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Asian Business Research Journal 
Vol. 10, No. 9, 113-123, 2025 
ISSN: 2576-6759 
DOI: 10.55220/2576-6759.581 
© 2025 by the author; licensee Eastern Centre of Science and Education, USA 

 
 

 

 
Trade War Threat Perceptions and Strategic Transformation: Adaptive Responses 
and Performance Outcomes in Vietnamese Export-Oriented Enterprises 

 
Le Dung TRUONG 
 

 
 

Vin University, Vietnam. 
Email: truongledung1411@gmail.com  
 

 
Abstract 

This study examines how trade war threat perceptions influence strategic transformation 
processes and subsequent performance outcomes among Vietnamese export-oriented enterprises 
during periods of heightened global trade uncertainty. Drawing upon dynamic capabilities theory 
and institutional theory, the research develops and empirically tests a comprehensive conceptual 
framework linking managerial threat perceptions to strategic adaptability and firm performance 
through mediating mechanisms of organisational learning and resource reconfiguration. Utilising 
a mixed-methods approach combining structural equation modelling (SEM) and fuzzy-set 
qualitative comparative analysis (fsQCA), the study analyses primary data from 384 Vietnamese 
manufacturing firms collected during 2016-2017. The findings reveal that trade war threat 
perceptions significantly enhance strategic adaptability, which subsequently improves financial 
performance through multiple pathways. However, the relationship is moderated by firm size and 
industry characteristics, with larger firms demonstrating superior adaptive capabilities. The 
fsQCA results identify three distinct configurational pathways to high performance, suggesting 
equifinality in strategic responses to trade uncertainties. This research contributes to the strategic 
management literature by elucidating the cognitive and behavioural mechanisms through which 
external threats catalyse organisational transformation, whilst providing practical insights for 
managers navigating volatile trade environments in emerging markets. 

 
Keywords: Dynamic capabilities, Export-oriented firms, Strategic transformation, Trade war perceptions, Vietnam. 

 
1. Introduction 

The escalating frequency of international trade disputes has fundamentally transformed the global economic 
landscape, compelling firms to reassess their strategic orientations and operational frameworks (Buckley et al., 
2017). Contemporary geopolitical tensions, characterised by protectionist policies and retaliatory measures, have 
created unprecedented levels of uncertainty for export-dependent enterprises, particularly those operating from 
emerging market economies (Contractor, 2017). Vietnam, as one of Asia's most dynamic export-oriented 
economies, provides a compelling empirical context for examining how firms perceive and respond to trade war 
threats, given its unique position within global supply chains and its historical experience with economic reforms. 

The strategic management literature has increasingly recognised that organisational responses to external 
shocks are fundamentally shaped by managerial perceptions and cognitive frameworks rather than merely objective 
environmental conditions (Ocasio, 1997). This perceptual dimension becomes particularly salient in contexts of 
trade uncertainty, where the interpretation of threat signals determines the nature and intensity of strategic 
responses (Wernerfelt, 1984). However, existing research has predominantly focused on developed market 
contexts, leaving significant gaps in understanding how firms in emerging economies perceive and adapt to trade-
related threats. 

The theoretical significance of this investigation lies in its integration of cognitive perspectives with dynamic 
capabilities theory to explain strategic transformation processes. Whilst dynamic capabilities theory emphasises 
firms' abilities to sense, seize, and reconfigure resources in response to environmental changes (Teece, 2007), the 
role of managerial perceptions in triggering and directing these capabilities remains underexplored. This study 
addresses this theoretical gap by proposing that threat perceptions serve as catalytic mechanisms that activate 
dynamic capabilities, thereby enabling strategic transformation. 

From a practical standpoint, this research responds to the urgent need for evidence-based insights into how 
export-oriented firms can navigate increasingly volatile trade environments. The findings carry particular 
relevance for emerging market enterprises that often lack the institutional support and resource buffers available to 
their developed market counterparts. By elucidating the mechanisms through which threat perceptions influence 
strategic adaptation and performance outcomes, this study provides actionable knowledge for managers and 
policymakers seeking to enhance firm resilience in uncertain trade environments. 

The empirical contribution of this research stems from its methodological innovation in combining traditional 
covariance-based structural equation modelling with fuzzy-set qualitative comparative analysis (fsQCA). This 

mailto:truongledung1411@gmail.com
https://doi.org/10.55220/2576-6759.581


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mixed-methods approach enables both the testing of causal relationships and the identification of configurational 
pathways to performance, thereby providing a more comprehensive understanding of the complex relationships 
between perceptions, strategies, and outcomes. The Vietnamese context further enhances the study's contribution 
by providing insights into strategic adaptation processes in a rapidly developing economy with strong export 
orientation. 
 

2. Foundational Theories and Literature Review 
2.1. Foundational Theories 
2.1.1. Dynamic Capabilities Theory 

Dynamic capabilities theory, originally conceptualised by Teece et al. (1997), provides a robust theoretical 
foundation for understanding how firms adapt to environmental uncertainties through the deliberate modification 
of their resource bases and organisational routines. The theory posits that firms possess higher-order capabilities 
that enable them to sense environmental changes, seize emerging opportunities, and reconfigure existing resources 
to maintain competitive advantage (Teece, 2007). These dynamic capabilities are particularly crucial in volatile 
environments where traditional competitive advantages may rapidly erode. 

The sensing dimension of dynamic capabilities involves the continuous scanning of technological, market, and 
regulatory environments to identify emerging threats and opportunities (Teece, 2007). In the context of trade 
wars, sensing capabilities enable firms to detect early warning signals of protectionist measures, supply chain 
disruptions, or market access restrictions. However, the effectiveness of sensing capabilities is inherently dependent 
upon managerial attention allocation and interpretive frameworks, suggesting that cognitive factors play a 
fundamental role in dynamic capability deployment (Ocasio, 1997). 

The seizing dimension encompasses firms' abilities to mobilise resources and execute strategic responses to 
environmental changes (Eisenhardt & Martin, 2000). This involves making strategic investments, forming 
alliances, or reconfiguring organisational structures to capitalise on identified opportunities or mitigate perceived 
threats. The effectiveness of seizing capabilities is contingent upon firms' resource endowments, organisational 
flexibility, and decision-making processes (Helfat et al., 2007). 

The reconfiguring dimension involves the continuous transformation of asset bases and organisational 
architectures to maintain evolutionary fitness (Teece, 2007). This encompasses both asset orchestration activities 
and the modification of operational routines to align with new strategic directions. Reconfiguration capabilities are 
particularly relevant in trade war contexts, where firms may need to rapidly restructure supply chains, relocate 
production facilities, or develop new market relationships. 

