Table A1. Selected reviews on dynamic... | Emerald Publishing

Table A1.

Selected reviews on dynamic capabilities

Year	Authors	Title	Focus	Findings	Limitations
2010	Barreto	Dynamic capabilities: a review of past research and an agenda for the future	Assess prior DC research, organize definitional diversity, propose a clearer conceptualization, and set a future research agenda	The literature remains conceptually fragmented; definitions differ on nature, role, context, heterogeneity, outcomes, and purpose; the field has advanced but is not yet a theory because it lacks construct consolidation, clear causal laws, and well-specified contingencies	Notes definitional proliferation, disconnected research streams, vagueness, tautology concerns, limited boundaries and contingencies, unresolved tension between idiosyncrasy and commonality, and weak measurement development
2018	Laaksonen and peltoniemi	The essence of dynamic capabilities and their measurement	Examine how DCs are measured, assess whether these measures align with the theoretical essence of the construct, and propose recommendations for future empirical work	Identifies Four major operationalization types; finds substantial mismatch between theory and empirical measures; proposes Eight recommendations, including clearer distinction between ordinary and dynamic capabilities, indirect performance logic, longitudinal data, and better measurement of learning outcomes	Finds that empirical studies often fail to distinguish DCs from ordinary capabilities, model DCs as direct determinants of performance, rely on common method variance, measure quantity rather than type/existence, ignore longitudinal accumulation, and privilege learning opportunities over learning outcomes
2018	Schilke et al.	Quo vadis, dynamic capabilities? A content-analytic review of the current state of knowledge and recommendations for future research	Synthesize the current state of dynamic capabilities research, develop a comprehensive meta-framework of antecedents, dimensions, mechanisms, moderators, and outcomes, and derive future research directions from a systematic coding of limitations and recommendations in prior work	The review finds increasing convergence in definitions; richer theorizing around assumptions such as bounded rationality, agency, and heterogeneity; broader theory integration; and significant empirical progress on antecedents, dimensions, consequences, moderators, and, to a lesser extent, mechanisms. It proposes a comprehensive organizing framework for DC research and argues that the literature has become more coherent and cumulative than critics often assume. It also identifies weak spots, especially limited work on mediating mechanisms, insufficient attention to market and ecosystem shaping, underdeveloped treatment of some theoretical integrations, and continued need for methodological diversification	The article identifies several limitations and unresolved issues in the literature: only partial consensus on definitions; need for clearer elaboration of theoretical assumptions such as bounded rationality and agency; insufficient study of mechanisms/mediators; underdeveloped work on shaping markets and ecosystems; unresolved tensions regarding routinization and dimensionalization; excessive empirical focus on performance rather than proximate outcomes; and reliance on a relatively narrow empirical toolkit dominated by surveys and qualitative case studies
2024	Pitelis et al.	Dynamic capabilities and MNE global strategy: a systematic literature review-based novel conceptual framework	Assess how DCs have been used in MNE global strategy research, compare theory and evidence, identify gaps, and propose a new framework	Global strategy cannot be understood without DCs; the MNE literature underuses DCs despite their relevance; empirical work over-relies on surveys; key themes include global strategy, resources, innovation, entrepreneurship, and performance; underexplored areas include co-creation, imagination, and co-specialization	Notes weak direct measurement of sensing/seizing/reconfiguring, limited distinction between DCs and ordinary capabilities, inconsistency in higher- vs lower-order categorization, underdeveloped treatment of governance, resource-base mediation, context creation, FDI/modality consequences, competition as moderator, and causality/simultaneity issues
2024	Bruyaka et al.	Dynamic capabilities measurement safari: a roadmap	Clarify the operationalization of the DC construct in quantitative research, especially the conceptual definition, construct scope, dimensionality, and measurement model choice	Finds large diversity in measurement models; unidimensional models remain prevalent despite multidimensional calls; the same type of DC is often measured inconsistently across studies; measurement choices often appear disconnected from conceptual definitions. The article proposes a roadmap built around Four auxiliary-theory decisions and recommends controlled plurality rather than random diversity	Identifies lack of transparency, mismatch between conceptualization and operationalization, neglect of dimensionality, inconsistent model specification, use of different models for the same DC types, and continued risk of measurement misspecification and false findings. Also notes its own limits: exclusion of qualitative studies and no adjudication of whether every labeled construct is truly a DC

