Analyzing the determinants of sustainability of China Pakistan Economic Corridor (CPEC) projects: an interpretive structural modelling (ISM) approach.

China Pakistan Economic Corridor (CPEC) is a game changer initiative of South Asian Pacific Rim. It has great importance for almost all Asian countries. Its success is expected to dictate the economic development of the stakeholders. The aim of this study is to evaluate the essential determinants deriving the sustainability of CPEC projects. The design of the study comprises of the review of literature, data collection, and analysis. Population under study is the folk of stakeholders of CPEC. Sampling envisages on purposive sampling design, i.e., 14 experts from within the stakeholders. Primary data is collected in the field setting through a survey questionnaire appropriate for the study. ISM is used for modelling and MICMAC for analysis and classification using inductive approach. The findings of the literature survey show that there are 23 prime determinants of sustainability of CPEC projects. The results of ISM show that 13 determinants are at Level-I, nine at Level-II, and one determinant namely "economic globalization" is at Level-III being the most critical and driving determinant. The findings of MICMAC show that only one determinant is classified in independent quadrant, and all the remaining determinants are in linkage quadrant, whereas, no determinant is shown in autonomous and/or dependence quadrant. But most of the determinants have potential to be classified in dependent and independent quadrants. It is intimately evident that the results of MICMAC corroborate the results of ISM. It is useful for folk of the stakeholders by way of developing an understanding about the multitude of determinants, intra-determinant relations, prioritizing the determinants for policy decisions, and/or for building future studies. This study has some limitations, e.g., the study uses qualitative approach and answers what and how questions that do not quantify the relations or tell the cause of indicated relations.

Introduction

Recent economic crises all around the world have hit both developed and developing economies while hurting the developing economies the most. In order to boost productivity in south Asian region, many mega projects have been started (Hassan et al. 2022). Mega projects in the form of economic corridors are becoming increasingly popular these days around the world. Economic corridors are trade routes between two or more countries to facilitate trade, transportation, and regional economic integration between these countries (Usman and Radulescu 2022; Brunner 2013).Some countries, either have economic corridors or trade routes between them, are working on them or considering to initiate one in order to benefit from the investments and infrastructural facilities that are associated with these routes. CPEC is an economic corridor which is expected to be build and fulfill Pakistan’s needs for its infrastructure. CPEC is a combination of various infrastructural, energy, and information technology mega projects which is important for both Pakistan and China as it is not only providing Pakistan with heavy foreign direct investment, required infrastructure, and human capital investment (Mehdi 2020) but also giving China an opportunity to have access to Middle Eastern, African, and European countries (Roy 2019; Safdar and Zabin 2020). Economic activities rely heavily on good infrastructure, and to cater for these needs, governments do invest heavily in mega infrastructure projects just as the case of CPEC. However, these projects do come with a cost, i.e., environmental, social, and financial costs (Thounaojam and Laishram 2022). Mega projects are often linked with increased CO2 emission.

Numerous authors (Balsalobre-Lorente et al. 2022a, b; Usman et al. 2022a; Rehman et al. 2021) affirmed that economic complexity and growth produces CO2 and vice versa. Işik et al. (2017) claimed that economic growth progression, financial development, enhanced international trade along with increased tourism lead to increased CO2 emissions. Similarly, increased industrialization infrastructure, transportation, and globalization negatively affects environment and increases CO2 emission (Suki et al. 2020; Sharif et al. 2020a, b). On the other hand, Hassan et al. (2022) stated that CPEC could appear as environmental corridor having capability to initiate renewable energy trade between Pakistan and China. The sustainability of CPEC projects is, therefore, could be considered as a factor that could lead towards sustainable environment. Pakistan and China both are going to link underdeveloped provinces and/or cities with developed ones through this route which will have a cascading/spillover effect in terms of knowledge, technology, employment opportunities, and economic development (Usman et al. 2022b; Makhdoom et al. 2018).

The CPEC and its constituent mega projects are expected to create several million jobs with a potential to upgrade living standards of almost 1.1 million people because of its contribution to cross country communication, infrastructure and economic activities (Dawn, 2020; Akhtar, et al. 2021). As asserted by Akhtar et al. (2021), CPEC is vital to change the destiny of Pakistan and its citizens as Pakistan does not has sustainable projects/investments to get rid of poverty without CPEC. An avalanche of studies is surging on phenomenon of CPEC that relates to both international and national perspective of strategic partners, e.g.,:Khalil, et al. (2021); Mukhtar, et al. (2021); Hussain et al. (2021b); Shaikh and Chen (2021); Akhtar et al. (2021); Fu et al. 2021; Hamid and Khan (2020). It is not out of context to evaluate the stock of research literature specific to Pakistan perspective that has potential to set out the very outset of this study viz: Aijaz et al. (2021) claimed that CPEC is vital to achieve blue growth economy in Pakistan and emphasized to conduct further research on determinants that can drive/hinder blue growth in perspective of CPEC. Xiaolong et al. (2021) asserted that it has become inevitable to study the underlying structure of determinants of CPEC projects. It is also important to study determinants of sustainability of CPEC because having sustainable CPEC projects are vital for regional economic development, and integration among both countries as well as for other south Asian countries indirectly linked with this route (Hussain et al. 2021a, b). To be more specific, it is a call of the day to identify, investigate, analyze, classify, explicate, and develop a structure of an array of the determinants of sustainability of the projects of CPEC. Therefore, this study has the objectives like: (1) to identify determinants pivotal for sustainability of CPEC projects, (2) to rank the identified determinants on the basis of vitality and priority, (3) to explicate the relations among the determinants, (4) to develop some structural model of underlying relations among determinants, and (5) to discuss results of this study as against reality.

