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Mirjalili Z, Babaeinejad A, Sayadi S, Mollaei H R. Recognizing and Describing the Factors Affecting the Design of the Innovation Ecosystem Model in the Field of Health with an Emphasis on the Role of E-Government. JCHR 2024; 13 (1) :101-108
URL: http://jhr.ssu.ac.ir/article-1-1058-en.html
URL: http://jhr.ssu.ac.ir/article-1-1058-en.html
1- Department of Public Administration, Islamic Azad University, Kerman Branch, Kerman, Iran
2- Department of Management, Islamic Azad University, Kerman Branch, Kerman, Iran ,a.babaei@iauk.ac.ir
3- Department of Management, Islamic Azad University, Kerman Branch, Kerman, Iran
2- Department of Management, Islamic Azad University, Kerman Branch, Kerman, Iran ,
3- Department of Management, Islamic Azad University, Kerman Branch, Kerman, Iran
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Zahra Mirjalili 1
, Abbas Babaei Nejad * 2 , Saeed Sayadi 2 , Hamid Reza Mollaei 2
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Introduction
Table 3. Coding results
References
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8. Esmailipour Masouleh E, Afshari-Mofrad M, Bashiri M. Innovation Ecosystem in Iran’s Automotive Industry; What it has, What it Lacks. Journal of Improvement Management. 2022; 15(4): 105-27. [Persian]
9. Asgharzadeh S, Safari A. Investigating the position of electronic government in the era of virtual communication. Management and accounting studies. 2023; 9(1): 113-22. [Persian]
10. Dabbagafrouz R, Zendeh AB, Pasebani M. Designing a Strategic Model of Innovation Ecosystem by Using Grounded Theory in the Field of Biotechnology. Depiction of Health. 2021; 12(2): 113-26. [Persian]
11. Arena C, Catuogno S, Saggese S, Sarto F. The adoption of e-Health in public hospitals. Unfolding the gender dimension of TMT and line managers. Public Management Review. 2021; 23(10): 1553-79.
12. Soumitra D, Lanvin B, Wunsch-Vincent S, editors. Global innovation index 2020: who will finance innovation?. WIPO; 2020.
13. Dabbagafrouz R, Zendeh AB, Pasebani M. Designing a Strategic Model of Innovation Ecosystem by Using Grounded Theory in the Field of Biotechnology. Depiction of Health. 2021; 12(2): 113-26. [Persian]
14. Asadifard R, Nozari M. A Development Pattern for University-Based Innovation Ecosystems: The Case Study of Sharif Innovation District. Journal Strategi c Studies of Public Policy. 2023; 12(45): 140-65. [Persian]
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16. Song Y, Sahut JM, Zhang Z, Tian Y, Hikkerova L. The effects of government subsidies on the sustainable innovation of university-industry collaboration. Technological Forecasting and Social Change. 2022; 174: 121233.
17. Smorodinskaya N, Russell M, Katukov D, Still K. Innovation ecosystems vs. innovation systems in terms of collaboration and co-creation of value; 2017.
18. Almpanopoulou A, Ritala P, Blomqvist K. Innovation ecosystem emergence barriers: Institutional perspective; 2019.
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| Recognizing and Describing the Factors Affecting the Design of the Innovation Ecosystem Model in the Field of Health with an Emphasis on the Role of E-Government |
Zahra Mirjalili 1
, Abbas Babaei Nejad * 2 , Saeed Sayadi 2 , Hamid Reza Mollaei 2 - Department of Public Administration Comparative and Development Tendency, Islamic Azad University, Kerman Branch, Kerman, Iran
- Department of Management, Islamic Azad University of Kerman, Kerman, Iran
| ARTICLE INFO | ABSTRACT | |
| Original Article Received: 13 Feb 2024 Accepted: 11 May 2024 |
Background: Development of innovation issues in countries has led to the formation of new concepts in this field. Some of these concepts include innovation systems ranging from national, sectoral, etc., innovation networks, commercialization, and innovation ecosystems. Therefore, the purpose of this study is to design recognition and description of the factors affecting the design of the ecosystem model of innovation in the field of health with an emphasis on the role of e-government.
