A Review Of The Transportation Mode Choice And Carrier Selection Literature

A review of the transportation
mode choice and carrier
selection literature
Mary J. Meixell and Mario Norbis
Department of Management, Quinnipiac University, Hamden,
Connecticut, USA
Abstract
Purpose – The purpose of this paper is to categorize transportation choice research (mode choice and
carrier selection) leading to insight on themes in the literature and directions for future research
Design/methodology/approach – The proposed transportation choice research categorization
framework is based on a comprehensive literature review of the peer-reviewed journal papers
published over the past 20 years, supplemented with a review of practitioner articles to identify
current challenges in the logistics field. The academic papers are analyzed in terms of research
purpose/question, methodology, findings, and challenges addressed.
Findings – The review reveals that several important themes are under-represented in the
transportation choice literature: environmental and energy use concerns; security in the supply chain;
supply chain integration; international growth; and the role of the internet and emerging information
technologies. This review also found that simulation, case study, and interview methodologies are
under-represented, and that normative modeling research is only lightly represented in this research.
Originality/value – The contributions of this research are three-fold: the development of a
classification scheme for transportation choice research, a structured review that provides a guide to
earlier research on the subject of transportation choice, and the identification of research issues for
future investigation.
Keywords Transportation, Freight forwarding, Channel relationships, Supply chain management
Paper type Literature review
Introduction
A key decision in logistics management is the selection of the transportation mode and
carrier to move the firm’s inbound and outbound freight. Managers typically consider
multiple attributes when making this decision, often focusing on cost and transit time
as the primary criteria. This is not a trivial decision, however, as the process often
involves multiple criteria, some of which are not readily quantified. Additionally, the
importance of individual factors often differs from industry to industry, company to
company, and even within a company from one facility to the next. Then too, mode and
carrier selection is often viewed differently for inbound and outbound shipments, even
at the same location.
Mode choice and carrier selection are part of the decision-making process in
transportation that includes identifying relevant transportation performance variables,
selecting mode of transport and carrier, negotiating rates and service levels, and
evaluating carrier performance (Monczka et al., 2005). No doubt, these are all important
decisions for logistics managers. Within manufacturing firms, transportation costs
average 20 percent of total production costs (Russell and Taylor, 2003). For the
Norwegian companies surveyed in Pedersen and Gray (1998), more than 50 percent of
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The International Journal of Logistics
Management
Vol. 19 No. 2, 2008
pp. 183-211
q Emerald Group Publishing Limited
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DOI 10.1108/09574090810895951

the total logistics cost of a product is attributed to transportation. But transportation is
more than an incurred cost, as transportation and distribution can be instrumental in
achieving competitive advantage (Reimann, 1989). The performance of the transport
carrier may influence the effectiveness of the entire logistics function of a company.
It follows that the process of selecting an appropriate transport carrier is important to
the firm’s success.
At the same time, mode and carrier selection have become increasingly complex.
Historically, carrier selection has been structured as a two-step process, first the choice
of the mode followed by the selection of the carrier within that mode. These decisions
today are often made simultaneously, along with the alternative of outsourcing to
third-party logistics organizations. Deregulation of the rail and trucking industries,
implementation of innovative manufacturing strategies such as JIT, and increased
emphasis on quality management have all made the transportation choice problem
more complex. More factors/variables are involved in the decision, leading to the
development of numerous approaches and models that not only involves multiple
variables but also multiple objectives leading to compromise optimal solutions
(Murphy and Farris, 1993).
As will be demonstrated in this literature review, this topic has drawn a good deal of
interest from the research community. We argue here, however, that research in
logistics to date has employed a limited set of paradigms, and that these paradigms
should be updated. This paper addresses change in the challenges associated with
logistics in general, and then extends to the context of mode and carrier selection in
particular. Accordingly, we find that changes in both the methodologies and in the
research agenda that addresses transportation choice issues are in order.
Industry challenges
A number of forces have brought about new challenges in logistics management, which
we use as motivation for this study. Some forces originate in the shipper community –
retailers are requiring, for example, the use of RFID technology in transportation and
distribution of the products into their facilities. Others are based with the carrier
community – as is the case with railroads and trucking companies who have made
capital decisions that have led to capacity shortfalls in facilities and equipment. Some of
the challenges originate with the consumers themselves, such as the growing concern for
the environmental impact of the products they purchase, which influences companies to
strive to be “green” in the eye of the consumer. And then other challenges are driven by
markets, including the unprecedented fuel prices that have induced substantial
increases in transportation rates. In this section, we identify five logistics challenges that
influence transportation choice: capacity shortages, international growth, economies of
scale and scope, security concerns, and environmental and energy use concerns.
Transportation capacity shortage. An important issue that has surfaced in logistics
management is that of capacity shortages in all transportation modes. In the motor
carrier industry, Byrne (2004) reports that as fuel prices have risen, carriers have had to
raise prices, leaving shippers with an increase in rates without a concomitant increase
in service. Compounding the motor carrier shortage problem are tighter
hours-of-service regulations, driver shortages, and higher tolls that strain truck
capacity. In addition to these complicating factors, shippers are moving fewer goods
more frequently so that more trucks are traveling partially loaded. Experts attribute
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rail capacity problems to inadequate investment which translates in a reduction in
service reliability (LaLonde, 2004). The problem has drawn the attention of
government regulators as the Surface Transportation Board recently announced the
creation of a Rail Energy Transportation Advisory Committee to aid in developing
policy that ensures that increased production of ethanol can be delivered, respectively,
to power companies and car drivers (Kamalick, 2007).
Airlines too have cut over one quarter of their seat capacity since 2000 as a response
to decreased demand and financial hardship (LaLonde, 2004). Maloni and Jackson
(2005) report that even though international marine container volumes have surged
over recent years, North American ports and their supporting container distribution
networks have not increased capacity accordingly. These capacity limitations tend to
affect all carriers within a given mode more or less equally, rather than differentiating
among carriers, so the ability of individual carriers to overcome these limitations will
help to differentiate them from the competition.
International growth. Global transportation from sources and to markets around the
world yields higher cost and longer transit times, and so international growth is an
important challenge in logistics management. On the one hand, it is often the activities
associated with international trade that provide the challenge, e.g. providing adequate
transportation and storage, getting items through customs, delivering to foreign
locations in a timely fashion at an acceptable cost. In many cases, these challenges are
alleviated by the participation of third-party logistics services (Wisner et al., 2005) and
partnership arrangements (Ireton, 2007).
On the other hand, the volume of material, information and money flowing across
international borders provides a challenge because it is ever expanding. In the USA, for
example, the import and export trade has grown faster than the US economy and this
trend is likely to continue. The growing capability to design and produce sophisticated
products abroad using skilled labor and complex processes has expanded off-shore
sourcing beyond the familiar low-cost labor intensive products. As a result, the number
and membership of trading blocks have been growing such that in the western
hemisphere alone there are more than six such blocks (Webster, 2008). And finally,
since many international shipments are by ocean, this presents a new challenge for
many logistics managers relative to carrier selection, as all-water transport for this
class of shipments has risen about 65 percent since 1990 (Favey, 2003).
Economies of scale and scope. An area that is often overlooked in carrier selection is
the impact of economies of scope (also known as network effects) and economies of
scale on carrier choice. Economies of scope are readily apparent relative to the use
of transportation equipment after it is emptied. This is also referred to as the empty
backhaul, and has been addressed in a general context (Mentzer, 1986), in
container-on-barge operations (Choong et al., 2002), in inter-modal railroad-truck
transportation (Evers, 1994) and in retail logistics (Dutton, 2003; Byrne, 2004).
Economies of scale, on the other hand, are a concern relative to shipment size. There is
a strong incentive to ship in full truckloads to minimize the cost associated with the
considerable capital expenditure for equipment. Economies of scale are also affected by
the handling of inventory – it is cheaper to ship cases than to ship individual units and
it is cheaper to ship pallets than to ship individual cases.
