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on Economics of Strategic Management |
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Issue of 2026–06–15
eleven papers chosen by João José de Matos Ferreira, Universidade da Beira Interior |
| By: | Jongduk KIM (KOREA INSTITUTE FOR INTERNATIONAL ECONOMIC POLICY (KIEP)) |
| Abstract: | As U.S.–China competition intensifies, rivalry is also sharpening within the global knowledge system. This raises a central question: how does deepening U.S.–China tension reshape the global innovation network (GIN)—the cross-border web through which knowledge is created, shared, and recombined?<p> Governments worldwide have long emphasized the strategic importance of science, technology, and knowledge. Yet science and technology policy has often been approached primarily as a domestic agenda. In today’s global economic environment—marked by heightened strategic competition—this perspective is increasingly incomplete. The key issues are not only how much a country invests in innovation, but also how its position within global knowledge networks is changing, how geopolitical frictions affect knowledge flows, and what strategic direction policy should take in response.<p> This study therefore focuses on the cross-country and cross-industry structure of technology and innovation. Traditional policy approaches have tended to prioritize expanding total R&D spending. However, innovation cannot be generated by the R&D efforts of a single country, industry, or firm alone. A defining feature of innovation—often underappreciated in policy debate—is its networked and cumulative nature: advances in one sector shape the trajectory of innovation in others, often with long-run effects. Semiconductor progress, for example, does not remain within the semiconductor industry; it underpins innovation in telecommunications, computing, and automobiles. Conversely, knowledge developed in these downstream industries feeds back into semiconductor advances. These interactions occur not only within national borders but also across them, as knowledge diffuses through multiple channels linking countries and sectors. Accordingly, effective R&D allocation and innovation strategy require explicit attention to international and intersectoral “network effects.”<p> Against this backdrop, this World Economic Brief traces how Korea and other major economies—including the United States, China, Japan, and Europe—have evolved within the global innovation network over 2000–2020. Using this network perspective, we examine (i) changing patterns of interdependence and (ii) shifts in countries’ relative positions across key technologies. |
| Keywords: | global innovation network; technology; interdependence; US-China rivalry |
| Date: | 2026–03–04 |
| URL: | https://d.repec.org/n?u=RePEc:ris:kiepwe:022509 |
| By: | Junbin Wang (CIT - Changshu Institute of Technology); Yangyan Shi (Macquarie University [Sydney], CUEB - Capital University of Economics and Business); Xinyu Jiang (ECNU - East China Normal University [Shangaï]); V.G. Venkatesh (Métis Lab EM Normandie - EM Normandie - École de Management de Normandie = EM Normandie Business School) |
| Abstract: | Artificial Intelligence (AI) capabilities are increasingly pivotal for enhancing production system resilience in today's volatile business environments. However, the integration of AI technologies with established organizational information processing and decision-making frameworks remains inadequately understood. Grounded in the Human-Organization-Technology (HOT) fit theory, this study investigates how AI capacity positively influences a firm's operational performance. Using multi-wave survey data collected from 305 manufacturing firms via a professional online platform during the COVID-19 pandemic, we identify critical factors that reinforce this positive effect and elucidate its underlying mechanisms, with particular emphasis on how AI reconfigures organizational information flows and knowledge practices. Partial least squares-based structural equation modeling was employed to test the hypothesized model. The findings reveal a significant positive impact of AI capacity on production system resilience. Furthermore, production system resilience itself exerts a strong positive influence on operational performance. Crucially, production system resilience serves as a key mediating mechanism, through which AI capacity indirectly enhances operational performance. Finally, the degree of fit, conceptualized across task-tool, human-tool, and data-tool dimensions, moderates the positive effect of AI capacity on production system resilience. This research is contextualized within the Chinese manufacturing sector, a major global production hub, and enriches the theoretical discourse on AI capacity and production system resilience from an information management perspective, highlighting its transformative role in organizational information flows, knowledge creation, and data-driven decision processes. |
