Document Type : Original
Authors
1 Department of Sport Management, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran.
2 Department of Sport Management, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
3 Department of Sports Management, Faculty of Educational Sciences and Psychology. University of Mohaghegh Ardabili. Ardabil, Iran
Abstract
Keywords
Main Subjects
Introduction
Weightlifting is a foundational, highly competitive sport that plays a central role in promoting health, physical capacity, and the development of athletic skills (Benito et al., 2020). Beyond building muscle and increasing strength, it is a demanding form of physical activity that can enhance overall health and support the optimal function of multiple bodily systems (El-Kotob et al., 2020). Globally, weightlifting has a long tradition of major championships, records, and international competitions, and in many countries, it is considered a core component of strength and conditioning programs across different levels of sport (Huebner & Perperoglou, 2019). In addition to these physical benefits, weightlifting and resistance training more broadly are associated with improvements in mental health, including reductions in depressive symptoms and gains in self-efficacy and perseverance, as they require sustained concentration, psychological resilience, and consistent training over time (Gordon et al., 2018).
The growth and development of weightlifting across countries, particularly in developing nations, is confronted with numerous challenges (Reiche, 2017). These difficulties stem from limited financial resources and inadequate infrastructure, as well as broader social, cultural, and political constraints (Gao, 2024). Moreover, in some societies, prevailing social and cultural attitudes mean that weightlifting does not receive sufficient attention, and in certain cases it is actively avoided or discouraged (Vasudevan & Ford, 2022). By contrast, in many high-income countries weightlifting is regarded as a popular and established sport which, supported by strong financial backing and advanced facilities, has achieved substantial international success, while in many developing countries it still requires more precise strategies and targeted planning to support its systematic growth and expansion (García & Meier, 2022). These general challenges facing developing nations are particularly pronounced in the context of Iraq, a country where the intersection of political instability, economic hardship, and social transformation has created a uniquely difficult environment for sports development generally (Miho, 2024).
Given that weightlifting is a highly competitive sport, it requires sustained support from governments, sport organizations, and relevant institutions (Kumar, 2024). In this regard, robust educational and development programs are needed to raise awareness of the sport and promote it at the community level. In addition, access to appropriate facilities and equipment for training and competition, together with ongoing programs for talent identification and development, are among the key factors underpinning the growth of weightlifting (Comfort et al., 2023). Alongside these structural elements, improving the broader cultural and social environment can also substantially contribute to the sport’s development (Pierce et al., 2022). Ultimately, as with any sport and particularly in the case of weightlifting positive shifts in social and cultural attitudes are necessary so that young people and other groups are encouraged to participate actively and are given the opportunity to realize and showcase their potential (Gravelle et al., 2025). However, in the Iraqi context, these fundamental requirements remain largely unfulfilled. The country's sports infrastructure, has suffered extensive damage and neglect due to decades of conflict and underinvestment (Al-Zubaidi et al. 2024). Moreover, the absence of systematic talent identification programs and limited access to qualified coaches has hindered the development of promising athletes (Sarmento et al, 2018). Cultural attitudes toward Strength exercises, particularly regarding participation by women and youth, remain complex and often restrictive, further limiting the sport's reach and potential talent pool (Shaheen, 2024).
Moradi et al. (2023) stated in their research: The results of qualitative analysis and open, central and selective coding showed that the management transformation in weightlifting in Asia, the development of a local model of talent management in weightlifting in Asia, the improvement of the position of weightlifting in the sport of the member countries of the Asian Confederation, the development of training and empowerment of human resources, the improvement of economic and marketing processes Weightlifting federations, development of venues and sports equipment related to weightlifting, branding and development of the Asian weightlifting brand, structural development and legal environment are among the most important strategies for the development of weightlifting in Asia. Paying attention to the factors obtained in this research will make the development of weightlifting in Asia smoother.
While these strategies provide a valuable framework for Asian countries, their applicability to a nation like Iraq, which faces extreme political and economic volatility, requires careful contextualization. The Iraqi weightlifting federation, like many sports institutions in the country, operates within an environment characterized by limited institutional capacity, inconsistent funding, and periodic disruptions caused by broader national instability. Understanding how these Asian development strategies can be adapted to such a fragile context is a critical gap that the present study seeks to address.
Foresight analysis is a strategic and powerful tool for identifying and assessing key driving forces that can shape development and progress in any field (Wright et al., 2020). It is particularly valuable in complex and rapidly changing contexts such as economic development, social transformation, and the improvement of management systems because it helps decision-makers better understand how dynamic and interdependent these systems are (del Mar Delgado-Serrano et al., 2016). By applying foresight methods, it becomes possible to map out the opportunities and threats present in both the internal and external environment of a given system or domain, anticipate potential shifts and disruptions, and construct alternative scenarios for how the future might unfold (Emami et al., 2022). Such analysis is especially critical when change is fast, uncertainty is high, and events are difficult to predict, as it can significantly enhance the quality of strategic planning and decision-making in high-risk environments (Raford, 2015). Iraq's weightlifting sector exemplifies precisely such a high-risk, high-uncertainty environment, making the application of foresight methodologies particularly appropriate and potentially transformative.
In today’s rapidly changing world, the use of foresight-oriented analytical tools has become essential for steering and managing different types of change (Monteiro & Dal Borgo, 2023). Foresight analyses help to identify emerging trends and can play a significant role in shaping development strategies that are grounded in the actual and potential needs of societies and organizations (Westphal et al., 2023). Such analyses enable managers, policymakers, and decision-makers to anticipate possible future pathways by developing a sound understanding of the key forces at play and their interactions, and on this basis to design both long-term and short-term strategies in a more informed and deliberate way (Meskó et al., 2024). Seifi et al. (2025), The findings underscore the importance of strategic knowledge management in enhancing the strategic capabilities of sports federations. These strategies can serve as a pathway for improving performance and fostering innovation within these organizations. Also, Moharramzadeh et al. (2025) stated in their research: Clubs must move beyond match-day results and adopt integrative strategies that align organizational behavior with the cultural and psychological needs of supporters.
