How Technological Gaps and Institutional Voids Influence Green Global Value Chains—A Systematic Literature Review
Abstract
1. Introduction
2. Literature Review
3. Methodology
3.1. Question Formulation
3.2. Locating Studies
3.2.1. Information Sources and Database Coverage
3.2.2. Search Strategy
3.2.3. Search Saturation
3.2.4. Timeline Justification
3.3. Study Selection and Evaluation
Screening & Coding Reliability
3.4. Analysis and Synthesis
3.4.1. Data Collection and Thematic Coding Procedure for Framework Building
3.4.2. Quality Assessment/Risk of Bias Evaluation
4. Results
4.1. Results of the Bibliometric Analysis
4.1.1. Employed Methods
4.1.2. Two-Dimensional Evidence Map of Identification Strategies and Outcomes
4.1.3. Industrial Sector and Geographical Skew
4.1.4. Theoretical Lens
4.1.5. Three-Field Plot (Authors—Keywords—Sources)
4.1.6. Most Local Cited Sources
4.1.7. Keyword Co-Occurrence Analysis Summary (VOSviewer)
4.2. Results of the Content Analysis and Framework Building
4.2.1. Institutional Voids’ Influence on GVC Environmental Performance
Role of Green Governance
Market Conditions
Green Strategies
4.2.2. Technological Gap Influence on GVCs Environmental Performance
Moderating Role of Research and Development
GVC Embedding Modes and Technology Gap
5. Discussion and Future Research Agenda
5.1. Theoretical Gaps
5.2. Methodological and Contextual Gaps
6. Conclusions
6.1. Managerial Contributions
6.2. Practical Implications
6.3. Limitations of the Study
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
| GVC | Global Value Chain |
| IB | International Business |
| NA | Not available |
| DVA | Decomposition Value Added |
| SPPLM | Semi-Parametric Partially Linear Model |
| HEM | Hypothetical extraction method |
| DiD | Difference-in-Difference |
| GEM | Gravity Equation Model |
| IOA | Input Output Analysis |
| ML | Maximum Likelihood |
| GMM | Generalized Method of Moments |
| SEM | Structural Equation Modeling |
| LTBs | Liquid Transportation Biofuels |
| GHG | Greenhouse Gas |
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| Title | Journal | Authors | Contribution |
|---|---|---|---|
| Global value chains and the environmental sustainability of emerging market firms: A systematic review of literature and research agenda. | International Business Review | [1] | The systematic review examines the environmental viability of emerging market firms (EMFs) integrated into global value chains. |
| A Systematic Literature Review of the Environmental Upgrading in Global Value Chains and Future Research Agenda | Journal of Distribution Science | [14] | An in-depth review of environmental upgrading is the least studied area in the GVC literature. |
| Global value chains: A review of the multidisciplinary literature | Journal of International Business Studies | [15] | This article reviews the rapidly expanding global value chain (GVC) research field by analyzing several highly cited conceptual frameworks and evaluating GVC studies published across various disciplines. |
| Nurturing International Business research through Global Value Chains literature: A review and discussion of future research opportunities | International Business Review | [16] | This article provides comprehensive theoretical concepts and analytical tools to understand and assess value-creation models in light of the new international division of labor. |
| International business sustainability and global value chains: Synthesis, framework, and research agenda | Journal of International Management | [11] | Comprehensively encapsulates the current state of research on GVCs, focusing on sustainability standards, policies, and their association with GVCs in the context of international trade. |
| Reference | Focus | Method | Sample | Author’s Added Novelty |
|---|---|---|---|---|
| [1] | (GVC, emerging markets, environmental sustainability) | SLR | 64 | This research does not explicitly analyze the joint effects of institutional voids and technological gaps on environmental performance, nor does it develop a theory-driven, testable conceptual framework. |
| [14] | Environmental upgrading in Global Value Chains (GVCs) | SLR | 12 | Our work develops a theory-driven framework that links the effects of institutional voids between developing and developed countries and technological gaps to overall global value chain environmental performance, and does not focus solely on environmental upgrading. |
