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Container ports operate in more challenging and volatile environments at present times. Events such as US-China trade tensions and the COVID-19 pandemic severely affect numerous container ports at various levels. Strategies pursued by container ports are key to port development and management amidst these challenges. Drawing on configuration theory, this research employs Fuzzy-set Qualitative Comparative Analysis to investigate the relation between port strategies and container throughput. The research contributes to the literature by proposing an approach to account for complexity of the port sector and offers insights into strategies adopted by major container ports. The research further identifies 10 port strategies and proposed indicators that can represent the essence of these strategies. Being able to represent strategies in a quantitative format is important for strategy analysis and performance evaluation. Results reveal that major container ports employ a combination of strategies which address both the supply and demand-side aspects of the port business. Growing digitalization and digitization coupled with advancements in information capture, diagnostics capabilities and predictive abilities means a greater role for data analytics to influence container port strategy and performance. Implications for port managers, policy makers and researchers from the perspective of port policy and management are proposed.
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Background: Institutions across the country are experiencing delays in receipt of essential infant formula and feeding supplies due to a supply chain crisis. The supply chain crisis commenced during the COVID-19 pandemic and has continued into present day, late 2022. The supply chain crisis led to an unstable supply of ready to feed (RTF) infant formulas for a children's hospital within a medical center containing a neonatal ICU, pediatric ICU, pediatric floor and newborn nursery. RTF formulas are the recommended inpatient infant feeding due to their sterility. Method(s): To address these RTF formula supply challenges, interprofessional leadership from Clinical Nutrition, Nursing and Supply Chain developed a local infant formula committee. The committee convened based on the needs of the institution, ranging from daily to weekly beginning October 2021 to present day. A shared, live spreadsheet allowed for real time inventory of RTF formula on the Nursing units and amount of product pending receipt in supply chain. Upon identification of low RTF supply, increased usage or RTF outage, the committee implemented a three-tiered action plan for each unit. For the first tier, the formula roomdiluted a higher calorie RTF liquid with water to the desired calorie density (example RTF 24 to RTF 20 calorie/oz). The medical team had an infant formula substitution list to guide feeding alternatives for specialty preparations. In the second tier, the formula room prepared stock formula for each unit daily, with a 24-hour expiration time, to accommodate potential for rapid census changes outside of the formula room operation. As a third layer of safety, powder emergency stock was pre-measured and sent with instructions for Nursing to reconstitute with sterile water, in a dedicated space, if all stock RTF formula was used. The powder emergency stock expired in 30 days, which allowed for a longer shelf life than the stock RTF formula. Result(s): It is practical for institutions without a formula room to implement similar processes using dedicated infant formula preparation space and storage. It also worth mentioning during this time there was a national shortage of powdered infant formulas due to a recall issued in May of 2022 by a major formula manufacturer. The national shortage included elemental powdered formulas for which there is no RTF alternative. Management of elemental formula outages were managed on a case-by-case basis by the Clinical Nutrition department. The Committee also convened to discuss allocations and identify substitutions for other neonatal and pediatric specialty items including sterile water, feeding preparation bottles, ENFit syringes and syringe caps, breastmilk collection containers and infant feeding nipples. Conclusion(s): Using this three-tiered process, the medical center provided sterile RTF formula to infants when available, remained consistent with best practices, predicted inventory needs consistent with usage and prevented waste of powdered infant formula in a time of scarcity. Technology and the anticipatory interprofessional leadership using a three-tiered action plan equipped the medical center for this most extraordinary infant formula crisis nationally.
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As a key enabler of international trade, the container shipping market experienced port congestion, space shortages, and skyrocketing freight rates following the outbreak of the COVID-19 pandemic. Therefore, this paper first utilizes the vector autoregressive model with exogenous variables (VARX) to analyze the interactive mechanisms of economy, capacity, freight rate, and port congestion during the pandemic to identify the causes behind the excessive market volatility. We then introduce government supervision to improve the policy deficiencies in pricing rules and assess whether prohibiting liner companies from charging excessive surcharges can solve market dilemmas by constructing a tripartite evolutionary game model. The results show that liner companies deliberately maintained congestion by using strict control over shipping capacity to raise freight rates and obtain high profits, which is one of the main reasons for the problems. However, we also conclude that relying solely on the spontaneous behavior of the market is unlikely to resolve the predicament. Instead, government intervention can play a crucial role in encouraging liner companies to increase appropriate container capacity, stabilize freight rates, and mitigate the risk of supply chain disruptions due to port congestion. This, in turn, can enhance the resilience of the container transport system.