In this regard, the core function of foresight analysis is to pinpoint major shifts and key trends that have the potential to shape the future (Naughtin et al., 2024). These trends may emerge directly or indirectly from changes in technology, the economy, politics, or culture (Szpilko et al., 2020). For example, in the economic domain, developments in global markets, fluctuations in commodity prices, and adjustments to fiscal policies in different countries can substantially affect the economic position of nations and organizations. Likewise, at the social and cultural level, evolving public attitudes, values, and social norms can have a significant impact on how decisions are made and priorities are set across different societies (Toivonen, 2025). In Iraq, these macroeconomic and socio-cultural forces are particularly dynamic and unpredictable, shaped by the country's ongoing reconstruction efforts, its relationship with regional and global powers, and the gradual evolution of its post-conflict social fabric. Any meaningful strategy for weightlifting development must therefore account for these broader contextual forces and their potential trajectories.
Accordingly, foresight analysis is essential not only for identifying opportunities and threats, but also for understanding how different forces interact within a system or organization (Saritas et al, 2022). This deeper insight into the web of interrelationships among key factors makes it possible to design strategies that both mitigate risks and enable the optimal use of existing opportunities and resources (Nascimento et al., 2021). Ultimately, given that the future is never fully predictable and uncertainty is an inherent part of it, foresight as a tool for anticipation and planning can play a crucial role in building greater resilience and adaptability in the face of future change (Neuhoff et al, 2021).
Weightlifting is one of the most difficult and competitive sports, and it is important for many countries around the world to build physical strength and improve health. But in developing countries, this sport often has a lot of problems that make it hard for it to grow and reach its full potential. These problems are mostly related to infrastructure, education, and cultural acceptance. In nations like Iraq, despite substantial potential and emerging talent in weightlifting, political, economic, and social challenges profoundly influence and limit its developmental trajectory. Iraqi weightlifters have demonstrated remarkable resilience, with Paralympic athletes like Faris al-Ajeeli and Thaer al-Ali winning multiple medals at international competitions including the Athens 2004 Paralympics and world championships, yet they have been forced to train in makeshift home gyms due to the destruction of sports infrastructure during decades of conflict (). The national women's weightlifting team, established in 2011 despite strong societal resistance in conservative communities, has achieved regional medals and provides crucial monthly incomes of $400-$800 for athletes from modest families, yet they continue training in rundown facilities with limited equipment. These conditions ranging from ISIL's occupation that prevented athletes from competing under the Iraqi flag to the absence of systematic talent identification programs and qualified coaches have created a uniquely challenging environment where raw talent exists but systematic development remains elusive. These conditions underscore the necessity for a thorough and methodical inquiry to identify and evaluate the principal factors affecting the advancement of weightlifting in Iraq and other nations with analogous circumstances. The primary objective of this study is to ascertain the principal driving forces and examine the obstacles that impede the advancement of weightlifting. In this context, foresight tools, especially cross-impact analysis, can be very useful and helpful. Sport policy-makers can make development plans that are based on real and possible needs by mapping out the opportunities and threats in both the internal and external environments of the sport and looking at how these factors interact with each other. In the end, this study aims to suggest practical solutions that can help weightlifting grow in a sustainable way in developing countries and help everyone involved make the most of the sport's potential.
Study adopted a structural analysis approach to explore the driving forces shaping the development of weightlifting in Iraq. The research design combined a literature- and document-based phase with expert-based foresight techniques, namely a three-round Delphi process followed by MICMAC cross-impact analysis. First, a comprehensive review of the academic literature on sport development, talent pathways and high-performance systems in weightlifting and related sports, together with national sports policy documents and regulations relevant to Iraq, was conducted to identify an initial pool of potential drivers. A systematic search strategy was employed across multiple scientific databases including SPORTDiscus, PubMed, Web of Science, Scopus, and Google Scholar to ensure comprehensive coverage of relevant literature. The search utilized combinations of keywords in both English and Arabic, including: "weightlifting development," "talent identification," "sport development," "high-performance sport," "developing countries sport," "Iraq sport," "sport policy," and "sport governance," as well as specific terms related to the PESTEL dimensions such as "sport funding," "sport infrastructure," and "sport participation." Additionally, Boolean operators (AND, OR) were applied to refine search results, and reference lists of identified articles were manually screened to locate additional relevant publications. The search was limited to peer-reviewed journal articles, books, and conference proceedings published between 2000 and 2024 to ensure contemporary relevance while capturing foundational literature. National sports policy documents, strategic plans of the Iraqi Ministry of Youth and Sports, and regulations from the Iraqi Weightlifting Federation were also collected through official government websites and direct requests to relevant institutions. These candidate drivers were organized according to the PESTEL framework, covering political, economic, social, technological, environmental and legal dimensions of the Iraqi weightlifting system. The Delphi technique was then used to refine and validate this pool.
