Green Shipping Management

Lun, Y.H. Venus; Lai, Kee‐hung; Wong, Christina W.Y.; Cheng, Tao

doi:10.1007/978-3-319-26482-0

Cited by 21 publications

(23 citation statements)

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“…Yuen et al (2016b) showed that the link between SSM and business performance could be strengthened by employing continuous improvement principles. Lun et al (2016) emphasised SSM with a focus on relationship management as it plays a key role in enhancing stakeholders' satisfaction and building trust and commitment.…”

Section: Sustainable Shipping Management Is Defined As Addressing Thementioning

confidence: 99%

A theory-driven identification and ranking of the critical success factors of sustainable shipping management

Tran

Yuen

et al. 2020

Journal of Cleaner Production

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Sustainable shipping management is arguably the most challenging issue that shipping companies faced for the coming years. Hence, examining the critical success factors of sustainable shipping management is vital. Although previous research mainly focused on the motives and implication of sustainable shipping management, practical research that proposes how sustainable shipping management can be implemented is still lacking. Therefore, this study fills the gap by identifying and ranking the critical success factors of sustainable shipping management with a theory-driven approach. The critical success factors were developed through the theoretical lenses of five organisational theories, namely, stakeholder theory, resource-based view theory, relational-view theory, innovation diffusion theory, and contingency (fit) theory. Based on these theories, this study proposes stakeholders' focus, intra-firm management, interfirm collaboration, new technology acceptance, and strategic fit as the critical success factors of sustainable shipping management. Further, 20 sub-criteria were identified to operationalise the critical success factors. A survey questionnaire was pretested and then administered to 36 shipping companies in Vietnam. Thereafter, the obtained data was analysed using fuzzy analytic hierarchy process. The findings show that the critical success factors of sustainable shipping management, in descending order of their importance with their respective local weights, are (1) stakeholders' focus (0.298), (2) intra-firm management (0.248), (3) new technology acceptance (0.156), (4) inter-firm collaboration (0.154), and (5) strategic fit (0.143). Moreover, results of this study show that among the sub-criteria of sustainable shipping management, the most important ones are primarily related to monetary resources and tangible infrastructures and equipment. Additionally, sustainable shipping management implementation in shipping companies can be improved by addressing the needs of stakeholders and aligning sustainable shipping management activities with shipping companies' strategies. By evaluating the critical success factors, this study contributes to theory by holistically identifying and reviewing five theoretical frameworks that can enhance sustainable shipping management. This research also contributes to practice by contextualising and operationalising these theories into meaningful criteria and sub-criteria for shipping companies to implement sustainable shipping management. Consequently, it addresses the question of how sustainable shipping management should be implemented to maximise a shipping company's sustainability performance.

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Section: Sustainable Shipping Management Is Defined As Addressing Thementioning

confidence: 99%

A theory-driven identification and ranking of the critical success factors of sustainable shipping management

Tran

Yuen

et al. 2020

Journal of Cleaner Production

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“…Incluso muchas navieras han adoptado prác ticas ecológicas de envío (GSPs-Green Shipping Practices). Las GSP incluyen el cálculo de la huella de carbono de las rutas de envío y el uso de equipos de envío alternativos con el objetivo de reducir el daño ambiental en el transporte de cargas (Lun et al, 2016).…”

Section: Prácticas Sostenibles En El Transporte Marítimounclassified

“…Con este objetivo, muchas empresas han optado por asociarse en la bús queda de soluciones conjuntas, por ejemplo, navieras como Hapag-Lloyd, American President Lines (APL), Maersk, y los cargadores como Home Depot, Mattel o Hewlett Packard (HP), forman parte del Grupo de Trabajo de Carga Limpia. Estas colaboraciones buscan conectar diferentes partes interesadas (fabricantes, intermediarios comerciales o transportistas de carga), para abordar los problemas de incumplimiento en los códigos de conducta y las regula ciones, a fin de mejorar el bienestar en la comunidad (Lun, Lai, Wong y Cheng, 2016). Estas iniciativas ponen de manifiesto que, para conseguir resultados óptimos en la gestión de prácticas sostenibles, es importante la colaboración entre empresas.…”

Section: Introductionunclassified

Efectos de la sostenibilidad y del valor logístico en las relaciones entre empresas de transporte marítimo

2020

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El objetivo de este trabajo fue analizar cómo la sostenibilidad (económica, social y ambiental), bajo el enfoque de triple línea base, afecta la calidad de servicio, el valor logístico y la satisfacción en empresas del sector marítimo. Se propone un modelo teórico que se contrasta con la información suministrada por una muestra de 50 responsables de empresas (transitarios, importadores y exportadores) en Panamá. La información se analiza mediante la estimación de regresión por mínimos cuadrados parciales, que permite confirmar el carácter multidimensional de la sostenibilidad y del valor logístico. Los resultados también confirman que las percepciones de los clientes sobre las iniciativas de sus proveedores, con base en este enfoque, poseen la capacidad de impulsar su satisfacción a través de la calidad y el valor; esto demuestra los beneficios de llevar a cabo tales iniciativas y, con ello, su alcance a nivel global.

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“…The health of marine industry hinges on the environmentally sustainable operations in maritime shipping [1]. To control the air pollution from ships, the International Maritime Organization (IMO) issued the MARPOL Annex VI-prevention of air pollution from ships in 2005, and delineated several sulphur emission control areas (SECAs), such as the Baltic Sea, the North Sea and the North American Area (coastal areas of the United States and Canada) [2].…”

Section: Introductionmentioning

confidence: 99%

An Expected Utility-Based Optimization of Slow Steaming in Sulphur Emission Control Areas by Applying Big Data Analytics

et al. 2020

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This paper analyses the operator's risk-based decision (RBD) company for slow steaming, and creates a sailing speed optimization model for slow steaming (SSOM-SS), aiming to balance the expected utility-based objectives (EUO) of fuel consumption, SOx emissions and delivery delay. Considering the limitations of existing theoretical fuel consumption functions under uncertainties in voyages, the authors applies big data analytics (BDA) techniques like data fusion and feature selection to provide the SSOM-SS with accurate and suitable data on fuel consumption. In addition, a solver is built based on the genetic algorithm (GA) to solve the SSOM-SS. The effectiveness of the SSOM-SS is verified through a case study on the RBD for slow steaming of an Orient Overseas Container Line (OOCL) containership sailing across the sulphur emission control areas (SECAs) in Chinese coastal regions. The results show that the SSOM-SS can facilitate the RBD for slow steaming, and provide a novel tool for sailing speed optimization. INDEX TERMS Big data analytics (BDA), slow steaming, sailing speed optimization, fuel consumption, genetic algorithm (GA), risk aversion.

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Green Shipping Management

Cited by 21 publications

References 0 publications

A theory-driven identification and ranking of the critical success factors of sustainable shipping management

A theory-driven identification and ranking of the critical success factors of sustainable shipping management

Efectos de la sostenibilidad y del valor logístico en las relaciones entre empresas de transporte marítimo

An Expected Utility-Based Optimization of Slow Steaming in Sulphur Emission Control Areas by Applying Big Data Analytics

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