Containerised maritime transportation involves complex decision making processes involving multiple agents faced with significant amount of uncertainty making decisions about multi- mode of transportation. As such, shippers’ containerised maritime transportation choices have to be integrated into an integrated SC rather than be made in isolation. To complicate matters, SC and firm heterogeneity, including differences in production processes, organisational structures and shipment characteristics are all likely to influence shippers’ choice behaviour. Further, the importance and perceived value of factors influencing key decisions may vary over time, or in the event of a SCD. It is effect of the later which is the focus of this thesis.
This thesis makes use of discrete choice models applied to stated choice data to address a number of hypotheses. According to theory, population heterogeneity may result in significantly different estimations of values in non-market valuation studies. Therefore, the identification of key transport attributes and different heterogeneity sources affecting shippers’ choice from a SC perspective are the subjects of the hypotheses tested in the context of discrete choice modelling in this thesis. In light of this, the hypotheses to be tested herein are now detailed.
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The first hypothesis (H1) relates to the identification of the key maritime transport service
attributes influencing shippers’ containers transport decisions under normal operations. Based on a review of the literature, the null hypothesis is:
H0: Compared with other selection criteria (such as capacity, directness, reputation,
communication, tracking system and market consideration), freight rate, transit time, reliability, damage rate, and sailing frequency are not taking precedence over other factors, with these factors having equivalent importance when shippers make choice decisions in containerised maritime transport under normal operations.
The alternative hypothesis therefore is stated as:
H1: Compared with other selection criteria (such as capacity, directness, reputation,
communication, tracking system and market consideration), freight rate, transit time, reliability, damage rate, and sailing frequency take precedence over other factors, and these factors have different values to shippers’ choice decisions in containerised maritime transport under normal operations.
Hypothesis two (H2), examines the influences of a SCD on shippers’ preferences and the
value placed on key maritime transport service attributes. This hypothesis aims to identify the salient maritime transport service attributes influencing shippers’ transport decisions when experiencing a disruption event, and to investigate how these preferences vary in terms of attribute importance from normal operating conditions. The null hypothesis is:
H0: Surcharge or rebate, delay time, reliability, and damage rate are the same as other
potential affected factors (such as communication, documentation, and tracking system), and contribute equivalent value to shippers’ containerised maritime transportation decisions given a disruption, and shippers’ preference and WTP for these attributes under a disruption do not differ as they do under normal operating conditions.
The alternative hypothesis two therefore is stated as:
H2: Surcharge or rebate, delay time, reliability, and damage rate are found to take precedence
over other potential affected factors (such as communication, documentation, and tracking system), and contribute different value to shippers’ choice behaviour in containerised
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maritime transportation decisions given a disruption, and shippers’ preference and WTP for these attributes under a disruption do differ as they do under normal operating conditions.
If H1 and H2 are not rejected, then the following hypotheses can be tested.
The third hypothesis (H3) attempts to verify the influence of company geographic location on
shippers’ WTP for transport service attributes with and without a disruption event. The null hypothesis can be presented as:
H0: Shippers in different geographic locations have equivalent logistics preferences and
WTPs for containerised maritime transport service attributes independent of whether they are operating under normal or disrupted service conditions.
The alternative hypothesis is therefore:
H3: Shippers in different geographic locations have different logistics preferences and WTPs
for containerised maritime transport service attributes under normal operating conditions as they do under a disruption event.
The fourth hypotheses (H4) examines whether product characteristics, such as product
category and value of goods transported affect shippers’ transportation choices, and whether differences in product characteristics influence shippers’ transportation preferences given a SCD. The null hypothesis for H4 is:
H0: Shippers shipping different industrial products of differing value have the same WTPs for
containerised maritime transport service attributes under normal operating conditions as they do when facing a SCD.
The alternative hypothesis is:
H4: Shippers shipping different industrial products of differing value significantly have
different WTPs for containerised maritime transport service attributes under normal operating conditions as they do when facing a SCD.
The fifth hypothesis (H5) investigates how company characteristics (including a role of
importer/exporter and organization sales) impact on shippers’ transport decisions and WTPs for key transport attributes with or without a SCD. The null hypothesis is:
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H0: All shippers have equal WTPs for containerised maritime transport service attributes
under all operating conditions, independent of their company characteristics, such as their nature of business (importers and exporters) and firm size.
The alternative hypothesis five therefore is stated as:
H5: All shippers have unequal WTPs for containerised maritime transport service attributes
under all operating conditions, depending on their company characteristics, such as nature of business (importers and exporters) and firm size.
The sixth hypothesis (H6) explores whether different SCM strategies (such as contingency
planning, the assessment of carrier reputation and the application of JIT inventory principles) affect shippers’ WTPs for maritime transport service attributes, and how these vary during a SCD. Thus, the null hypothesis is:
H0: The WTPs for containerised maritime transport service attributes do not vary by alternate
SCM strategies under both normal and disrupted operating conditions.