| [15] | GVC literature | SLR | 87 | Technology effects are less addressed in this review. Our review, aiming to extend beyond the multi-disciplinary synthesis of GVC literature, examines specific drivers of environmental performance in GVCs, integrating firm- and country-level factors that have been largely overlooked in broad GVC reviews. |
| [16] | GVC literature | SLR | 30 | Beyond focusing solely on the nexus between International Business (IB) and Global Value Chain (GVC) research, we propose a more focused theoretical and methodological research agenda that addresses underexplored contexts, mechanisms, and empirical opportunities at the intersection of environmental performance and GVC research. |
| [11] | International business sustainability and global value chains | SLR | 77 | This research focuses on sustainability by considering both environmental and social effects in the GVC literature, without providing a deep and rich focus on context-specific influencing factors for environmental performance alone. |
| Full Boolean Query (Wildcards, Field Limits, Logic Operators, Extraction Date, and Counts per Stage) | |
|---|---|
| Web of Science (ISI) | |
| Extraction date | 7 November 2024 |
| #1 = | Title = ((“global value chain” OR “GVC” OR “Value chain*”)) |
| #2 = | Title = ((“Environment*” OR “Green” OR “Ecolog*” OR “Sustain*” OR “Eco-Friendly”) OR (“Carbon” OR “Gaz emission” OR “emission*” OR “Pollution” OR “waste” OR “waste management” OR “Climate” OR “Climate change” OR “energy”) OR (“green governance*” OR “institutional environment” OR “green policy*” OR “Corporate social responsibility*” OR “CSR” OR “Green invest*”) OR (“ESG” OR “Environmental Social Governance” OR “green governance*” OR “institutional environment” OR “green policy*” OR “Corporate social responsibility*” OR “CSR” OR “Green” OR “Strategy”) OR (“Organizational Capabilities” OR “Technology” OR “Skills*” OR “Green invest*” OR “green initiatives” OR “Green practices” OR “Ethic*”) OR (“Factor*” OR “Determinant*” OR “Influence” OR “Impact” OR “Driver*” OR “Antecedent*”)) |
| #3 = | Topic = ((“Organization” OR “Enterprise” OR “firm” OR “industry” OR “Compa*” OR “Business”)) |
| #4 = #1 AND #2 | 1720 documents |
| #5 = #4 AND #3 | 971 Documents |
| #6 = | #5 and (Document Types) peer-reviewed articles only |
| #7 = | #6 and English (Languages) |
| #8 = | #7 + (Publication Years: 2012 or 2013 or 2014 or 2015 or 2016 or 2017 or 2018 or 2019 or 2020 or 2021 or 2022 or 2023 or 2024) |
| Duplication | Internal duplicates were checked using Excel, and among the 897 articles extracted from Web of Science, no internal duplicates were identified. |
| Final results | 897 peer-reviewed scientific articles in English languages were date of publication is between (2012 and 2024) |
| Step 01: Initial data extraction from (Web of Science, EBSCO, ProQuest) | |||
| Inclusion criteria: Peer-reviewed articles, English only, published between 1 January 2012 and 31 December 2024. Exclusion criteria: Magazines, conference papers, policy documents, theses, book chapters, articles published before 2012, articles published in languages other than English, and non–peer-reviewed articles. | |||
| DB | Web of Science | EBSCO | ProQuest |
| Counts | 897 | 274 | 435 |
| Total | 1606 articles | ||
| Duplications found across the three databases were identified and excluded (n = 590). | |||
| Step 02: Screening of articles based on: (Title, abstract and keywords) | |||
| Inclusion criteria: Articles whose titles or abstracts include the term ‘global value chain’ together with environmental performance or related sustainability keywords (e.g., green transition, eco-friendly practices, sustainability, ecological performance). | |||
| Exclusion criteria: Articles that do not address the nexus between global value chains and environmental performance, or that discuss these topics independently without establishing a clear relationship between them. | |||
| Databases | Web of Science | EBSCO | ProQuest |
| Counts (n = 1016) | 650 | 35 | 331 |
| Included (n = 421) | 290 | 16 | 115 |
| Excluded (n = 227) | 160 | 12 | 55 |
| Step 03: Full text screening based on methodology and quality assessment | |||
