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Impact of Operation Management on Sustainable Development of Corporation

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 26753

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Special Issue Editors

Prof. Dr. Tsu-Ming Yeh

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Guest Editor

Department of Industrial Engineering and Management, National Quemoy University, Kinmen County 892, Taiwan
Interests: operation management; service management; decision analysis; human resource management
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Hsin-Hung Wu

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Guest Editor

Department of Business Administration, National Changhua University of Education, Changhua 500, Taiwan
Interests: Internet of Things; artificial intelligence; decision analysis; supply chain management
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Prof. Dr. Yuh-Wen Chen

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Guest Editor

Professor, Department of Information Management, Da Yeh University, No.168, University Rd., Dacun, Changhua 51591, Taiwan
Interests: big data analysis; operations management; multiple criteria decision making; artificial intelligience
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Fan-Yun Pai

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Guest Editor

Department of Business Administration, National Changhua University of Education, Changhua 500, Taiwan
Interests: production and operations management; supply chain management; technology management; industrial marketing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Sustainability is an increasingly relevant issue for a wide range of organizations, and therefore sustainability management strategies and practices are of growing significance. Many sustainability impacts are strongly influenced by operation management decisions and the operations management function embraces the requirements of sustainability management. This has implications for decisions and processes associated, with all aspects of operations management, including strategy, design, planning and control, and improvement.

Over recent years, traditional operation management has been facing several challenges such as globalization, resource scarcity, energy crisis, regulatory pressure, pollution, and environmental issues. In order to face these economic, societal, and environmental challenges, many companies have started implementing sustainable-oriented practices on their operations. Besides, recent advances in Information Communication Technologies (ICTs), such as Big Data, Artificial Intelligence, and the Internet of Things(IOT) are also changing traditional operation management.

This Special Issue aims to address questions related to the impact of operation management on the sustainable development of corporations. This Special Issue invites original research papers, case studies, reviews, and critical perspectives for current and new applied approaches. Potential topics for the Special Issue include, but are not limited to, the following:

operation strategies
operation management
operation research applications
quality measurement
quality management
optimization methods and industrial management
performance evaluation
applications in production, manufacturing and logistics
statistics in production, manufacturing and logistics
decision support
application in computing, artificial intelligence
information management
management science
enterprise resource planning (ERP)
multiple criteria decision making
soft computing on production, manufacturing and logistics
business models for sustainable supply chains
supply chain operations for a circular economy
strategic collaboration
sustainable supply chain management

Prof. Tsu-Ming Yeh
Prof. Hsin-Hung Wu
Prof. Yuh-Wen Chen
Prof. Fan-Yun Pai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

operation management
supply chain management
circular economy
sustainability
performance evaluation
sustainable development
multiple criteria decision making
quality management
new product development
manufacturing

Published Papers (10 papers)

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Research

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13 pages, 1178 KiB

Open AccessArticle

An Inner Dependence Analysis Dynamic Decision-Making Framework

by Yun-Ning Liu and Hsin-Hung Wu

Sustainability 2022, 14(10), 5968; https://0-doi-org.brum.beds.ac.uk/10.3390/su14105968 - 14 May 2022

Cited by 3 | Viewed by 1220

Abstract

During the last decade, with the rapid development of information technology, the immense volume of data poses a challenge to decision-makers. We use a combined dynamic decision-making approach based on the analytic hierarchy process (AHP) to select the best supplier. In this paper, we discuss the interaction between criteria that can lead to expanding our proposed dynamic framework to consider the inner dependencies among criteria. The main contributions are: (1) identifying the most important criteria of supplier selection in a steel bar manufacturer in Taiwan; (2) proposing a simple and rapid analysis of the appropriate supplier selection evaluation framework; and (3) using the AHP and transformation matrix to present the inner dependence among the criteria. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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20 pages, 1707 KiB

Open AccessArticle

The Role of GARCH Effect on the Prediction of Air Pollution

by Kai-Chao Yao, Hsiu-Wen Hsueh, Ming-Hsiang Huang and Tsung-Che Wu

Sustainability 2022, 14(8), 4459; https://0-doi-org.brum.beds.ac.uk/10.3390/su14084459 - 08 Apr 2022

