Search Results (77)

This study develops a modular framework for the diagnostic application of microfoundational theory to examine how individual-level actions aggregate into macro-level technological capabilities and operational performance in innovation intermediaries within emerging economies. Grounded in Coleman’s bathtub model and the Viable System Model, we dissect three interdependent modules to diagnose systemic issues within institutional voids. Methodologically, we conduct a qualitative critical case study of a centenary Brazilian Research and Technology Organization, utilizing semi-structured interviews across three distinct organizational levels—senior executives, unit heads, and research leads—triangulated with eleven institutional management documents (2019–2024) through categorical content analysis. Theoretically, this research aims to establish a conceptual taxonomy that synthesizes Coleman’s micro–macro link, potentially serving as an analytical baseline for future cross-context evaluations of innovation intermediaries while exploring how meso–micro actions co-evolve with ecosystem-level environments. Practically, this study seeks to offer actionable governance levers for managers and policymakers, illustrating how the strategic deployment of dedicated internationalization units to buffer external complexity and the targeted cultivation of soft competencies in senior research leads may help overcome collaborative network isolation within late-development settings. Full article

The rapid advancement of artificial intelligence (AI) and growing global fragmentation are reshaping how multinational enterprises manage cross-border strategic alliances. Prior research has focused on alliance formation and resource access, yet less attention has been paid to how AI transforms the managerial capabilities required for effective alliance orchestration. This study addresses this gap by examining how AI augmentation may alter the microfoundations of dynamic managerial capabilities (DMC) in cross-border alliances. Building on DMC theory, the paper proposes an AI-augmented framework with four interrelated microfoundations: AI-enhanced managerial cognition, algorithmic social capital, hybrid human–AI capital, and AI-enabled political capital. Using an abductive research design and longitudinal case analyses of Carrefour–Google, Walmart–IBM, and Tesco–Carrefour, the study illustrates how AI may support the reshaping of sensing, seizing, and reconfiguring processes. It uses a Gioia-informed coding procedure to enhance transparency in the elaboration of theory. The findings suggest that AI may improve data-driven sensing, enable scalable coordination through algorithmic trust, enhance ambidexterity through human–AI collaboration, and support proactive regulatory positioning. However, these benefits are expected to be contingent on institutional conditions, including data governance constraints and power asymmetries. The study contributes by extending DMC theory and highlighting how AI-enabled capabilities could drive alliance performance in complex global environments. Full article

Digital markets increasingly coordinate prices, matches, orders, and allocations through automated systems whose decision–execution loops can close faster than humans can intervene. This article develops a microfounded framework in which latency is a temporal feasibility constraint that complements adjustment costs, information delay, costly information acquisition, queueing, and technological execution costs. The model distinguishes common latency, human intervention latency, and relative latency. Common latency is produced by platform and participant investment and affects welfare through the freshness of the state on which decisions are executed. Human intervention is represented by a smooth, task- and organization-specific probability q(L,z,s), derived from a distribution of completion times and modified by interface and organizational support. Human, hybrid, and algorithmic decision technologies differ in speed, accuracy, cost, and systematic misspecification risk. Relative speed is modeled as a strategic priority contest in which each intermediary’s best response depends on rivals’ investments, while platform rules determine the sensitivity and value of being first. The framework derives conditions for human-algorithm substitution, welfare-improving common-speed investment, socially excessive strategic speed investment, and welfare-enhancing batching or latency floors. It separates temporal from structural market distortions, integrates decision-technology quality and state freshness in a total-welfare function, and develops an incidence model that traces gains across heterogeneous users, intermediaries, and infrastructure owners. Robustness results cover diffusion, mean-reverting, jump, stochastic-volatility, and regime-switching state processes. An illustrative dynamic simulation, explicit scope conditions, and an operational empirical agenda show how the theory can be tested without claiming empirical calibration. The central contribution is a non-equivalence result: when latency enters the probability of successful intervention, shortening the decision window can change the technology and locus of marginal choice even when information, objectives, adjustment costs, and the substantive decision rule are held fixed. Full article