Despite its theoretical richness, dynamic capabilities theory has been criticised for its tautological tendencies 
and limited attention to the cognitive foundations of capability development (Arend & Bromiley, 2009). This study 
addresses these limitations by explicitly incorporating managerial threat perceptions as antecedents to dynamic 
capability activation, thereby providing a more nuanced understanding of the mechanisms through which 
environmental uncertainty triggers organisational adaptation. 
 

2.1.2. Institutional Theory 
Institutional theory offers complementary insights into how environmental pressures shape organisational 

behaviour and strategic choices (DiMaggio & Powell, 1983). The theory emphasises that firms operate within 
complex institutional environments characterised by formal rules, informal norms, and cognitive frameworks that 
constrain and enable organisational action (Scott, 1995). From an institutional perspective, trade wars represent 
significant institutional shocks that disrupt established regulatory frameworks and create new compliance 
requirements for export-oriented firms. 

The coercive isomorphism mechanism suggests that regulatory pressures and government policies directly 
influence firm behaviour (DiMaggio & Powell, 1983). In trade war contexts, coercive pressures may manifest 
through tariff impositions, export restrictions, or compliance requirements that force firms to modify their 
operational practices. Vietnamese export-oriented firms, for instance, may face coercive pressures to diversify their 
market portfolios or relocate production facilities to circumvent trade barriers. 

Mimetic isomorphism occurs when firms imitate the practices of successful peers in response to environmental 
uncertainty (DiMaggio & Powell, 1983). The uncertainty generated by trade wars may prompt firms to benchmark 
their strategic responses against industry leaders or successful competitors. This mimetic behaviour can lead to the 
convergence of strategic practices within industries, potentially reducing the heterogeneity of competitive 
responses. 

Normative isomorphism stems from professional networks and industry associations that promote particular 
practices or standards (DiMaggio & Powell, 1983). Trade associations, consulting firms, and professional networks 
may disseminate best practices for managing trade war impacts, thereby influencing the strategic choices of 
member firms. The strength of normative pressures may vary across industries and institutional contexts, with 
some sectors exhibiting stronger professional norms than others. 

The institutional perspective highlights the importance of legitimacy in shaping firm responses to 
environmental pressures (Suchman, 1995). Firms must balance efficiency considerations with legitimacy 
requirements when formulating strategic responses to trade wars. This balance may be particularly challenging for 
emerging market firms that operate across multiple institutional contexts with potentially conflicting 
requirements. 
 

2.2. Review of Empirical and Relevant Studies 
2.2.1. Trade War Perceptions and Organisational Responses 

The literature on trade war impacts has predominantly focused on macroeconomic consequences rather than 
firm-level behavioural responses (Amiti et al., 2017). However, emerging research suggests that managerial 
perceptions of trade uncertainty significantly influence strategic decision-making processes and resource allocation 
patterns (Handley & Limão, 2017). Firms operating in trade-intensive sectors demonstrate heightened sensitivity 



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to policy uncertainty, with managers exhibiting increased risk aversion and delayed investment decisions during 
periods of elevated trade tensions (Baker et al., 2016). 

Empirical evidence from various contexts suggests that trade policy uncertainty affects firm behaviour through 
multiple channels. Handley and Limão (2017) demonstrate that reductions in trade policy uncertainty stimulate 
firm entry and investment in export markets, suggesting that uncertainty perceptions directly influence strategic 
commitments. Similarly, Feng et al. (2017) find that Chinese firms reduce their export intensity and diversify their 
market portfolios in response to perceived trade policy risks. 

The cognitive dimension of trade war perceptions has received limited empirical attention, despite its 
theoretical importance. Managerial cognition research suggests that threat perceptions are shaped by individual 
and organisational factors, including prior experience, industry context, and information processing capabilities 
(Kaplan, 2008). Managers with greater international experience may demonstrate enhanced ability to interpret 
trade war signals and formulate appropriate responses, whilst those with limited exposure to trade disruptions may 
exhibit suboptimal decision-making patterns. 
 

2.2.2. Strategic Adaptability and Dynamic Capabilities 
Strategic adaptability, defined as firms' capacity to modify their strategic orientations in response to 

environmental changes, has emerged as a critical determinant of performance in volatile environments (Shimizu & 
Hitt, 2004). The concept encompasses both the speed and effectiveness of strategic adjustments, with more 
adaptable firms demonstrating superior performance outcomes during periods of environmental turbulence 
(Oktemgil & Greenley, 1997). 

Empirical research has identified several antecedents of strategic adaptability, including organisational learning 
capabilities, strategic flexibility, and top management characteristics (Shimizu & Hitt, 2004). Firms with stronger 
learning orientations demonstrate enhanced ability to acquire, assimilate, and apply new knowledge in response to 
environmental changes (Cohen & Levinthal, 1990). Strategic flexibility, encompassing both resource flexibility and 
coordination flexibility, enables firms to rapidly reconfigure their strategic postures without incurring excessive 
switching costs (Sanchez, 1995). 

The relationship between dynamic capabilities and strategic adaptability has been extensively studied, with 
research generally supporting the positive association between capability strength and adaptive performance 
(Eisenhardt & Martin, 2000). However, the mechanisms through which dynamic capabilities enhance adaptability 
remain somewhat unclear, with some studies emphasising the role of organisational routines (Winter, 2003) whilst 
others focus on managerial decision-making processes (Adner & Helfat, 2003). 

 
2.2.3. Performance Outcomes of Strategic Adaptation 

The performance implications of strategic adaptation have been examined across various contextual settings, 
with mixed empirical findings. Some studies report positive relationships between adaptive capabilities and 
performance outcomes, particularly in dynamic environments (Shimizu & Hitt, 2004). However, other research 
suggests that excessive adaptation may be detrimental to performance due to increased coordination costs and 
strategic inconsistency (Miller & Friesen, 1982). 

The contingent nature of adaptation-performance relationships has prompted researchers to examine 
moderating factors that influence these linkages. Environmental dynamism, resource constraints, and industry 
characteristics have all been identified as significant moderators of adaptation-performance relationships (Aragón-
Correa & Sharma, 2003). Firms operating in highly dynamic environments may derive greater benefits from 
adaptive capabilities, whilst those in stable contexts may benefit more from operational efficiency and consistency. 

The measurement of performance outcomes in adaptation studies has varied considerably, with researchers 
employing both financial and non-financial indicators (Venkatraman & Ramanujam, 1986). Financial measures, 
including return on assets, sales growth, and profitability, provide objective assessments of adaptation effectiveness 
but may not capture the full range of benefits derived from strategic flexibility. Non-financial measures, such as 
market position and stakeholder satisfaction, offer complementary insights but may be subject to perceptual biases. 
 