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To cater to the gradually increasing sizes of ships, several traditional container ports in East Asia built deep-water wharves to attract shipping carriers to berth, a decision that is considered highly reasonable because it allows for shipping carriers to gain a cost advantage. For traditional Far East/Europe (F/E) trunk routes, shipping carriers must deploy vessels that are large enough at hub ports to maintain low transshipment costs. However, for a port to attract shipping carriers, it should be able to first meet the cargo demand of these carriers. The port would also need to improve the loading ratio to enjoy the cost advantage. Simultaneously, the port should leverage the loading and unloading efficiency of the terminal to gain a competitive advantage. Although the port congestion observed at the F/E trunk during COVID-19 was not as serious as that in North American ports, it was sufficient to affect the route deployment and port selection decisions of shipping carriers. Currently, because the size of container carriers is the most critical factor in the reduction of shipping costs, as demonstrated in this study, the upsizing trend of container ships is regarded as a highly relevant aspect in the deployment of trunk routes and the selection of hub ports. © 2023 National Taiwan Ocean University.
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The COVID-19 pandemic has created an urgent need for mathematical models that can project epidemic trends and evaluate the effectiveness of mitigation strategies. A major challenge in forecasting the transmission of COVID-19 is the accurate assessment of the multiscale human mobility and how it impacts infection through close contacts. By combining the stochastic agent-based modeling strategy and hierarchical structures of spatial containers corresponding to the notion of geographical places, this study proposes a novel model, Mob-Cov, to study the impact of human traveling behavior and individual health conditions on the disease outbreak and the probability of zero-COVID in the population. Specifically, individuals perform power law-type local movements within a container and global transport between different-level containers. It is revealed that frequent long-distance movements inside a small-level container (e.g., a road or a county) and a small population size reduce both the local crowdedness and disease transmission. It takes only half of the time to induce global disease outbreaks when the population increases from 150 to 500 (normalized unit). When the exponent c1 of the long-tail distribution of distance k moved in the same-level container, p(k)â¼k-c1·level, increases, the outbreak time decreases rapidly from 75 to 25 (normalized unit). In contrast, travel between large-level containers (e.g., cities and nations) facilitates global spread of the disease and outbreak. When the mean traveling distance across containers 1d increases from 0.5 to 1 (normalized unit), the outbreak occurs almost twice as fast. Moreover, dynamic infection and recovery in the population are able to drive the bifurcation of the system to a "zero-COVID" state or to a "live with COVID" state, depending on the mobility patterns, population number and health conditions. Reducing population size and restricting global travel help achieve zero-COVID-19. Specifically, when c1 is smaller than 0.2, the ratio of people with low levels of mobility is larger than 80% and the population size is smaller than 400, zero-COVID can be achieved within fewer than 1000 time steps. In summary, the Mob-Cov model considers more realistic human mobility at a wide range of spatial scales, and has been designed with equal emphasis on performance, low simulation cost, accuracy, ease of use and flexibility. It is a useful tool for researchers and politicians to apply when investigating pandemic dynamics and when planning actions against disease. Supplementary Information: The online version contains supplementary material available at 10.1007/s11071-023-08489-5.
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Purpose - The purpose of this study is to analyze the market power of the Korea Container Shipping Market (Intra Asia, Korea-Europe, and Korea-U.S.) to verify the existence of collusion empirically, and to answer whether the joint actions of liner market participants in Korea have formed market dominance for each route. Precisely, it will be verified through the Lerner index as to whether the regional market of Asia is a monopoly, oligopoly, or perfect competition. Design/methodology - This study used a Lerner index adjusted with elasticity presented in the New Imperial Organization (NEIO) studies. NEIO refers to a series of empirical studies that estimate parameters to judge market power from industrial data. This study uses B-L empirical models by Bresnahan (1982) and Lau (1982). In addition, NEIO research data statistically contain self-regression and stability problems as price and time series data. A dynamic model following Steen and Salvanes' Error Correction Model was used to solve this problem. Findings - The empirical results are as follows. First, lambda, representing market power, is nearly zero in all three markets. Second, the Korean shipping market shows low demand elasticity on average. Nevertheless, the markup is low, a characteristic that is difficult to see in other industries. Third, the Korean shipping market generally remains close to perfect competition from 2014 to 2022, but extreme market power appears in a specific period, such as COVID-19. Fourth, there was no market power in the Intra Asia market from 2008 to 2014. Originality/value - Doubts about perfect competition in the liner market continued, but there were few empirical cases. This paper confirmed that the Korea liner market is a perfect competition market. This paper is the first to implement dynamics using ECM and recursive regression to demonstrate market power in the Korean liner market by dividing the shipping market into Deep Sea and Intra Asia separately. It is also the first to prove the most controversial problems in the current shipping industry numerically and academically.