Background: Counterfeit governance in e-commerce platforms is a real-world problem characterized by strategic interdependence, information asymmetry and dynamic feedback among platforms, merchants and consumers. Linear or single-actor regulatory approaches are often insufficient to address such complexity, as platform regulation, merchant behaviour, consumer trust and online reputation mechanisms jointly shape the evolution of market trust. Methods: Guided by systems thinking, this study conceptualizes counterfeit governance as a socio-technical system and develops a tripartite evolutionary game model involving e-commerce platforms, merchants and consumers. The model delineates the system boundary around transaction-stage platform governance and incorporates key variables, including regulatory costs, fraudulent gains, honest transaction costs, subsidies, penalties, consumer transaction costs, online word-of-mouth influence and reputation losses. System dynamics simulation using Vensim PLE 10.5.2 is then employed to examine evolutionary trajectories, local stability, parameter sensitivity and threshold regions. Results: The results show that weak or static regulation may allow fraudulent strategies to persist or fluctuate, whereas stronger penalties and subsidies for honest transactions can reshape the payoff structure and promote merchant integrity. Transaction-related consumer incentives and enhanced online word-of-mouth mechanisms support consumer trust and stabilize the system toward trustworthy transactions. Conclusions: This study operationalizes systems thinking through system dynamics, while evolutionary game theory provides behavioural micro-foundations for stakeholder strategy adjustment in digital platform governance. Full article

Research on the informal economy has traditionally emphasized its measurement and macroeconomic effects, focusing on structural and institutional determinants. Individual psychological factors that may help explain social tolerance toward informal practices have received far less attention. This exploratory study addresses this gap by examining how Big Five personality traits and dimensions of competitiveness are associated with two components of tolerance: the acceptance of informal behaviors, and justificatory beliefs. To this end, an ad hoc questionnaire was developed, and a cross-sectional design was implemented using a stratified sample of 339 students enrolled in Business Administration programs at a Spanish university. Multivariable models estimated these associations while adjusting for gender. The results indicate that conscientiousness and extraversion are negatively associated with both acceptance and justificatory beliefs, whereas competitive affectivity exhibits a positive and consistent association with both dimensions. Within the study sample, tolerance scores were higher among male respondents. These findings raise a hypothesis for future research: awareness campaigns may achieve greater precision when they account for psychological heterogeneity. This implication should be tested in broader and more diverse populations. Drawing on this exploratory evidence, we propose a preliminary analytical model that articulates the relationships between dispositional traits and competitiveness dimensions in relation to the two components of tolerance, providing a basis for future research. From a theoretical perspective, the proposed model offers a structured basis for longitudinal testing and future experimental designs aimed at deepening the understanding of the microfoundational mechanisms underlying the informal economy. Full article

As firms increasingly rely on external partnerships to navigate complex and volatile environments, understanding the distinct pathways through which such collaborations may relate to resilience has become essential. However, despite growing interest in interorganizational collaboration, limited research has explicitly examined how university–industry collaboration relates to organizational resilience, as prior studies have predominantly focused on innovation and performance-related consequences. This study examines whether university–industry collaboration is associated with organizational resilience, conceptualized as a micro-foundation of sustainable development. Specifically, it investigates the mediating role of relationship quality within the university–industry collaboration and resilience nexus and the moderating effect of institutional alignment. The proposed research model and hypotheses were tested using survey data collected from 220 firms operating in science and technology parks (STPs) in Türkiye through partial least squares structural equation modeling (PLS-SEM) with SmartPLS. The results indicate that university-industry collaboration exhibits a significant association with organizational resilience, which is also linked to long-term sustainability at both firm and systemic levels. Furthermore, relationship quality serves as a distinct mediating pathway linking university–industry collaboration with organizational resilience. In addition, institutional alignment shows a significant moderating role in this relationship, such that higher alignment between university and industry partners strengthens the collaboration–resilience linkage. This study offers an early empirical attempt to conceptualize university–industry collaboration as an external driver associated with organizational resilience while delineating the distinct processes of mediation and moderation. Drawing on institutional theory and relational coordination theory, the findings elucidate the distinct institutional and relational pathways through which collaborations are associated with organizational resilience. For managers and policymakers, the study underscores the importance of investing in high-quality relationships and institutional congruence to better leverage collaborative partnerships for sustainable organizational resilience. Full article

