Discrete Choice Analysis of Shippers' Preferences

Ben‐Akiva, Moshe; Bolduc, Denis; Park, Jay Q.

doi:10.1108/9781786359537-008

Cited by 12 publications

(4 citation statements)

References 8 publications

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“…where Q is the total of shipments over the period of analysis, say a year, and Z is the vector of characteristics of the specific transport considered (mode, carrier, means or combination thereof). These characteristics are mainly its reliability R, safety during transport S, transport time T, flexibility F and frequency N (Ben-Akiva, Bolduc & Park, [17]; Beuthe, Bouffioux, Krier & Mouchart, [18]).…”

Section: Estimating Total Cost Of Logistics Transport Chainmentioning

confidence: 99%

Priority Areas in Nigeria’s Maritime Sector: Developing Agenda for Research

Onwuegbuchunam¹

2019

IJTET

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This paper proposes research agenda to identify research priority areas in Nigeria's maritime sector.. The aim is twofold: to systematically identify and evaluate critical areas in the maritime sector as basis for optimized investments in human and material resources and secondly based on our findings, propose policy response models that could be applied to resolve impacts of random developments in international shipping environment on Nigeria's maritime sector. The main research agenda items addressed in this paper included: port infrastructural facilities, shipping outputs, ship repair service capacity, maritime clusters, offshore shipping service demands, pollution management and manpower needs in the industry. Risk management strategies for commercial shipping operation and critical transport infrastructure/logistics supply chains were also discussed. Specifically, modelling techniques and models that could be employed for empirical studies on the identified areas were proposed.

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Section: Estimating Total Cost Of Logistics Transport Chainmentioning

confidence: 99%

Priority Areas in Nigeria’s Maritime Sector: Developing Agenda for Research

Onwuegbuchunam¹

2019

IJTET

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“…The above contributions to SNDP are made to achieve a system-optimal solution. However, modeling for freight transport demand has significant wields on SNDP with the expanding commercial competitiveness over the past decade [7]. During a demand analysis, many sophisticated disaggregated models based on individual data have been used.…”

Section: Introductionmentioning

confidence: 99%

Multicriteria Intermodal Freight Network Optimal Problem with Heterogeneous Preferences under Belt and Road Initiative

Zhang

Tavasszy

et al. 2020

Sustainability

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In this study, we demonstrate the importance of incorporating shippers’ preference heterogeneity into the optimization of the China Railway express network. In particular, a bilevel programming model is established to minimize the total construction cost for the government in the upper level and maximize the shippers’ satisfaction in the lower level. The proposed model considers price, time, reliability, frequency, safety, flexibility, traceability, and emission. Two designs are obtained by applying the model to two scenarios, in which one is of the aggregate shipper group and the other is of the three distinct clusters. Results show that explicitly including heterogeneity in network optimization pays off in terms of the dramatic increase in shippers’ satisfaction and the share of the sustainable railway without generating extra cost for the system. The results of this study could lead to insightful implication for proper network planning for the China Railway express and some useful suggestions on the subsidies of the government.

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“…Usually, DCM in transport are based on survey data (either revealed or stated preferences). As pointed out by Ben-Akiva et al (2008), this kind of data is expensive and usually proprietary. Fortunately, nowadays there are a lot of sources of public data that reveal choices.…”

Section: Introductionmentioning

confidence: 99%

“…Ben-Akiva, Bolduc and Park (2008) used a random coefficients model to predict shippers' choice of mode but, to the best of the authors' knowledge, only two studies controlled for preference heterogeneity in the port choice field, both of them by including the size of port users as a continuous variable in the form of an interaction term: Steven & Corsi (2012) and Kashiha, Thill & Depken (2016).…”

Section: Introductionmentioning

confidence: 99%