Methods: The type of qualitative study is a type of theory. A semi-structured interview was used to gather information. And the analysis of Strauss and Corbyn's method and the paradoxical model were used. The samples were selected through targeted sampling. And finally, 7 senior and middle managers of government and non-governmental hospitals in Yazd province entered the study. Results: The model designed in this study includes the effective dimensions and components, obstacles and strategies, causal conditions, contextual, intermediary and constituent elements that are the pivotal phenomenon, Shows the consequences and strategies. identifiers and Ecosystem Factors Innovation 37 Concepts, 4 Main categories Enabling policies and regulations, Access to data and infrastructure، funding and validation opportunities and ease of acceptance and dissemination of innovations (from interviews and research literature) were formulated in the form of a conceptual model
Conclusion: The process of study was explained in the form of the story line of the electronic government data theory. Finally, the innovation ecosystem model in the field of biotechnology was designed and analyzed. Finally, this model can be used to design an innovation ecosystem in the field of health. Keywords: Ecosystem, innovation, technology, electronics, health, hospital |
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Corresponding Author:
Abbas Babaei Nejad management7204020@yahoo.com |
Mirjalili Z, Babaei Nejad A, Sayadi S, Mollaei HR. Recognizing and Describing the Factors Affecting the Design of the Innovation Ecosystem Model in the Field of Health with an Emphasis on the Role of E-Government. J Community Health Research 2024; 13(1): 101-108.
Introduction
The term ecosystem (ecosystem) is derived from two terms «aco» and «system» (system), the first to the relationship between living organisms and their environment، And the second refers to a whole systemized cosmos (1). It can be said that an ecosystem means a system of living organisms and their environment (2). According to the general theory of systems, a system means a set of objects that interact with each other. All systems include components and relationships and features (3). systems also share a common boundary and common purpose (4). The term ecosystem has been used in various fields except living systems, in the field of management، The term is usually used to refer to a network of co-dependent organizations that have been formed around a focal firm or platform 5 or 5, and have formed a focal value 6. Innovation is also commonly referred to as new ideas, improvements, or solutions that have been implemented into useful outcomes 1. The innovation ecosystem is made up of « economic factors and economic relations, as well as non-economic components such as technology, institutions, social interactions and culture (7).
E-government refers to the use of information and communication technology programs in the public sector, with the aim of improving management efficiency and providing the convenience of access to government information and services to the public. Among the goals that are usually raised for e-government, we can mention these, improving the quality of public services and changing government with increasing access، Efficiency and transparency, as well as more recently, the issue of increasing public participation has also been raised (8). E-government is a new, simple and challenging concept for governments, and it is a concept that has come to realize with the coming of the virtual and digital age, a change in contexts Various have become inevitable and in the event of nonconformity, the inefficiency of organizations will become more evident than size. E-government is the fruit of a transformation in information technology, which is the use of technology to increase access to and provide services and information to citizens, business partners, employees and other institutions. E-government means the government's use of technology, especially information and communication technology, to promote access to and the provision of government services and information to people, business partners, employees and other devices and governments or the continuous optimization of service delivery, participation and governance through the transformation of internal and external communications are interpreted by technology, the internet and new media (9).
Health technology is a multidisciplinary process of policy analysis that addresses clinical, economic, social, ethical aspects, added value checks the release and use of health technology. Innovation plays an important role in health (10). New approaches include outbreaks and tools that aim to reduce cost and improve quality of life. In this domain, the activity of the organization is unpredictable and dynamic. While decision-makers should manage the complex relationship between multiple actors and different entities (patients, health care providers, and suppliers). Numerous innovations in the field of health have not only been able to increase their ability to respond to patients’ expectations of life expectancy, quality of life, Diagnosis and treatment methods are also effective for more efficient organization (12).
In the study of Dabbagh Afrouz and colleagues, 5 main articles of Amal Ali (State, Finance), the central category (University and Research Institutions), strategies (University and Research-oriented institutions, Shorten the process of obtaining the necessary permits, state support for research and development, material and spiritual incentives and increase in venture capital), consequences (development and economic growth) and contextual factors (location attraction), banking Services, Intellectual Property Rights) Intervention Conditions (Culture) Designing a Strategic Model for Innovation Ecosystem in Health Identified (13).
In the study of Asadi Fard and colleagues, 4 types of cooperation, the method of institutionalization, activities and characteristics of the main actor were identified as the main components (14).