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Container shipping has suffered a sharp decline since COVID-19, and risks associated with container transit will persist in the future. The decrease in container transportation has caused a ripple impact on the global supply chain. However, container throughput forecasting is both critical and complicated under the circumstances of economic uncertainty and the outbreak of the COVID-19 pandemic. A novel model propounded in this paper for container throughput forecasting to assist the port management bureau and container shipping industry integrates with the variational mode decomposition (VMD) algorithm, SARIMA technique, convolutional neural network (CNN) method, long short-term memory (LSTM) approach, and attention mechanism, among others. In this model, there are three stages: (i) data decomposition, (ii) component prediction, and (iii) ensemble output. In the first stage, the original data of the container throughput time series is decomposed into several different components using the VMD algorithm. Next, from low frequency to high frequency, each component is modeled by the corresponding prediction approach. Subsequently, the prediction results of each component generated by the previous stage are integrated into the final forecasting results by addition strategy. To enhance the prediction accuracy in the second stage, the attention mechanism is adopted in the CNN-bidirectional LSTM method. Finally, six measurement criteria, the container throughput times series at four ports, and a statistical evaluation approach are applied to comprehensively evaluate the proposed model compared with seven benchmark models. The empirical analysis demonstrates that the proposed model significantly outperforms other comparable models with regard to prediction results, level, and directional prediction accuracy.
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Since the COVID-19 outbreak, the use of disposable plastics has rapidly increased along with the amount of plastic waste. During fragmentation, microplastics and other chemical substances contained in plastics are released. These then enter humans through food which could be problematic considering their hazardous potential. Polystyrene (PS), which is widely used in disposable containers, releases large amounts of microplastics (MPs), but no studies have investigated the release mechanisms of PS-MPs and simultaneously exposed contaminants. Therefore, in this study, the effects of pH (3, 5, 7, and 9), temperature (20, 50, 80, and 100 °C), and exposure time (2, 4, 6, and 8 h) on MPs release were systematically examined. A quantitative/qualitative study of MPs and styrene monomers was performed using microscopy-equipped Fourier-transformed infrared spectroscopy and gas chromatography-mass spectrometry. The release of PS-MPs (36 items/container) and simultaneously exposed pollutants (SEP), such as ethylene glycol monooleate (EGM), was highest at pH 9, 100 °C, and 6 h, which was proportional to the test temperature and time. Under the same conditions, 2.58 µg/L of styrene monomer migrated to the liquid food simulants. The fragmentation was proceeded by oxidation/hydrolysis and accelerated by increased temperature and exposure time. The strong positive correlation between PS-MPs and SEPs releases at pH and temperature indicates that PS-MPs and SEPs follow the same release process. However, a strongly negative correlation between PS-MPs and styrene monomers at the exposed time shows that styrene migration does not follow the same release process, but does its partition coefficient.