Small- and medium-sized enterprises (SMEs) operate under conditions of rapid change, competitive pressure and growing informational complexity, while their owner-managers often have limited time and cognitive bandwidth to interpret emerging strategic possibilities. Artificial intelligence (AI) is beginning to change this by extending how firms detect signals, interpret shifting environments and evaluate possible strategic responses. However, existing work in dynamic capabilities, sensemaking and microfoundations does not fully explain how AI-augmented cognitive systems shape organisational interpretive capacity, strategic adaptability and sustainable competitive positioning. This article addresses that gap by developing Strategic Edge Architecture (SEA), a sociotechnical microfoundational theory of how AI-augmented cognitive infrastructure enhances environmental sensing, prospective sensemaking, adaptive strategic response and sustainability integration in SMEs. Drawing on a multiparadigm theoretical synthesis, this article integrates insights from strategic management, organisational cognition, microfoundations, AI governance and sustainability strategy. SEA conceptualises strategic capability as an emergent property of cognitive infrastructure within which human and AI systems interact to support environmental interpretation, strategic adaptation and sustainable growth. The framework proposes a causal pathway through which AI augmentation strengthens sensing and sensemaking, with human-in-the-loop governance acting as a key moderating condition. The article concludes with formal propositions to guide future empirical research on AI-augmented organisational cognition, whilst recognising that the framework’s claims remain inferential and require empirical examination before SEA’s explanatory power can be assessed. Full article

Digital transformation and artificial intelligence are increasingly being recognized as strategic enablers of sustainable organizational performance, yet the mechanisms linking them to sustainability outcomes remain fragmented, particularly regarding the microfoundations of organizational intelligence. This study reviews how digital transformation and artificial intelligence contribute to sustainable performance through organizational intelligence from a microfoundational perspective. A systematic literature review followed the Preferred Reporting Items for Systematic Reviews 2020 guidelines, using Scopus and Web of Science and covering peer-reviewed studies published between 2018 and 2026. Sixty studies were selected and analyzed through narrative and thematic synthesis. The findings suggest that digital transformation provides digital infrastructure, connectivity, and data integration, while AI supports prediction, automation, analytics, and decision-making. However, neither is consistently linked to sustainable performance in isolation. Their contribution appears to depend on individual skills, organizational capabilities, and process-level routines. The review also shows that economic, environmental, and social performance follow different pathways and require different configurations. Persistent gaps include conceptual fragmentation, proxy constructs for organizational intelligence, limited multilevel integration, and weak empirical modeling of internal mechanisms. Overall, digital transformation and artificial intelligence are more plausibly linked to sustainability when embedded in capability-driven configurations that transform information into coordinated organizational action. Full article

Using panel data from Chinese cities spanning 2010–2023 and leveraging the natural experiment provided by the establishment of the National Big Data Comprehensive Pilot Zone (NBDPZ), we employed the difference-in-differences (DID) method alongside double machine learning (DML) to systematically examine how these policies influence urban economic resilience efficiency. The empirical results demonstrate that the NBDPZ significantly enhances urban economic resilience efficiency. This finding is robust under parallel trend and placebo tests, confirming that the improvement is a policy-driven causal effect. Mechanism analysis reveals that the policy enhances urban economic resilience efficiency primarily by promoting the upgrading and rationalization of industrial structure to consolidate the micro-foundation of sustainable economic transformation; increasing innovation output to facilitate the sustainable accumulation of knowledge capital; and enhancing urban entrepreneurial activity to inject sustainable endogenous vitality into the economic system. Heterogeneity analysis indicates that the positive effects are more pronounced in eastern and western regions, second-tier cities, and cities with lower industrial agglomeration, better digital infrastructure, and stronger legal and regulatory environments. The study’s findings offer both theoretical support and practical guidance for refining the policy framework of the NBDPZ policy and promoting sustainable urban economic development. Full article

