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This study aims to apply some concepts of actuarial statistics to the authorship of Iranian ISI papers in the field of chemistry based on Price’s model. The study determines scientific birth rate, death rate, infant mortality rate, natural increase rate and life expectancy.

Price maintained that authors in each given period in any field fall into four categories including newcomers, transients, continuants and terminators. He suggested that actuarial statistics could be applied to authorship to calculate death rate and birth rate in scientific fields. A total 25,573 papers written by 59,661 Iranian chemistry authors between 1973 and 2012 were downloaded from Web of Science (WoS) and were subjected to statistical analysis.

The average birth rate was 66.7 per cent, the average death rate was 19.4 per cent, infant mortality rate was 51.2 per cent, average natural increase was 47.3 per cent, the average life expectancy was 1.98 years and the longest scientific age was 22 years. The results show that although a large number of people start their scientific activity, the number of those who terminate their activity in the same year as they start (infant mortality rate) is also large and little continuity exists in the publishing activities of Iranian chemists.

The findings have implications for the planning of human resources in science. They could help maintain a stable scientific labor force and decide for instance whether a larger number of scientists should be trained and hired, or the barriers should be removed so the existing scientists can work for more years. The limitation is that the study is restricted to ISI articles, although they are not the only kind of scientific output.

This is the first study of its kind on Iranian scientific output. It shows that the overall labor force in the field of chemistry in Iran was not satisfactory, as the majority of authors in each period are transients. There is a need for better planning for the labor force.

The purpose of this study is to develop a domain independent, cost-effective, time-saving and semi-automated ontology generation framework that could extract taxonomic concepts from unstructured text corpus. In the human disease domain, ontologies are found to be extremely useful for managing the diversity of technical expressions in favour of information retrieval objectives. The boundaries of these domains are expanding so fast that it is essential to continuously develop new ontologies or upgrade available ones.

This paper proposes a semi-automated approach that extracts entities/relations via text mining of scientific publications. Text mining-based ontology (TmbOnt)-named code is generated to assist a user in capturing, processing and establishing ontology elements. This code takes a pile of unstructured text files as input and projects them into high-valued entities or relations as output. As a semi-automated approach, a user supervises the process, filters meaningful predecessor/successor phrases and finalizes the demanded ontology-taxonomy. To verify the practical capabilities of the scheme, a case study was performed to drive glaucoma ontology-taxonomy. For this purpose, text files containing 10,000 records were collected from PubMed.

The proposed approach processed over 3.8 million tokenized terms of those records and yielded the resultant glaucoma ontology-taxonomy. Compared with two famous disease ontologies, TmbOnt-driven taxonomy demonstrated a 60%–100% coverage ratio against famous medical thesauruses and ontology taxonomies, such as Human Disease Ontology, Medical Subject Headings and National Cancer Institute Thesaurus, with an average of 70% additional terms recommended for ontology development.

According to the literature, the proposed scheme demonstrated novel capability in expanding the ontology-taxonomy structure with a semi-automated text mining approach, aiming for future fully-automated approaches.

The purpose of this paper is to identify and design the axial coding pattern of the factors affecting the unplanned use behavior of users of the academic libraries and information centers.

The study as an applied research with a qualitative approach employed the grounded theory. The data collection tool was a deep and semi-structured interview. The interviews data were analyzed and coded during three stages of open, axial and selective coding using the MAXQDA 10 qualitative analysis software. The research population consisted of faculty members and experts in three areas of library and information science, management and psychology. Using the combined targeted sampling method (targeted and then the snowball), 12 subjects were selected as the sample size.

According to the research findings, the factors affecting the unplanned behavior of users in the use of academic libraries resources and services were identified as factors related to technology, environmental factors, information resources, information services, human resources, individual features, time position factor, cultural factors and social factors. Accordingly, the axial coding pattern of this type of behaviors was designed.

