4. Literature on Industry Experiences and Case Studies

As discussed in the White Paper that presents the proposed framework for FHWA's Freight BCA Study, we will rely on revealed and stated preference surveys of industry to enhance the robustness of the methodology. This Section provides a review of literature on how industries react to improvements in freight transportation.

4.1 Introduction

There is a very small compendium of "industry case studies" which attempt to directly relate improvements in transport infrastructure in general or highways in particular to industry restructuring of distribution (logistics) functions. The general absence of literature directly linking infrastructure improvements to logistics changes does not suggest lack of interest or unimportance of the topic. The infrastructure improvement logistics productivity relationship is a distinct subset of the overall prevailing logistics literature which focuses on least total cost tradeoffs within customer service objectives for a network of diverse inputs (transportation, warehousing, inventory control, order processing, etc.), processes and ensuing technological changes in each of the logistics inputs. To the extent that there have been changes in transport infrastructure the logistics literature has indirectly incorporated these changes in process, such as decreases in average and/or variability of transit time for existing modes, or technology, such as changes in speed or reliability of new transport services, for example air freight, or electronic shipment tracking.

The relationship between infrastructure improvements and logistical restructuring that is addressed by the literature has an approach similar to the early studies of changes in railroad and intercity truck market shares for transportation (tons and ton-miles) of manufactured products. A number of studies demonstrated the obvious: there was a distinct shift of market share from rail to truck for most manufactured goods particularly during the 1960's and 1970's. The rail truck market share studies took two basic forms: macro, reflecting changes in total shares of industrial output between the modes for commodities based on SIC or STCC industry or commodity codes, respectively, and; micro, reflecting "case studies" of shifts in mode split of a firm or industry. The macro studies tended to be in the public domain often as part of policy debates while the micro studies tended to be proprietary often related to carrier market research.

Both macro and micro approaches to measuring rail truck market shares were useful to explain trends in intercity freight competition. However, neither approach was particularly useful to explicitly identify the causal variables for the shift from rail to truck, among which were improvements in cost and service because of new road infrastructure. This situation seems analogous to the "industry" case studies pertaining to the relationship between highway improvements and logistics restructuring. The macro studies, exemplified by statistical relationships between public investment and productivity, do not provide understanding of the logistics process responses to infrastructure. The micro studies, exemplified by industry logistical changes nominally associated with changes in highway infrastructure, do not provide the logistical supply elasticities that reflect shifts in the quality of transportation as a function of improvements in highways.

The issues, problems and needs of the industry "case studies" can be expressed in macro or micro perspective. From a macro perspective the case studies could reflect any transportation improvement with respect to changes in transit time and variability. Rail truck competition would be an example where modal substitution typically results in changes in transit time and variability with ensuing logistics responses. From a micro perspective the case studies would reflect changes in truck transit time and variability based on highway improvements.

There is an extensive body of logistics literature on mode split that reflects least total cost tradeoffs. Although conceptually relevant to the issue of defining logistics restructuring to reflect improvements in transit time and variability, much of the changes in mode split have already occurred as firms shifted from rail to truck for most high value time sensitive goods. Attempts to replicate rail and truck based logistics systems to define responses to changes in transit time and variability are likely to be mostly conjectural. Moreover, the substantial differences between carload rail and truck service, particularly transit time variability, are likely to inflate logistics restructuring relative to changes in truck service from highway improvements unless assumptions are made about non-linear elasticities of logistics inputs.

However, comparisons of shipper logistics restructuring based on cargo shifts to or from rail intermodal to truck is a distinct possibility in strategic long haul rail double stack intermodal corridors which have service quality performances similar to truck. Similarly, changes in shipper logistics restructuring between the use of truck service providers who use (rail) intermodal (for example J.B. Hunt) and those who do not use rail intermodal (for example Werner Enterprises) offers another alternative for investigation. The public domain literature is silent about these recent rail-truck mode split logistics. Both avenues of potential investigation would have to control for more than service changes because of differences in loss and damage, freight rates, packaging, etc. This tends to detract from "intermodal" case studies to the extent that they exist or can be undertaken.