Security concerns. Another important issue that logistics managers face pertains to
security in the supply chain, from the perspective of complying with new security
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measures put in place to reduce terrorist threats, and from the perspective of dealing
with the aftermath of a terrorist attack that influences their business operation.
An important consequence of the new security measures is an additional $151 billion
annual cost, $65 billion of which is in logistical changes to supply chains (Russell and
Saldanha, 2003). Shippers can minimize these impacts by selecting security-conscious
carriers, shipping via secure ports, meeting packaging security requirements, and
providing background information on key personnel (Rinehart et al., 2004).
Furthermore, logistics managers would do well to adjust relations with suppliers
and customers, contend with transportation difficulties, and amend inventory
management strategies (Sheffi, 2001).
Environmental and energy concerns. A growing concern over the environment and
energy use also presents a challenge to logistics managers. The issues surrounding the
environment are certainly broad (Nijkamp et al., 1997; Markley and Davis, 2007;
Patterson et al., 2008). Environmental impact is of increasing concern to consumers,
evidenced by research from LEK Consulting who found that just over half of people in
the UK say they “would value details concerning a product’s carbon footprint when
making a buying decision” (Harvey, 2007a). Similar in concept to nutritional labels, a
carbon footprint label would show consumers how their buying decisions increase or
decrease their environmental impact (Harvey, 2007b). Wal-Mart Stores CEO Lee Scott
recently addressed 250 supplier CEOs to outline the company’s plans to hold them
accountable for their “carbon footprints” and excess packaging (Neff, 2007). The
transportation sector is a major contributor to air pollution (57 percent of the carbon
monoxide), acid rain, maritime water quality problems, and noise (Coyle et al., 2006).
Srivastava (2007) identifies a need for integrating environmentally sound choices into
supply-chain management research and practice, minimizing the impact of
transportation on the environment.
Plan for this paper
Given this set of current issues in logistics management, we now turn our attention to
the transportation choice literature. In the next section, we describe the methodology
we followed for this review. We then summarize each of the selected papers, and
analyze the research methods, approaches, and challenges in logistics management.
We close the paper with insight on the themes and missing themes that lead to new
research questions that the academic community may undertake to continue to support
the business community in the area of transportation choice.
Methodology for this review
In this review, we focus on the literature relating to transportation choice, i.e. mode
choice and carrier selection, from the joint perspective of the logistics management and
research communities. We categorize research in this area using multiple dimensions.
First, we adopt a practical point of view and scan the literature to identify challenges
currently faced by logistics managers and the approaches developed to address them.
The results of this review are described in the previous section and fall into five
categories: transportation capacity shortage, international growth, economies of scale
and scope, security concerns, and environmental and energy concerns.
The subject of transportation choice has long attracted the interest of academic
researchers. It has been 40 years since Baumol and Vinod (1970) first investigated
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shippers’ choice of transport and developed a model to determine the optimal choice of
mode as a trade-off among freight rates, speed, dependability and en-route losses.
Many other researchers have followed their lead – some of the early work includes
Grabner et al. (1971), Saleh and La Londe (1972); Evans and Southard (1974) and
Jerman et al. (1978).
In this review, we focus on articles published since de-regulation, and largely over
the past two decades. This literature can be classified into three categories of research:
attribute identification, decision process development, and supply chain integration.
The first research category entails identifying important attributes, primarily for the
carrier selection decision. Some of this research relies on surveys and interviews to better
understand shipper priorities for carrier choice; others are shipper-carrier comparison
studies that endeavor to explain why carriers have a different perspective on which
attributes are most important to shippers. The second category is the study of the mode
choice and carrier selection decision processes, sometimes including the development of
qualitative or mathematical models to support the process. These models are in some
cases descriptive in nature, and in other cases they are normative and attempt to
prescribe how the transportation choice decision should be made in practice. The third
category of research pertains to supply chain management, where firms collaborate to
integrate processes; in this case, we include articles that address transport choice as one
of the decisions. These dimensions are summarized in Table I, and serve as a
categorization scheme for our review of the academic literature on the subject.
We exclude third party logistics research from this review as the topic has recently
been comprehensively reviewed by Selviaridis and Spring (2007). Their review
highlights that the decision to outsource is substantively different from the carrier
selection decision, but the factors used to evaluate alternate providers are similar –
cost, service quality, reliability, flexibility, and responsiveness.
With this scope in mind, we conducted a search using library databases that cover
the top logistics journals, including International Journal of Logistics Management,
Journal of Business Logistics, International Journal of Physical Distribution and
Logistics Management, Transportation Journal, and Transportation Research. To
ensure a thorough examination of the carrier selection literature, we also identified
articles in other major journals including Industrial Marketing Management, Industrial
Management and Data Systems, Transportation Research Forum, etc. and included
those based on a foundation published in the top logistics journals.
From these sources, we selected 48 articles that span the last 20 years on the topic of
mode choice and carrier selection. In this paper, we summarize the articles and then
categorize the literature according to the review dimensions to facilitate identification
of patterns that point to themes as well as missing themes. These research articles
deploy a variety of research methods as illustrated in Table II. The list of research
Challenges Approaches
Transportation capacity shortage Attribute identification
International growth Decision process
Economies of scale and scope Supply chain integration
Security concerns
Environmental and energy use
Table I.
Literature review
dimensions
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methods are adopted from Sachan and Datta (2005) and include survey, simulation,
interviews, mathematical models, case studies, conceptual models. Note that the
majority of the articles employ a survey (38 percent) or a mathematical model
(44 percent) in their investigation. Several of the papers included simulation as part of
their methodology (Moore et al., 1991; Crosby and LeMay, 1998; deJong and Ben-Akiva,
2007), but that none relied on simulation models as the primary method in this body of
research is also noted.
We found no literature reviews of the same scope as this review on the subject of
mode choice and carrier selection. On a more limited scope, we found a literature
review on carrier attribute identification (Keller, 1996), and research articles that
provide excellent reviews on the subject of attribute identification (Coulter et al., 1989;
Semeijn, 1995a, b; Evers et al., 1996; Kent et al., 2001; Dobie, 2005). We also draw the
reader’s attention to related reviews, including logistics management (Sachan and
Datta, 2005), third party logistics (Selviaridis and Spring, 2007), supply chain
management (Bechtel and Jayaram, 1997; Mentzer et al., 2001), and horizontal
cooperation in the supply chain (Cruijssen et al., 2007).
The final categorization addresses the challenges: transportation capacity
shortages, international growth, economies of scale and scope, security concerns,
and environmental and energy use concerns. We assessed each research paper relative
to these dimensions as follows. Articles were considered to address the transportation
capacity shortage if equipment availability, or a closely related term, was included in
the list of attributes. We also included articles that address capacity from a policy
perspective relating to national infrastructure issues. Articles that included attributes
that evaluated a firm’s ability to ship internationally (e.g. ships to Mexico), or had a
high percentage of international shippers in the database, were considered to contain
the international dimension. Note that shipments between countries in the EU were
also considered international shipments. For the environmental/energy concerns
category, we looked for the use of the term or a concept in the problem description, and
a response in the study to address it. Articles were treated as addressing the security
dimension if attributes relating to security were included, or if the terms or concepts
were used in the problem description, along with a response in the study that
addressed it. Finally, articles were treated as addressing the network effect dimension
if attributes relating to economies of scope were included, or if the terms or concepts
were used in the problem description, along with some type of response in the study to
address it. Note that although some of the articles mentioned these dimensions in their
Methodology Percent
Surveys (18) 38
Simulation (0) 0
Interviews (1) 2
Math model (20) 42
Case study (1) 2
Conceptual model (2) 4
Other (3) 6
Multi-methods (3) 6
Total (48)
Table II.
Research method
summary
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introductory remarks, we selected for the dimension analysis only those that dealt with
the issue in a significant way in the research paper.
A framework for the mode choice/carrier selection problem
In this section, we review the selected research articles in chronological order.
