Search

The mother is traditionally the primary caregiver for the child, and uncertainty is a major source of psychological distress for parents of sick children. As a result, the current study sought to investigate the impact of an educational program on illness uncertainty in mothers of children with insulin-dependent diabetes mellitus (IDDM). This is a quasi-experimental study with a pretest-posttest design, involving 40 mothers of children with IDDM. After visiting the research site and recruiting eligible mothers, the researcher used the purposive sampling method to randomly assign them to one of two intervention and control groups. Taking into account their needs and conditions, mothers were scheduled for at least three sessions, with a 30-minute interval every other day. The data analysis revealed no significant differences between the two groups in terms of child age and gender, mother age and education level, number of children, and duration of diabetes. There was a significant difference in the total score of uncertainty, total score of ambiguity, lack of clarity, lack of information, unpredictability, and their dimensions between mothers of diabetic children before and after the intervention (P=0.02). Based on the findings, it is recommended that the educational needs of children and their mothers be assessed upon admission and that educational content be prepared and taught accordingly, thereby helping to reduce illness uncertainty in mothers.

Background High-grade gliomas (HGGs) are the most prevalent primary malignancy of the central nervous system. The tumor results in vasogenic and infiltrative edema . Exact anatomical differentiation of these edemas is so important for surgical planning. Multimodal imaging could be used to differentiate the edema type.

Abstract Background This observational study aims to describe and compare histopathological, architectural, and nuclear characteristics of sebaceous lesions and utilized these characteristics to develop a predictive classification approach using machine learning algorithms. Methods This cross-sectional study was conducted on Iranian patients with sebaceous tumors from two hospitals between March 2015 and March 2019. Pathology slides were reviewed by two pathologists and the architectural and cytological attributes were recorded. Multiple decision tree models were trained using 5-fold cross validation to determine the most important predictor variables and to develop a simple prediction model. Results This study assessed the characteristics of 123 sebaceous tumors. Histopathological findings, including pagetoid appearance, neurovascular invasion, atypical mitosis, extensive necrotic area, poor cell differentiation, and non-lobular tumor growth pattern, as well as nuclear features, including highly irregular nuclear contour, and large nuclear size were exclusively observed in carcinomatous tumors. Among non-carcinomatous lesions, some sebaceoma and sebaceous adenoma cases had features like high mitotic activity, which can be misleading and complicate diagnosis. Based on multiple decision tree models, the five most critical variables for lesion categorization were identified as: basaloid cell count, peripheral basaloid cell layers, tumor margin, nuclear size, and chromatin. Conclusions This study implemented a machine learning modeling approach to help optimally categorize sebaceous lesions based on architectural and nuclear features. However, studies of larger sample sizes are needed to ensure the accuracy of our suggested predictive model.

The supply chain for perishable products, especially agricultural goods, has always been one of the most important and challenging management issues at different times. Because, at all stages of the agricultural production process, unsafe and unsanitary factors may endanger the health of agricultural products. In addition, one of the key problems of the agricultural supply chain is the high volume of products wasted throughout the whole supply chain. For example, in Iran, as a developing country, about 30% of all agricultural products are wasted annually. The high volume of agricultural waste is especially important concerning wheat products as a political and strategic product. The results of some studies show that a large amount of wheat waste in developing countries is due to the widespread use of traditional methods in the storage process. Therefore, the application of emerging technologies such as the Internet of Things (IoT) can be an effective solution to this kind of problem. However, there are shortcomings in the IoT deployment in the supply chain, especially in the logistics sector, and researchers need to cover theoretical gaps in this area through modeling and optimization. Therefore, the present study intends to emphasize this important research issue for the first time in Iran using the Action Design Research approach. The most important findings of this research include the conceptual data model, the logical model of the database, and the physical data model for the IoT deployment in the storage section of the wheat supply chain, which has been designed and validated with the participation of industry and software engineering experts. The models designed in this research can be useful for the implementation of IoT technology in wheat storage centers and food factories. The findings of this study can provide a good guideline for officials and decision-makers to deploying IoT in the field of wheat storage.