These candidate drivers were organized according to the PESTEL framework, covering political, economic, social, technological, environmental and legal dimensions of the Iraqi weightlifting system. The Delphi technique was then used to refine and validate this pool. The expert panel for this study was selected using a purposive and criterion-based sampling strategy. The panel consisted of 15 experts, all of whom met predefined inclusion criteria requiring a minimum of ten years of professional experience in at least one of the following domains: sport management and policy-making within Iraqi sports federations; high-performance weightlifting coaching at the national or international level; academic expertise in sport development with specific knowledge of the Iraqi context; or governance roles within the Iraqi Weightlifting Federation or the National Olympic Committee of Iraq. Experts were identified through professional networks, official records of the Iraqi Weightlifting Federation, and snowball sampling, ensuring that all selected individuals possessed direct, practical, and authoritative knowledge of the challenges and opportunities facing weightlifting in Iraq. In the first Delphi round, semi-structured interviews were conducted with a panel of experts in sport management, weightlifting coaching and federation governance. The purpose of this round was to generate, clarify and consolidate potential drivers across the PESTEL dimensions rather than to quantify their importance. The qualitative material from these interviews was analyzed and merged with insights from the literature and policy review to produce a consolidated list of 20 candidate drivers. The interview data were analyzed using thematic analysis following the six-phase framework proposed by Braun and Clarke. All interviews were audio-recorded and transcribed verbatim. Two researchers independently coded the transcripts, identifying initial codes inductively and then organizing them into broader themes aligned with the PESTEL framework. The two researchers met regularly to compare coding decisions and resolve discrepancies through discussion until consensus was reached. The final thematic structure was subsequently reviewed and validated by a third researcher with expertise in qualitative sports research methodology, ensuring that the interpretation accurately reflected the content of the expert interviews. In the second round, a structured questionnaire was administered to the same expert panel. Experts were asked to rate the importance of each of the 20 drivers on a five-point Likert scale, and consensus was operationalized as the percentage of experts assigning each item to a predefined “high-importance” range. For this study, the high-importance range was defined as ratings of 4 or 5 on the five-point Likert scale. Consensus was calculated using the formula: (number of experts rating the driver as 4 or 5 / total number of experts) × 100. A consensus threshold of 70% was adopted, meaning a driver was considered to have achieved expert consensus if at least 70% of panel members assigned it a rating of 4 or 5. All drivers achieved at least 70% consensus in this round, indicating that none of the 20 variables needed to be discarded on the basis of low perceived relevance. In the third Delphi round, controlled feedback was provided to the experts. For each driver, the group-level statistical summaries from Rounds 2 and 3, specifically the consensus percentages, were presented to the panel, allowing individual experts to reconsider their judgements in light of the emerging collective pattern. Experts were invited to review and, if they wished, adjust their previous ratings, thereby promoting convergence while preserving anonymity and independence of opinion. Following this round, consensus percentages were recalculated using the same formula and 70% threshold, resulting in final consensus percentages ranging from 80% to 100%. This iterative process resulted in high and generally increasing levels of agreement across all 20 drivers, confirming their perceived importance as key determinants of the future development of weightlifting in Iraq. The final list of drivers, together with their PESTEL classification and consensus levels from the second and third Delphi rounds, constituted the validated input for the subsequent structural analysis phase.
Following the validation of the 20 drivers, a 20 × 20 cross-impact matrix was constructed to capture the perceived causal relationships among them. Members of the expert panel assessed the pairwise influence of each driver on every other driver using the MICMAC influence scale. This scale comprised five response options: 0 for no influence, 1 for weak influence, 2 for moderate influence, 3 for strong influence, and P for potential influence, indicating a relationship that may become significant in the future. For each ordered pair of drivers, experts judged the extent to which changes in the row variable would directly affect the column variable. These judgements were then aggregated at the matrix level to obtain a single value for each cell, thereby estimating, for each driver, its driving power how strongly it shapes other variables and its dependence how strongly it is conditioned by them. The completed cross-impact matrix was analyzed using MICMAC software to derive the direct and indirect influence structures of the system. In the first step, the software generated the matrix of direct influences (MDI) and calculated, for each driver, the sum of its row values and the sum of its column values. The row sum represents the total direct influence a driver exerts on the rest of the system, while the column sum indicates its total direct dependence on all other drivers. These indices provide an initial quantitative representation of how influence and dependence are distributed across the 20 variables and serve as the basis for positioning them in the direct influence/dependence space. In a second step, the analysis was extended to potential and indirect effects. MICMAC iteratively propagated influences through multi-step paths, producing matrices of potential direct and potential indirect influences. From these, potential influence and dependence indices were computed for each driver, capturing not only immediate effects but also longer causal chains operating within the system. To refine the structural interpretation, the Proportions module of MICMAC was employed. This procedure transforms the raw potential influence dependence indices into comparable scores on a 0–1000 scale and ranks the drivers according to their relative weight in the system. Separate proportions were obtained for potential direct influence, potential direct dependence, potential indirect influence and potential indirect dependence, allowing the identification of drivers that concentrate a large share of systemic influence versus those characterized mainly by potential dependence. Finally, MICMAC was used to generate graphical representations of the system: a direct influence/dependence map and an indirect influence/dependence map, as well as direct and indirect influence graphs. In the maps, each driver is positioned according to its influence and dependence scores, enabling its classification as a determinant, relay, dependent or relatively autonomous variable. In the graphs, drivers are represented as nodes connected by directed arcs that depict the strength and direction of direct or indirect influences. Together, these outputs provide a structured, system-level view of the key drivers of weightlifting development in Iraq and constitute the empirical basis for the subsequent foresight interpretation.
Table 1 profiles the Delphi expert panel (N = 15) by gender, education level, field of study, average sports executive experience, and age.