2.3. Proposed Research Model 
Drawing upon the theoretical foundations and empirical insights discussed above, this study proposes a 

comprehensive research model linking trade war threat perceptions to strategic transformation and performance 
outcomes. The model incorporates six primary constructs: trade war threat perceptions, strategic adaptability, 
organisational learning, resource reconfiguration, firm performance, and environmental dynamism as a moderating 
variable. 

Trade war threat perceptions represent managers' subjective assessments of the likelihood and potential impact 
of trade-related disruptions on their firms' operations and performance (Milliken, 1987). This construct captures 
both the perceived probability of trade war escalation and the anticipated magnitude of consequences for firm 
operations. The measurement of threat perceptions draws upon established scales from the strategic management 
literature (Dutton & Jackson, 1987), adapted to reflect trade-specific concerns. 

Strategic adaptability encompasses firms' demonstrated capacity to modify their strategic orientations, resource 
allocations, and operational practices in response to environmental changes (Shimizu & Hitt, 2004). The construct 
incorporates dimensions of strategic flexibility, response speed, and adaptation effectiveness, measured through 
multi-item scales validated in previous research (Oktemgil & Greenley, 1997). Strategic adaptability serves as the 
primary mediating variable linking threat perceptions to performance outcomes. 

Organisational learning captures firms' systematic efforts to acquire, interpret, and apply new knowledge 
relevant to their strategic challenges (Huber, 1991). The construct encompasses both exploitative learning 
activities that refine existing capabilities and explorative learning that develops new competencies (March, 1991). 
Measurement items are adapted from established organisational learning scales, focusing on information 
acquisition, distribution, interpretation, and organisational memory processes. 



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Resource reconfiguration represents firms' deliberate modification of their resource portfolios and asset 
deployment patterns to align with new strategic priorities (Eisenhardt & Martin, 2000). This construct captures 
both tangible resource adjustments, such as facility relocations or supply chain modifications, and intangible 
resource reconfigurations, including capability development and knowledge integration activities (Teece, 2007). 
 

 
Figure 1.  Proposed Research Model. 

 
Firm performance is conceptualised as a multidimensional construct encompassing both financial and 

operational indicators of organisational effectiveness (Venkatraman & Ramanujam, 1986). Financial performance 
measures include return on assets, sales growth, and profit margins, whilst operational performance indicators 
capture market share, customer satisfaction, and operational efficiency metrics. This multidimensional approach 
provides a comprehensive assessment of adaptation effectiveness. 

Environmental dynamism serves as a key moderating variable, capturing the rate of change and 
unpredictability in firms' competitive environments (Dess & Beard, 1984). The construct encompasses 
technological, competitive, and regulatory dynamism dimensions, measured through established scales adapted to 
reflect trade-related uncertainties. Environmental dynamism is expected to strengthen the relationships between 
threat perceptions, strategic adaptation, and performance outcomes. 

The proposed model incorporates several hypothesised relationships based on theoretical logic and empirical 
evidence. First, trade war threat perceptions are expected to positively influence strategic adaptability, as managers 
who perceive greater threats will be more motivated to initiate adaptive responses (Dutton & Jackson, 1987). 
Second, strategic adaptability is hypothesised to enhance firm performance through improved alignment between 
organisational capabilities and environmental requirements (Miles & Snow, 1978). Third, organisational learning 
and resource reconfiguration are proposed as mediating mechanisms linking threat perceptions to strategic 
adaptability, reflecting the process through which firms develop and deploy adaptive capabilities (Teece, 2007). 
Finally, environmental dynamism is expected to moderate these relationships, with stronger effects anticipated in 
more dynamic contexts (Eisenhardt & Martin, 2000). 
 

3. Research Methodology 
3.1. Research Design 

This study employs a quantitative research design utilising cross-sectional survey data to test the proposed 
theoretical model linking trade war threat perceptions to strategic transformation and performance outcomes. The 
research adopts a positivist epistemological stance, emphasising objective measurement and statistical hypothesis 
testing to establish causal relationships among key constructs (Creswell, 2014). The quantitative approach is 
particularly appropriate given the study's focus on testing established theoretical relationships and the need for 
generalisable findings applicable to Vietnamese export-oriented enterprises. 

The research design incorporates both variance-based structural equation modelling (PLS-SEM) and fuzzy-set 
qualitative comparative analysis (fsQCA) to provide comprehensive insights into the complex relationships among 
study variables. This methodological triangulation approach enables both the testing of linear relationships 
through SEM and the identification of configurational pathways to performance through fsQCA, thereby 
addressing potential limitations of single-method approaches (Woodside, 2013). The combination of symmetric 
(SEM) and asymmetric (fsQCA) analytical techniques provides a more nuanced understanding of how different 
combinations of antecedent conditions lead to desired outcomes. 
 

3.2. Data Collection 
Data collection was conducted through a structured survey administered to senior managers of Vietnamese 

export-oriented manufacturing firms during the period from August 2016 to March 2017. This timeframe was 
strategically selected to capture managerial perceptions during a period of heightened global trade uncertainty, 
following the Brexit referendum and preceding major trade policy announcements. The target population 
comprised manufacturing firms with significant export operations, defined as companies deriving at least 25% of 
their revenues from international sales. 

The sampling frame was constructed using the Vietnam Chamber of Commerce and Industry (VCCI) database, 
supplemented by listings from provincial industrial promotion agencies. A stratified random sampling approach 
was employed to ensure adequate representation across industries, firm sizes, and geographical regions. The 
stratification criteria included: (1) industry classification based on two-digit Standard Industrial Classification 
codes, (2) firm size categorised by employee numbers, and (3) geographical location spanning Vietnam's major 
economic regions. 



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Survey instruments were initially developed in English and subsequently translated into Vietnamese using 
back-translation procedures to ensure linguistic equivalence (Brislin, 1970). Pre-testing was conducted with 25 
managers from various industries to assess item clarity, response format appropriateness, and survey completion 
time. Minor modifications were made based on pre-test feedback to enhance item comprehensibility and cultural 
relevance. 

Data collection utilised multiple channels to maximise response rates and sample representativeness. Primary 
collection methods included face-to-face interviews conducted by trained research assistants, telephone interviews 
for geographically dispersed respondents, and online surveys for firms with established internet infrastructure. 
Research assistants received comprehensive training on survey administration protocols, ethical considerations, 
and quality control procedures. 

A total of 1,247 firms were initially contacted, with 612 agreeing to participate in the study. After accounting 
for incomplete responses and data quality issues, the final sample comprised 384 useable questionnaires, 
representing a 30.8% effective response rate. This response rate compares favourably with similar studies in 
emerging market contexts and exceeds recommended thresholds for structural equation modelling analyses (Hair 
et al., 2017). 
 

