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This study aims to investigate the impact of seaport efficiency on economic growth in Ghana over the period 2006–2020.

Comprehensive methodology, diverse data analysis techniques, including Augmented Dickey–Fuller tests, autoregressive distributed lag (ARDL) modeling and Granger Causality, were applied to explore the intricate relationship between Seaport Efficiency and Economic Growth.

The findings reveal a statistically significant and positive association between seaport efficiency and GDP, underscoring the crucial role of efficient seaport operations in actively stimulating economic growth. Beyond seaport efficiency, influential factors such as capital, human capital, knowledge spillover and productive capacities were identified, contributing to the dynamics of economic growth.

The Granger Causality Test solidifies seaport efficiency as a robust predictor of GDP fluctuations, emphasizing its significance in economic forecasting. Notably, this study contributes to the existing body of knowledge with its nuanced exploration of the intricate relationship between seaport efficiency and economic growth in the specific context of Ghana.

This study’s implications extend beyond academia, offering invaluable guidance for policymakers and planners. It serves as a comprehensive roadmap for informed decision-making, emphasizing the pivotal role of efficient seaports in charting a trajectory for enduring and resilient economic progress in the nation.

While the broader theme has been explored in existing literature, the uniqueness of this study lies in its specific application to the Ghanaian context. The choice of Ghana, a nation where maritime transport handles over 90% of trade, underscores the significance of understanding seaport efficiency in this regional and economic setting. The study’s originality is reinforced by incorporating diverse economic variables, aligning with recommendations for a comprehensive analysis of factors influencing port performance.

This paper reviews and analyses renewable energy options, namely underground thermal, solar, wind and marine wave energy, in seaport cargo terminal operations.

Four renewable energy options that are deployed or tested in different ports around the world are qualitatively examined for their overall implementation potential and characteristics, and their cost and benefits. An application to the port of Singapore is discussed.

Geophysical conditions are key criteria in assessing renewable energy options. In the case of Singapore, solar power is the only suitable renewable energy option.

Being a capital-intensive establishment with high intensities of cargo operations, seaports usually involve a high level of energy consumption. The study of renewable energy options contributes to seaport sustainability.

A key recommendation is to implement a smart energy management system that enables the mixed use of renewable energy to match energy demand and supply optimally and achieve higher energy efficiency.

The use of renewable energy as an eco-friendlier energy source is underway in various ports. However, there is almost no literature that analyses and compares various renewable energy options potentially suitable for cargo terminal operations in ports. This paper narrows the knowledge gaps.

This study aims to provide a comprehensive review of electric tugboat deployment in maritime transportation, including an in-depth assessment of its advantages and disadvantages. Along with the identification of advantages and disadvantages of electric tugboat deployment, the present research also aims to provide managerial insights into the economic viability of different tugboat alternatives that can guide future investments in the following years.

A detailed literature review was conducted, aiming to gain broad insights into tugboat operations and focusing on different aspects, including tugboat accidents and safety issues, scheduling and berthing of tugboats, life cycle assessment of diesel tugboats and their alternatives, operations of electric and hybrid tugboats, environmental impacts and others. Moreover, a set of interviews was conducted with the leading experts in the electric tugboat industry, including DAMEN Shipyards and the Port of Auckland. Econometric analyses were performed as well to evaluate the financial viability and economic performance of electric tugboats and their alternatives (i.e. conventional tugboats and hybrid tugboats).

The advantages of electric tugboats encompass decreased emissions, reduced operating expenses, improved energy efficiency, lower noise levels and potential for digital transformation through automation and data analytics. However, high initial costs, infrastructure limitations, training requirements and restricted range need to be addressed. The electric tugboat alternative seems to be the best option for scenarios with low interest rate values as increasing interest values negatively impact the salvage value of electric tugboats. It is expected that for long-term planning, the electric and hybrid tugboat alternatives will become preferential since they have lower annual costs than conventional diesel tugboats.

The outcomes of this research provide managerial insights into the practical deployment of electric tugboats and point to future research needs, including battery improvements, cost reduction, infrastructure development, legislative and regulatory changes and alternative energy sources. The advancement of battery technology has the potential to significantly impact the cost dynamics associated with electric tugboats. It is essential to do further research to monitor the advancements in battery technology and analyze their corresponding financial ramifications. It is essential to closely monitor the industry’s shift toward electric tugboats as their prices become more affordable.

The maritime industry is rapidly transforming and facing pressing challenges related to sustainability and digitization. Electric tugboats represent a promising and innovative solution that could address some of these challenges through zero-emission operations, enhanced energy efficiency and integration of digital technologies. Considering the potential of electric tugboats, the present study provides a comprehensive review of the advantages and disadvantages of electric tugboats in maritime transportation, extensive evaluation of the relevant literature, interviews with industry experts and supporting econometric analyses. The outcomes of this research will benefit governmental agencies, policymakers and other relevant maritime transportation stakeholders.