Table 1- Frequency and Percentage Distribution of Demographic Characteristics of Delphi Group Experts
|
Characteristic |
Gender |
Education Level |
Field of Study |
Average Sports Executive Experience |
Age |
|||||
|
Male |
Female |
Master's |
Doctorate |
Physical Education |
Non-Physical Education |
Lowest |
Highest |
Lowest |
Highest |
|
|
Frequency |
12 |
3 |
8 |
7 |
9 |
6 |
10 |
25 |
32 |
61 |
Following a comprehensive review of the literature and relevant policy documents, the Delphi technique was employed to finalize the list of driving forces shaping the development of weightlifting in Iraq. In the first round, semi-structured interviews with a panel of experts in sport management, weightlifting coaching and federation governance were conducted to generate and refine an initial roster of drivers across the PESTEL dimensions. In the second round, a structured questionnaire was administered to the same panel to rate the importance of the 20 candidate drivers on a five-point Likert scale; all items reached at least 70% consensus within the predefined “high-importance” range. In subsequent iterations, experts were given the opportunity to revise their judgements in light of group statistical feedback, and the consolidated results, including consensus percentages for Rounds 2 and 3, were presented to them in the third Delphi round. The final outputs of the literature review and three-round Delphi procedure are reported in Table 2.
Following the validation of the 20 key drivers influencing the future development of weightlifting in Iraq, a 20 × 20 cross-impact matrix was constructed. Members of the expert panel assessed the pairwise influence of each driver on every other driver using the MICMAC five-point scale (0 = no influence; 1 = weak; 2 = moderate; 3 = strong; P = potential influence). These ratings were aggregated to estimate, for each driver, its driving power the extent to which it shapes other components of the weightlifting system and its dependence the extent to which it is affected by them. The completed matrix was subsequently analyzed in MICMAC to derive the system’s direct and indirect influence structures and to position and profile the drivers within the influence–dependence space.
Table 2- Foresight of Weightlifting Development in Iraq: Delphi Validated PESTEL Drivers and Consensus Levels
|
Domain |
Drivers |
Consensus (Delphi Round 2) (%) |
Consensus (Delphi Round 3) (%) |
|
Political |
Provincial autonomy and support for developing grassroots clubs |
85.6 |
89.4 |
|
Sports diplomacy for hosting events and international presence |
79.3 |
87.6 |
|
|
Facilitating imports and access to standard weightlifting equipment |
80.5 |
81.2 |
|
|
Policies to expand girls' participation in weightlifting |
78.1 |
90.3 |
|
|
Economic |
Diversification of funding sources and reduced dependence on oil revenue |
77.4 |
83.1 |
|
Sustainability and adequacy of the elite sports budget |
79.0 |
83.7 |
|
|
The capacity and attractiveness of the sponsorship market in the provinces |
72.8 |
86.7 |
|
|
Families' financial ability to cover sports expenses |
74.2 |
79.5 |
|
|
Social |
Family social capital and parental involvement in supporting grassroots clubs |
92.4 |
90.5 |
|
Developing a culture of sports participation in local communities and schools |
74.8 |
78.9 |
|
|
Changing societal attitudes toward strength sports |
76.1 |
79.7 |
|
|
Technological |
The digitalization of athlete talent identification processes |
91.5 |
91.7 |
|
The use of video analysis and training monitoring software |
76.3 |
82.4 |
|
|
Environmental |
Adaptation of training environments to diverse climatic conditions |
72.5 |
78.1 |
|
Optimization of facility design and safety in line with standards |
77.8 |
89.2 |
|
|
Resilience of sports infrastructure to natural disasters |
84.2 |
90.0 |
|
|
Legal |
Compliance with national and international anti-doping regulations |
79.9 |
89.8 |
|
A legal framework to support insurance coverage for athletes and coaches |
74.2 |
78.4 |
|
|
Legislation to ensure accountability in the governance of federations and clubs |
80.1 |
87.5 |
|
|
Development of binding regulations for coaches' professional qualifications |
75.5 |
79.8 |
After identifying the key drivers shaping the development trajectory of Iraqi weightlifting, the expert panel completed the cross-impact matrix using the MICMAC influence scale. Based on these inputs, the software generated the matrix of direct influences (MDI) and calculated, for each driver, the sum of its row and column values. The row sum reflects the total direct influence exerted by a driver on all other drivers, whereas the column sum represents its total direct dependence on the rest of the system. Together, these indices offer an initial quantitative overview of how influence and dependence are distributed across the drivers shaping the future of weightlifting in Iraq. The results are presented in Table 3.
Table 3- Row and column sums of the matrix of direct influences (MDI)
|
No |
Variable |
Total number of rows |
Total number of columns |
|
1 |
P1 |
36 |
25 |
|
2 |
P2 |
32 |
32 |
|
3 |
P3 |
23 |
18 |
|
4 |
P4 |
31 |
29 |
|
5 |
E1 |
32 |
17 |
|
6 |
E2 |
30 |
25 |
|
7 |
E3 |
28 |
46 |
|
8 |
E4 |
18 |
9 |
|
9 |
S1 |
24 |
36 |
|
10 |
S2 |
26 |
40 |
|
11 |
S3 |
28 |
31 |
|
12 |
T1 |
23 |
25 |
|
13 |
T2 |
19 |
25 |
|
14 |
En1 |
17 |
9 |
|
15 |
En2 |
30 |
36 |
|
16 |
En3 |
24 |
18 |
|
17 |
L1 |
26 |
25 |
|
18 |
L2 |
33 |
29 |
|
19 |
L3 |
29 |
26 |
|
20 |
L4 |
28 |
36 |
|
|
Total |
537 |
537 |
As shown in Table 3, the distribution of row and column sums provides an initial structural reading of how influence and dependence are allocated within the weightlifting system. Drivers with comparatively high row totals exhibit a stronger ability to shape other components of the system, reflecting their role as direct sources of change. In contrast, drivers with higher column totals function primarily as dependent elements whose behavior is conditioned by developments elsewhere in the network.