Hyperscale data center construction has become one of the largest concentrated capital flows in the global built-environment sector, with global hyperscale capital expenditure exceeding USD 230 billion in 2024 and the leading hyperscalers committing more than USD 325 billion for 2025. Generative artificial intelligence workloads have driven a structural shift in mechanical and electrical design, increased delivery-pace demands, and concentrated supply-chain pressure on a small number of specialist general contractors. This paper develops and tests a microfoundational model of dynamic capabilities for hyperscale data center project delivery using fuzzy-set Qualitative Comparative Analysis (fsQCA) on a sample of N = 18 primarily North American hyperscale-active general contractors. Capabilities are formalized as fuzzy sets X ⊆ Ω with membership functions μ_X: Ω → [0, 1] over the case space Ω; necessity and sufficiency consistency are computed using the canonical formulas Cons_N(X→Y) = Σ_i min(μ_X(i), μ_Y(i))/Σ_i μ_Y(i) and Cons_S(C→Y) = Σ_i min(μ_C(i), μ_Y(i))/Σ_i μ_C(i), and necessity is interpreted as the fuzzy-set containment PDP_high ⊆ X. Capability scores are coded from secondary public sources—ENR rankings, SEC filings, trade press, and company disclosures—rather than from primary survey or interview data. Three findings emerge: process microfoundations and seizing capability are necessary conditions for both project delivery performance and competitive advantage (Cons_N ≥ 0.97); the dominant causal recipe for high project delivery performance is the conjunction SEN ∩ SEI ∩ TRA ∩ ED with consistency 1.000 and coverage 0.771; the dominant recipe for high sensing capability is the conjunction IND ∩ PRO ∩ STR ∩ INT with consistency 1.000 and coverage 0.799. The findings are positioned against prior dynamic-capabilities studies and microfoundations theory, confirming convergence on conjunctive bundle structure while extending literature into a previously unstudied AEC segment with sharper containment relations. Full article

Ensuring that government-led large-scale online public services evolve from formal participation to substantive quality represents a key governance challenge. This study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating value identity as a core value-rational driver and by taking self-reported teaching practice quality as the ultimate outcome variable. Based on a cross-sectional survey of 2226 teachers analyzed via structural equation modeling, our findings reveal a stark ‘Governance Paradox’: at the aggregate level, both Behavioral Intention (β = −0.213) and Social Influence (β = −0.098) are unexpectedly associated with lower self-reported teaching practice quality, despite Value Identity being a powerful predictor of intention (β = 0.900). We conceptualize this statistical paradox not as an anomaly, but as a diagnostic for misaligned subsystems within a complex socio-technical system. Crucially, this paradox is systematically resolved through multi-group analysis; disaggregating the sample by institutional context reveals the expected positive relationships within homogeneous subgroups. This suggests that hidden heterogeneity and contextual factors are responsible for distorting the aggregate picture. Theoretically, this research offers two contributions: it reframes statistical aggregation artifacts as a systems-diagnostic framework for governance and introduces “Motivation Fusion” as a micro-foundational mechanism to explain the institutional and psychological conditions that produce such artifacts. Practically, the study provides a micro-foundational diagnostic framework for designing more targeted and effective public service policies. Full article

This study examines the impact of Japan’s energy policy on sustainable economic growth from 2005 to 2025. The analysis involved adding carbon externalities to a DSGE model to evaluate the effects of a carbon tax, a renewable energy subsidy, and energy-efficiency improvements. All policies are uniformly assessed within a unified, dynamic, micro-founded macroeconomic model that links energy use and emissions. According to the empirical findings, the carbon tax is the most effective policy for reducing emissions (6.8%). Nonetheless, this improvement incurs economic costs, as output and welfare fall by 0.85% and 0.35%, respectively. Renewable energy subsidies have no unbalanced effect. They reduce emissions by 3.2%. However, they support output by 0.42% and welfare by 0.28%. It occurs through substitution and investment effects. The most prominent outcomes of energy-efficient design are 1.2% increase in output, 0.75% increase in welfare, and 2.5% decrease in emissions. It also indicates the degree of decoupling. The carbon price is vital to achieving decarbonization; however, policies that support improved energy efficiency and clean energy could be accompanied by differential pricing. Findings indicate that a coordinated policy mix would be most effective for Japan in meeting emissions targets without harming growth or improving welfare. Full article