There is a very limited body of literature on the narrow issue of logistics restructuring in response to improvements in truck transit time and variability. Although the literature identifies many changes in truck services based on revisions of processes and applications of new technology, most relate to information and communications which only relate tangentially to improvements in transit time and variability. The literature suggests that the bulk of truck service improvements have more to do with the speed and quality of shipment related information, including advance notification of expected delay and delivery. Therefore attempts to relate changes in transit time and variability must include the existence of information substitution effects for impacts on transit time and variability changes on logistics restructuring. Improvements in information technology (IT) and different applications in shipping and trucking enterprises is another element that confounds attempts to use pre IT literature for possible logistics restructuring benchmarks other than to depict that a causal relationship exists between transit time improvements and restructuring. Indeed, it appears possible to deduce from the literature that recent and emerging IT applications to transportation, particularly trucking, could decrease the impact of transit time variability within distribution networks that have dynamic substitution possibilities, for example closely located networks of affiliated retail stores handling consumer durable goods such as tires, appliances, etc.

4.2 Review of the Literature and Summary of Results

The results of the literature indicate that there are causal relationships between changes in average and variation of transit time and logistics inputs, for example faster more reliable truck transport effects on inventory safety stocks. However, the nature of the causal relationships with regard to logistics elasticities for substituting strategic inputs such as increased use of transportation and reduced number of stocking locations, partly as a function of changes in safety stock, cannot be a-priori defined. For example, for a particular situation defined in terms of average and variation of sales demand during the lead time, and average and variation in transit time, inventory safety stock can be empirically determined to provide a level of inventory availability during the reorder cycle affected by transit time. Other things equal, changes in transit time (average and or variability) will affect the required amount of safety stock. How the transit time changes affect the number of stocking locations because of increased transportation from highway improvements is not evident from algorithms commonly used to estimate safety stock.

Masking the situational nature of the logistics substitutions (restructuring) in response to transportation improvements is the indirect nature and relevance of highway improvements to logistics managers (shippers) compared to carriers (truckers). The literature seems to have focused on extracting changes in processes used by logistics providers who are only indirectly influenced by changes in infrastructure that affect transit time and variability. As a result there is a paucity of explicit causality between highway improvements, truck service (transit time and variability) and logistics responses. Attempts to make explicit linkages are characterized by assumptions or hypothetical situations. Robust linkages and statistics are notably absent.

The literature directly relevant to the relationship between transit time service improvements (mean and variability) ostensibly related to highway improvements and logistics restructuring is exclusively qualitative or incidental in nature such that empirical generalizations do not exist. The principle of dynamic changes in logistics inputs and some examples of logistics restructuring exist but this phenomenon generally has not been related to one variable such as transit time improvements other than in a conjectural sense. Moreover, attempts to relate logistics restructuring in a quantitative manner as an explicit function of transit time improvements have not been possible based on the limited industry case studies available. Consider the results reported in Faucett:

In the initial stages of the research we hoped to obtain estimates of cost savings due to highway system improvements in the various operations of the plants of the firms interviewed in the sample industries. As it turned out, we were able to obtain many fragmentary estimates but these were not in sufficient detail nor comprehensive enough to warrant a quantification of cost savings in each of the sample industries.

There are a number of reasons why the desired measures of cost savings are difficult to obtain. First and foremost are the complicated interrelationships among the operations within the plant and between these operations and the logistics operations. For example, savings in inventory costs due to faster delivery time and reliability affect not only the costs of holding inventories (storage, insurance, pilferage, and interest costs) but also handling costs (labor and equipment). —It was difficult for firms to estimate the effects on these interrelated costs, and the tradeoffs in costs, except in a very approximate fashion.

Second, the impacts of improvements to the highway system on industry cost savings take place over time as firms and plants structure their operations to take advantage of the potential savings. Some of the major cost savings occurred as the interstate system was put in place years ago. Current officials take this system for granted and are hard pressed to estimate what it meant to their operations. Finally, the major impacts of deregulation and advances in communication and computer technologies over the past decades are intertwined with the impacts of highway improvements and are difficult to separate in the cost savings estimates that current officials have witnessed (Faucett).

