During disasters the demand for transportation increases to distribute relief supplies, but the capacity decrease due to damaged infrastructure and competition for limited assets, leading to higher procurement prices. With the increase in frequency of natural disasters and resulting economic losses, we are motivated to study the historical impact to prepare for the future. We contribute to the disaster modeling, management, and transportation planning literature by measuring the causal effects of disasters on a critical system’s performance, i.e., truckload transportation procurement prices. This research quantifies the magnitude, geographical extent, timing, and duration of the causal effects of disaster (Hurricane Harvey and Hurricane Irma) conditions and consequent relief activity by the Federal Emergency Management Agency (FEMA) on the procurement prices using a difference-in-differences methodology. We find that long-haul truckloads inbound to nodes near the hurricane’s paths experienced the largest statistically significant increase in prices during the hurricane periods. Additionally, FEMA’s relief activity added to the impact of the hurricanes on prices with a larger magnitude, but did not cause an effect outside of the hurricane areas. Notably, the causal increase in prices were both localized and short-lived. We further identify that increase in competition for transportation is a more significant driving factor, for increase in prices, compared to damaged infrastructure. We provide valuable insights for shippers to formulate their emergency transportation decisions, motivate alternate procurement practices to reduce externalities while ensuring timely and economical delivery of relief supplies, and finally discuss future extensions to the modeling approach.

Under a relational contract, the value placed on expected future business must outweigh the short-term temptations to deviate for the buyer-supplier relationship to persist. Operational and relational factors that influence this trade-off have been explored, however, there is a considerable lack of research on the moderating effects of supplier and market characteristics. We offer insights into how supplier service models and market dynamics impact suppliers' decisions to renege on the relational contract. Limited access to transactional and contractual data has restricted previous exploration. We overcome this limitation with a detailed dataset in the for-hire truckload transportation sector. We find that a third-party brokerage service model is better able to overcome operational demand challenges and maintain service due to lower capacity constraints and pooling effects as compared to asset-based providers. Furthermore, when the overall market is capacity-constrained, long-term relationships become less of a deterrent for suppliers to reject business. In addition, during tightly constrained markets, suppliers respond with higher rejection rates to short-term demand surges but not to historical demand variability.

The body of literature on truckload (TL) transportation procurement decisions by firms (shippers) and their transportation service providers (motor carriers) has been driven by real-world challenges faced by a large and important segment of the economy. The field has received the attention of researchers from a wide range of domains. While this attention demonstrates the appeal of these complex procurement problems, it also underscores a key challenge: the literature is dispersed and uncoordinated. This makes it difficult to identify meaningful new streams of research, risks slowing progress in the field, and limits the exposure of the research to wider supply chain audiences. With this review of the existing literature, we coordinate the growing set of research in this domain and demonstrate how the TL procurement literature is positioned within the broader streams of service procurement research. We develop a framework that describes the types (make vs. buy) and timing (strategic or execution stage) of decisions about the procurement of TL transportation services, organized by which actor's perspective is taken-the shipper's or the carrier's. We suggest areas of future research informed by an existing set of industry-led research and the gaps we have identified in the academic literature.

In the for-hire truckload market, firms often experience unexpected transportation cost increases due to contracted transportation service provider (carrier) load rejections. The dominant procurement strategy results in long-term, fixed-price contracts that become obsolete as transportation providers' networks change and freight markets fluctuate between times of over and under supply. We build behavioral models of the contracted carrier's load acceptance decision under two distinct freight market conditions based on empirical load transaction data. With the results, we quantify carriers' likelihood of sticking to the contract as their best known alternative priced load options increase and become more attractive; in other words, carriers' contract price stickiness. Finally, we explore carriers' contract price stickiness for different lane, freight, and carrier segments and offer insights for shippers to identify where they can expect to see substantial improvement in contracted carrier load acceptance as they consider alternative, market-based pricing strategies.

Due to constraints on pack sizes in which products are shipped to retail stores, excess inventory can accumulate in stores. In order to optimize the allocation of store space between storage and customer-facing areas, simple expressions are required for backroom inventory levels that can be inserted into optimization models. This paper systematically investigates the effect of pack size constraints on in-store inventory and storage space needs. The context and problem definition are based on a limited service restaurant setting. An approximation for the distribution of inventory positions after replenishment is proposed, and its accuracy is compared to results obtained from simulation. Furthermore, the effect of pack size constraints on the probability of stock-outs is derived. The expressions are found to be good approximations that are usable in complex optimization models for store space allocation. Building on these results, we perform exploratory analyses and demonstrate how increasing pack sizes increases service levels but also removes revenue-generating frontroom space because by increasing backroom space requirements.

