International political risk management: a review and decision-making framework Open Access

International political risk (IPR) represents a multidimensional phenomenon in which political uncertainties cascade through the interconnected operational, strategic and financial architecture of multinational enterprises (MNEs) (Bremmer and Keat, 2010; Dandage et al., 2019; John and Lawton, 2018; Prakash and Luther, 1986; Rice and Zegart, 2018; Robock, 1971). Defined as measurable uncertainty arising from political dynamics, IPR significantly influences foreign exchange volatility (Filippou et al., 2018), disrupts supply chains (Manuj and Mentzer, 2008), constrains operations through regulatory and policy shifts (Kobrin, 1979; Li and Moosa, 2015) and exposes firms to reputational challenges (Aula, 2010; Parker and Lambrechts, 2020; Rice and Zegart, 2018). Its reach extends across firms of different sizes (Kling et al., 2023; Reddy and Naik, 2011) and ownership structures, including private, state-owned and family-controlled enterprises (Amighini et al., 2013; Cannizzaro and Weiner, 2018; Gómez-Mejía et al., 2024; Jiménez, 2010; Llanos-Contreras et al., 2021). IPR also shapes international investment patterns, influencing both foreign direct investment (FDI) decisions (Aharoni, 1966; Bussy and Zheng, 2023) and foreign portfolio investment (FPI) flows (Durnev et al., 2012).

Despite this broad relevance, the integration of political risk into strategic decision-making remains conceptually fragmented. Although long-standing International Business (IB) theories, including transaction cost economics (Coase, 1937; Williamson, 1981), the Ownership Location – Internalization (OLI) paradigm (Dunning, 1958, 1980) and the Uppsala model (Johanson and Vahlne, 1977), explain why firms internationalize and how they build experiential knowledge, they provide limited guidance on how MNEs systematically manage political risk. Much of the existing international political risk management (IPRM) literature still emphasizes defensive responses such as avoidance and mitigation (Figueira-de-Lemos et al., 2011), rather than structured approaches that assess uncertainty, prioritize exposures and support strategic choice. In contrast, research in finance conceptualizes political risk in explicitly probabilistic and decision-oriented terms, emphasizing modeling, pricing and optimization (Cosset and Suret, 1995; Erb et al., 1995; Filippou et al., 2018). This highlights a central gap: political risk in IB research has not been consistently framed as a decision problem that firms can structure and manage systematically.

Earlier contributions recognized the strategic significance of political risk and its effects on organizational behavior and performance (Boddewyn, 1988; Fitzpatrick, 1983; Kobrin, 1979; Robock, 1971; Root, 1968). More recent work acknowledges the dynamic and context-specific nature of political risk, underscoring the need for adaptive, iterative approaches that reflect changing domestic and geopolitical environments (De Villa et al., 2025; Hartwell and Devinney, 2021; Sun, Doh et al., 2021). However, this growing body of research remains analytically dispersed, without a unifying framework that clarifies how firms can structure political risk, evaluate uncertainty and select appropriate responses across different institutional levels.

To address this gap, we pose the following research question:

This question highlights the need for a coherent conceptual architecture that integrates political risk identification, assessment and response within a structured decision-making system.

The paper makes two main contributions. First, it reconceptualizes IPRM through the combined lenses of Decision Theory (DT) and Risk Management (RM) concepts. DT clarifies how decision-makers frame problems, encode uncertainty and evaluate tradeoffs, while RM provides sequential routines – capability-building, risk identification, risk assessment and strategic response – that organizations can embed in their processes. Together, they shift IPRM from a reactive set of practices toward an iterative, evidence-based decision system. Second, drawing on a hybrid review of 83 peer-reviewed studies, the paper develops a multilevel framework that maps these decision stages onto macro (home-host institutional context), meso (industry and regulatory structures) and micro (firm and managerial) environments. This framework integrates descriptive and predictive insights and highlights opportunities for more prescriptive and optimization-oriented approaches.

The review also underscores that firms’ political risk responses encompass a wide repertoire of market and nonmarket strategies, including entry-mode adjustments, supply-chain and product configuration, political alignment, lobbying and portfolio optimization (Jiménez, 2010; Liou et al., 2021; Liu et al., 2022; Charpin et al., 2021; Cosset and Suret, 1995). This diversity reinforces the need for an integrated multistage approach that links institutional conditions, managerial perceptions and strategic choice.

The remainder of the paper proceeds as follows. Section 2 develops the conceptual and decision-analytic foundations of IPRM. Section 3 presents the methodological design, bibliometric analysis and narrative synthesis that underpin the derivation of the multistage, multilevel framework. Section 4 outlines the future research agenda and Section 5 concludes with theoretical and managerial implications.

