Since the inception of the Green Shipping Corridor (GSC) concept in 2021, 126 GSCs have been initiated worldwide as of January 2026. However, significant misunderstandings have occurred regarding the naming of GSCs, their governance frameworks, the type of zero-emission vessels (ZEVs) with alternative fuels and ZEV fleet deployment on GSCs, and the greenhouse gas emissions computation from the fleet. To address these, this paper aims to conduct a systematic review of the development of GSCs by incorporating the most recent literature and policy developments. By doing so, it clarifies common misunderstandings of the GSC concept. This paper contributes to further refinement of GSC concept to enhance the implementation of GSCs in advancing the decarbonisation of the maritime industry. The paper also proposes research and policy agendas in implementing GSCs and optimizing ZEV fleet deployment.

This paper investigates the impact of port-specific factors on port time variability by identifying, analysing, and modelling their effects. Key factors are innovatively extracted from Automatic Identification System (AIS) data and country-level port data, capturing port dynamics and complex vessel flow network metrics. Structural equation modelling (SEM) is employed to assess their influence on port time variability, defined as the deviation from the average port time - the interval between a vessel’s arrival and departure. The findings reveal that high-quality port infrastructure and geographically favourable locations enhance port logistics efficiency, leading to reduced port time variability. Additionally, port infrastructure quality, location conditions, and network connectivity positively influence port dynamic flow. Port network connectivity and dynamic flow partially mediate the relationship between location conditions and port time variability. These insights contribute to developing strategic port management approaches aimed at improving operational efficiency, reducing congestion and delays, and guiding long-term infrastructure investments to strengthen inter-port connectivity.

This paper develops a weighted-sum scalarised mixed-integer linear programming framework to evaluate freight-transit route options connecting Kathmandu, Nepal, with key seaports in Kolkata, India; Chittagong, Bangladesh; and Tianjin, China. The model compares road-only and rail–road configurations and incorporates transportation cost, carbon emissions, transshipment requirements, and delivery lead time within a unified corridor-level decision-support framework.The analysis evaluates alternative corridor configurations linking Kathmandu with Kolkata, Chittagong via India, and Tianjin through inland rail and road connections, including Xian and Lhasa. Alternative weighting scenarios are used to represent different policy priorities, including cost efficiency, time sensitivity, and carbon-emission reduction.The results consistently identify the Kolkata–Kathmandu corridor as the most efficient option because of its shorter inland distance and favourable rail–road configuration. The Chittagong–Kathmandu corridor remains a relevant complementary alternative but is constrained by additional border-processing requirements and transit dependency through India. The Tianjin–Kathmandu corridor benefits from comparatively stronger logistics infrastructure along parts of the route; however, its substantially longer inland distance remains a major structural disadvantage.The contribution of the study lies in integrating the landlocked country–transit country–seaport structure into a corridor-level decision-support framework for Nepal rather than in proposing a new optimisation algorithm. The findings support a corridor-based planning approach focused on improving rail utilisation, transshipment efficiency, and cross-border logistics coordination.

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This paper aims to analyze China's iron import trade patterns and estimate transportation costs of iron-ore from Australia and Brazil. A twin strategic framework of iron-ore imports from the perspective of economic security and decarbonization of maritime industry is proposed to overcome geographical disadvantage for Brazilian iron-ore suppliers. Augmenting capacity through the deployment of ChinaMax with 400,000 DWT to leverage from economies of scale (so-called economic security strategy) and establishing the longest Green Shipping Corridor (GSC) (so-called decarbonization strategy) are recommended. This will enable Brazil to utilize zero-emission ships that consume green (alternative) fuels. The GSC strategy with zero-emission ships is innovative yet challenging to decarbonize Brazilian Iron-Ore Supply Chain through backward and forward linkage effects. The integration of cost estimation methods with political economy arguments to maintain a balance between China's strategic interest and economic value addition with decarbonization, and maritime security of raw material resources is future proof to business disruptions. The paper concludes by proposing a strategic framework discussion and strategic insights for China.