This ordering reflects the issues that were important in transportation choice research
over time, as well as the decision technologies available and of interest in the academic
community. In Tables III-V, we summarize the characteristics of the articles along
Methodology Papers
Surveys (18) Abshire and Premeaux (1991)), Bagchi et al. (1987), Bardi et al. (1989),
Coulter et al. (1989), Crum and Allen (1997), Dobie (2005), Foster and
Strasser (1991), Gibson et al. (1993, 2002), Lambert et al. (1993), Kent et al.
(1999, 2001), Murphy et al. (1991, 1997), Pearson and Semeijn (1999),
Pedersen and Gray (1998), Premeaux (2002) and Semeijn (1995a, b)
Simulation (0)
Interviews (1) Esper and Williams (2003)
Math model (20) Bagchi (1989), Carter and Ferrin (1995), Caputo et al. (2005), Danielis et al.
(2005), deJong and Ben-Akiva (2007), Evers and Johnson(2000), Evers et al.
(1996), Garrido and Leva (2004), Kuo and Soflarsky (2003), Larson (1988),
Liao and Rittscher (2007), Liberatore and Miller (1995), Lu (2003), Maier
et al. (2002) Miller and deMatta (2003), Min (1998), Sheffi et al. (1988),
Shinghal and Fowkes (2002), Voss et al. (2006) and Walters (1988)
Case study (1) Carter and Ferrin (1995)
Conceptual model (2) Murphy and Farris (1993) and Naim et al. (2006)
Other (3) McGinnis (1989, 1990) and Pisharodi (1991)
Multi-methods (3) Caplice and Sheffi (2003), Crosby and LeMay (1998) and Moore et al. (1991)
Table III.
Research methods
Topics Papers
Transportation choice – attribute
identification (27)
Abshire and Premeaux (1991), Bardi et al. (1989), Bagchi et al.
(1987), Crosby and LeMay (1998), Crum and Allen (1997),
Danielis et al. (2005), Dobie (2005), Evers and Johnson (2000),
Evers et al. (1996), Foster and Strasser (1991), Gibson et al.
(1993, 2002), Kent and Parker (1999), Lambert et al. (1993), Lu
(2003), Maier et al. (2002), McGinnis (1990), Murphy and Farris
(1993), Murphy et al. (1991, 1997), Naim et al. (2006), Pearson
and Semeijn (1999), Pedersen and Gray (1998), Premeaux (2002),
Semeijn (1995a, b), Shinghal and Fowkes (2002) and Voss et al.
(2006)
Transportation choice – decision
process (12)
Bagchi (1989), Caputo et al. (2005), Coulter et al. (1989), Danielis
et al. (2005), deJong and Ben-Akiva (2007), Garrido and Leva
(2004), Webster (2008), Liberatore and Miller (1995), McGinnis
(1989), Min (1998), Pisharodi (1991) and Sheffi et al. (1988)
Transportation choice – supply
chain integration (9)
Caplice and Sheffi (2003), Carter and Ferrin (1995), Esper and
Williams (2003), Larson (1988), Liao and Rittscher (2007), Miller
and deMatta (2003), Moore et al. (1991), Murphy and Farris
(1993) and Walters (1988)
Table IV.
Research topic in
transportation choice
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the research dimensions. In particular, we note in each case the research question as it
pertains to mode choice and carrier selection, the research method, and the findings.
Transportation choice – identifying carrier attributes
We start this review with Bagchi et al. (1987), which was written at the time of JIT
systems introduction into American manufacturing plants. The authors of this paper
investigated how JIT influences attributes for carrier selection, as the changes typically
resulting from JIT implementations are likely to influence the attributes for carrier
selection. This research was based on a questionnaire which asked shippers to rate the
importance of carrier selection determinants. Factor analysis reduced the individual
attributes to four factors: rate, customer service, claims handling/follow-up, and
equipment availability/service flexibility. The analysis that compared organizations
using JIT and those not using JIT revealed that firms in the JIT group give
significantly higher emphasis to all factors. The results also showed that customer
service received the maximum emphasis for both groups of firms, whether or not the
firm worked in a JIT environment. Bardi et al. (1989) compare the importance of the
same determinants of carrier selection before and after the passage of the Motor Carrier
Act of 1980, and find that the greatest change in emphasis was in the rate-related
carrier selection factor, and to a lesser extent in the customer service factor. Both of
these papers addressed the capacity issue from the challenge dimensions discussed
earlier – equipment availability is on their list of attributes.
Thus, some of the research on transportation attributes is motivated by
de-regulation of the transportation industries in the 1980s and the impact it had on
how transportation carriers manage their business, especially relative to marketing to
their customers in a dramatically changed environment. McGinnis (1990) reviewed the
Challenges Papers
Capacity (29) Bagchi et al. (1987), Bagchi (1989), Bardi et al. (1989), Caplice
and Sheffi (2003), Crosby and LeMay (1998), Dobie (2005), Esper
and Williams (2003), Evers et al. (1996), Foster et al. (1991),
Garrido and Leva (2004), Kent et al. (1999, 2001), Lambert et al.
(1993), Liao and Rittscher (2007), Liberatore and Miller (1995),
Lu (2003), Maier et al. (2002), McGinnis (1989, 1990), Miller and
deMatta (2003), Min (1998), Moore et al. (1991), Murphy et al.
(1991, 1997), Naim et al. (2006), Pearson and Semeijn (1999),
Sheffi et al. (1988), Shinghal and Fowkes (2002) and Voss et al.
(2006)
International growth (14) Caputo et al. (2005), Crum and Allen (1997), Danielis et al. (2005),
deJong and Ben-Akiva (2007), Dobie (2005), Garrido and Leva
(2004), Kent et al. (1999, 2001), Lu (2003), Maier et al. (2002),
Murphy et al. (1991), Pearson and Semeijn (1999), Pedersen and
Gray (1998) and Shinghal and Fowkes (2002)
Economies of scale and scope (5) Caplice and Sheffi (2003), Caputo et al. (2005), deJong and
Ben-Akiva (2007), Esper and Williams (2003) and Moore et al.
(1991)
Security concerns (1) Voss et al. (2006)
Environmental/energy concerns (0)
Table V.
Challenges in logistics
management
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carrier attribute literature before and after deregulation and found that transportation
choice was largely influenced by six factors: freight rates; reliability; transit time;
loss/damage/claims processing/tracing; shipper market considerations; and carrier
considerations. Service variables were found to be more important than freight rates on
the average; however, freight rates are an important variable and in some segments
rank higher than service. This paper also addressed the capacity issue – the “carrier
consideration” variable includes “availability” as an attribute.
Several authors investigated the degree to which carriers hold the same view on
shipper emphasis of carrier selection attributes. Abshire and Premeaux (1991)
addressed this research question with a questionnaire that queried managers in both
the carrier and the shipper communities on the relative importance of variables used to
select carriers. The researchers found that there are significant ranking discrepancies
and conclude that shippers and carriers do not classify nineteen of the thirty-five
selection variables similarly, which may very well lead to carriers not emphasizing
the more important selection variables. In a later study, Premeaux (2002) revisited this
line of research with a similar survey that provided for a longitudinal analysis.
He found that:
.
shippers were more concerned in 2001 than in 1991 with information access,
consistent carrier performance, solid customer relations, and availability of
certain desired services; and
.
the degree to which carriers understood shipper priorities increased notably over
this time.
In 1991, shippers and carriers agreed on ratings (i.e. there were no statistically
significant differences) on 16 of 35 attributes versus agreement on 25 of 36 variables in
2001. Apparently, for the sample surveyed by Premeaux, carriers have improved
in their understanding of shipper needs. We found that none of the four
under-represented logistics challenges identified earlier were directly addressed in
this research.
Foster and Strasser (1991) also ranked carrier selection criteria, paying particular
attention to why shippers and carriers rank selection factors differently. They conduct
a survey to compare how shippers and carriers:
.
rank criteria; and
.
appraise performance within their organizations, and found similar results to
earlier research studies on the subject.