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Increasing the level of containerization in Russia is a source of competitiveness growth, since it focuses on increasing the efficiency of nationally oriented logistics and integration into global logistics chains, ensures transparency and productivity of the transport and logistics sector. The negative consequences caused by COVID-19 have affected freight transportation by all modes of transport. The reaction of carriers to the existing challenges largely determines the trajectory of development not only of railway container transportation, but also the format of the development of Russian cargo traffic for the coming years or even decades. The purpose of this study is to develop measures to increase the mobility of container cargo turnover on Russian railways and indicative designation of possible effects from their implementation. We prove that the development of infrastructure, stabilization of tariff policy, optimization of operational activities, expansion of the digital platform significantly affects the qualitative and quantitative development of rail container transportation based on mobility and logistics efficiency. The methodology of the study is based on the analysis of the target indicators of containerization of Russian railways for 2010–2020, the main product line of container transportation and competitors of the railway by means of transport. As a result of the study, trends in the growth of the share of container cargo turn-over on the Russian railway network are determined, the support of digital tools is justified in order to increase the mobility of container cargo turnover, a set of mechanisms for supporting and developing railway container transportation based on mobility and logistics efficiency is proposed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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There are many inevitable disruptive events, such as the COVID-19 pandemic, natural disasters and geopolitical conflicts, during the operation of the container port supply chain (CPSC). These events bring ship delays, port congestion and turnover inefficiency. In order to enhance the resilience of the CPSC, a modified two-stage CPSC system containing a container pretreatment system (CPS) and a container handling system (CHS) is built. A two-dimensional resilience index is designed to measure its affordability and recovery. An adaptive fuzzy double-feedback adjustment (AFDA) strategy is proposed to mitigate the disruptive effects and regulate its dynamicity. The AFDA strategy consists of the first-level fuzzy logic control system and the second-level adaptive fuzzy adjustment system. Simulations show the AFDA strategy outperforms the original system, PID, and two pipelines for improved dynamic response and augmented resilience. This study effectively supports the operations manager in determining the proper control policies and resilience management with respect to indeterminate container waiting delay and allocation delay due to disruptive effects.
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Accurate and effective container throughput forecasting plays an essential role in economic dispatch and port operations, especially in the complex and uncertain context of the global Covid-19 pandemic. In light of this, this research proposes an effective multi-step ahead forecasting model called EWT-TCN-KMSE. Specifically, we initially use the empirical wavelet transform (EWT) to decompose the original container throughput series into multiple components with varying frequencies. Subsequently, the state-of-the-art temporal convolutional network is utilized to predict the decomposed components individually, during which an improved loss function that combines mean square error (MSE) and kernel trick is employed. Eventually, the deduced prediction results can be obtained by integrating the predicted values of each component. In particular, this research introduces the MIMO (multi-input and multi-output) strategy to conduct multi-step ahead container throughput forecasting. Based on the experiments in Shanghai port and Ningbo-Zhoushan port, it can be found that the proposed model shows its superiority over benchmark models in terms of accuracy, stability, and significance in container throughput forecasting. Therefore, our proposed model can assist port operators in their daily management and decision making. © 2023 John Wiley & Sons Ltd.
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Purpose: The coronavirus disease (COVID-19) has increased food delivery service demand, which generates massive amounts of solid waste, specifically plastic material. Therefore, this study aims to examine the determinants of consumers' intention to reuse food delivery containers (ITR) using the extended theory of planned behavior (TPB). Moral obligation was included as an antecedent, while behavioral expectation (BE) ahead of behavioral intention was an immediate predictor of consumers' pro-environmental behaviors. Design/methodology/approach: The hypotheses were tested on 348 food delivery service users in Malaysia and analyzed using the partial least squares structural equation modeling (PLS-SEM). Findings: The findings indicated that consumers' ITR is directly influenced by perceived behavioral control and attitude. Perceived behavioral control and attitude had a positive partial indirect effect on ITR through BE. Meanwhile, subjective norms and moral obligation had a positive full indirect effect on ITR through BE. Research limitations/implications: The findings can be directly applied to practical situations of food delivery companies and environmental protection organizations managing solid waste among food delivery services. Practical implications: Understanding consumers' ITR could promote practical environmental sustainability. Practically, the study provides insights to the food delivery service industry, policymakers and relevant stakeholders to encourage consumer behavior change by reusing food delivery containers in line with Sustainable Development Goal 12. Originality/value: The study enhances the existing literature by extending TPB with two psychological variables: moral obligation (independent variable) and BE (mediating variable). To the best of the authors' knowledge, this study is the first attempt to empirically investigate BE in consumers' pro-environmental behavioral intention in a high-context culture and developing economy. This study could benefit food and beverage merchants, food delivery companies, governments, non-governmental organizations and pro-environmental behavior researchers in this industry. © 2023, Emerald Publishing Limited.