To be more specific, this research answers the following questions:

What are the determinants of sustainability of CPEC projects?

What is the underlying structure of the determinants, i.e., which determinant gets high priority as compared to the rivals?

What are the contextual relationships among determinants of CPEC sustainability?

What is the key determinant?

A range of methodologies could be considered to achieve the objectives of the study and to address the research questions. These methodologies have been iterated below in the Methodology section. After due consideration, we opted for review of literature along with opinion of panel of experts for identification cum verification of determinants, ISM for structural modelling, and MICMAC for classification, analysis, and corroboration of results, because ISM and MICMAC have advantages over statistical/other mathematical methodologies (Avinash et al. 2018; Li et al. 2019a; Fu et al. 2022; Abbass et al. 2022a, b; Shaukat et al. 2021a, b; Abbass et al. 2022c; Warfield 1973). ISM is considered to be a useful technique for qualitative analysis. It is suitable for analyzing complex interdependent relations in a dynamic environment. It has the capacity of transforming complex mental models into visible, well-structured, and well-defined models with graphical depiction (Warfield 1973; Sushil 2012; Li et al. 2019b). As determinants of sustainability of CPEC is a relatively new phenomenon which is being researched widely these days, this method is not only justified but also the most suitable one. This study contributes (i) a list of determinants extracted from the jumbled literature and duly verified by the panel of experts, (ii) a structural model, (iii) a classification of determinants by way of driving dependence diagram, (iv) new information about level to level and at level relationships among determinants, and (v) policy guidelines for stakeholders. Remaining part of the research paper is arranged as follows: context and review of contemporary literature (“Context and review of contemporary literature” section), methods (“Methods” section), results (“Results” section), discussion (“Discussion” section), and conclusion (“Conclusion” section).

Context and review of contemporary literature

Being recognizant of the fact that review of contemporary literature not only provides background and basis of the knowledge on topic but also justifies ones’ research. Therefore, a thorough review of literature is conducted by exploring the databases viz: Hindawi, MDPI, Frontiers, Elsevier (Science Direct), Springer link, Emerald, Cogent, PLOS, IEEE, Karger, Wiley-Blackwell, and Taylor & Francis using Google as search engine with key words like CPEC, sustainability, China, Pakistan, economic corridor, Pak China collaboration, CPEC projects, one belt one road, etc., and found a plethora of published researches. Relevant studies are reviewed critically and reported the ones that are highly relevant and necessary for building the context of current study. A major project among six projects of belt and road initiative, CPEC, offers a trade route to China using Gawadar port to reach European Union, Middle East, and South Asia (Abbass et al. 2022d; Murshed et al. 2021). With investment in Pakistan, it is expected that Pakistan is going to be a trade hub requiring it to build and enhance its infrastructure in terms of industrial zones, cities, roads, and railways joining Pakistan and China (Kakar and Khan 2021). It also identified the impact of socio economic and environmental determinants on sustainable development of CPEC. It found insignificant association of environmental determinants with sustainable CPEC development and suggested that economic benefits can be used as a significant tool for sustainability. Ali and Butt (2021) argued that no country can achieve sustainable growth unless there is provision of equitable socioeconomic opportunities coupled with environment friendly conditions. Akhtar et al. (2021) evaluated the potential challenges of the CPEC including local communities’ fear and concerns with regard to awareness and acceptance of CPEC projects and its impact on local trade. The results of the research suggested that older people expect CPEC as a positive driver of social, economic, and environmental change. Xiaolong et al. (2021) dealt with success of CPEC project based on determinants including environmental, economic, and international relations. The study suggested that success of CPEC projects can be achieved by focusing on environment protection, accelerated economic growth and strong international relations. Ullah et al. (2021) highlighted that CPEC is an opportunity for Pakistan and other stakeholders to have sustainable economic development and to improve its E-Government Development Index. The authors claimed to have good governance along with transparency in order to have successful economic zones which can lead towards combating challenges to CPEC’s success. Aijaz et al. (2021) asserted that in order to have blue growth in Pakistan, it is imperative to have a balanced approach between internal and external stakeholders and top management’s support. They bolstered the importance of CPEC for economic sustainability of Pakistan.

We have reviewed a wide variety of recent researches on different factors that can lead towards sustainable projects. Many studies were directly and indirectly related to our topic of research and hence reported briefly for the purpose of brevity here: Balsalobre-Lorente et al. (2022a) concluded that reduced impact of foreign direct investment on energy use and lower carbon emission hence leading towards sustainable economic growth. To reduce carbon emission, Jahanger et al. (2022) suggested electric heating industry to use an alternate path. In similar way, authors suggested the use of stringent environmental tax laws (Doğan et al. 2022; Shahzad et al. 2021) to persuade businesses to use cleaner methods of production. Farrukh et al. (2022) claimed that an environment vigilant behavior can be promoted in organizations if green leadership and green human resource practices are there. The environmental pollution caused by industrialization can be reduced with increased use of renewable energy sources (Usman and Balsalobre-Lorente 2022). Sinha et al. (2022) developed a framework for inequality decomposition of energy use around the world. Many researchers are working on finding the appropriate level of GDP that can minimize CO2 emission (Ahmad et al. 2022; Ongan et al. 2022). Similarly, Sinha et al. 2021 suggested that green financing mechanism may affect environmental responsibility. Renewable energy consumption can be stimulated by religious and ethnic diversity which can help in devising environmental protection policies required for developmental projects (Amin et al. 2022). Whereas, the globalization is expected to have both positive and negative impact on environment (Sharif et al. 2019).