Many carrier managers at that time believed that shippers really valued price, even
though they said they valued service. At the same time, many shippers said they
valued long-term relationships with carriers, when in fact their managers were
rewarded the least for developing these relationships. The authors drew two
conclusions: selection criteria are best viewed as a package, and both carriers and
shippers would do well to reward performance which supports the true goals of the
firm. This research addressed the capacity issue, as equipment availability is on their
list of selection criteria variables.
Lambert et al. (1993) developed and administered a questionnaire to shippers to
investigate the criteria for selecting LTL carriers. The study included a total of 166
possible attributes. The results indicated that respondents placed great importance on
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high-quality customer service, accurate billing, and surprisingly, were relatively
unconcerned with price as long as the rates they paid were competitive (i.e. within an
acceptable and reasonable range). Interestingly, the study also investigated
relationships between performance scores and importance scores for the attributes
deemed most critical, and found that carriers typically under-perform on the highest
ranked attributes and thus remain undifferentiated. This study provides a good
summary of attributes in the carrier selection process. This paper addressed as form of
the capacity issue, as the “ability to provide direct delivery without interlining” is on
their list of selection criteria.
When shippers and carriers choose to form a long-term alliance instead of the
traditional transaction-based relationship, the criteria for transportation choice will
change, as demonstrated in Gibson et al. (1993). In this research, these authors
developed and administered a shipper survey and found that shippers select and
evaluate carriers in a partnership environment based on willingness to meet service
expectations, established history of outstanding performance, willingness to focus on
continuous improvement, ability to handle special needs and emergencies, willingness
to meet cost goals, strong technical capability, and established safety programs – in
descending order of importance. Gibson et al. (2002) follow up with a second study that
investigated critical success attributes in their partnership. They survey both shippers
and carriers concerning the relative importance of 13 partnership characteristics and
found that shippers ranked cost, effectiveness, and trust as most important, while
carriers ranked trust, effectiveness and flexibility as the top attributes. Note that this
differs from earlier studies that tested carrier perception of shipper practices, as this
study evaluated the characteristics that carriers value in a partnership relationship
with a shipper. None of the logistics challenges identified earlier are directly addressed
in this research.
In a study addressing carrier-shipper relationships, Crum and Allen (1997) surveyed
managers in the motor carrier industry to investigate carrier perceptions of the
importance that shippers attach to carrier selection criteria. Carrier managers were
asked to rank 22 selection criteria which revealed that the most important factors at
that time were reliability, rate, and quality of carrier personnel. The authors included a
factor and assessed the importance of international shipping in this study and found
that it was perceived as fairly low in relative importance, as the mean score on a
seven-point Likert scale was 2.88 versus 6.5 for the highest ranking factor. This paper
contains an international theme and so addresses the international challenge from the
dimensions list.
Lu (2003) also investigated shipper-carrier partnerships, and the relationship
between carriers’ service factors (timing, pricing, warehousing, and sales service) and
shippers’ satisfaction. Specifically, the author explored the influence of service
attributes on a partnering relationship using a structural equation model with survey
data from shippers in Taiwan using ocean freight transportation services. The five
most important carrier service attributes in this environment were availability of cargo
space, low damage and loss record, accurate documentation, reliability of advertised
sailing schedules, and courtesy of inquiry. This study addresses two of the challenges
listed earlier – capacity is considered as “availability of cargo space,” and growth in
international shipping is represented as the study is based on primarily international
shipments.
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Murphy and Farris (1993) discussed the time-based strategy that was emerging at
the time, and its impact on transportation choice with an aim to determine how
logistics managers will need to adapt to address a time-based focus in business. This
paper is important because it broadened the perspective of this research stream to
include other functional areas of the firm, and to focus on integration of carriers
through enhanced information technologies such as EDI. The article was largely
conceptual, and developed a framework based on a literature review. The authors
found that models used for transportation choice should include timeliness and
reliability, and suggested that the problem be re-structured so that all factors,
including timeliness and reliability, are stated in terms of cost. None of the logistics
challenges identified earlier are directly addressed in this research.
Semeijn (1995a, b) investigated how carrier selection differs in an international
setting. The paper provided a helpful list of how international shipping is
substantively different from domestic shipping, i.e.:
.
choice of modes is more restricted;
.
other parties such as freight forwarders are often involved; and
.
international shipments are more complex with large volume of paper work and
insurance requirements.
The author used a questionnaire to survey shipper and carrier perceptions of
31 international logistics service attributes, and found that shipper perceptions on basic
service variables are consistent with previous carrier selection studies, i.e. reliability,
transit time, and cost, in that order. Interestingly, Semeijn (1995a, b) also found that the
carrier and shipper ratings of the criteria differed significantly. This research was
extended in Pearson and Semeijn (1999) with a survey that investigated differences
between small and large shippers in international markets, which found similarities in the
ranking of the top three criteria (reliability, transit time, and cost), as well as differences
relative to carrier considerations, forwarding services, shipper considerations and
electronic data interchange. Both of these papers have an international theme, and so
addressed the international challenge from the dimensions list.
In Murphy et al. (1997), the authors noted that earlier studies tended to focus on
mean importance scores for attributes, when in fact, other statistics might be
enlightening and should be investigated as well. They conducted a survey of shippers
and truckload carriers of general freight to assess whether within-group rankings of
attribute importance would show a high degree of similarity between shippers and
carriers. They found a high degree of similarly between the shipper and carrier
rankings, but a low degree of similarity when mean scores are tested for statistical
significance. The survey also showed that shippers and carriers have widely different
views on two of the eighteen attributes in the study – rates (ranked eighth by shippers
and 14th by carriers) and negotiated service (ranked 13th by shippers and seventh by
carriers). The authors suggested that relative importance of selection factors varies by
situation, which accounts for some of the discrepancy, and recommended that further
research be undertaken to further investigate these comparisons. This research
addressed the capacity issue – equipment availability was on their list of carrier
selection factors.
A number of authors have addressed quality attributes in the context of
transportation service using one or more of three dimensions of the SERVQUAL
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instrument (Parasuraman et al., 1988). Crosby and LeMay (1998) specifically addressed
carrier selection and formulated SERVQUAL in terms of service quality in the trucking
industry. The authors integrated three methods for identifying customer requirements:
SERVQUAL, direct questioning of the customer by trucking managers, and
policy-capturing via simulation of the customer’s decision process. Policy-capturing
was particularly useful in this context as the first two methods lacked the impact of
resource constraints and respondents tended to select all factors as important. Data
were collected using mail survey questionnaire methods that contained elements of all
three approaches. The attributes of service were in the following categories: assurance,
tangibles, empathy, responsiveness and reliability for SERVQUAL; responsiveness,
convenience, timeliness, equipment, price and image for direct questioning; and
approach, accuracy, support and price for the policy-capturing approach. Although,
this paper largely addressed the best approach for developing an instrument for
measuring customer requirements and the associated measurement of logistics service
quality, the selection of criteria is helpful in developing a picture of traditional
attributes for use in carrier selection. This paper included equipment as a service
attribute, and as a result does address the capacity dimension.
Evers et al. (1996) took a somewhat different perspective on this line of research,
focusing on how perceptions of a mode in general may predispose a logistics manager
to choose or reject a specific carrier for shipping freight, perhaps without an economic
analysis. They used a questionnaire to collect shipper ratings information for three
transportation modes on characteristics that included timeliness, availability,
suitability, firm contact, restitution for loss and damage, and cost. A statistical
analysis of the data indicated that the shipper’s overall perceptions are most affected
by timeliness and availability – suggesting that carriers can reduce misconceptions by
focusing on these two factors. This paper included availability as a service attribute,
and so also addressed the capacity dimension. This research was extended to the
intermodal railroad-truck service realm in Evers and Johnson (2000). In this second
article, perception of communication, quality of customer service, consistent delivery,
transit times, and competitive rates were found to drive shipper perceptions, and their
intention to continue using the carrier. None of the logistics challenges identified earlier
were directly addressed in this second research paper.
In Pedersen and Gray (1998), the authors sought to determine whether general
assumptions about the importance of cost criteria hold true in the country of Norway.
