The electronic exchange of health-related data can support different professionals and services to act in a more coordinated and transparent manner and make the management of health service networks more efficient. Although mental health care is one of the areas that can benefit from a secure health information exchange (HIE), as it usually involves long-term and multiprofessional care, there are few published studies on this topic, particularly in low- and middle-income countries.The aim of this study was to design, implement, and evaluate an electronic health  platform that allows the technical and informational support of a Brazilian regional network of mental health care. This solution was to enable HIE, improve data quality, and identify and monitor patients over time and in different services.The proposed platform is based on client-server architecture to be deployed on the Web following a Web services communication model. The interoperability information model was based on international and Brazilian health standards. To test platform usage, we have utilized the case of the mental health care network of the XIII Regional Health Department of the São Paulo state, Brazil. Data were extracted from 5 different sources, involving 26 municipalities, and included national demographic data, data from primary health care, data from requests for psychiatric hospitalizations performed by community services, and data obtained from 2 psychiatric hospitals about hospitalizations. Data quality metrics such as accuracy and completeness were evaluated to test the proposed solution.The eHealth-Interop integration platform was designed, developed, and tested. It contains a built-in terminology server and a record linkage module to support patients’ identification and deduplication. The proposed interoperability environment was able to integrate information in the mental health care network case with the support of 5 international and national terminologies. In total, 27,353 records containing demographic and clinical data were integrated into eHealth-Interop. Of these records, 34.91%  were identified as patients who were present in more than 1 data source with different levels of accuracy and completeness. The data quality analysis was performed on 26 demographic attributes for each integrable patient record, totaling 248,248 comparisons. In general, it was possible to achieve an improvement of 18.40%  in completeness and 1.10%  in syntactic accuracy over the test dataset after integration and deduplication.The proposed platform established an eHealth solution to fill the gap in the availability and quality of information within a network of health services to improve the continuity of care and the health services management. It has been successfully applied in the context of mental health care and is flexible to be tested in other areas of care. The care of mental disorders frequently requires a coordination of efforts among different health care professionals, services, and care levels  . There iHowever, all around the world, an adequate continuity of care—defined as the coordination and integration of different health care events to meet patient care needs in a coherent, connected, and consistent manner —is commoAn extensive research area in computer science that seeks to assist in the problem of fragmentation of health care information systems is interoperability and data integration. The Institute of Electrical and Electronics Engineers Standards Computer Dictionary defines interoperability as “the ability of two or more systems or components to exchange information and to use the information that has been exchanged” . In the Health information systems that offer support to physicians and other health professionals are often not integrated , and theCoffey et al  point ouBrazil is a middle-income country with the world’s fifth largest population. Since 1988, a complex national health system  has been implemented, with responsibilities in the funding and management divided between the 3 federated levels . The national health system is also composed of a mix of public and private, and profit and nonprofit services . As in oConsidering the need for a computational environment to facilitate the exchange of health information to improve the continuity of care between care levels, the eHealth-Interop computing platform was designed and deployed. The main objective of the eHealth-Interop platform is to provide a service for the exchange of standardized information on mental health, promoting the improvement of the quality of information and its availability in a transparent way for all the regional services responsible for mental health care.In Brazil, public mental health care has to be carried out through regional public mental health care networks (MHCNs), whose objectives are to guarantee the continuity and integrality of care through the different services and care levels .The XIII Regional Health Department (RHD) covers over 26 municipalities , with apThe extreme financial and administrative decentralization of public health services in Brazil  results in enormous heterogeneity of computerized information systems used by different services and professionals. For example, within the XIII Region of Health of the State of São Paulo, each of its 26 municipalities has 1 specific information system. Furthermore, each state-sphere health service has its own information system. The same happens with the private health services hired by the municipal or state public authority. Each one has its own computerized information system that is not shared with other services.Sistema de Informação em Saúde Mental; in English, mental health information system) [In the last 5 years, the Brazilian Ministry of Health has made available for primary care–level services a computerized information system called e-SUS AB  as part  system) , which hAlthough the different services present in the network have mechanisms to integrate care between them, as recommended by Brazilian health legislation (such as the SISAM itself and periodic meetings between services representatives) ,18, fromTherefore, information loss, data duplicity, lack of consistency, and rework are common. In this scenario, the work reported here was focused on the integration of 5 information sources from different information systems that support MHCN in the various care levels. The information sources are as follows: SISAM; e-SUS AB; data from 2 state psychiatric hospitals; and access to Web services of the Brazilian Ministry of Health for integration, with patients’ demographic data through the national health card.In the eHealth-Interop platform, the interoperability data model corresponds to the information set that is exchanged and made available to health professionals at different care levels. To define this set of information, we analyzed the main processes involved in patient care. The identification of the main processes occurred in meetings with the professionals involved in the MHCN using a sociotechnical approach. With this approach, potential users and technical developers act together during the planning, development, and implementation of computational solutions ,22. The Associação Brasileira de Normas Técnicas  [The documents analyzed include records used in MHCN logistic instruments, national standards, and international documents. The records used are SISAM demographic form and a regional mental health specialized hospital discharge summary. Furthermore, the minimal health dataset structured by the Brazilian Ministry of Health was analyzed , togethermatics) .Besides this set of national documents, documents from the United Kingdom, Canada, and Australia were also analyzed. From Australia, the following documents were analyzed: national minimum dataset—admitted patient mental health care , nationaAs a result of the described process, a set of information was defined for each of the 4 events: demographic form, with patient demographic and identification information; primary care assessment, with clinical information from primary care; admission form, with information of the hospitalization request and the admission moment; and the discharge summary, with data of the whole hospitalization process. These information sets were reviewed, reformulated, and approved by a group of around 20 professionals, representative of the several health services and municipalities involved in MHCN.The defined interoperability data models serve as a conceptual basis for the HIE. The eHealth-Interop platform acts as a central repository of the data exchanged. All communication is performed through Web services available at the eHealth-Interop. Each data source, which is the information system in the different health services, sends and queries data from its patients through Web service clients that communicate with eHealth-Interop.The process of sending patient data can be compared with the extraction-transformation-load steps in a classical data integration process. First, the data of interest are extracted from the local databases in the format that is specific to each information system. Then, the data are transformed to the interoperability data model previously defined. These transformed data are then uploaded to eHealth-Interop using specific end points provided by the platform Web services application programming interface (API). Thereafter, the data undergo a syntactic and duplicity analysis, aiming to improve the quality of the information. If the patient’s record is already recorded in eHealth-Interop, the new information will be aggregated, making a more complete record.The analysis of the effectiveness of quality improvement, obtained from data integration provided by the proposed interoperability solution, was performed through the measurement of data quality. Data quality metrics used were as follows:Completeness