Abstract Background Disseminated intravascular coagulation (DIC) has been reported in various solid malignancies and is a common coagulation‐related complication in prostate cancer. However, DIC has been rarely reported as the initial presentation of prostate cancer. Herein, we reported a patient referring with subdural hemorrhage (SDH) and DIC with an unexplained cause who was later diagnosed with prostate cancer. Case Presentation We presented a 68‐year‐old man who was referred to the hospital with a gradual deterioration of consciousness, dyspnea, and edema in the genitalia and lower limbs. His primary laboratory tests showed elevated prothrombin time (PT) and partial thromboplastin time (PTT) and a decreased fibrinogen level of 47 mg/dL [200–400 mg/dL]. The DIC score was 7, which was suggestive of DIC. Moreover, cranial imaging showed SDH. Further work‐up revealed elevated prostate‐specific antigen and prostate enlargement with a mass effect on the bladder with a bone lesion, which was suggestive of metastatic prostate cancer. Conclusion This report highlights DIC as a possible initial presentation of an underlying malignancy, as well as the importance of treatment of underlying disease in the management of DIC. A comprehensive and systematic work‐up is essential for early diagnosis in patients with DIC to avoid further complications and mortality.

Introduction: Distal forearm fractures’ realignment and fixation is a painful procedure. This study aimed to compare the efficacy of periosteal nerve block and intravenous morphine in distal radius and ulna fractures’ pain management. Methods: In the present randomized, parallel, double-blind, controlled clinical trial, patients with distal radius or ulna fractures were divided into two groups. In the first group, for periosteal nerve block, 1% lidocaine was injected at a distance of 6 to 8 cm near the wrist from the lateral radius and medial ulna. In the second group, morphine sulfate at a dose of 0.1 mg/kg was slowly injected through the peripheral vein within 5 minutes. The visual analog scale (VAS) score was evaluated before the intervention and every 15 minutes until 90 minutes after the intervention and was compared between the two groups. Results: 75 subjects were studied (39 in the periosteal nerve block and 36 in the intravenous morphine group). There were no significant differences between the groups in terms of mean age (p = 0.384), gender distribution (p = 0.464), past medical history (p = 0.106), trauma type (p = 0.836), fracture type (p = 0.613), and baseline pain severity on VAS (p = 0.987). Both methods reduced the VAS scores during the 90 minutes of the study. The mean pain scores of the patients in the periosteal nerve block group with 2.56±1.44, 2.15±1.11, 2.66±1.26, and 3±1.27 at 15, 30, 45, and 60 minutes after the analgesic injection, respectively, were significantly lower than those of the intravenous morphine group with 4.75±1.27, 4.22±1.22, 3.97±1.27, and 4.13±1.35, respectively (p < 0.001 for all comparisons). In the present study, no local or systemic complications were observed in the periosteal nerve block group, while the complications of dyspnea, vomiting, and pruritus were reported by 5.5%, 2.8%, and 2.8%, respectively, in the intravenous morphine group. Moreover, the percentage of need for additional analgesia in the intravenous morphine group was higher than that of the periosteal nerve block group. Conclusion: In the first hour after the intervention, pain reduction in periosteal block was significantly higher than intravenous morphine administration. Also, the incidence of complications and the need for additional analgesia were lower in the periosteal block group compared to intravenous morphine administration.

Objective: Saffron is a spice derived from the Crocus sativus L. with antioxidant, anti-inflammatory, and neuroprotective effects. This study aims to systematically review the systematic reviews (SRs) investigating the clinical neuropsychotropic effects of saffron.Materials and Methods: The protocol of this SR was registered in PROSPERO (CRD42021268446). Scopus, ISI Web of Science, Embase, MEDLINE, PubMed, CINAHL, Cochrane Library, Google Scholar, and PROSPERO were searched up to June 6, 2021, to find SRs investigating the neuropsychotropic effects of saffron. The primary outcome was a report on whether or not saffron was effective in each study. AMSTAR was checked for the included reviews.Results: Twenty-three studies were reviewed with a mean AMSTAR score of 6.08 (ranging from 1 to 10). Thirteen SRs investigated the effects of saffron on depression. Six of the SRs studied its impact on sexual dysfunction. Each of the anxiety and cognitive disorders was discussed in three distinct reviews. Furthermore, possible effects of saffron on some other disorders, like premenstrual syndrome, postpartum depression, sleep disorders, and snacking behavior, have been reported.Conclusion: Saffron is beneficial, safe, and tolerable in treating the mentioned neurological and psychiatric disorders. Further high-quality, large-scale studies are recommended to rectify the shortcomings.