This study analyses factors affecting container dwell time (CDT) at the Mombasa Port using machine learning (ML) algorithms. The study employs real-time container movement data to evaluate several ML models. It finds that CDT varies significantly across different periods in the year and even in the days and weeks. For example, it peaks in the afternoons and during November/December. Although models like Artificial Neural Networks and Random Forest outperform others, the Decision Tree model was chosen for its interpretability, despite a slightly higher error rate. It identifies transportation modes as the key predictor, with truck-based movements leading to longer dwell times than rail transport. The study highlights the impact of specific locations and times of the week/year on CDT. Its originality lies in using real-time data from the Global South and its application of ML to improve operational efficiency and strategic decision-making. Unlike typical studies focused on terminal operations, this research also considers broader exogenous factors. The findings provide valuable insights for optimizing port operations and reducing CDT.

PurposeThis study integrates economic, environmental, and social dimensions into the distribution network for India’s Public Distribution System (PDS). It aims to identify multi-modal strategies that balance cost efficiency, lower emissions, and community well-being.Design/methodology/approachA model is proposed to allocate grains from base to field silos via road, rail, and inland waterways considering Triple Bottom Line (TBL). The costs, emissions, and social factors (e.g. employment) were quantified and combined to generate a composite score, enabling rigorous trade-off evaluation.FindingsResults from a representative case study show that integrating rail and waterways reduces total costs and emissions while boosting employment and community welfare. Intermodal configurations improve the PDS’s sustainability, demonstrating the feasibility of aligning economic objectives with environmental and social outcomes.Research limitations/implicationsFuture work could incorporate stochastic demand or disruptions, and extend beyond a single commodity or region, enhancing the model’s robustness and generalizability.Practical implicationsInsights guide planners in selecting routes, modes, and facility investments aligned with cost reduction, emissions control, and social uplift.Social implicationsThe approach promotes inclusive development by increasing employment opportunities and ensuring a more equitable distribution of benefits in vulnerable communities.Originality/valueThis research extends conventional cost-centric frameworks by incorporating TBL metrics in a large-scale, government-run distribution setting. It provides a practical blueprint, informing infrastructural investments and policy interventions for holistic, enduring improvements in food security and resource utilization.

This study investigates the influence of circular economy (CE) enablers on supply chain resilience (SCR) within the pulp and paper industry. Specifically, it examines the mediating role of circular economy implementation (CEI) in translating operational and strategic enablers into resilient supply chain outcomes. A quantitative survey approach was adopted, targeting firms within the Malaysian pulp and paper industry. Data were collected from 186 firms and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test direct and indirect relationships among eco-design, reverse logistics, supplier collaboration, green manufacturing, waste minimization, CEI, and SCR. The results confirm that all CE enablers significantly influence CEI, with reverse logistics and supplier collaboration exerting the strongest effects. CEI was found to have a significant direct effect on SCR and partially mediated the relationship between all five enablers and SCR. These findings underscore the strategic role of CEI in fostering resilient supply chains. This study is industry-specific and geographically focused on Malaysian firms, which may limit generalizability. Future studies could explore cross-industry or cross-country comparisons. Moreover, qualitative insights could enrich the understanding of implementation barriers and contextual dynamics. This study advances the theoretical integration of circular economy and supply chain resilience by establishing CEI as a mediating construct. It provides empirical evidence from an under-researched yet high-impact industry and offers actionable insights for supply chain managers and policymakers aiming to embed sustainability and resilience in industrial ecosystems.

This paper applies Markov Chain to model fire risk in Melbourne and Geographically Weighted Regression (GWR) to analyze local effects of spatial characteristics on fire risk variability. Results show that fire risk tends to vary across space and time, influenced by socio-urban characteristics of Melbourne. The inner city and its surrounding suburbs are more susceptible to fire incidents. Language barriers, residential mobility, home ownership, types of dwellings and dwelling density tend to significantly affect local fire risk. The outcomes from this research enable fire authorities to help develop geo-targeted and need-based education campaigns on fire safety at a local area.