This article aims to explore the concept of chain value of the public port system in Ecuador from the perspective of importing/exporting companies, analyzing how perceived value in the use of port services affects customer satisfaction and the intermediate links of the influence of trust and commitment on customer loyalty.

Relying on a survey of 634 Ecuadorian companies with experience in international trade as port users and a theoretical framework well-established in the literature on consumer behavior, the empirical study found evidence of a positive and significant relationship with the knowledge of chain effects.

The findings confirm the chain effect and reveal ways to maintain an ongoing satisfactory, trust and committed relationship with users, thereby ultimately gaining and maintaining their loyalty. The conclusions suggest how this postulate can help to close the gap referred to the effective management of port services, and point out that port managers should be concerned with a continuous in-depth understanding of the perceived value and its chain effects.

The authors add evidence of the use of the postulate of the chain of effects on these dimensions, whose applicability is very well established, tested and consensual for the doctrine in industrial marketing. In contrast, it is scarcely present in the port relationship with its users.

We identify and further aggregate the most commonly engaged risk factors in dry port projects into dimensions. Noting the importance of developing a multi-perspective view of risk, we further assess the priority, interdependency and heterogeneity of the identified risk dimensions.

We identified 44 risk factors from the literature, which were aggregated via exploratory factor analysis (EFA) into 8 major risk dimensions. We employ a fuzzy-based decision-making trial and evaluation laboratory (DEMATEL) relationship map to articulate various relationships among the risk dimensions.

“Cost” emerged as the most important risk influencing the success of the dry port project, followed by “location,” “accessibility,” “infrastructural” and “operational,” which were also ranked prominently.

This study offers significant insight into the management of risk in dry port projects. By aggregating key risk factors into distinct dimensions, we develop a structured framework for effective risk assessment and management. The insights gleaned from the study extend globally, as it serves as a concrete knowledge base to understand potential barriers to successful dry port projects.

In this chapter, we propose a strategic framework for capacity-building in cross-border transport megaprojects. First, we make the case for infrastructure megaprojects as wicked policy fields marked by a complex web of stakeholders' interests and characterized by uncertainty and entrenched value divergence and conflict. Second, inspired by Pettigrew's contextualism and by drawing evidence from the case of the Lyon-Turin high-speed railway megaproject, we suggest that strategic management involves the analysis of three different albeit interconnected dimensions: the content of change, the process of change, and the context of change. Our study shows that variations in performance (content) are determined by and determine variations in (1) the openness or closure of national institutional contexts to civil society stakeholders (inner context), (2) the intensity of supervision and control functions realized by actor seating in the supranational institutional context (outer context), and (3) national and supranational actors' capability of making agreements over contested megaprojects aspects (process). We suggest that, from a strategic point of view, there is not a linear relationship between the content, context, and process of change in megaproject development. This is rather a complex nonlinear relationship that varies over time with little predictability. Time is a key factor in understanding these interactions between the content, context, and process. We claim that the capacity for organizing wickedness in megaprojects should rest on a socioeconomic logic and, in particular, on three core governance features: (1) open decision-making systems, (2) bottom-up performance management, and (3) active dialogue between proponents and opponents.

The purpose of this study is to analyze the challenges encountered by international nongovernmental organizations (INGOs) operating in armed conflicts within the Democratic Republic of the Congo (DRC) and the Central African Republic (CAR). Through a 20-month fieldwork analysis, this research maps logistical risks and highlights key obstacles on the ground for successful humanitarian deployments in dynamically changing and complex environments. The study brings together academics and practitioners, providing practical and concrete recommendations for nongovernmental organizations (NGOs) to focus on in the conflict zones studied.

Using a mixed-methods approach that combines qualitative and quantitative methods, this research provides valuable insights into the challenges faced by INGOs in conflict zones. After collecting data from the field, including interviews with key stakeholders and on-the-ground observations, the data analysis uses software tools such as Text Analysis Markup System analyzer and Macbeth. By adhering to ethical principles and incorporating a reflexive analysis, the study sheds light on the multidimensional nature of successful humanitarian deployments.

The primary risk in all armed conflict zones, including the DRC and CAR, is insecurity. However, to achieve a successful humanitarian deployment in such contexts, a multidimensional approach is required. This involves first securing the acceptance of local communities and conflict parties, which can be achieved through a deep understanding of both political and customary structures, with a focus on respecting key engagement leaders. Sustainability also plays a crucial role, and NGOs must maintain a secure stock of energy and provide greater initiative for on-the-ground managers to meet the expressed needs of beneficiary populations and involve them from the planning stage onwards. Finally, effective communication, cooperation and collaboration with United Nations Office for the Coordination of Humanitarian Affairs are essential to overcome procurement, technical and security risks, particularly during the initial deployment phases.