represents the degree to which a given collection of data has the data it should represent. Data completeness is defined as the level of missing data for a data elementSyntactic accuracy represents the degree to which the given data are correct and reliable. Syntactic accuracy measures the degree to which the given data correspond to a possible value in the dataset, for example, age must be between 0 and 120 yearsDuplicity represents the degree to which the given data are unnecessarily duplicated within a dataset of interest, for example, 2 or more records belonging to a same record in the same data sourceThe data quality metrics of completeness and syntactic accuracy were calculated considering the data sources in 3 different moments during the data interoperability process. In the first moment, the data are available based on as they are originally represented in the different data sources. In a second moment, the data are available considering the normalization process into the data source adapters. During this process, each value of each attribute is transformed (if necessary) to conform to the defined interoperability data model. In a third moment, different records belonging to the same patient, which are originally in different sources, are integrated into a single record, and then the quality metrics are applied over them.The duplication analysis was performed to verify the use of the record linkage (RL) algorithms and was applied over a set of records in the second stage that did not have deterministic identifiers.During the design and implementation stage of eHealth-Interop and its components, 2 health information standards served as the basis: the Integrating the Healthcare Enterprise (IHE) and the Health Level-7 Fast Healthcare Interoperability Resources (HL7-FHIR).IHE is a joint initiative initially formed by the HIMSS and Radiological Society of North America in 1988 . The IHEFHIR is an HL7 standard that seeks to enable the construction of effective interoperability between applications using Web development standards .The general principles of development enforced by HL7-FHIR, such as RESTful architecture; use of Web development standards such as JavaScript Object Notation (JSON) and open authorization (OAuth); and definition of concise and flexible data models have been adopted for the management of clinical and demographic data in eHealth-Interop. The HL7-FHIR terminology module specification was implemented for the eHealth-Interop terminology server. The IHE PIX profile served as the basis for the overall planning of the patient identification process, although not completely adopted. In this context, eHealth-Interop acts as the patient actor identifier cross-reference manager, and we rely on the patient identity feed, patient identity management, and PIX query transactions to define some of the services responsible for managing demographic data.The architecture of a computational system seeks to define the general structures such as its main elements, the relationships between these elements, and the properties of the elements and these relationships . AccordiTaking into account that regional care delivery is made up of different actors located at different points in a given region, the Web environment was defined as the basis for the integration platform following a client-server architecture. The proposed conceptual architecture of eHealth-Interop is shown in Each layer has specific components. Functionalities of each component are described below.In the data layer, data are stored following a dual model, ensuring the differentiation between demographic and clinical information. This distinction seeks to establish a solid foundation for patient identification algorithms and at the same time make the database flexible to be extended to different application contexts in the medical field . AnotherThe semantic layer is mainly composed of a terminology server responsible for the storage of codifications, terminologies, and ontologies as well as their relationships. It also comprises the clinical and sociodemographic concepts that compose the information models and the schema management module that connects the information model with the terminologies and communicates with databases.The communication layer is responsible for generating the service API from the information models represented in the semantic layer and for promoting a secure communication by the security module that verifies the authentication and authorization of the person responsible for the process of data sending and retrieval. The exchange of information from the data source to the interoperability platform is done through adapters that are software agents that translate the source schema into the global model provided by the service interface.Medical vocabulary is highly heterogeneous, and several information artifacts are constantly emerging aiming to standardize not only medical concepts but also relationships between them. These artifacts are usually named codifications, terminologies, controlled vocabularies, and ontologies, among others . The terThe main classes implemented are CodeSystem, ConceptDefinition, ConceptMap, and mapping . CodeSysIn the medical context, or specific mental health, CodeSystem represents more complex terminologies such as Systematized Nomenclature of Medicine (SNOMED) , classifTo support the information model defined for continued care in the MHCNs, 5 terminologies have been used:ICD-10International Classification of Functioning, Disability, and HealthInternational Classification of Primary CareTable of Procedures, Medications and Orthotics, Prostheses, and Materials of the Unified Health System in BrazilBrazilian Classification of OccupationsIn addition, local value sets were created to represent different concepts such as sex, marital status, and sexual orientation, among others. These codifications, for the most part, are in agreement with those used in the national information system for primary care or based on information models from a national standard for discharge summary.RL can be defined generally as the process of identifying records from different sources that correspond to the same real-world entity . The RL The health information system usually implements the RL based on a deterministic method in which certain precise rules are defined to guarantee the uniqueness of a patient’s record. In mental health context and in other areas such as medical emergencies, it is often not possible to obtain a unique identification or reliable information from patients. Therefore, using a deterministic method for patient RL is not always possible. In addition, duplicity may occur from erroneous manual registration by users operating health information systems. These errors and lack of information can be propagated in a scenario of HIE in which several systems are involved.To solve this kind of inconsistency, eHealth-Interop comprises an RL module that uses a 2-stage verification to ensure the uniqueness of the patient record. This process is summarized in Information security and privacy are important aspects of any information system. In the medical field, it usually becomes a major barrier for the exchange of health information between different institutions . The conThe division of the data layer architecture in 2 different repositories, which store patient demographic information and clinical information separately, allows these repositories to be made available on different physical locations with different access methods, increasing security at system level.All data access is done through Web services that use the HTTPS protocol, establishing a secure communication channel between the client and the server, where the data are encrypted . Every cA hierarchy of user access was also implemented following the model already defined by MHCN professionals. In this model, the professionals of the municipal health services have access to the patient’s data only from their own municipality, allowing these data to be accessed by another service in case of a transfer. The regional hospital services have access to the data about those patients who are referred to them. The access is provided based on the OAuth2 protocol . The data priori in clinical documents that are exchanged during different moments of the patient care process. A Web tool was also developed to assist the construction of adapters displaying all the services available in eHealth-Interop as well as how to access them  are provided. This Web application also provides access to a timeline of patient care events .The implementation of this conceptual architecture was made using the LoopBack framework  and was The software API Dedupe  was usedThe eHealth-Interop performance with the dataset available for testing was satisfactory, with no delay during its use (less than 1 second time of response). It is also important to consider that the set of events that generate access to eHealth-Interop simultaneously is low. Stress testing is needed for scenarios where a much larger volume of data is used concurrently.A total of 27,353 patient health records were obtained from the 5 data sources used in this work for a period from 2011 to 2016. Out of these, 9547  records have been integrated in eHealth-Interop platform. In these records, the same patient is present in at least two different sources of information with the same identification data. The total number of unique patient records after integration was 4252, which means there were approximately 2.25 records per patient in the original dataset. The number of data sources having the same patient’s record are presented in Completeness and syntactic accuracy analyses were performed over patients’ demographic data. In total, 26 different attributes have been analyzed. For each attribute of each record, a value of 1 or 0 of