| Inclusion criteria: Empirical studies that explicitly examine the relationship between global value chains (GVCs) and environmental performance, articles that identify, test, or analyze determinant variables influencing environmental performance within GVCs, or studies providing quantitative or qualitative data allowing for the assessment of factors or mechanisms shaping environmental outcomes in GVCs. We designed quality assessment criteria related to research design, industry choice, sample size, data collection method, and analysis transparency to ensure a relevant final selection of articles, facilitating a better mapping for our bibliometric and content analysis and addressing the research questions. Each study was independently reviewed by two researchers, and any discrepancies were resolved through discussion. Studies rated as low quality were excluded from the synthesis, and the reasons for exclusion are provided below. | |||
| Exclusion criteria: Articles out of context or not aligned with the research objectives; papers focusing on technical, engineering, or mathematical modeling unrelated to environmental performance in GVCs; theoretical, conceptual, systematic review, umbrella, meta-analysis, or sociometric review papers without empirical validation; and studies whose methodology or results do not identify or analyze variables significantly affecting environmental performance in GVCs. | |||
| Included (n = 194) | 130 | 04 | 60 |
| Articles suggested by experts (n = 07) all the articles were identified in the initial screening. | |||
| Step 04: final exclusion after methodology check and full article analysis | |||
| Exclusion reasons in the final stage: | |||
| Out of context, not aligned with our research objectives, or using irrelevant variables in the empirical section (n = 55). | Technical and mathematical papers (n = 19). | Theoretical, conceptual, systematic review, umbrella, meta-analysis, and sociometric review papers (n = 18). | The methodology and empirical results do not identify any significant variables that influence environmental performance in GVCs (n = 46). |
| Total articles excluded (n = 55 + 19 + 18 + 46 = 138 articles). | |||
| Included studies in the systematic review (n = 56 articles (See Table S4)). | |||
| Symmetric Measures (Step 01) | ||||
|---|---|---|---|---|
| Value | Asymptotic Standard Error a | Approximate T b | Approximate Significance | |
| Kappa agreement | 0.900 | 0.014 | 28.707 | 0.000 |
| n of Valid Cases | 1016 | |||
| Symmetric Measures (Step 02) | ||||
|---|---|---|---|---|
| Value | Asymptotic Standard Error a | Approximate T b | Approximate Significance | |
| Kappa agreement | 0.976 | 0.011 | 20.028 | 0.000 |
| n of Valid Cases | 421 | |||
| Symmetric Measures (Step 02) | ||||
|---|---|---|---|---|
| Value | Asymptotic Standard Error a | Approximate T b | Approximate Significance | |
| Kappa agreement | 0.975 | 0.017 | 13.587 | 0.000 |
| n of Valid Cases | 194 | |||
| Final Decision per Author | |||
|---|---|---|---|
| Author 01 | Author 02 | Agreement (%) | |
| Included | 56 | 56 | 100% |
| Conceptual/Theoretical/Review | 18 | 16 | 88.88% |
| No listed determinants | 46 | 46 | 100% |
| Not relevant | 55 | 55 | 100% |
| Technical/Mathematical modelling | 19 | 19 | 100% |
| Authors | Method | Region | Industry | Credibility-Triangulation | Transferability | Quality Tier |
|---|---|---|---|---|---|---|
| [30] | Interviews | Global | Tanker | High-Moderate | ||
| [46] | IOA | Ireland | Aquaculture | Moderate-High | ||
| [22] | Case study | Asia | IT sector | High | ||
| [24] | Case study | Sweden | LTB | Moderate | ||
| [33] | Case study | Global | Fish industry | High-Moderate | ||
| [47] | Action research | Guatemala | Coffee sector | High | ||
| [34] | Case study | Kenya–UK | horticulture | Moderate | ||
| [48] | Case study | Italy | Leather industry | Moderate | ||
| [25] | Case study | Europe, North America | Maritime transport | High | ||
| [43] | Case study | Italy | Home-furnishing | Moderate | ||
| [49] | Case study | Global | the wine and coffee | Moderate | ||
| [50] | Comparative study | China, India | Clothing, Tea | Moderate | ||
| [51] | Case study | Italy | Wine | Moderate | ||
| [52] | Interviews | Pakistan | apparel | Moderate | ||
| [53] | Interviews | Northern Europe | Plastics | Moderate | ||
| [54] | Case study | NA | Natural Fiber-Based | Moderate |
| Authors | Method | Region | Industry | Model Quality | Endogeneity Treatment | External Validity | Quality Tier |
|---|---|---|---|---|---|---|---|
| [55] | Pareto-optimal | South Africa | Iron and steel | High | |||