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The transport and logistics sector, which include freight forwarders companies, constitutes a vast network of entities that are central to a good performance in services. With the COVID-19 pandemic and its effects on the global economy, there was a huge shortage in the number of containers available, thus creating the need to optimize the loading of available equipment to avoid waste and maximize profits from each export. The present work presents a novel approach where a set of restrictions were created that, applied in synergy with the Non-Linear GRG algorithm, aim to allocate the boxes in different consecutive lines until forming a wall, and, therefore, the walls complete the container, in order to maximize the occupancy on it. To validate the proposed approach a prototype was developed and studied in real-world problem where the solutions resulted in occupations around 80% to 90%. Thus, we can foresee the importance of the proposed approach in decision-making regarding container consolidation services. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The COVID-19 pandemic has affected various industries in different ways depending on their type of business. We attempt to understand the impact of the pandemic on the performance of 26 major container carriers. To capture performance differences before and during the pandemic, we collect data the years 2019 and 2020. Further, we divide carriers' business processes into two stages, i.e., asset acquisitions and transport operations. We employ relevant data envelopment analysis (DEA) models to this effect. The mean efficiency score in 2020 was higher than in 2019. Overall, container carriers increased their performance during the COVID-19 pandemic. However, seven companies showed lower efficiency in 2020. Similarly, eight companies were efficient in their operations but not in asset acquisition decisions. Our results show that firm strategy is important in coping with external shocks. The contribution of the paper is in measuring the impact of external shocks, such as the COVID-19 pandemic, on the performance of container carriers, both in regard of their acquisitions and their operations. © 2023, This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply.
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U.S. container ports have experienced unpresented congestion since mid-2020. The congestion is generally attributed to import surges triggered by heavy spending on consumer goods during the COVID-19 pandemic. Port congestion has been compounded by the inability of importers to retrieve, receive, and process all the inbound goods they have ordered, resulting in supply chain shortfalls and economic disruption. How can the shipping industry and government organizations predict the end of the current surge and anticipate future surges? Expected seasonal variations in import volume are associated with peak holiday shopping periods; nonseasonal import surges are signaled by other factors. The research goes beyond transportation data sources to examine broader connections between import volume and indicators of economic and retail industry conditions. The strongest and most useful relationship appears to be between retail inventory indicators and containerized import growth. From January 2018 through July 2021, there was a relatively strong negative correlation between retail inventory- and import TEU indices with a 4-month lag (corresponding roughly to the time between import orders and -arrival). In the 2020 to 2021 pandemic period the negative correlation was stronger, again with a 4-month lag. These findings suggest that observers might anticipate import surges after marked, nonseasonal drops in retail inventories, and that import surges are likely to last until target inventory levels are restored. In a broader sense, an awareness of the linkages between consumer demand, retail chain responses, and containerized import volumes could better inform port, freight transportation, and government planning and policy choices.
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The recent emergence of new drug technologies such as mRNA-based (messenger ribonucleic acid) vaccines developed to fight the outbreak of the Corona Virus Disease (COVID-19) global pandemic has driven increased demand for delivery solutions capable of withstanding deep cold storage conditions down to -50°C, and even down to -80°C. While significant data exist for deep cold storage in vials, little evidence is available for pre-filled syringes. Since pre-filled syringes serve as both the storage container and the delivery mechanism, there are additional risks to performance that must be evaluated, such as plunger gliding performance, syringe lubrication, silicone layer stability, and container closure integrity (CCI). In the present study, a comprehensive assessment of functional and physical performances of Pre-Filled Syringes (PFS filled with water) was performed after one or multiple freeze/thaw (F/T) cycles between ambient temperature and various temperature cycles including -40°C, -50°C or -80°C for both 'staked needle' and 'luer lock' configurations. The experiments were guided by historical normative methods such as ISO11040-4 and USP<1207> and combined with headspace gas analysis for barrel-stopper tightness testing. In addition, they were complemented with a novel approach namely in situ real time optical imagery to track plunger stopper movement during F/T cycle. The findings indicate that there is no significant impact on the functional performances from F/T down to -80°C, while no CCI risk was found after F/T down to -50°C.