Given that e-government in the world and Iran has been new and has not yet reached the stage of evolution, it can be said that research has so far failed to be an integrated model of innovation ecosystem in the field of biotechnology, especially in the health system, a successful ecosystem is the result of a long-term transformation and there are no identical guidelines for all ecosystems. Due to the lack of compatibility of existing models with local culture and environment, any kind of prediction is expected. Therefore, this study aimed to identify and describe the factors affecting the design of the ecosystem model of innovation in the field of health with an emphasis on the role of e-government in 1402 in Yazd province. The results of this research are aimed at policy makers, planners, managers and university presidents, Health-based companies help entrepreneurs and startups to innovate so that they don’t fall behind science and technology in the current global competition.
E-government refers to the use of information and communication technology programs in the public sector, with the aim of improving management efficiency and providing the convenience of access to government information and services to the public. Among the goals that are usually raised for e-government, we can mention these, improving the quality of public services and changing government with increasing access، Efficiency and transparency, as well as more recently, the issue of increasing public participation has also been raised (8). E-government is a new, simple and challenging concept for governments, and it is a concept that has come to realize with the coming of the virtual and digital age, a change in contexts Various have become inevitable and in the event of nonconformity, the inefficiency of organizations will become more evident than size. E-government is the fruit of a transformation in information technology, which is the use of technology to increase access to and provide services and information to citizens, business partners, employees and other institutions. E-government means the government's use of technology, especially information and communication technology, to promote access to and the provision of government services and information to people, business partners, employees and other devices and governments or the continuous optimization of service delivery, participation and governance through the transformation of internal and external communications are interpreted by technology, the internet and new media (9).
Health technology is a multidisciplinary process of policy analysis that addresses clinical, economic, social, ethical aspects, added value checks the release and use of health technology. Innovation plays an important role in health (10). New approaches include outbreaks and tools that aim to reduce cost and improve quality of life. In this domain, the activity of the organization is unpredictable and dynamic. While decision-makers should manage the complex relationship between multiple actors and different entities (patients, health care providers, and suppliers). Numerous innovations in the field of health have not only been able to increase their ability to respond to patients’ expectations of life expectancy, quality of life, Diagnosis and treatment methods are also effective for more efficient organization (12).
In the study of Dabbagh Afrouz and colleagues, 5 main articles of Amal Ali (State, Finance), the central category (University and Research Institutions), strategies (University and Research-oriented institutions, Shorten the process of obtaining the necessary permits, state support for research and development, material and spiritual incentives and increase in venture capital), consequences (development and economic growth) and contextual factors (location attraction), banking Services, Intellectual Property Rights) Intervention Conditions (Culture) Designing a Strategic Model for Innovation Ecosystem in Health Identified (13).
In the study of Asadi Fard and colleagues, 4 types of cooperation, the method of institutionalization, activities and characteristics of the main actor were identified as the main components (14).
Given that e-government in the world and Iran has been new and has not yet reached the stage of evolution, it can be said that research has so far failed to be an integrated model of innovation ecosystem in the field of biotechnology, especially in the health system, a successful ecosystem is the result of a long-term transformation and there are no identical guidelines for all ecosystems. Due to the lack of compatibility of existing models with local culture and environment, any kind of prediction is expected. Therefore, this study aimed to identify and describe the factors affecting the design of the ecosystem model of innovation in the field of health with an emphasis on the role of e-government in 1402 in Yazd province. The results of this research are aimed at policy makers, planners, managers and university presidents, Health-based companies help entrepreneurs and startups to innovate so that they don’t fall behind science and technology in the current global competition.
Methods
The type of qualitative study is a type of fuzzy cognitive theory and mapping. In order to sample from sample, sample method was used purposefully. Finally, 7 senior and middle managers of government and non-governmental hospitals in Yazd province were carried out. In order to formulate the foundations, definitions and theoretical concepts of library resources, including library resources, treasure trove & treasure trove & treasure & treasure ^_Need, SID, G ^_Need. In order to collect the desired data and measure the variables of the research, interviews have been used. In reviewing the validity of the content, test questions are provided to experts or some subjects and ask them to determine whether the test questions measure the adjective and whether the questions contain the entire content It covers the test or not. If there is agreement between different persons, the validity of the test, that test has content validity to examine the formal validity, the opinions of the target sample group or the company of research representatives are used, and this part of the test validity does not require the opinions of expert experts.
