Junfei Chu, Jie Wu, Qingyuan Zhu and Jiasen Sun
Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at the…
Abstract
Purpose
Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at the problem of resource scheduling in the private cloud environment, the purpose of this paper is to propose a resource scheduling approach from an efficiency priority point of view.
Design/methodology/approach
To measure the computational efficiencies for the resource nodes in a private cloud environment, the data envelopment analysis (DEA) approach is incorporated and a suitable DEA model is proposed. Then, based on the efficiency scores calculated by the proposed DEA model for the resource nodes, the 0-1 programming technique is introduced to build a simple resource scheduling model.
Findings
The proposed DEA model not only has the ability of ranking all the decision-making units into different positions but also can handle non-discretionary inputs and undesirable outputs when evaluating the resource nodes. Furthermore, the resource scheduling model can generate for the calculation tasks an optimal resource scheduling scheme that has the highest total computational efficiency.
Research limitations/implications
The proposed method may also be used in studies of resource scheduling studies in the environments of public clouds and hybrid clouds.
Practical implications
The proposed approach can achieve the goal of resource scheduling in private cloud computing platforms by attaining the highest total computational efficiency, which is very significant in practice.
Originality/value
This paper uses an efficiency priority point of view to solve the problem of resource scheduling in private cloud environments.
Details
Keywords
Weijiao Wang, Shanshan Chen, Jinan Shao, Junfei Chu and Zhe Yuan
The aim of this study is to empirically test the link between servitization and trade credit in manufacturing firms as well as the boundary conditions of this link.
Abstract
Purpose
The aim of this study is to empirically test the link between servitization and trade credit in manufacturing firms as well as the boundary conditions of this link.
Design/methodology/approach
Using a unique dataset of 4,974 observations covering 838 manufacturing firms publicly listed in the United States during 1990–2020, this study examines the impact of servitization on trade credit and the moderating impacts of financial slack and service relatedness based on fixed-effect regression models.
Findings
The authors find that servitization shows a U-shaped relationship with trade credit. Besides, financial slack negatively moderates this U-shaped relationship whereas service relatedness has no significant impact on this relationship.
Originality/value
This paper is the first to empirically verify the influence of servitization on trade credit in manufacturing firms based on longitudinal secondary data and signaling theory. The research findings can provide several important theoretical and managerial implications for scholars and practitioners in operations management.