Bad Ratings Research Articles

The Factors that Affect Customer Ratings in E-Commerce Company

In developing the e-commerce business in Indonesia, e-commerce companies must maintain customer satisfaction. In the e-commerce company, customer satisfaction can see from the ratings given by consumers. This research aims to find factors influencing consumers in providing ratings to improve services. The company’s current condition does not know the indicators when consumers give ratings. The current situation is decreasing order because the number of bad rating is higher and impact to profit company. This research uses several methods, such as the Unified Theory of Acceptance and Use of Technology (UTAUT), the Technology Acceptance Model (TAM), and product quality that influences ratings. The target respondents are consumers who have given bad ratings and have never been given a rating, with 326 respondents. The statistical analysis processing used was Partial Least Square (PLS) with SmartPLS v.4 tools. The results of the research concluded that the factors that influence bad rating respondents in giving ratings with significant positive results are the factors of perceived ease of use, social influence, and customer satisfaction, with an r-square rating value of 0.354 (moderate). From moderation, the variable with the most significant positive effect is the female gender. Meanwhile, respondents who have never been given a rating that has a significant positive impact are performance expectancy, social influence, and customer satisfaction, with an r-square value for ratings of 0.823 (strong). The results of this research concluded that there are several improvements to improve service, namely improving application algorithms, developing operational teams, and several strategies to overcome the impact of the covid pandemic.

Student Satisfaction Information System on Administrative Services in Information Engineering Study Program Muhammadiyah University Bengkulu

The level of student satisfaction with the services of the Administrative Services section of the Faculty of Engineering, University of Muhammadiyah Bengkulu is not yet known. To determine the level of student satisfaction in receiving these services, it is necessary to create a system that can measure the level of student satisfaction with the services provided. In conducting this research, the development method of the System Development Life Cycle (SDLC) is a gradual approach to analyze and build a system design using a specific cycle for user activities and the approach method used in measuring the level of satisfaction using a licker scale. This system is built with the XAMPP tool that can test applications without requiring an internet connection, PHP programming language and MySQL database. The results of the system made can help and make it easier to find out the level of student satisfaction with the services provided and the faculty in particular can quickly improve and improve the performance of services that get bad ratings. From the overall assessment, the value of service satisfaction level is 89.26 with a very good predicate. It is hoped that this application is always up to date so that it follows the development of Android-based technology.

A Cognitive Similarity-Based Measure to Enhance the Performance of Collaborative Filtering-Based Recommendation System

Advances in technology and high Internet penetration are leading to a large number of businesses going online. As a result, there is a substantial increase in the number of customers making online purchases and the number of items available online. However, with so many options available to choose from, users have to face the information overload problem. Several techniques have been developed to handle this, but the performance of the recommendation system (RS) has been recorded unprecedentedly. The collaborative filtering (CF) of RS is the most prevalent technique, which suggests personalized items to users based on their past preferences. The efficacy of this technique mainly depends on the similarity calculation, which the traditional or cognitive approach can ascertain. In the traditional approach, a similarity measure utilizes the user’s ratings on an item to compute the similarity. Most similarity measures in this approach suffer from either data sparsity and/or cold-start problems. To address both of them, a new similarity measure based on the Jaccard and Gower coefficients, the efficient Gowers–Jaccard–Sigmoid Measure (EGJSM), is proposed in this article. It also includes a nonlinear sigmoid function to penalize the bad ratings. The performance of EGJSM is evaluated by conducting experiments on benchmark datasets, and the results depict that the proposed technique outperforms several existing methods. Along with this, a cognitive similarity (CgS) measure has been proposed, which considers cognitive features such as genre and year of release along with rating information, to calculate similarity. The CgS method also outperforms the proposed EGJSM method and produces almost 4% and 1% lower mean absolute error (MAE) and root-mean-squared error (RMSE) values than that.

