Interpretive Structural Analysis of Interrelationships of the Sustainable Development Goals (SDGs) in Iran

The world has experienced major advances since the advent of 21^st century. Extreme poverty has been diminished to half, child mortality is declining and literacy in youth has achieved an unprecedented record. However, despite these achievements, serious challenges persists. More efforts have to be put to alleviate poverty, including all of its forms, and to deliver the Millennium Development Goals (MDGs) unfinished targets. We must go beyond economic indicators of development to encompass all spheres of sustainable development and more generally well-being [1].

In this regard, the long-term goals of global achievement in the 21st century were presented in a document called “Transforming our world: the 2030 agenda for sustainable development” which provides a pragmatic approach to recon ciliate collective action towards shared goals [2]. The 2030 Agenda entails seventeen goals, called Sustainable Development Goals (SDGs), consist of 169 targets and 232 indicators [3]. This agenda was the key result of the Rio + 20 Sustainable Development Summit held in 2012 [4] and approved by the UN General Assembly in September 2015 by UN’s 193 member states. The SDGs are a global initiative to wipe out poverty establish an equal, just and secure world for the people of planet Earth. They have been formulated in a consultative process that gathered governments and citizens globally to work together and create an ambitious plan of actions [5]. They are now the main reference for development policies and programs at the national level. Each country reviews 17 goals to determine how they can be turned into practical but ambitious development programs, and how national resources can be mobilized based on needs, stage of development, capacities, resources, and strategies to produce a real change [6]. Besides, consensuses reached in Addis Ababa, Istanbul [7], as well as Paris on climate change in further strengthen this agenda [8].

The president of Iran in his speech at the UN Summit in 2015 emphasized Iran's active participation in the preparation of the 2030 Agenda and stated that Iran's cooperation will continue to fulfill its commitments. In this regard, in 2015, the 2030 agenda was approved by the Cabinet in the Government of Iran, and various ministries and government organizations were responsible for its implementation. The committee on sustainable development of Iran has the custodian of coordinating and monitoring how to achieve these goals. Since 2015, various government organizations such as the Planning and Budget Organization, Department of Environment, Vice Presidency for Women and Family Affairs, the Ministry of Energy have organized various workshops and meetings with the aim of promoting public awareness on the SDGs in Iran. Besides, the Iranian National UNESCO Commission has organized classes aimed at promoting gender equality and women's empowerment in Iran. Achieving 59th rank out of 166 countries in the global SDGs index in 2020 and 30-step growth compared to 2018 shows the Iranian government's attention to sustainable development. Iran also has the highest rank in this index in the Mena region and in indicators such as affordable & clean energy, quality of education, and good health & well-being has grown in recent years [9]. The total installed capacity of renewable power plants in 2019 compared to 2020, increased by 18% that reached 820 MW. This has led to a 53% increase in emissions avoidance in 2019 compared to 2020 [10]. As Iran faces challenges and weakness in various indicators such as zero hunger, gender equality, decent work and economic growth, reduced inequalities and peace, justice and strong institutions [9], paying attentions to SDGs would play a key role in tackling with them. In 2019, Iran was ranked 99th in the world in the global competitiveness index, which compared to 2018, has weakened its position by 10 levels and was ranked 140th in the world in the labor market index. [11]. We are facing a situation in Iran and the Mena region where the continuation of the old patterns is no longer sustainable and we need to change the prevailing pattern and move towards sustainable development [7].

The 2030 Agenda is a common foundation for addressing the mentioned problems and challenges that threaten the well-being and livelihood of humanity now and in the future. The countries of the Mena region and Iran can use SDGs as the guiding basis for their action and policy efforts. However, as of now, the pace of their implementation fluctuates from country to country depending on their domestic preconditions, challenges & capacities. Although the SDGs provide a promising roadmap for the development of the Mena region and a country like Iran, recent progress of Iran in ending Extreme poverty, promoting clean energy, and facilitating access to energy services in remote villages [9] as well as the growth of health care activities [12], Food Safety and Security, Rural Development, quality education, life below water [9], and knowledge-based Economics [13] show the understanding of the need for sustainable development by Iranian policymakers. However as stated, Iran faces significant challenges and weakness in various indicators such as zero hunger, gender equality, decent work and economic growth, reduced inequalities and peace, justice and strong institutions [9] which highlight the need for a plan to achieve SDGs in this country, Still, as mentioned, the pace of their implementation depends on the specific challenges, preconditions, and capacities of each country [14]. Therefore, the prioritization of SDGs is of great importance in terms of the resources, capabilities, and context of each country to plan to achieve the set goals.