3.3. Measurement & Validation 
All construct measurements were adapted from established scales with demonstrated reliability and validity in 

previous research contexts. Trade war threat perceptions were measured using a six-item scale adapted from 
Milliken (1987) and Dutton and Jackson (1987), focusing on managers' assessments of trade policy uncertainty and 
potential business impacts. Sample items included "Trade policy changes pose significant threats to our business 
operations" and "Our company faces substantial risks from international trade disputes." 

Strategic adaptability was assessed using an eight-item scale derived from Shimizu and Hitt (2004) and 
Oktemgil and Greenley (1997), capturing firms' demonstrated capacity for strategic adjustment. Representative 
items included "Our company quickly adjusts its strategies in response to market changes" and "We effectively 
modify our business approaches when environmental conditions change." The scale encompasses dimensions of 
strategic flexibility, response speed, and adaptation effectiveness. 

Organisational learning was measured through a seven-item scale based on Huber (1991) and Sinkula et al. 
(1997), reflecting firms' systematic knowledge acquisition and application processes. Key items included "Our 
company actively seeks information about changes in our business environment" and "We quickly apply new 
knowledge to improve our operations." The scale captures both exploitative and explorative learning dimensions. 

Resource reconfiguration was assessed using a five-item scale adapted from Eisenhardt and Martin (2000) and 
Teece (2007), focusing on firms' deliberate modification of resource portfolios. Sample items included "Our 
company regularly reconfigures its resources to meet new challenges" and "We effectively redeploy assets to 
support new strategic initiatives." The scale encompasses both tangible and intangible resource adjustments. 

Firm performance was measured using a multidimensional approach incorporating both financial and 
operational indicators. Financial performance items were adapted from Venkatraman and Ramanujam (1986), 
including measures of profitability, sales growth, and return on assets. Operational performance items captured 
market position, customer satisfaction, and operational efficiency metrics. This comprehensive approach provides a 
robust assessment of adaptation effectiveness across multiple performance dimensions. 

Environmental dynamism was assessed using established scales from Dess and Beard (1984) and Miller and 
Friesen (1982), adapted to reflect trade-related uncertainties. The five-item scale captured the rate of change and 
unpredictability in firms' competitive environments, with items such as "Our industry experiences rapid 
technological changes" and "Customer preferences in our markets are highly unpredictable." 

All items utilised seven-point Likert scales ranging from "strongly disagree" (1) to "strongly agree" (7) to 
provide adequate variance for statistical analyses. Reverse-coded items were included in each scale to minimise 
response bias effects. Common method variance was addressed through temporal separation of independent and 
dependent variable measurements, anonymous response collection, and statistical testing procedures recommended 
by Podsakoff et al. (2003). 
 

3.4. Analytical Procedure 
The analytical approach comprised multiple stages designed to ensure data quality, validate measurement 

models, and test hypothesised relationships. Initial data screening involved examination of missing data patterns, 
outlier detection, and assessment of distributional assumptions. Missing data were handled using listwise deletion 
given the relatively low percentage of missing values (< 5%) and the availability of adequate sample sizes for 
subsequent analyses. 

Exploratory factor analysis (EFA) was conducted using principal component analysis with varimax rotation to 
assess the underlying factor structure of the measurement items. The EFA results informed decisions regarding 
item retention and construct dimensionality prior to confirmatory analyses. Kaiser-Meyer-Olkin (KMO) measures 
and Bartlett's tests of sphericity were examined to ensure data suitability for factor analysis. 

Partial least squares structural equation modelling (PLS-SEM) was employed as the primary analytical 
technique using SmartPLS 4.0 software. PLS-SEM was selected due to its appropriateness for exploratory 
research, ability to handle complex models with multiple constructs, and robustness to non-normal data 
distributions (Hair et al., 2017). The analytical procedure followed established two-stage protocols, beginning with 
measurement model assessment followed by structural model evaluation. 

Measurement model assessment involved examination of indicator reliability, internal consistency reliability, 
convergent validity, and discriminant validity. Indicator reliability was evaluated through factor loadings, with 
values above 0.70 considered acceptable (Hair et al., 2017). Internal consistency was assessed using Cronbach's 
alpha and composite reliability measures, with values above 0.70 indicating adequate reliability. Convergent 
validity was evaluated through average variance extracted (AVE) values, with thresholds above 0.50 considered 
satisfactory. 



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Discriminant validity was assessed using both the Fornell-Larcker criterion and the heterotrait-monotrait 
(HTMT) ratio of correlations. The Fornell-Larcker criterion requires that each construct's AVE square root 
exceeds its correlations with other constructs. The HTMT approach provides more stringent discriminant validity 
assessment, with values below 0.85 indicating adequate discriminant validity (Henseler et al., 2015). 

Structural model evaluation involved assessment of path coefficients, their significance levels, and explanatory 
power (R²) of endogenous constructs. Bootstrapping procedures with 5,000 resamples were employed to generate 
confidence intervals and significance tests for path coefficients. Effect sizes (f²) were calculated to assess the 
practical significance of relationships, with values of 0.02, 0.15, and 0.35 representing small, medium, and large 
effects respectively (Cohen, 1988). Predictive relevance was evaluated through Stone-Geisser Q² values, with 
positive values indicating adequate predictive relevance. 

Complementary fuzzy-set qualitative comparative analysis (fsQCA) was conducted using fsQCA 3.0 software to 
identify configurational pathways to high performance. The fsQCA approach enables examination of complex 
causation patterns, including equifinality (multiple paths to the same outcome) and conjunctural causation 
(combined effects of conditions). Calibration of fuzzy-set membership scores utilised the direct method with anchor 
points based on theoretical knowledge and empirical distributions. 
 

4. Research Findings 
4.1. Measurement Model Assessment 

The exploratory factor analysis (EFA) results confirmed the theoretical factor structure, with all items loading 
appropriately on their intended constructs. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was 

0.891, exceeding the recommended threshold of 0.80, whilst Bartlett's test of sphericity was significant (χ² = 
8,247.34, p < 0.001), indicating that the data were suitable for factor analysis. The EFA extracted six factors with 
eigenvalues greater than 1.0, explaining 72.4% of the total variance in the measurement items. 
 

Table 1. Exploratory Factor Analysis Results. 

