An Agent-Based Simulation Model for Supply Chain Collaborative Technological Innovation Diffusion

Zhang, H. P.

doi:10.2507/ijsimm14(2)co6

Cited by 11 publications

(4 citation statements)

References 28 publications

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“…The agent based simulation is used for testing new ideas, to predict the effect of a new technology, developing new theory, to aid decision-making and what-if training, conducting critical experiments and hypotheses generators [16]. The main software for this type of simulation are Swarm®, Repast®, NetLogo®, AnyLogic®, MASON® and Ascape®.…”

Section: Agent-based Simulationmentioning

confidence: 99%

Using Hybrid Simulation to Represent the Human Factor in Production Systems

Oliveira¹,

Montevechi²,

Pinho³

et al. 2017

Int. j. simul. model.

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Discrete-event simulation (DES) has been widely used in systems analysis. However, authors defend the idea that this kind of simulation does not properly represent the human element or the factors affecting its productivity. In Agent-Based Simulation (ABS), agents are intelligent, autonomous and proactive beings, which are features closely related to human behaviour. Therefore, ABS and DES were combined into one model to represent the human element as agents, who were subjected to one of the factors that affect their performance, the circadian rhythm. After statistical validation it was determined that the computer models integrating ABS and DES represent the productive systems under analysis with high level of confidence. A comparison between the model built and a DES model where operators are represented by resources was also performed. It was verified that the ABS/DES represents better the actual systems behaviour than the DES, showing a lower average of relative error.

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Section: Agent-based Simulationmentioning

confidence: 99%

Using Hybrid Simulation to Represent the Human Factor in Production Systems

Oliveira¹,

Montevechi²,

Pinho³

et al. 2017

Int. j. simul. model.

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“…The following articles are examples: in [5] the authors synchronized the manufacturing agents on a JADE™ platform of a shop floor controller using the hybrid communication protocols in the simulation; Zhang [6] simulated an agent-based model to answer how the technological information of the supply chain emerges and diffuses between suppliers and manufacturers.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Allocation of Additional Human Resources Using Hybrid Simulation

Sena¹,

Silva²,

Costa³

et al. 2017

Int. j. simul. model.

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This work simulated several alternatives for the dynamic allocation of additional human resources in a company that produces a group of specific products. The goal was to increase the average amount of the margin of the total contribution through a hybrid application of a discrete event simulation (DES) and an agent-based modelling simulation (ABMS). Two different decision-making forms were proposed to determine which workstation should receive an additional operator. The first proposal was based on the occupancy level of the operators, while the second one was based on the intermediate queue size. The computational model was operationally validated by comparing the results with actual production data from the company. Twelve scenarios were analysed using a margin of the established contribution. Based on the occupancy rate, the ratio improved on average by 27.68 %, with an additional operator in the workstation. According to the second criterion, this improvement raised to 117.51 %.

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“…The high-technology (high-tech) industry in China also presents a trend of intra-product specialisation. Total factor productivity (TFP) can deeply reflect the influence generated by scientific and technological innovation and progress, scale economy and organisational innovation, and other advanced production factors (Zhang, 2015). Therefore, TFP can represent the innovation ability of an industry.…”

Section: Introductionmentioning

confidence: 99%

Intra-product Specialisation and the Innovation Ability of the High-technology Industry in China

Cao

Zhang

et al. 2017

Science, Technology and Society

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The purpose of this paper is to analyse the influence of intra-product specialisation on the innovation ability of the high-technology industry in China. To achieve this research goal, we use the generalised method of moments (GMM) with a dynamic panel data model in our empirical research. Total factor productivity (TFP) and its decomposition variables are used to measure the innovation ability. The Malmquist index is employed to calculate TFP and its decomposition variables, namely, technology progress, technical efficiency and scale efficiency. Previous studies show that intra-product specialisation can raise TFP, but our empirical results reveal that the impact of the intra-product specialisation on the TFP is uncertain: it decreases TFP in the initial period but increases it in the lag period. Results also indicate that an increase in the proportion of state-owned property rights exerts a positive influence on TFP and the change in pure technical efficiency. Technical efficiency is greatly influenced by intraproduct specialisation, whereas intra-product specialisation exerts a slight influence on technological progress. The capital investment in research and development (R&D) has a positive effect on TFP, and the contribution rate of R&D labour input to TFP is relatively low. The main conclusion is that China need to improve the degree of intra-product specialisation, accelerate the evolution of industry technical standards and reduce the coordination cost of intra-product specialisation to enhance the innovation ability of the high-technology industry.

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An Agent-Based Simulation Model for Supply Chain Collaborative Technological Innovation Diffusion

Cited by 11 publications

References 28 publications

Using Hybrid Simulation to Represent the Human Factor in Production Systems

Using Hybrid Simulation to Represent the Human Factor in Production Systems

Dynamic Allocation of Additional Human Resources Using Hybrid Simulation

Intra-product Specialisation and the Innovation Ability of the High-technology Industry in China

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