Abstract Background Delirium is a neurobehavioral syndrome, which is characterized by a fluctuation of mental status, disorientation, confusion and inappropriate behavior, and it is prevalent among hospitalized patients. Recognizing modifiable risk factors of delirium is the key point for improving our preventive strategies and restraining its devastating consequences. This study aimed to identify and investigate various factors predisposing hospitalized patients to develop delirium, focusing mostly on underlying diseases and medications. Method In a prospective, observational trial, we investigated 220 patients who had been admitted to the internal, emergency, surgery and hematology-oncology departments. We employed the Confusion Assessment Method (CAM) questionnaire, The Richmond Agitation Sedation Scale (RASS), the General Practitioner Assessment of Cognition (GPCOG), demographic questionnaire, patient interviews and medical records. Multivariate logistic regression models were used to analyze the predictive value of medications and underlying diseases for daily transition to delirium.; demographics were analyzed using univariate analysis to identify those independently associated with delirium. Results Two hundred twenty patients were enrolled; the emergency department had the most incident delirium (31.3%), and the surgery section had the least (2.4%); delirium was significantly correlated with older ages and sleep disturbance. Among multiple underlying diseases and the medications evaluated in this study, we found that a history of dementia, neurological diseases and malignancies increases the odds of transition to delirium and the use of anticoagulants decreases the incident delirium. Conclusion Approximately 1 out of 10 overall patients developed delirium; It is important to evaluate underlying diseases and medications more thoroughly in hospitalized patients to assess the risk of delirium.

In recent years, the number of articles studying the Internet of Things technology in supply chain management and logistic has grown rapidly. The purpose of this paper is analyzing the studies that have been done in this area by reviewing the relevant literature and while identifying the existing theoretical gaps, introduces future research opportunities. This paper collects and analyzes information using a systematic literature review methodology and paradigm funnel approach. Systematic literature review is a methodology reliable and recommended by a large number of scientific papers. However, selection of certain criteria for inclusion and exclusion of papers introduces publication bias, which should be considered an intrinsic limitation to systematic literature review. Numerous studies have been conducted in the area of Internet of Things and supply chain management, but there is no synthesis of the knowledge that would allow one to draw conclusions regarding the evolving nature Internet of Things in supply chain management and to extend the theories in this area. This paper will address that gap, applying the paradigm funnel technique. For this purpose, Scopus, Science Direct, Emerald and Francis & Taylor databases were searched and a total of 209 articles were retrieved. After initial screening, 105 articles were excluded due to inconsistency with inclusion criteria and after qualitative screening, a total of 36 studies were selected for analysis. The selected 36 articles focus mainly on level 2 and 3 of the paradigm funnel. Only two articles were placed in the first level of the paradigm funnel and no studies in the level of deep hypotheses (fourth level) were observed. Most studies used qualitative methods to collect and analyze data. Also, the findings show that future researches can use empirical observations and data generation to further exploration of internet of things in supply chain management and logistic.

In recent years, crowd funding has seriously been considered as a novel method of financing start-up businesses and innovative ideas. In its short life time so far, the method has significantly grown in different aspects such as the number of proposed platforms, the number of campaigns and their success rate, the amount of capital provided, and the number of proposed models. In addition, various researchers have investigated the phenomenon from different points of view. Nevertheless, just a few studies have carried out a comprehensive review of the factors affecting this method. The main purpose of this research is to design and implement a comprehensive framework for factors that affect crowd funding. In order to achieve this goal, the effective factors in this regard were first identified through systematic review of the literature on crowd funding. Then, they were classified and clustered in a hexagonal framework based on the stakeholder's model. In other words, a qualitative method is used to extract the factors affecting crowd funding. The hexagons extracted from the literature were in 82 clusters out of which 38 were accounted for by capital seekers, 16 by investors and platforms, and 12 by other stakeholders. This study is the first effort to design a comprehensive framework for factors that affect crowd funding. Doi: 10.28991/HIJ-2021-02-02-07 Full Text: PDF

Studies show that there are shortcomings in the deployment of the Internet ofThings (IoT) in the supply chain of agricultural products, especially in thefield of quality control in the logistics sector, and researchers can model theexisting theoretical gaps through modeling and optimization. Therefore, thepurpose of this paper is to identify the most important categories affectingthe deployment of the Internet of Things in the wheat supply chain storagesector and explain and mapping the relationship between these categories.For this purpose, the present article uses meta-synthesis method by searchingWeb of Science and Scopus citation databases. Then, the grounded theorycoding procedures were used to determine categories and themes. Finally,the results of meta-synthesis lead to the identification and extraction of 3macro categories; IoT technology, the main category (IoT-based storage),and the results and consequences of IoT deployment.