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Maritime shipping lines and global terminal operators have benefited from economies of scale to expand geographically and functionally their infrastructure, leading to a corporatized network. Terminal operators are key asset managers seeking value creation by expanding the global maritime container terminal infrastructure network. While corporatization has systematically ensured that terminal capacity was created to accommodate the rise in global trade volumes, the network hit its boundaries when confronted with COVID-19 induced global supply chain disruptions. This paper provides a better understanding of the importance of infrastructure and observed corporatization as a framework for explaining economic processes, notably when transport infrastructures are extensive and capital-intensive. The structure of the global container shipping network is analyzed to unveil the realities of liner service networks operated by shipping lines, and the market structure and consolidation in container shipping and terminal operations. The discussion on the corporatization of the global maritime infrastructure network for container handling is embedded in international business literature. This study also extracts the main implications of the current structure and governance of the global maritime infrastructure network for international business policy, with a particular focus on the current market structure and network resilience.
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Pharmaceutical drugs and vaccines require the use of material containers for protection, storage, and transportation. Glass and plastic materials are widely used for packaging, and a longstanding challenge in the field is the nonspecific adsorption of pharmaceutical drugs to container walls – the so-called "sticky containers, vanishing drugs” problem – that effectively reduces the active drug concentration and can cause drug denaturation. This challenge has been frequently discussed in the case of the anticancer drug, paclitaxel, and the ongoing coronavirus disease 2019 (COVID-19) pandemic has brought renewed attention to this material science challenge in light of the need to scale up COVID-19 vaccine production and to secure sufficient quantities of packaging containers. To reduce nonspecific adsorption on inner container walls, various strategies based on siliconization and thin polymer films have been explored, while it would be advantageous to develop mass-manufacturable, natural material solutions, especially ones involving pharmaceutical grade excipients. Inspired by how lipid nanoparticles have revolutionized the vaccine field, in this perspective, we discuss the prospects for developing lipid bilayer coatings to prevent nonspecific adsorption of pharmaceutical drugs and vaccines and how recent advances in lipid bilayer coating fabrication technologies are poised to accelerate progress in the field. We critically discuss recent examples of how lipid bilayer coatings can prevent nonspecific sticking of proteins and vaccines to relevant material surfaces and examine future translational prospects. © 2021 The Authors. VIEW published by Shanghai Fuji Technology Consulting Co., Ltd, authorized by Professional Community of Experimental Medicine, National Association of Health Industry and Enterprise Management (PCEM) and John Wiley & Sons Australia, Ltd.
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Gnosis Freight employs low-code/no-code development tools to provide container visibility information for shippers. The case takes place as U.S. supply chains are still reeling from the impacts of the Covid-19 pandemic. Shipping costs have sky-rocketed with shippers facing huge uncertainties as shipments are marooned on container ships or in container port yards. Accustomed to reliable pick-up and delivery forecasts at reasonable rates, they find themselves with unreliable delivery forecasts or unknown locations of their shipments. Gnosis Freight, by combining data from several sources, provides logistics and transportation managers with near real-time information on their shipments. Gnosis solutions engineers, armed with low-code and no-code development tools, are able to quickly install customer-tailored container visibility portals with little adverse effects on the customer's existing work processes and data flows. The implementation speed of these edge development tools provides Gnosis Freight with a strategic advantage over competitive offerings that require major changes in a customer's operations. But the company also faces issues with its own data supplier, giving students a specific "make vs buy" problem to analyze. © 2023, Association for Information Systems. All rights reserved.
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Purpose: The Coronavirus disease 2019 (COVID-19) pandemic has increased the use of food delivery containers in the food and beverage industry. Based on the theory of planned behavior (TPB), the aim of this paper is twofold: Firstly, it examines the influence of three elements of TPB (attitude, perceived behavioral control and subjective norm) and time pressure on the intention to reuse reusable food delivery containers (ITR). Secondly, it examines ITR as an antecedent to the willingness to pay more for reusable food delivery containers (WTPM). Design/methodology/approach: Data were collected from 401 higher education institution (HEI) students and analyzed using partial least squares structural equation modelling (PLS-SEM). Findings: The study found that the three elements of TPB influenced ITR. Furthermore, the results revealed that ITR directly influenced WTPM. Surprisingly, time pressure did not influence ITR. Originality/value: The research is one of the earliest studies to investigate HEI students' intention to reuse food delivery containers during the COVID-19 pandemic. The study contributes to TPB by presenting a novel, integrated model to explain the independent roles of time pressure and ITR on ITR and WTPM, respectively. Finally, it contributes to the existing body of knowledge on pro-environmental behavior among HEI students and advances methodologically by establishing the PLS-SEM approach. © 2023, Emerald Publishing Limited.