| [56] | DVA | China | Manufacturing | High | |||
| [57] | DVA | China | Manufacturing | Moderate | |||
| [31] | Linear regression | China | Manufacturing | Moderate | |||
| [58] | Linear regression | China | Manufacturing | High | |||
| [59] | ML | China | Manufacturing | Moderate | |||
| [60] | SPPLM | NA | NA | Moderate | |||
| [61] | DVA | China | NA | Moderate | |||
| [62] | DVA | Germany | NA | Moderate | |||
| [63] | Linear regression | Developing countries | Manufacturing | High | |||
| [64] | Probit model | Europe | Restructuring | High | |||
| [65] | Tobit model | China | Manufacturing | Moderate | |||
| [66] | Linear regression | China | Import and Export | High | |||
| [26] | HEM | China, United States | Global trade | High | |||
| [67] | Panel estimation | Belt and Road countries | Manufacturing | High | |||
| [23] | IOA | Emerging economies | IT sector | High | |||
| [68] | Fuzzy analysis | China | Manufacturing | Moderate | |||
| [29] | Panel estimatio | China | Manufacturing | High | |||
| [69] | DiD | China | Energy | High | |||
| [70] | Threshold model | Brazil, Russia, India, China, Mexico | Manufacturing | High | |||
| [12] | GMM | Global | NA | Moderate | |||
| [13] | IOA | Global | Energy | Moderate | |||
| [6] | Tobit model | Global | Manufacturing | High | |||
| [4] | Panel estimation | China | Manufacturing | High | |||
| [3] | IOA | Asia | Energy | High | |||
| [71] | Linear regression | China | Manufacturing | High | |||
| [72] | Linear regression | China | Manufacturing | High | |||
| [73] | DVA | China | Manufacturing | Moderate | |||
| [74] | Linear regression | Global | Energy | High | |||
| [28] | Panel estimation | Global | industrial sector | High | |||
| [75] | Tobit model | China | Manufacturing | High | |||
| [21] | DVA | China | Manufacturing | High | |||
| [27] | DVA | China | Manufacturing | High | |||
| [76] | IOA | Global | Manufacturing | High | |||
| [32] | DiD | China | Import and Export | Moderate | |||
| [77] | SEM | China | Manufacturing | High | |||
| [20] | Linear regression | China | Manufacturing | Moderate | |||
| [78] | GEM | NA | ICT | High |
| Identification Method | Total | Promote | Hinder | Ambiguous |
|---|---|---|---|---|
| DVA | 07 | 03 | 01 | 03 |
| Pareto optimal | 01 | 01 | ||
| Fuzzy analysis | 01 | 01 | ||
| DiD | 02 | 02 | ||
| GMM | 01 | 01 | ||
| HEM | 01 | 01 | ||
| IOA | 04 | 01 | 03 | |
| Linear regression | 09 | 05 | 04 | |
| ML | 01 | 01 | ||
| Panel estimation | 04 | 04 | ||
| Probit model | 01 | 01 | ||
| SPPLM | 01 | 01 | ||
| SEM | 01 | 01 | ||
| GEM | 01 | 01 | ||
| Threshold model | 01 | 01 | ||
| Tobit model | 03 | 02 | 01 |
| Journal | Frequency |
|---|---|
| Science of The Total Environment | 2 |
| Economy and Space | 2 |
| Economic Geography | 2 |
| Energy economics | 2 |
| Energy Policy | 3 |
| Frontiers in Environmental Science | 5 |
| Environment, Development and Sustainability | 3 |
| International journal of environmental research and public health | 3 |
| Journal of Cleaner Production | 5 |
| Review of International Political Economy | 2 |
| Structural Change and Economic Dynamics | 2 |
| Sustainability | 5 |
| Technological Forecasting and Social Change | 3 |
| Others less than 01 | 27 |
| Theoretical Lens | |
|---|---|
| No theory | 41 |
| Added-value trade theory | 1 |
| Economic growth theory | 1 |
| Environmental Kuznets curve (EKC) | 1 |
| Pareto-Optimal | 1 |
| GVC theory | 4 |
| Networks Theory | 1 |
| Signaling theory | 1 |
| Stakeholder theory | 1 |
| Innovation theory | 2 |
| organizational theory | 1 |
| Economic growth theory | 1 |
| Smile Curve Theory | 1 |
| Polution Heaven Hypothesis | 1 |
| Competitive advantage theory | 1 |
| The externality theory | 1 |
| Resource allocation distortion theory | 1 |
| Government Role, Instruments, and Enabling Factors for Environmental Performance in GVCs | ||||
|---|---|---|---|---|
| Dimension | Role/Mechanism | Challenges | Impact on Green GVCs | References |
| Environmental regulation | Set entry standards, incentivize cleaner production, penalize polluting industries | Higher compliance costs for firms, especially in developing countries; risk of carbon leakage; uneven adoption | Encourage green practices if adapted to local conditions; reduce GHG emissions in well-regulated regions; may shift pollution to less-regulated regions | [31,49,55] |