Objective: Available treatments of depression have limited efficacy and unsatisfactory remission rates. This study aims to review randomized controlled trials (RCTs) investigating effects of glutamate receptor modulators in treating patients with resistant depression. Method: The study protocol was registered in PROSPERO (CRD42021225516). Scopus, ISI Web of Science, Embase, Cochrane Library, Google Scholar, and three trial registries were searched up to September 2020 to find RCTs evaluating glutamate receptor modulators for resistant depression. The difference between intervention and control groups in changing depression scores from baseline to endpoint was considered the primary outcome. Version 2 of the Cochrane risk-of-bias tool for randomized trials was used to assess the quality of the RCTs. No funding was received. Results: Thirty-eight RCTs were included. Based on the included studies, compelling evidence was found for ketamine (with or without electroconvulsive therapy, intravenous or other forms), nitrous oxide, amantadine, and rislenemdaz (MK-0657); the results for MK-0657, amantadine, and nitrous oxide were only based on one study for each. Lithium, lanicemine, D-cycloserine, and decoglurant showed mixed results for efficacy, and, riluzole, and 7-chlorokynurenic acid were mostly comparable to placebo. A limited number of studies were available that addressed drugs other than ketamine. Conclusion: The study cannot determine the difference between statistical and clinical significance between the agents and placebo due to high heterogeneity among the RCTs. Nevertheless, ketamine could be used as an efficacious drug in TRD; still, additional studies are needed to delineate the optimum dosage, duration of efficacy, and intervals. Further studies are also recommended on the effectiveness of glutamatergic system modulators other than ketamine on treatment-resistant depression.

Introduction: Health insurance supervision and control has important role in achieving the health insurance and health system mission and goals, but it has not received much attention. This study aimed to review the researches related to health insurance supervision and control, and categorize the used topics and related data sources. Methods: The study was conducted using systematic mapping method. A total of 316 research papers (published until the end of 2018) were investigated in related databases. Atlas.ti8 software and keywording technique were used for analysis and data extraction. Results: Seven health insurance supervision (health insurance program/policy monitoring, cost control, coverage and financial protection, equity in health, health insurance data and claims assessment, and people/insured and health service supplier and control topics) as well as nine data sources were identified. Conclusion: Health insurance program/policy monitoring and cost control topics had the most research number, and people/insured and health service supplier topics were the least related researches.

Along with the influence of the Internet and the dramatic advances in the use of information technology in businesses, a new concept has been introduced in the tourism literature called smart tourism destinations. Although studies have been conducted in this area in recent years, the research process is not clear due to the short time of introduction and development of this technology. In addition, the synthesis of knowledge has not been done in order to draw conclusions about the evolutionary nature of this issue and to develop its theories. This study used the paradigm funnel method to fill this gap and investigate the research. For this purpose, 105 articles were reviewed from 2000 to 2017, and after selecting articles, 34 articles were identified and classified. The findings indicate the focus of the articles is on the level of specific theories and the lack of articles in the field of ontology and basic hypotheses. This study will help researchers to better understand the conducted research process, to get acquainted with the concepts and components, and to identify the existing research gap.

Infrequent and ineffective usage of IT after initial adoption may incur undesirable costs or results in waste of effort to develop the IT. Most of information systems (IS) continuance models try to define how users accept IS and use it. The aim of these models which originally were developed for marketing research and modeling of repurchase behavior of consumer, is evaluation of loyalty and continuance in individual level of system usage or measures of acceptance of systems is used for studying continuance of systems while effective factors of continuance for organizational user are ignored. Therefore, in this research for identifying affecting factors on continuance of information systems, the main factors are defined by reviewing literature, and through semi-structured interview independent variables are defined including independent variables like governor, manager, leadership style, technology change, strategy, users, customer expectation, culture, law, transparency, system position and mediator variables like positive and negative switching costs and the model is made by using Atlas T/I software in the last step, final model of research is customized in the Ministry of Communication and Information Technology.