| Keywords: | Decision-making, Fit, Operational performance, Production system resilience, AI capacity |
| Date: | 2026–04–01 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05629070 |
| By: | Jong Duk Kim (Korea Institute for International Economic Policy (KIEP)); Gusang Kang (Korea Institute for International Economic Policy (KIEP)); Wonseok Choi (Korea Institute for International Economic Policy (KIEP)); Hyunjin Lee (Korea Institute for International Economic Policy (KIEP)); Jun Hyun Eom (Korea Institute for International Economic Policy (KIEP)); Boyeong Park (Korea Institute for International Economic Policy (KIEP)) |
| Abstract: | 본 연구는 새로운 지식(혁신)의 창출 현황을 ‘국가-산업 간 네트워크’ 관점에서 살펴보고 ‘혁신 네트워크’ 참여의 경제적 함의에 대해 분석하였다. 지금까지 정책 입안자들은 기술을 발전시키고 혁신 역량을 강화하면서 의례히 자국의 R&D 투자 총액을 늘리는 데 집중해 왔다. 하지만 현대 사회에서 혁신은 한 국가, 산업 또는 기업의 자체적인 R&D만으로는 달성이 불가능하다. 한 국가 내에서뿐만 아니라 국경을 넘어 다른 나라에서의, 다른 산업에서의 혁신은 또 다른 국가로, 또 다른 산업으로 여러 경로를 통해 공유되고 전파되므로 이 점을 충분히 고려하여 정책을 만들어 나가야 한다. 특히 한국의 경우 네트워크의 중요성은 다시 한번 강조될 필요가 있다. This research project examines the current state of new knowledge creation from the perspective of global knowledge networks and analyzes the economic implications of participating in the so-called ‘innovation network.’ Policymakers have as a matter of course prioritized increasing their own country’s total R&D investment to advance technology and strengthen innovation. This research, however, asserts that in our current economic environment innovation cannot be achieved solely through the R&D of a single country, industry, or company. Policies must be formulated with the full understanding that innovation is shared and disseminated across borders—flowing from other countries and industries to new ones through various channels. For Korea, in particular, participating in these networks are critical. |
| Keywords: | Global Innovation Network;Trade Policy Directions;Technology cooperation;International trade |
| Date: | 2025–12–30 |
| URL: | https://d.repec.org/n?u=RePEc:ris:kieppa:022535 |
| By: | Hung-Ju Chen (National Taiwan University); Hao Guo (Liaoning University); Chien-Yu Huang (International University of Japan); Yibai Yang (University of Macau) |
| Abstract: | This study explores the cross-country effects of inflation on innovation and technology transfer in a North-South variety-expansion model. We find that higher southern inflation causes a permanent increase in the North-South relative wage ratio, a temporary decrease in the northern innovation rate, and a permanent decrease in technology transfer. Higher northern inflation causes a permanent decrease in the North-South relative wage ratio, a temporary decrease in the northern innovation rate, and a permanent decrease (increase) in technology transfer if the southern population is sufficiently small (large). We calculate the model to the China-US data to justify the model implications. |
| Keywords: | Inflation; Innovation; North-South product cycles; R&D; Technology transfer |
| JEL: | E41 F43 O30 O40 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:iuj:wpaper:ems_2026_10 |
| By: | Ozili, Peterson K |
| Abstract: | This study examines the asymmetric effect of artificial intelligence (AI) innovation on economic growth in 50 countries from 2000 to 2020 using the quantile regression method. The findings reveal that AI innovation stimulates economic growth at low and middle tail of the economic growth distribution. Interaction analyses reveal that the use of AI innovation in the stock market stimulates economic growth while the use of AI innovation to support financial stability and international trade activities diminish economic growth. Asymmetric interaction analyses reveal that: AI innovation stimulates economic growth when countries are experiencing low growth rates; the use of AI innovation in the stock market stimulates economic growth when countries are experiencing high growth rates and in mid-growth emerging market and developing countries; the use of AI innovation to support financial stability activities diminish economic growth when countries are experiencing low growth rates and the use of AI innovation to support international trade activities diminish economic growth when countries are experiencing high growth rates. |
| Keywords: | Quantile regression, asymmetry, economic growth, artificial intelligence, innovation, internet, financial stability, unemployment, trade openness, endogenous growth theory |
| JEL: | O30 O31 O33 O47 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:128950 |
| By: | Nauman, Khalida; Siddiqui, Danish Ahmed |