Modern logistics concepts in that country are well known, but the direct costs of
transportation and logistics are very high. Norway, with exports at 45 percent of its
GNP and imports at 37 percent, is more dependent on foreign trade than many other
nations. A report by a committee appointed by the Norwegian government showed
that the cost of transport and other logistics costs for Norwegian exporters accounted
for at least 20 percent of the value of traditional goods exported from the country.
Beyond the type of product and the availability of the mode of transportation, the
topography and climate of the country represent special challenges. The methodology
used by the authors is literature survey. The survey results suggest that transport
price factors are rated as more important than other transport selection criteria by a
high proportion of Norwegian exporters. This observation can be explained by the
high cost of transportation in Norway, which can in part be explained by the country’s
topography. In general, the study supports findings of other carrier choice studies,
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but also identifies features particular to Norway. With the high degree of import and
export traffic in Norway, we consider it to have an international dimension.
While other studies have examined the perceptual differences between carriers and
shippers, Kent and Parker (1999) expanded the literature base by examining the
perceptual differences between international containership carriers, import shippers,
and export shippers. A mail survey asked managers to rate 18 selection factors on a
5-point Likert scale, from which mean response scores were calculated. The top
shipper-identified factors for selecting carriers are: reliability, equipment availability,
service frequency, rate changes, loss and damage, and financial stability – although
the factor rankings do vary somewhat between import and export shippers. The
MANOVA analysis suggested that carriers place lower importance than the shippers
on several criteria, and that they seemed to have less understanding of the needs of
export shippers than those of import shippers. In short, the international influence on
the containerization carrier industry requires change in the transportation strategy
that a company would employ. By its nature, this paper addressed the international
dimension. Since equipment availability is one of the carrier selection factors, it also
addressed the capacity dimension.
Recently, authors have argued that earlier attribute studies were not well focused,
either too broad in description of the attributes, too general in selection of truck
segments, or too local in selection of the carrier sample. In Kent et al. (2001), the authors
set out to add clarity to this line of research by segmenting the national truckload
transportation market. The authors used the results of a survey to analyze mean
responses to a set of 42 motor carrier selection attributes. The results suggest that there
are several selection attributes that are important for all shippers regardless of the
carrier segment – reputation, knowledge/problem solving skills of contact personnel,
quality of drivers, competitive pricing, action and follow-up on service complaints,
billing accuracy, equipment availability and consistent and dependable transit times.
The shippers that used temperature-controlled trucks expressed a need for additional
carrier attributes, including for example, satellite tracing and communications, and
air-ride equipment. This study included attributes for international transportation
(service to Mexico and Canada), and for capacity as reflected in the equipment
availability service-selection attribute.
Murphy et al. (1991) surveyed large US manufacturers and determined that shippers
play an important role in evaluating and selecting international water ports, despite
using international freight forwarders. The authors found that 77.2 percent of the
shippers who responded claimed they play an important role in evaluating different
water ports, and list low frequency of cargo loss and damage, availability of equipment
and convenience of location as the top three factors. The survey also found
that 25 percent of outbound tonnage had an international destination and that
60 percent of that traffic moved by water transportation. By its nature, this study
addressed the international dimension, and also addressed the capacity dimension as
equipment availability is found to be an important attribute.
Other authors have approached the question of service attribute importance using
discrete choice models such as logit and probit to better understand the attributes that
logistics managers prioritize when selecting a transportation carrier (Maier et al., 2002;
Shinghal and Fowkes, 2002; Danielis et al., 2005). Importantly, this style of analysis
estimates both the relative and the absolute importance that shippers assign to
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transportation attributes. Danielis et al. (2005) collected data through face-to-face
interviews with logistics managers in Italy to evaluate shipper preferences for cost,
time, reliability and damage. The experiments consisted of four sets of questions:
(1) unacceptable levels;
(2) importance of attribute levels;
(3) paired-comparison trade-offs; and
(4) calibration.
The analysis provided individual estimates for each shipper as well as aggregate
estimates for segments and for the entire sample. The parameters for an ordered probit
model were estimated, with all variables having the expected sign and showing
statistical significance. The estimates indicated a strong preference for quality
attributes over cost, that is, a high willingness to pay for reliability and safety for the
65 Italian manufacturing firms in the study. The segment level results implied that the
type of good shipped (input or output) influences preferences, and that firm size was
negatively related to the intensity of preference for quality attributes. In Danielis et al.
(2005), attributes were viewed in the context of the international shipping dimension.
Maier et al. (2002) considered the international dimension as well, but also addressed
the capacity dimension from a perspective of private and public investment in
transport infrastructure decisions. Shinghal and Fowkes (2002) addressed the need for
container train services in India, and so also relates to both the international and the
capacity dimension.
Dobie (2005) introduced the concept of core shipper strategy, a bilateral selection
process where shippers and carriers both develop criteria for selection. Transportation
carriers have faced a particularly challenging business environment over the past few
decades, and those who have survived would do well to choose shippers that best fit
their individual competencies. Carriers may ask if the shipper is timely in providing
loads, offers sufficient volume to justify the cost-to-serve, makes efficient use of the
carrier’s freight equipment, packages their goods to minimize loss and damage, and so
on. The paper suggested that future research in:
.
performance measurement;
.
model development to assess the relative importance of criteria;
.
investigation of shipper segmentation strategies;
.
development of cost models; and
.
routing and scheduling algorithms focused on shipper selection.
Dobie mentioned global volume in the shipper selection criteria, and so addressed the
international dimension.
One of the competencies that carriers need to address is that of transport flexibility.
Naim et al. (2006) surveyed the literature and developed a framework for transportation
flexibility that may be useful for carrier strategy development. The authors found
14 key components of transport flexibility, which include: mode, fleet, vehicle, node,
link, temporal, capacity, routing, communication, product, mix, volume, delivery and
access. This paper introduced several new attributes not previously considered in
shipper attribute studies. In this study, capacity is a type of flexibility, defined as the
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ability of a transport system to accommodate variations or changes in traffic demand,
and so the capacity dimension is well-reflected in this paper.
Voss et al. (2006) relied on a different theoretic base and employed the Theory of
Reasoned Action (TRA) to determine the most important carrier selection criteria. The
authors noted a need to reevaluate the topic of importance of carrier attributes, based on
increased emphasis on reducing transport cost, increased need for carrier preparedness
in the event of unforeseen circumstances, and an increased emphasis on supply chain
security. The TRA model is noted as being robust in predicting behavioral intentions
under a variety of circumstances, including selection from alternatives, and so
is expected to be useful in modeling the carrier selection decision process. The authors
developed a carrier selection model and fit the parameters of the model to rank the choice
criteria, and find that delivery reliability and rates are the top two criteria. The authors
expected to see that carrier security would be identified as an important selection
criterion, but found only marginal support for this hypothesis. Other dimensions
addressed in this paper included capacity, formulated as equipment availability.
Transportation choice – decision process
Although the attributes discussed earlier are an important input to carrier selection,
they are only a part of the solution. Certainly, the importance of these factors will vary
from one shipper to the next, and so a decision process for using the factors to develop
a transportation solution is necessary. Research on carrier selection that addresses the
decision process itself is reviewed in this section, some of which propose a
mathematical or qualitative model to support logistics managers in this undertaking.
Some authors have adopted a straightforward cost-based approach to mode choice
and carrier selection. Sheffi et al. (1988) use a simple form of total cost of ownership in
their mode choice model developed for the Burlington Northern Railroad, where the
model was developed for educating customers as well as their own personnel on
the benefits of reduced transit time and improved reliability. This paper addressed the
issue of equipment capacity. Kuo and Soflarsky (2003) adopted a similar approach,
developing a decision support system that searches a database for the lowest cost
carrier to any customer location for a specific high-pressure gas containment
equipment application. This paper did not, however, address any of the logistics
challenges identified earlier in this research.