The way of conducting the interview was in this way that at first the topic of the interview was generally stated in relation to the design of the innovation ecosystem model with emphasis on the role of electronic government and further explanations were avoided due to the possible bias of the interviewee's mind. After the first interview, all the issues expressed by him were re-read and related topics of the initial coding, which part of this coding was done in a written and professional manner. Then the second interview was conducted and the issues related to the previous codes were separated and assigned to new topics. This process was also used in later interviews until practically new codes were not extracted from the topics discussed. It is necessary to state that in the qualitative method of interviewing, while trying to non-intervention of the researchers personally, although they are very strong, their personal opinion will be entered. Therefore, in order to reduce the direct application of the researcher's opinion in the purification of the initial codes, all the extracted codes were converted into direct questions with the relevant criteria and a questionnaire was distributed and collected.
The approach of this research in research data analysis is the process of editing. In this type of style, the editor who, in the wake of meaningful sections, reduces and increases the words or sentences, removes unnecessary words in the text, enters the text. The best example of a "data-based approach" is Glaser and Strauss 1967, which provides guidelines for the development of qualitative data-driven theory. In fundamental conceptualization theory, this process is called "continuous investigation" and aims to reach the point of "theoretical philosophy" where additional analysis does not play any role in the discovery of new knowledge about a category or class. In fact, it can be said that interviews continue until they are theoretically saturated. To extract the concepts from the mass volume of information that is obtained during the interview, a coding is done. Corbin and Strauss (1998) consider coding to be a kind of deep analysis in which data، The word is studied to the word, and eventually the codes are removed from the bottom to the words or phrases. In this research, "primary and secondary" research has been used to form concepts and categories.
The way of conducting the interview was in this way that at first the topic of the interview was generally stated in relation to the design of the innovation ecosystem model with emphasis on the role of electronic government and further explanations were avoided due to the possible bias of the interviewee's mind. After the first interview, all the issues expressed by him were re-read and related topics of the initial coding, which part of this coding was done in a written and professional manner. Then the second interview was conducted and the issues related to the previous codes were separated and assigned to new topics. This process was also used in later interviews until practically new codes were not extracted from the topics discussed. It is necessary to state that in the qualitative method of interviewing, while trying to non-intervention of the researchers personally, although they are very strong, their personal opinion will be entered. Therefore, in order to reduce the direct application of the researcher's opinion in the purification of the initial codes, all the extracted codes were converted into direct questions with the relevant criteria and a questionnaire was distributed and collected.
The approach of this research in research data analysis is the process of editing. In this type of style, the editor who, in the wake of meaningful sections, reduces and increases the words or sentences, removes unnecessary words in the text, enters the text. The best example of a "data-based approach" is Glaser and Strauss 1967, which provides guidelines for the development of qualitative data-driven theory. In fundamental conceptualization theory, this process is called "continuous investigation" and aims to reach the point of "theoretical philosophy" where additional analysis does not play any role in the discovery of new knowledge about a category or class. In fact, it can be said that interviews continue until they are theoretically saturated. To extract the concepts from the mass volume of information that is obtained during the interview, a coding is done. Corbin and Strauss (1998) consider coding to be a kind of deep analysis in which data، The word is studied to the word, and eventually the codes are removed from the bottom to the words or phrases. In this research, "primary and secondary" research has been used to form concepts and categories.
Results
Table 1 shows the demographic characteristics of the participants in the study. Most of the male participants were 4.71%, between the age of 54-36, 85.71%, and had a master's education, 28.57%.
Table 1. Demographic characteristics of the participants in the study
| Percentage (%) | Frequency | Variable |
71.439 |
5 | Male |
| 28.57 | 2 | Female |
| 71.439 | 5 | 36 to 40 years old |
| 14.28 | 1 | 41 to 45 years old |
| 14.28 | 1 | 46 to 50 years old |
| 71.439 | 5 | Doctorate degree |
| 28.57 | 2 | Master's degree |
14.28 28.57 57.14 |
1 2 4 |
Work experience Less than 10 years 10-20 years More than 20 years |
Results from interviews
CODED FINDINGS
This section consists of two parts, the table of the first codes extracted from the interviews and the table of categories extracted from the concepts along with their secondary codes are presented in Table 2 of the concepts extracted from the interviews.
After compiling the key points and concepts, the information categorized in Table 3 coded results are presented based on category, concept and secondary code
CODED FINDINGS
This section consists of two parts, the table of the first codes extracted from the interviews and the table of categories extracted from the concepts along with their secondary codes are presented in Table 2 of the concepts extracted from the interviews.