Effective knowledge management (KM) is essential to almost any organization. Regardless of its size or subject matter, an organization should use the knowledge it possesses in the most effective way possible. But the implementation of KM is still challenging. One of the solutions for this challenge which mentioned in KM literature is knowledge management roadmapping. Roadmaps provide a graphical means for exploring and communicating the relationships among any types of knowledge in the organization. Therefore, in this research, a framework for roadmapping organizational knowledge management has developed. In the first phase, beneficiary systematic literature review, qualitative content analysis and interview with expertise, the basic components of organizational knowledge management (OKM) roadmapping have determined and specified. These components have divided into seven main categories: “causal conditions”, “OKM Roadmap components”, “roadmapping requirements”, “requirements for successful OKM implementation”, “OKM Roadmap preparation and the development process”, “visual and content characteristics of an OKM roadmap” and “OKM Roadmap outcomes”. After that, by calculating the correlation (Pearson correlation coefficients) between these components “OKM roadmap framework” was proposed. The final framework provides a flow between components which describe the way of drawing a roadmap for OKM implementation. The reliability of research has been evaluated by Kappa coefficient (0.743).

Designing an effective structure for knowledge management is one of the critical factors for its success in the organization. Structuring to KM and identifying the experts of this field in the structure of the organization is necessary to achieve the sustained and continuous benefits of knowledge management. This paper deals with the conceptualizing of knowledge management office as the organizational structure for effective management of knowledge. For this purpose, Meta-synthesize methodology was adopted. From 198 sources founded, 12 articles were consistent with accepted standards. As a result of combining the findings, concept of knowledge management office was figured with 54 codes, 12 concepts in the four themes including purpose (Strategic and Functional), structure (Centralized and Decentralized and Mixed), function (Strategies, Processes and Mechanisms) and role (KM Committee, CKO, knowledge manager, Knowledge Representative). Organizations can use the results of this study to establish an appropriate structure of knowledge management. According to research, any article was not found by the researchers that have has this integrity and methodology. So, this paper has innovation.

Cloud computing is a new technology that considerably helps Higher Education Institutions (HEIs) to develop and create competitive advantage with inherent characteristics such as flexibility, scalability, accessibility, reliability, fault tolerant and economic efficiency. Due to the numerous advantages of cloud computing, and in order to take advantage of cloud computing infrastructure, services of universities and HEIs need to migrate to the cloud. However, this transition involves many challenges, one of which is lack or shortage of appropriate architecture for migration to the technology. Using a reliable architecture for migration ensures managers to mitigate risks in the cloud computing technology. Therefore, organizations always search for suitable cloud computing architecture. In previous studies, these important features have received less attention and have not been achieved in a comprehensive way. The aim of this study is to use a meta-synthesis method for the first time to analyze the previously published studies and to suggest appropriate hybrid cloud migration architecture (IUHEC). We reviewed many papers from relevant journals and conference proceedings. The concepts extracted from these papers are classified to related categories and sub-categories. Then, we developed our proposed hybrid architecture based on these concepts and categories. The proposed architecture was validated by a panel of experts and Lawshe’s model was used to determine the content validity. Due to its innovative yet user-friendly nature, comprehensiveness, and high security, this architecture can help HEIs have an effective migration to cloud computing environment.

Despite the various models and frameworks on electronic good governance are introduced, the multiple dimensions model of electronic good governance in the field of e-Learning has not been reviewed this subject in a integrated, comprehensive, process-oriented and systematic model. In this article, in order to explain the process of electronic good governance, by a systematic review of the related literature and backgrounds, all factors were identified using meta-synthesis methodology. Then, based on grounded theory methodology and Strauss and Corbin paradigmatic approach, the open, axial and selective coding were conducted. In the following, by using survey method, we determined the importance and priority of all proposed factors. It was also indicated that this research was innovative in the fields of methodology, results and the proposed model which had not been considered in the previous researches. So that, the proposed model resolved the shortcomings of past researches and made it possible for the public sector, private and civil society organizations to consider the process of establishing electronic good governance in e-Learning sector in Iran as a dynamic process.