The research in Faucett reportedly covered 27 companies in six different industries. While the research resulted in a great deal of descriptive information, there was a virtual absence of empirical results by which a direct relationship could be distinguished between highway investments and productivity. The results of the investigation suggested that there were three principal sources of cost (productivity) savings from highway improvements: 1) reduced inventory costs resulting from faster and more reliable replenishment delivery times; 2) economies of scale in larger volumes of output per plant due to access to wider distribution markets; and 3) reductions in regional warehouse operations due to more direct deliveries from plants to retailers, wholesales, and final users as a result of more reliable delivery times direct from manufacturers (Faucett).

The difficulty of the task of linking highway improvements to changes in logistics costs (other than directly related to vehicles) manifested by Faucett was nevertheless urged by Quarmby as a necessity to fully reflect the benefits of road improvements:

Benefits to commercial vehicles of road improvements, calculated as straight time savings, will tend to underestimate the true "business potential". It could be shown that, in a typical operation of retail distribution of food, the benefits from restructuring the distribution and depot network could exceed the benefits of straight time savings by 30 – 50 per cent (sic). It is important that the "business potential" released in this and other industries by network improvements should be better understood (Quarmby).

Quarmby uses the example of a hypothetical retail chain store food distribution warehouse network to construct a conceptual model of "business potential" (logistics restructuring) cost savings that are understated when major highway improvements are evaluated by traditional benefit cost models. The retail food industry example is perhaps among the more obvious instances wherein changes induced in warehouse location through highway improvements increasing vehicle driver productivity have visible effects on the number and location of retail stores served, including new markets. The results suggested as comprising unaccounted business potential seem obvious: 1) it is feasible to serve branches located further away; this opens up new market potential for the company; and 2) the number of warehouses serving a total geographical territory can be reduced (Quarmby).

The author "quantifies" the restructuring benefits as distinct from cost benefit vehicle operating cost savings by presuming savings from warehouse reductions (denoted as economies of scale) and reductions of safety stock from centralization of inventory at fewer stocking locations. Warehouse reduction cost savings are based on assuming marginal costs for warehouse throughput per case handled and inventory savings are based on an assumed annual carrying cost expressed as a percentage (twelve percent) of product investment applied to the estimated average value of the safety stock savings.

The assumed cost of extra transport because of fewer warehouses in response to highway improvements is deducted from the total gross savings of fewer warehouses and reduced inventory safety stock to arrive at estimated net restructuring savings. The estimated net savings of restructuring (reduction in number of warehouse and safety stock) are about 23% greater than that reduction of direct transport savings without restructuring based on hypothetical linear costs assumed by the author. It is important to note that the author does explicitly indicate that, "This section can do no more than illustrate the means by which this 'business potential' can be unlocked in retail physical distribution (emphasis added)."

The results of a series of industry case studies on highway improvements and logistics restructuring were reported in 1990 (Apogee, 1990) and 1991 (Apogee, 1991). The case study methodology was used to find examples of how transportation improvements affect the productivity of specific firms or industries. The focus of the research was to determine through interviews the corporate logistics executives how firms respond with changes in their internal operations to transportation improvements. Productivity changes from transportation improvements were adduced to reflect the following phenomenon: 1) reduce bottlenecks in production and management; 2) increase flexibility in production sourcing and scheduling; 3) improve assess to labor; 4) permit increased specialization of corporate functions; and 5) increase access to near or larger markets.

The results of the case study of approximately fourteen firms revealed three major findings: (1) there is a clear interaction between high technology and transportation; (2) there is a chain-reaction effect that links transport improvements to a series of productivity gains that can effect the structure of how firms do business; and (3) there are clear examples of a relationship between transportation and productivity across a wide range of industries surveyed.

The research was largely exploratory in nature, leading to generalizations that the productivity gains that are occurring in logistics systems are the result of integrating high technology communications and location of vehicles. The preliminary implications were that the transportation improvement linkage with (logistics) productivity was quite different from tangible measures of inputs or outputs such as lane miles built or ton miles of goods moved. The emphasis appeared to be on transportation improvements related to reliability and coordination with attendant impacts on inventories and spatial location within changing distribution networks.