PurposeThis study aims to evaluate the efficiency levels of Australian banana farms and identify strategies for improvement. The findings address critical challenges in the horticulture industry by promoting more efficient resource utilisation during the growing phase, thereby reducing waste and enhancing overall supply chain sustainability.Design/methodology/approachData from 27 banana farms across Queensland, New South Wales and South Australia were analysed using both traditional and entropy-based data envelopment analysis (DEA). A variable returns to scale (VRS) model with an input orientation was applied, incorporating one output (cartons packed) and four inputs (employee wages, fertiliser usage, packaging costs and on-costs).FindingsThe study's findings using entropy-based DEA reveal that among 27 farms analysed, 37% achieve technical efficiency scores exceeding 90%, with 26% identified as fully efficient relative to their counterparts. Two farms emerge as key benchmarks for others. However, only 22% of farms exhibit scale efficiency scores above 90%. Most farms, except the two fully efficient ones, operate under increasing returns to scale, highlighting potential benefits from farm size expansion. On average, achieving full technical efficiency could result in cost savings of 26.9% on employee wages, 34.7% on fertilizer use, 21.7% on packaging costs and 33.1% on on-costs. The entropy-based DEA produces results comparable to the traditional DEA but offers greater discriminative power, making it a more effective decision-making tool.Research limitations/implicationsThrough efficiency comparison of farms, this study advances the understanding of horticultural waste reduction by improving farm practices related to labour deployment, fertiliser use, packaging and other resources. Using Australian banana farms as a case study, it demonstrates that enhanced farm management and more efficient input usage can minimise production costs while maintaining target output levels, thereby promoting long-term sustainability. Limited sample size and unmapped farm locations are the key limitations of this study.Practical implicationsThe findings provide insights for government and trade associations to formulate strategies and develop sector action plans for improving efficiency hence sustainability of the entire industry through knowledge sharing and inter-farm collaboration. These improvement measures can also be applied across other sectors of the food supply chain to help reduce food loss and waste at the farm level.Social implicationsThis research identifies benchmarks to help banana farmers enhance farming practices and management skills. By reducing crop loss and waste, it fosters sustainability, mitigates food loss and promotes circularity in the banana supply chain. The findings empower farmers to adopt efficient, environmentally friendly practices for long-term impact. Reducing losses at the farm level can significantly strengthen the global food supply and contribute to alleviating chronic hunger in vulnerable regions.Originality/valueThis study extends the use of traditional and entropy-based DEA to comparing the efficiency of banana farms to help identify areas for improvement in terms of resource usage and farm management. Availability of a relatively simple and easy-to-understand efficiency comparison tool can help the industry identify benchmarks for knowledge sharing to benefits farming communities.

Urban fire scholarship on the global south is scarce. Despite the majority of the 180,000 annual global fire deaths (World Health Organization, 2023) being from low- and middle-income nations we know very little about their characteristics and dynamics. At a time where most current and future urban growth is being experienced in the global south, the need to understand urban fire dynamics has never been more pressing. The current study seeks to empirically capture the antecedent conditions that bring about elevated levels of fire in Kathmandu, Nepal using a spatial analytic approach. Findings reveal elevated levels of fire during winter, weekends, during evening hours and related to extreme weather events. There were strong associations in areas characterised by low socio-economic areas, higher populations of children and locales with no school attendance. Findings are important in their capacity to directly advise both in a strategic capacity (policy design such as a campaign to check electrical equipment before the onset of cold spells) and for operational activities, such as optimal fire resource location based upon the observed patterning in the historical data. Our hope is that the current study acts as a new point of reference to encourage other similar studies of urban fires in the global south through which we can assemble a more complete and robust understanding.

Last mile delivery (LMD) logistics research has drawn attention due to increased urban compactness and environmental concerns arising from freight traffic congestion.This has affected the cost-effectiveness and on-time delivery of urban freight.This study aims to develop a strategic framework to formulate future LMD scenarios based on transport and urban planning constraints using a scenario thinking approach.A scenario thinking stakeholder workshop was conducted to collect data on last mile delivery constraints in Metropolitan Melbourne.The research develops five abridge scenario thinking stages that researchers can adopt in scenario thinking methodology.Using brainstorming and storytelling of scenario thinking approach, participants identified 34 transportation and planning constraints clustered into six urban builtenvironment dimensions that formed the basis of the development of LMD future scenarios.The six clustered dimensions include Freight Infrastructure, Infrastructure Supply, Land use Intensity, Infrastructure Sharing, Intersection Controls and Human Behaviour.Infrastructure Supply and Land use Intensity were found to represent higher uncertainty and higher impact on city logistics provisions.The proposed regulatory-informed and efficiency-responsive strategies are the key to manage LMD.These strategies will help city logistics providers and planners in development of operational plans in making investment decision on LMD challenges.