Kecemasan Berbahasa untuk Ketrampilan Berbicara Bahasa Arab pada Tingkatan Perguruan Tinggi

Speaking anxiety is a common phenomenon in foreign language teaching, but if this anxiety and fear continue to include students, the goal of learning to speak, namely to improve oral competence in Arabic, will be difficult to achieve.<strong> </strong>Therefore, this study aims to describe: (1) the level of language anxiety in Arabic speaking skills, (2) the factors that cause language anxiety in students' speaking skills, and (3) strategies that can be pursued to overcome language anxiety in students. student speaking skills. This research uses qualitative and quantitative methods (<em>mixed methods</em>) using questionnaires and interviews in collecting data. The results showed that: (1) that the students' anxiety was at the high level with a score of 2.69. (2) The factors that cause anxiety are quite diverse, including students' perceptions of speaking skills; the complexity of the Arabic language; lack of mastery of Arabic; do not master the topic of conversation; worried about getting bad ratings; lecturer assessment; and insecurity.

IT-enabled management of project complexity – An Action Design Research project

PurposeProject complexity has been researched much. The majority of publication is searching for law-like relations or development of descriptive frameworks. More prescriptive knowledge is needed to guide the project managers in navigating the project complexity in project managers' pursuit of success. Identifying the complexities of a given project is a real-world problem for project managers (Mikkelsen et al., 2021). The purpose of the paper is to investigate the research of prescriptive knowledge on the management of project complexity.Design/methodology/approachBased on a longitudinally case study, this paper uses Action Design Research (Sein et al., 2011) (ADR) to research the management of project stakeholder complexity. ADR is a variation of action research (AR) with inspiration from design science (Hevner et al., 2004) where an artifact is designed to solve a real-world problem. In this case study, an information system was configured in collaboration with the project managers of the recipient organization.FindingsThe findings from the research project are presented using the affordance theory (Gibson, 1977) as a framing concept and give special attention the affordance perception (Pozzi et al., 2014). Among the project managers, who were very engaged in the co-design, the majority refrained from activating the information system and got the outside view from the stakeholders. Interviews afterward identified “fear of bad project ratings from the stakeholder” as the main course of resistance to deploy the surveying information system.Originality/valueThe paper contributes on two levels. The paper presents a novel approach to researching project complexity based on engaging the stakeholder in generating a common perception of the ongoing state of the projects. The paper also contributes insights into reasons for reluctance on the part of the participants (the project managers) of the recipient organization and hereby adds to the understanding of the organizational change aspect of AR in the research of project management. The paper concludes with the identified benefits of using ADR in research on project complexity management and gives recommendations for future research.

The value of bad ratings: An experiment on the impact of distortions in reputation systems

We study the robustness of reputation management systems against positive and negative distortions. In a laboratory trust experiment with reputation management, we mimic a positive bias by exclusively offering the option to rate positively or to give no rating. As predicted by theoretical considerations, this bias leads to significantly less trust than a system that additionally offers a negative rating option. A system relying solely on negative ratings does not have such an adverse effect. This highlights the importance of negative ratings options for the effectiveness of reputation systems.

Reaksi Pasar Atas Pengumuman Anugerah Program Penilaian Peringkat Kinerja Perusahaan dalam Pengelolaan Lingkungan Hidup

This study aims to examine the market's reaction to information regarding the announcement of a company performance rating assessment program award in environmental management. Market reaction is measured by abnormal return around the announcement date of the environmental management program. This research is conducted at the Indonesia Stock Exchange. The population in this study are all publicly listed companies receiving PROPER awards listed on the IDX in 2018 for a total of 51 companies. Samples that met the purposive sampling criteria are 50 companies. The analysis technique used is one sample t-test and independent samples t-test. The results of this study indicate that there is a market reaction around the PROPER rating announcement date, and there is no different market reaction between companies with good ratings and companies with bad ratings. 
 Keywords: Event Study; Abnormal Return; PROPER.

To supervise or to self-supervise: a machine learning based comparison on credit supervision

This study investigates the need for credit supervision as conducted by on-site banking supervisors. It builds on a real bank on-site credit examination to compare the performance of a hypothetical self-supervision approach, in which banks themselves assess their loan portfolios without external intervention, with the on-site banking supervision approach of the Central Bank of Brazil. The experiment develops two machine learning classification models: the first model is based on good and bad ratings informed by banks, and the second model is based on past on-site credit portfolio examinations conducted by banking supervision. The findings show that the overall performance of the on-site supervision approach is consistently higher than the performance of the self-supervision approach, justifying the need for on-site credit portfolio examination as conducted by the Central Bank.

