Fixed Cost and Resource Allocation Considering Technology Heterogeneity in Two-Stage Network Production Systems

2020 ◽  
pp. 227-249
Author(s):  
Tao Ding ◽  
Feng Li ◽  
Liang Liang
Keyword(s):  
Resource Allocation ◽  
Production Systems ◽  
Fixed Cost ◽  
Two Stage ◽  
Technology Heterogeneity

scholarly journals Centralized resource allocation with the possibility of downsizing in two-stage network production systems

2021 ◽  
Author(s):  
Amir Hossein Yadollahi ◽  
Reza Kazemi Matin
Keyword(s):  
Resource Allocation ◽  
Resource Constraints ◽  
Production Systems ◽  
Data Envelopment ◽  
Two Stage ◽  
New Approach ◽  
Organizational Perspective ◽  
Dea Models ◽  
Common Resource ◽  
Component Processes

The network data envelopment analysis (NDEA) technique has been recently developed to measure the relative efficiency of complex production systems. NDEA models provide more meaningful and informative results in comparison to the conventional black-box DEA approach that ignores the operations of the component processes. Regarding the centralized decision-making systems, normal management imposes common resource constraints to maximize produced outputs and minimize consumed inputs. The present study seeks to introduce new centralized resource allocation models in two-stage network production systems. This intra-organizational perspective also provides the possibility of closing down some of the existing units to improve system efficiency. To do so, three scenarios of centralized DEA models are introduced to take advantage of this possibility. A simple numerical example is used for illustration purposes. An empirical application of the proposed approach to the twenty branches of a university is also presented to show the applicability of the new approach.

Centralized fixed cost and resource allocation considering technology heterogeneity: a DEA approach

2017 ◽  
Vol 268 (1-2) ◽  
pp. 497-511 ◽  
Author(s):  
Tao Ding ◽  
Ya Chen ◽  
Huaqing Wu ◽  
Yuqi Wei
Keyword(s):  
Resource Allocation ◽  
Fixed Cost ◽  
Technology Heterogeneity ◽  
Dea Approach

Fixed cost and resource allocation based on DEA cross-efficiency

2014 ◽  
Vol 235 (1) ◽  
pp. 206-214 ◽  
Author(s):  
Juan Du ◽  
Wade D. Cook ◽  
Liang Liang ◽  
Joe Zhu
Keyword(s):  
Resource Allocation ◽  
Fixed Cost

Decomposition of technical and scale efficiencies in two-stage production systems

2011 ◽  
Vol 211 (3) ◽  
pp. 515-519 ◽  
Author(s):  
Chiang Kao ◽  
Shiuh-Nan Hwang
Keyword(s):  
Production Systems ◽  
Two Stage

Measurement of innovation resource allocation efficiency in civil–military integration enterprises

Kybernetes ◽  
2019 ◽  
Vol 49 (3) ◽  
pp. 835-851 ◽  
Author(s):  
Zilong Wang ◽  
Zhiwen Zhang ◽  
Ng Choon Yeong Jhony
Keyword(s):  
Resource Allocation ◽  
Tobit Model ◽  
Two Stage ◽  
Content Type ◽  
Innovation Activities ◽  
Resource Allocation Efficiency ◽  
Dea Method ◽  
Overall Efficiency ◽  
Positive Effect ◽  
Stage Efficiency

Purpose As a transition economy, China is interested in allocating its limited innovation resources economically, reasonably and efficiently to produce as many outputs as possible with its limited financial and human resources. Nonetheless, what is the efficiency of the allocation of innovative resources for civil–military integration enterprises, and what factors hinder its efficiency improvement? The purpose of this paper is to explore these problems. Design/methodology/approach The improved two-stage network data envelopment analysis (DEA) method is used to measure the overall efficiency and stage efficiency of the innovation resource allocation of 58 Chinese civil–military integration listed companies from 2010 to 2016. Tobit model is used to analyze the influencing factors of resource allocation efficiency. Findings The results indicate that the overall efficiency and stage efficiency of innovation resource allocation fluctuate in varying degrees during the period. The optimization of overall efficiency is restricted by lower efficiency of innovation achievement transformation. Enterprise scale was found to have a significant negative impact on both overall and two-stage efficiencies. Proportion of research and development (R&D) personnel had a positive effect on the overall and two-stage efficiency. Government support had a significant positive effect on the stage of innovation resource development and overall efficiency. Originality/value Previous research studies have used either the DEA or stochastic frontier analysis method to measure the efficiency of innovation activities as a whole and ignored the stage of initial investment to final output in innovation activities. That is, the process in which initial input of R&D resources becomes innovation output, and then becomes economic benefits. Therefore, this paper studies the efficiency of innovation resource allocation of civil–military integration listed companies. The improved two-stage chain network DEA method and Tobit model were used.

scholarly journals Ranking intervals for two-stage production systems

2019 ◽  
Vol 71 (2) ◽  
pp. 209-224 ◽  
Author(s):  
Yongjun Li ◽  
Xiao Shi ◽  
Ali Emrouznejad ◽  
Liang Liang
Keyword(s):  
Production Systems ◽  
Two Stage

scholarly journals POLCA Control in Two-Stage Production Systems

2020 ◽  
Vol 51 ◽  
pp. 1491-1496
Author(s):  
Nuno O. Fernandes ◽  
Matthias Thürer ◽  
Nima Mirzaei ◽  
Luis Pinto Ferreira ◽  
Francisco J.G. Silva ◽  
...  
Keyword(s):  
Production Systems ◽  
Two Stage

Lagrangian Bounds and a Heuristic for the Two-Stage Capacitated Facility Location Problem

2012 ◽  
Vol 1 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Igor Litvinchev ◽  
Edith L. Ozuna
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Computational Study ◽  
Facility Location Problem ◽  
Mixed Integer ◽  
Variable Cost ◽  
Fixed Cost ◽  
Two Stage ◽  
Capacitated Facility Location Problem ◽  
Capacitated Facility Location

In the two-stage capacitated facility location problem, a single product is produced at some plants in order to satisfy customer demands. The product is transported from these plants to some depots and then to the customers. The capacities of the plants and depots are limited. The aim is to select cost minimizing locations from a set of potential plants and depots. This cost includes fixed cost associated with opening plants and depots, and variable cost associated with both transportation stages. In this work, two different mixed integer linear programming formulations are considered for the problem. Several Lagrangian relaxations are analyzed and compared, and a Lagrangian heuristic producing feasible solutions is presented. The results of a computational study are reported.

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