Extended Abstract
Introduction: Amid intensifying global competition, rapid environmental changes, and growing complexities, particularly within the oil industry, companies are increasingly driven to strengthen their alliances with strategic collaborators to sustain productivity and effectively navigate dynamic market conditions. Strategic alliances have become a vital mechanism for securing essential resources, enhancing competitiveness, entering new markets, and extending supply chains. These alliances are defined by characteristics such as resource and knowledge sharing, risk distribution, and mutual trust and commitment. In oil-based economies like Iran, legal provisions and technical capacities support the formation of such alliances. However, the high failure rate and inherent risks associated with strategic alliances, especially in large-scale oil projects, can lead to substantial losses for firms and adverse impacts on the national economy. Accordingly, a comprehensive understanding of alliance-related risks and the key factors influencing their success or failure is essential for informed strategic decision-making.
Methodology: This study adopts an interpretive-symbolic paradigm with an exploratory aim and a developmental-applied nature, employing an inductive and qualitative approach. A multi-phase methodology based on grounded theory was implemented to develop a comprehensive model of strategic alliance risk factors in Iran's downstream oil industry. The research integrates both theoretical and empirical foundations. The population for this study includes industry experts and senior managers in the downstream oil and gas contracting sector. The sample was selected using purposive and snowball sampling methods, targeting key stakeholders with relevant expertise. The sample size was determined by theoretical saturation. In the first phase, a meta-synthesis approach was employed to identify theoretical components using credible academic sources. In the second phase, empirical data were collected through semi-structured interviews with 12 senior industry experts. Data were analyzed using open, axial, and theoretical coding in MAXQDA software. The final phase involved integrating findings from both phases through axial coding to construct a cohesive, multi-layered grounded theory model. This model identifies strategic alliance risks as the central phenomenon and categorizes causal, contextual, and intervening factors, along with mitigation strategies and resulting consequences. Excel and MAXQDA were used for analysis across all stages.
Results and Discussion: In this study, a multiple grounded theory model for managing strategic partnership risks in Iran's downstream oil industry was developed by combining both empirical and theoretical approaches. The model consists of six key components in both domains: strategic partnership risks as the central phenomenon, causal factors that lead to the emergence of these risks, contextual factors influencing these risks, intervening factors that either mitigate or exacerbate the risks, strategies to overcome the risks, and finally, the consequences of improper management of these risks.
In the first phase of the research, open coding concepts related to each component of the model were extracted. A total of 240 open coding concepts were identified from valid scientific sources, each specifically related to the components of the model, including the central phenomenon, causal conditions, and other model elements.
In the second phase, a team of senior managers from Iran's oil industry, responsible for decision-making in strategic partnerships within contractor consortia, was selected as experts. From an initial 131 empirical open codes, 73 final empirical open codes were selected after expert review and filtering, and these codes were subsequently analyzed. In the third phase, the axial coding process resulted in the identification of five theoretical and five empirical subcategories, with four common categories identified as "shared risks." In the causal conditions section, seven theoretical and seven empirical subcategories were identified, with four overlapping categories, including "managerial," "relational," "human resources," "legal," and "cultural" issues. In the contextual conditions section, seven theoretical and four empirical subcategories were determined, with three common subcategories of "economic instability," "legal weakness," and "infrastructure weakness." In the intervening factors section, three theoretical and five empirical subcategories were identified, with two common subcategories, "company characteristics" and "environmental factors." The theoretical and empirical strategies to overcome strategic partnership risks were also categorized into four subcategories, with three common categories: "risk management and planning," "strengthening cooperation and infrastructure," and "improving resources and infrastructure." The similarities and distinctions between the theoretical and empirical findings were visually represented. Finally, the theory was enriched by linking the main categories—central phenomenon, causal conditions, contextual conditions, intervening factors, strategies, and consequences—resulting in a comprehensive narrative of the multiple grounded theories.
Conclusion: The proposed model presents both practical and theoretical contributions, with a distinct methodological approach that enhances its credibility and applicability. From a practical standpoint, it equips managers and policymakers with the tools needed to improve decision-making, optimize project performance, and reduce risks in strategic partnerships within the oil industry. By systematically identifying and analyzing potential risks, the model fosters more effective mitigation strategies, contributing to the alignment of projects with broader economic and operational goals.
On the theoretical front, the study advances the understanding of risk management in strategic partnerships by offering a comprehensive framework for addressing associated risks. It integrates theoretical insights with empirical findings, identifying key causal, contextual, and intervening factors that enrich the existing literature and provide a robust foundation for future research.
One of the significant strengths of this study lies in its methodological approach, which sets it apart from existing literature. The research offers a clear, replicable process for multi-grounded theory modeling, ensuring the results' validity. In phase one, concept identification and coding followed strict meta-synthesis principles, utilizing credible sources. In phase two, interviews were conducted with senior managers from Iran’s downstream oil industry, conducted by a researcher deeply familiar with the field, thus ensuring data reliability. The third phase focused on the transparent integration of theoretical and empirical findings, preserving the integrity of the research. These methodological innovations improve the study's robustness and ensure the model’s broader applicability across various industries and regions.