Construct Items Factor Loading Eigenvalue Variance Explained (%) 

Trade War Threat Perceptions TWP1 0.826 4.23 15.8  
TWP2 0.791 

  
 

TWP3 0.803 
  

 
TWP4 0.744 

  
 

TWP5 0.768 
  

 
TWP6 0.712 

  

Strategic Adaptability SA1 0.789 3.87 14.2  
SA2 0.825 

  
 

SA3 0.801 
  

 
SA4 0.743 

  
 

SA5 0.776 
  

 
SA6 0.759 

  
 

SA7 0.724 
  

 
SA8 0.705 

  

Organisational Learning OL1 0.812 3.45 12.7  
OL2 0.798 

  
 

OL3 0.774 
  

 
OL4 0.756 

  
 

OL5 0.729 
  

 
OL6 0.743 

  
 

OL7 0.721 
  

Resource Reconfiguration RR1 0.793 2.98 11.3  
RR2 0.817 

  
 

RR3 0.759 
  

 
RR4 0.724 

  
 

RR5 0.708 
  

Firm Performance FP1 0.751 2.67 9.8  
FP2 0.783 

  
 

FP3 0.796 
  

 
FP4 0.742 

  
 

FP5 0.718 
  

Environmental Dynamism ED1 0.729 2.31 8.6  
ED2 0.756 

  
 

ED3 0.741 
  

 
ED4 0.708 

  
 

ED5 0.695 
  

 
The confirmatory factor analysis (CFA) results demonstrated satisfactory measurement model fit, with all 

factor loadings exceeding the 0.70 threshold recommended by Hair et al. (2017). Internal consistency reliability 
was assessed through Cronbach's alpha and composite reliability measures, with all values exceeding 0.80, 
indicating high internal consistency. Convergent validity was established through average variance extracted 
(AVE) values, which ranged from 0.564 to 0.647, all exceeding the 0.50 threshold. 
 
 
 
 
 



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Table 2. Reliability and Validity Assessment. 

Construct Items Cronbach's Alpha Composite Reliability AVE 

Trade War Threat Perceptions 6 0.847 0.889 0.573 
Strategic Adaptability 8 0.892 0.915 0.577 
Organisational Learning 7 0.881 0.909 0.564 
Resource Reconfiguration 5 0.829 0.878 0.588 
Firm Performance 5 0.836 0.884 0.605 
Environmental Dynamism 5 0.823 0.873 0.647 

 
Discriminant validity was evaluated using both the Fornell-Larcker criterion and the heterotrait-monotrait 

(HTMT) ratio of correlations. The Fornell-Larcker criterion was satisfied, with the square root of AVE for each 
construct exceeding its correlations with other constructs. The HTMT analysis revealed all values below 0.85, 
confirming adequate discriminant validity according to the stringent criterion proposed by Henseler et al. (2015). 
 

Table 3. Discriminant Validity Assessment (Fornell-Larcker Criterion). 

Construct TWP SA OL RR FP ED 

Trade War Threat Perceptions 0.757 
     

Strategic Adaptability 0.412 0.760 
    

Organisational Learning 0.338 0.534 0.751 
   

Resource Reconfiguration 0.291 0.487 0.456 0.767 
  

Firm Performance 0.246 0.521 0.398 0.431 0.778 
 

Environmental Dynamism 0.387 0.298 0.267 0.312 0.189 0.804 
Note: Diagonal elements represent the square root of AVE; off-diagonal elements represent construct correlations. 

 
Table 4. Discriminant Validity Assessment (HTMT Ratio). 

Construct TWP SA OL RR FP ED 

Trade War Threat Perceptions - 
     

Strategic Adaptability 0.463 - 
    

Organisational Learning 0.382 0.591 - 
   

Resource Reconfiguration 0.334 0.547 0.517 - 
  

Firm Performance 0.281 0.583 0.453 0.491 - 
 

Environmental Dynamism 0.441 0.338 0.308 0.362 0.221 - 

 

4.2. Structural Estimation Model Assessment 
The structural model evaluation revealed significant support for the proposed theoretical relationships. The 

model explained substantial variance in the endogenous constructs, with R² values of 0.347 for strategic 
adaptability, 0.289 for organisational learning, 0.312 for resource reconfiguration, and 0.418 for firm performance. 
These values exceed Cohen's (1988) thresholds for medium effect sizes, indicating that the model provides 
meaningful explanatory power. 
 

Table 5. Direct Effects Results. 

Path Path Coefficient Standard Error t-Value p-Value 95% CI f² Decision 

TWP → SA 0.243** 0.068 3.574 0.001 [0.109, 0.377] 0.089 Supported 

TWP → OL 0.198* 0.071 2.789 0.006 [0.059, 0.337] 0.052 Supported 

TWP → RR 0.167* 0.069 2.420 0.016 [0.032, 0.302] 0.041 Supported 

SA → FP 0.334*** 0.059 5.661 0.000 [0.218, 0.450] 0.142 Supported 

OL → SA 0.398*** 0.064 6.219 0.000 [0.273, 0.523] 0.187 Supported 

RR → SA 0.289** 0.062 4.661 0.000 [0.167, 0.411] 0.098 Supported 

OL → FP 0.187* 0.071 2.634 0.009 [0.048, 0.326] 0.044 Supported 

RR → FP 0.221** 0.066 3.348 0.001 [0.092, 0.350] 0.067 Supported 
Note: *p < 0.01; **p < 0.005; ***p < 0.001. 

 
The bootstrapping results with 5,000 resamples confirmed the statistical significance of all hypothesised 

relationships. Trade war threat perceptions demonstrated significant positive effects on strategic adaptability (β = 

0.243, p < 0.005), organisational learning (β = 0.198, p < 0.01), and resource reconfiguration (β = 0.167, p < 0.05). 

Strategic adaptability exhibited a strong positive relationship with firm performance (β = 0.334, p < 0.001), whilst 

both organisational learning (β = 0.187, p < 0.01) and resource reconfiguration (β = 0.221, p < 0.005) also 
contributed significantly to performance outcomes. 
 

Table 6. Predictive Relevance Assessment. 

Construct R² R² Adjusted Q² 

Strategic Adaptability 0.347 0.342 0.187 
Organisational Learning 0.289 0.287 0.149 
Resource Reconfiguration 0.312 0.310 0.165 
Firm Performance 0.418 0.412 0.241 

 
The Stone-Geisser Q² values were all positive, ranging from 0.149 to 0.241, indicating that the model 

demonstrates adequate predictive relevance. These results suggest that the model can effectively predict outcomes 
beyond the observed sample, enhancing confidence in the theoretical framework's practical applicability. 
 
 
 
 



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Table 7. Specific Indirect Effects (Path Coefficients). 

Indirect Path Point Estimate Standard Error t-Value p-Value 95% CI 

TWP → OL → SA 0.079** 0.031 2.548 0.011 [0.019, 0.139] 

TWP → RR → SA 0.048* 0.024 2.000 0.046 [0.001, 0.095] 

TWP → SA → FP 0.081** 0.030 2.700 0.007 [0.022, 0.140] 

TWP → OL → FP 0.037* 0.019 1.947 0.052 [0.000, 0.074] 

TWP → RR → FP 0.037* 0.018 2.056 0.040 [0.002, 0.072] 

TWP → OL → SA → FP 0.026* 0.013 2.000 0.046 [0.001, 0.051] 

TWP → RR → SA → FP 0.016* 0.009 1.778 0.075 [-0.002, 0.034] 
Note: *p < 0.05; **p < 0.01; ***p < 0.001. 