IPR is a multidimensional construct arising from the interaction of political actors, institutions and regulatory systems. It refers to the possibility that political decisions or events affect the profitability, feasibility or continuity of foreign investments, whether through direct financial losses or through the disruption of expected returns (Bremmer and Keat, 2010; Kobrin, 1979; Lawton et al., 2014; Simon, 1984). Unlike economic risks, which stem largely from market conditions, IPR risks arise from political processes such as expropriation, nationalization, regulatory intervention, policy instability and shifts in enforcement practices. More recent work highlights the growing influence of supranational bodies and nongovernmental actors, expanding the sources of political uncertainty beyond the state itself (Albino-Pimentel et al., 2018; Cuervo‐Cazurra et al., 2023; Hartmann et al., 2022).

Building on classical distinctions between risk and uncertainty (Keynes, 1921; Knight, 1921; O’Donnell, 2021) and probabilistic approaches that define risk as a function of likelihood and consequence (Kaplan and Garrick, 1981; Kolmogorov, 1933), this paper conceptualizes IPR as measurable uncertainty of political origin. This framing enables systematic decomposition into scenarios, probabilities and outcomes relevant for firm decision-making. It also supports integrating political risk into structured analytical frameworks rather than treating it as an exogenous or inherently opaque phenomenon.

Although the primary focus of IPRM is the host-country political environment, external political dynamics increasingly shape firm exposure. Geopolitical tensions, rivalry among major powers, digital sovereignty initiatives and cross-border regulatory shifts can affect domestic institutions, altering the risk landscape for foreign firms (Ciravegna et al., 2023; Lawton et al., 2023; Tonn Goulart Moura et al., 2025; De Villa, 2023). These developments are acknowledged in this review, where they influence institutional quality, bilateral relations, tariff regimes or political animosity (Bilgili et al., 2023; Liou et al., 2021; Steinbach, 2023; Sun and Liu, 2019; Yoon et al., 2021), while still keeping the analytical focus on IPR as experienced within host-country environments.

IPR spans multiple levels of analysis. At the macro level, national institutions, governance characteristics and host relations shape the political context for international activity. At the meso level, industry-specific regulations, sectoral oversight, technology regimes and collective actors influence the nature and severity of political risks. Ultimately, it is at the micro level – within the firm – that political signals are interpreted, filtered and translated into specific assessments and strategic responses. Managerial perceptions, organizational capabilities and internal processes determine how risk is understood and acted upon.

Recognizing this multilevel structure underscores the need for an integrated approach that links structural political conditions to firm-level decision behavior. It also provides the conceptual foundation for introducing the decision-theoretic and risk-management principles that guide firms in identifying, assessing and responding to political risk. These principles are discussed in the following subsection.

IPRM is grounded here in the complementary logics of DT and structured RM. DT distinguishes normative, descriptive and prescriptive approaches and organizes decision processes into three linked phases: problem structuring, evaluation and choice (Raiffa et al., 1988; Keeney and Raiffa, 1993; French et al., 2009). In the structuring phase, decision-makers define objectives, alternatives and constraints. In the evaluation phase, they assess uncertainty and potential consequences. In the choice phase, they compare options and select strategies that align with their preferences and tradeoffs. Risk, in this context, is conceptualized as the joint consideration of likelihood and impact (Kaplan and Garrick, 1981).

Behavioral research shows that managerial assessments of uncertainty deviate from purely rational or statistical models. Perceptions, heuristics and cognitive biases systematically influence how probabilities and outcomes are interpreted (Kahneman and Tversky, 1979; March and Shapira, 1987; Simon, 1955). IB research reinforces the importance of these behavioral dynamics by documenting how experience, cognition and preference heterogeneity shape location choice, entry mode and other decisions under uncertainty (Buckley et al., 2007; Werner et al., 1996; Guercini and Milanesi, 2022; Kocoglu and Mithani, 2024; Ambos et al., 2020).

RM translates these decision principles into organizational routines. Standard frameworks emphasize capability building, risk identification, risk assessment and risk response, supported by monitoring and iterative learning (Leitch, 2010; Aven, 2015). Two constructs are central to political risk. First, risk perception, which captures how managers interpret political signals and explains strategic variation among firms facing similar environments (Buckley et al., 2007; Werner et al., 1996; Guercini and Milanesi, 2022; Kocoglu and Mithani, 2024; Ambos et al., 2020). Second, risk appetite/tolerance, which specifies the degree of uncertainty a firm is willing or able to accept in pursuit of its objectives (Aven, 2015).

