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The use of common carriers to control internal capacity: a survey of the industry.


The use of common carriers to supplement private and dedicated resources has increasingly become a strategy that many transportation providers are utilizing to control internal capacity. This problem has been addressed in the literature, but primarily from a cost perspective. We utilize a survey of industry participants to gather data on the maturity of this process in practice, as well as the drivers that are most influencing the decision of what routes to assign to private/dedicated resources versus common carriers. The results show a primarily manual process, as decision models do not currently incorporate the customer service and asset utilization factors that practitioners say are driving this decision. We then discuss how this is an opportunity to develop analytic solutions that allow transportation providers the ability to improve implementation of this veiy important decision.


Transportation strategy, dedicated fleet, private fleet, capacity control, third-party logistics


Prior to the economic downturn in 2008, research described how transportation providers were faced with a changing environment that included constantly increasing service level requirements, customer demand for lower-cost transportation services, increasing driver shortages, new regulations on driver horns of service, and a focus on better asset utilization (Dobie 2005). Other dialogue in the same timeframe discussed not only these challenges, but also the mounting pressures of rising fuel costs, industry capacity issues, and rising insurance costs that shippers face when designing their transportation network and selecting ground transportation options (Morrison 2004). Such changes appear to have only been accelerated by the most-recent economic recession in the United States, and shippers are now faced with developing even more tailored solutions that meet customer service and cost requirements despite a transportation industry in which shipments are outpacing trailer capacity (Solomon 2014; Finley and Blaeser 2014).

Traditionally, many firms have relied on private fleets, dedicated fleets from outside operators, or a mixture of the two for their transportation needs. Shrinking capacity has made relying on just these resources impractical in most instances, and thus firms are looking to other avenues such as common (for-hire) carriers to supplement their private and/or dedicated fleets. This has led to a realization by some organizations that certain aspects of the traditional pre-recession strategy for ensuring trailer capacity were not flexible enough, and that new approaches were needed to add more flexibility and agility into the supply chain while also ensuring sufficient capacity. This new post-recession business model "more closely resembles a dynamic, collaborative shipping network that includes aspects of dedicated and for-hire operations, and sometimes private trucking fleets" (Cassidy 2013,2). Simply said, firms cannot always internally provide for enough vehicle capacity to meet their full shipping needs and thus must supplement their own dedicated and/or private fleets with capacity from external common carriers.

As firms move more to this hybrid approach for providing transportation solutions, they now face the problem of deciding which shipments to assign to their available dedicated (or private) fleet vehicles, and which to assign to the flexible and changing capacity volumes provided by common carriers. A problem for transportation providers is that most software assigns shipments to private or dedicated fleet on an individual basis, and thus integrating common carriers into the decision process is many times a manual process because the algorithms in the software do not account for many factors outside of cost. This assignment must also account for factors listed above such as desired customer service level and driver constraints that have to be balanced against cost. Further, the assignment may also have to be reevaluated at more frequent time intervals than that of traditional prerecession models. The industry-focused research presented in this article examines the decision-making process for selecting and utilizing a mixture of dedicated, private, and common carrier vehicles in order to investigate gaps in the current process for assigning shipments to different types of resources. The study uses a survey of transportation, logistics, and supply chain managers to investigate the following:

* The prevalence of common carrier usage by dedicated and private operators;

* The maturity of the processes used to manage the decision of when to use additional common carrier capacity; and

* The factors that are driving this decision in practice.

What Is Driving This Change?

The decision of whether to operate a private fleet or use dedicated carriers has been discussed in the literature (Farris and Pohlen 2008; Lynch 2007; Maltz 1993). These studies clearly indicate that this is not a purely cost-related decision, and that firms must evaluate strategic, tactical, and operational factors from both a direct and indirect perspective when determining the right solution for their organization. Both private and dedicated fleets can provide benefits such as increased customer service in addition to cost savings if implemented correctly. However, a key step discussed by Farris and Pohlen (2008) is the need for a total cost of ownership perspective that incorporates multiple decision factors when developing a strategy.