PurposeThere is a growing interest among academics, government agencies and private organisations to examine the scale, characteristics, and impact of Open Innovation (OI). Studies have examined these issues mainly in the context of a developed world. Because firms in developing economies face unique challenges of OI such as building networks, inter-firm interactions, collaboration for resource utilisation and knowledge sharing, these warrant an examination of the theoretical relationships between the antecedents of OI and their impact on performance as well as mediators of these relationships. Therefore, this study develops a comprehensive OI framework to measure open innovation and analyse its effect on the innovation performance of Indian IT organisations.Design/methodology/approachTheoretically, the study draws upon the Resource-Based View, Relational View, and Absorptive Capacity theories. Empirically, a survey questionnaire was distributed to Indian IT organisations through the online survey tool “Qualtrics”. The research framework was tested using the data collected from 346 Indian IT organisations.FindingsThe results highlight the positive effect of OI activities on innovation performance and the mediating role of absorptive capacity. IT organisations with a higher inbound knowledge and absorptive capacity demonstrated better innovation performance.Research limitations/implicationsThis study is limited to understanding the mediating effect of absorptive capacity for inbound innovation. Future studies into the mediating role of desorption capacity could reveal its impact on innovation performance.Practical implicationsFrom a management perspective, this knowledge will enable managers and policymakers to emphasise OI to achieve better innovation performance. This knowledge will provide both government decision-makers and IT managers with definite OI implications for innovation performance.Originality/valueThe main contribution of this study lies in exploring the interconnectedness among IT organisations and collaborative processes on OI and innovation performance. This empirical study pinpoints the causes and sources of OI that would lead to innovation performance and the mediating role of absorptive capacity in achieving innovation performance. It extends the empirical base of OI scholarship based on firms in an emerging economy.

Exploring Spatio–temporal patterns of fire incidents provides important information to help develop strategies to prevent and mitigate fire risk based on geographical knowledge. This study aims to map and analyse the Spatio–temporal patterns of urban fire incidents. Fire incident data were obtained from Ardabil Municipality Fire Department and Emergency Services and analysed using radial shape charts, kernel density estimation and average nearest neighbour to quantify spatial and Spatio–temporal patterns of fires. The results show that the Spatio–temporal fire patterns vary, depending on time, their types and causes. Interestingly, results indicate that fires are most likely to occur on Tuesdays and Thursdays and during summer. The study provides evidence to enhance decision-making on resource allocation in terms of establishing new fire stations and deploying an additional workforce to more vulnerable localities, or to formulate prevention strategies, such as education campaigns, to mitigate fire risk.

Thermal power generation based on coal has been identified as the second largest polluting industry due to the greenhouse gas emissions caused by coal combustion. The pollution caused by this industry is not limited to power generation, but it also manifests itself throughout the use of products. Although a huge emphasis has been placed on replacing coal-based power generation with renewable resources, we showed that Indian power generation will depend on coal for more than fifty percent of its demand in the near future. In our study, we utilized a combination of linear cointegration, non-linear cointegration, ARIMA, and the VECM to forecast the use of coal based on the Indian industrial index and the amount of electricity generated through coal combustion required to meet the demand. Given that pollution and carbon emissions are inherent in the coal usage cycle, we drafted policy implications and recommendations to mitigate the consequences, green the coal usage cycle, and improve the coal supply chain.

In recent years, there is a growing demand for corporations to demonstrate their commitment for and performance in sustainable sourcing of their goods and services. This has led to the promulgation of several sustainable procurement indicators (SPIs) and disclosure indexes (DIs) to guide businesses in meeting 'responsible' or 'ethical' business operations. However, extant SPIs and guidelines have reliability challenges due to inconsistencies and varying focuses as most DIs are skewed towards non-discriminatory practices and equity in wealth and income distribution. This study proposes a methodological framework and uses 33 indicators of globally accepted ethical norms and standards for business conduct to develop an index for disclosure of sustainable procurement practices. Based on the proposed framework, we conducted a proof-of-concept study using a sample of 60 companies in four industries listed in the Australian Securities Exchange. The findings reveal significant variations in disclosure, with less than 20% of the investigated companies reporting 80% or more of the 33 indicators that constitute the disclosure index. It is observed that companies tend to disclose more in the governance and the environmental dimensions, but less in the economic and the social domains. These results indicate that the disclosure index developed using the proposed framework can be a useful tool for assessing transparency in reporting sustainable procurement practices and can help improve sustainability performance across the supply chain. The index thus provides stakeholders and the public with a lens to examine and monitor a company's sustainable sourcing practices.