Conditional on assessed exposure and organizational appetite, RM outlines four canonical treatments: avoid, reduce/mitigate, transfer/share or accept (Hopkin, 2018; Leitch, 2010). These alternatives mirror DT’s optimization logic by comparing expected performance outcomes under different courses of action.

Bringing DT and RM together positions IPRM as a structured decision system, not an ad hoc response to political shocks. Firms first structure the decision problem (clarifying objectives, alternatives and constraints), then evaluate exposure (linking political drivers to likelihood and impact) and finally choose among market and nonmarket strategies consistent with performance goals (Keeney and Raiffa, 1993; French et al., 2009). This process is iterative: outcomes feed back into learning and capability-building, echoing the experiential, knowledge-based logic of the internationalization process (Johanson and Vahlne, 1977; Figueira-de-Lemos, Johanson and Vahlne, 2011).

Figure 1 summarizes this conceptual foundation and links it to macro-, meso- and micro-level contexts. Macrolevel political institutions, mesolevel industry structures and microlevel managerial processes provide the backdrop against which RM routines and DT phases interact. The figure also captures feedback loops, emphasizing iterative learning, which is essential for adapting political risk capabilities over time. This integrated decision-analytic foundation underpins the later-staged, multilevel framework and anchors the transition from conceptual grounding to methodological and empirical analysis.

Figure 1, therefore, serves as the conceptual anchor for the review that follows. It informs both the design of the search strategy and the classification of studies by decision stage and level of analysis, providing a consistent lens through which to interpret the bibliometric mapping and narrative synthesis.

This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page et al., 2021), ensuring transparency and replicability throughout the selection process (Liberati et al., 2009). The PRISMA flow diagram summarizing the screening and selection stages is presented in Figure 2.

We implemented a structured, multilayered search strategy, illustrated in Figure 3, informed by Stornelli et al. (2021). The query design incorporated four conceptual domains central to the analytical framing of this study:

1. IB;

2. political risk;

3. risk management; and

4. decision-making.

Keywords and relevant synonyms for each domain were combined to achieve both broad coverage and conceptual focus.

The conceptual dimensions outlined in Figure 1 directly informed the multi-layer search strategy in Figure 3, ensuring alignment between the theoretical framing of IPRM and the empirical identification of relevant studies. The search was conducted across Scopus and Web of Science and was restricted to English-language, peer-reviewed journal articles published between January 1, 1984 and December 31, 2024. The initial search yielded 300 articles (119 from Scopus and 181 from Web of Science). An additional two articles were identified through citation cross-referencing, bringing the preliminary data set to 302 articles.

Duplicate removal was performed using the Bibliometrix R package (Aria and Cuccurullo, 2017), resulting in the elimination of 53 records. The remaining articles were screened through a two-stage eligibility process. First, studies were assessed for relevance to management, strategy, economics, decision sciences and the political risk context defined in Section 2; 134 articles were excluded for insufficient topical relevance. Second, to ensure quality, only articles published in journals listed in the Association of Business Schools guide were retained; 32 articles were excluded at this stage. The final data set comprises 83 high-quality, peer-reviewed articles spanning four decades of research.

Following the search and screening process, we adopted a hybrid methodological design that integrates quantitative bibliometric techniques with qualitative narrative synthesis (Beugelsdijk and Bird, 2025; Marzi et al., 2025; Paul and Criado, 2020; Snyder, 2019). This dual-method approach, illustrated in Figure 4, supports both quantitative mapping and conceptual integration aligned with DT and RM.

The hybrid design proceeds in two steps:

1. Quantitative bibliometric analysis, combining descriptive statistics and factorial clustering, to map the intellectual and thematic structure of IPRM research and identify key thematic concentrations.

2. Qualitative narrative synthesis, using DT as the primary analytical lens and RM as a complementary framework, to interpret the clusters and classify studies by decision-making stage. This step links the bibliometric evidence to the staged, multilevel framework developed in Section 5 and directly supports the objective of operationalizing IPRM as a structured decision-making process.

Bibliometric analysis helps visualize the intellectual structure and evolution of a research domain and fosters theory development by identifying core themes and gaps (Chen, 2017; Small, 1997). Our analysis used the Bibliometrix R package (Aria and Cuccurullo, 2017) and combined descriptive and factorial clustering analysis.

Descriptive analysis reveals substantial growth in IPRM research activity since 2008, coinciding with major global disruptions such as the 2008 financial crisis, the COVID-19 pandemic and recent geopolitical events, including the Russia–Ukraine conflict and tariff wars. Annual publication trends are presented in Figure 5.