Usability Evaluation of KAI Access Application

The Government of Indonesia develops some distribution of transportation especially land transportation, i.e. train. This transportation only available in Java Island, but now available in Sumatra Island. The existence of this train was supported by the development of the Industry 4.0 which is train tickets purchased by Applications that can minimize cash payment, increasing the efficiency and effectiveness of customers. User ratings for KAI Access Application on Google Playstore is not good enough, there are still a lot of users who give complaints and bad ratings on this Application. From the data, there is a usability issue in this application. The purpose of this research is to evaluate KAI Access application with a usability approach in Sumatera Island which can be used as a basis for Increase performance of KAI Access application after comparing with Java Island users. This evaluation using a usability approach with the System Usability Scale (SUS) questionnaire, mapping complaints and task completion time for user performance. The result of this research are alternatives to improve this application such as redesign interface for home page and improvement of the database. Positive correlation is found between type of user (novice and expert) and origin of user (Java and Sumatra) where results show significant difference.

The Value of Bad Ratings: An Experiment on the Impact of Distortions in Reputation Systems

We study the robustness of reputation management systems against distortions in rating behavior. In a laboratory trust experiment with reputation management, we mimic a positive bias by exclusively offering the option to rate positively or to give no rating. As predicted by theoretical considerations, this bias leads to significantly less trust than a system that additionally offers a negative rating option. A system relying solely on negative ratings does not have such an adverse effect. This highlights the importance of negative ratings for the effectiveness of reputation systems.

Evaluation of Hospital Information Systems (HIS) in terms of their Suitability for Tasks

In the context of hospital information systems (HIS), "suitability for the task" refers to several factors, including not imposing additional tasks on users, executing everyday activities in their entirety, and displaying all relevant information on the screen. In this descriptive cross-sectional study, a multi-stage sampling strategy was utilized to select hospitals to participate in the study. In other words, the first thing done was to locate hospitals with companies that supplied them with health information systems. Then, one hospital was selected among those that were provided funding by each of the companies. The ISO Metric Standard Questionnaire 9241 was utilized for this investigation. The evaluation of HIS aptitude for the job will be based on his responses to these 15 questions in the questionnaire. The data were examined by employing descriptive tests and the software SPSS. According to the investigation results, the average number of HIS characteristics suitable for the undertaking was 3.04 out of 5. This feature has an average rating of 2.96 out of 5 stars from paraclinical users. The scores of 3.03 and 3.13 given by secretaries and nurses, respectively, are presented here. Items that received bad ratings, such as the imposition of tasks that were not within the user's obligations, highlight the fact that the majority of users consider that such systems are not following their responsibilities, despite all of the claims that have been made regarding the benefits of computer information systems in the field of medicine. In other words, these kinds of systems have not only failed to simplify the regular duties of their users, but they have also resulted in the users having to execute those actions multiple times. The users initially write the data down on paper before entering it into the digital information systems. As a result, those responsible for developing computerized information systems used in healthcare should emphasize the appropriateness of these systems for the job.

Analisis Reaksi Pasar Atas Pengumuman Peringkat Kinerja Perusahaan Dalam Pengelolaan Lingkungan Hidup

This study aims to determine the market reaction to the PROPER announcement event and whether there are differences in market reactions between good ratings and poor PROPER ratings. This research is an event study with a window of events for 5 days. The study was conducted on PROPER participating companies listed on the Indonesia Stock Exchange from 2015 to 2017. The number of samples that met the criteria were 39 companies. PROPER announcements are measured using abnormal returns. The analysis technique used is the one sample t-test and the independent t-test. The test results show that the PROPER announcement was reacted negatively by the capital market, and there was no difference in market reaction between good ratings and bad ratings.
 Keywords : Event Study; Abnormal Return; Environmental Performance; PROPER.