After compiling the key points and concepts, the information categorized in Table 3 coded results are presented based on category, concept and secondary code
Table 2. Concepts extracted from interviews
| Extracted Initial Codes | Row |
| Strong leadership and vision from government authorities to support digital health | 1 |
| Developing a national digital health strategy with stakeholders' input | 2 |
| Sandbox regulatory environments for testing innovations in a controlled setting | 3 |
| Tax incentives for investment in digital health startups and research & development | 4 |
| Simplified procurement policies for testing digital health solutions | 5 |
| Global patient identifiers and interoperable EHR systems | 6 |
| APIs and architectures to encourage third-party innovations | 7 |
| Secure cloud infrastructure for storing and analyzing health data | 8 |
| Workforce training programs in digital literacy and new technologies | 9 |
| Public-private partnerships for sharing risks and benefits | 10 |
| Competitions and awards for identifying promising innovations | 11 |
| Frameworks of responsibility and cybersecurity standards for digital health | 12 |
| Telehealth regulations enabling virtual care models and remote monitoring | 13 |
| Support for international collaboration and knowledge sharing | 14 |
| Budget for evaluating effectiveness and cost-effectiveness of feedback mechanisms in design processes | 15 |
| Standardization of data formats, terminologies, and protocols | 16 |
| Regulations concerning artificial intelligence, data privacy, and information governance | 17 |
| Interoperability between old and new electronic health systems | 18 |
| Change management support during organizational transitions | 19 |
| Technical assistance for implementation and system integration | 20 |
| Workforce training on digital skills and new care models | 21 |
| Incentives for adopting and meaningfully using digital health tools | 22 |
| Consumer protection against potential digital health harms | 23 |
| | Pilot programs to demonstrate effectiveness to policymakers | 24 |
| Innovation hubs and testing grounds for emerging technologies | 25 |
| Cybersecurity requirements for digital health vendors | 26 |
| Reimbursements for digital health interventions | 27 |
| Portability of health data between providers and platforms | 28 |
| Alignment of digital priorities among government health agencies | 29 |
| Oversight processes for monitoring and auditing data operations | 30 |
| Support for scaling successful digital health testers at a national level | 31 |
| Guiding artificial intelligence insights into public health decision-making | 32 |
| Protection against algorithmic bias and discriminatory effects | 33 |
| Emergency plans for technology failures or outages | 34 |
| Engagement with ethical, legal, and social issues surrounding digital health | 35 |
| Commitment to reducing inequality in access and digital literacy collaboration across sectors and disciplines | 36 |
| Assessment of successes and failures to improve future iterations | 37 |
Table 3. Coding results
| Factors | Row |
| Simple regulatory approvals to incentivize digital health innovations | 1 |
| Policies on health data standards and exchange | 2 |
| Guidelines for the use of artificial intelligence and accountability in healthcare | 3 |
| Telemedicine laws enabling virtual care models | 4 |
| Procurement policies facilitating pilot implementation of innovations | 5 |
| Deployment of health identifier systems and EMR / EHR | 6 |
| Accessible APIs for integration with public digital health platforms | 7 |
| Anonymous public health datasets for analysis | 8 |
| Cloud infrastructure and data storage for scaling innovations | 9 |
| Rapid integration with government remote health systems | 10 |
| Government financial aid and incentives for health technology innovations | 11 |
| Electronic procurement mechanisms for startups to supply to the public health sector | 12 |
| Platforms for experimental testing and validation of innovations at scale | 13 |
| Public-private partnership models for collaborative innovation | 14 |
| Awards and recognition programs for identifying promising innovations | 15 |
| Digital literacy programs for integrating innovations into workflows | 16 |
| Management support transition in change phases | 17 |
| Online educational systems for users of new health innovations | 18 |
| Mechanisms for user feedback and acceptance monitoring | 19 |
| Communication campaigns to build trust and awareness | 20 |
Categories are more abstract and at a higher level than what concepts show. That is, combining and putting together a few concepts of forming a category or class. This final table is used to formulate questionnaires in the second stage.
Identifying the Factors Affecting the Role of E-Government in the Biobomass Development of Innovation in Health
Validation and adjustment of the extracted factors were carried out based on the views of experts. In the interviews conducted with experts, 7 main factors are identified as factors affecting the role of e-government on the development of innovation ecosystem in the field of health، Classification and set in table 4.