Coulter et al. (1989) adopted the carrier perspective and developed a process for
designing services for specific market segments. The authors demonstrated the
technique using data from a questionnaire that examined carrier attributes for a
Midwestern geographical market. The data were first analyzed using cluster analysis
of the attribute values to see if natural interest groups existed among the shippers that
might represent a market segment, followed by a discriminant analysis that grouped
the 21 attributes into five factors. Five factors are identified for this regional market:
reliability of performance (which included rate), insurance of service provision,
customer services, personalization, and handling. The paper finds that market
segments were readily identified for the carrier in the case, and that the essential
service criteria for each segment could be readily defined by the five factors. None of
the logistics challenges identified earlier are directly addressed in this research.
McGinnis (1989) examined transportation choice models reported in the literature,
and evaluates the usefulness of four model types:
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(1) classic economic models of transportation choice that identify the distance
breakpoint between truck and rail shipments;
(2) inventory-theoretic models that identify the best mode based on total
transportation, ordering, and inventory-related costs;
(3) trade-off models that identify the best mode based on the sum of transportation
and non-transportation costs; and
(4) constrained optimization models that identify the best mode by minimizing
transportation costs subject to non-transportation cost constraints.
The article also reviewed the empirical literature pertaining to carrier attributes in an
effort to further define appropriate non-transportation costs as parameter values in the
constrained optimization model, concluding that service-related factors are best
handled as constraints. The author included a carrier constraint in the optimization
model and mentions that it could be used to restrict equipment availability, so we find
that this paper does address a form of capacity.
The research purpose in Pisharodi (1991) was to develop and illustrate an inductive
modeling approach for the transport choice process using Knowledge Management
techniques. Pisharodi claimed that many decision models are based on rational
frameworks that may not accurately reflect the logistics manager’s decision making
process, and that it would be better to incorporate organization considerations and
personal preferences and biases. The article explained the script-theoretic approach
that allows for organized knowledge about activities and processes to be codified into
models, and illustrated its use for motor-carrier choice on a new route. The author
concluded that it would be beneficial to shift the focus of transport-choice decision
modeling from the determination of factors which influence decisions concerning mode
choice and carrier selection to the determination of the activities involved in the
decision making. The paper did not address any of the key logistics challenges.
As noted earlier, carrier selection attributes are often diverse, and may be
quantifiable or intangible. Liberatore and Miller (1995) listed several qualitative
evaluation criteria, including perceived quality, EDI capabilities, potential to develop
long-term partnership, etc. An important research question is, then, how can these
qualitative criteria best be incorporated into the decision process? In Bagchi (1989) as
well as Liberatore and Miller (1995), the authors advocated the use of Analytic
Hierarchy Process as an appropriate mathematical model for transportation choice,
and each presented a platform for using the AHP model in this way. Liberatore and
Miller (1995) considered mode choice and carrier selection jointly, and provided an
illustrative example of how this method could be applied in this context. Bagchi (1989)
included equipment availability as a capacity dimension in his version of the AHP
model, while Liberatore and Miller (1995) included cargo capacity limitations as a
capacity dimension in their model.
Min (1998) contributed to the research on the carrier selection decision process by
developing a decision support system for selecting private or common carriage at the
Master Lock Company. The decision process is complicated by the multi-attribute
and multi-objective nature of the problem, as well as the dynamic nature of
the factors involved in the process. As fuel price, driver wage, market competition and
government regulation change over time, the decision should be made with anticipation
of these adjustments and then revisited as necessary to address unanticipated changes
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in the environment. A set of databases were identified and models were developed for
forecasting sales, determining expected inbound and outbound shipments through
MRP, and carrier selection using AHP. Using these three steps, the traffic manager is
able to select the best mode (private or common) of shipment for each route, and if
common carrier, then a specific carrier is chosen. The capacity dimension was
addressed in this model as driver availability and was included as a criterion in the
AHP model.
In Garrido and Leva (2004), the authors addressed the joint selection of carrier and
destination port for the case of Chilean fruit exporters using a space-time structure
defined within a multi-objective program. The choice of the destination port implies
spatial interactions because of issues of accessibility, land use and infrastructure
availability. The carrier choice has temporal effects due to the large distances traveled.
A stochastic multi-nominal probit model is used that considers serial correlation,
spatial autocorrelation and state dependence. The research found that there is
significant state dependence, serial and spatial correlation in the choice of carrier and
destination choice. This paper analyzed an international case for which the time factor
is almost independent of the destination (small percent variations in the distances) and
incumbent only on the carrier, while the space factor (a shared component of capacity)
is only dependent on the destination. This research addressed the challenges of
international transportation and capacity.
Caputo et al. (2005) also developed a decision support system to aid in mode and
carrier selection, for long range direct shipping (LRDS) in the EU. LRDS is a type of
truck transportation where goods are shipped from the manufacturer to the final
customer without intermediate warehouses, which results in a decision problem that is
increasingly complex since customer assignment and order aggregation are an
important part of the problem. Logistics managers refer to these as “milk runs” (Ferrin,
1994; Du et al., 2007), where small shipments may be consolidated at the origin with
other small shipments that have destinations in the same region. This results in a truck
route that has a line-haul segment and a tour segment where the individual shipments
are delivered to the customer locations.
The design of these “milk runs” (multiple-zone FTL’s in the paper) are often a difficult
problem. Caputo et al. (2005) developed a decision support system that will compute
(but not optimize) the cost of shipping by pre-established alternatives, taking into
account the customer assignment and order aggregation decisions. Only cost is
considered in the carrier selection module, as the authors argue that it is often the most
important factor. Transit time and reliability are treated as a constraint in this model, by
assigning a service level to each customer based on their relevance to the shipper. The
model is developed for EU application and so takes international shipping
considerations into account. The authors also note that a carrier with a significant
number of customers in the destination zone may have a cost advantage due to a good
chance of a return load – a benefit that may be achieved with collaboration between
shippers. Note that this efficiency is realized without shipper collaboration by a trucking
firm that has sufficient economies of scope to support a high frequency of return loads.
A discrete choice model was employed in deJong and Ben-Akiva (2007) to describe
the decision process for transportation choice, and applied to freight traffic in Norway
and Sweden. The authors developed a multi-nomial logit model that focused on the
choice of:
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.
shipment size;
.
number of segments in the transport chain;
.
use of consolidation and distribution centers for road, rail, water, and air
transport; and
.
mode choice for each segment.
These decisions were incorporated into the model as a minimization of the full logistics
cost function which included order, transport, and inventory related costs. The authors
found a plausible general structure for the use of a discrete choice model for freight
transport for use as both a causal and a policy-sensitive model. Here, too, the authors
allowed for efficiencies due to a high frequency of return loads that results from
economies of scope. Additionally, international flows were included in the model so the
international dimension is represented.
Transportation choice – supply chain integration
Cooper et al. (1997) defined supply chain management as “the integration of key business
processes from end-user through original suppliers that provides products, services, and
information that add value for customers and other stakeholders.” These processes
include customer relationship management, customer service management, demand
management, order fulfillment, manufacturing flow management, procurement, product
development and commercialization, and the returns channel. This set of business
processes is quite broad and, of course, includes transportation choice at several points.
In particular, mode choice and carrier selection appear in product development, order
fulfillment, manufacturing flow management, and the returns channel. In this section,
we review articles that integrate the transportation choice decision with other decisions
in the supply chain, or where companies collaborate to achieve economies of scale or
scope that could not be achieved individually.
An optimization model for carrier selection is presented in Moore et al. (1991). The
case study reports on Reynolds Metal Company, who centralized its interstate
truckload freight operation and developed MIP to select and deploy carriers. This
model has a single objective to minimize freight cost, but provides flexibility to ask
what-if questions in a simulation format. The model also identifies lanes that can be
served in sequence and carriers to serve both lanes, thereby providing the carriers with
the advantage of a loaded backhaul. As a result, the company improved on-time
delivery and reduced annual freight costs. Both capacity and economies of scope
dimensions appear in this paper.