Total factor productivity (TFP) acts as the core micro-foundation for enterprises to enhance resource allocation efficiency, thereby fundamentally boosting their sustainable development capability and long-term sustainability performance. Based on differentiated exposure to the R&D additional deduction policy (the R&D policy), this paper explores TFP disparities and heterogeneous responses among intelligent manufacturing enterprises, together with potential mechanisms. The results indicate that enterprises with access to the R&D policy present higher TFP levels on average and show noticeable differences in TFP performance relative to non-affected enterprises. Mechanism tests suggest that the R&D policy is associated with relieved financing constraints, strengthened R&D willingness, and optimized allocation of R&D resources, which may jointly correlate with the variation in enterprise TFP. Further heterogeneous analysis demonstrates that such disparities in TFP performance are more pronounced in enterprises with high labor intensity, low capital intensity, slow industrial technology iteration, eastern regional distribution, and large scale. This paper clarifies the differential performance characteristics and potential influencing pathways of enterprise TFP under the context of the R&D policy, and provides empirical evidence and practical references originating from China for relevant policy research in other countries and regions. Full article

This conceptual article introduces knowledge-centric recruitment (KCR) as a distinct dynamic capability that reframes recruitment and post-hire socialization as strategic knowledge-development activities. (1) Background: Unlike conventional vacancy-driven approaches, KCR is a proactive process through which firms deliberately access and import external organizational capabilities embodied in senior professionals—termed knowledge-hires—from rival organizations. These knowledge-hires embody tacit, socio-cognitive building blocks of capabilities developed through involvement in their prior employers’ routines and practices. (2) Methods: This article develops a micro-foundational model of KCR comprising four interrelated processes: external capability scanning and prioritization, identification of target capabilities and knowledge-hires, evaluation through the novel lens of contextual capability fit, and expectations of adaptation during onboarding. (3) Results: Contextual capability fit integrates complementary and supplementary quality with knowledge distance to enable firms to forecast both the strategic value of inbound capabilities and the hire’s expected socialization difficulty. (4) Conclusions: The primary theoretical contribution lies in advancing the learning-by-hiring literature by shifting the focus from passive knowledge diffusion to deliberate, calculative capability acquisition. By integrating insights from the knowledge-based view, person–organization fit, absorptive capacity, and strategic recruitment, the KCR model offers a coherent micro-foundational framework for transforming employee mobility into a source of sustained competitive advantage. Full article

How non-dominant specialized firms sustain systemic innovation influence in modular service ecosystems without occupying architectural control positions remains theoretically underdeveloped. This study develops a dual-path Resource–Strategy–Capability (R–S–C) mechanism framework to explain how structurally distinct network positions generate divergent innovation trajectories among non-dominant firms. The empirical analysis draws on large-scale patent collaboration network data from China’s autonomous driving industry, covering 26 hidden champion firms and 14 global leading enterprises across 2009–2023. The framework identifies two divergent pathways: firms occupying structural hole positions adopt specialization-deepening strategies that build module-anchoring capabilities, while firms with high betweenness centrality adopt T-shaped strategies that build interface-bridging capabilities—both enabling systemic influence without architectural control. To make the resource construct theoretically precise, the framework distinguishes four categories of network-derived resources operative in the R–S–C mechanism—informational, coordination, reputational, and module-definition resources—and specifies three microfoundational processes through which strategic orientation translates into capability: experiential learning, codification of routines, and legitimation through external recognition. Institutional policy environments moderate these mechanisms by reshaping network structural heterogeneity rather than directly driving firm outcomes. The study challenges the canonical prediction of structural hole theory by demonstrating that brokerage positions generate specialization deepening rather than scope expansion when absorptive capacity constraints are binding, extends service ecosystem theory by introducing non-dominant firm pathways to systemic value co-creation, and reframes institutional policy as a network-structural moderator with transferable implications beyond the Chinese context. Full article