Scientific growth is one aspect of development that demonstrates how competitive each nation is regarding its science and technology achievements. Different indicators have been developed in order to show the scientific and scholarly competency of nations, including what follows: (a) quantity of contribution in production of scholarly literature on a global level, such as what appears in Scimago (Guerrero-Botea & Moya-Anegón, 2012) and Web of Science; (b) innovations and registered patents, especially if registered by international authorities; (c) access to and utilization of new technologies such as access to high speed Internet; and (d) the amount of investment in technology and research, especially compared to the whole of expenditures in a single country. Details on science and technology indicators on a national level can be found in Grupp and Mogee (2005).
Research and development (R&D) intensity refers to the expenditures on R&D as a proportion of GDP and can indicate the relative amount of investment for generating new knowledge (OECD, 2012). Since the 1990s, in many developing countries governments started adopting new knowledge-based economies, paying attention to R&D strategies, science and technology (S&T) infrastructures, and foreign investments in science, research, and technology (U.S. Census Bureau, 2011). The global pattern on expenditure on R&D shows a 6.7 percent increase each year during the first decade of the 21st century; though 2011 statistics revealed that the main countries spending on research and science are limited to North America, Europe, and East Asia. In contrast, the countries in Central America, South America, Central Asia, the Middle East, Australia/Oceania, and Africa have accounted for only 10 percent of global expenditures on R&D in 2011 (International Comparisons of R&D Performance, 2014).
Regarding international movements for scientific development, the developing country of Iran has included science and technology development policies in its socioeconomic plans such as the continuing
In contrast to the quantitative growth of scientific output, there is little evidence about the global scientific impact of Iran. On the other hand, the effects of research activities have not been evident and visible in the social and economic development of the country. From the geographical viewpoint, the unbalanced regional development is an obvious issue in this developing country.
Focusing on the contribution of different provinces of Iran toward the production and use of scholarly publications, the goal of this research is to study the geographical distribution of the scientific wealth in Iran. The main problem addressed in this research is how to calculate and measure the distribution of the scientific wealth among Iranian provinces. The following questions are studied in this research:
1. What is the contribution of Iranian provinces in production of national scientific wealth? 2. What is the contribution of Iranian provinces in the use of national scientific wealth? 3. How can the distribution of scientific wealth be measured at a sub-country level? 4. How are the Iranian provinces ranked according to their share in the country’s national scientific wealth?
Science production and use has been a topic of research for years. Inhaber and Alvo (1978) offered an approach to measuring science with paying attention to the inputs and outputs of a scientific activity. The term scientific wealth has appeared in the research entitled “The
It is necessary to mention that the presented model can be challenged in two ways: comprehensiveness and reliability. Comprehensiveness means that the model of the scientific wealth should be able to reveal all the intervening aspects of the production and exploitation of the science. Reliability of the presented model also can be found out via common ways such as the feedback of the experts’ view.
According to the amount of the contribution of the provinces in the production and the exploitation of scientific wealth, provinces have been classified into three groups: rich, average, and poor. It can be assumed that provinces with more than n publications are ranked as rich provinces from the viewpoint of the production of scientific wealth. Such thresholds have sometimes been used in other situations. For instance, Iranian families have been divided into two groups, of higher and lower than the poverty line, by the determination of the specific amount of income. We have modified this categorization as it is explained in the Methodology section. Using such categorizations in order to emphasize the inequity of the provinces in the case of science and technology can help to reach a sustainable national development. From a global view, adopting new technology and investments in infrastructures reduces the gap between North and South countries (UNESCO, 2010).
Scientometrics researchers have considered geography as a key item for analysis of scientific collaborations. The first steps were taken to illustrate world regions’ contributions in the global citation indices. Frame, Narin, and Carpenter (1977) reported on the global coverage of ISI’s SCI. The rate and inadequate coverage of developing countries’ scientific productions in global citation indices was also considered by Garfield (1983), Moravcsik (1985), Frame (1985), and Shrum (1997).
Other research efforts show that the international contribution of the different regions and universities of a country follows different patterns. For instance, a study on the international contribution of different organizations and regions of Spain revealed that the older universities have more international contribution. In this country, the Catalonia region also has more international records according to its special autonomy (Olmeda-Gómez et al, 2008). Okubo and Zitt (2004) studied the scientific relationship of France with its neighboring countries and showed that France, Germany, and England had the best level of scientific contribution. From the researchers’ point of view, language has been the key factor in the mentioned international contributions in the way that, for example, there has been more contribution between Finland and Sweden.
Navaro and Martin (2008) studied the patterns of domestic and international collaboration in some countries. The results show that the more a country produces scientific publications the more it has inner scientific cooperation among its regions and organizations; however, the amount of international contribution is not necessarily high. Instead, the most international collaboration is among countries where their scientific production is not as high. The European countries have paid more attention to scientific relationships with other European countries than for other countries, which probably is the result of geographic proximity.
Glanzel, Schubert, and Czerwon (1999) studied the scientific production of the Europe Union or other world regions. King (2004) studied the publications of 31 countries from the different regions of the world from 1993 to 2000. Osareh and Wilson (2000) focused on the international scientific collaboration of Iranian authors and found out that the most repeated joint papers happened with colleagues from the U.S. and U.K.