As figure 1 shows, private and dedicated fleet usage has significantly increased in the most recent US Census Bureau Commodity Flow Survey. In 2012 this usage accounted for 46.4 percent of total tons shipped by truck (up from around 40% prerecession) (US Census Bureau 2014). This type of transportation design can generate cost savings for shippers, but more often it is the increase in customer service that has been reported as the most important factor for why organizations choose a private fleet (Banker 2009). Additionally, a dedicated fleet provided by an outside transportation provider can offer many of the same advantages as a private fleet. For example, these devoted resources can offer the same capacity assurances and reduced shipping costs, and have been shown to improve on-time delivery performance by approximately 5 to 10 percent (Lynch 2007; Panchalavarapu 2010). Therefore, the central issue of this examination is not whether the use of a private or dedicated fleet is a better strategy, but how to make decisions about the right mix and use of dedicated fleet, private fleet, and common carrier assets, and how to properly control these resources.

The issue of effectively controlling truck and trailer capacity has also become more significant as firms work to ensure that they meet asset utilization goals. The president of the National Private Truck Council discussed this changing climate in a 2006 interview when he said, "Companies realize having control of their own capacity to get their product to market is becoming essential, [and] capacity control is increasingly seen as a core competency that a company cannot afford to be without" (Edwards 2006, 3). Realizations such as this are key in moving forward in the transportation industry, as they not only mitigate risk in the supply chain, but also offer the ability for firms to create a non-price differentiated advantage that may provide a competitive protection against commoditization pressure common to the industry (Randall, Defee, and Brady 2010). For example, firms can more cost-effectively use a common carrier for a route with a low backhaul potential, rather than selecting an internal private or dedicated truck for the route that would otherwise lower overall and increase cost.

Another important reason that must be mentioned as an impetus for a hybrid model for a firm's motor carrier transportation strategy is the growing driver shortage. This is an issue not only in the United States (Cronin 2014), but also internationally in markets such as Canada (Dummett 2013), Europe (Rauwalld and Schmidt 2012), and Asia (Chomchuen 2013). In fact the estimated 30,000 driver shortage in the United States is expected to grow to as many as 200,000 over the next decade (Irwin 2014). Thus, firms must clearly recognize the importance of properly utilizing internal (private and/or dedicated) fleets and drivers and may find it a necessity to supplement these valuable internal resources with external common carriers in many instances.

Another driver-related issue that can make supplementing certain shipments with common carriers more advantageous is time at home, which has been shown to affect driver retention (Williams, Garver, and Taylor 2011). Firms can utilize dedicated and/or private fleets and drivers primarily on routes that return to the same depot each day, and supplement for longer and more erratic routes with common carrier capacity. In addition, driver management processes that focus on integrating a firm's private fleet drivers into the company culture, instead of leaving them to feel as if they are outside contractors, has also been found to be a factor in improving customer service and creating cost advantages that dedicated and private fleet are designed to provide (Kemp, Kopp, and Kemp 2013; Saldanha, Hunt, and Mello 2013). Assigning shipments so that these internal drivers are able to return home each night is one strategy that can accomplish the cultural objective mentioned above, and is thus another influence that should be considered during the decision of what shipments to assign to different types of resources.

Existing Research on Hybrid Fleet Strategies

The above factors help explain why firms are building hybrid fleet strategies that use a mix of their own private and/or dedicated vehicles with common carrier vehicles to meet their unique transportation needs. This option is not unknown to the literature, and there is some existing research in this area. (2) Table 1 gives a brief overview of the relevant literature and, more important, highlights factors used in these hybrid strategies so that they can be compared to factors that our study reveals practitioners are basing their shipment assignment decisions on. All of these strategies are based on common vehicle routing scenarios, as they most often require that private resources start and end their routes at their assigned depot and only consider delivery of the primary shipment in the mix decision.

Table 1 illustrates the reliance on direct cost factors in existing models even though, as discussed above, one of the key reasons that firms use private/dedicated fleets is a customer service advantage. This could represent a gap in the current research, and the feedback from this study will be useful in determining if these factors are what managers (practitioners) value. In addition, it provides insight regarding what value they currently aim to achieve from a hybrid fleet approach.

Current Industry Approach

An industry database maintained by the Global Supply Chain Institute at the University of Tennessee was used to identify managers with transportation roles in their organizations. This list of potential study participants was supplemented by a Worldwide Web search to identify professionals who might meet the survey participant criteria, which was someone with knowledge of how his or her firm assigns shipments to different types of fleets whether internal or external. In total, 3,200 professionals were identified and contacted to participate in the survey. As the database was not purely a transportation specific list due to the fact that responsibility for this activity can be within the control of several managerial titles, not all contacts had the knowledge to take the survey. One hundred and fifty managers clicked the survey link; this resulted in 101 usable responses. Tables 2 and 3 provide a demographic overview of the participants, and show the diversity of both firm type and size of company based on annual sales revenues.

