 35, no. 10 (April 10, 2020): 1605–18. http://dx.doi.org/10.1108/jbim-01-2019-0017.

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Purpose Cross-border e-commerce in China has been booming in recent years. This paper aims to study pricing in Chinese cross-border e-commerce companies and focuses on the baby food market, which is simply examined as a case study to highlight broader implications. In this intensely competitive sector, the biggest challenge faced by such companies is ensuring that they are in a position to be able set prices in the short-term to maximize their competitive advantage and profitability. The study of pricing will help management to make correct operational decisions. Design/methodology/approach This study utilizes transaction data, which were obtained from the Taobao e-commerce platform. Taobao is the largest e-commerce retail platform in the world. We analyzed factors, including business models, homogeneity, reputation ratings and sales volumes, which may affect pricing. Findings This study found that consumers in the baby food sector of Chinese cross-border e-commerce are not price-sensitive. Consumers are reputation-rating-sensitive. The reputation ratings of sellers affect the price dispersion in e-commerce markets. The Core Price Dispersion Rate Model not only considers the prices but also takes sales volumes into account in the calculations. Finally, based on Gaussian processes, a model was developed for price forecasting in the area of cross-border e-commerce. The experimental results show that the proposed method is highly valuable for price forecasting. Originality/value This study provides a novel understanding of the baby food sector in the Chinese cross-border e-commerce market by examining the business model, price dispersion, reputation rating and correlation between the reputation of sellers, prices and sales volume. Furthermore, a model for price forecasting is proposed.

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Jin, Byoungho, Jin Yong Park, and Jiyoung Kim. "Cross‐cultural examination of the relationships among firm reputation, e‐satisfaction, e‐trust, and e‐loyalty." International Marketing Review 25, no. 3 (May 30, 2008): 324–37. http://dx.doi.org/10.1108/02651330810877243.

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Wang. "E-Satisfaction Ratings on Merchant Reputation Systems: An Exploratory Study." e-Service Journal 4, no. 1 (2005): 29. http://dx.doi.org/10.2979/esj.2005.4.1.29.

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Tian, Bo, Kecheng Liu, and Yuanzhong Chen. "Dynamical Trust and Reputation Computation Model for B2C E-Commerce." Future Internet 7, no. 4 (October 27, 2015): 405–28. http://dx.doi.org/10.3390/fi7040405.

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Khan, Salman, and Jacques Digout. "A Synthetic Literature Review and Prognosis of Corporate E-Reputation." Indian Journal of Computer Science 2, no. 2 (April 1, 2017): 7. http://dx.doi.org/10.17010/ijcs/2017/v2/i2/112039.

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JIANG, Shou-Xu. "A Reputation-Based Trust Mechanism for P2P E-Commerce Systems." Journal of Software 18, no. 10 (2007): 2551. http://dx.doi.org/10.1360/jos182551.

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Liang, Wang, Guo Yajun, and Qi Mei. "A Reputation-Based Trust Evaluation Model for P2P E-Commerce." International Journal of Distributed Sensor Networks 5, no. 1 (January 2009): 39. http://dx.doi.org/10.1080/15501320802533467.

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Wang, Ming. "E-Satisfaction Ratings on Merchant Reputation Systems: An Exploratory Study." e-Service Journal 4, no. 1 (2004): 29–40. http://dx.doi.org/10.1353/esj.2006.0005.

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Ghiasi, Hesam, Mohammad Fathian Brojeny, and Mohammad Reza Gholamian. "A reputation system for e-marketplaces based on pairwise comparison." Knowledge and Information Systems 56, no. 3 (November 29, 2017): 613–36. http://dx.doi.org/10.1007/s10115-017-1141-2.

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