Purpose of this paper

This research aims to explore how supply chain information integration (SCII) improves green supply chain innovation performance (GSCIP) by analysing essential mediating processes and boundary conditions in supply chains. The study specifically aims to (1) evaluate the direct and indirect impact of SCII on GSCIP, (2) investigate the mediating role of green supply chain learning (GSCL) and assess the moderating influence of green entrepreneurial orientation (GEO), and (3) analyse the sequential mediation of green absorptive capacity (GACAP) and employee green creativity (EGC). By addressing these objectives, the study seeks to provide a comprehensive explanation of the importance of digital information integration for green innovation performance in manufacturing supply chains. This study examines Saudi manufacturing firms and addresses the need for context-specific research on sustainability and logistics, especially in rapidly evolving economies with high environmental and digital transformation goals.

Design/methodology/approach

The proposed research model was examined using partial least squares structural equation modelling (PLS-SEM), which is particularly appropriate for predictive research, complex models, and emerging research contexts (Hair et al., 2021). The investigation used a two-stage process: first, evaluating the measurement model for reliability and validity; second, assessing the structural relationships and testing the hypotheses. To strengthen the robustness and practical relevance of the findings, the study integrates Importance–Performance Map Analysis (IPMA) and Necessary Condition Analysis (NCA) with PLS-SEM. IPMA was used to identify the relative importance and performance of key antecedents influencing GSCIP, while NCA was applied to determine whether specific constructs represent necessary conditions for achieving high levels of green innovation performance. This multi-method analytical approach enables a deeper understanding of both sufficient and necessary drivers of GSCIP within supply chains.

Findings

The findings reveal that SCII has a significant and positive impact on GSCIP. SCII enables manufacturing firms to enhance environmental transparency, coordinate sustainability-related decisions, and support green innovation initiatives across SCPs. The results further demonstrate that GSCL plays an important mediating role, highlighting that information integration must be transformed into shared understanding and collective learning to generate innovation outcomes. The role of GEO as a moderator strengthens the SCII-GSCL relationship, suggesting that firms with proactive, sustainability-oriented strategic postures are better positioned to enhance learning mechanisms when they benefit from information integration. In addition, the study identifies a significant sequential mediation effect: SCII enhances GACAP, which, in turn, stimulates EGC, ultimately leading to improved GSCIP. This finding underscores the importance of organizational capabilities and employee-level creativity in translating knowledge flows into green innovations.

Value

This paper offers several original contributions to green supply chain management literature. First, it advances understanding of green innovation by explaining how SCII translates into GSCIP through both organizational and individual-level mechanisms. Second, by integrating KBV and DCT, the study provides a multi-theoretical framework that clarifies the roles of knowledge transformation and dynamic capabilities in sustainability-driven innovation. Third, the combined use of PLS-SEM, IPMA, and NCA offers novel methodological insights by distinguishing between sufficient and necessary conditions for green innovation performance. Finally, the study enriches empirical knowledge by focusing on Saudi manufacturing firms, an underexplored context undergoing rapid digital and environmental transformation.

Research limitations/implications

This study is subject to several limitations. The cross-sectional research design restricts causal inference, suggesting that future studies could adopt longitudinal approaches to capture dynamic learning and innovation processes. The data were collected from a single country and industry context, which may limit generalizability.

Practical implications

The findings provide clear guidance for supply chain managers and policymakers. Managers should prioritize supply chain information integration as a strategic capability rather than a purely technological investment. Establishing structured learning mechanisms and enhancing GACAP can help firms convert shared information into innovative outcomes.

Purpose

The purpose of this paper is to generate policy-relevant and industry-grounded evidence on how freight transport decarbonisation can be achieved in fast-fashion supply chains without undermining export competitiveness in Global South production hubs. International freight transport remains a significant and growing contributor to global greenhouse gas emissions, with apparel supply chains particularly exposed due to long distances, tight lead times, and frequent dependence on carbon-intensive air freight (UNCTAD, 2023). Despite increasing regulatory attention in importing countries such as the UK, decarbonisation strategies often focus on downstream markets and logistics providers, with limited empirical consideration of upstream production realities in exporting countries (BEIS, 2021).

This research focuses on apparel trade between Sri Lanka and the United Kingdom, a strategically important corridor linking a major Global South textile producer with a high-consumption, policy-active market. Sri Lanka’s apparel sector is central to national export earnings and employment, yet faces structural logistics challenges, including volatility in demand, exposure to air freight cost shocks, and increasing sustainability compliance pressures from international buyers (Marwah, R., & Ramanayake, S. S, 2024). These pressures are particularly pronounced in fast-fashion segments, where speed-to-market incentives frequently conflict with emissions reduction objectives.

The paper aims to demonstrate how a Digital Twin of real-world apparel logistics can be used to reconcile these competing pressures by enabling evidence-based evaluation of alternative freight strategies and policy interventions. Focusing on three product categories (activewear, intimates, and denim) the study examines how differences in lead-time sensitivity, production complexity, and demand volatility shape decarbonisation potential. By embedding producer-side operational data into a Digital Twin modelling framework, the research seeks to identify pathways that reduce emissions, stabilise production planning, and enhance export resilience, while generating actionable insights for UK sustainable freight and trade policy (BEIS, 2021).