The aim of current paper is to create a hierarchical framework of SDGs using the interpretive structural modeling (ISM) modeling method to provide a tool to help policymakers implement SDGs in Iran. The ISM method has been used by many researchers to create hierarchical models and priority structures in various fields. Recently, the ISM approach has been used by Kumar et al. [4] and Zaini and Akhtar [15] to model SDGs. The application of ISM in each country provides a hierarchy of factors based on local requirements to policymakers and researchers that can be used in current and future planning to achieve sustainable development based on each country’s specific priorities and issues. In the rest of the article, in the literature review section, first, the origins of SDGs are discussed and then an overview of researches is presented. In the next section, the research method and steps of interpretive structural modeling (ISM) are discussed. In the fourth section, the findings of the SDGs hierarchical model in Iran and MICMAC analysis are presented. In the next section, we will discuss and compare the findings of the present study with other studies. In the final section, we discuss implications for decision-makers and policymakers.

Interpretive Structural Modeling was proposed by Warfield (1973) to examine complex socio-economic systems [28]. It is different from conventional approaches in using quantitative variables [29]. ISM is an interactive process of learning with a set of different elements that are structured to shape a holistic meticulous model and explains complex schema of conceptual relationships of a set of variables [30, 31]. This method has a mathematical basis, a philosophical basis, and an analytical and conceptual structure, and provides a tool to transform the mental hierarchy into well-defined patterns for planning. Unlike conventional questionnaires in which respondents just score the importance of issues, ISM requires respondents to assess different linkages among issues [30]. In this method, there is no specific criterion for determining the number of experts [28]. However, according to sources [28, 32], 15 experts have been selected, as shown in Table 3.

Table 3. Profiles of selected experts

To collect data from primary and secondary data, which have been used appropriately, first, the researchers reviewed the secondary sources (policy reports, articles, and websites) and provided basic information, then 15 experts were selected to complete the questionnaire. Experts are affiliated to the public, private and academic/ educational bodies to reflect different actors’ opinions in the results to ensure unbiased and inclusive results. Selected academic experts have research activities in the field of sustainable development and were sufficiently familiar with the concepts of SDGs in theory and practice. Government experts are those in charge of implementing the SDG Agenda in Iran. Experts selected from private companies also have knowledge and experience on sustainable development agenda. Relevant description, including questionnaires, were sent to experts, and group meetings were convened with 15 experts in the winter of 2019 (November 11, 2019). They were provided explanations about ISM and SDGs methods to complete the questionnaire. Subsequently they filled questionnaires in person. The research territory is Iran and its temporal interval is from 2018 to 2020. Thus, the experts, considering the conditions of Iran in these years, proceeded to complete the questionnaire.

The steps of the interpretive structural modeling method [33, 34] that have been performed in the present study are as follows:

3.1 Structural Self-Interaction Matrix (SSIM)

A self-interacting structural matrix is a variable-sized matrix in which the first row and column of those variables are listed in order and are formed on the basis of the expert group views. The relationship between issues is analyzed in two ways, both pairs, and experts use the following symbols. The symbol (V) is used when the index (i) is lead to (j). The symbol (A) is used when index (j) leads to (i). The symbol (X) is used if there is a two-way connection between the row (i) and the column (j) and that both indices underlie each other. Finally, the symbol (O) is used to show the absence of a relationship between the two elements.

3.2 Initial Reachability Matrix

Initial Reachability Matrix is created by converting the SSIM into a two-value matrix (zero and one). The rules for formulating this matrix are as follows:

In the SSIM if the cell (i, j) is assigned symbol (V), (A), (X) and (O), in the initial reachability matrix, this cell (i, j) entry becomes respectively 1, 0, 1 and 0 and the cell (j, i) entry becomes 0, 1, 1 and 0 respectively.

3.3 Final Reachability Matrix

After the initial reachability matrix is created, an internal consistency has to be determined in it. For instance, if variable (i) leads to variable (j), and variable (j) leads to variable (k), then, variable (i) must also lead to variable (k), and if this relationship does not hold in the reachability matrix, then the matrix should be modified and the missing relationships must be substituted. Various methods have been proposed to achieve consistency in the matrix. In the present study, the Boolean rule was used to convert the initial reachability to the final reachability matrix, which was performed by MATLAB b2016a software.

3.4 level partitions

To discover the relationship and leveling of the elements, the Reachability Set and the Antecedent Set must be calculated for each variable. The Reachability set entails variables and variables that are affected by it. The Antecedent Set comprises of each variable and variables that affected it. This step is undertaken using the reachability matrix. When the Reachability and Antecedent sets are calculated for each variable, the Intersection set in these sets is identified for each variable. As the antecedent and reachability and intersection sets are calculated, the levels of the variables become known. In Table 1, the variable with completely similar reachability and intersection sets has the highest level. After identifying the former variable(s), they are removed from the table, and a table is created by the remaining variables. This process stops when the level of all the variables are assigned.