Year	Authors	Title	Focus	Findings	Limitations
2010	Barreto	Dynamic capabilities: a review of past research and an agenda for the future	Assess prior DC research, organize definitional diversity, propose a clearer conceptualization, and set a future research agenda	The literature remains conceptually fragmented; definitions differ on nature, role, context, heterogeneity, outcomes, and purpose; the field has advanced but is not yet a theory because it lacks construct consolidation, clear causal laws, and well-specified contingencies	Notes definitional proliferation, disconnected research streams, vagueness, tautology concerns, limited boundaries and contingencies, unresolved tension between idiosyncrasy and commonality, and weak measurement development
2018	Laaksonen and peltoniemi	The essence of dynamic capabilities and their measurement	Examine how DCs are measured, assess whether these measures align with the theoretical essence of the construct, and propose recommendations for future empirical work	Identifies Four major operationalization types; finds substantial mismatch between theory and empirical measures; proposes Eight recommendations, including clearer distinction between ordinary and dynamic capabilities, indirect performance logic, longitudinal data, and better measurement of learning outcomes	Finds that empirical studies often fail to distinguish DCs from ordinary capabilities, model DCs as direct determinants of performance, rely on common method variance, measure quantity rather than type/existence, ignore longitudinal accumulation, and privilege learning opportunities over learning outcomes
2018	Schilke et al.	Quo vadis, dynamic capabilities? A content-analytic review of the current state of knowledge and recommendations for future research	Synthesize the current state of dynamic capabilities research, develop a comprehensive meta-framework of antecedents, dimensions, mechanisms, moderators, and outcomes, and derive future research directions from a systematic coding of limitations and recommendations in prior work	The review finds increasing convergence in definitions; richer theorizing around assumptions such as bounded rationality, agency, and heterogeneity; broader theory integration; and significant empirical progress on antecedents, dimensions, consequences, moderators, and, to a lesser extent, mechanisms. It proposes a comprehensive organizing framework for DC research and argues that the literature has become more coherent and cumulative than critics often assume. It also identifies weak spots, especially limited work on mediating mechanisms, insufficient attention to market and ecosystem shaping, underdeveloped treatment of some theoretical integrations, and continued need for methodological diversification	The article identifies several limitations and unresolved issues in the literature: only partial consensus on definitions; need for clearer elaboration of theoretical assumptions such as bounded rationality and agency; insufficient study of mechanisms/mediators; underdeveloped work on shaping markets and ecosystems; unresolved tensions regarding routinization and dimensionalization; excessive empirical focus on performance rather than proximate outcomes; and reliance on a relatively narrow empirical toolkit dominated by surveys and qualitative case studies
2024	Pitelis et al.	Dynamic capabilities and MNE global strategy: a systematic literature review-based novel conceptual framework	Assess how DCs have been used in MNE global strategy research, compare theory and evidence, identify gaps, and propose a new framework	Global strategy cannot be understood without DCs; the MNE literature underuses DCs despite their relevance; empirical work over-relies on surveys; key themes include global strategy, resources, innovation, entrepreneurship, and performance; underexplored areas include co-creation, imagination, and co-specialization	Notes weak direct measurement of sensing/seizing/reconfiguring, limited distinction between DCs and ordinary capabilities, inconsistency in higher- vs lower-order categorization, underdeveloped treatment of governance, resource-base mediation, context creation, FDI/modality consequences, competition as moderator, and causality/simultaneity issues
2024	Bruyaka et al.	Dynamic capabilities measurement safari: a roadmap	Clarify the operationalization of the DC construct in quantitative research, especially the conceptual definition, construct scope, dimensionality, and measurement model choice	Finds large diversity in measurement models; unidimensional models remain prevalent despite multidimensional calls; the same type of DC is often measured inconsistently across studies; measurement choices often appear disconnected from conceptual definitions. The article proposes a roadmap built around Four auxiliary-theory decisions and recommends controlled plurality rather than random diversity	Identifies lack of transparency, mismatch between conceptualization and operationalization, neglect of dimensionality, inconsistent model specification, use of different models for the same DC types, and continued risk of measurement misspecification and false findings. Also notes its own limits: exclusion of qualitative studies and no adjudication of whether every labeled construct is truly a DC

Source(s): Authors’ own work