Işık et al. (2021a, b) suggested to implement environmental protection policies that can help in protecting environment. Furthermore, Aziz et al. (2020a, b): Aziz et al. (2020a); Aziz et al. (2021); Sharif et al. (2021) confirmed that increased use of renewable energy sources is considered important to minimize environmental degradation. It is therefore recommended that governments should focus on environmental factors while not compromising on their projects related to economic growth (Zhang et al. 2022; Usman et al. 2022c). These issues may impact on sustainability of mega infrastructure projects which in turn affect sustainability of the economic growth. Many researchers (Isik et al. 2021; Işık et al. 2021a) tested environmental Kuznets curve (EKC) hypothesis for checking the environmental quality with economic growth and development. It has been argued that both economic and environment can be positively affected by green practices adopted at national level (Khan et al. 2020).

In nutshell, from the review of literature, a total of 95 determinants were initially identified. After the critical review by the authors based on relevance, importance, and redundancy criteria, they were reduced to 20. The list of 20 determinants was presented to panel of experts with an option to add, delete, merge, and/or bifurcate the determinants. As a result of this process, we reached to 23 determinants (Table 1).

Table 1

Experts’ vote sheet on determinants

Sr. no	Determinants	Experts														Vote
		1	2	3	4	5	6	7	8	9	10	11	12	13	14
1	Internal stakeholders pressure	√	X	√	√	√	√	√	√	√	√	√	√	√	√	13
2	External stakeholders pressure	√	√	√	√	√	√	√	√	√	√	√	√	√	√	14
3	Negative publicity	X	√	√	X	X	√	√	√	√	√	√	√	√	√	11
4	Regulatory framework	√	√	X	√	√	√	√	√	√	√	√	√	√	√	13
5	Economic globalization	√	√	√	√	√	√	√	√	√	√	√	√	√	√	14
6	External funding	√	√	X	√	√	√	√	√	√	√	√	√	√	X	13
7	Support from industrial associations	√	X	√	√	√	√	√	√	√	√	√	X	√	√	12
8	Support from government	√	√	√	√	√	√	√	√	√	√	√	√	√	√	14
9	New market opportunities	X	√	√	√	√	√	√	√	√	√	√	√	√	√	13
10	Employment opportunities	X	√	√	X	√	√	√	√	√	√	√	√	√	√	12
11	Infrastructure (transportation, IT, etc.)	√	√	√	X	√	√	√	√	√	√	√	√	√	√	13
12	Excessive exploitation of water resource	√	√	X	√	√	√	√	√	X	√	√	X	√	√	11
13	Pollution (air, soil, and noise)	√	√	√	√	√	√	√	√	X	√	√	X	√	√	12
14	Deforestation	√	√	X	√	√	√	√	√	√	√	√	√	√	√	13
15	Bribery and corruption	√	√	X	√	√	√	√	√	X	√	√	√	√	√	12
16	International conflict	√	√	√	√	√	√	√	√	X	√	√	X	√	√	12
17	Cultural change	X	√	√	√	√	√	√	√	X	√	√	√	√	√	12
18	Labor security	X	√	√	√	√	√	√	√	√	√	√	√	√	√	13
19	Energy efficiency	√	√	X	X	√	√	√	√	X	√	√	√	√	√	11
20	Geographical harmony	√	√	√	X	√	√	√	√	X	√	√	√	√	√	12
21	Interest of China	√	√	√	√	√	√	√	√	√	√	√	√	√	√	14
22	Credit risk	X	√	X	√	√	√	√	√	X	√	√	√	√	√	11
23	Vulnerability to infant domestic industry	√	√	√	√	√	√	√	√	√	√	√	√	√	√	14

In view of the aforementioned representation, the study is entailed on 23 determinants of sustainability of CPEC projects (Table 2).