Cited by 5 | Viewed by 1355

Abstract

Air pollution prediction is an important issue for regulators and practitioners in a sustainable era. Air pollution, especially PM_2.5 resulting from industrialization, has fostered a wave of global weather migration and jeopardized human health in the past three decades. Taiwan has evolved as a highly developed economy and has a severe PM_2.5 pollution problem. Thus, the control of PM_2.5 is a critical issue for regulators, practitioners and academics. More recently, GA-SVM, an artificial-intelligence-based approach, has become a preferred prediction model, attributed to the advances in computer technology. However, hourly observation of PM_2.5 concentration tends to present the GARCH effect. The objective of this study is to explore whether the integration of GA-SVM with the GARCH model can build a more accurate air pollution prediction model. The study adopts central Taiwan, the region with the worst level of PM_2.5, as the source of observations. The empirical implementation of this study took a two-step approach; first, we examined the potential existence of the GARCH effect on the observed PM_2.5 data. Second, we built a GA-SVM model integrated with the GARCH framework to predict the 8 h PM_2.5 concentration of the sample region. The empirical results indicate that the prediction performance of our proposed alternative model outperformed the traditional SVM and GA-SVM models in terms of both MAPE and RMSE. The findings in this study provide evidence to support our expectation that adopting the SVM-based approach model for PM_2.5 prediction is appropriate, and that prediction performance can be improved by integrating the GARCH model. Moreover, consistent with our prior expectation, the evidence further supports that taking the GARCH effect into account in the GA-SVM model significantly improves the accuracy of prediction. To the knowledge of the authors, this study is the first to attempt to integrate the GARCH effect into the GA-SVM model in the prediction of PM_2.5. In summary, with regard to the development of sustainability for both regulators and practitioners, our results strongly encourage them to take the GARCH effect into consideration in air pollution prediction if a regression-based model is to be adopted. Furthermore, this study may shed light on the application of the GARCH model and SVM models in the air pollution prediction literature. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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18 pages, 646 KiB

Open AccessArticle

Ranking Decision Making for Eco-Efficiency Using Operational, Energy, and Environmental Efficiency

by Pyoungsoo Lee

Sustainability 2022, 14(6), 3489; https://0-doi-org.brum.beds.ac.uk/10.3390/su14063489 - 16 Mar 2022

Cited by 3 | Viewed by 1450

Abstract

The objective of this paper is to propose a method for evaluating the eco-efficiency of business organizations. In order to adequately capture the inherent properties of eco-efficiency, we present a decision support model that can evaluate an organization based on ranking the derived efficiencies at the operational, energy, and environmental dimensions and taking these factors into account comprehensively. The proposed model was designed in the form of a combination of data envelopment analysis (DEA) and TOPSIS, and we tried to make use of the advantages of each method and offset the disadvantages. Specifically, the operational, energy, and environmental efficiencies were derived through DEA. Then, each efficiency was set as the criteria, and the eco-efficiency ranking was determined through TOPSIS. This study shows that it has the advantage of not requiring preference information from the decision maker and, at the same time, can improve the discriminatory power between efficient and inefficient decision-making units. To apply the proposed model, the analysis results are presented through an illustrative example, and the theoretical significance is described. It is also explained that the proposed model can provide a more realistic and convincing evaluation. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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15 pages, 3167 KiB

Open AccessArticle

A Comparative Study of Unbalanced Production Lines Using Simulation Modeling: A Case Study for Solar Silicon Manufacturing

by Chen-Yang Cheng, Shu-Fen Li, Chia-Leng Lee, Ranon Jientrakul and Chumpol Yuangyai

Sustainability 2022, 14(2), 697; https://0-doi-org.brum.beds.ac.uk/10.3390/su14020697 - 09 Jan 2022

Cited by 1 | Viewed by 1590

Abstract

In the solar silicon manufacturing industry, the production time for crystal growth is ten times longer than at other workstations. The pre-processing time at the ingot-cutting station causes work-in-process (WIP) accumulation and an excessively long cycle time. This study aimed to find the most effective production system for reducing WIP accumulation and shortening the cycle time. The proposed approach considered pull production systems, and the response surface methodology was adopted for performance optimization. A simulation-based optimization technique was used for determining the optimal pull production system. The comparison between the results of various simulated pull production systems and those of the existing solar silicon manufacturing system showed that a hybrid production system in which a kanban station was installed before the bottleneck station with a CONWIP system incorporated for the rest of the production line could reduce the WIP volume by 26% and shorten the cycle time by 16% under the same throughput conditions. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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30 pages, 5715 KiB