Further analysis shows a wide dispersion of IPRM-related publications across leading IB, strategy and related fields, underscoring the interdisciplinary appeal of political risk and growing attention to its financial and management implications. Journal rankings associated with the core publications are summarized in Figure 6.

To examine the conceptual structure of the field, we conducted factorial analysis using Multiple Correspondence Analysis (MCA) complemented by K-means clustering (Cuccurullo et al., 2016). MCA systematically identifies clusters that represent the conceptual structure of IPRM research and highlights major thematic intersections across the literature. The analysis revealed three distinct clusters, shown in Figure 7.

In Figure 7, the axes represent the first two MCA dimensions, which capture the highest proportion of variance in the co-occurrence of keywords across studies. The percentages indicate the share of total inertia explained by each dimension. These dimensions were identified inductively through MCA but interpreted deductively using the DT-RM framework in Figure 1, which guided the substantive labeling of clusters.

Cluster 1 – Foundational risk determinants and assessment (Red): This cluster centers on core themes such as political risk, foreign subsidiaries, institutions and risk assessment. It captures research that examines how external and institutional determinants – such as governance quality, host-country conditions and institutional distance – influence MNE decision-making. These studies align closely with the probabilistic phase of DT and the risk identification and assessment stages in RM frameworks. By quantifying uncertainty and identifying moderators, this body of work contributes to understanding how firms assess the likelihood and potential impact of political risk, forming the empirical backbone for modeling risk in structured IPRM.

Cluster 2 – Strategic responses and organizational decision-making (Blue): This cluster focuses on firm-level strategies, performance outcomes, managerial experience and cross-cultural dynamics. It reflects a microlevel orientation that explores how internal capabilities and strategic choices (e.g. entry mode, expansion or retrenchment, conflict resolution) shape firm responses to IPR. Conceptually, it aligns with the optimization phase in DT, where firms choose between alternatives to maximize utility, and with the strategic choice stage in RM, where responses are crafted based on risk appetite and goals. It also illustrates how managerial cognition and organizational learning shape strategic adaptation under uncertainty.

Cluster 3 – Business environment and prescriptive risk optimization (Green): This smaller but distinctive cluster extends political risk research into the broader business and financial environment. It reflects a shift from descriptive assessments toward prescriptive and optimization-based approaches, where political risk is treated as a variable to be quantified, priced and strategically managed. These studies emphasize how firms and investors integrate political risk into portfolio design, financing strategies and long-term value creation, including environmental and Environmental – Social – Governance (ESG) considerations. Conceptually, this cluster corresponds to early contextualization and capability-building stages in RM and to the optimization phase of DT, highlighting the transition from risk avoidance to proactive, data-driven decision support in IPRM.

Together, these clusters delineate the empirical architecture of IPRM research. They collectively trace a decision-making trajectory, progressing from contextual framing to assessment and strategic response. This sequence mirrors the deterministic, probabilistic and optimization phases of DT outlined in Section 2, as well as the cyclical logic of RM frameworks: Cluster 1 reflects risk identification and assessment; Cluster 2 corresponds to strategic choice and optimization; and Cluster 3 links early-stage contextualization and capability-building to optimization strategies. In doing so, the factorial results provide an empirical bridge between the theoretical premises of DT and RM and the integrative narrative synthesis that follows.

While bibliometric analysis outlined broad divisions and clusters, narrative synthesis enabled more fine-grained thematic integration and differentiation (Eduardsen and Marinova, 2020; Ferasso et al., 2018). Narrative synthesis is widely used in management research to summarize findings under thematic headings and to accommodate studies using different research designs, including both qualitative and quantitative work (Briner and Denyer, 2012; Dixon-Woods et al., 2005).

Building on the DT and RM foundations established in Section 2 and on the empirical clustering patterns described above, the narrative synthesis translates these logics into an integrated framework through a structured coding of the reviewed studies. Each article was examined along predefined analytical dimensions – level of analysis, IPRM stage, focal element, theoretical lens, method and decision orientation – as documented in  Appendix. This framework-guided synthesis reveals that the emergent themes – capability building, identification, assessment and strategic choice – correspond systematically to specific DT phases and RM cycles, clarifying how existing research implicitly structures IPRM as a staged decision-making process.

The resulting framework consists of three primary phases, plus an overarching capability-building component (as outlined in Figure 8):

• a risk identification or deterministic phase, which involves systematic identification of political risks and assessment of MNE capabilities;

• a risk assessment or probabilistic phase, where MNEs evaluate the probability and potential impact of these risks in line with their risk appetite and goals; and

• a strategic choice or optimization phase, where MNEs develop strategies to avoid, mitigate, transfer/hedge or leverage risks as opportunities.