completeness was assigned, based on the presence or absence of any data. Thereafter, the syntactic accuracy analyses were performed for those attributes with completeness value equals to 1. The syntactic accuracy analysis was done at attribute level for each patient record. Rules of syntactic analysis were defined for each attribute. Some of these rules are demonstrated in Then, each attribute value was tested according to the defined rule of the respective attribute. For example, if the patient has the birth date as February 2, 1970, then the rule is applied to verify if this value is a valid birth date. If the value passes in the test, then it has a value of syntactic accuracy equal to 1, otherwise the value will be zero. general subgroup consists of general demographic information such as name, mother’s name, father’s name, gender, and date of birth. The identification subgroup is composed of key attributes for patient unique identification, including identifiers used at national and local health level. The contact subgroup includes residential telephone, cell phone number, and email. The address subgroup includes the residence address information of the patient such as city name, street name, and house number. Results presented in In case of inconsistent data (2 different birthdates) when performing the entity integration, the value that is syntactically correct is adopted. If both values pass the test, the one from the record with highest value of completeness is adopted. Nevertheless, all the original data from both integrated records are stored before the integration. It is possible to change the canonical record later.For duplicity analysis, a cured dataset was organized with records that did not have unique identifiers. Then, a semiautomatic strategy was conducted: initially the RL module was used to perform a preselection of possible duplications and then, in the next step, each duplication result was manually verified for the determination of a true positive set of duplicates.The RL algorithm has been configured to take into account the patient’s name and mother’s name because they have 100% of completeness after data integration. The adopted threshold was 0.75 (referring to the probability of finding a duplicity), seeking for a high sensitivity for duplications detection. From a total of 6427 records tested, 1066 duplications were automatically preidentified, and from those, 226 were manually confirmed. The duplicity analysis served as proof of concept of the RL module with the pre-established settings.Coordination and continuity of care at different care levels have been a challenge in many health systems. Major informational barriers for continuity of care are the lack of support information mechanisms to ensure information exchange among health providers. Health information systems are important tools to overcome these barriers, but fragmentation and heterogeneity, particularly prominent in the Brazilian national health system, do not allow to achieve the greatest advantages from their use.To solve this kind of limitation, a computational interoperable health care platform was designed and deployed to establish an HIE environment. In eHealth-Interop, sociodemographic and clinical information are split into 2 different repositories, aiming to provide data security and extensibility.In the definition of the interoperability information model, in a joint decision with health professionals, it was decided to consider as much as possible of the defined national standards, while taking into account the other documents already used locally by the services and some international documents as well. Some concepts were out of context with respect to mental health, such as surgical procedures performed and allergies. Despite this, the strategy of keeping this information as optional in the data model was adopted. The standardization and use of international documents allows a comparison with other services and contexts.Although there are several initiatives for HIE, few of these works are applied in the context of mental health. In this context, some characteristics are quite relevant from the point of view of information sharing, such as a greater number of patient passages by different health services, often generating more readmissions and patient’s demographic information not always reliable, generating patients without unique identifiers. The eHealth-Interop acts as integration middleware, flexible to allow the sharing of information, even in situations of low reliability but having mechanisms to improve quality and ensure entity integration such as the RL module and the terminologies service.Another important result of this work was the measurement of data quality metrics to gauge the impact of the eHealth-Interop platform in informational continuity of care, as impact of HIE are not yet adequately studied ,50.In the mental health use case described, the eHealth-Interop supported HIE between primary health care and mental hospital care, but it was not possible to conduct tests with specialized ambulatory care data. However, the platform is able to automatically generate the Web services API and the database schema to store this information if necessary.Although the HL7-FHIR standard and the IHE PIX profile have been used as the basis for the definition of eHealth-Interop architecture and the interoperability model, they were not fully adopted. It was not possible to fully adopt the standards, mainly because it would be highly costly to enforce the adaptation by the stakeholders involved. It was then opted for as an intermediate strategy, where the basic principles were adopted but with a more flexible and simplified approach, allowing greater adaptation to the client systems that are part of the MHCNs. A future step will be the conformation of the API involving clinical and demographic data management for the HL7-FHIR standard and not just the terminology service.Another limitation of this project is that in the mental health use case, there is no mapping between the concepts of the adopted terminologies. The eHealth-Interop supports interterminology mapping; however, there was no need to translate concept from 1 terminology to another for the initial application.Several reviews analyzing the usage, barriers, facilitators, impact, and cost of HIE have been conducted ,49-51. LIn the technical domain, there are several papers proposing the implementation of platforms for the exchange of health information -55. YuksThere are few HIE studies in the context of mental health. Cifuentes et al  analyzedAlthough there are several studies and proposals for establishing an HIE environment, this remains an open problem, and its use is still limited . In thisThe eHealth-Interop is a computing platform designed for health information system interoperability. This proposal was successfully implemented and tested in the context of mental health care. This platform has been built to be (1) flexible, so it can be applied in other scenarios and clinical domains and (2) robust, so records of patients with little information can be integrated and completed.As future work, we intend to support the creation of alerts and automatic warnings based on specific process, for example, when a patient is hospitalized, a warning is generated for a certain health service warning about the event. We also intend to enable semantic querying using a SPARQL end point and implement algorithms to help the process of semantic markup, as well as add similarity functions to the terminology server, allowing a broad approach in concept searching.


The aims of this paper are: to provide a comprehensive introduction to eDia, an online diagnostic assessment system; to show how the use of technology can contribute to solve certain crucial problems in education by supporting the personalization of learning; and to offer a general reference for further eDia-based studies. The primary function for which the system is designed is to provide regular diagnostic feedback in three main domains of education, reading, mathematics, and science, from the beginning of schooling to the end of the 6 years of primary education. The cognitive foundations of the system, the assessment frameworks, are based on a three-dimensional approach in each domain, distinguishing the psychological (reasoning), the application, and the disciplinary (curricular content) dimensions of learning. The frameworks have been carefully mapped into item banks containing over a 1,000 innovative (multimedia-supported) items in each dimension. The online assessments were piloted, and the system has been operating in experimental mode in over 1,000 schools for several years. This paper outlines the theoretical foundations of the eDia system and summarizes how results from research on the cognitive sciences, learning and instruction, and technology-based assessment have been integrated into a working system designed to assess a large population of students. The paper describes the main functions of eDia and discusses how it supports item writing, constructing tests, online test delivery, automated scoring, data processing, scaling and the provision of feedback both for students and teachers. It shows how diagnostic assessments can be implemented in school practice to facilitate differentiated instruction through regular measurements and to provide instruments for teachers to make formative assessments. Beyond its main function , the eDia platform has been used for assessments in a number of areas from pre-school to higher education both in Hungary and in a number of other countries as well. The paper also reviews results from eDia-based studies and highlights how technology-based assessment extends the possibilities of educational research by making more constructs measurable. The eDia online assessment system has been built and