The research suggested that beyond the general finding of increased productivity there was no systematic study of transportation improvements on productivity gains in a cross-section of industries. Few examples were found where any real attempt has been made to quantify potential productivity gains. Attempts to quantify micro-productivity effects are rare. Most managers focus on their immediate problems and departments while transportation induced productivity improvements typically cut across a series of departments. Moreover, the direct measurement of gain is difficult since many of the most significant effects of transportation improvements relate to customer service (Apogee 1991).

A fruitful series of research reports on trucking operators' responses to congestion and used of advanced information technologies were produced from a 1998 survey of California-based trucking fleets (for-hire and private carriage) and larger national carriers with operations in California. An overview of the research plan describes the survey and summarizes the results of the research with respect to traffic congestion, use of information technologies, and use of intermodal facilities in California (Regan and Golob, 1999). The survey reflects a comprehensive knowledge of different operational aspects of sectors within the trucking industries such that it was possible to relate operator profiles to responses to congestion, use of information technology and California intermodal terminals. Subsequently, the authors parsed the data to produce research publications that reflect these topics.

A structural equations model is estimated on the survey data to determine how five aspects of congestion differ across sectors of the trucking industry with respect to: (1) slow average speeds; (2) unreliable travel times; (3) increased driver frustration and morale; (4) higher fuel and maintenance costs; and (5) higher costs of accidents and insurance. For both for-hire and private carriers, scheduling problems due to unreliable travel times is the most important component of the congestion problem. Unreliable travel times are a significantly more serious problem for intermodal air operations and less of a problem for specialized bulk operators. Although much of the findings are common sense, the research does empirically identify sectors of the trucking industry that are most likely to benefit from and support different types of congestion improvements (Golob and Regan, 1999).

Further results of truck freight operator responses to congestion include attitudes towards policies to reduce congestion (Golob and Regan, 1999) and perceptions of congestion problems and potential solutions in maritime intermodal operations in California (Regan and Golob, 1999). The authors used conformity factor analysis with regressor variables to classify twelve hypothetical congestion relief policies: 1) more freeway lanes; 2) electronic clearance stations; 3) special truck freeway lanes; 4) longer hours of operation at ports and distribution centers; 5) congestion tolls; 6) traffic signal optimization; 7) truck only lanes on some surface streets; 8) truck only access to intermodal terminals; 9) real time HAZMAT load information system; 10) electronic international border clearance; 11) traffic signal preemption for trucks; and 12) on street parking bans. The authors arrived at six distinct classes or natural groupings of congestion mitigation policies denoted as factors. The factors (and associate congestion relief policy numbers in parenthesis) are as follows: 1) Dedicated truck facilities (3, 7 and 8); 2) Improvements in operational efficiency (2, 4, 8, 9, 10, and 11); 3) Improvements in traffic management (2, 3, 6, 8 and 9); 4) Truck urban arterial priority (3, 7, 11 and 12); 5) Increased road capacity (1, 4, 6, 7 and 12); and (6) Congestion pricing (1, 5 and 10). The authors conclude that:

From a transportation planning perspective, implementation of the policies included in classes three and four, improved traffic management and truck urban arterial priority, appear to be the most cost effective. Moreover, industry spokespersons who are in favor or either of these two classes of policies tend not to favor the policy of dedicating a single freeway lane to truck traffic, a policy that would be controversial, have potentially severe consequences for other road users, and lead to increased taxation of trucking operations. The addition of a third class, improved operational efficiency, would effectively guarantee a set of policies that appeal in some way to all industry segments. The other advantage of these three sets of policies is that they each encompass a set of policies that can be implemented in small pieces and targeted to severely congested regions (Golob and Regan, April 1999).

Similar research was reported for a subset of trucking companies that serve California marine terminals. The research concluded that:

• Information technologies hold particular promise for reducing delays inside and outside ports. Increased use and reliability of container status inquiry systems which supply carriers with information about what has been unloaded, and where on the port property containers are stored, could go a long way in preventing the problem of drivers arriving at the port before their loads are ready to be moved. Additionally, information about when carriers have scheduled their pickups at the port could help port operators make more appropriate decisions about short, medium and long term staging areas for unloaded containers.
• It seems likely that further improvements in marine international operations will be the result of creative public/private sector collaboration. Goods movement, once primarily a private sector concern is of increasing interest to local, regional and state governing agencies determined to support "sustainable" growth (Regan and Golob, June 1999).