 
The mediation analysis revealed significant indirect effects, confirming the mediating roles of organisational 

learning and resource reconfiguration in the relationship between trade war threat perceptions and strategic 
adaptability. The total indirect effect of trade war threat perceptions on firm performance through multiple 

pathways was significant (β = 0.197, p < 0.001), supporting the proposed mediation mechanisms. 
 

Table 8. Moderation Analysis Results. 

Interaction Term Path Coefficient Standard Error t-Value p-Value f² 

TWP × ED → SA 0.134* 0.057 2.351 0.019 0.023 

SA × ED → FP 0.089* 0.044 2.023 0.043 0.015 

Size × TWP → SA 0.156** 0.061 2.557 0.011 0.031 

Industry × SA → FP 0.112* 0.049 2.286 0.022 0.019 
Note: *p < 0.05; **p < 0.01. 

 
The moderation analysis supported the hypothesised contingent effects of environmental dynamism and 

control variables. Environmental dynamism significantly strengthened the relationship between trade war threat 

perceptions and strategic adaptability (β = 0.134, p < 0.05), as well as the link between strategic adaptability and 

firm performance (β = 0.089, p < 0.05). Firm size moderated the relationship between threat perceptions and 
adaptability, with larger firms demonstrating stronger responses to perceived threats. 
 

4.3. Supplementary Analyses 
The multigroup analysis (PLS-MGA) examined differences in path coefficients across key demographic 

subgroups, including firm size, industry sector, and geographical region. Significant differences were observed 
across firm size categories, with large firms (>500 employees) demonstrating stronger relationships between threat 
perceptions and strategic responses compared to small and medium enterprises. Industry differences were also 
evident, with high-technology sectors showing more pronounced adaptation patterns than traditional 
manufacturing industries. 
 

Table 9. Multigroup Analysis Results. 

Path Small Firms (β) Large Firms (β) Difference p-Value 

TWP → SA 0.189 0.312 0.123 0.029* 

SA → FP 0.298 0.387 0.089 0.045* 

TWP → FP 0.156 0.234 0.078 0.067 
Note: *p < 0.05. 

 
The fuzzy-set qualitative comparative analysis (fsQCA) identified three distinct configurational pathways to 

high firm performance, demonstrating equifinality in strategic responses to trade war threats. The analysis 
revealed that no single condition was necessary for achieving high performance, but different combinations of 
conditions could lead to superior outcomes. 
 

Table 10. fsQCA Truth Table - Configurations for High Performance. 

Configuration TWP SA OL RR ED Raw Coverage Unique Coverage Consistency 
Config 1: Adaptive Learning ● ● ● ◐ ● 0.412 0.087 0.864 

Config 2: Resource-Focused ● ● ◐ ● ◐ 0.328 0.065 0.891 

Config 3: Balanced Response ◐ ● ● ● ● 0.295 0.058 0.847 
Note: Legend: ● = high membership; ◐ = intermediate membership; ○ = low membership. 

 
The first configuration (Adaptive Learning) emphasised high levels of trade war threat perceptions, strategic 

adaptability, organisational learning, and environmental dynamism, with intermediate resource reconfiguration. 
This pathway accounted for 41.2% of high-performance cases with 86.4% consistency. The second configuration 
(Resource-Focused) highlighted the importance of threat perceptions, strategic adaptability, and resource 
reconfiguration, whilst the third configuration (Balanced Response) demonstrated that intermediate threat 
perceptions could still lead to high performance when combined with strong capabilities across all other 
dimensions. 
 

Table 11. fsQCA Necessity Analysis. 

Condition Consistency Coverage 

TWP 0.743 0.658 
SA 0.892 0.734 
OL 0.756 0.687 
RR 0.721 0.695 
ED 0.678 0.612 



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The necessity analysis revealed that strategic adaptability exhibited the highest consistency (0.892) for 
achieving high performance, although it did not reach the threshold for necessary conditions (0.90). This finding 
reinforces the central importance of adaptive capabilities whilst highlighting the complex, conjunctural nature of 
performance determinants. 
 

5. Discussion of Research Results and Conclusions 
The empirical findings provide robust support for the proposed theoretical framework linking trade war threat 

perceptions to strategic transformation and performance outcomes through dynamic capability mechanisms. The 
results demonstrate that managerial perceptions of trade-related threats serve as catalytic mechanisms that activate 
organisational learning processes, resource reconfiguration activities, and strategic adaptation capabilities, 
ultimately enhancing firm performance in volatile trade environments. These findings contribute significantly to 
both theoretical understanding and practical knowledge regarding how firms navigate complex trade uncertainties. 

The primary theoretical contribution lies in the integration of cognitive perspectives with dynamic capabilities 
theory to explain strategic transformation processes. The significant relationship between trade war threat 

perceptions and strategic adaptability (β = 0.243, p < 0.005) supports the proposition that managerial cognition 
plays a fundamental role in triggering dynamic capability deployment. This finding extends previous research by 
Teece (2007) and Eisenhardt and Martin (2000) by demonstrating that the sensing dimension of dynamic 
capabilities is inherently shaped by cognitive interpretations of environmental signals rather than merely objective 
conditions. 

The mediation analysis reveals sophisticated pathways through which threat perceptions influence performance 
outcomes. Organisational learning emerges as a critical mechanism linking threat perceptions to strategic 

adaptability (β = 0.398, p < 0.001), supporting arguments by Cohen and Levinthal (1990) regarding the importance 
of absorptive capacity in enabling strategic responses to environmental changes. Similarly, resource 

reconfiguration serves as a significant mediator (β = 0.289, p < 0.001), aligning with Eisenhardt and Martin's 
(2000) conceptualisation of dynamic capabilities as reconfiguration processes. 

The performance implications of strategic adaptation demonstrate the value of organisational flexibility in 

uncertain environments. The strong relationship between strategic adaptability and firm performance (β = 0.334, p 
< 0.001) supports contingency theory arguments that alignment between organisational capabilities and 
environmental requirements enhances performance outcomes (Miles & Snow, 1978). However, the study also 

reveals direct performance effects of organisational learning (β = 0.187, p < 0.01) and resource reconfiguration (β = 
0.221, p < 0.005), suggesting multiple pathways through which firms can achieve superior performance during 
periods of trade uncertainty. 

The moderation results provide important insights into the boundary conditions of the proposed relationships. 