developed by the Centre for Research on Learning and Instruction, University of Szeged. The principal function for which the system is designed is to provide regular diagnostic information in three main domains of education, reading, mathematics, and science, from the beginning of schooling to the end of the 6 years of primary education. In its present form, the eDia system is an integrated assessment system that is based on sophisticated frameworks and supports assessment processes from item development through test administration and data analyses to well-interpretable feedback. It is one realization of the “integrated, learning-centered assessment systems” envisioned by One of the main challenges of school education stems from the fact that students are different. Looking at the problem from a historical perspective, two main approaches may be identified as school systems have attempted to respond to this challenge: (1) selecting students  in the hope that homogeneous classrooms can be set up and (2) accepting different students for heterogeneous classrooms, then differentiating instruction to adjust teaching to the different individual needs of the students . The first option has failed, mostly for two reasons: (1) students are different not only in one dimension but also in a number of different ways, with the differences changing dynamically over time; therefore, (2) the intention of selection has generally resulted in social selection (segregation) with numerous negative side effects. The second option is more promising, and a number of progressive initiatives have emerged in recent decades. However, there have also been a great many difficulties that have stood in the way of personalizing learning; among these, the most prominent is continuously identifying the critical differences between students, differences that determine successful learning options. The most crucial issue in teaching a heterogeneous classroom is teaching students with temporary or permanent difficulties in learning, thus requiring that the difficulties that block their progress be identified.From a cognitive point of view, the core of the problem was best conceptualized by Ausubel in his frequently cited observation: “The most important single factor influencing learning is what the learner already knows. Ascertain this and teach him accordingly” , p. vi. In this paper, we first outline the theoretical foundations of the eDia system, including the role of diagnostic assessment, the content of assessment, and the ways to use feedback. Then, we introduce the eDia system, describe its structure, and highlight how technology serves its functions. Finally, we review research studies that have been carried out using eDia.Throughout this paper, we emphasize that there are a number of innovations that technology brings into numerous aspects of instructional processes, including assessment. However, currently, there is still unexploited potential in the use of technology, including the possibilities of personalizing learning, adjusting teaching and learning processes to the individual needs of students. From a cognitive point of view, if students are always taught what they are prepared for , then they will better comprehend and master the teaching material. From an affective perspective, if each student individually always faces an optimally challenging learning task  In research and development, there is a shift from summative to formative assessment, which provides immediate feedback and direct support for learning. (2) Technology-based assessment has shown enormous progress in the past decade, and ICT infrastructure in schools has improved so that assessment can enter into everyday school practice. (3) Progress in cognitive and educational psychology has produced results which have not yet been exploited in practice and which may contribute to a solution for certain crucial problems, especially in the first year of schooling. (4) Finally, a number of promising models for personalizing learning has had limited influence on practice, mostly because of the lack of easy-to-use assessment instruments. Although efforts within this latter (4) trend highlight the need for regular diagnostic feedback and the reformed teaching methods provide adequate educational context for the assessments, in this section, we only deal in detail with the first (1–3) trends as they have determined the development of the eDia system more directly.Large-scale international assessment programs  have had an immense impact on the development of educational systems in many different ways and have inspired the introduction or expansion of national assessment programs. These programs have also advanced testing in a number of areas, including framework development, test administration, data analyses, and reporting. This progress has also highlighted some deficiencies in educational assessment from the perspective of practice as well, for example, the long time between test administration and feedback, the limited usefulness of summative test results with regard to personalized intervention, and the lack or limitations of student-level feedback in general. Another source of dissatisfaction with testing has been the way summative tests have been used in certain countries, especially for high-stakes assessments, e.g., for test-based accountability. These types of testing have caused some negative effects, such as teaching for testing and test score inflation . Although there is a need for frequent personal feedback from teachers, the subjective nature has prompted the use of objective instruments; thus, formative tests have been proposed for this purpose. As these tests have been customized and adjusted to contexts and actual needs, they have usually been teacher-made tests of questionable psychometric quality. Formative tests have been used most systematically in personalized models of instruction, but in any case, their production, administration, and scoring have required immense resources. The use of technology has been proposed to solve these problems, to support certain aspects of the assessments  or to deAlthough technology-based assessment (TBA) is almost as old as the computer itself, modern TBA has a much shorter history. Its potential in assessment has been clear for decades, but it has required several initiatives and the development of the infrastructure at schools to fulfill its promise. We review here only a few major projects and programs that have aided in the realization of eDia as well.The European Union has launched several initiatives to modernize education, including the expansion of educational assessments to new areas with new technologies. The EU’s Joint Research Centre has organized conferences and workshops to collect experience with TBA projects . One sucThe Assessment and Teaching of 21st-Century Skills (ATC21S) project was located at the intersection of two major trends in research and development: the need to re-define the purpose of education in the new millennium with a greater focus on the skills required in modern societies and to make these skills measurable through TBA. In the first phase of the project, four working groups were formed to define the targeted skills  and to eThe PISA assessments have had an impact on the development of TBA in two major ways: (1) they have advanced the technological background and (2) they have tested the preparedness of individual countries for the assessments, identified deficiencies and exercised some pressure to ensure the necessary conditions to make large-scale TBA possible. The application of TBA started in 2006, when Computer-Based Assessment of Science was an optional domain . Only thThe 2012 PISA cycle brought a breakthrough in two respects. First, although paper-based tests remained the main delivery method, the TBA version of assessments was offered as an option for reading and mathematics, making the two delivery methods comparable and linking paper-based and TBA achievement . Second,The projects and programs reviewed here have influenced the development of the eDia system in several ways. PISA re-defined the content to be measured, while ATC21S linked the skills and technology used for assessment and highlighted the importance of framework development. The technology was developed in interaction with the communities running the projects under review; the major forum, beyond several meetings at conferences, was the Szeged Workshop on Educational Evaluation, held annually at the University of Szeged between 2009 and 2016. The programs reviewed here focused on summative testing among older age groups (secondary schools), underscoring the lack of formative assessment and neglecting the needs of younger students, while recent research in education has emphasized both aspects. The experiences gained from the technological realization of these programs  have been transferred to diagnostic assessments, and eDia has extended them with a number of novel solutions .Beyond the developments reviewed here, a parallel evolution took place related to computer-aided instruction  and intePrevious assessment projects have stressed the importance of defining the content of assessments, and this is even more significant for diagnostic assessments in the early phases of schooling. Diagnosis requires not only a better understanding of the teaching and learning processes but also the cognitive and affective development of pupils as well. Therefore, framework development has been a prominent component in establishing the eDia system. With a brief description of framework development, we demonstrate that only the use of technology  has made it a realistic goal to differentiate the special aspects of learning by defining the three dimensions of assessments.The reading, mathematics, and science frameworks have been based on a three-dimensional model of learning