3.5 Mapping the diagraph or model

After the relationships and the variable levels are determined, their diagraph can be mapped. First, the variables are arranged from top to bottom based-on their levels, and a consistent reachability matrix arranged by level and the structural hierarchy is mapped. If the relationships between the variables from (i) to (j) exist, they are shown with arrows.

3.6 MICMAC analysis

The MICMAC analysis determines and analyzes variables driving power (D.P) and dependence (D). In MICMAC, variables are categorized into four batches based on their D.P and D:

1) Autonomous variables: that have a poor D.P and D. These variables have poor relations with the system and have nearly no link to the system. 2) Dependent variables: that have a poor D.P, but a high D. 3) Linkage variables that have high D.P and D. These variables are dynamic, since every change in them can affect the system, and the system’s feedback can, in turn, change the variables once again. 4) Independent variables (driving variables): that have a high D.P but a low D. We will describe the status of each SDGs in the MICMAC analysis in four clusters of autonomous, dependent, Linkage, and Independent variables in the Findings and Conclusions section.

In this study, SDGs are presented in the form of an interpretive structural model because all of these goals are interrelated. Therefore, before planning to achieve SDGs, policymakers need to be aware of the level of interaction among goals and how they affect each other. The present study aims to provide insight into the interaction and how SDGs affect each other in the context of Iran and the way to achieve them. Understanding the interactions between goals and knowing the prerequisites is very important before trying to achieve a specific goal. Some goals cannot be achieved before knowing the goal of the prerequisites. For example, if we want to achieve SDG 1 which means no poverty, we cannot achieve this goal without achieving SDG 8, or decent work and economic growth, and SDG 9 or industry, innovation, and infrastructure, which is also mentioned in the research of Kumar et al. [4] and Zaini and Akhtar [15]. Similarly, we will not be able to achieve SDG 11, i.e. sustainable cities and communities, if we have not achieved SDG 6, meaning clean water and sanitation, and SDG 13, which means climate action. According to our research, SDG 4 meaning quality education and SDG 12 meaning responsible consumption and production are the most essential goals. In the studies of Kumar et al. [4] and Zaini and Akhtar [15], SDG 4, i.e. quality education, has been identified as the most essential goal, still, SDG 12, i.e. responsible consumption and production in their research, has not been identified as an essential goal, although Türkeli [5] also mentions it as one of the important goals.

MICMAC analysis also showed that SDGs 4, 6, 9, 12, 13, and 14 are independent variables with high D.P and low D, which also in the study of Kumar et al. [4] SDGs 13 and 14 are mentioned as independent variables. Also in Zaini and Akhtar’s [15] study, SDG 12 is in this cluster, and in all three studies, SDG 4 has been identified as an independent variable. SDGs 6 and 9 are independent variables in our study, which do not rank high in the studies of Kumar et al. [4] and Zaini and Akhtar [15]. This means that, along with quality education and responsible consumption and production and, policymakers must pay attention to clean water and sanitation, industry, innovation and infrastructure, climate action and sustainable life below water in their planning. Also, in the present study, like the research of Kumar et al. [4], none of the goals were identified as the linkage variable, which is contrary to the research of Zaini and Akhtar [15]. In the present study, SDGs 2, 3, 5, 7, 15, 16, and 17 arbitration in the cluster of autonomous variables, which have poor D.P and D, which in the studies by Kumar et al, SDGs 5, 9, 10, 12 and in the studies by Zaini and Akhtar [15], SDGs 7 and 13 are in this cluster. These variables are somewhat different from other variables and have poor relations with the system. Finally, SDGs 1, 8, 10, and eleven have been identified as dependent variables in this study. These variables have poor D.P but high D and effectiveness. The study by Kumar et al. [4] also named SDGs 2, 3, 8, 11, 16, and 17 as dependent variables. Also in Zaini and Akhtar’s [15] study, SDG 2, 3, 6, and 15 are in this cluster, and in all three studies, SDG 1 has been identified as a dependent variable.

Table 8. The main custodians of SDGs in Iran (National level)

Given the importance of planning and policy-making at the national level for achieving Sustainable Development Goals (SDGs) in the present study, in addition to presenting all SDGs in a form of an interpretive structural model so that policymakers are aware of the level of interaction among goals and how they affect each other, the supervisors overseeing each of the objectives have been identified, as outlined in Table 8. Trustees can play an important role in building understanding, cooperation, and coordination with other stakeholders to achieve these goals.