The final set of research reports from the California based truck operator survey concerned perspectives on the usefulness of various sources of traffic information (Golob and Regan, 2000) and trucking industry adoption of information technology (Golob and Regan, 2000). Both reports suggest that the trucking sectors vary by reliance on congestion information and use of different information technologies.

The Golob and Regan literature is of value primarily because it attempts to draw relationships between different operational sectors of the trucking industries and issues related to congestion and responses thereto. A different approach taken by Nagarajan, et. al. emphasizes that innovations in the trucking industry have addressed two basic issues: the enhancement of value to customers at an affordable price and the utilization of information to improve business practices through the application of technology. The non-technological factors influencing the trucking industry are identified as: 1) globalization; 2) intermodalism; 3) changing distribution practices; 4) competitive pressures on price and service; 5) labor productivity and workforce skills; and 6) environmental and safety factors. Technological factors influencing the trucking industry are identified as: 1) telecommunications; 2) computer hardware and software; 3) navigation and positioning systems; 4) surveillance, sensing and tagging technologies; and 5) data exchange and blending. The paper presents an overview of the non-technological and technological factors as well as a conceptual model of the influence of these elements on innovation and firm performance. Although the paper concludes with some obvious effects of technology on the trucking industry, it primarily depicts how different the trucking industry is today from a decade ago.

An attempt to formulate logistics restructuring from hypothetical reductions in average transit time and variability for a sample of fifty shippers along the Interstate 5 corridor in Oregon is quite divorced from the esoteric content of much of the trucking industry literature related to transit time. This "case study" seems to exist to demonstrate that something (logistics restructuring) changes based on shipper responses to degradations of transit time and/or reliability. The theoretical approach to estimate the benefits to industry from a network of infrastructure improvements is succinctly presented as a step-wise procedure:

1. Assess the improvements in travel times and travel time reliability throughout the affected region. Divide the region into sub-regions with distinct transport characteristic impact.
2. Survey the sources of business activity in the region that depends on freight transport. The identified firms need to be categorized according to 1) sub-regions with unique characteristics; and 2) type of industry.
3. For each category of firms the following information needs to be obtained: 1) total sales; 2) logistics costs as a percentage of sales; and 3) relevant elasticities of logistical costs.

However, rather than proceeding with this methodology a "short-form" approach was utilized for a sample of fifty firms to estimate the two types of cost reductions, cost reductions due to logistics restructuring and conventional cost reductions (related to vehicle operating cost time savings). A survey instrument addressed "small," hypothetical degradations in average transit time and variability of transit time that would not prompt logistics restructuring and larger changes that would prompt logistics restructuring. A critical assumption is that the willingness to pay for an improvement in the transportation conditions is the same as the willingness to accept compensation for a decline in these conditions.

The findings reflect the limitations of the survey: only three out of fifty firms would restructure their logistics if the predictability in travel time improved (note assumption of similar elasticities for service degradations and improvements in average transit time and variations of transit time) by twenty percent or the average transportation time is decreased by seventeen percent. Not surprisingly, the three firms that would restructure their logistics in response to changes in transit time reflected the food industry (two respondents) and a manufacturer of office supplies. Otherwise the study notes that:

It is interesting that other 10 firms claim that they would restructure their logistics in response to a sufficient change in travel time reliability or travel time, but they do not provide cost information. It is assumed that all the 47 firms, for which cost information is not available or does not respond to the question, would not restructure. The above result suggests the value of the industry restructuring benefits is quite probable to be of magnitude several times higher than the estimates obtained in this report.

The case study attempts to arrive at a quantitative estimate of the benefits from logistics restructuring using three pivotal assumptions:

1. all industries in the manufacturing sector, on average, experience the same benefit from restructuring, expressed as a cost margin;
2. the sample is considered representative for the industry; and
3. the transportation improvements are big enough to prompt logistics restructuring. Progressing from these laudable assumptions the study indicates that the vague answers to some questions requires the data to be interpreted by assuming a reasonable range of logistics restructuring benefits.