outcomes. This model takes into account the traditions of defining learning objectives . The psychometric indicators for the assessments  are constantly monitored, items with poor parameters are modified or deleted from the system, and new items are added to improve coverage of the content defined in the frameworks. The validity of the three-dimensional model has already been empirically tested. Based on the data collected The eDia system began being built in April 2007, when researchers at the University of Szeged implemented the TAO open source software  on univeThe eDia online diagnostic assessment system can be divided into two main parts. One is the hardware infrastructure (a server farm) and the software that operates the system. This has been developed and optimized for diagnostic assessment, e.g., being continuously accessible for the entire Grade 1–6 student population , and for the management of large item banks (with tens of thousands of items). In addition, this infrastructure can also be used for several other assessment purposes. The other part is the main content of the system, the item banks prepared for the diagnostic assessment of reading, mathematics, and science.The eDia system is functionally ready for the implementation of systematic assessments and has operated in experimental mode since 2015. At present, there are more than 1,000 partner schools (approx. one-third of the primary schools in Hungary), where it is used on a regular basis. It contains over 25,000 items. The software has been continuously developed, with both the number of partner schools and the number of items available in the system growing.Currently, three different testing procedures are run with eDia. There are central assessments initiated by the assessment center three times in a school year, at the beginning, in the middle, and at the end of the year. These assessments provide data to establish item parameters and normative reference points. There are teacher-initiated assessments which are used for frequent diagnostic assessments adjusted to the needs of a class or of individual students. The teachers may compile tests out of the items available in the item banks for their own assessment activities. Furthermore, there is testing for research in numerous projects using either items from the item banks or specific tests developed for research purposes.The system contains an item builder module that makes the task of item writing as easy as writing multimedia documents. Item developers receive extensive training in the content of the assessment and in test theory and psychometrics, enabling them to master the use of the item builder module easily ,b, 2018.In the present mode of operating the system, tests consisting of a number of tasks form the units of the assessment. Tests may be constructed out of the tasks in several ways. Typically, booklets are formed out of the tasks, and then they can be combined variously into tests, for example, to eliminate the position effect or to optimize linking/anchoring options. Tests can be constructed with adaptive testing techniques, i.e., based on the answers given to all previous items or to items present in the last cluster, to minimize the difference between the students’ ability level and the test difficulty level.Students complete the diagnostic tests as part of their school activity using the available school infrastructure. The tests can be done practically from any device equipped with an internet browser, but the items are optimized for keyboard, mouse, and a large screen. For central assessments, there is an approx. two-week window when eDia is open for the actual assessment. Teacher-initiated testing can take place any time teachers find it useful . Students have a specific secret assessment identification code to log into the system.The eDia system is designed for both automated and human scoring. However, the items in the item banks that are prepared for the regular diagnostic assessments are scored automatically, with human scoring reserved for research and specific applications. Automatic scoring makes it possible to provide immediate feedback, and it is necessary for the rapid scoring of a large number of assessments. The system offers a variety of scoring options, adjusted to item type and form of response capture.The eDia system contains a statistical analytics module, which can perform every computation required by the assessment from descriptive statistics through classical test theory to IRT modeling. The computations are programmed using the open source “R” programming language and are continuously adapted to the developing system. The data can be exported from the system for further analyses.Teachers have been encouraged to use objective assessment instruments since the very beginning of educational testing; however, most tests available for classroom assessment are summative tests. Such tests are difficult to adapt to the actual needs of a class, not to mention individual students. Another option is teacher-made tests, but the time and resources needed to prepare and score them hinder practical use. The teacher-assembled tests in eDia fill this gap. Participating teachers are granted access to the item banks, so they can assemble tests out of available tasks. These tests can then be administered to individual students, a group of students or an entire class, with the results made available immediately after testing. Models for the co-existence of centrally initiated tests and teachers’ assessment are under development. The current model is that central assessments serve a screening function, while teacher-initiated tests are mostly used for formative and diagnostic purposes if needed. Further options are being explored, e.g., automated recommendations for testing based on previous assessment results.At present, there are two basic forms of feedback. One is the immediate feedback students receive right after the test has been completed in the form of percentage of total score of a particular test. Another form is contextualized information based on normative reference data, available only after the central assessments. After the general assessments, both students and teachers receive detailed information about the results for each assessment dimension. Students may download a PDF file with a detailed description of the content of the assessment and their own achievement compared to the national norm and class mean. Teachers receive similar information on their students individually in each dimension as well as a comprehensive, contextualized picture of their class, comparing it to other members of the same age group in the entire school, school district, region, and country. This feedback is provided in graphic form as well to help teachers comprehend and use the data.An IRT model is used to establish assessment scales. There are nine distinct scales in the eDia system as they are defined in the assessment framework; each one is developed separately. Establishing normative scales is a long process, one which requires several steps in the case of the eDia system. The results of the end-of-year assessments are used to establish the scales. In the first step, separate norms are defined for the different grades, with the mean for a grade set for 500 with a SD of 100. This phase has already been completed, and the 54 (6 grades × 3 domains × 3 dimensions) reference scales have been established.The next step is to devise developmental scales with vertical scaling of the data, linking the achievement of the different grades. This can be done easily with a psychological dimension, where a more or less continuous development can be assumed. As cognitive development is stimulated by out-of-school experiences as well, there may be large differences within a given cohort; some students’ achievement may be closer to the mean for a different cohort. Thus, linking the grades causes no difficulties. These considerations are only partially appropriate for the application dimensions, while the disciplinary dimensions are based on the material taught. Therefore, students in a particular grade may only be offered tasks from earlier grades, but not from later ones. Due to these complications, the first vertical scales for the psychological dimensions have already been prepared , but vertical scaling in the other two dimensions requires more sophisticated statistical procedures .Finally, longitudinal scales will also be devised, making it possible to monitor student progress and to observe how they progress within a given period, compared to his/her previous and others’ mean change. Developing such scales requires even more care and time and is especially difficult because collecting longitudinal data from the period covered by eDia takes at least 5 years, while the social and contextual conditions are also rapidly changing in the meantime. On the other hand, eDia does not provide high-stakes testing, nor is producing trend data a requirement. Thus, it can be flexible in establishing normative scales. Whatever the means used for scaling, scale development should also serve the formative, diagnostic function of the system.Quality of testing can be defined in terms of validity , reliability, and objectivity. In this section, we show how new item formats made possible by technology can improve the quality of testing. A number of media effect studies have been carried out in past decades to explore most aspects of assessments. The quality of TBA is usually compared to paper-and-pencil or face-to-face testing, so we also compare the eDia items to these traditional testing modes. Technology offers numerous new options both in presenting stimuli and in capturing students’ responses that are not possible through traditional testing modes; in addition, technology improves objectivity and validity significantly .Use of