Table 2

List of determinants of sustainability of CPEC projects

Code	Drivers	Description	Source
1	Internal stakeholders pressure	Stakeholders of CPEC from within the Pakistan	(Haupt et al. 2015)
2	External stakeholders pressure	An attempt by the external stakeholders (stakeholders from outside of Pakistan) to persuade the collation partners of CPEC for endurance of the projects relevant to CPEC	(Haupt et al. 2015)
3	Negative publicity	Noticing or giving attention to something bad associated with CPEC	(Haupt et al. 2015)
4	Regulatory framework	Compliance with regulation: sustainability is subject to legislation and government regulations, which firms must comply with	(Haupt et al. 2015)
5	Economic globalization	The widespread international movement of goods, capital, services, technology, and information between the countries	(Tang et al. 2020)
6	External funding	Presence of monetary support, e.g., loan from financial institutions. It includes third-party financing	(Neri et al. 2018)
7	Support from industrial associations	This support consist of sharing knowledge, resources, and common initiatives	(Neri et al. 2018)
8	Support from government	Support provided by government. This may consist in providing advice and information for the adoptions of sustainability in CPEC projects	(Neri et al. 2018)
9	New market opportunities	Prospect of new market opportunities	(Neri et al. 2018)
10	Employment opportunities	Set of circumstances that create the state of having paid work (state of employment) for the people of Pakistan	(Palmer 2009)
11	Infrastructure (transportation, IT, etc.)	The basic physical structure and facilities (e.g., buildings, roads, and power supplies) needed for operation of CPEC project	(Newman 2015)
12	Excessive exploitation of water resource	Use of water resources excessively and unfairly because of being available free/cheap	Recommended by experts
13	Pollution (air, soil, and noise)	Producing a substance harmful to environment (air, soil, and noise etc.)	(Zhang et al. 2017)
14	Deforestation	Removal of forests from land to convert it for non-forest use	(Pope et al. 2015)
15	Bribery and corruption	Giving or offering bribe in form of money or benefits for getting the jobs done or the abuse of public office for private gain	(Ganda, 2020; Epperly and Lee 2015)
16	International conflict	Chance of a serious disagreement between countries/nations	(Ward 2006)
17	Cultural change	The change relating to ideas, customs, and social behaviors of Pakistani society	(Gunn 2010)
18	Labor security	The state of workers being free from threat of removal from work/risk to their lives	(Zhang et al. 2017)
19	Energy efficiency	Achieving better ratio of useful work performed by machines/process to the total energy expended	(Shen and Lin, 2017)
20	Geographical harmony	The situation of people or things seeming suitable together within the region	(Di Fabio and Tsuda 2018)
21	Interest of China	Excitement of China towards curiosity to execute the projects of CPEC	Recommended by experts
22	Credit risk	The probability that some of the Banks’s assets (loans) will decline in value and perhaps to become worthless for repayment of loan	(Belás et al. 2017)
23	Vulnerability to infant domestic industry	The state of infant Pakistani industry being exposed to the possibility of being harmed	Recommended by experts

The study finally is built on 23 identified determinants (Table 2) and proceeds according to the methodology aforementioned. According to the norms of ISM, approximately 20 elements of the system are considered sufficient to evaluate the same (Sushil 2017).

Methods

The study follows interpretivism as philosophy and induction as approach of inference generalization. The design of the study consists of survey of relevant literature, data collection from primary source, and mathematical analysis. Population under study includes folk of stakeholders of CPEC. Study follows non probability-based purposive sampling design (i.e., panel of experts) (Ranjbar et al. 2012; Usman et al. 2021; Azevedo et al. 2013). Since the study is based on binary matrices (Warfield 1973; Sushil 2012) with no predetermined statistical population frame, therefore, non-probability sampling is used. The panel of experts (sample size) is 14 experts only. The methods used for proceeding to the study are entailed below:

Method of identification of determinants

A range of methodologies available for identification of determinants, for example; literature review (Avinash et al. 2018; Dhochak and Sharma 2016; Gothwal and Raj 2017; Li et al. 2019a, b; Thamsatitdej et al. 2017; Valmohammadi and Dashti 2016), expert opinion: (Cai and Xia 2018; Majumdar and Sinha 2019; Talib et al. 2011; Hussain et al. 2022; Ke et al. 2022; Begum et al. 2022; Thamsatitdej et al. 2017; Vinodh et al. 2016), case study: (Valmohammadi and Dashti 2016), Delphi method: (Zhang and Wei 2010), exploratory determinants analysis: (Usman et al. 2021; Li and Yang 2014), presumed by authors (Lohaus and Habermann 2019), and idea engineering workshop and brainstorming session (Kumar et al. 2013) are considered. The review of literature coupled with expert opinion is found to be the most appropriate method of determinants’ identification for the purpose of this study.

Method of modelling and analysis

An array of mathematical and statistical modelling methods viz; AHP, ANP, FANP, PROMETHEE, DEMATEL, VIKOR, SWARA, TOPSIS, DEA, ISM, TISM, MICMAC, ELECTRE (Qazi et al. 2021; Shaukat et al. 2021a, b) are considered, and ISM in combination with MICMAC is opted for modelling and analysis.

Method of data elicitation

There are many methods to elicit the data from the experts, for example, one-to-one, face-to-face interview, Delphi method, discussion session, repertory-grid interview technique, matrix type questionnaire, elect alternatives (V,A,O,X) for every pair of relations through software/questionnaire, and idea generation. We used the method of face to face, one on one interview and extracted the data on matrix type questionnaire (Trigunarsyah and ParamiDewi 2015; Ayad et al. 2022; Jahanger et al. 2021; Shaukat et al. 2021a, b) using traditional symbols of VAXO. During the elicitation of data, we developed the rapport with respondents. While collecting the data, certain rules for completing the questionnaire (Annexure I) were shared viz: (i) contextual relationship = leads to, (ii) fill only white cells, and (iii) fill in the white cells: V when the row influences the column, A when the column influences the row, O when there is no relation between the row and the column, and X when row and column influence each other.