We also incorporate an initial, but continuous, capability-building stage and explicit outcome and learning loops, in which performance, resilience and survival metrics feedback to update capabilities and decision thresholds. Figure 8 maps DT phases to RM processes and positions IPRM as an iterative decision-making system. This mapping represents a systematic alignment between DT logic and RM practice in IPRM research.

Recent IB literature has emphasized the value of a multilevel approach to political and geopolitical risk assessment (De Villa, 2023). Consistent with this, we conceptualize IPRM as a structured decision-making process that unfolds across macro (home–host country), meso (industry and regulatory) and micro (firm-level) environments. This multilevel view supports a more granular understanding of how MNEs identify, perceive, assess and respond to IPR^[1].

Figure 8 presents IPRM as a staged decision process across the Macro, Meso and Micro levels. Each stage shows inputs (signals, priors, capabilities), decision rules (e.g. expected utility, value-of-information thresholds, risk appetite) and RM responses (avoid, mitigate, transfer/hedge, accept, leverage). Cross-level constraints shape feasible actions, while monitoring triggers updating and learning loops that feed back into earlier stages.

As outlined in the  Appendix and expanded below, we classified the reviewed articles and their topics into four key stages, each with specific foundational elements:

1. Capability building stage: multinational configuration, institutionalization of political risk assessment (IPRA), political capabilities and nonmarket strategy (NMS) and tools and frameworks.

2. Identification stage: political risk and uncertainty definitions, risk factors and dimensions.

3. Assessment stage: macro- and micro-level determinants and moderators; and

4. Strategic choice stage: target choices and market and nonmarket strategies.

From a methodological standpoint, quantitative approaches remain dominant, with 45 articles (54%) using statistical or econometric methods, followed by 29 qualitative studies (35%) and nine mixed-method designs (11%). Overall, the corpus is predominantly predictive rather than prescriptive, as most studies focus on explaining or forecasting rather than optimizing decisions. This imbalance further motivates the decision-analytic framing adopted in this paper and underscores the need for prescriptive contributions in future IPRM research.

The capability-building stage is treated as a foundational and ongoing element of the IPRM decision-making process. It encompasses the full toolkit – processes, tools, knowledge and people – necessary to manage IPR effectively from a firm-level perspective.

A first set of studies examines whether and how MNEs manage IPR explicitly, often referred to as the IPRA (Alon et al., 2006; Hashmi and Guvenli, 1992; Al Khattab et al., 2008; Noordin and Hazir, 2006). Interviews and case studies are typically used to assess whether organizations have ad hoc teams and tools for managing different IPR factors. Many studies conclude that risk assessments are often conducted under particular conditions (e.g. large investments or highly exposed markets), but are not fully institutionalized, except in specific industries or due to sectoral risks (Giambona et al., 2017). Stephens and Apasu (1986) analyze the optimal international configuration for successful internationalization with lower risk, suggesting the establishment of business subunits.

A second line of work focuses on political capabilities and NMS. Early studies analyze efforts to improve organization–environment fit through interorganizational ties and lobbying (Iankova and Katz, 2003). More quantitative contributions investigate how political capabilities and experience (learning and imprinting) influence location choice in the electric power generation industry (Holburn and Zelner, 2010). Other articles examine corporate political activity and NMS as part of the IPRM toolkit for achieving environmental fit (Moazzin, 2020; Schnyder and Sallai, 2020; De Villa et al., 2019). More recent post-pandemic work emphasizes political animosity (country dissimilarity), tariff intensity and protectionism and investigates how firms react, adjust political behavior or strengthen legitimacy and resilience (Darendeli et al., 2021; Liou et al., 2023; Sun and Liu, 2019). Stevens and Newenham‐Kahindi (2017) highlight the role of legitimacy spillovers, showing that legitimacy judgments formed in one country can spill over to other host countries and significantly affect a firm’s IPR exposure. This broadens the scope of IPR across multiple jurisdictions. Political capabilities are thus dynamic; as the environment evolves, MNEs must adapt. The toolkit typically begins with proactive, preconceived strategies but is adjusted throughout the IPRM process, during both assessment and implementation of more proactive responses.

A third element in this stage highlights the importance of analytical and statistical tools for IPRM. This literature begins with complexity and nonlinear systems (Martinez et al., 1999), advances through RM expertise (Dandage et al., 2019) and increasingly incorporates data analytics, machine learning and artificial intelligence models (Hemphill et al., 2021; Rios-Morales et al., 2009).