Open AccessArticle

An Improved Revenue Distribution Model for Logistics Service Supply Chain Considering Fairness Preference

by Fuqiang Lu, Liying Wang, Hualing Bi, Zichao Du and Suxin Wang

Sustainability 2021, 13(12), 6711; https://0-doi-org.brum.beds.ac.uk/10.3390/su13126711 - 13 Jun 2021

Cited by 16 | Viewed by 2154

Abstract

Revenue distribution is an important issue in the operations of a logistics service supply chain (LSSC). The existing works on revenue distribution are mostly based on the assumption of rational economic people that are purely self-interested. However, people also have a fairness preference, which impacts people’s decision-making behavior or even the success operations of the LSSC. For a two-level supply chain consisting of logistics service integrator (LSI) and several functional logistics service providers (FLSP), this paper establishes an improved revenue distribution model considering FLSPs’ inequity aversion. Specifically, the BO model (abbreviation of a model proposed by Bolton and Ockenfels in 2000) is improved to describe the FLSPs’ inequity aversion, which is combined into the conventional revenue distribution model. The proposed model aims to maximize the revenue of logistics service supply chain and obtains the best revenue distribution ratio of each member under equilibrium. In the numerical cases, the impacts of inequity aversion and the number of members with inequity aversion on the revenue distribution are discussed, respectively. The results show that a higher degree of FLSP’s advantageous inequity aversion corresponds to a lower revenue distribution ratio; a higher degree of FLSP’s disadvantageous inequity aversion corresponds to a higher revenue distribution ratio. Increasing the number of FLSP members with inequity aversion results in a higher profit of LSI and lower total utility of FLSPs and the utility of the supply chain. The more FLSP members with inequity aversion there are, the higher the LSI’s profit is, and the lower the total utility of FLSPs and the utility of supply chain are. In addition, the revenue distribution ratio of the FLSP increases with its relative fairness revenue coefficient among FLSPs. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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14 pages, 1526 KiB

Open AccessArticle

Integrated Operational Model of Green Closed-Loop Supply Chain

by Chui-Yu Chiu, Chen-Yang Cheng and Ting-Ying Wu

Sustainability 2021, 13(11), 6041; https://0-doi-org.brum.beds.ac.uk/10.3390/su13116041 - 27 May 2021

Cited by 6 | Viewed by 1765

Abstract

Due to increasing environmental awareness, companies have started embracing the green supply chain concept to reduce waste of resources. Based on this increased awareness, an integrated green closed-loop supply chain has been developed, which integrates the forward supply chain and reverse supply chain. The reverse supply chain follows the same path as the forward supply chain in the reverse direction to recycle used products. Due to the uncertain quality of used products, not all products can be selected for recycling and reproduction, as the reduced yield might decrease the overall net income in the supply chain. The study develops an evaluation model to consider government subsidy, used product recycling rate, and quality of the used products to explore their impacts on the entire system. The results show that when the reproducibility rate of used raw materials decreases, the net income would also decrease accordingly. Furthermore, when government subsidy increases, the net income of the supply chain also increases accordingly. Similarly, when the recycling rate of used products increases, the net income also increases. As government subsidy affects the net income more than the recycling rate of used products, this research concludes that government subsidy is a key factor in the green closed-loop supply chain. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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12 pages, 530 KiB

Open AccessArticle

Budget Participation Capacity Configuration (BPCC), Budgeting Participation Requirement and Product Innovation Performance

by Mu-Jung Huang, Kuo-Chih Cheng, Shao-Hsi Chung, Huo-Ming Wang and Kuo-Hua Wang

Sustainability 2021, 13(10), 5614; https://0-doi-org.brum.beds.ac.uk/10.3390/su13105614 - 18 May 2021

Cited by 1 | Viewed by 1923

Abstract

As the relationship between the execution of budget participation and innovation performance is still full of controversy, and the innovation capability formed by the important control elements of the organization is the key to bring about product innovation performance, this study aims to explore the impact of the formation of product innovation capabilities on product innovation performance under the demand for budget participation. This study proposes the concept of budget participation capacity configuration (BPCC), which is the integration of procedural justice, self-efficacy, and trust in superiors. This study adopted a questionnaire survey to collect sample data from production managers of the electronics-related companies listed on the Taiwan Stock Exchange and employed structural equation modeling to verify measurement model fit and research hypotheses. The study results present that budgeting participation requirement does not directly affect product innovation performance and confirms that the three organizational control elements together constitute BPCC, which plays a fully intermediary role between budget participation requirement and product innovation performance. The contribution of this research for academic theory is to put forward an explanation of the budget participation-innovation performance dispute, and propose an integrated viewpoint for organizational control elements instead of fragmental studies in the past. For practice, this research provides new evidence for budget participation requirements and sources of innovation capabilities. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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14 pages, 418 KiB