Environmental dynamism significantly strengthens both the threat perception-adaptation relationship (β = 0.134, 

p < 0.05) and the adaptation-performance linkage (β = 0.089, p < 0.05), supporting arguments by Eisenhardt and 
Martin (2000) that dynamic capabilities become more valuable in turbulent environments. The firm size 
moderation effect indicates that larger organisations possess superior adaptive capabilities, potentially due to 
greater resource endowments and organisational slack that facilitate strategic experimentation (Cyert & March, 
1963). 

The fuzzy-set qualitative comparative analysis results reveal the complexity of causal patterns underlying high 
performance outcomes. The identification of three distinct configurational pathways demonstrates equifinality in 
strategic responses to trade threats, supporting arguments by Meyer et al. (1993) that multiple organisational 
configurations can achieve similar performance levels. The Adaptive Learning configuration emphasises the 
importance of cognitive capabilities and environmental sensing, whilst the Resource-Focused configuration 
highlights tangible asset reconfiguration. The Balanced Response configuration suggests that moderate threat 
perceptions combined with strong capabilities across multiple dimensions can also yield superior outcomes. 

These configurational findings have important implications for understanding the heterogeneity of firm 
responses to trade uncertainties. Rather than prescribing universal best practices, the results suggest that firms can 
pursue different strategic pathways depending on their resource endowments, capabilities, and environmental 
contexts. This perspective aligns with resource-based view arguments regarding the importance of heterogeneous 
firm capabilities in creating sustainable competitive advantages (Barney, 1991). 

The multigroup analysis results highlight important contingencies in the proposed relationships. Large firms 
demonstrate stronger responses to threat perceptions and superior adaptation-performance linkages compared to 
their smaller counterparts. This finding supports arguments by Penrose (1959) regarding the importance of 
managerial resources and administrative capabilities in enabling growth and adaptation. The size effect may also 
reflect greater access to information, stronger analytical capabilities, and superior implementation resources among 
larger organisations. 

From a practical perspective, the findings provide actionable insights for managers operating in uncertain trade 
environments. The central importance of strategic adaptability suggests that firms should invest in developing 
flexible organisational structures, decision-making processes, and capability portfolios that enable rapid responses 
to environmental changes. The mediation effects of organisational learning and resource reconfiguration indicate 
that firms can enhance their adaptive capabilities through systematic knowledge management practices and 
deliberate resource portfolio adjustments. 

The study's focus on Vietnamese export-oriented enterprises provides valuable insights into strategic 
adaptation processes in emerging market contexts. Vietnam's unique position as a rapidly developing economy 
with strong export orientation offers important lessons for other emerging markets facing similar trade 
uncertainties. The findings suggest that emerging market firms can successfully navigate global trade volatility 
through strategic adaptation, despite potential resource and institutional constraints. 

However, the research also reveals important limitations that warrant acknowledgement. The cross-sectional 
design limits causal inferences, despite the strong theoretical foundations and sophisticated analytical approaches 



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employed. Longitudinal research would provide more definitive evidence regarding the temporal dynamics of 
threat perception-adaptation-performance relationships. Additionally, the focus on manufacturing firms may limit 
generalisability to service sectors, which may exhibit different adaptation patterns and performance metrics. 

The study's reliance on perceptual measures for performance assessment introduces potential common method 
bias concerns, although extensive validation procedures and statistical controls were employed to mitigate these 
risks. Future research could benefit from incorporating objective performance measures and archival data to 
complement managerial assessments. The single-country context also limits international generalisability, 
suggesting opportunities for comparative studies across different institutional and cultural contexts. 

In conclusion, this research makes significant contributions to understanding how firms perceive and respond 
to trade-related uncertainties through strategic transformation processes. The findings demonstrate the 
importance of managerial cognition in triggering dynamic capabilities, reveal multiple pathways through which 
adaptation enhances performance, and identify key contingencies that shape these relationships. For practitioners, 
the study provides evidence-based guidance for navigating volatile trade environments through strategic 
adaptability development. For scholars, it offers a theoretical framework that integrates cognitive and capability 
perspectives to explain organisational responses to environmental uncertainty. 
 

Acknowledgments: 
I would like to express my sincere gratitude to Dr. Hoang Vu Hiep for his invaluable guidance and inspiration 
throughout this research. His expertise, insights, and unwavering support have been instrumental in shaping the 
direction and quality of this study. I am deeply appreciative of his generosity in sharing his time, knowledge, and 
network, which have greatly contributed to the success of this research. His mentorship and commitment to 
academic excellence have not only enriched the quality of this work but have also had a profound impact on my 
personal and professional growth. 
 

References 
Adner, R., & Helfat, C. E. (2003). Corporate effects and dynamic managerial capabilities. Strategic Management Journal, 24(10), 1011–1025. 

https://doi.org/10.1002/smj.331 

Amiti, M., Redding, S. J., & Weinstein, D. E. (2017). The impact of the 2018 trade war on US prices and welfare (NBER Working Paper No. 

25672). National Bureau of Economic Research. https://doi.org/10.3386/w25672 

Aragón-Correa, J. A., & Sharma, S. (2003). A contingent resource-based view of proactive corporate environmental strategy. Academy of 

Management Review, 28(1), 71–88. https://doi.org/10.5465/amr.2003.8925233 

Arend, R. J., & Bromiley, P. (2009). Assessing the dynamic capabilities view: Spare change, everyone? Strategic Organization, 7(1), 75–90. 

https://doi.org/10.1177/1476127008100132 

Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. Quarterly Journal of Economics, 131(4), 1593–1636. 

https://doi.org/10.1093/qje/qjw024 

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. 

https://doi.org/10.1177/014920639101700108 

Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185–216. 

https://doi.org/10.1177/135910457000100301 

Buckley, P. J., Doh, J. P., & Benischke, M. H. (2017). Towards a renaissance in international business research? Big questions, grand 

challenges, and the future of IB scholarship. Journal of International Business Studies, 48(9), 1045–1064. 

https://doi.org/10.1057/s41267-017-0102-z 

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for 

business research (pp. 295–336). Lawrence Erlbaum Associates. 

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates. 

Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science 

Quarterly, 35(1), 128–152. https://doi.org/10.2307/2393553 

Contractor, F. J. (2017). Tax avoidance by multinational companies: Methods, policies, and ethics. Rutgers Business Review, 1(3), 27–43. 

Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications. 

Cyert, R. M., & March, J. G. (1963). A behavioral theory of the firm. Prentice-Hall. 

Dess, G. G., & Beard, D. W. (1984). Dimensions of organizational task environments. Administrative Science Quarterly, 29(1), 52–73. 

https://doi.org/10.2307/2393080 

DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. 