An analysis of the data indicates a prevalence of firms using a mixture of private/dedicated fleets along with common carriers to provide the overall capacity they require. As figure 2 below shows, 74 percent of the survey respondents indicated that their firm used a combination of private/dedicated assets and common carriers for their outbound shipments. Of these responses, 45 percent of the firms managed internal capacity through the use of a private fleet, while the rest outsourced control to a third party through utilization of a dedicated fleet.

The data also show that only 73 percent of firms have a "defined, specific process" for choosing how to assign a shipment between the available dedicated/private and common carrier vehicles. The manner in which the hybrid strategy is created and implemented represents a distinct opportunity in this area. While this fact in isolation is significant, it becomes even more important when the degree of automation in the process is considered. Only 28 percent of respondents indicated that they have a fully automated information process for assigning shipments to dedicated/internal resources versus common carriers. Some 52 percent indicated this was still a manual process at their firm (with the remaining 20% using a mixture of manual and automated). This represents a meaningful area of opportunity for firms moving forward. Further, the data underlines the current immaturity of the decision-making process at many firms, and represents a potential to improve the efficiency and implementation of such hybrid strategies. The impact of addressing this gap is only heightened in a trucking industry strained by increasing costs and customer service requirements in an environment with capacity constraints.

The following sections of the article discuss how transportation managers view the current process of assigning shipments to different types of resources, and gaps in that process that need to be addressed to provide solutions that incorporate all of the relevant factors into the decision.

Satisfaction with Current Process of Shipment Assignment

Participants in the survey were asked to report their level of satisfaction with their firm's current process for assigning shipments to dedicated/ private resources or common carriers across a range of factors including: cost, service, asset utilization, and overall value from the process. An overview of the results is shown in table 4.

The results indicate that respondents are on the positive side of the scale with no statistical difference between the factors. That is, in general they are somewhat satisfied with their current process. However, the upper 95 percent confidence interval is not above level 6 (satisfied) for any of the four factors. In fact, the lower 95 percent confidence interval is either close to or below level 5 (somewhat satisfied) for all the factors. These results indicate that while firms do see some value in their current process for selecting and assigning shipments to dedicated/private or common carrier capacity, there is still a great deal of room for improvement from a cost, service, asset utilization, and overall value perspective.

The study also examined the importance of different decision factors in shipment assignment. The results give some insight into where improved techniques, when compared to existing strategies for making this decision, would lead to increased value.

What Factors Matter in Practice?

In order to determine how different types of decision factors impact shipment assignment, respondents were asked to rate the importance of five factors on assigning a shipment to a dedicated/private resource versus a common carrier. The factors evaluated include cost, dedicated asset utilization, route length, backhaul potential of the route, and time sensitivity of the shipment. Table 5 presents the results from this question.

The analysis shows several statistically significant differences between the five factors. Perhaps the most noteworthy result is that time sensitivity is clearly just as important as cost when making the decision on how to assign shipments between dedicated/private and common carrier assets. Additionally, cost and time sensitivity are also significantly more important than the other factors in the decision process. This conclusion is based on the fact that neither factor's 95 percent confidence interval overlaps with that of the other three factors. It also appears that the respondents deem the backhaul potential of a route as less important than the other factors, although the relatively high importance of dedicated asset utilization in the results illustrates that backhauls as an asset utilization strategy are still an important issue.

Additionally, none of the factors were on the unimportant side of the scale, which indicates that there is some importance placed on each of these factors in practice. These results support ancillary evidence that some organizations use the ability to control route length as a strategy to increase driver retention. While not as high as cost and customer service, the results also show that asset utilization and route length still need to be considered in decision models as resources become scarcer as the driver shortage continues to grow.

However, most important, taken together the results in tables 1 and 5 reveal an important gap between what factors managers/practitioners believe are the most important in making the carrier assignment decision and what current analytic models created by academics include in their criteria. For example, the time sensitivity of the shipment is the highest rated factor in the industry sample, and yet none of the analytic models discussed earlier in table 1 include this factor as a variable. The Bausch, Brown, and Ronen (1994) model included a latest shipment date, but this still does not include any other customer service factors that might make a particular shipment more time sensitive. Further, none of the models included the other factors such as asset utilization, except for Bausch, Brown, and Ronen (1994), who penalized potential solutions that left dedicated/private fleet assets idle.