Design/methodology/approach

This research employs a mixed-methods, case-based approach centred on developing and applying a bespoke Digital Twin of a Sri Lankan apparel manufacturer’s supply chain for three product categories: activewear, intimates, and denim. The design involves in-person, collaborative engagement with the partner company in Sri Lanka to map logistics processes, collect operational data (e.g., transport modes, lead times, costs, carbon factors), and co-define key performance indicators. The Digital Twin, a dynamic computational model, serves as the primary analytical tool to simulate the end-to-end logistics from Sri Lankan factory to UK distribution. The methodology involves creating a baseline scenario and then running comparative simulations to evaluate the impact of alternative logistics practices (e.g., modal shift from air to sea, production planning adjustments, inventory optimisation) and policy interventions (e.g., carbon pricing, green corridor incentives). The approach is interdisciplinary, integrating supply chain management, sustainability science, and digital modelling to provide a holistic analysis of economic and environmental trade-offs.

Findings

Simulation results from the Digital Twin are expected to indicate that significant emissions reductions can be achieved in UK–Sri Lanka apparel logistics without proportionate increases in total supply-chain costs, provided that decarbonisation interventions are tailored to product-specific characteristics. Across the three product categories, the model is expected to demonstrate whether air freight is a disproportionate contributor to emissions intensity, particularly for activewear and intimates, where short lead times and volatile demand frequently trigger last-minute shipments.

For activewear, the Digital Twin is expected to show that improved production planning and earlier order finalisation could substantially reduce reliance on air freight, enabling a shift towards lower-carbon sea transport with limited impacts on service levels. In the case of intimates, where product complexity and smaller batch sizes increase logistics variability, hybrid strategies combining sea freight with targeted inventory buffers are expected to have the potential to stabilise lead times while reducing emissions. Denim, characterised by longer production cycles and lower fashion volatility, is expected to exhibit the greatest decarbonisation potential, with simulations indicating that near-complete elimination of air freight may be feasible under existing commercial conditions.

At a system level, the expected findings are likely to highlight significant trade-offs between emissions reduction, cost efficiency, and operational resilience, while also identifying multiple “win–win” scenarios in which emissions and logistics costs decline simultaneously. Policy-aligned interventions, for example incentives for slower steaming, improvements in port efficiency, and regulatory signals discouraging routine use of air freight are expected to amplify these benefits. Importantly, the analysis is expected to demonstrate that decarbonisation strategies developed without producer-side input risk shifting costs and operational volatility upstream, whereas co-designed solutions are more likely to enhance export competitiveness and resilience for Sri Lankan manufacturers.

Value

This paper offers original value by applying a Digital Twin methodology to a real, global South to UK fast-fashion supply chain, moving beyond conceptual discussions of sustainable logistics to provide operationally grounded, policy-testable evidence. Unlike most freight decarbonisation studies, which focus on downstream markets or single transport modes, this research integrates product-level dynamics, producer-side constraints, and international policy considerations within a unified modelling framework.

The study is valuable to multiple audiences. For policymakers, it provides concrete evidence on how UK sustainable freight objectives interact with upstream production realities, supporting more inclusive and effective regulation. For industry stakeholders, particularly apparel exporters and buyers, it demonstrates how digital supply-chain tools can identify cost-effective decarbonisation pathways while improving operational stability. For researchers, the paper advances methodological approaches to Digital Twins in global supply chains and highlights the importance of equitable international collaboration in sustainability research.

Practical implications

The findings will have direct implications for supply chain managers and policymakers. For apparel manufacturers and logistics providers, the study will provide a replicable model for using digital twins to assess and implement low-carbon logistics strategies tailored to product characteristics. It will recommend practices like product category-specific transport planning and enhanced production scheduling to facilitate modal shift. For policymakers, particularly in the UK, the evidence will support the creation of targeted interventions, such as developing ‘Green Textile Corridors’ with Sri Lanka, which provide reliable, low-emission shipping options. The research would suggest that supporting supplier-side capacity and stability is essential for the viability of broader retail sector net-zero commitments. For Sri Lankan exporters, the research will highlight pathways to enhance competitiveness through stability and predictability rather than cost-cutting alone.

Research limitations/implications

This study is based on in-depth collaboration with a single major Sri Lankan apparel exporter, which may limit the generalisability of findings across the entire sector. While the selected firm is representative of large-scale export operations, future research should extend the Digital Twin framework to multiple firms, different sourcing regions, and alternative destination markets. Data availability and confidentiality constraints also limit the resolution of certain operational parameters, particularly buyer-side decision rules. Future work could integrate real-time demand data and multi-tier supplier modelling to enhance predictive capability.

References

BEIS (2021). Decarbonising Transport: A Better, Greener Britain. UK Department for Business, Energy & Industrial Strategy. Decarbonising Transport – A Better, Greener Britain

Marwah, R., & Ramanayake, S. S. (2024). Pandemic-led trade shocks & supply chain disruption: case studies of the readymade garments (RMG) sector in Sri Lanka and Bangladesh. International Journal of Innovation and Sustainable Development, 18(1-2), 45-70.

UNCTAD (2023). Review of Maritime Transport 2023. United Nations Conference on Trade and Development.

https://unctad.org/publication/review-maritime-transport-2023