Open AccessArticle

Establishing a Multiple-Criteria Decision-Making Model for Stock Investment Decisions Using Data Mining Techniques

by Kuo-Chih Cheng, Mu-Jung Huang, Cheng-Kai Fu, Kuo-Hua Wang, Huo-Ming Wang and Lan-Hui Lin

Sustainability 2021, 13(6), 3100; https://0-doi-org.brum.beds.ac.uk/10.3390/su13063100 - 11 Mar 2021

Cited by 12 | Viewed by 2865

Abstract

This study attempts to integrate the decision tree algorithm with the Apriori algorithm to explore the relationship among financial ratio, corporate governance, and stock returns to establish a stock investment decision model. The sports and leisure related industries are employed as the research target. The data are collected and processed for generating decision tree and association rules. Based on the analysis outcome, an investment decision model is constructed for investors expecting to decrease their investment risks and further increase their profits. This stock investment decision model is one type of multiple-criteria decision-making model. This study makes three critical contributions to investors. (1) It proposes a systematical model of exploring related data through the decision tree algorithm and the Apriori algorithm to reveal the implicit investment knowledge. (2) An effective investment decision model is established and expected to provide a reference basis during stock-picking decisions. (3) The investment decision model is enhanced with implicit rules found among variables using association rules. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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19 pages, 1299 KiB

Open AccessArticle

Two-Stage Stochastic Program for Supply Chain Network Design under Facility Disruptions

by Kanokporn Kungwalsong, Chen-Yang Cheng, Chumpol Yuangyai and Udom Janjarassuk

Sustainability 2021, 13(5), 2596; https://0-doi-org.brum.beds.ac.uk/10.3390/su13052596 - 01 Mar 2021

Cited by 11 | Viewed by 3125

Abstract

A supply chain disruption is an unanticipated event that disrupts the flow of materials in a supply chain. Any given supply chain disruption could have a significant negative impact on the entire supply chain. Supply chain network designs usually consider two stage of decision process in a business environment. The first stage deals with strategic levels, such as to determine facility locations and their capacity, while the second stage considers in a tactical level, such as production quantity, delivery routing. Each stage’s decision could affect the other stage’s result, and it could not be determined individual. However, supply chain network designs often fail to account for supply chain disruptions. In this paper, this paper proposed a two-stage stochastic programming model for a four-echelon global supply chain network design problem considering possible disruptions at facilities. A modified simulated annealing (SA) algorithm is developed to determine the strategic decision at the first stage. The comparison of traditional supply chain network decision framework shows that under disruption, the stochastic solutions outperform the traditional one. This study demonstrates the managerial viability of the proposed model in designing a supply chain network in which disruptive events are proactively accounted for. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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Review

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20 pages, 1203 KiB

Open AccessReview

Classification of Industry 4.0 for Total Quality Management: A Review

by Erhan Baran and Tulay Korkusuz Polat

Sustainability 2022, 14(6), 3329; https://0-doi-org.brum.beds.ac.uk/10.3390/su14063329 - 11 Mar 2022

Cited by 11 | Viewed by 4682

Abstract

The philosophy of total quality management is based on meeting quality requirements in all processes and meeting customer needs quickly and accurately through the contribution of all employees. This concept means that all the processes in an enterprise, all the technology used, and all the workforce employed represent the total quality of the enterprise, with the necessary controls and corrections made to ensure that the quality is sustainable. In this study, a detailed literature review and classification study regarding Industry 4.0, Industry 4.0 technologies, and quality has been carried out. The place and importance of quality in Industry 4.0 applications have been revealed by this classification study. In previous studies in the literature, the relationship between Industry 4.0 technologies and quality has not been examined. With this classification study, the importance of quality in Industry 4.0 has emerged, and an analysis has been conducted regarding which quality criteria are used and how often. Full article

(This article belongs to the Special Issue Impact of Operation Management on Sustainable Development of Corporation)

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