Securing sufficient truckload transportation capacity is a challenge for most shippers. The dominant design currently used across North America is to run an annual reverse auction collecting rates from carriers on each of their freight lanes (origin-destination pairings) and then feeding these rates into the shipper’s transportation management system (TMS), which then uses a routing guide to determine which carrier to tender a load to when a particular shipment materialises. Unfortunately, the routing guide frequently fails. This results in the shipper having to use backup carriers or the spot market, thereby incurring much higher rates. This paper explains why the current dominant design arose in the first place and why it is no longer sufficient. Four promising practices that can improve the transportation procurement process for shippers, carriers and brokers are presented and discussed: Data-driven analysis, transportation portfolio management, dynamic contracting and continuous procurement. These practices are meant to complement the current procurement methods in order to reduce the risk and level of uncertainty for all parties by making the procurement process more dynamic and responsive to the market.

Dynamic macroeconomic conditions and non-binding truckload freight contracts enable both shippers and carriers to behave opportunistically. We present an empirical analysis of carrier reciprocity in the US truckload transportation sector to demonstrate whether consistent performance and fair pricing by shippers when markets are in their favor result in maintained primary carrier tender acceptance when markets turn. The results suggest carriers have short memories: they do not remember shippers' previous period pricing, tendering behavior, or performance when making freight acceptance decisions. However, carriers appear to be myopic and respond to shippers' current market period behaviors, ostensibly without regard to shippers' previous behaviors.

Un reciente estudio arroja luz sobre como la planificacion de posibles escenarios futuros afecta a la toma de decisiones estrategicas de los directivos

The nature of operations executives’ strategic cognition, as the antecedent to their choices about operations strategy, remains underexplored in the literature. This mixed‐methods study examines executives’ thinking about supply chain strategy through the lens of managerial cognition. Our qualitative study at a pharmaceutical distributor, which examined 25 executives’ outlook on the future of the turbulent U.S. healthcare sector and their suggestions for adapting the company's supply chain strategy to that future, suggests that an executive's strategic cognition can be defined by its regulatory focus—whether the executive envisions the future environment in terms of opportunities or threats—and the level of optimism in regards to the envisioned future. We propose a typology that predicts the strategic choices of operations executives based on four types of cognition: pioneering, pushing, protective, and provocative. It describes whether an executive's strategic choices target traditional or novel sources of revenue, and if they seek to influence either the firm's structure and practices or its environment. Our empirical test of the typology using quantitative data collected in a survey of senior operations executives supports the study's propositions associating three of the four types of cognition with their respective preferred strategic choices.

Scenario planning can obviously help leaders make smarter long-term decisions, but effective scenario planning requires a great deal of legwork and research. Committing to it can be extremely beneficial and it is recommended but it is a time- and resource-consuming effort. The authors' studies provide objective evidence that the use of scenarios influences executives judgments about long-range, strategic decisions. But their study does not provide a comprehensive picture of the efficacy of scenario planning. Their results pertain to the effect of a onetime use of scenario planning on long-term decisions. However, the researchers did not examine whether the continual practice of scenario planning would help executives improve when it comes to their long-term decision-making skills.

Changes to the strategy, context or environment of a business unit may necessitate a revision of its supply chain strategy. However, rethinking a supply chain strategy is not an easy problem, and has no clear answer in the specialized literature. Some fundamental questions about supply chain strategizing—i.e., the process of doing supply chain strategy—have been largely ignored, while others have been answered with overly-simplistic type-and-match approaches of unclear validity. In this paper, we present a holistic approach to supply-chain strategizing, called Conceptual System Assessment and Reformulation (CSAR), developed through a series of collaborative management research projects over a decade. This paper presents the key ideas of CSAR and explains how it can be used to capture, evaluate and reformulate the supply chain strategy of a business unit. We argue that these ideas can serve as a step towards a theory of supply chain strategy. Finally, we illustrate the practical merits of CSAR by presenting the case of a large world-class corporation that used the approach as a starting point for an initiative to rethink the supply chain strategy of most of its business units.

This paper shows that ignoring bimodality and lognormality in transit time distributions can cause large increases in the logistic costs of maritime transportation. Bimodal and lognormal transit time distributions are observed to be of moderate frequency (approximately 17%) but high impact in the volume of shipment carried (approximately 85%) in these lanes. Ignoring and assuming incorrect distribution of transit time can have dramatic implications on the safety stock levels and reorder points and hence inventory cost incurred by the shipper. To display the incorrectness of such assumptions, the paper compares the typical approach of using a deterministic value (Case 1) for transit time and Hadley–Whitin (1963) with normal approximation (Case 2) to the authors' simulation and empirical analysis on bimodal and lognormal transit time distributions (Case 3). This paper further explores how the shipper should optimally manage inventory in the parameters of transit time distribution and critical ratio (or the service level of the shipper). Specifically, different regions are defined by the transit time distribution parameters and critical ratios that determine the magnitude of relative cost differences when the three cases are compared.