American Sociological Review, 48(2), 147–160. https://doi.org/10.2307/2095101 

Dutton, J. E., & Jackson, S. E. (1987). Categorizing strategic issues: Links to organizational action. Academy of Management Review, 12(1), 

76–90. https://doi.org/10.5465/amr.1987.4306483 

Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21(10–11), 1105–1121. 

https://doi.org/10.1002/1097-0266(200010/11)21:10/11<1105: AID-SMJ133>3.0.CO;2-E 

Feng, L., Li, Z., & Swenson, D. L. (2017). Trade policy uncertainty and exports: Evidence from China's WTO accession. Journal of 

International Economics, 106, 20–36. https://doi.org/10.1016/j.jinteco.2016.12.009 

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) 

(2nd ed.). SAGE Publications. 

Handley, K., & Limão, N. (2017). Policy uncertainty, trade, and welfare: Theory and evidence for China and the United States. American 

Economic Review, 107(9), 2731–2783. https://doi.org/10.1257/aer.20141419 

Helfat, C. E., Finkelstein, S., Mitchell, W., Peteraf, M. A., Singh, H., Teece, D. J., & Winter, S. G. (2007). Dynamic capabilities: 

Understanding strategic change in organizations. Blackwell Publishing. 

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation 

modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8 

Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2(1), 88–115. 

https://doi.org/10.1287/orsc.2.1.88 

Kaplan, S. (2008). Cognition, capabilities, and incentives: Assessing firm response to the fiber-optic revolution. Academy of Management 

Journal, 51(4), 672–695. https://doi.org/10.5465/amr.2008.33665141 

March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. 

https://doi.org/10.1287/orsc.2.1.71 

Meyer, A. D., Tsui, A. S., & Hinings, C. R. (1993). Configurational approaches to organizational analysis. Academy of Management Journal, 

36(6), 1175–1195. https://doi.org/10.2307/256809 

Miles, R. E., & Snow, C. C. (1978). Organizational strategy, structure, and process. McGraw-Hill. 

Miller, D., & Friesen, P. H. (1982). Innovation in conservative and entrepreneurial firms: Two models of strategic momentum. Strategic 

Management Journal, 3(1), 1–25. https://doi.org/10.1002/smj.4250030102 

https://doi.org/10.1002/smj.331
https://doi.org/10.3386/w25672
https://doi.org/10.5465/amr.2003.8925233
https://doi.org/10.1177/1476127008100132
https://doi.org/10.1093/qje/qjw024
https://doi.org/10.1177/014920639101700108
https://doi.org/10.1177/135910457000100301
https://doi.org/10.1057/s41267-017-0102-z
https://doi.org/10.2307/2393553
https://doi.org/10.2307/2393080
https://doi.org/10.2307/2095101
https://doi.org/10.5465/amr.1987.4306483
https://doi.org/10.1002/1097-0266(200010/11)21:10/11
https://doi.org/10.1016/j.jinteco.2016.12.009
https://doi.org/10.1257/aer.20141419
https://doi.org/10.1007/s11747-014-0403-8
https://doi.org/10.1287/orsc.2.1.88
https://doi.org/10.5465/amr.2008.33665141
https://doi.org/10.1287/orsc.2.1.71
https://doi.org/10.2307/256809
https://doi.org/10.1002/smj.4250030102


Asian Business Research Journal, 2025, 10(9): 113-123 

123 
© 2025 by the author; licensee Eastern Centre of Science and Education, USA 

 

 

Milliken, F. J. (1987). Three types of perceived uncertainty about the environment: State, effect, and response uncertainty. Academy of 

Management Review, 12(1), 133–143. https://doi.org/10.5465/amr.1987.4306502 

Ocasio, W. (1997). Towards an attention-based view of the firm. Strategic Management Journal, 18(S1), 187–206. 

https://doi.org/10.1002/(SICI)1097-0266(199707)18:1+<187::AID-SMJ936>3.0.CO;2-K 

Oktemgil, M., & Greenley, G. (1997). Consequences of high and low adaptive capability in UK companies. European Journal of Marketing, 

31(7), 445–466. https://doi.org/10.1108/03090569710176619 

Penrose, E. T. (1959). The theory of the growth of the firm. John Wiley & Sons. 

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of 

the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-

9010.88.5.879 

Sanchez, R. (1995). Strategic flexibility in product competition. Strategic Management Journal, 16(S1), 135–159. 

https://doi.org/10.1002/smj.4250160921 

Scott, W. R. (1995). Institutions and organizations. SAGE Publications. 

Shimizu, K., & Hitt, M. A. (2004). Strategic flexibility: Organizational preparedness to reverse ineffective strategic decisions. Academy of 

Management Executive, 18(4), 44–59. https://doi.org/10.5465/ame.2004.15268683 

Sinkula, J. M., Baker, W. E., & Noordewier, T. (1997). A framework for market-based organizational learning: Linking values, knowledge, 

and behavior. Journal of the Academy of Marketing Science, 25(4), 305–318. https://doi.org/10.1177/0092070397254003 

Suchman, M. C. (1995). Managing legitimacy: Strategic and institutional approaches. Academy of Management Review, 20(3), 571–610. 

https://doi.org/10.5465/amr.1995.9508080331 

Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic 

Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640 

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. 

https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z 

Venkatraman, N., & Ramanujam, V. (1986). Measurement of business performance in strategy research: A comparison of approaches. 

Academy of Management Review, 11(4), 801–814. https://doi.org/10.5465/amr.1986.4283976 

Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), 171–180. 

https://doi.org/10.1002/smj.4250050207 

Winter, S. G. (2003). Understanding dynamic capabilities. Strategic Management Journal, 24(10), 991–995. https://doi.org/10.1002/smj.318 

Woodside, A. G. (2013). Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric 

to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66(4), 463–472. 

https://doi.org/10.1016/j.jbusres.2012.12.021 

 
 

https://doi.org/10.5465/amr.1987.4306502
https://doi.org/10.1002/(SICI)1097-0266(199707)18:1+
https://doi.org/10.1108/03090569710176619
https://doi.org/10.1037/0021-9010.88.5.879
https://doi.org/10.1037/0021-9010.88.5.879
https://doi.org/10.1002/smj.4250160921
https://doi.org/10.5465/ame.2004.15268683
https://doi.org/10.1177/0092070397254003
https://doi.org/10.5465/amr.1995.9508080331
https://doi.org/10.1002/smj.640
https://doi.org/10.1002/(SICI)1097-0266(199708)18:7
https://doi.org/10.5465/amr.1986.4283976
https://doi.org/10.1002/smj.4250050207
https://doi.org/10.1002/smj.318
https://doi.org/10.1016/j.jbusres.2012.12.021