| Policy adaptation to local conditions | Tailor environmental policies to the economic and institutional context of each region | Complexity of local implementation; requires understanding of firm-level capabilities and GVC positioning | Makes regulations more effective; mitigates risk of pollution relocation; supports equitable green transition | [64,79] |
| International trade and carbon leakage | Address pollution displacement through cross-border trade | Weak regulations in developing countries attract high-emission industries; long-term environmental degradation | Need for coordination across countries to prevent “pollution havens”; may affect MNE market choice | [65,76] |
| Innovation and green technology promotion | Properly designed standards can drive innovation and resource productivity | High costs; lack of government financial support; governance challenges | Can foster low-carbon technologies, industrial competitiveness, and sustainability in GVCs if coupled with incentives | [12,31,65] |
| Micro-Firm Considerations | Influence depends on firm characteristics (financial and innovation capabilities) | Limited resources may prevent adoption of green technologies; dependence on external support | Determines success of green upgrading in smaller GVC actors | [2,12,73] |
| Lead Firm’s Role, Instruments and Enabling Factors for Environmental Performance in GVCs | ||||
|---|---|---|---|---|
| Dimension | Role/Mechanism | Role in Green Governance | Conditions and Factors Affecting Effectiveness | References |
| Governance Type | Lead firms/relational governance; hybrid between public and private governance | Develop governance instruments for sustainability outcomes. | Local political dynamics, Cross-country disparities (economic growth and inequalities levels) | [47,66,75] |
| Power | Act as power holders in GVCs; influence subsidiaries and suppliers | Legitimize the adoption of green standards in developing countries | Trust, Coordination and control mechanism, distance management | [55,83] |
| Risk management | Extract value by pushing compliance costs and risks upstream | Leverage profit maximization while driving green practices | Hidden costs often not visible to consumers, governments, or NGOs | [49] |
| Knowledge transfer | Cooperation with subsidiaries, suppliers, distributors | Facilitate green values transition from developed to developing countries | Limited by suppliers’ financial capabilities and access to immaterial resources (knowledge, expertise) | [64,79] |
| Multi-stakeholders’ collaboration | Cooperation with subsidiaries, suppliers, distributors | Collaborative problem-solving; greening production, shipping, product design, and consumption | Interplay shaped by complex transnational and local public–private intersections | [47] |
| Constraints | Standards’ implementation, sourcing practices, financial barriers | Green strategies limited by firm resources; sourcing pressures can undermine social/environmental outcomes | Buyer support, cost of environmental upgrading, exploitative labor conditions, and environmental shortcuts | [53] |
| Authors | Method | Technology Type | Green Performance Indicator | GVC Level | Direction Results |
|---|---|---|---|---|---|
| [88] | Interviews | Water management technologies | Sustainable practices | Firm and national level | Positive |
| [46] | IOA | Low carbon technologies | GHG emissions per sector | National level | Promote/conditional |
| [56] | DVA | Low carbon technologies | GHG emissions | Regional level | Mixed/conditional |
| [57] | DVA | Green technologies | GHG emissions | National level | Mixed/conditional |
| [31] | Linear regression | Green technologies | Green factor productivity | Firm level | Positive |
| [90] | Linear regression | Technology gap | GHG emissions | National and firm level | Positive |
| [60] | SPPLM | Not mentioned | GHG emissions | National | U-shaped relationship |
| [62] | DVA | Not mentioned | GHG emissions | Intersectoral | Positive |
| [63] | Linear regression | Clean energy technologies | sustainable practices | Firm level | Mixed/conditional |
| [65] | Tobit model | Low carbon technologies | Innovation performance | Firm level | Mixed/conditional |
| [66] | Linear regression | Advanced technologies | Production efficiency | Firm level | Indirect and conditional |
| [67] | Panel estimation | Low carbon technologies | GHG emissions | National level | Spillover effect |
| [23] | IOA | Carbon intensity- technologies | GHG emissions | National level | Positive |