To refine the structural analysis of the system, the Proportions module of MICMAC was then used. This procedure expresses the potential influence dependence indices on a common 0–1000 scale and ranks the drivers according to their relative weight in the system. In this way, it becomes possible to identify which drivers concentrate the largest shares of potential direct and indirect influence, and which ones are predominantly characterized by potential dependence. Table 4 reports these proportional scores, including for each driver its rank, code, potential direct influence, potential direct dependence, potential indirect influence and potential indirect dependence.
Table 4- Proportions of potential direct and indirect influence and dependence for the key drivers of the future development of weightlifting in Iraq
|
Rank |
Label |
Direct influence |
Label |
Direct dependence |
Label |
Indirect influence |
Label |
Indirect dependence |
|
1 |
P1 |
670 |
E3 |
856 |
P1 |
631 |
E3 |
815 |
|
2 |
L2 |
614 |
S2 |
744 |
L2 |
608 |
S2 |
715 |
|
3 |
P2 |
595 |
S1 |
670 |
P2 |
603 |
L4 |
655 |
|
4 |
E1 |
595 |
En2 |
670 |
E1 |
581 |
S1 |
647 |
|
5 |
P4 |
577 |
L4 |
670 |
P4 |
579 |
En2 |
638 |
|
6 |
E2 |
558 |
P2 |
595 |
L3 |
549 |
S3 |
602 |
|
7 |
En2 |
558 |
S3 |
577 |
En2 |
547 |
P2 |
587 |
|
8 |
L3 |
540 |
P4 |
540 |
E2 |
546 |
P4 |
561 |
|
9 |
E3 |
521 |
L2 |
540 |
S3 |
530 |
L2 |
532 |
|
10 |
S3 |
521 |
L3 |
484 |
L4 |
521 |
L3 |
523 |
|
11 |
L4 |
521 |
P1 |
465 |
E3 |
506 |
L1 |
513 |
|
12 |
S2 |
484 |
E2 |
465 |
L1 |
504 |
T1 |
477 |
|
13 |
L1 |
484 |
T1 |
465 |
S2 |
493 |
T2 |
469 |
|
14 |
S1 |
446 |
T2 |
465 |
S1 |
458 |
P1 |
463 |
|
15 |
En3 |
446 |
L1 |
465 |
P3 |
446 |
E2 |
441 |
|
16 |
P3 |
428 |
P3 |
335 |
En3 |
443 |
E1 |
356 |
|
17 |
T1 |
428 |
En3 |
335 |
T1 |
435 |
P3 |
346 |
|
18 |
T2 |
353 |
E1 |
316 |
T2 |
363 |
En3 |
317 |
|
19 |
E4 |
335 |
E4 |
167 |
E4 |
328 |
E4 |
172 |
|
20 |
En1 |
316 |
En1 |
167 |
En1 |
317 |
En1 |
160 |
As shown in Table 4, the distribution of the proportional indices of potential direct and indirect influence and dependence clarifies the different roles that the drivers of weightlifting development in Iraq play within the system. Drivers that occupy the top ranks in terms of potential influence particularly those combining high direct and indirect influence with comparatively lower levels of dependence can be interpreted as determinant variables, because they exert a strong shaping effect on the rest of the system. By contrast, drivers that display simultaneously high values for both influence and dependence behave as relay (linkage) variables: they not only affect many other drivers but are also strongly affected by changes elsewhere in the system, and therefore function as key transmission channels through which the effects of determinant variables propagate. Finally, drivers with relatively low influence but high dependence are mainly outcomes of the system’s dynamics and are more responsive to changes initiated by other factors. This pattern of influence–dependence proportions underscore the complex interplay between direct and indirect effects and highlights the need to priorities determinant and relay drivers when designing strategies to foster the development of weightlifting in Iraq.
To visualize the overall structure of direct relationships among the variables, a direct influence/dependence map was generated in MICMAC for the drivers of the future development of weightlifting in Iraq. In this map, the horizontal axis represents the level of direct dependence of each driver on the rest of the system, while the vertical axis shows its direct influence on the other drivers. The position of each variable in this two-dimensional space makes it possible to classify the drivers as determinant, relay, dependent, or relatively autonomous elements within the weightlifting development system. The resulting configuration is displayed in Figure 1.

Figure 1. Direct influence/dependence map of the key drivers of the future development of weightlifting in Iraq
As shown in Figure 1, the direct influence/dependence map reveals the overall structure of the relationships among the key drivers of the future development of weightlifting in Iraq. The variables are positioned according to their level of direct influence on other drivers (vertical axis) and their direct dependence on the rest of the system (horizontal axis). Drivers in the upper-left quadrant have high direct influence with relatively low dependence, indicating that they play a significant role in shaping the system while remaining somewhat independent. The upper-right quadrant contains relay variables, which have both strong influence and high dependence on other factors, suggesting that they are pivotal in transmitting effects throughout the system. Conversely, variables in the lower-right quadrant have low direct influence but high dependence, highlighting their role as outcomes of changes in other drivers. Finally, the lower-left quadrant includes drivers with low levels of both influence and dependence, indicating a more marginal or autonomous position within the system. This map helps to visualize the structural roles of each driver and provides insights into how changes within the weightlifting system may spread and evolve.
To capture the longer-term and chain-like effects among the variables, MICMAC was also used to compute the indirect influence/dependence map. This representation is based on the propagation of influences through multi-step paths in the system, rather than only on immediate, direct links. As in the previous figure, the horizontal axis indicates the level of dependence and the vertical axis indicates the level of influence, but here both measures incorporate indirect effects. The resulting configuration of drivers is shown in Figure 2.