| Abstract: | This study investigates the influence of green human resource management (GHRM) practices on employees' in-role and extra-role green behaviors in small and medium-sized enterprises (SMEs) in Karachi, Pakistan. The research examines the direct effects of Green Recruitment and Selection (GRS), Green Training and Development (GTD), and Green Compensation and Benefits (GCB), the mediating role of Green Organizational Culture (GOC), and the moderating effects of Top Management Commitment (TMC), Transformational Leadership (TL), and Employee Green Passion (EGP). Data were collected from 190 employees using purposive sampling and analyzed with structural equation modeling via SmartPLS. Results reveal that GTD significantly enhances in-role green performance, while GRS and GCB have no significant direct effects on employee green behaviors. Mediation analysis shows that GOC does not significantly transmit the effects of GHRM practices. Moderation analysis indicates that TMC strengthens the relationship between GRS and extra-role green behavior, whereas TL positively moderates the GTD-extra-role green behavior link and negatively moderates GRS effects. EGP did not exhibit significant moderating effects. The findings highlight the critical role of training and leadership in promoting sustainable employee behaviors in SMEs, while organizational culture and intrinsic motivation have limited influence in this context. |
| Keywords: | Green Human Resource Management, Employee Green Behavior, Organizational Culture, Transformational Leadership, Top Management Commitment, SMEs, Pakistan |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:341065 |
| By: | Tugrul Temel, Tugrul |
| Abstract: | This paper develops a co-evolutionary network model to analyze how micro-level interactions among heterogeneous organizations generate macro-level structural patterns and performance outcomes in innovation systems. Organizations possess knowledge stocks, absorptive and distributive capacities, and adaptively rewire their connections. We integrate six key mechanisms---capacity-constrained knowledge flows, endogenous capacity accumulation, resource-based collaboration costs, innovation as a growth-structure interaction, strategic repositioning, and adaptive network rewiring---into a formal simulation framework. The model is calibrated using Approximate Bayesian Computation to match stylized facts from the innovation literature and employed in a structured scenario analysis spanning alternative policy-relevant regimes. Results reveal systematic trade-offs with important policy implications. Expanding connectivity without parallel capacity development yields limited gains; isolated capacity building amplifies inequality. In contrast, coordinated interventions targeting both network structure and organizational capabilities produce the most robust and equitable growth. Comparative analysis across four distinct economic environments demonstrates that intervention effectiveness is highly contingent on underlying frictions. The findings underscore the need for innovation policy that is explicitly network-aware and systemic, emphasizing bundled, context-sensitive interventions rather than isolated levers. The model provides a computational laboratory for exploring such policy design principles. |
| Keywords: | innovation systems; policy design; network analysis; graph-theoretic concepts; |
| JEL: | O31 O32 O38 |
| Date: | 2026–02–11 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:128018 |
| By: | Ahmed, Owais; Siddiqui, Danish Ahmed |
| Abstract: | This study explores how the influence of Industry 4.0 technologies affects circular economy (CE) adoption. Drawing on the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT), the study develops a conceptual model incorporating smart manufacturing technologies, data processing capabilities, and IT infrastructure as drivers of digital transformation. We contend that Industry 4.0 technologies such as Smart Manufacturing, and Data Processing technologies, increase Supply Chain integration (SCI), which will in turn enhance Supply chain collaboration, and visibility leading to a Circular Economy (CE). We also infer that the effect of Industry 4.0 technologies on SCI is moderated by IT Advancement in a way that high levels of advancement will make these relationships more pronounced. Using data collected from 343 professionals across diverse industries in Pakistan, the model is tested through Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings reveal that smart manufacturing and data processing technologies significantly enhance SCI, which in turn positively affects collaboration, visibility, and circularity. IT advancement strengthens the relationship between digital technologies and SCI. The study contributes to the theoretical understanding of digital transformation and sustainability and offers practical guidance for firms aiming to build resilient and environmentally responsible supply chains. |
| Keywords: | Industry 4.0, Supply Chain Integration, Circular Economy, Smart Manufacturing, IT Advancement, PLS-SEM, Sustainability |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:341047 |
| By: | Suliman, Abdulhameed; Nihar, Samia; Arabi, Zuhair; Omer, Namariq |