Identifying the Factors Affecting the Role of E-Government in the Biobomass Development of Innovation in Health
Validation and adjustment of the extracted factors were carried out based on the views of experts. In the interviews conducted with experts, 7 main factors are identified as factors affecting the role of e-government on the development of innovation ecosystem in the field of health، Classification and set in table 4.
Table 4. Factors Affecting the Role of E-Government in the Development of Ecosystem Innovation in Health
| Of factors of main indicators | Factors | Row |
| Enable policies and regulations | Simple regulatory approvals to encourage digital health innovations | 1 |
| Policies around data standards and health information exchange | 2 | |
| Guidelines for the use of artificial intelligence and accountability in healthcare | 3 | |
| Telemedicine laws enabling virtual care models | 4 | |
| Procurement policies facilitating pilot implementation of innovations | 5 | |
| Access to data and infrastructure | Deployment of health identifier systems and EMR / EHR Access to data and infrastructure | 6 |
| 7 Accessible APIs for integration with public digital health platforms | 7 | |
| Anonymous public health datasets for analysis | 8 | |
| Cloud infrastructure and data storage for scaling innovations | 9 | |
| Rapid integration with government remote health systems | 10 | |
| Funding and accreditation opportunities | Government financial aid and incentives for health technology innovations Financial opportunities and validation | 11 |
| 12 Electronic procurement mechanisms for startups to supply to the public health sector | 12 | |
| 13 Platforms for experimental testing and validation of innovations at scale | 13 | |
| Public-private partnership models for collaborative innovation | 14 | |
| Awards and recognition programs for identifying promising innovations | 15 | |
| Ease of adoption and dissemination of innovations | Digital literacy programs for integrating innovations into workflows Facilitating acceptance and dissemination of innovations | 16 |
| Management support transition in change phases | 17 | |
| Online educational systems for users of new health innovations | 18 | |
| Mechanisms for user feedback and acceptance monitoring | 19 | |
| Communication campaigns to build trust and awareness | 20 |
Discussion
The present study was conducted to identify and describe the factors affecting the design of the innovation ecosystem model in the field of health with an emphasis on the role of e-government in Yazd province.
The development of innovation issues in countries has led to the formation of new concepts in this field (15). Some of these concepts include innovation systems ranging from national, sectoral, etc., innovation networks, commercialization and innovation ecosystem (16). In the past few years, some businesses have been formed with an innovative model in Iran and have grown well, which can be referred to as Digi Kala, Alibaba or Snap 1. But despite the formation and growth of a number of successful examples, the ecosystem of innovative businesses in Iran still exists in the early stages of its emergence and development. The biotech industry has a special place and feature in the modern industry sector (18). The industry has brought new scientific disciplines and attitudes, and in less than three decades, the pace of growth and development in its functional areas is astonishing (17). The success and impact of this industry is itself the result of its vast capabilities and scope of action (16)
In creating innovative ecosystems, policymakers must identify different bottlenecks, and in the early stages must ensure the active participation of local actors, which is the stage of need to build or upgrade the facilities are infrastructure. The absence of one or more coordinating actors can prevent the development of a Novaian ecosystem. On the other hand, the participation of local companies of organizations and universities promotes the growth and strengthening of the technology ecosystem. And ultimately, the growth of these systems will lead to the growth and development of a sustainable economy, and the cycle will be created. This way, with the development of economic growth, the government gets more resources and more funds can be spent on research and research activities (13).
The results of this study showed that the 4 main components of enabling policies and regulations, data access and infrastructure، Financing and validation opportunities and ease of acceptance and dissemination of innovations play a role in creating the ecosystem of innovation. While in the study of Dabbagh Afrouz and colleagues, 5 components of causal factors (government, financial capital), central category (university and research institutions), strategies (founding universities and research-oriented institutions،Shorten the process of obtaining licenses, government support for research and development, material and spiritual incentives and increase in venture capital), consequences (economic development and growth) and contextual factors (local attractiveness, banking services, intellectual property rights) intervening conditions (culture) were identified (13). And in the study of Asadi Fard and colleagues, factors affecting the formation and development of the university-based innovation ecosystem in 4 main categories including the type of cooperation, the way of institutionalization، the activities and characteristics of the main actor are classified (14).