Figure 2. Indirect influence/dependence map of the key drivers of the future development of weightlifting in Iraq
As shown in Figure 2, the indirect influence/dependence map illustrates the structural relationships among the key drivers of the future development of weightlifting in Iraq when considering the cumulative and multi-step effects within the system. The positioning of each driver reflects its indirect influence on other factors (vertical axis) and its indirect dependence on other variables (horizontal axis). Variables positioned in the upper quadrants tend to act as intermediaries, influencing and being influenced by several other factors across the system. In contrast, drivers positioned in the lower quadrants exhibit lower indirect influence or dependence, indicating a more peripheral role in the system’s broader dynamics.
To complement the positioning of variables on the influence/dependence maps, MICMAC was also used to generate a direct influence graph for the key drivers of the future development of weightlifting in Iraq. In this network representation, each node corresponds to a driver within the weightlifting development system, and each directed arc represents a direct influence exerted by one driver on another. The thickness and color of the arcs differentiate weaker from stronger relationships, allowing a clear visualization of both the density of direct connections and the primary pathways through which immediate effects spread across the system. The resulting network structure is presented in Figure 3.

Figure 3. Direct influence graph of the key drivers of the future development of weightlifting in Iraq
As shown in Figure 3, the direct influence graph presents a dense network of immediate causal relationships among the key drivers of weightlifting development in Iraq. The structure of the graph highlights the complexity of the system, with numerous interconnected pathways through which direct effects circulate. The variation in line thickness and color illustrates differences in the strength of these relationships, allowing a clear distinction between weaker, moderate and stronger direct influences. The overall pattern reveals that certain drivers act as central nodes with multiple outgoing links, indicating their importance as initiators of direct change, while others occupy more peripheral positions with fewer direct connections. This visualization offers a comprehensive view of how direct interactions are distributed across the system and provides an essential foundation for understanding how shifts in specific areas may propagate through the weightlifting development landscape.
In a final step, MICMAC was used to generate an indirect influence graph, based on the matrix of potential indirect influences. This network representation captures how drivers affect one another through multi-step paths rather than only through immediate, direct links. Each node again represents a driver in the system, while the arcs show the cumulative strength of indirect influences that propagate across the network. The different line types and colors distinguish weaker from stronger indirect effects. The resulting configuration is presented in Figure 4.

Figure 4. Indirect influence graph of the key drivers of the future development of weightlifting in Iraq
As shown in Figure 4, the indirect influence graph illustrates the broader network of relationships among the key drivers of the future development of weightlifting in Iraq, considering not only direct but also cumulative, multi-step effects. In this graph, each node represents a driver, while the arcs depict indirect influences across the system. The varying thickness and color of the arcs represent the strength of these indirect influences, with red arcs indicating the strongest relationships, blue arcs for moderate influences, and lighter blue for weaker connections. This graph reveals the pathways through which changes in one driver can propagate and affect others over time. It highlights the complex, interdependent nature of the system, where multiple drivers influence each other in indirect ways, underscoring the importance of considering long-term, cascading effects in policy and decision-making related to the development of weightlifting in Iraq.
The current study employed a structural foresight approach, integrating Delphi and MICMAC analyses, to identify and map the 20 key drivers shaping the future development of weightlifting in Iraq. The findings reveal a complex, multi-layered system in which political, economic, social, technological, environmental, and legal factors interact through both direct and indirect causal pathways. This discussion interprets these findings in depth, compares them with existing literature, and explicates the causal mechanisms that underlie the observed influence dependence structures.
A central finding of this study is the decisive role of political and legal drivers. Provincial autonomy and support for developing grassroots clubs (P1) emerged as one of the most influential and least dependent variables in the system, characterized by exceptionally high direct influence and relatively low dependence on other factors. This positioning indicates that political decentralization and local commitment to club development are not merely facilitative conditions but fundamental starting points for systemic change. The causal mechanism here operates through what Reiche (2017) identified as the governance deficit in developing country sport systems: when provincial authorities possess both autonomy and mandate to invest in grassroots sport, they can create localized ecosystems of support including facility provision, coaching employment, and competition organization that are more responsive to community needs than centralized structures. This finding aligns with García and Meier's (2022) analysis of sport governance transplants in the Global South, which found that imported governance models often fail when they do not align with local political structures. In Iraq's emerging federalizing context, where provinces are gaining greater authority, this driver represents a structural opportunity to build weightlifting development on this evolving political reality.
Similarly, legal drivers exhibited high potential influence, particularly insurance coverage for athletes and coaches (L2) which ranked among the most influential variables, and accountability mechanisms in federation governance (L3). The causal logic here involves risk reduction and institutional trust. In the absence of formal insurance protections, participation in weightlifting a sport with inherent physical risks becomes precarious for athletes and families, particularly where out-of-pocket medical costs can be catastrophic. Insurance provisions reduce this perceived risk, lowering a key barrier to entry and retention. This mechanism is consistent with Kumar's (2024) argument that legal clarity and institutional accountability are foundational to sport development in fragile states. Likewise, governance accountability mechanisms (L3) address what North's institutional theory would term the "commitment problem": without credible oversight, stakeholders cannot trust that federations will act in their interests, leading to disengagement. The high influence of these legal variables confirms that formal rules and enforcement are not bureaucratic formalities but essential preconditions for stable, growth-oriented sport organizations.
The economic drivers identified diversification of funding sources (E1), adequacy of the elite sport budget (E2), and provincial sponsorship market attractiveness (E3) occupy distinct positions that reveal their causal relationships. E1 functions as a determinant variable with strong direct influence and notably low dependence, suggesting that funding structure itself shapes possibilities for all other economic activity. The causal mechanism involves portfolio effects: when funding concentrates in a single source like oil revenue, the entire system becomes vulnerable to commodity price fluctuations and political allocation decisions. Diversification creates multiple revenue streams that buffer against sector-specific shocks. This finding empirically supports Emami et al.'s (2022) foresight analysis of the Iranian health system, which similarly identified funding diversification as an upstream driver of system resilience, and echoes Miho's (2024) comprehensive review of economic diversification challenges in Iraq.