| Abstract: | The study examines how digital inclusion shapes the economic empowerment and resilience of women entrepreneurs in Kassala State, Eastern Sudan, using a mixed‑methods design that combines SLMPS 2022 survey analysis with interviews and focus groups. Grounded in a technological capability and inclusive innovation framework, it conceptualizes digital inclusion as meaningful, safe use of technologies for enterprise functions rather than simple access, and constructs a Women’s Economic Empowerment Index (WEEI) to capture empowerment attitudes. Quantitative findings show that education and household wealth are positively associated with empowerment, while age and marriage correlate negatively, and that basic digital access indicators are not robust predictors of empowerment, suggesting that technology alone is insufficient in the absence of key conversion factors such as skills, affordability, and institutional support. Qualitative evidence explains these patterns by revealing widespread “ownership without business use”, with women constrained by high data and device costs; unreliable electricity and connectivity; low digital skills; and gendered norms and reputational fears that limit public-facing online activity, leading them to rely mainly on low-barrier platforms like WhatsApp and Facebook. The study concludes that digital inclusion contributes to women’s economic empowerment in Kassala only conditionally, depending on the interaction between access, individual capabilities, and enabling ecosystem factors, and argues that policy and programme interventions must move beyond access metrics to address these structural and normative constraints. |
| Keywords: | Digital inclusion, women entrepreneurs, economic empowerment, technological capabilities, inclusive innovation, Women's Economic Empowerment Index (WEEI) |
| JEL: | J24 O3 O33 |
| Date: | 2026–02–10 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:128011 |
| By: | Johann Kortsch; Stefan Raff-Heinen; David Bendig; Martin Murmann; Colin Schulz; Fiona Murray |
| Abstract: | The term “deep-tech innovation” has attracted growing attention in research, policy, and practice, but it is applied inconsistently and lacks an agreed-upon definition. This limits cumulative knowledge building and blurs how deep-tech innovation relates to adjacent concepts. We address this gap by developing a framework that treats deep-tech innovation as a distinct object of inquiry. Using a multi-method design that combines a systematic, integrative, concept-centric literature review and semi-structured interviews with deep-tech founders, we identify twelve defining attributes structured across three levels: invention, venture, and ecosystem. At the invention level (the conceptual core), we specify six attributes: three foundational attributes that capture the scientific and technological basis of the invention, and three attributes that describe its characteristic exposure profile. The remaining six attributes capture recurring implications at the venture level (staged financing strategies, dual scientific and commercial maturation, and the multidisciplinary broadening of teams) and the ecosystem level (multi-actor interactions, specialized incubation support, and industrial de-risking and scaling partnerships). We use this framework to delineate the boundaries of deep-tech innovation, distinguish it from adjacent concepts, and propose an agenda for future research. |
| JEL: | O33 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35255 |
| By: | Han-Teng Liao; Karen Ang |
| Abstract: | Global Business Services (GBS) have emerged as a "living laboratory" for the Twin Transition of Green and Digital Transformation, as multinational corporations (MNCs) face increasing pressure to harmonize digital efficiency with environmental stewardship. Aiming to derive a socio-technical framework, this paper synthesizes Technology Roadmapping (TRM) with the International Telecommunication Union (ITU) ICT-centric innovation ecosystem toolkit. A bibliometric analysis of research clusters reveals an evolutionary shift from basic process automation toward "Sustainable Intelligence, " identifying the GBS unit as a central "operational airlock" that mediates between landscape pressures -- such as the EU's dual mandate and Carbon Border Adjustment Mechanisms -- and niche innovations in AI-native workflows. The study further maps these clusters onto a stakeholder engagement canvas, highlighting how resilient "Middle Power" hubs in Poland, Portugal, and Malaysia are bypassing the middle-income trap to provide a "third way" for global value chains amidst a bifurcated geopolitical cloud. The results offer a data-driven design approach for leaders and entrepreneurial support networks to orchestrate talent and supply chain flows, thereby enriching the conceptual understanding of Industry 5.0 and the role of GBS as a primary mechanism for navigating a volatile, multipolar digital economy. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.12787 |