The research limitations include the lack of theoretical basis related to the unplanned behavior issue in the field of library and information science and the lack of full familiarity of most of the experts in the field of library and information science with this topic. These factors lead to the necessity of explaining the subject under discussion.

The unplanned behavior of clients can be utilized to persuade users to use the information resources and library services so that the costs spent on their preparation and collection will be justifiable. The current research addressed this aspect of the unplanned information-seeking behavior.

This study aimed to present a model for open-data management for developing innovative information flow in Iranian knowledge-based companies (businesses).

The method was mixed (qualitative-quantitative) and data collection tools were interview and questionnaire. The qualitative part was done to identify the influential components in open data management (ecosystem) using the grounded theory method. A questionnaire was developed based on the results of the qualitative section and the theoretical foundations, and the quantitative section was conducted by analytical survey method and the model was extracted using factor analysis and the integration of the qualitative section.

Seven categories of entrepreneurial incentives, sustainable value, innovative features, challenges and barriers, actors, business model and requirements are the main categories that should be considered in open data management (ecosystem) with all categories of research have a significant relationship with open data management.

The study focused on open data management from an innovation paradigm perspective and its role in developing innovative information flow. The study aimed to identify the key components of the open data ecosystem, open-data value creation, and the need to use the “open data” approach to develop data-driven and knowledge-based businesses in Iran–an emerging approach largely ignored.

The dynamism of new economy requires information professionals not only to create knowledge quickly but also to acquire and apply knowledge through knowledge sharing (KS). So, determining factors that may influence knowledge sharing within an organization or among organizations has become an important area of research. This paper aims to review determinant factors influencing inter- and intra-organizational knowledge sharing in order to offer a framework.

The present paper proceeds in three phases. In the first phase, the published literature on knowledge sharing has been reviewed extensively with consideration of their empirical applications. Next, based on the understanding gained from the previous stage, a conceptual framework of successful factors for effective inter-organizational knowledge sharing has been proposed. In the third phase, the proposed framework has been developed and finalized towards its maturity.

Based on the literature, the authors have developed a framework for understanding factors which influence inter-organizational knowledge sharing. Knowledge sharing among organizations appears theoretically sound, but it is a difficult task due to some complexities.

This paper attempts to set a theoretical framework for inter-organizational knowledge sharing as a foundation to address the gap in current literature though it does not claim to be comprehensive.

A few attempts have been made to investigate success factors for inter-organizational knowledge sharing empirically or even theoretically, but this is the first of its kind that provides a theoretical framework to arrange success factors for the knowledge sharing based on inter-organizational collaborations. It serves as a useful starting point for those interested in knowledge management (KM). So it can serve as a roadmap of significant knowledge sharing research for researchers, designers and managers considering their options for fostering KM.

The purpose of this paper is to evaluate the status of organizational climate of Iranian academic libraries and map its structural equation model. Organizational climate is one of the main indicators of organizational health and dynamic.

This research was an applied survey. The statistical population of the research included all staff working in 96 central libraries of Iranian governmental universities (N = 520). A self-administered questionnaire was used for data collection. Some descriptive and inferential statistical methods applied for data analysis in SPSS and factor analysis in LISREL software were used for modelling organizational climates in the libraries.

The t values of factor analysis pass showed that the effect of all indicators of ClimateQUAL on organizational climate was significant. The factor loading of the pass model showed that among the nine indicators, climate for psychological safety with 5.24, climate for innovation with 5.06 and climate for leadership with 4.93 had a higher effect on organizational climate of the libraries. Considering the values of goodness-of-fit indicators, the path model has an optimal status in all indicators, but that of RMSEA in which the status is relatively acceptable. The observed data relatively matched the theoretical model.

The t values of factor analysis pass showed that the effect of all indicators of ClimateQUAL on organizational climate was significant. The factor loading of the pass model showed that among the nine indicators, climate for psychological security with 5.24, climate for innovation with 5.06 and climate for leadership with 4.93 had a higher effect on organizational climate of the libraries. Considering the values of goodness-of-fit indicators, the path model has an optimal status in all indicators, except the RMSEA in which the status is relatively acceptable. The observed data relatively matched the theoretical model.