Carter and Ferrin (1995) claimed that collaboration between a buyer and a supplier
cannot succeed without involvement of the transportation carrier, and proposed that
three-way collaboration is required for the success of such ventures. Particular
attention was given to transportation cost and transit time, both of which are key
parameters in mode choice, and a main consideration for the integrated purchase
quantity and lot sizing decision. In their paper, the authors developed a model that
allows the optimal quantity to be computed, and illustrated the necessity of three-way
collaboration with an example that features the break-even point problem in
transportation rate structures. Accordingly, a number of authors have considered the
integration of supplier selection, lot size, mode choice and carrier selection. Larson
(1988) also developed a model that determines the optimal transportation mode and
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shipping quantity considering inventory, order, and loading costs, and illustrated the
trade-off between air and LTL shipment. In Walters (1988), the author gave an example
of jointly selecting a supplier, the transportation mode, and carrier, for inbound
materials in the glass manufacturing industry. None of the challenge dimensions are
mentioned in these papers.
Miller and deMatta (2003) developed a multi-plant production and transportation
model that includes the mode-choice decision. The model minimizes total cost
including variable production costs, line setup costs, line changeover costs, WIP
inventory carrying costs and FGI inventory carrying costs in both plants as well as
freight costs for each available mode and in-transit WIP inventory carrying costs. The
formulation considered capacities for plant production, but not for carrier transport.
Carrier selection and mode choice are addressed as procurement of transportation
services in Caplice and Sheffi (2003), who developed an approach for procuring
truckload motor carrier transportation services based on economies of scope in
transportation. The paper describes a combinatorial auction run by the shipper to
determine the minimum cost allocation of its lanes to carriers. The process is
structured so that carriers bid on bundles of lanes, i.e. a conditional package bid that
reflect the firm’s cost based on volume and lane assignment. This paper addressed
both economies of scope and capacity dimensions.
The model by Liao and Rittscher (2007) integrated three groups of decision
variables: dynamic procurement lot sizing, supplier selection decision and carrier
selection. Their multi-objective formulation minimized cost, number of rejected items
and late deliveries subject to demand satisfaction and capacity constraints. A genetic
algorithm was used to solve the problem and weight the objectives to obtain different
Pareto optimal solutions. This paper addressed the capacity issue as a constraint in the
model.
Many of the supply chain initiatives discussed in this section were addressed in Esper
and Williams (2003), which developed a conceptual framework and quantifiable measures
for Collaborative Transportation Management (CTM). The goal of CTM is to improve the
cost, service, and efficiencies associated with transportation and delivery through
collaborative relationships among buyers, sellers, carriers, and in some cases, third-party
logistics provides (3PL’s). The methodology in this paper was a case study of a logistics
service provider, TRANSPLACE, and was primarily based on interviews with the firm’s
employees and customers. A key concept in CTM is the need for processes that convert
order forecasts into shipment forecasts, along with their accurate fulfillment. In practice,
the processes that CTM coordinates can be extensive – in Esper and Williams (2003), the
firms improved logistics performance through enhanced electronic carrier-shipper
communication, by consolidating shipments across vendors, by optimizing mode
selection, and by matching inbound and outbound freight shipments to reduce empty
backhauls. Performance indicators were identified through these case studies, which
include: transportation cost, on-time performance, asset utilization, and administrative
cost. This paper addressed both capacity and economies of scope.
Discussion and significant findings
We found six major themes in this literature on mode choice and carrier selection.
First, attributes are an important thrust in transportation choice research. Much of
the earliest literature focused on the factors that are most important to decision makers,
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and the interest continues, as attributes and their importance in transportation choice
change over time. A lag in understanding these changes has made it difficult for
carriers to compete, as is the case when carriers have a different view of which
attributes the shippers consider most important. In fact, carrier perception of the
shipper’s ranking of attributes can be measured through attribute studies. Several of
the articles reviewed here have taken a carrier marketing perspective and glean
knowledge about shipper priorities for use in the design of transportation services
(Coulter et al., 1989; McGinnis, 1990; Abshire and Premeaux (1991); Evers et al., 1996;
Murphy et al., 1997).
Next, the choice of transportation mode and carrier is a multi-attribute problem.
This has been confirmed by all shipper surveys and in one conceptual model (Murphy
and Farris, 1993). This finding motivates multi-factor evaluation methods for
transportation choice, as in Bagchi (1989); Liberatore and Miller (1995) and Min (1998).
One approach for incorporating multiple attributes, some of which conflict with each
other, is through the use of multi-objective mathematical programming formulations
that optimize mode choice and/or carrier selection, as in Liao and Rittscher (2007).
The development of decision models that incorporate current challenges in logistics
has been complicated by the difficulty in quantifying attributes such as environmental
effects and security.
Then, we found that regulatory and market changes have been drivers for change in
transportation choice attributes. During the years covered in this study, the attribute
set that is relevant to transportation choice has changed due to deregulation of the
transportation industry, implementation of the just-in-time philosophy at US
manufacturing companies, an improved understanding of quality in the
transportation industry, and increases in international trade. For example, there are
few articles on international shipping in the earlier time frame of our study (Murphy
et al., 1991), and more in recent years (Kent and Parker, 1999, Pearson and Semeijn,
1999, Evers and Johnson, 2000).
The topic of capacity is well addressed in this literature, largely because equipment
availability is typically a criterion for carrier selection. Although none of the articles
specifically address the transportation capacity shortage described earlier, we found
that 28 of 48 articles do consider capacity concerns as an attribute.
Survey methodology and mathematical models have been widely used in this
research. A large share (82 percent) of the articles employed one of these two
methodologies. The survey methodology was important to the empirical work in the
attribute identification studies. Several of the mathematical models in this research are
normative models that find a good solution to the transport choice decision problem
(Larson, 1988; Sheffi et al., 1988; Bagchi, 1989; McGinnis, 1989; Moore et al., 1991;
Liberatore and Miller, 1995; Min, 1998; Kuo and Soflarsky, 2003; Garrido and Leva,
2004; Caputo et al., 2005). The remaining mathematical models are descriptive in
nature.
Supply chain integration among carriers and/or shippers provides new
opportunities in mode choice and carrier selection. Performance can be improved
through integration involving transport choice in the supply chain initiatives. The
most common type of integration in this literature is within a firm, as in Moore et al.
(1991) where multiple divisions collaborated internally to achieve economies of scope
and scale or in Walters (1988) and Liao and Rittscher (2007) where multiple functions
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integrated decision processes. In Esper and Williams (2003)), multiple shippers and
multiple carriers collaborated through a third-party logistics provider to achieve
economies of scope and scale. In Caplice and Sheffi (2003), the collaboration is
shipper-managed and also technology-assisted on the internet. Carter and Ferrin (1995)
describes collaboration between a shipper, supplier and carrier. Many options are
available for improving performance with integration that includes transport choice.
Identified gaps and directions for future research
On the other hand, a number of themes are not well represented or are missing in this
literature.
International growth and international issues are lightly represented in this research
Only 13 out of 48 articles include an international dimension, and of these, relatively
few relate to growth. What models best describe mode and carrier choice for
international freight transport? What models may be used in a normative fashion for
mode and carrier choice for international freight transport? We found one article
(Garrido and Leva, 2004) that integrates port-related decisions with domestic
transportation choice decisions. What are the challenges to integrating these decision
processes? What models best address these situations? What metrics should be used to
evaluate the performance of an integrated supply chain? What are the gains, and how
should they be distributed? What are the barriers to implementation?
The topic of economies of scope and scale in transportation choice is under-represented
in this research
Only five of the 48 articles address network effects in transport choice, and of these,
only three explicitly consider economies of scope in the research (Moore et al., 1991;
Caplice and Sheffi, 2003; Esper and Williams, 2003). This literature largely addresses
economies relating to empty backhauls, an economy of scope. What other operational
activities relating to transport choice might lead to performance improvements
through economies of scope? What other operational activities might lead to
improvements through economies of scale? How large is the opportunity associated
with these, and what processes could be used to assess them?