Panel of expert

Expert’s responses are elicited because data of determinants of sustainability of mega projects like CPEC is not readily available from secondary sources, and taking the data from experts is important since it provides quality not the quantity (Shen et al. 2016). There are two types of panel of experts: heterogeneous and homogenous. For heterogeneous panel of experts, the common definition is 8–14 experts on panel whereas for homogenous, it consists of 12–25. The minimum size of the panel of experts is eight as suggested by Warfield (1973) or it may be as small as comprising of 5–7 members (Li et al. 2019a, b). A panel of experts of 10–20 in number is considered ample in many researches (Clayton 1997; Khan and Khan 2013; Shaukat et al. 2021a, b). This study uses heterogeneous panel of experts that consists of 14 experts. Expert group outperform over statistical group as they are having more knowledge, expertise, and experience of the phenomenon for which responses are being elicited. The experts for the study are selected on the basis of their knowledge, experience, and direct relation to the ongoing projects of CPEC making them reliable and authentic source of information. Experts are recruited on the predetermined set of criteria that includes (i) experts should be at least a university graduate, (ii) must have a relevant working experience of at least 10 years, (iii) have fair and sufficient theoretical and practical knowledge of CPEC, (iv) have some acumen of research, and (v) show willingness to participate in the study. The experts are selected from among investors, academia, Chinese citizens in Pakistan, civil servants, and employees working on CPEC projects. The composition of panel is: 3 from investors investing in CPEC projects, 3 from academia having experience of more than 10 years, 2 Chinese citizens residing in Pakistan since last 5 years, 2 civil servants currently working on CPEC projects, 2 researchers working on CPEC projects, and 2 from employees currently working on CPEC projects. Initially, 21 experts were approached through emails, phone calls, and personal invitation by going to their offices, of which 18 agreed to respond and we received 14 responses in its completed form. This process took a time period of approximately 3 months to approach the experts for time and stimulating the responses. Three discussion rounds were held with experts on panel. One for invitation, second for rapport development and briefing for concept, and third for data elicitation. The data is elicited individually from all experts on ij part of matrix type questionnaire which was subsequently aggregated by majority rule (Li et al. 2019a, b; Qazi et al. 2019; Ahmad et al. 2022; Abbass et al. 2022e; Basit et al. 2021). The experts were involved at three stages: first for verification of identified determinants, second for data collection, and third for model confirmation (Vasanthakumar et al. 2016). In the verification, the panel checked the model logically, theoretically, and/or conceptually as to whether there is any inconsistency.

Proceeding to ISM process

The study uses classical procedure of ISM modelling as devised by Warfield (1973). The study proceeds step wise according to flowchart for ISM devised by Abbass et al. 2021a, b) and Attri et al. (2013). As a first step, the data collected from experts is aggregated into Structural Self-Interaction Matrix (SSIM) Table 3.

Table 3

SSIM

The SSIM (Table 3) is converted into initial reachability matrix (Table 4) using the classical rules of translating VAXO symbols into binary codes (Warfield 1973; Niazi et al. 2020; Attri et al. 2013).

Table 4

Initial reachability matrix

All 0 s existing in the initial reachability matrix (Table 4) are checked for possible transitive relations using Hide/Unhide functions of MS Excel since the ISM procedure is always applied on an asymmetric transitive matrix. Therefore, some of the 0 s are replaced with 1* (that necessarily means presence of transitive relations) and prepared the final reachability matrix (Table 5).

Table 5

Final reachability matrix

Code	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	Driving
1	1	0	1*	1	0	1*	1	1*	1*	1	1	1*	1*	1*	1*	1*	1	1	1*	1	1*	1*	1	21
2	1	1	1*	1	1*	1	1	1*	1*	1	1	1	1*	1	1*	1	1	1	1	1	1	1	1	23
3	1	1	1	1	1*	1	1	1	1*	1	1	1*	1*	1*	1*	1	1	1	1*	1	1	1	1	23
4	1*	1*	1*	1	0	1	1	1	1	1*	1	1	1	1*	1	1*	1*	1	1*	1	1*	1	1	22
5	1	1	1	1	1	1	1	1	1	1	1	1*	1	1	1*	1	1	1	1	1	1*	1	1	23
6	1	1*	1*	1*	1*	1	1	1	1	1	1	1*	1*	1*	1	1	1	1*	1	1	1*	1*	1*	23
7	1*	1*	1*	1*	0	1*	1	1	1	1	1	1*	1	1	1*	1*	1*	1	1	1	1	1	1	22
8	1	1	1*	1*	0	1*	1*	1	1	1	1	1	1	1	1*	1*	1	1	1	1	1*	1	1*	22
9	1	1	1	1*	1*	1*	1*	1*	1	1	1	1	1*	1*	1	1	1	1	1	1	1*	1	1	23
10	1*	0	1*	1	0	1*	1*	1*	1*	1	1*	1	1*	1*	1*	0	1*	1*	1*	1	1*	1*	1	20
11	1*	1*	1*	1*	1*	1*	1*	1*	1*	1	1	1	1	1	1*	1	1	1	1	1	1*	1*	1	23
12	1	1*	1	1*	0	1*	1*	1*	1*	1*	1*	1	1	1	1*	1*	1*	1	1	1*	1*	1*	1*	22
13	1	1	1	1*	0	1	1*	1*	1	1*	1*	1*	1	1	1*	1*	1*	1*	1*	1*	1*	1*	1*	22
14	1	1*	1	1*	0	1*	1*	1*	1	1*	1*	1*	1	1	1*	1*	1*	1*	1	1*	1*	1*	1*	22
15	1	1	1	1*	1*	1*	1	1	1*	1	1*	1*	1*	1*	1	1	1*	1	1*	1	1	1	1	23
16	1	1	1*	1	1	1	1	1	1*	1	1*	1*	1*	1*	1	1	1	1*	1*	1	1	1	1	23
17	1*	1*	1*	1*	1*	1*	1*	1*	0	1	0	1*	1*	0	1*	1	1	1	1	1*	1*	1*	1	20
18	1*	1*	1*	1*	1*	1	1*	1*	1*	1	1*	1*	0	0	1	1	1*	1	1*	1*	1	1*	1*	21
19	1*	1*	1*	1	1*	1	1*	1*	1*	1	1*	1*	1	1*	1	1	1*	1	1	1*	1*	1*	1	23
20	1*	1*	1*	1*	0	1*	1*	1*	1*	1*	1*	1*	1	1*	0	1*	1	1*	1*	1	1	0	1	20
21	1	1	1*	1	1*	1	1	1*	1	1	1	1	1*	1*	1*	1	1	1	1*	1*	1	1*	1	23
22	1	1*	1	1*	0	1	1	1	1*	1	1	1*	1*	1*	1*	1*	1*	1	1*	1*	1	1	1	22
23	1	1*	1	1*	0	1	1	1	1*	1*	1*	1*	1*	1*	1*	1*	1*	1	1*	1*	1*	1*	1	22
Dependence	23	21	23	23	12	23	23	23	22	23	22	23	22	21	22	22	23	23	23	23	23	22	23	508