It was noted that on average a twenty-percent change in travel predictability or a seventeen-percent change in travel time would prompt restructuring. The study also notes that:

An interesting finding is that 10 firms say, in answering question A, that they would restructure in response to some degradation in predictability, travel time or both, but these firms did not provide any information in Question C about their current and expected logistics costs after a restructuring (DKS Associates).

The study concludes with upper and lower bound estimates of industry benefit from logistics restructuring, expressed as a markup from unit costs, assuming that all surveyed firms have the same relative weight, of 0.45 and 0.25 percent respectively. The range of restructuring benefits would be between $62 and $111 million (1997 dollars) a year for the region of Oregon affected by Interstate 5 corridor improvements. The present value of the stream of potential logistics restructuring benefits would be $584 to $1046 million (1997 dollars).

The study concludes that:

The benefit from logistics restructuring should not be neglected, though probably it is not enough on its own to justify an infrastructure investment. It is worth remembered that this benefit comes in addition to the conventional benefit stemming from transportation time and cost savings, and may, in some cases change the balance of benefits and costs in favor of the former (DKS Associates).

Although of recent vintage, the work by Nagarajan, et. al. fails to address the integration of trucking into supply chains through emerging IT systems. The rapid growth in electronic business for both industrial distribution (business to business or B2B) and consumer distribution (business to customer or B2C) is reviewed by Chow to define impacts on transportation industrial organization, particularly trucking. Chow identifies emerging forces that are affecting the role of truck service providers such as supply chain disintermediation, supply chain integration, and the state of the art of e-business maturity reflecting the development and utilization of the Internet by transportation companies.

According to Chow there are different business models of carrier participation in emerging electronic freight exchanges that affect shipper and truck service provider relationships:

1. Virtual Third Party Logistics (TPL) dot.coms, representing one stop access to multiple transportation and logistics services from multiple suppliers and extensive decision support offered through an intermediary;
2. sites representing multiple transport carriers and logistics expertise offered as a consulting service in place of an extensive decision support from an affiliated intermediary; and
3. transportation for a specific industry sector.

At this time in the very early stages of electronic logistics networks it is premature to accurately predict whether these information networks will supplement traditional business relationships by concentrating only on spot market movements such as backhauls or the medium will rise to a role of dominating freight service selection. Regardless of the future of different forms of Internet logistics service providers it seems clear that there are fundamental implications for the business model of transportation firms, particularly trucking. Trucking will increasingly become an integral part of electronic logistics because of IT linkages based on speed and reliable processing of information. While some of the trends are evident, such as supply chain disintermediation leading to increased number of small shipments, other elements of the IT service provider organization are less understood, particularly with regard to traditional market structures of transportation service providers such as trucking.

4.3 Relevance of this Body of Literature to the Freight BCA Study

The literature pertinent to "logistics restructuring" benefits of highway improvements suggests that past efforts to empirically relate transportation improvements to logistics cost savings have seriously underestimated the analytical complexities and paucity of non-proprietary information that could be obtained to sustain causal relationships. Indeed, it is by no means clear that the full logistics complexities are sufficiently understood and/or sufficient resources are provided for their identification as witnessed by the DKS short form methodology.

There appear to be three components and applications of the literature germane to highway improvements and logistics restructuring.

• First, the effect of highway improvements on truck service providers with regard to decreased transit time performance (average and variability). It seems reasonable that logistics managers would not normally be able to directly associate highway improvements with transit time changes unless they had responsibility for a private truck fleet which had comparable operating circumstances to typical for-hire sector general freight less than truckload (LTL) and truckload (TL) service providers.
  