In contrast, provincial sponsorship market attractiveness (E3) emerged as the most dependent variable in the entire system, exhibiting the highest dependence scores among all drivers. This indicates that sponsorship does not emerge spontaneously but is contingent upon prior developments in governance, infrastructure, and social legitimacy. The causal pathway involves signaling effects: private sponsors invest when they perceive weightlifting as professionally managed, socially valued, and capable of delivering reputational returns. This requires foundational work in legal accountability (L3), facility quality (En2), and cultural acceptance (S3). The implication, consistent with Fathi et al.'s (2021) findings on organizational resilience, is that policymakers seeking sponsorship should begin with institutional and social groundwork that makes weightlifting a credible investment vehicle, not with direct appeals to businesses.
Social and cultural variables occupy what the MICMAC analysis reveals as the "relay" quadrant, exhibiting simultaneously high influence and high dependence. Family social capital and parental involvement (S1), community sports participation culture (S2), and changing societal attitudes toward strength sports (S3) all show this dual character. S2, for instance, demonstrates very high dependence while maintaining substantial influence throughout the system. This positioning reveals a dual causal function: these variables are powerful transmitters of change originating elsewhere in the system, yet they are also sensitive receivers whose state determines whether structural reforms translate into behavioral outcomes.
The relay mechanism can be understood through the concept of social capital as a transformative resource. Families with high social capital networks, information, trust are better positioned to navigate the sport system and support their children's participation. However, this capital activation depends on whether political decisions (policies to expand girls' participation, P4) and economic investments create environments where families feel empowered to engage. Conversely, when families withdraw support due to cultural stigma or economic constraints, even well-designed policies may fail. This bidirectional causality explains why social variables occupy the relay space: they are channels through which macro-level forces translate into micro-level behaviors.
The finding that changing societal attitudes toward strength sports (S3) is both influential and dependent aligns with Vasudevan and Ford's (2022) systematic review of barriers to women's strength training, which found that cultural framing of strength sports as masculine operates as a powerful deterrent that can shift through sustained exposure and role modeling. In Iraq, where traditional gender norms remain influential, Shaheen's (2025) study of Palestinian women in strength sports documented similar dynamics: women's engagement emerges not from individual choice alone but from complex negotiation of family dynamics, community attitudes, and cultural framing. This suggests that policies to expand girls' participation (P4) cannot succeed without parallel efforts to reshape cultural narratives a conclusion directly supported by the relay position of these variables.
Technological drivers, including digitalization of talent identification (T1) and video analysis software (T2), exhibited moderate influence and dependence, positioning them as enablers rather than primary drivers. T1 achieved exceptionally high consensus among experts yet demonstrated relatively modest influence compared to political and legal drivers. These finding challenges technological determinism and supports a socio-technical systems perspective: technology's effects are mediated by institutional and social contexts. In systems with weak governance, unstable funding, and low social participation, technological tools alone cannot catalyze development. However, when combined with strong political backing and adequate infrastructure, they can accelerate talent identification and improve training quality. The causal mechanism involves information asymmetry reduction: digital platforms can identify promising athletes in remote areas where coaching expertise is scarce, expanding the talent pool beyond major cities particularly relevant for Iraq's geographic disparities in sport resource access.
Environmental drivers, particularly facility design optimization (En2) and infrastructure resilience to natural disasters (En3), emerged as important through indirect influence pathways. En2 shows high dependence while maintaining moderate influence, reflecting its role as both outcome and enabler. This indirect role reflects the often-unseen nature of environmental factors: when facilities are safe and well-designed, they enable consistent training; when they fail due to disaster or neglect, the entire system disrupts. Iraq's vulnerability to environmental risks makes this finding strategically significant, aligning with Al-Zubaidi et al.'s (2024) identification of infrastructure deficits as critical barriers to sustainable sport development in Iraq. The causal mechanism is continuity of operations: resilient infrastructure ensures that political commitments, economic investments, and social engagement are not periodically nullified by environmental shocks.
Comparing these findings with Moradi et al.'s (2023) Asian weightlifting development model reveals both alignment and contextual divergence. Their emphasis on management transformation, talent management systems, and structural development resonates with Iraq's need for governance accountability (L3) and coaching qualifications (L4). However, Iraq's political volatility and oil-dependent economy create distinct challenges: while Asian strategies assume relatively stable institutional environments, Iraq requires approaches that build resilience into the system's core diversified funding (E1), disaster-resistant infrastructure (En3), and decentralized political structures (P1) that can withstand national-level disruptions. This contextualization addresses the critical gap identified in the introduction: adapting Asian development strategies to fragile contexts requires explicit attention to these foundational drivers.
The methodological contribution of integrating Delphi and MICMAC merits discussion. Traditional approaches often produce lists of barriers that provide little guidance about intervention leverage points. By mapping influence–dependence relationships, this study reveals causal structure, distinguishing drivers that initiate change (determinants), transmit it (relay), and register effects (dependent). This responds to calls in the foresight literature for methods capturing system dynamics rather than static snapshots (Saritas et al., 2022; Wright et al., 2020; del Mar Delgado-Serrano et al., 2016). For Iraqi policymakers, this offers practical leverage: interventions should prioritize determinant variables (P1, L2, E1) and manage relay variables (S1, S2, S3) as transmission channels, recognizing that dependent variables (E3, T1, T2) will improve as upstream conditions strengthen.