This study provides an illustration of the uncommon practice of conducting collaborative research in humanitarian settings amidst two neighboring areas of armed conflict. The authors identified 268 common risk factors across eight categories during five deployment phases. To analyze these risks based on criticality and NGO responsiveness, the authors used a multicriteria method. This approach allowed the authors to validate unanimous judgments, resulting in valuable insights and concrete recommendations.

This study aims to investigate the relationship between dynamic capabilities and sustainable business performance in Vietnamese small- and medium-sized enterprises (SMEs), focusing on the mediating role of digitalization strategies. Specifically, the authors seek to explore whether and how the three critical characteristics of dynamic capabilities (DCs) – sensing, seizing and transforming capabilities – are linked to business model innovation (BMI) or sustained performance and what dimensions contribute to their development and adoption in digitalization strategies.

The authors analyse a sample of 596 Vietnamese SMEs using a validated measurement framework to explore the three clusters of DCs activities and their contributions to digitalization strategies, BMI and sustainable business performance across economic, social and environmental dimensions.

The study highlights the pivotal role of sensing, seizing and transforming capabilities in the adoption of digitalization strategies, BMI, as well as in promoting sustainable business performance. Firstly, sensing capability profoundly influences product digitalization strategy, whereas seizing capability has the greatest impact on process digitalization strategy. Secondly, sensing and transforming capabilities significantly contribute to BMI. Thirdly, both process and product digitalization strategies exert a significant positive influence on sustainable business performance, especially the environmental dimension. Finally, the study exhibits the indirect impacts of seizing and sensing capabilities on sustainable business performance through product and process digitization strategies.

This study extends recent research by investigating the DCs underlying a firm’s digitalization strategies and contribute to ongoing calls for further investigation in the DCs literature. This research design, which draws from a validated measurement framework, responds to recent calls to broaden the toolkit used in DCs research. The practical implications of this study can benefit SMEs in Vietnam and beyond as they seek to enhance their digitalization strategies and achieve sustainable competitive advantage.

According to extant Supply Chain Risk Management (SCRM) literature, manufacturing firms must align their choice of SC bridging or buffering strategies with their operating environment to achieve high plant performance and minimize SC disruption impacts. However, very few empirical studies have examined the relative performance of these strategies in dynamic industry environments. This study aims to address this research gap. This study also seeks to supplement the limited empirical research that has examined the empirical relationships between a firm’s Supply Base Complexity (SBC), the likelihood of SC disruptions, and plant performance.

This study uses data from a cross-sectional survey of 202 manufacturing firms in India. The data is analyzed, and the study hypotheses are tested using PLS path modeling and SPSS PROCESS Macro.

The study shows that increased SBC leads to an increased frequency of SC disruptions with a negative impact on plant performance. The study also finds that the firm’s implementation of SC bridging or buffering strategies effectively moderates this performance impact. However, the study results do not support the hypothesis that industry dynamism moderates the relative effectiveness of SC bridging or buffering strategies in mitigating the negative impact of SC disruptions.

The study adds to the limited empirical research examining the SC disruption risk associated with SBC and the resulting performance impact. It addresses a gap in extant research by evaluating the efficacy of SC bridging and buffering strategies in mitigating this performance impact in dynamic industry environments.

Based on the strong feature representation ability of the convolutional neural network (CNN), generous object detection methods in remote sensing (RS) have been proposed one after another. However, due to the large variation in scale and the omission of relevant relationships between objects, there are still great challenges for object detection in RS. Most object detection methods fail to take the difficulties of detecting small and medium-sized objects and global context into account. Moreover, inference time and lightness are also major pain points in the field of RS.

To alleviate the aforementioned problems, this study proposes a novel method for object detection in RS, which is called lightweight object detection with a multi-receptive field and long-range dependency in RS images (MFLD). The multi-receptive field extraction (MRFE) and long-range dependency information extraction (LDIE) modules are put forward.

To concentrate on the variability of objects in RS, MRFE effectively expands the receptive field by a combination of atrous separable convolutions with different dilated rates. Considering the shortcomings of CNN in extracting global information, LDIE is designed to capture the relationships between objects. Extensive experiments over public datasets in RS images demonstrate that our MFLD method surpasses the state-of-the-art methods. Most of all, on the NWPU VHR-10 dataset, our MFLD method achieves 94.6% mean average precision with 4.08 M model volume.

This paper proposed a method called lightweight object detection with multi-receptive field and long-range dependency in RS images.