  The impacts of highway improvements on truck service capabilities (transit time) should best be determined from relevant sectors of the trucking industries. Work done for the Port Authority of New York and New Jersey on truck sensitivity to congestion toll incentives supports the work of Regan and Golob that trucker perceptions of congestion and improvements vary by sector (Berger). Highway improvements that reduce congestion, whether through additional capacity or changes in the use of existing infrastructure will be perceived differently by various truck sectors as having relevance to transit time average and variability and resulting impacts on vehicle productivity measured in trips or stops.[17]
• Second, the effect of transit time improvements on logistics system inputs can most likely be empirically addressed by logistics managers in relatively controlled environments where there is a similarity of product characteristics from the standpoint of logistics inputs and requirements. Ideally, the firms to utilize would have multiple production and/or distribution warehouse locations such that network effects of changes in transit time could be heuristically simulated and network costs compiled. Firms, which have recently conducted warehouse location analysis, would appear to be more likely to be able to empirically address the logistics restructuring cost savings compared to asking hypothetical questions to a senior manager of a multi-product enterprise.
• Third, IT has brought about radical changes in the integration of trucking companies into supply chains. There are obvious substitution effects between transit time performance (mean and variability) and the speed and accuracy of order processing and fulfillment. To some degree the capability of real time monitoring of shipments enables potential late shipments to be subject to early warning tests and possible corrective action taken to minimize lateness by expediting, substituting or rescheduling shipment or production. These actions should reduce the level and importance of safety stock relative to probabilistic occurrences of late shipments. Real time shipment tracking would appear to diminish the importance of safety stock to reduce potential lost sales (or disrupted production) to the extent that potentially late shipments can be corrected. Similarly, JIT systems would appear to reduce the impact of highway improvements on finished goods warehousing for affected product sectors.

Alternatively, to the degree that highway congestion affecting truck transit time reliability is non-reoccurring, and alternatives for shipment expediting or substitution are very limited, for example retail deliveries in Manhattan from a warehouse in New Jersey, IT offers less opportunity than highway improvements that reduce these delays such as improved information. In the retail sector the reliance on imports and seasonal merchandise interfacing with local marine terminal highway connector congestion may affect the demand for number of warehouses.

The literature pertinent to the impacts of highway improvements on transit time as well as technological changes in the trucking industries suggest that distinguishing causal relationships of highway improvements on logistics has become more complex due to the IT integration of trucking in supply chain commercial relationships. Although web based supply chain IT linkages between shippers and intermediaries, including trucking, are still evolving, the new organizational relationships should be more fully understood to identify whether there are distinctions between supply chain organization of truck service providers and the importance of transit time performance as an independent variable that can be linked to logistics restructuring.

4.4 Concluding Remarks

The public domain literature that contains empirical relationships of the impacts of transit time improvements on logistics system restructuring is for all practical purposes non-existent. The reasons are obvious since this is a highly specialized avenue of inquiry that has different applications within and between distribution networks, for example inbound versus outbound logistics and JIT demand pull versus traditional production push systems. As least total cost logistics systems evolved IT has made transportation service primarily a commodity that is bought at a minimum price in conformity to a set of shipment service specifications, including transit time.

Deregulation of trucking has allowed a wide menu of competitive services and contractual relationships to integrate transportation into supply chain networks wherein the motor carrier has become an extension of the shipper logistics organization. In some instances shipper selection of motor carriers is entirely contracted to third party logistics service providers (3PL). For all possible practices motor carriers have lost their ability to discriminate or differentiate other than by integrating themselves into shipper logistics systems and supply chains through value added services (warehousing, assembly, etc.) or value added information capabilities (shipment tracing, status, etc.).

Distribution networks have become more complex over the last decade since the topic of logistics restructuring in response to transit time improvements was initiated. There has been a shift from seller or buyer logistics systems to integrated supply chain vertical relationships, typified by retailing, and substitution of electronic real time information for traditional elements of logistics such as forecasting and carrier delivery notifications in JIT systems. There is abundant evidence that logistics system productivity with respect to key drivers such as inventory performance measures have been maximized.

This suggests two diametrical possibilities for research into transit time improvements on logistics restructuring:

1. that sweeping productivity improvements have or are anticipated to be achieved through the integration of IT and fully integrated supply chains so that improvements in transit time would generally be regarded as insignificant relative to restructuring unless order of magnitude changes were achieved; or
2. supply chains that are at maximum productivity under full application of existing technology and organizational integration are awaiting transit time improvements for the next wave of logistics restructuring in the absence of further IT innovations. The likely reality is somewhere in between these scenarios, depending on the measures to define the logistics restructuring impacts of transit time improvements.

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