The development of innovation issues in countries has led to the formation of new concepts in this field (15). Some of these concepts include innovation systems ranging from national, sectoral, etc., innovation networks, commercialization and innovation ecosystem (16). In the past few years, some businesses have been formed with an innovative model in Iran and have grown well, which can be referred to as Digi Kala, Alibaba or Snap 1. But despite the formation and growth of a number of successful examples, the ecosystem of innovative businesses in Iran still exists in the early stages of its emergence and development. The biotech industry has a special place and feature in the modern industry sector (18). The industry has brought new scientific disciplines and attitudes, and in less than three decades, the pace of growth and development in its functional areas is astonishing (17). The success and impact of this industry is itself the result of its vast capabilities and scope of action (16)
In creating innovative ecosystems, policymakers must identify different bottlenecks, and in the early stages must ensure the active participation of local actors, which is the stage of need to build or upgrade the facilities are infrastructure. The absence of one or more coordinating actors can prevent the development of a Novaian ecosystem. On the other hand, the participation of local companies of organizations and universities promotes the growth and strengthening of the technology ecosystem. And ultimately, the growth of these systems will lead to the growth and development of a sustainable economy, and the cycle will be created. This way, with the development of economic growth, the government gets more resources and more funds can be spent on research and research activities (13).
The results of this study showed that the 4 main components of enabling policies and regulations, data access and infrastructure، Financing and validation opportunities and ease of acceptance and dissemination of innovations play a role in creating the ecosystem of innovation. While in the study of Dabbagh Afrouz and colleagues, 5 components of causal factors (government, financial capital), central category (university and research institutions), strategies (founding universities and research-oriented institutions،Shorten the process of obtaining licenses, government support for research and development, material and spiritual incentives and increase in venture capital), consequences (economic development and growth) and contextual factors (local attractiveness, banking services, intellectual property rights) intervening conditions (culture) were identified (13). And in the study of Asadi Fard and colleagues, factors affecting the formation and development of the university-based innovation ecosystem in 4 main categories including the type of cooperation, the way of institutionalization، the activities and characteristics of the main actor are classified (14).
Conclusion
The results showed that in order to promote technology in the field of health, 4 basic dimensions (activation of policies and regulations, access to data and infrastructure) must be، funding and validation opportunities and ease of acceptance and dissemination of innovations (noticed). The process was explained in the form of the story line of the data theory of the electronic government. Finally, the innovation ecosystem model in the field of biotechnology was designed and analyzed. Finally, this model can be used to design an innovation ecosystem in the field of health.
The results showed that in order to promote technology in the field of health, 4 basic dimensions (activation of policies and regulations, access to data and infrastructure) must be، funding and validation opportunities and ease of acceptance and dissemination of innovations (noticed). The process was explained in the form of the story line of the data theory of the electronic government. Finally, the innovation ecosystem model in the field of biotechnology was designed and analyzed. Finally, this model can be used to design an innovation ecosystem in the field of health.
Conflict of interest
The authors hereby state that this work is the result of an independent study and has no conflict of interest with the organization or other persons. There is no conflict of interest among the authors of this article.
Acknowledgments
All the senior and middle managers of Yazd University of Medical Sciences who helped us in the implementation of this research are sincerely grateful.
Conflict of interest
The authors have no conflicts of interest to declare for this study.
Funding
None
Ethical considerations
The authors hereby state that this work is the result of an independent study and has no conflict of interest with the organization or other persons. There is no conflict of interest among the authors of this article.
Acknowledgments
All the senior and middle managers of Yazd University of Medical Sciences who helped us in the implementation of this research are sincerely grateful.
Conflict of interest
The authors have no conflicts of interest to declare for this study.
Funding
None
Ethical considerations
Ethical considerations were carefully addressed and implemented in the research study, including obtaining informed consent from participants, ensuring their privacy and confidentiality, and conducting the study in accordance with relevant ethical guidelines and regulations.
Code of ethics
IR.IAU.KERMAN.REC.1402.111
Authors’ contribution
IR.IAU.KERMAN.REC.1402.111
Authors’ contribution
All authors (Z.M., A.B.N., S.S., H.R.M) had an equal contributio and were involved in all aspects of study conception and design, data collection, data analysis, interpretation, drafting of the manuscript, and critically revising the manuscript for intellectually important content. All the authors have read and approved the final version of the manuscript and agreed to be accountable for all aspects of the work.
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