Asymmetric transitive matrix (Table 5) is partitioned into hierarchies using iteration method (Warfield, 1973) Table 1A–3A in Annexure II. Through the iterations method, the transitive matrix is decomposed into three hierarchical sub matrix depicting three levels of determinants present in binary matrix. On the basis of hierarchies, Table 5 is rearranged as Table 4A in Annexure II. The model appeared on the diagonals of rearranged matrix (Table 9) highlighted as gray from which we prepared a diagraph (being optional) (Sushil 2012), therefore not reported here for brevity. The summarized process of ISM is presented in condensed form Table 6.

Table 6

Condensed representation of ISM reachability sets

Dependence Power

By completing the stepwise application of ISM process, it has become possible to generate an ISM model with complete description of the determinants; hence, using the elementary concepts of directed graph theory, an ISM model is developed as Fig. 1.

Fig. 1

Hierarchical ISM model.

Source: Author’s constructed

Observing the ISM model derived from iteration depicts that 13 determinants coded as 1, 3, 4, 6, 7, 8, 10, 12, 17, 18, 19, 20, and 21 are at top Level-I whereas nine determinants coded as 2, 9, 11, 13, 14, 15, 16, 22, and 23 fall at Level-II. The determinant coded as 5 is at Level III. At level all the determinants, interalia, have two way relations highlighted by two-way arrows.

MICMAC analysis

Cross impact matrix multiplication applied to classification is a standalone structural methodology based on Boolean algebra. It is commonly used to corroborate the results of ISM. Therefore, MICMAC analysis (Fig. 2) is prepared as suggested by Godet (1986).

Fig. 2

Driving-dependence graph.

Source: Author’s constructed

The driving dependence diagram (Fig. 2) shows that one determinant coded as 5 is in independent quadrant and remaining 22 determinants coded as 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, and 23 are categorized in linkage quadrant, whereas, no determinant is classified in autonomous and dependent quadrant.

Results

CPEC is a lifeline important project for Pakistan, China, and other countries of this region. It is extremely important to investigate different facets of sustainability of CPEC constituent projects. It is a problem of high precedence to be studied. The study, therefore, identifies the determinants of sustainability of CPEC projects, imposes hierarchy on them through ISM, and analyzes/classifies them by way of MICMAC. As a result of literature review coupled with expert opinion, 23 determinants qualified to be studied (Table 2).The results of ISM show that determinants namely internal stakeholders pressure (1), negative publicity (3), regulatory framework (4), external funding (6), support from industrial associations (7), support from government (8), employment opportunities (10), excessive exploitation of water resource (12), cultural change (17), labor security (18), energy efficiency (19), geographical harmony (20), and interest of China (21) are at top Level I. At Level II, determinants that is external stakeholders pressure (2), new market opportunities (9), infrastructure (transportation, it etc.) (11), pollution (air, soil, and noise) (13), deforestation (14), bribery and corruption (15), international conflict (16), credit risk (22), and vulnerability to infant domestic industry (23) are found. The most important determinant of sustainability of mega projects of CPEC, “economic globalization “coded as 5 with highest driving power is at bottom Level III. The results of MICMAC show economic globalization (5) as the key determinant of sustainability which falls under independent quadrant. This determinant should be prioritized among all other determinants as it is having the strongest driving power which can influence other determinants for achieving sustainability of CPEC projects leading towards economic progression of Pakistan. In order to have sustainable CPEC projects, it is a need of time to give due focus to economic globalization policies so that benefits of CPEC-related projects can be reaped. All determinants except economic globalization (5) lye in the linkage quadrant, i.e., determinants namely internal stakeholders pressure (1), external stakeholders pressure (2), negative publicity (3), regulatory framework (4), external funding (6), support from industrial associations (7), support from government (8), new market opportunities (9), employment opportunities (10), infrastructure (transportation, IT, etc.) (11), excessive exploitation of water resource (12), pollution (air, soil, and noise) (13), deforestation (14), bribery and corruption (15), international conflict (16), cultural change (17), labor security (18), energy efficiency (19), geographical harmony (20), interest of China (21), credit risk (22), and vulnerability to infant domestic industry (23).There is no determinant classified in autonomous or dependence quadrant. MICMAC is a relational analysis of elements of a system, and the elements might be classified distributive over the four quadrants or in one or more quadrants (Kamal et al. 2021; Kumar et al. 2018; Abbass et al. 2022f; Majumdar and Sinha 2019). The results of both methods in contrast with findings of literature review are juxtaposed as Table 7.

Table 7

Results of the ISM and MICMAC juxtaposed

From the comparative results of the study presented in Table 7, it can be observed that determinant coded as 5 namely “economic globalization” surged as key determinant as a result of both the structural methodologies that deserve high priority to be dealt with in policy matters.