Little attention in the transportation choice research has been given to security issues
Only one of the 48 articles reviewed here addresses security concerns – Voss et al.
(2006) pointed to preparedness and security as new criteria for carrier selection. More
work is needed, perhaps in the area of multi-objective optimization that includes carrier
choice as a decision variable, with objective functions that include the new dimensions.
An interesting question pertains to how these criteria might be quantified? How can
appropriate weights for the objectives be established? Can survey results be used to
weight the objectives and generate the Pareto optimal sets? What procedures are best
for formulating and fitting the parameters of a model of this type?
Environmental and energy use concerns are a missing theme in this body of research
None of the 48 articles address environmental and energy concerns. We discussed
consumer interest in the carbon footprint in this paper, but there are other
sustainability issues as well. A comprehensive list of which issues are most likely to
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relate to transportation choice is a good place to begin exploring this topic. Then, how
should these environmental criteria be included in the transport choice decision? What
impact would it have on the environment? Which shippers or industries would have
the largest impact?
Few supply chain integration concepts include transportation choice
Transportation choice seems to be a good candidate for applying integration concepts,
yet we found only three decision model papers that do so. Transportation choice is
integrated with the lot size decision in Larson (1988) and Carter and Ferrin (1995)), with
the lot sizing and supplier selection in Liao and Rittscher (2007) and with production
schedules in Miller and deMatta (2003). Often mode choice and carrier selection are
modeled as parameters and not as decision variables – this is an area of future
research. What other types of integration with transportation choice are possible?
Product design? Demand planning? Replenishment planning? Other forms of
production and material planning? Other decisions in the transportation planning
realm? Can carrier choice be integrated with shipper selection, as proposed in Dobie
(2005)? Could mode choice and carrier selection be addressed as decision variables and
integrated with other decisions like supplier choice and lot size? Are multi-objective
programming formulations a viable approach? Can a capacity constraint in these
formulations be separated into an individual component specific to the carrier and a
shared component depending on the mode’s capacity limitations, independent of the
carrier? How can a carrier exercise its ability to overcome share limitations and in that
way differentiate itself from the competition? Could a smart use of technology help in
this process?
Simulation, case study, and interview methodologies are under-represented in this
research
A small share, 18 percent, of the articles employed the simulation, interview, case
study, conceptual and multiple methodologies. What are the challenges to using these
methodologies in the transportation choice environment?
Normative modeling research is under-represented in this body of literature
Lambert et al. (1998) argue that “a top priority should be research to develop a
normative model that can guide managers in the effort to develop and manage their
supply chains.” Here we see relatively few normative decision models to aid in either
stand-alone transportation choice decision-making, or integrative decision processes of
the type addressed by Lambert and his colleagues. We find that ten of the models in
this literature are normative models for the transport choice decision process (Larson,
1988; Sheffi et al., 1988; Bagchi, 1989; McGinnis, 1989; Moore et al., 1991; Liberatore and
Miller, 1995; Min, 1998; Kuo and Soflarsky, 2003; Garrido and Leva, 2004; Caputo et al.,
2005). But the development of a model is not the final step in research directed at
guiding managers. Case study research and applications provide additional
perspective. Of the papers we reviewed, only a few are case studies (Min, 1998; Kuo
and Soflarsky, 2003) and a few are application papers (Moore et al., 1991; Caputo et al.,
2005). How well do the models described perform in practice? What are the difficulties
in implementing these models? What features of the real-world are not well captured?
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Emerging information technologies in transportation choice are under-represented
We found relatively few information technology papers relating to transportation
choice. Only the script-theoretic decision process as described in Pisharodi (1991)
appears in the transportation choice literature. What other techniques and emerging
information technologies might be deployed in the transportation choice decision
process?
The role of the internet in transportation choice is a missing theme
Even though the articles in this review address initiatives that depend on the internet
for efficient communications, little research has been undertaken that addresses how
the internet influences transportation choice. Kale et al. (2007) show that private
communities of shippers and carriers can collaborate to a shared advantage. Cruijssen
et al. (2007) discuss horizontal cooperation and emphasize that cooperation can exist
between other competitors (i.e. shippers, carriers). How can these types of collaboration
be used to influence the transportation choice decision process? Also, there are few
papers on the impact of the internet relating to carrier selection. Gibson et al. (1993)
noted that transportation management at that time was shifting from selection of
different carriers for individual route or services to negotiation with a few individual
carriers. How has this changed since the transportation exchanges as described in Kale
et al. (2007)? Is transportation choice more transaction-based? If so, under what
circumstances?
Conclusions
In this paper, we categorized transportation choice research on the topic of mode choice
and carrier selection, and examine it using dimensions related to research methods,
approaches, and the challenges that have emerged in recent years in logistics
management. Our contributions are three-fold: the development of a classification
scheme, a structured review that provides a guide to earlier research on the subject of
transportation choice, and the identification of research issues for future investigation.
Overall, we find a number of interesting themes in this literature. Certainly, the
research has been dominated by the investigation of attributes used by shippers when
making transportation choices, and has been given a fair amount of attention using
survey methodology and mathematical models. But this is a dynamic problem, as the
set has transformed with regulatory changes and broad initiatives directed at
improving firm performance. The multi-attribute nature of this problem has been well
established and establishes a structure for research models used in this domain.
We also find that the topic of capacity is well addressed in this literature typically
associated with carrier selection, but it is not addressed in relation to the transportation
capacity shortage. Supply chain integration among carriers and/or shippers provides
new opportunities in mode choice and carrier selection. Different types of integration
were presented and discussed, the most important, inter-firm integration, across firm
collaboration and third-party logistics. The most common type of integration in this
literature is within a firm. Many options are available for improving performance with
integration that includes transport choice.
The review also reveals that several important themes are under-represented in the
literature in light of current challenges in logistics management. In general, the subject
of network effects in transportation choice was under-represented in this research and
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more specifically economies of scope and scale in relation to transportation choice.
Similarly, little research has addressed supply chain integration topics that include
transportation choice. International growth and international issues are lightly
represented in this research. Then, too, solutions to the challenges of environmental
and energy use concerns and security in the supply chain are largely absent in the
transportation choice literature. We also found that the role of the internet and
emerging information technologies in transportation choice are not well covered.
Likewise, the under-representation of research methodologies such as simulation,
case study, and interview methodologies suggest opportunities in future research.
Also, higher priority should be given to research that develops normative models to
better manage the supply chain, as relatively few prescriptive decision models were
found for either stand-alone transportation choice or as integrated decision processes.
This review reveals a need for future research on the topic of transportation choice.
Numerous research questions surround the current issues in logistics management,
many of which are pertinent in the purview of transportation choice. The insights
identified in this paper suggest that future efforts on this topic be forward-looking in
methodology, but also practical from an industry perspective.
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About the authors
Mary J. Meixell is an Associate Professor of Management at Quinnipiac University in Hamden,
CT. She earned a BS in Civil Engineering from Penn State University, an MS in Transportation
from Massachusetts Institute of Technology, and a PhD in Industrial Engineering from Lehigh
University. Her areas of expertise are in production and logistics operations analysis and supply
chain management. She has extensive industry background in transportation management,
production planning, supplier management and supply chain design from 15 years of
employment at General Motors and Lucent Technologies. She has authored publications on the
bullwhip effect in automotive supply chains, on modeling demand scenarios in technology
markets using leading indicators, and on integrating knowledge management techniques with
decision support systems. Mary J. Meixell is the corresponding author and can be contacted at:
mjmeixell@quinnipiac.edu
Mario Norbis is a Professor of Management at Quinnipiac University in Hamden, CT.
He earned a BS in Chemical Engineering from the University of Uruguay, and an MS and PhD in
Industrial Engineering and Operations Research from the University of Massachusetts. His areas
of expertise include mathematical modeling, production and operations analysis and supply
chain management. He has authored publications in multidisciplinary areas including
optimization models, production, optimization, business education and education administration.
He has industry background in production and manufacturing systems having worked for Shell
Oil Company and manufacturing companies.
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