technology changes not only the forms of stimuli but also those of response capture. In the traditional test environment, response capture happened basically by circling, ticking, X-ing, underlining or writing letters, numbers, words or sentences. The TBA environment expands these options, but this expansion strongly depends on the technology used. There are different possibilities for response capture in the case of a tablet or a desktop computer. The eDia system is prepared for both. However, as the keyboard and mouse are used for input in most Hungarian schools, the eDia task responses are optimized for them.The TBA environment makes it possible to expand the possibilities of manipulation with task elements and to realize the following forms of response capture with a mouse: (1) clicking on form elements (radio button and checkbox), (2) using a drop-down menu, (3) clicking on pictures or parts of pictures, (4) clicking on texts or parts of texts, (5) coloring shapes or pictures or parts of them by clicking, (6) sequencing by ordering mouse clicks, (7) connecting two task elements with lines or arrows, (8) constructing answers with on-screen manipulations with drag-and-drop letters, words, sentences, numbers, shapes, pictures, voices, sounds, animations, simulations, etc., that is, all kinds of task elements, and (9) using sliders and functions or other changeable and interactive task elements. Other possibilities are available with the keyboard, such as typing letters, numbers, and words. Logging and analyzing log data by measuring response time, mouse movement, and navigation sequence to describe the activity of the students during testing can also contribute to more elaborated feedback; however, further studies are required to explore how to use these methods more effectively. All these possibilities for logging students’ activities while they respond to items are available in the eDia system.The eDia system was prepared to administer third-generation tests. The MicroDYN-based assessment of problem-solving  is availBeyond its main purpose of providing diagnostic assessments, the eDia platform has been used in a number of other domains and in research projects as well. In this section, we review the research in which data were collected by eDia.At present, there are over 20 further domains  for which tests or test batteries are implemented on the eDia platform. The principle in general is that different tests are prepared for the different age groups linked with anchor items.Supporting the kindergarten-school transition with assessment instruments is one of the current extensions of the eDia. First, the DIFER test battery, a broadly used face-to-face instrument, was digitized, and then the traditional and online delivery methods were compared. Results from the media effect study indicated that the two versions (face-to-face vs. online) were equivalent and that the digitized version was not only more convenient to use, but the objectivity and reliability had also improved on some subtests . Based oSeveral instruments were devised for assessments of curricular areas beyond the three major domains. The media effect on composing skills was studied with primary school students . A test Assessment of a variety of reasoning skills is embedded in the mathematics and science psychology dimension, mostly operational reasoning skills. However, there are some skills that play a distinct role in learning and cognitive development; therefore, comprehensive instruments have been prepared to assess them. Inductive reasoning is one of the most frequently assessed higher-order thinking skills, and several inductive reasoning tests have been developed for the eDia as well. First, a widely used paper-and-pencil inductive reasoning test , mathematics, history, science and English as a foreign language as well as a dynamic problem-solving test . Since tThe eDia system has been used for research within international collaborative projects carried out by the University of Szeged Centre for Research on Learning and Instruction and supports investigations by PhD students at the Doctoral School of Education at the same university. In this section, we review some results of these efforts, highlighting new opportunities for educational research offered by the online assessment.In Finland, the Centre for Educational Assessment, University of Helsinki, cooperates with Vantaa city schools in using tablets in everyday teaching and learning processes. Within the framework of this project, Hungarian tests were translated into Finnish and assessments were carried out in both countries using the same instruments, with the tests delivered from the University of Szeged servers . The firThe tests for assessing thinking skills implemented in the eDia have been used in several international studies. The knowledge acquisition phase of dynamic problem-solving involves two further skills, combinatorial reasoning  and inductive reasoning . The relationships of these skills were explored; the dynamic problem-solving tests, together with combinatorial and inductive reasoning tests were translated into Chinese and were administered to Chinese students. The results indicated a stronger impact of combinatorial reasoning than that of inductive reasoning . The relAnother set of studies was completed on learning foreign languages in three countries, Mongolia , KazakhsThe Hungarian Educational Longitudinal Program (HELP) was launched in 2003 and is maintained by the SZTE-MTA Research Group on the Development of Competencies . A new cSystematic feedback is a basic condition for the operation and development of any complex system and providing students and teachers with an inexpensive, easy-to-use, valid, and reliable assessment system may significantly contribute to solving certain crucial problems of education today. Making it possible to measure the different dimensions of learning separately, especially the mostly hidden psychological dimension, i.e., thinking and cognitive development may support meaningful learning and a deeper conceptual understanding. , and we may assume that with better instruments they will teach better. However, we may not assume that they will be able to fully exploit the potential of online diagnostic assessments; they need training to empower them. Several training programs (from one-day introductory workshops to two-year training of assessment experts) are available within the framework of the project. Ideally, the teacher-training component is an in-service adaptation of research-based teacher education . Educational data mining and process mining have already produced results applicable in practice as well . CertainLog file analysis is the easiest and most appropriate new method for using new types of assessment data (metadata and log data). An easily recordable and already routinely used piece of information is the time students spend on certain activities when completing online tasks; time-on-task analyses, among other methods, may indicate students’ attention and motivation. Some item types  allow the recording of more detailed information on students’ reasoning. Some analyses  using data collected with eDia have already been conducted , but furBoth of the authors, BC and GM, certify that they have participated sufficiently in the study to take responsibility for the content, including writing and final approval of the manuscript. Each author agrees to be accountable for all aspects of the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This paper aims to explore whether entrepreneurial ethics can improve entrepreneurial performance in new ventures. The dynamic impact of entrepreneurial ethics on entrepreneurial performance  is investigated from an institutional perspective, and the moderating role of firm visibility between them is explored. From different regions of China, 296 valid questionnaires are obtained and analyzed. We find that entrepreneurial ethics is adverse to the survival of new ventures but conducive to their sustainable growth of new ventures. We also find that high firm visibility can help entrepreneurial ethics be more effective in improving entrepreneurial performance. This study provides a new insight to explain the theoretical controversy of entrepreneurial ethics and provides guidance for the establishment of the internal ethical structures of new ventures. Suggestions for government and industry regulators on the management of entrepreneurial ethics are also provided. It is generally agreed among researchers that business ethics can promote performances of mature enterprises . For extHowever, the above conclusions are drawn mostly from the study on mature enterprises, rarely on new ventures; actually, whether ethics is conducive to improving the performance of new ventures is still controversial . Some stThus, this paper aims to explore two questions: this paper aims to investigate: (1) whether entrepreneurial ethics is beneficial to the improvement of entrepreneurial performance; (2) how the key factors at the micro-level of the institution affect the relationship between entrepreneurial ethics and entrepreneurial performance based on from the institutional perspective, it explores. Answering these two questions can make up for the research gap of new ventures in the field of business ethics  and provIn sum, the conclusion of this study makes several contributions to the literature. First of all, this paper provides a new perspective on the measurement of entrepreneurial ethics. Previous studies have mainly used the ethical practice to measure the moral stance of new ventures, ignoring the fact that ethical structure forms the basis for the ethical practice and climate of new ventures . This paEntrepreneurial ethics constitutes a reasonable and acceptable norm for entrepreneurs . Since tHowever, there is relatively little research on