MAdLens: Investigating Into Android In-App Ad Practice at API Granularity

In-app advertising has served as the major revenue source for millions of app developers in the mobile Internet ecosystem. Ad networks play an important role in app monetization by providing third-party libraries for developers to choose and embed into their apps. Various ad mediations help developers manage all of the ad libraries used in apps to show the best available ad among received ads from different ad network servers. However, developers lack guidelines on how to choose from hundreds of ad networks or ad mediations and various ad features to maximize their revenues without hurting the user experience of their apps. Our work aims to provide app developers guidelines on the selection of ad networks, ad mediations, and ad placement by observing current common practices. To this end, we investigate 838 unique APIs from 207 ad networks which are extracted from 277,616 Android apps, develop a methodology of ad type classification based on UI interaction and behavior, and perform a large scale measurement study of in-app ads with static analysis techniques at the API granularity. We found that developers have more choices about ad networks than several years before. Most developers are conservative about ad placement and about 77 percent of the apps contain at most one ad library. Besides, the likeliness of an app containing ads depends on the app category to which it belongs. Furthermore, we propose a terminology and classify mobile ads into five ad types: Embedded, Popup, Notification, Offerwall, and Floating. Also, our research shows that it is a better solution for developers to integrate ad libraries with ad mediation feature in their apps because it may avoid bad ratings and improve user experience. And in our findings, more than 95 percent of embedded, popup, notification, and offer ads locate in the zero activity (main activity), the first activity and the second activity of Android apps. More interestingly, developers tend to put high aggressive ads on activities which need deeper user interaction. Our research is the first to reveal the preference of both developers and users for ad networks, ad mediation feature and ad types.

Credence Goods Markets and the Informational Value of New Media: A Natural Field Experiment

Credence goods markets are characterized by pronounced informational asymmetries between consumers and expert sellers. As a consequence, consumers are often exploited and market efficiency is threatened. However, in the digital age, it has become easy and cheap for consumers to self-diagnose their needs using specialized webpages or to access other consumers' reviews on social media platforms in search for trustworthy sellers. We present a natural field experiment that examines the causal effect of information acquisition from new media on the level of sellers' price charges for computer repairs. We find that even a correct self-diagnosis of a consumer about the appropriate repair does not reduce prices, and that an incorrect diagnosis more than doubles them. Internet ratings of repair shops are a good predictor of prices. However, the predictive valued of reviews depends on whether they are judged as reliable or not. For reviews recommended by the platform Yelp we find that good ratings are associated with lower prices and bad ratings with higher prices, while non-recommended reviews have a clearly misleading effect, because non-recommended positive ratings increase the price.

Credence Goods Markets and the Informational Value of New Media: A Natural Field Experiment

Credence goods markets are characterized by pronounced informational asymmetries between consumers and expert sellers. As a consequence, consumers are often exploited and market efficiency is threatened. However, in the digital age, it has become easy and cheap for consumers to self-diagnose their needs using specialized webpages or to access other consumers' reviews on social media platforms in search for trustworthy sellers. We present a natural field experiment that examines the causal effect of information acquisition from new media on the level of sellers' price charges for computer repairs. We find that even a correct self-diagnosis of a consumer about the appropriate repair does not reduce prices, and that an incorrect diagnosis more than doubles them. Internet ratings of repair shops are a good predictor of prices. However, the predictive valued of reviews depends on whether they are judged as reliable or not. For reviews recommended by the platform Yelp we find that good ratings are associated with lower prices and bad ratings with higher prices, while non-recommended reviews have a clearly misleading effect, because non-recommended positive ratings increase the price.

Electronic physician ratings and reviews process.

209 Background: According to JAMA, Public Awareness, Perception, and Use of Online Physician Rating Sites; 35% of patients selected a physician based on good ratings, and 37% avoided one with bad ratings. Yet, there exists a stark difference between unstructured (i.e. Yelp) online reviews as compared to validated survey-generated data. A national network of hospitals that specializes in treating patients with complex cancer had been collecting patient satisfaction data using a validated tool administered by a 3rd party for some time. An electronic physician rating and review process was implemented as an adjunct to that survey process, providing a new mechanism for consumers visiting the networks’ website with accurate information about patients’ satisfaction with its oncologists. Methods: Physician ratings are obtained directly from patients who had an encounter using two specific questions regarding confidence and likelihood to recommend. Ratings are posted by physician and maintained on a 12-month rolling basis once a minimum of 30 ratings is achieved. Likert scale survey data are converted to a one-to-five star rating. De-identified verbatim comments are also posted. Criteria are in place to review comments prior to posting with limited exclusions, such as comments containing PHI or slanderous content. Physicians receive an email to review comments 15 days prior to posting, allowing a process for advance notice or appeal. Both positive and negative reviews are published. Results: Physician performance scores were 4.7 stars pre-launch compared to 4.8 stars post-launch. Additional performance statistics are provided below. Conclusions: Sharing information on the talent of physicians is an important component of transparency and arming patients with information to make informed treatment decisions. As a result, physicians have become more engaged with their data and utilizing reviews to identify improvement opportunities. This translates to a culture of accountability and deepened understanding of patients’ perceptions about care.[Table: see text]