The alternative hypothesis six therefore is stated as:
H6: The WTPs for containerised maritime transport service attributes do vary by alternate
SCM strategies under both normal and disrupted operating conditions.
The seventh hypothesis (H7) seeks to assess what shipping/transport characteristics (including
shipment contract terms (FOB/CIF), whether shipment reconsolidation is used, the shipment involves a transhipments, and the length of travel time) influence shippers’ WTPs for the marine transport service attributes, and whether these differ from normal and SC disrupted operations. The null hypothesis is:
H0: Shippers, independent of shipment and trip characteristics, have the same WTPs for
containerised maritime transport service attributes both under normal and disrupted operating conditions.
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H7: Shippers, independent of shipment and trip characteristics, have different WTPs for
containerised maritime transport service attributes both under normal and disrupted operating conditions.
The last hypothesis (H8) assesses whether concerns about security (e.g., terrorist attacks) or
other risks (such as delays) affect shippers’ WTPs for maritime service attributes under normal and disrupted operations. The null hypothesis is:
H0: Shippers, whether or not they consider and prepare for security and risks issues when
making their transport decision, would have exactly equivalent WTPs for containerised maritime transport service attributes under all operating conditions.
The alternative hypothesis eight therefore is stated as:
H8: Shippers, whether or not they consider and prepare for security and risks issues when
making their transport decision, would have entirely different WTPs for containerised maritime transport service attributes under all operating conditions.
74 Table 3-1: Summary of Thesis Hypotheses
Hypotheses
Important Transportation Attributes Affecting Shippers' Maritime Choice
H0: Compared with other selection criteria (such as capacity, directness, reputation,
communication, tracking system and market consideration), freight rate, transit time, reliability, damage rate, and sailing frequency do not take precedence over other factors, and these factors are having equivalent importance when shippers make choice decisions in containerised maritime transport under normal operations.
H1: Compared with other selection criteria (such as capacity, directness, reputation,
communication, tracking system and market consideration), freight rate, transit time, reliability, damage rate, and sailing frequency take precedence over other factors, and these factors have different values to shippers’ choice decisions in containerised maritime transport under normal operations.
H0: Surcharge or rebate, delay time, reliability, and damage rate are the same as other
potential affected factors (such as communication, documentation, and tracking system), and contribute equivalent value to shippers’ containerised maritime transportation decisions given a disruption, and shippers’ preference and WTP for these attributes under a disruption do not differ as they do under normal operating conditions. H2: Surcharge or rebate, delay time, reliability, and damage rate are found to take
precedence over other potential affected factors (such as communication, documentation, and tracking system), and contribute different value to shippers’ choice behaviour in containerised maritime transportation decisions given a disruption, and shippers’ preference and WTP for these attributes under a disruption do differ as they do under normal operating conditions.
Company Geography Location Impacting on Shippers' Transport Choice
H0: Shippers in different geographical locations have equivalent logistics preferences and
WTPs for containerised maritime transport service attributes independent of whether they are operating under normal or disrupted service conditions.
H3:
Shippers in different geographical locations have different logistics preferences and WTPs for containerised maritime transport service attributes under normal operating conditions as they do under a disruption event.
Production Characteristics Affecting Shippers' Transport Choice
H0: Shippers shipping different industrial products of differing value have the same WTPs
for containerised maritime transport service attributes under normal operating conditions as they do when facing a SCD.
H4: Shippers shipping different industrial products of differing value significantly have
different WTPs for containerised maritime transport service attributes under normal operating conditions as they do when facing a SCD.
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Company Characteristics Affecting Shippers' Transport Choice
H0: All shippers have equal WTPs for containerised maritime transport service attributes
under all operating conditions, independent of their company characteristics, such as nature of business (importers and exporters) and firm size.
H5: All shippers have unequal WTPs for containerised maritime transport service attributes
under all operating conditions, depending on their company characteristics, such as nature of business (importers and exporters) and firm size.
Supply Chain Management Strategies Affecting Shippers' Transport Choice
H0: The WTPs for containerised maritime transport service attributes do not vary by
alternate SCM strategies under both normal and disrupted operating conditions. H6:
The WTPs for containerised maritime transport service attributes do vary by alternate SCM strategies under both normal and disrupted operating conditions.
Shipping Characteristics Affecting Shippers' Transport Choice
H0: Shippers, independent of shipment and trip characteristics, have the same WTPs for
containerised maritime transport service attributes both under normal and disrupted operating conditions.
H7: Shippers, independent of shipment and trip characteristics, have different WTPs for
containerised maritime transport service attributes both under normal and disrupted operating conditions.
Security Issues and Risks Concerns
H0: Shippers, whether or not they consider and prepare for security and risks issues when
making their transport decision would have exactly equivalent WTPs for containerised maritime transport service attributes under all operating conditions.
H8: Shippers, whether or not they consider and prepare for security and risks issues when
making their transport decision would have entirely different WTPs for containerised maritime transport service attributes under all operating conditions.
3.5 Fundamentals of Discrete Choice Modelling