Anselin, Varga, and Acs (1997) studied the spatial spillover between university research and high-tech innovations and found spatial externalities between university research and high-tech innovations. Ponds, Oorta, and Frenkena (2007) showed that geographic proximity is important for scientific collaboration of academic-industrial sectors. This proximity is not effective for pure academic relations.
Another geographic feature of scientometrics studies can be found in the visualization of co-authorships around the world. Leydesdorff and Persson (2010), Leydesdorff and Rafols (2011), and Bornmann and Leydesdorff (2011) have studied the distribution of science production and scientific effectiveness in the world, with emphasis on Europe and the developed countries. A combination of GIS maps and social network analysis tools can result in interesting representations of knowledge around the world.
Science and technology (S&T) ties with economic development has led to different national and international measurements and indicators.
The relationship between scientific outcomes and regional development has been studied by Asadi and Moradi (2014). The correlation between industrial indicators and the scientific productivity of 31 Iranian provinces was examined and the results showed strong correlation.
In summary, the previous work has compared the scientific productivity of different countries or citations among those countries. How the science is nationally distributed has not been carefully studied and this paper focuses on this topic.
A survey was conducted on available research, science, and technology data on Iran as features of national scientific wealth in order to examine the practicability of the proposed model. Bibliometric techniques such as counting the number of publications co-authorship and citation analysis were used in order to make the components of the suggested model.
The dataset for this research was built using all of the publications indexed in seven databases of IRANDOC,
The number of hits for geographic names was considered as a weight for ranking the Iranian provinces for each single query. Based on the obtained weights, each province was classified in one of these groups: rich, average, and poor. Iran had 31 provinces in 2011 and for each query, these provinces were first looked up in the mentioned fields and then ranked according to the frequency of appearance. Twenty percent of the top and bottom provinces were tagged as
The retrieved records from IRANDOC databases have been analyzed in order to get comparative results. Table 1 shows the distribution of scientific products retrieved from the mentioned databases. Tehran province with 77,674 records has the most number of the indexed records. Considering all of the databases, this province still allocates the first position. This is due to the scientific, political, and cultural centrality of Tehran Metropolis, which holds various research centers and large universities. With 18,570 records, Isfahan province is ranked the second productive province. Having about 100 cities and towns and locating various centers of higher education, Isfahan province has enough facilities for production of more scientific resources. Mazandaran, Fars, Guilan, and Sistan and Baluchistan provinces have been placed in the next rankings. In contrast, Qom, Northern Khorasan, and Alborz provinces had the least scientific products. Due to its new establishment, Alborz province has the least reserved records in the form of Alborz province.
Distribution of Retrieved Records for Provinces With Separation of the Database
Figure 2 compares the number of retrieved records for 31 provinces regarding the sum of retrieved records from six databases. The share of Tehran province in the retrieved records has obviously been much more than the other provinces – at least 4 times more than Isfahan, the second high ranked province. The overall average of the retrieved resources from the six studied databases is 5,905 titles for each province.
Table 2 shows the results of the scientific products retrieved from each field. The
Frequency Distribution of Retrieved records for Each Province in Different Fields
Table 3 shows the distribution and percent share of each province from three different aspects related to the scientific wealth of the country. The first and second columns reveal the share of each province as the
Frequency of Appearance of Provinces as producer or beneficiary in the Dataset
Table 4 shows the final rank of 31 provinces based on their share in the national scientific wealth. For instance, Guilan province with 2.8% of the science production has the fifth rank in the science production of the country and is a
Ranking the Provinces Based on Indicators of Scientific Wealth
Figure 3 shows the status of the rich, average, and poor groups of the provinces respectively from the aspects of
Focusing on the concept of scientific wealth, a novel method was introduced and examined in this research to assess the distribution of scientific wealth at a sub-country level. By having a list of the inputs and outputs of the science cycle, it is possible to assess the amount of the contribution of the regions of a country in production or use of the national scientific wealth. In this research, the amount of the production or use of scientific products was paid attention to as indicators of scientific wealth. More studies are needed to determine the scientific wealth more carefully in each region and all over the country in regard to infrastructure, legislation, budgets, and human resources.
According to the Pareto principle (also known as “the 80-20 rule”) most of the wealth is concentrated in a small proportion of the population (Sanders, 1987). This study revealed that the Pareto principle can be roughly applicable to the share of Iranian provinces in national scientific wealth. It means that a small 20% of Iranian provinces held a 70% share in the national scientific wealth. This can indicate the unbalanced distribution of scientific wealth in Iran, in coordinate with previous research such as Garfield (1983), Moravcsik (1985), Frame (1985), and Shrum (1997) which indicated the scientific production gap between developed and developing countries. Sustainable scientific devel opment requires planning for more normal distribution of science in a country. This can be examined for any other country in the world to find out how equally this wealth is distributed.
A careful assessment of the distribution of scientific wealth in the country, the amount of equality, and logical justice in accessing it can be a subject for further research. Besides the quantitative aspect of the scientific productions of a country, the study of the effectiveness of the costs and infrastructure will lead to more useful results.