This paper aims to evaluate the use and the costs of AMIN, the interlibrary loan service in Iran.

A questionnaire was used for the data collection. It was completed by those librarians in charge of AMIN in academic libraries.

The statistics collected from six libraries showed that 514 items were loaned, of which 49 per cent were journal articles and 43 per cent were books. Post was used for the delivery of about 55 per cent of the items, while e‐mail was used for the delivery of only 7 per cent of the items. The average time spent dealing with each request (the time lapse between receipt of the request and dispatching the item) was about 7.1 days. The library of the University of Tehran was the most effective library in this regard as it only took 3.4 days on average for each request. The study revealed that the participating libraries did not have a proper procedure in place for collecting usage statistics and therefore one cannot evaluate the effectiveness of the AMIN service.

The paper reveals the cost of document supply in Iranian academic libraries and illustrates that ILL services in Iran are not efficient and that measures could be taken to reduce the cost and increase the efficiency of services.

The purpose of this study paper is to identify and prioritize the factors affecting the knowledge flow in high-tech industries.

This research is applied in terms of purpose and descriptive-survey in terms of data collection method. This research has been done in a qualitative–quantitative method. In the qualitative part, due to the nature of the data in this study, expert interviews have been used. The sample studied in this research includes 35 managers and expert professors with experience in the field of knowledge management working in universities and high-tech industries who have been selected by the method of snowball. In the quantitative part, the questionnaire tool and DANP multivariate decision-making method have been used.

In this study, a multicriteria decision-making technique using a combination of DEMATEL and ANP (DANP) was used to identify and prioritize the factors affecting the knowledge flow in high-tech industries. In this study, the factors affecting the knowledge flow, including 8 main factors and 31 subfactors, were selected. Human resources, organizational structure, organizational culture, knowledge communication, knowledge management tools, knowledge characteristics, laws, policies and regulations and financial resources were effective in improving knowledge flow, respectively.

By studying the research, it was found that the study area is limited, and the previous work has remained at the level of documentation and little practical use has been done. In previous research, the discussion of knowledge flow has not been very open, and doing incomplete work causes limited experiences and increases cost and time wastage, and parallel work may also occur. Therefore, to complete the knowledge management circle and fully achieve the research objectives, as well as to make available and transfer the experiences of people working in this field and also to save time and reduce costs, the contents and factors of previous models have been counted. It is designed for high-tech industries, a model for the flow of knowledge.

The library is one of the critical foundations of informing and educating the public, and it should fulfil its function in the community, which is disseminating knowledge effectively. The library must have a dynamic space and an appropriate atmosphere to do this. Also, librarians should assist clients outside of stressful work environments. This study aimed to examine the association between organizational climate and job burnout in the hospital and college libraries of Shahid Beheshti University of Medical Sciences.

This study is a cross-sectional survey. The population includes all librarians working in the college and hospital libraries of Shahid Beheshti University of Medical Sciences. Two questionnaires, including organizational climate “ClimateQUAL” and job burnout “Maslach and Jackson”, were applied to collect data. It was hypothesized that there is a correlation between the organizational climate and the burnout of librarians.

The findings revealed that the organizational climate and job burnout are not in a favourable situation, with average scores of 4.70 and 2.50, respectively. Furthermore, there is a significant statistical relationship between organizational climate and job burnout (p-value<0.001).

Knowledge of the significant relationship between the organizational climate and job burnout in medical libraries may encourage policymakers to make more efforts to provide their staff with a better climate and less burnout. Regarding that it is crucial to enhance the existing condition in medical libraries, the findings of the present study suggest that policymakers should be conscious of improving the current condition, which could lead to promoting patrons’ satisfaction and productivity in the mentioned libraries.