Several limitations temper these conclusions. The MICMAC analysis captures expert perceptions rather than observed longitudinal data; while expert judgment is valuable in foresight research, particularly where longitudinal data are scarce, it is subject to cognitive biases. The expert panel, though carefully selected for diversity, was limited to individuals engaged with the formal sport system, potentially underrepresenting athletes, families, and community leaders whose decisions ultimately determine participation. Future research should test these influence–dependence patterns using quantitative methods examining how funding variations, governance reforms, or community programs relate to participation rates and performance outcomes over time. Comparative studies with weightlifting systems in neighboring countries would also help distinguish context-specific factors from broader patterns in Global South sport development.
Despite these limitations, the findings provide a structured, empirically grounded starting point for strategic planning in Iraqi weightlifting. By making explicit the interplay among political, economic, social, technological, environmental, and legal forces, this study offers both a conceptual map and a practical agenda for guiding the sport toward a more sustainable and inclusive future.
This study employed an integrated Delphi-MICMAC foresight methodology to identify and analyze the 20 key drivers shaping the future development of weightlifting in Iraq. The findings demonstrate that weightlifting development is not merely a function of technical factors like coaching quality or facility availability, but rather an emergent property of complex interactions among political decentralization, legal accountability, economic diversification, social capital, technological adoption, and environmental resilience.
The most significant theoretical contribution lies in demonstrating that these drivers are not independent factors but elements of a structured system with unequally distributed influence and dependence. Political and legal drivers’ provincial autonomy (P1), insurance protections (L2), governance accountability (L3), and sports diplomacy (P2) occupy determinant positions, functioning as structural foundations upon which all other developments depend. Their high influence and relatively low dependence indicate that investments in these areas will generate cascading effects throughout the system, making them priority targets for intervention.
Economic diversification (E1) similarly operates as an upstream driver, shaping possibilities for sponsorship, budgeting, and investment. Its determinant position confirms that funding structure itself particularly reducing dependence on volatile oil revenue is a prerequisite for system resilience rather than merely a resource availability issue. The extreme dependence of provincial sponsorship markets (E3) on other drivers empirically demonstrates that sponsorship follows institutional development rather than preceding it.
Social and cultural variables family involvement (S1), community participation culture (S2), and attitudes toward strength sports (S3) serve as relay mechanisms, transmitting effects of structural reforms into behavioral outcomes while simultaneously conditioning whether those reforms can succeed. This dual role explains why top-down policies alone often fail: without concurrent engagement of families, communities, and cultural narratives, structural decisions may not translate into actual participation increases.
Technological and environmental factors play enabling roles, amplifying effects of stronger drivers but unable to substitute for them. Digital talent identification (T1) and video analysis (T2) can accelerate development when governance and funding are in place, but remain ineffective in institutional vacuums. Environmental resilience (En3) and facility optimization (En2) ensure continuity but depend on prior political and economic commitments.
These findings carry clear implications for policy and practice in Iraq. First, strengthening provincial mandates to support grassroots clubs (P1) should be the foundational priority, creating localized ecosystems that can sustain development regardless of national-level disruptions. Second, enacting insurance protections (L2) and governance accountability mechanisms (L3) addresses the risk and trust barriers that currently discourage participation and investment. Third, diversifying funding sources (E1) beyond oil revenue through private sponsorship, international partnerships, and commercial activities is essential for long-term resilience, requiring simultaneous work on the governance and social conditions that make weightlifting attractive to investors. Fourth, policies to expand girls' participation (P4) must proceed alongside community engagement and media campaigns that gradually shift cultural attitudes (S3), recognizing that social change is a co-evolutionary process not a prerequisite. Finally, technology and infrastructure investments should be deployed as amplifiers of these stronger drivers, not as standalone solutions.
The study also demonstrates the value of foresight methodology for sport development research. By moving beyond static barrier lists to map causal structures, the Delphi-MICMAC approach reveals leverage points and propagation pathways, enabling strategic choices based on systemic understanding rather than intuition or precedent. For Iraqi policymakers facing resource constraints and competing priorities, this offers a basis for prioritizing interventions with maximum cascading impact.
Future research should build on these findings through longitudinal studies tracking how changes in funding, governance, or policy affect participation and performance over time, testing the causal mechanisms hypothesized here. Comparative studies with weightlifting systems in other developing countries, particularly those sharing Iraq's political economy features such as oil dependence or post-conflict institutional fragility, could distinguish context-specific from generalizable patterns. Qualitative research engaging athletes, families, and community leaders would reveal how these structural drivers are experienced at the grassroots level, potentially identifying additional factors or refining causal pathway understanding.
In conclusion, the future of weightlifting in Iraq will be shaped not by any single intervention but by the evolving configuration of political will, economic capacity, social legitimacy, technological capability, and environmental sustainability. This study provides a conceptual map of this configuration and a practical agenda for navigating it. The challenge now is translating this systemic understanding into coordinated action that recognizes driver interdependence, leverages determinant variables for maximum impact, and builds the institutional and social foundations on which sustainable weightlifting development depends. If successful, Iraq can not only realize the potential of its weightlifting talent but also demonstrate a model of sport development applicable to other challenging contexts in the Global South.
This study was based on an in-depth expert panel, which ensured analytical rigor, although future studies may further enrich the findings by involving a broader range of stakeholders. In addition, the MICMAC approach captures structured expert assessments of influence within the system; subsequent research could complement this perspective with longitudinal and quantitative analyses and comparative studies across similar national contexts.
The authors thank all experts who participated in the Delphi rounds and contributed their time and insights to this research.
The authors declare no conflict of interest.
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Gemini AI was used for grammatical improvement of this article.