Identification and Structural Analysis of Key Drivers Influencing High-Rise Construction in the Southern Caspian Coastal Belt: A case study of Mazandaran Province

A B S T R A C T
This study aims to identify, prioritize, and structurally analyze the key drivers of speculative high-rise construction in the ecologically sensitive coastal areas of Mazandaran Province, Iran, employing a futures studies approach. This applied research utilized a mixed-methods design. Data were collected through document review and semi-structured interviews with 18 experts. The interviews were coded and analyzed using MAXQDA software to extract key trends. Following trend identification, 14 key drivers were extracted, and their cross-impact matrix, comprising 196 potential relationships (23 strong relationships, 80% fill rate), was assessed and categorized using structural modeling in MICMAC software. The matrix stabilized after two iterations. Vertical development forms a complex network of 14 drivers. Strategic drivers, "urban development control and governance system" (D5, direct influence score: 29), "land market investment attractiveness" (D4), and "building mass density" (D9), constitute the system's dynamic core. Influential drivers include "extra-provincial migration patterns" (D1, highest uncertainty score: 9), "ecological loading" (D8), and "municipal financing mechanisms" (D6). Dependent drivers, such as "high-rise spatial distribution" (D13, dependence score: 27) and "infrastructure-carcass coordination" (D14), primarily reflect the consequences of upstream forces. The spatial development structure is locked into a speculative urban growth machine and a penalty-based governance regime. Escaping this lock-in requires simultaneous intervention in the political economy of land, fundamental reform of municipal revenue systems, and full alignment of physical loading regulations with ecological thresholds. An exclusive focus on dependent variables will remain ineffective.
Extended Abstract
Introduction
Speculative high-rise construction in Mazandaran’s ecologically sensitive coastal zone has become a critical planning challenge. The province, bordered by the Caspian Sea, Hyrcanian forests, and farmland, faces intensifying migration and speculative investment while its limited ecological capacity turns unregulated building into hazards such as subsidence, flooding, climatic blockage, and infrastructure breakdown. In Sorkhrud, land-use change far outpaces indigenous growth, and a non-local “second-home” phenomenon dominates settlement. Drought and water stress on the central plateau have triggered climate migration, termed a “flood of climate refugees,” toward the Caspian littoral, pushing municipalities toward “penalty-based governance” where Article 100 building violations become the main revenue source, fueling high-rise construction. Security-motivated migration from metropolitan areas, especially Tehran, further raises population loads. Despite mounting consequences, a systematic driver analysis is missing. Classical theories of spatial political economy (Lefebvre, Harvey, Smith, Logan and Molotch) and environmental migration studies provide strong frameworks but are rarely linked in this context, and advanced futures methods like MICMAC have seldom been applied. This study identifies and structurally analyzes the key drivers of high-rise construction in Mazandaran’s sensitive coastal areas through a futures-studies lens, asking: (1) What are the key drivers? (2) How do they interact, and which exert most influence or dependence? Steps include trend analysis across social, economic, environmental, and spatial-physical systems; expert prioritization of drivers by importance and uncertainty; and MICMAC structural modeling. The novelty integrates spatial political economy with environmental migration theory, pioneers MICMAC application here, and empirically addresses penalty-based governance, climatic blockage, and infrastructure-carcass asynchrony.
Methodology
The study used a mixed-methods design with 18 experts from urban planning, land management, economics, and environment in Mazandaran, selected by purposive snowball sampling from institutions including the governorate, coastal municipalities, and relevant provincial departments. Data collection had two stages. First, interviews were recorded, transcribed, and coded in MAXQDA, alongside a review of scientific articles and verified news, yielding 15 mega-trends (social 4, economic 4, environmental 4, spatial-physical 3). Second, the panel completed a cross-impact matrix (196 relationships: 39 zero, 77 weak, 57 moderate, 23 strong; 80% fill rate, stable after two iterations). MICMAC computed influence and dependence scores, classifying drivers as strategic, influential, dependent, or autonomous. Validity was supported by triangulation, expert feedback, and high fill rate; reliability by matrix stability and theoretical consistency.
 
Results and discussion
MAXQDA analysis yielded 15 mega-trends; experts derived 14 drivers. Land market investment attractiveness (D4), ecological loading (D8), and infrastructure-carcass coordination (D14) scored highest importance (10); extra-provincial migration (D1) had greatest uncertainty (9). The matrix (80% fill, stable after two iterations) showed governance (D5) with highest influence (29), followed by D4 (24), D1 (22), and municipal financing (D6, 22). Most dependent were high-rise spatial distribution (D13, dependence 27), D14 (26), and building mass density (D9, 25). The influence–dependence map classified D4, D5, D9 as strategic (core dynamics); D1, D8, D6 as influential; D7, D10, D11, D12, D13, D14 as dependent (reflecting upstream forces); D2, D3 as autonomous. Results confirm the urban growth machine and rent-gap theory: a speculative coalition prioritizes exchange-value, and penalty-based governance fuels density. Strong interdependence among strategic drivers signals a systemic lock-in; isolated interventions on dependent variables will fail without simultaneous reform of land economy and municipal revenue. Findings align with Lefebvre, and show natural hazard risk (D12) is dependent, indicating regulation is needed to trigger risk-responsive behavior.
 
Conclusion
The MICMAC analysis identified 14 interconnected drivers. Strategic drivers D4, D5 (influence 29), and D9 form a locked-in core requiring simultaneous policy reform. Influential drivers D1 (uncertainty 9, heightened by security migration), D8, and D6 steer the system; dependent drivers (D7, D10, D11, D12, D13, D14) reflect upstream forces. The spatial structure is locked into a speculative urban growth machine with penalty-based governance. The study integrates political economy of space with environmental migration theory and pioneers MICMAC in this context. Limitations include data access and unaccounted geopolitical uncertainties; scenarios are deferred. Policies should combine governance and finance reform, ecological-capacity zoning, migration monitoring, and pilot regenerative density. Future research should quantify infrastructure-carcass asynchrony, monitor climatic blockage, model security migration, compare Caspian provinces, and link MICMAC with dynamic scenario tools.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to all stages and sections of the research.
 
Conflict of Interest
The authors declare that they have no conflict of interest regarding the authorship or publication of this article.
 
Acknowledgments
This article derives from the “Integrated High-Rise Construction Plan of Mazandaran Province” project, prepared by “Hamkar Pars Boom Consulting Engineers” under the General Directorate of Roads and Urban Development of Mazandaran Province. The two authors were responsible for futures studies, driver identification, and scenario development. The authors thank the project colleagues and client.