Delegation vs. direct sourcing revisited: contract types under correlated supply risks and asymmetric cost information

As a popular practice in purchasing, an ever-increasing number of upper-tier suppliers are being added in the supply base of the original equipment manufacturer (OEM) and leveraged to reduce supply risk. This new trend increases the OEM's opportunities to directly source from tier-2 suppliers (direct sourcing for better control) in addition to delegating tier-1 suppliers to source on behalf of the OEM itself (delegation). This paper is devoted to comparing these two mechanisms (delegation vs. direct souring) under both asymmetric information on the production costs of tier-2 suppliers and correlated supply disruptions with tier-2 suppliers. When the OEM offers a revenue-sharing term contract or a base-commitment term contract (in which the OEM is required to procure a fixed base quantity in addition to an option of procuring additional units at a pre-specified price) to a tier-1 supplier under delegation, delegation achieves the same profit for the OEM as direct sourcing does. However, under a fixed-quantity term contract, delegation achieves a lower profit for the OEM than direct sourcing does, no matter the CM is subject to the procurement budget constraint or deep pocket. Moreover, we find delegation may lead to a higher profit for the OEM than direct sourcing does if an improved fixed-quantity term contract is used under delegation with a deep-pocket CM.</p

Can digital technologies mitigate supply chain volatility? Empirical evidence from China

Digital technologies, such as AI, big data, blockchain, cloud computing, Internet of Things (IoT) and VR/AR, have been widely applied in firms and have greatly transformed supply chain management. We collect the annual reports of Chinese listed companies and adopt a machine learning algorithm to construct variables proxying for firms’ adoption of digital technologies, which we call digitalisation. Given the importance of mitigating supply chain volatility nowadays, we empirically show that a higher level of digitalisation can lead to a significant decrease in supply chain volatility measured by the bullwhip effect. We demonstrate that emerging digital technologies are effective in reducing supply chain volatility, among which the adoption of blockchain exhibits the largest impact. We further investigate whether the mitigating effect of digitalisation varies across different firm characteristics. Specifically, we find that mitigation is stronger for firms with more dispersed supply chain networks and a higher level of managerial expertise.</p

Analysis of dynamic determinants of vehicles involved in crash affecting severity based on in-depth crash data

The dynamic characteristics of vehicles involved in crashes may be an important factor affecting the crash severity. This study investigates the relationship between the dynamic characteristics of vehicles involved in crashes in the five seconds before the occurrence and the crash severity. The findings aim to offer insights for preventing severe crashes and advancing autonomous vehicle technology. This study aims to investigate the impact of dynamic features, such as speed, acceleration, and relative distance of vehicles involved in the crash in the five seconds before the crash, on the crash severity. Five hundred ninety-six crash samples from the China In-depth Mobility Safety Study-Traffic Accident database were selected for crash reconstruction. A random parameters logit model was used to extract and analyze the effect of dynamic features of the vehicles involved in the crash on the crash severity. The random parameters logit model demonstrated a satisfactory fit. Analysis of the parameter estimation results of the model showed that the variables of speed, acceleration, and relative distance between vehicles involved in the crash at some time points during the five seconds before the crash significantly affected the crash severity. Notably, the coefficient of variation of relative distance over 5 s emerged as the most influential positive determinant of the crash severity. Certain dynamic characteristics of vehicles involved in a crash in the five seconds before a crash significantly impact the crash severity. The study’s findings can serve as a reference for preventing severe crashes and advancing the development of autonomous vehicles.</p

Summary of transcriptome sequencing of <i>C</i>. <i>Paliurus</i> leaves and callus.

Summary of transcriptome sequencing of C. Paliurus leaves and callus.</p

The top 20 largest KEGG pathways.

<p>Annotated unigenes were classified into 335 KEGG pathways. The top 20 pathways containing unigenes are displayed.</p

GO classification of assembled sequences.

A total of 19,453 unigenes were classified into three main GO categories: Biological Processes, Cellular Component, and Molecular Function.</p

Frequency of SSRs repeat motifs in <i>C</i>. <i>Paliurus</i>.

Frequency of SSRs repeat motifs in C. Paliurus.</p

Summary of transcription factor unigenes of <i>C</i>. <i>Paliurus</i>.

<p>The number of unigenes related to TFs in each TF family. Among the TF families bHLH, NAC, bZIP and MYB_related proteins were the most abundant.</p

KEGG pathway annotation of the unigenes.

<p>These unigenes were divided into five branches (A, Metabolism; B, Genetic Information Processing; C, Environmental Information Processing; D, Cellular Processes; E, Organismal System.)</p

Summary of the SSRs identified in the transcriptome sequences.

<p>Summary of the SSRs identified in the transcriptome sequences.</p