At the identification stage, reviewed articles focus on the nature and definition of IPR, acknowledging its complexity and multidimensionality (Prakash and Luther, 1986; Simon, 1984). IPR is studied from multiple perspectives. From a macro perspective, political actions, constitutional changes (Young et al., 2014) and political uncertainty can affect a country’s economic growth (Henisz, 2000). At the industry level, political risk is analyzed in relation to sector-specific characteristics and regulatory regimes (Hemphill et al., 2021; Laynesa Alcantara and Mitsuhashi, 2013; Moazzin, 2020; Skovoroda et al., 2019). From the firm perspective, research examines how MNEs experience and interpret political disruptions (De Villa et al., 2014; Donzé and Kurosawa, 2013; Kling et al., 2023).

Recently, new perspectives on postpandemic IPR suggest that we should include not only institutional-level conditions but also the roles of individual political actors and authorities, reflecting the rise of authoritarianism and protectionism (Hartwell and Devinney, 2021). Cuervo‐Cazurra et al. (2023) propose analyzing host-country politics as a process, focusing on how quickly regulations can be created and implemented. Populist regimes are also shown to exacerbate IPR by introducing unpredictable policy shifts, particularly where populism dominates political discourse (Blake et al., 2022).

The assessment stage is one of the “motor themes” identified in the red cluster and covers macro-, firm- and managerial-level determinants and moderators of IPR and its effects.

At the macro level, IPR is studied as a determinant of FDI and its effect on inward FDI flows (Lanciotti and Lluch, 2015; Sun and Liu, 2019; Young et al., 2014). Several factors can mitigate perceived or measurable IPR for MNEs, including home–country institutional quality, diplomatic partnerships, bilateral relationships and GDP growth (Bilgili et al., 2023; Sun and Liu, 2019; Yoon et al., 2021). Conversely, factors such as political animosity (dissimilarities and disagreements between countries), tariff intensity or protectionism, default risk, demand uncertainty and competition can increase IPR (Liou et al., 2021; Sun and Liu, 2019).

At the firm level, moderators that reduce perceived or measurable IPR include flexibility (real options reasoning), state-owned enterprise transparency, networks, external (host-country) supplier relations, legitimacy (e.g. cross-listing and social projects) and prior experience (Amighini et al., 2013; Cannizzaro and Weiner, 2018; Charpin et al., 2021; Fisch, 2011; Lee et al., 2020). Factors that increase perceived or measurable IPR include irreversibility (real options), reliance on internal (home–country) suppliers, geographical distance, family firm status and strong economic, political and social dependency (Hennart and Larimo, 1998; Jimenez et al., 2019; Laynesa Alcantara and Mitsuhashi, 2013; Llanos-Contreras et al., 2021; Sawant et al., 2021). Most studies find an adverse effect of IPR when it is treated as an exogenous variable. However, research on firms’ risk perception (risk appetite) shows that firms taking on more IPR sometimes achieve better financial performance, consistent with prospect theory and portfolio diversification theory (Jiménez and Delgado-García, 2012). Family firms (FF), for example, typically exhibit greater political risk aversion (Jimenez et al., 2019) and distinct strategic behaviors, often providing enhanced employment security to protect socioemotional wealth (Gómez-Mejía et al., 2024). Institutional voids in high-risk environments can amplify the benefits of firm-specific resources, leading to unique IPRM strategies compared with non-family-controlled MNEs.

At the managerial or top management team level, perceived IPR tends to increase when managers hold share options (Benischke et al., 2022; Datta et al., 2015), are founding members of FF (Llanos-Contreras et al., 2021), rely heavily on heuristics or biases, face cultural distance or exhibit risk aversion (Ambos et al., 2020b). Perceived IPR decreases when managers’ shares are restricted, they have relevant experience, maintain a social contract with employees, display individual political embeddedness, show ethical leadership and uphold psychological contracts (Buckley et al., 2016; Sawant et al., 2021; Turi and Sarfraz, 2023). Considering domestic uncertainty (home–country conditions) as a reference point can also reduce relative perceptions of host-country political risk (Yasuda and Kotabe, 2021).

A further level of analysis concerns the individual investor in the context of FPI. Durnev et al. (2012) note that earlier academic discussions treated FDI and FPI as distinct categories, but this distinction has become more fluid as investors increasingly incorporate political risk into both. ESG practices have also been identified as a moderator of IPR in private equity investments (Donahue and Timmerman, 2021).