| [70] | Threshold model | Low carbon technologies | Pollution intensity | National level | Threshold effect |
| [12] | GMM | Technology gap | GHG emissions | National level | Mediation effect |
| [13] | Input-Output Analysis | Technology gap | GHG emissions | National level | Negative |
| [6] | Tobit model | Not mentioned | GVC position index | National level | Positive |
| Theory | Gap | Potential Research |
|---|---|---|
| Internationalization theory | Many firms base their market entry choices on the environmental context of their chosen countries. Therefore, this area needs to be investigated to see how weak environmental regulation and green policy support influence the attraction of foreign direct investments and partnership opportunities. |
|
| Institutional theory | Despite the divergence between the different actors participating in GVCs regarding the country’s economic characteristics and the institutional environment, Environmental norms cannot be uniformized for all. Policy makers should build personalized norms depending on each context, and how these norms will facilitate in order to hinder their participation in the global market |
|
| Pollution Heaven Hypothesis | Firms that do not consider green outcomes tend to relocate their activities to countries with less environmental control. Therefore, further investigation is needed, focusing on how firms’ environmental practices influence their location choices. Moreover, what are the consequences of these kinds of pollution haven transfer on the country’s environmental reputation and future collaboration with firms that mainly consider green values in their production systems. |
|
| Stakeholder theory | There is a need to examine how firms in developed countries, engaged in business or partnerships with firms possessing limited environmental capabilities, can establish cooperative frameworks to address green values within global value chains (GVCs). This cooperation should be context-dependent, tailored to the specific environmental, regulatory, and economic circumstances of each partner, while fostering collaboration and mutual adaptation to achieve green outcomes. |
|
| Internalization theory | Companies also have different organizational and technological dynamics. Corporate objectives may diverge: firms in advanced countries generally focus on environmental compliance and creating meaningful environmental and societal value, while firms in emerging economies, facing lower income levels, prioritize economic value generation, often at the expense of environmental and societal issues. Moreover, these firms are less compelled to create environmental and societal value and question the profitability of environmentally sustainable investments. Due to limited investment capabilities and lower revenues, they struggle to adopt the standards imposed by large Western firms with strong financial capacity. |
|
| Technology Acceptance Model | The digital divide and varying levels of maturity among actors within the SME chain can present a significant challenge, particularly for firms with limited connectivity, hindering their ability to transition to greener production systems. This issue is not only related to firms’ capacity to adopt green technologies but also to macro-environmental factors, such as a country’s level of openness and foreign direct investment, which can provide access to knowledge and technology. Future research should explore this area further. |
|
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Belabbas, I.; Su, Z. How Technological Gaps and Institutional Voids Influence Green Global Value Chains—A Systematic Literature Review. Sustainability 2026, 18, 1609. https://doi.org/10.3390/su18031609
Belabbas I, Su Z. How Technological Gaps and Institutional Voids Influence Green Global Value Chains—A Systematic Literature Review. Sustainability. 2026; 18(3):1609. https://doi.org/10.3390/su18031609
Chicago/Turabian StyleBelabbas, Imène, and Zhan Su. 2026. "How Technological Gaps and Institutional Voids Influence Green Global Value Chains—A Systematic Literature Review" Sustainability 18, no. 3: 1609. https://doi.org/10.3390/su18031609
APA StyleBelabbas, I., & Su, Z. (2026). How Technological Gaps and Institutional Voids Influence Green Global Value Chains—A Systematic Literature Review. Sustainability, 18(3), 1609. https://doi.org/10.3390/su18031609