Certainly in modern organizations knowledge & its management is basic & one of the most important issues. Powerful organizations in knowledge management are pioneer & always are in the first line of competition. It is obvious that rate & quality in creation, dissemination & use of knowledge are competitive advantage for organizations. As regards modern organizations use technology & new tools, enterprise 2.0 is known as a good organization in use of web 2.0 tools & high cooperation of staff. Passing of Enterprise 1.0 to Enterprise 2.0 & try for creation &diffusion of knowledge in Enterprise 2.0 have its own problems that without knowing of them & a certain framework, the probability of success is very low. This Research presents the framework of creation & diffusion of knowledge in Enterprise 2.0 according of library resources & presents learning 2.0, communications 2.0, generated content & collaboration 2.0 as 4 stages of creation &diffusion of knowledge in Enterprise 2.0. Then we investigate any of stages according of human, knowledge & technology. Also this research emphasizes that for creation &diffusion of knowledge in Enterprise 2.0 in addition of web 2.0 tools usage as a good communication tools, Cultural interaction, Consultation & association in a free Environment are very important too.

The allocation of information is one of the main responsibilities of a manager. In case there is a limitation in the available resources, the issue of resources allocation is raised. Universities and post graduate centers have faced limitations in accessing resources such as budget, human resources, physical space, etc. This problem results in inappropriate use of the approved budget in buying and sharing the different types of information resources, lack of easy access to information resources by users, and users’ dissatisfaction. This paper is intended to see whether the model of genetic algorithm can be used in helping library heads of university to develop a support system for the proper allocation of resources. The data of the central library of a university as the main core of DSS through using genetic algorithm in MATLAB was used in order to come up with a better distribution of effective resources. Research methodology used in this paper was field study and survey. The findings indicated that genetic algorithm was successful in achieving this end.

The organizational activities are political, because in this context interests, power and conflict of interests exist. Therefore, one of the apparent behaviors of people is political behavior. This study seeks to answer the question that what factors are causing political behavior in organization? Researcher after describing the theoretical foundations, tests the process of inter-organizational variables that indicate the formation of such behavior in the companies of water sector. This research method is survey. This research data was collected by using a sample of 525 people of managers and experts of water industry, with stratified random sampling method. Content validity of the questionnaires was confirmed and its reliability was confirmed with Cronbach,s alpha coefficient for each variable. For data analysis by Structural equation modeling and path analysis were used LISREl and Smart P.L.S. The research results show that identified variables except locus of control and self-monitoring affect the political behavior of employees.

Today, SOA has created the opportunities to improve agility and speed in matching business needs with information technology infrastructure. Since the organization in the process of using this technology faces many challenges and may spend a lot of energy and despite huge investments, failure, therefore need to implement a model for SOA governance that based on a gradual approach and SOA maturity of the organization determine what actions they do to move toward SOA. Therefore, this study was following present such a model. Data gathering tool was questionnaire. In order to confirm the model of study, sample included 16 academic experts. The results confirmed the model of this study.

Chooshing the Knowledge management strategy is affected by different organizational factors like business strategy, organizational structure, organizational culture, Information Technology strategy, human resource management, and dynamics of knowledge. It is difficult for strategists to consider all these factors in choosing appropriate KM strategy. In this research after presenting a six step methodology for KM strategy development, we designed a decision support expert system for supporting the process of knowledge management strategy development. This system has been implemented in three Iranian companies as a multi-case study. We used a questionnaire for validating the knowledge base and model base of the system. Furthermore, we compared the expert system results with the result of developing KM strategy without using expert system by analytical statistics techniques.

This paper contributes to identify systematic problems in NIS using Thinking Process (TOC-TP) and to eliminate the bottlenecks, which results in improving the innovation process and efficiency of NIS. The Case study in this research is the NIS of Iran. The national documents of the innovation system were studied and all problems of NIS mentioned in documents were gathered. The causal relationships between the systematic problems were identified by the survey and grouped into 6 components by Exploratory Factor Analysis: weakness in technology diffusion mechanisms, the lack of centralized governance on science and technology policy, the government's pivotal role as an executor in education and research, weak laws and regulations in the field of research and technology, the lack of adequate financial resources in R&D and the lack of any perspective on the creation of wealth and entrepreneurship among the actors of research and technology. Finally the bottleneck of Iran's NIS was recognized by Thinking Process tools: the small participation of private sector in research and education system as the result of government's pivotal role as an executor of Iran's national innovation system. So the researchers could diagnose the policy gaps related to the identified bottlenecks. First published online: 11 Aug 2014