new ventures; most of them focus on the impact of entrepreneurial ethics on organizational performance . On thisThe previous study shows ethical structures can be classified as two kinds: implicit  structure and explicit  structure in new ventures . The expEntrepreneurial performance can reflect the achievements and output of entrepreneurs in running enterprises , 31, andHowever, current studies about entrepreneurial ethics mostly measure entrepreneurial performance from a static perspective, ignoring the dependence of business ethics and CSR practice on time accumulation and failing to fully reflect the impact of entrepreneurial ethics on the entrepreneurial development process. Regarding entrepreneurial performance, Chrisman et al.  showed tFirm visibility comes from institutional theory –40, and Secondly, the institutional theory holds that the essence of new venture growth is to overcome the “legitimacy threshold”, obtain resources, and constantly embed into the institutional environment ; obtainiThirdly, previous studies have confirmed the positive effect of firm visibility. The higher the firm visibility is, the more interaction between the company and stakeholders could increase . This hi(1) Implicit ethical structure and survival of new venturesImplicit ethical structure such as ethical leadership can improve financial performance by increasing employee commitment and external stakeholder recognition , but it H1. An implicit ethical structure has a negative impact on the survival of new ventures.(2) Explicit ethical structure and survival of new venturesDowne et al.  pointed H2. An explicit ethical structure has a negative impact on the survival of new ventures.(3) Interaction of the two ethical structures and survival of new venturesThe two ethical structures–implicit and explicit–together constitute the ethical environment of new ventures. They promote each other to produce a marked effect and strengthen a just ethical environment. However, the development of the ethical structure may be detrimental to the short-term survival of new ventures. First of all, it is difficult for entrepreneurial ethics to make a difference in terms of profit in the short term. Market forces do not price socially responsible characteristics in the short run . It is, H3. Entrepreneurial ethics have a negative impact on the survival of new ventures.(1) Implicit ethical structure and sustainable growth of new venturesIn order to promote sustainable growth, new ventures need to gain legitimacy and committed followers, and it takes time to change the ethical climate in new ventures . In the H4. An implicit ethical structure has a positive impact on the sustainable growth of new ventures.(2) Explicit ethical structure and sustainable growth of new venturesFirst of all, an explicit ethical structure that involves a bona fide ethical code would reduce the unethical behavior of employees in the long term. The effect of ethical training on reducing such behaviors is gradually enhanced over time , and thiH5. An explicit ethical structure has a positive impact on the sustainable growth of new ventures.(3) Interaction of the two ethical structures and sustainable growth of new venturesWhen new ventures overcome early pressures in terms of the cost involved in building an ethical structure, the two structures promote one another in the long term and work together to promote venture’s growth. First of all, an implicit ethical structure can play a better role if there is an explicit ethical structure in place. Ethical ideas embodied in the implicit ethical structure are not directly expressed, so a venture needs an explicit ethical structure to formally express its moral intentions both to internal staff and external stakeholders alike. On the one hand, an explicit ethical structure can regulate the ethical behaviors of entrepreneurs and employees and reduce any immoral decisions. On the other hand, the practice of CSR without communication with external stakeholders would not have a positive impact on performance . ThroughH6. Entrepreneurial ethics have a positive impact on the sustainable growth of new ventures.Firm visibility can weaken the negative impacts of entrepreneurial ethics on the survival of new ventures. It is also conducive to increasing the interaction between enterprises and stakeholders. New ventures with high firm visibility tend to have ethical practices that are more likely to be known to the outside world. It can, therefore, create a positive reaction on the part of consumers and investors to ethical behaviors. For example, it can increase consumers’ understanding of a company’s products and their payment premium , restricH7. Firm visibility can weaken the negative impact of entrepreneurial ethics on the survival of new ventures.In addition, entrepreneurial ethics play a more significant role in improving sustainable growth in new ventures with high visibility. In the long term, enterprise ethics can gain a good reputation for a firm, increase customer loyalty and obtain the trust of partners. High firm visibility increases the attention of potential consumers and employees and attracts potential alliance partners . At the H8. Firm visibility can strengthen the positive influence of entrepreneurial ethics on the sustainable growth of new ventures.Each scale for the variables was based on previous scales or definitions in the literature on the subject. All items were measured on a Likert five scale .The measurement of the development of ethical structure was based on the research conducted by Morris . We carrIn this paper, the entrepreneurial performance was measured from two aspects: survival and sustainable growth. The measurement of the survival of new ventures was based on Naidoo’s scale , and incBased on Burke’s definition , this paIn order to avoid the model being influenced by external factors, three control variables were chosen: size, year, and industry. Details of the survey questions are in In the sample selection, potential samples were identified from the National Small and Medium-sized Enterprise Service Platform. The platform is managed by the Ministry of Industry and Information Technology of the People’s Republic of China, and there are a large number of directories and basic information of small and medium-sized enterprises (SMEs) in this platform. According to Li and Atuahene-Gima , we chooThe data were gathered in three phases. In the first phase, the enterprises were divided into four categories according to the regions in the platform: South Coast, North Coast, South inland and North inland. Then, 100 enterprises under eight years  were selected respectively from each region by using simple random sampling technology, which meets the random standard. Their contact information was obtained through Tianyancha, a professional enterprise credit query platform in China. The second step was to contact the sample company by phone, email, and so forth. Senior managers of the company are invited to participate in the survey because they are trusted to have more information about the companies and play a critical role in their management. In the survey process, we indicated the purpose of the research and stated that our research was sponsored by the National Social Science Foundation, guaranteeing that the survey data would be kept confidential and only be used for academic research. Finally, their Wechat (an online chat App in China) accounts and email addresses were obtained so that official questionnaires could be distributed through the network.The third step was to issue the formal questionnaire. A questionnaire link through the questionnaire collection tool was formed and subsequently sent to the senior manager through email and Wechat. The advantage of this collection method is that we are able to see the response of the questionnaire in the background, including the collection number of the collected questionnaire, filling time and other related information. In the whole process, most managers were given sufficient instructions and guidance about the scale items. It took us 11 months from the beginning of target enterprise screening and information collection to the end of questionnaire collection, from February 2018 to January 2019, making a total of 332 questionnaires. In order to ensure the high quality and validity of the questionnaires, 36 were removed for various reasons  and a later refusal for questionnaire). In the end, 296 questionnaires were retained and used for analysis. Analysis of Variance (ANOVA) tests found no non-response bias or missing-value bias. SPSS 21.0 software was used to test the reliability of this study. The result indicates that Cronbach’s α of various dimensions is higher than the standard value 0.7  and average variation extracted from later variables (hereinafter referred to as AVE). The results are shown in Tables Then, to test discriminant validity, Amos 24.0 software was utilized for confirmatory factor analysis. Since this paper aims to verify the different effects of entrepreneurial ethics on the survival and sustainable growth of new ventures, we conducted confirmatory factor analysis with the survival of new ventures as the dependent variable and other variables, as well as one with the sustainable growth of new ventures as the dependent variable and other variables, respectively. The results show that the four-factor model fitted the data reasonably better than any of the alternatives Tables  and 6. THarman’s single-factor method was applied to detect common method bias. The first extracted factor explains only 17.192% of the variance, which is less than the 50% common standard . A singlIn this paper, SPSS 21.0 was used to test the hypothesis by multivariate linear regression analysis. The threat of multicollinearity to the accuracy of the results needs to be eliminated before the regression