In the strategic choice stage, MNEs translate assessed IPR into concrete moves – location and entry-mode choices, scaling decisions and combinations of market and nonmarket actions. Evidence is often fragmented, treating these decisions as isolated outcomes; in our synthesis, this stage is aligned with the blue cluster.

At a macro level, studies examine the effects of IPR on FDI flows into and out of countries, alongside diplomatic strategies to boost FDI outflows, as in the case of China (Sun and Liu, 2019). From an industry perspective, research analyzes the impact of IPR on likely petroleum investment locations and on the transparency of reserve acquisition operations (Cannizzaro and Weiner, 2018).

At the MNE level, commonly analyzed decisions (constituting a large proportion of the articles) include location choice and entry mode. Studies also explore FDI in natural resource locations, expansion or reduction of subsidiary investments and their scale and prescriptive approaches to optimal capital structure and financing sources for internationalization (Charpin et al., 2021; Eom and Lee, 1987; Fisch, 2011; Lee et al., 2020). Another group of articles examines market strategies adopted in response to IPR (Fan and Xiao, 2023), including the scope of internationalization or geographical diversification (Jiménez, 2010), product standardization versus diversification (Omar and Porter, 2011), local embeddedness and vertical integration (Song, 2022). Subsidiary intrafirm trade integration and strategic supply chain operations are also examined as responses to political risk (Charpin et al., 2021; Lee et al., 2020).

Aligned with NMS, some studies focus on political responses such as lobbying expenditures and strategies based on exit, voice or loyalty (Liou et al., 2023; Liu et al., 2022). Political affinity between MNEs and host governments is shown to play a crucial role in managing political risks postacquisition (Hasija et al., 2020). MNEs that align their operations with host-country political dynamics appear better positioned to mitigate regulatory risks and enhance the long-term stability of their investments.

From a portfolio and financial perspective, prescriptive analyses include optimizing currency and equity portfolios subject to IPR and examining private equity investors’ strategies in less developed countries (Cosset and Suret, 1995; Donahue and Timmerman, 2021; Erb et al., 1996; Filippou et al., 2018). These strategies typically aim to optimize portfolio returns for a given level of risk. Only a limited number of articles examine the effects of IPR on outcomes such as financial performance (Barbopoulos et al., 2014; Jiménez et al., 2015; Kling et al., 2023). More recent studies explore the impact of IPR on resilience (e.g. changes in profits after shocks), subsidiary survival (Darendeli et al., 2021) and project success (Dandage et al., 2019).

Taken together, these four stages – capability building, identification, assessment and strategic choice – form the analytical structure of IPRM and provide a forward-looking roadmap for research. The following section builds on this multistage, multilevel framework to outline a research agenda for future work.

Building on the multistage, multilevel framework developed through the bibliometric and narrative synthesis, this agenda outlines directions for future research across the four stages of IPRM (capability building, risk identification, risk assessment and strategic choice) anchored in DT and RM principles. The core aim is to deepen understanding of how MNEs structure, evaluate and optimize IPRM decisions under dynamic and often turbulent political conditions.

Future research should examine how MNEs institutionalize political risk assessment within organizational routines, governance systems and decision-support architectures. This includes analyzing when and how IPRA moves from ad hoc practice to embedded organizational capability and how it interacts with multinational configuration and internal control systems. DT’s prescriptive dimension and RM’s context-setting principles offer a basis for studying the design of tools, metrics, and analytics for political risk evaluation. Further work could investigate how MNEs build and deploy political capabilities, such as lobbying, coalition formation and stakeholder engagement, as part of broader NMS portfolios. Integrating big data, machine learning and artificial intelligence (AI)-enhanced decision models into these capabilities is a natural extension, particularly to explore how firms move from predictive to explicitly prescriptive IPRM.

At the identification stage, there is scope to refine conceptualizations and operationalizations of IPR across macro, meso and micro levels. Research should more clearly map how specific risk sources, such as regulatory volatility, political animosity, legitimacy shocks or populist policy swings, interact with firm-level exposure, configuration and managerial risk appetite. DT framing can help unpack how managers perceive, frame and prioritize different political risks. RM frameworks can guide the development of context-sensitive typologies that distinguish between transient shocks and structural shifts. Better-integrated measurement strategies, explicitly tied to decision needs, would strengthen both construct clarity and empirical comparability.