These gaps could also potentially explain why a majority of the study respondents reported that their current process was either manual or a hybrid of automated and manual, as the current analytic and information systems tools may not allow organizations to assign shipments based on the factors they value. The discrepancy is important, as the results show that guidance for how to assign shipments to dedicated/private fleet versus common carriers is growing in importance. New insight and guidance from academic research may be needed to make this common decision in today's transportation climate through the development of solutions that incorporate all of the relevant factors that managers/practitioners are incorporating into the assignment process.

Discussion and Conclusions

There has been a significant increase in the use of private and dedicated fleets in today's trucking industry following the economic recession. However, this is only one of several changes that have occurred. Mounting constraints and pressures on the industry brought about by increased regulations, driver shortages, and increased customer expectations on service and quality are making the decision of how to select the appropriate transportation option for a firm's shipments even more important. In fact, firms are commonly using a mix of internal assets (private/dedicated fleets) and external assets (common carriers) to meet their shipping needs.

The results of our study indicate that the process for making the decision on which shipments to assign to different fleet types may not currently be mature in many firms. In a large majority of the firms that participated in this study, the process is currently being accomplished manually without the aid of information systems or analytic methods. Additionally, the analytic models available in the academic literature do not appear to capture or include some of the most important factors identified by practitioners in our study. In fact, "time sensitivity" does not appear to be a variable in any of the models published in the literature to date, despite being the highest ranked variable by practitioners.

The implications are clear; there is ample room for improving the decision-making process on how to allocate shipments and utilize available trucking assets using a combination of internal and external fleets. Transportation managers would benefit from a better understanding of how to more optimally use a mixture of internal and external fleets, and determine how the decision is currently being made in their firms. Where possible, the use of analytical models that include more customer service- oriented variables needs to be implemented.

The development of these models is not a simple undertaking. The current literature does not include models that integrate all of the factors that managers/practitioners are actually basing the decision of which shipments to assign to dedicated/private fleet versus common carriers. Available software that does allow assignment to multiple types of resources usually does this by using heuristics that assign priority by resource type. The current environment of constrained capacity is driving a need for solutions that incorporate all types of resources, whether dedicated/private or common carrier, and make assignments at the disaggregate level without relying solely on direct costs. From a modeling perspective the methods are present, but the variables and constraints that those models use need to be updated to reflect the current transportation industry environment. These factors are already being used to make this decision, albeit in a predominantly manual manner. Thus an effort is needed to take this native knowledge and convert it into analytical solutions that integrate those factors. The current environment has made the development of these solutions something that can no longer be overlooked in practice or theory, as being a good steward of a firm's transportation resources can be a source of competitive advantage.

Overall, the findings of this study suggest a gap in current research, and as such present an opportunity for academic researchers to build analytic models and approaches related to this decision that are academically rigorous and, most important, include the relevant variables of value to managers/practitioners.


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Lance W. Saunders

Corresponding Author

University of Tennessee

John E. Bell

University of Tennessee

Rapinder (Rupy) Sawhney

University of Tennessee
Table 1/Overview of Research on Assigning Shipments to Dedicated/
Internal Fleets or Common Carriers

Paper                  Overview                 Key Variables and
                                               Constraints Included

Klincewicz,   Fleet sizing problem where    Fixed vehicle cost
Luss, and     customer set is partitioned   Variable vehicle cost
Pilcher       into sectors that are         Common carrier route cost
1990          either served by private
              fleet or common carriers

Bausch,       Uses elastic set              Fixed vehicle cost
Brown, and    partitioning model for        Variable vehicle cost based
Ronen 1994    sample of up to 40 trucks     on distance, speed, and
              and 250 orders to dispatch    travel times
              shipments to either           Common carrier route cost
              private/dedicated resources   Latest shipment date for
              or common carriers            each order
                                            Penalties assigned for
                                            violations such as truck
                                            idleness and schedule
                                            Truck constraints such as
                                            operating radius,
                                            equipment, capacity, and
                                            backhaul capability

Diaby and     Solved distribution problem   Internal travel costs
Ramesh        with carrier service using    consisting of vehicle
1995          branch and bound technique    recall considerations,
              for single vehicle            deadhead costs of overnight
              instances between internal    stop, fuel cost, insurance
              resource and outside          and tariff costs,
              carrier for up to 200         differential customer
              customers                     pricing structure
                                            Common carrier route cost