Discussion

Discussion of the study is built into five parts, viz, discussion: on results, contrasting the current studies with contemporary literature, implications, limitations of the study, and recommendations for future researchers/academicians.

From the survey of literature, we learnt that there is influx of empirical studies based on selective two to five variables pertaining to the phenomenon under study using the statistical primary/secondary type of data in deterministic models. We can hardly find a theory-building study that accounts for most of the relevant elements of the system. The current study is an attempt to account for all important variables concerning the phenomenon under study that is evident from generation of list of 95 determinants methodically culminated into 23 (Tables 1 and 2). This list of determinants is a bit comprehensive and equally useful for all the stakeholders of CPEC. There are numerous studies available on sustainably of mega projects, CPEC project, and economy that have used deterministic models to quantify the relations among selected variables. Whereas, the current study opted for a theory development of the phenomenon and accounted for a larger set of variables. ISM process while applied on the list of determinants extracted from literature disentombed the underlying structure of complex relations among these determinants. It simplified the relations into a hierarchical model that provides useful information by way of prioritization (bottom-up approach, at level relationships and level to level relationships). The results of ISM ranked all these determinants into three levels with economic globalization being a critical determinant having the highest driving power to contribute towards sustainability of CPEC projects. The ISM model (Fig. 1) depicts that all determinants have bidirectional relationship among themselves at each level. Whereas, the relationship among intra-level is unidirectional. The MICMAC is also a structural methodology based on binary multiplication (Abbass et al. 2022g). This has the capacity of analyzing and classifying the elements of a system into four clusters. Interestingly, all the determinants in this study are clustered in linkage quadrant except determinant codded as 5 but that does not mean that this is no more insightful rather it is more insightful since it generates an alert for stakeholders that elements of the system are not settled, agile, unbalanced, or ambivalent. Any action on these variables will not only affect them but at the same time it will affect other variables and in turn to themselves as well because they have high driving as well as high dependence. This is also indicative of the interactive complexity of elements of the system.

It is also important to contrast the current study with some of the relevant studies from contemporary literature and to discuss them qua realities (Table 8).

Table 8

Comparison of present study with prior ones

Sr	Study	Country	Focus	Variables	Results	Method
1	Current	Pakistan	Determinants of CPEC sustainability	23 determinants of CPEC sustainability	Economic globalization is found to be the strongest driver	ISM, MICMAC
2	Akhtar et al. (2021)	Pakistan	Determinants of CPEC	Public support and local communities’ concerns	Educated older age people have more understanding of CPEC projects	Descriptive, bivariate, and multivariate analyses
3	(Kakar and Khan 2021)	Pakistan	Economic and environmental determinants for sustainable mega projects	Economic, environmental, and social determinants	The repute of CPEC projects largely depends on economic benefits and satisfaction of community	SEM
4	(Aijaz et al. 2021)	Pakistan	Drivers and barriers for blue growth	Uncertainty avoidance, functional strategic focus, prioritization of the short-term growth (rather than long-term orientation), and weak innovativeness, balanced approach between stakeholders and shareholders, and top management commitment/support	A balance approach between internal and external stakeholders and top level management is the major driver for blue economic growth	PLS-SEM
5	(Li et al. 2020)	Pakistan	Economic corridor and economic stability	Economic stability, including honest leadership, improved infrastructure, revenue generation, environmental sustainability, and sustainable development	CPEC along with honest leadership, enhanced infrastructure, revenue growth have a positive relationship with economic stability	PLS-SEM
6	(Mahmood et al. 2020)	Pakistan	Sustainable development and infrastructure projects	Land acquisition and dissatisfaction with CPEC	Dissatisfaction with CPEC projects is more in areas without economic zone	Logit model

This is the first study of its nature that used qualitative research for developing a hierarchical model of determinants of sustainability of CPEC projects (ISM) and driving dependence diagram (MICMAC). Whereas, studies are available on economic corridors’ sustainability that have used quantitative techniques. For example, Akhtar et al. (2021) used descriptive, bivariate, and multivariate analysis and concluded that older age people have more awareness about CPEC projects and benefits associated with such projects. Kakar and Khan (2021) used structural equation modelling (sem) to conclude that repute of CPEC projects largely depends on economic benefits and satisfaction of community, and Aijaz et al. (2021) conducted research on divers and barriers for blue growth in Pakistan using SEM and claimed that uncertainty avoidance, functional strategic focus, prioritization of the short-term growth, and weak innovativeness are barriers towards blue growth, whereas, a balance approach between internal and external stakeholders and top level management is the major driver for blue economic growth. Li et al. (2020) used PLS on data collected from employees of CPEC and concluded that there is a positive association between economic stability, honest leadership, enhanced infrastructure, accelerated revenue, and CPEC. Mahmood et al. (2020) examined nexus between land acquisition and dissatisfaction of local community with CPEC projects. They used legit model to argue that dissatisfaction is more in areas where land is acquired by force or where economic zones are not being developed. It is also relevant to discuss the practical and theoretical implications of the study and highlight the usefulness of the results of this research for different stakeholders. All these studies though pertinent to determinants of CPEC are different in scope, methodology, data set and/or results from that of the current study. However, the results in general conform to the contemporary literature.

Practical implications: This study has a lot of practical and theoretical implications:

For community at large: As for as practical implications are concerned, this research will increase awareness and understanding of determinants contributing towards sustainable CPEC projects development for community at large.