The influence of online ratings and reviews on hotel booking consideration

This paper analyses the impact of good vs. bad ratings during the first stage of the decision-making process when booking a hotel. This study tested the interaction between numerical ratings given to a product or service and the number of verbal reviews it has received while controlling subject susceptibility to interpersonal influence. The study conducted a full factorial between subjects design of 2 levels of ratings (good vs. bad) x 2 levels of reviews (high vs. low) in a decision-controlled setting. Results suggest an asymmetric interaction between numerical ratings and reviews: When the rating is good, the trust in the rating depends on the number of reviews, but conversely, if the rating is bad, the number of reviews has no effect on how trustworthy the rating is. Academic and managerial implications of this study and scope for future research have also been discussed.

The economic functioning of online drugs markets

The economic functioning of online drug markets using data scraped from online platforms is studied. Analysis of over 1.5 million online drugs sales shows online drugs markets tend to function without the significant moral hazard problems that, a priori, one might think would plague them. Only a small proportion of online drugs deals receive bad ratings from buyers, and online markets suffer less from problems of adulteration and low quality that are a common feature of street sales of illegal drugs. Furthermore, as with legal online markets, the market penalizes bad ratings, which subsequently lead to significant sales reductions and to market exit. The impact of the well-known seizure by law enforcement of the original Silk Road and the shutdown of Silk Road 2.0 are also studied, together with the exit scam of the market leader at the time, Evolution. There is no evidence that these exits deterred buyers or sellers from online drugs trading, as new platforms rapidly replaced those taken down, with the online market for drugs continuing to grow.

How Do Platform Participants Respond to an Unfair Rating? An Analysis of a Ride-Sharing Platform Using a Quasi-Experiment

Online rating systems can lead, on occasion, to reviews that are unfair or unrepresentative of the true quality provided. On the one hand, receiving an unfairly low rating once, might induce participants to exert more effort and receive a better rating the next time. On the other hand, it might dispirit participants and make them exert less effort. We use data from a ride-sharing platform in India where driver ratings were made particularly salient to the driver after each trip. Our data suggests that if a customer experiences a ride cancellation, they are more likely to unfairly blame the replacement driver. We use this as a exogenous source of unfair negative ratings for the driver. We show that drivers are more likely to respond negatively to a bad rating and receive subsequently bad ratings if they were blameless for the previous negative rating. This effect is larger in contexts where there is a higher potential for an emotional response and when there is a greater need for driver skill in the subsequent ride. These unfair ratings can lead drivers to leave the platform, suggesting a broader negative effect of unfair negative ratings on platform participation.

How Do Platform Participants Respond to an Unfair Rating? An Analysis of a Ride-Sharing Platform Using a Quasi-Experiment

Online rating systems can lead, on occasion, to reviews that are unfair or unrepresentative of the true quality provided. On the one hand, receiving an unfairly low rating once, might induce someone a platform supplier to exert more effort and receive a better rating the next time. On the other hand, it might dispirit suppliers and make them exert less effort. We use data from a ride-sharing platform in India where driver ratings were made particularly salient to the driver after each trip. Our data suggests that if a customer experiences a ride cancellation, they are more likely to unfairly blame the replacement driver. We use this as a exogenous source of unfair negative ratings for the driver. We show that drivers are more likely to respond negatively to a bad rating and receive subsequently bad ratings if they were blameless for the previous negative rating. This effect is larger in contexts where there is a higher potential for an emotional response and when there is a greater need for driver skill in the subsequent ride.