analysis. The results of the analysis show that the maximum variance inflation factor (VIF) of the coefficient was 1.169, which was far lower than the critical value 10, and the tolerance value of each variable was greater than 0.5, reducing the threat of multicollinearity on the research results. Therefore, the data in this paper are suitable for multivariate linear regression analysis.This paper studied the varying impacts of entrepreneurial ethics on the survival and sustainable growth of new ventures respectively. The regression results of entrepreneurial ethics on the survival of new ventures are shown in To test the moderation effect, we conducted a regression analysis using the procedure described by Baron and Aiken . We haveThe same method was used to study the impact of entrepreneurial ethics on the sustainable growth of new ventures. The results are shown in By applying the same method as before to test the moderation effect, the results showed that in Model 8 that firm visibility had a positive impact on entrepreneurial ethics  for the sustainable growth of new ventures , indicating that Hypothesis 8 is supported.To determine whether the forms of the interactions matched with those suggested by Hypotheses 7 and 8, in this paper, a simple slope analysis method proposed by Aiken  is used.A summary of the results for all the hypotheses is shown in This paper studied the different impact of the two structures–implicit ethical structure and explicit ethical structure–and their interaction on influencing entrepreneurial performance . Also, this paper investigated the regulating effect of firm visibility, which is of theoretical and practical significance to businesses.This research made the following three theoretical contributions to business ethics studies. Firstly, this paper measures entrepreneurial ethics from the perspective of the internal ethical structure of new ventures, instead of ethical practice in the measurement of the previous research –6. Such Secondly, this paper divides entrepreneurial performance into two dimensions: survival and sustainable growth; and the paper focuses on the performance of new ventures. Thus, it makes up for the lack of dynamic investigation on the relationship between entrepreneurial ethics and entrepreneurial performance in previous studies. We find that entrepreneurial ethics is adverse to the survival of new ventures. Newness may restrict new ventures’ abilities to gain benefits from stakeholder relationships and positive reputations arising from ethical behavior. The establishment of ethical structures increases the operating costs of new ventures. We also find that entrepreneurial ethics can improve the sustainable growth of new ventures. As time passes by, ethical structures would contribute to an excellent internal ethical climate, thus increasing employees’ organizational commitment and improving their ability to innovate their performance. The above findings confirm the previous research conclusion that business ethics can promote the sustainable growth of enterprises . DiffereThirdly, this paper puts firm visibility, which is the premise variable recognized by the institutional theory, into the research framework. In addition, this paper studies its moderating role in the relationship between entrepreneurial ethics and entrepreneurial performance, filling the research gap of institutional perspective on the relationship between ethics and performance. We find that high firm visibility is an important factor to amplify the positive effect of ethics. Empirical results showed that high firm visibility reduces the negative impact of entrepreneurial ethics on the survival of new ventures, and magnifies the positive impact of entrepreneurial ethics on the sustainable growth of new ventures. In contrast, the low firm visibility of new ventures is an important obstacle in the path of entrepreneurial ethics affecting entrepreneurial performance. Through simple slope analysis, we find that when the visibility of enterprises is low, the positive influence of entrepreneurial ethics on the sustainable growth of new ventures disappears. Because of the low visibility of new ventures, the ethical behavior of enterprises is not perceived by external stakeholders, and cannot obtain legitimacy, which greatly weakens the positive effect of ethics. The above findings confirm the positive moderating effect of good institutional environment on the relationship between CSR practice and performance –11. DiffThe results of this study have important implications for the ethical management of new ventures and the formulation of government policies. First of all, this study finds that establishing a perfect ethical structure in the initial stage of the enterprise would generate huge survival pressure. However, in the long run, a proper ethical structure can help enterprises standardize the ethical behavior of employees and entrepreneurs, establishing a good image of an ethical company and forming a sustainable competitive advantage. Therefore, new ventures could establish a proper ethical structure based on the strategic positioning of long-term development. However, as explicit ethical structure needs relatively high costs, we suggest that new ventures should establish standardized explicit ethical structures according to their own business conditions. Such explicit ethical structure could involve making ethical guidelines to regulate employees’ behavior, writing ethical declarations to increase the recognition of customers and partners, and implementing regular ethical training. Consequently, the moral consciousness of employees and entrepreneurs would be improved continuously; the standard of moral for the enterprises would be formed finally. On the other hand, new ventures should not ignore the construction of implicit ethical structure. Entrepreneurs and senior managers should set moral examples, increase ethical dialogue among internal employees, and form a good moral climate. Additionally, we believe that the two ethical structures complement and promote each other. Therefore, new ventures should increase the understanding of the two structures and their interaction, form a closed-loop of mutual promotion between them, and maximize the synergy of the two ethical structures, thus promoting the sustainable performance of enterprises.Secondly, based on the institutional theory, this study finds that firm visibility can weaken the negative impact of entrepreneurial ethics on the survival of new ventures and strengthen the positive impact of entrepreneurial ethics on the sustainable growth of ventures. Therefore, the government and society could improve the firm visibility of new ventures, help them to be recognized by more stakeholders, thus forming a virtuous circle that helps new ventures to be more ethical. For media and industry regulators, they should increase their focus on ethical behaviors of new ventures, reward ethical companies, and punish unscrupulous companies. For the government, it is necessary to strengthen the establishment of relevant laws and regulations, support ethical new ventures, and expand the influence of law. Through the above methods, the regulatory agencies and the ethical new ventures can gain more benefits. Inspiringly, a good social atmosphere can also be formed, benefiting the whole society. For enterprises, they can increase firm visibility by increasing advertising expenditure and increasing interaction with stakeholders. Therefore, the image of the ethical company could be known to more stakeholders and magnify the effective role of ethical management.It is still unclear whether new ventures’ performance benefits from entrepreneurial ethics and how they relate with each other. This paper explores the relationship between entrepreneurial ethics, firm visibility and entrepreneurial performance of new ventures from the institutional perspective. The impact of entrepreneurial ethics on entrepreneurial performance is explored in a dynamic way. Through the questionnaire survey method, we have obtained 296 effective questionnaires. The results show that: firstly, entrepreneurial ethics have a “two-sided” impact on entrepreneurial performance, which is unconducive to the survival of new ventures, but conducive to their sustainable growth. Secondly, firm visibility, as an institutional factor, plays a positive moderating role in the impact of entrepreneurial ethics on entrepreneurial performance. This conclusion confirms the usefulness of a good institutional environment and explores more beneficial factors to help ethics play an effective role in improving the entrepreneurial performance, so as to provide suggestions to guide the implementation of ethical management of the institution.Although our study has explored the different effects of entrepreneurial ethics on the survival and sustainable growth of new ventures and has taken institutional factors into consideration, there are still some limitations. First of all, we used China for our data selection–a single country. Scholars have confirmed that enterprise ethics and CSR have a varying impact on performance in a different institutional environment. Therefore, the conclusions obtained in this paper cannot be fully representative. In the future, the scope of the data collection could be expanded to further test the hypotheses put forward in this paper. Secondly, firm visibility has many antecedents, such as enterprise advertising investment, media exposure, the degree of market development, etc. This paper measured “firm visibility” based only on a stakeholder perspective. Since firm visibility is affected by multiple variables, such as advertising intensity and market development, future research could measure it from multiple dimensions.S1 File(DOCX)Click here for additional data file.S1 Dataset(XLSX)Click here for additional data file.