For government: This study is useful for government officials and policy makers as it is an informative study that the information disseminated by it can be used for strategy building on the basis of relationships among determinants identified. This study is advantageous for the policymakers in devising policies for CPEC projects’ implementation in order to be successful and sustainable. It is significant not only in terms of CPEC but can be used as a stepping stone for other mega projects of such a nature.

For project managers: This study is also helpful for project managers working on CPEC and other mega projects to focus more on the determinants identified here so that they can take better decisions.

Theoretical implications: The study also has theoretical implications, since it is a theory-building research using elementary concepts of binary mathematics, set theory, and directed graph theory, and it does not confirm or debunk any existing theory nor it require priory theory. It contributes a theoretical framework for future research and contributes information on interactions among determinates. The researchers can use this study as a base to quantify the relationship among determinates using GRA, PLS, SEM, or other statistical methodological techniques.

Conclusion

Since Pakistan and China have entered into a contract of an economic corridor and emerged as one of the vital economic projects of the region, to build research studies around CPEC is literally one of the very important topics. Despite of its importance, there is dearth of theory building studies. This study is a theory building attempt that evaluates the underlying structure of determinants of sustainability of CPEC projects. For that purpose, discourse of literature review, ISM, and MICMAC is employed. Results of literature discourse revealed that there are total 23 vital determinates (Tables 1 and 2). Results of ISM show that determinants, 3, 4, 6, 7, 8, 10, 12, 17, 18, 19, 20, and 21 are at top Level-I whereas nine determinants coded as 2, 9, 11, 13, 14, 15, 16, 22, and 23 fall at Level-II. The determinant coded as 5 namely “economic globalization” is at Level III. Level-to-level relationship is unidirectional using bottom-up approach, whereas, at level all the determinants are two-way connected. The results of MICMAC show “economic globalization (5)” as the key determinant of sustainability which falls under independent quadrant. All determinants except 5 lye in linkage quadrant that is determinants coded as 1–4 and 4–23 are categorized in linkage quadrant, whereas, no determinant is classified in autonomous and dependent quadrant. Overall results of the study show that economic globalization is the critical and key determinant, all determinants included in this study are highly relevant elements of the system under study, and they are highly unbalanced, agile, ambivalent, and uneven. This conundrum result demands high attention of policy makers and the researchers. This study has a lot of theoretical and practical implications for discerner stakeholders. It, in fact, develops understanding and provides a lot of new insights to stakeholders, details of which is represented in the Discussion section. This study has contributed to the body of literature by presenting a list of determinants (Table 2) that can be used as a foundation towards having sustainable CPEC projects. Another contribution of this study is ISM model (Fig. 1) and MICMAC diagram (Fig. 2) based on mathematical analysis. These models provide information about driving dependence and direct/transitive relationship among determinants identified, and discussions here are presented qua reality. This study is a great contribution towards those who wish to make CPEC a successful venture for Pakistan’s economic boost up. On the basis of the results of the study, some policy guidelines are also formulated. Firstly, policymakers should consider more the determinant of economic globalization while devising any policy before and during working on CPEC projects. Secondly, due importance should be given to Level determinants like external stakeholder’s pressure, new market opportunities being created by CPEC, infrastructure enhancement, control of pollution (air, soil, and noise), deforestation, bribery and corruption, international conflict, credit risk, and vulnerability to infant domestic industry be given. In light of the results of the study, economic globalization is the key determinant to focus on for maintaining the sustainability of CPEC project. But current economic crises due to pandemic made it difficult for Pakistan and all countries involved in CPEC to maintain the steady growth required for timely and sustainable completion of these projects. As suggested by Sharif et al. (2020a, b) COVID-19 strongly affects geopolitical risk than economic uncertainty in the USA. The same is the case in Pakistan as authors (Ahmad et al. 2021) provided the list of factors that should be adopted to avoid the uncertainties of pandemic related to mega projects. This uncertainty in economic policies due to COVID-19 not only affects economic activities but also tourism as well (Işık et al. 2020). In this regard, future studies can be directed towards sustainability issues of CPEC projects amidst and post COVID-19 pandemic.

Limitations and future directions

The study has certain limitations as well. Firstly, it is a qualitative research conducted with limited resources; therefore, its results should be generalized accordingly, and in this context, it is recommended that future studies should be designed quantitatively to corroborate the results. Secondly, although it is a study of folks of stakeholders but with a small sample to be considered as representative of the population, therefore the implications of the results are accordingly limited, and it is recommended that future studies must envisage on rather a larger sample size that may be large focus group/or statistical sample. Thirdly, although a reasonable number of contemporary studies have been reviewed by the authors and a list of determinants has carefully been prepared but still the determinants are limited and authors no way claim to be exhaustive, and there may be some other determinants that might have been overlooked in this behalf. Therefore, it is recommended that a rather comprehensive literature review should be done. Fourthly, we have used interpretive structural modelling (one of the qualitative methodologies in combination with another corroborative structural methodology); there are certain other options as well. Therefore, it is recommended that future studies should use other qualitative/quantitative methodologies. Fifthly, although there is one expert on panel from China but still the panel majorly consists of experts from Pakistan and results may accordingly be limited. It is, therefore, recommended to replicate the study with Chinese experts.

It is also useful for the discerners since it contributes a model, classification, and new information about the phenomenon under study. It is also based on limited list of 23 determinants and 14 experts from Pakistan; therefore, generalizability of the results is accordingly limited. It is a seminal study which uses firsthand information from the representative of the folk of stakeholders of CPEC projects with a different type of methodology. It is built on the data collected from real-time field setting that gives firsthand authentic and useful information on a unique type of phenomenon.

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 27 KB)