Chu 2005      Mathematical model and        Fixed vehicle cost
              heuristic algorithm for       Variable vehicle cost
              assigning shipments from      (fuel)
              warehouse to fixed number     Common carrier route cost
              of private trucks or
              outside carriers

Bolduc et     Metaheuristic algorithm for   Fixed vehicle cost
al. 2008      vehicle routing problem       Travel cost
              with private fleet and        Common carrier route cost
              common carrier resources

Cote and      Tabu search heuristic for a   Fixed vehicle cost
Potvin        vehicle routing problem       Variable vehicle cost
2009          where a shipper can either    Common carrier route cost
              use private fleet to serve
              the customer or utilize a
              common carrier

Potvin and    Uses a Tabu search            Fixed cost of internal
Naud 2011     heuristic with a              resources
              neighborhood structure        Variable cost of internal
              based on ejection chains to   resources
              solve problem of assigning    Common carrier route cost
              shipments to internal
              resources or common
              carriers for a
              transportation company

Table 2/Breakdown of Responses by Industry

Industry                           Number of   Percentage
                                   Responses    of Total

Energy/Chemical/Mining                10          10%
Retail                                11          11%
Utilities                              2           2%
Manufacturing--General                10          10%
Manufacturing--Consumer Products      17          17%
Manufacturing--Aerospace/Defense       2           2%
Manufacturing--High Technology         6           6%
Manufacturing--Automotive              2           2%
Life Sciences--Pharmaceuticals         4           4%
Life Sciences--Medical Devices         1           1%
Transportation Service Provider       25          25%
Other                                 11          11%
Total                                101         100%

Table 3/Breakdown of Responses by Annual Sales (USD)

Annual Sales (USD)         Number of   Percentage
                           Responses    of Total

Less than $250 million        11          11%
$250-$500 million              9           9%
$500 million-$1 billion        2           2%
$1-$2 billion                 11          11%
$2-$3 billion                  5           5%
$3-$5 billion                  9           9%
$5-$9 billion                  9           9%
> $9 billion                  45          45%
Total                        101         100%

Figure 1 Private and Dedicated Carrier Percent of Total Weight Shipped

1992    40.1%
1997    40.9%
2002    39.2%
2007    40.5%
2012    46.4%

(Source: US Census Bureau Commodity Flow Survey, 2014).

Note: Table made from bar graph.

Table 4/Satisfaction in Dedicated/Private versus Common Carrier
Decision Process


Statistic                       Cost   Service      Asset      Overall
                                                 Utilization    Value

Mean                            5.36    5.44        5.11        5.33
Standard Deviation              1.38    1.29        1.36        1.31
Lower 95% confidence interval   5.05    5.15        4.81        5.03
Upper 95% confidence interval   5.67    5.72        5.41        5.62
Upper 95% confidence interval   5.67    5.72        5.41        5.62

Scale: 1 = very dissatisfied, 2 = dissatisfied, 3 = some dissatisfied,
4 = neutral, 5 = somewhat satisfied, 6 = satisfied, 7 = very satisfied

Table 5/Importance of Decision Factors on Dedicated/Private versus
Common Carrier Assignment

Statistic    Cost    Dedicated    Route    Backhaul       Time
                       Asset      Length   Potential   Sensitivity
                    Utilization            of Route    of Shipment

Mean         5.90      5.21        4.98      4.31         6.07

Standard     0.80      1.58        1.40      1.90         1.13

Lower 95%    5.90      5.21        4.98      4.31         6.07

Upper 95%    6.07      5.55        5.28      4.72         6.31

Scale: 1 = not important at all, 2 = very unimportant, 3 = somewhat
important, 4 = neither important or unimportant, 5 = somewhat
important, 6 = very important, 7 = extremely important

Figure 2 Responses to Use of Common Carrier and Dedicated Fleet with
Common Carriers to Deliver Outbound Shipments

No               26%

Fleet with
Carriers         33%

Contract Fleet
with Common
Carriers         41%

Note: Table made from pie chart.
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Title Annotation:Industry Notes
Author:Saunders, Lance W.; Bell, John E.; Sawhney, Rapinder, "Rupy"
Publication:Transportation Journal
Date:Jan 1, 2015
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