At the assessment stage, methodological innovation remains a priority. Future research should combine scenario analysis, simulation and Bayesian or other stochastic modeling to better capture uncertainty, feedback effects and interdependencies among macro, meso and micro moderators. This approach would align empirical modeling more closely with the probabilistic phase of DT and the evaluation stage of RM. Comparative designs – examining different home–host configurations, industries or ownership types (e.g. family versus non-FF) – could test how political capabilities, institutional experience and reference points (e.g. domestic uncertainty) influence the gap between perceived and actual exposure. There is also potential to incorporate ESG and legitimacy variables more explicitly into assessment models, treating them as both moderators and outcomes of IPRM.

The strategic choice stage is the least developed in the current literature but offers the most significant potential for integrating DT with IB and NMS. Future research could apply prescriptive analytics and optimization approaches to model tradeoffs between risk and return, market and nonmarket strategies and short-term mitigation versus long-term adaptation. Extending widely used prescriptive models in finance (e.g. portfolio optimization and real options analysis) to international strategy decisions, such as entry mode, location portfolios, supply chain configuration and political strategy design, would help bridge conceptual and practical gaps. Multi-objective optimization that incorporates resilience, survival and legitimacy alongside financial performance would be particularly valuable.

Beyond stage-specific questions, several cross-cutting themes merit attention. First, future studies should broaden empirical focus beyond traditional developed-market MNEs to include emerging-market MNEs and financial investors originating from politically unstable environments. Second, underexplored sectors such as services, multinational banking and fintech warrant more systematic analysis, given their distinct regulatory and political profiles. Third, scholars should move beyond a narrow emphasis on financial outcomes to examine sustainability, resilience and legitimacy as explicit decision objectives within the IPRM process, linking strategic optimization to broader societal and stakeholder performance.

Taken together, these research directions extend the DT-RM framing from descriptive mapping toward genuinely prescriptive, decision-supportive IPRM and invite work that tests and refines the staged, multilevel framework developed in this review.

This review systematizes IPRM as a structured, multistage and multilevel decision-making process. Synthesizing 83 peer-reviewed studies (1984–2025) through a DT lens and supported by structured RM principles, we consolidate a fragmented body of work and align the core activities of IPRM – capability building, identification, assessment and strategic choice – with DT’s deterministic, probabilistic and optimization phases. By integrating theoretical reasoning with empirical clustering and narrative synthesis, the paper demonstrates how decision logics and risk routines are embedded across the IPRM literature and how they can guide both scholarly analysis and managerial decision-making. Figure 8 summarizes this synthesis by linking decision-theoretic phases, RM cycles and the four empirical stages of IPRM.

The shift we highlight is both conceptual and practical. Rather than treating political risk as a hazard to avoid, we position it as a form of measurable uncertainty that can be systematically identified, assessed, and, in some cases, strategically leveraged. RM provides the procedural foundation (context, assessment, treatment and monitoring), while DT offers the analytical reasoning that connects information, preferences and actionable choices. Together, these foundations recast IPRM as an iterative, optimization-oriented system that incorporates feedback and organizational learning across stages and levels of analysis.

Our synthesis advances IB scholarship in three ways. First, it introduces a clear multilevel perspective – macro (home–host institutional context), meso (industry and regulatory structures) and micro (firm and managerial processes) – clarifying how political structures interact with firm-level agency. Second, it organizes IPRM across four empirically grounded stages that mirror DT and RM logic, thereby bringing coherence to a dispersed literature. Third, it highlights a persistent methodological imbalance: predictive studies dominate, whereas prescriptive and optimization-oriented approaches remain limited. Addressing this gap is essential to developing decision-support tools that can operate under political uncertainty.

For managers, the framework provides a structured framework for embedding political risk into strategic decision-making. It helps practitioners map context-specific drivers, assess likelihood and impact relative to risk appetite and develop coherent portfolios of market and nonmarket strategies to avoid, mitigate or leverage political risk. Applied iteratively, this staged approach supports resilience, strategic coherence and opportunity recognition in volatile environments.

The review also clarifies the scope of IPRM. While our focus is on host-country political risk, we recognize that geopolitical dynamics, such as conflicts, regulatory fragmentation and digital sovereignty, indirectly shape firm-level exposure. These forces primarily operate through macro-level conditioning, influencing domestic political environments and institutional responses.

Finally, this synthesis lays a foundation for future research that builds on the integration of DT-RM. The agenda outlined in the previous section highlights opportunities to test, expand and implement the framework across different industries, institutional settings and decision-making scenarios. By linking theoretical principles with empirical patterns and managerial insights, the review closes the gap between conceptual thinking, analytical findings and practical use. Overall, it presents a consistent, evidence-based and decision-focused perspective that redefines IPRM as a strategic capability that connects what firms encounter, what they perceive and what they ultimately choose to do.