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Managing Sustainable Development: Technology, Modelling & Applications

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Management".

Deadline for manuscript submissions: closed (20 August 2023) | Viewed by 26015

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Special Issue Editors

Prof. Dr. V. Ravi.

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Guest Editor

Department of Humanities, Indian Institute of Space Science and Technology, Department of Space, Government of India, Valiamala P.O., Trivandrum 695547, Kerala, India
Interests: supply chain and logistics management; reverse logistics; digital supply chain; sustainable supply chain management; new product development; technology management; multi-criteria decision making

Prof. Dr. Suresh Subramoniam

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Guest Editor

Professor & Director, CET School of Management, College of Engineering, Trivandrum 695016, India
Interests: sustainability; AI; information systems and operations

Prof. Dr. Bijulal D.

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Guest Editor

Department of Mechanical Engineering, Government Engineering College, Barton Hill, Thiruvananthapuram 695035, Kerala, India
Interests: operations management; supply chain management; system modelling and simulation; operations research

Special Issue Information

Dear Colleagues,

Sustainable models offer a comprehensive strategy to implement environmentally and socially inclusive applications. The models for its successful application should demonstrate progressive steps and measurable metrics. Sustainable development models should encompass the various areas in the product lifecycle. In their development models, companies have to focus on people and the planet alongside profits. Every developmental activity consists of sourcing, value addition, and the delivery of products and services. Sourcing for companies should include green products and reused and recycled inputs. The cost for the development of greener sourcing strategies needs to be encouraged in organizations. The use of toxic substances should be avoided in manufacturing, and the adoption of fair-trade practices should be encouraged to assist sustainable development. The suppliers using renewable resources should be given preference and weightage in the selection process. The manufacturing process should cause the least pollution and emission of GHG possible. Sustainable practices and processes in manufacturing have a significant effect on improving the sustainability aspect in the supply chain. Labour practices, especially in manufacturing firms, have a tremendous social impact.

Renewable energy usage and energy-efficient equipment constitute an important aspect for sustainable development. Transportation has been a major cause of pollution due to the use of fossil fuels. The inventory management applications therefore have a huge role to play in sustainable development. The application of hydrogen fuel and renewable fuels such as ethanol should be promoted. The acceptance or willingness of consumers to pay higher prices for environmentally friendly products and services could prove to be a major motivation for sustainable development models. The packing and labelling of such products can highly affect the choice of consumers for such products. Reuse, recycle, and return play a major role in the sustainability of supply chains. The role of government and organizations to better implement schemes such as extended producer responsibility (EPR) has to be investigated. The role of stakeholders, market forces, technology, product development, and policy and regulations in operations of sustainability management are crucial. The research on the role of metrics in sustainability management is limited. The application of sustainability factors in different industries such as chemicals, transportation, agriculture, automotive, textiles, pharmaceuticals, tourism, construction, electronics, and healthcare have to explored.

Businesses will be successfully overseen by embracing vital unions in SCM with sustainability facilitators through quicker administration and assistance in expansion, effectiveness, and cost benefits. The articles may criticize or support models in previous reviews of sustainable development. They should present new perspectives on the ecological front and links to the sustainability elements in an organization. A conceptual framework with importance to supplier selection and sustainable products addressing the environmental and social issues dominant within literature would be valuable. Research problems pertaining to issues of renewable source utilization, reusable material development, renewable energy, cleaner sources, and circular supply chains, value recovery, and closed-loop supply chains, applications in emerging economies, sustainability, and virgin material sources, or the applications for the adoption of Industry 4.0 could offer new insights in sustainable development. Managing sustainability amidst unpredictable situations such as a pandemic outbreak makes it even more challenging. The operation of firms in specific geographic locations and the related turbulences create an imbalance in managing supply chains. This Special Issue aims to focus on these areas.

Potential topics for research include, but are not limited to:

Sustainability, its application in the context of viability;
Modeling decision tools for the development of sustainable development in the context of digital technology innovations;
Sustainable development goals: targets and indicators;
Modeling to tackle the disruptions and focusing on sustainability dimensions during unforeseen events
Modeling of sustainability due to impacts on account of servitization and circular economy aspects;
Modeling the performance metrics of sustainable supply chains and operations;
Risk mitigation with the application of digital technologies from a sustainability perspective;
Sustainability in from an emerging economies perspective and its applications;
Model development for conservation and utilization concerning sustainable supply chain perspectives;
Smart manufacturing and sustainability aspects;
Sustainability and big data analytics applications;
Interorganizational requirements and sustainable model development;
Biodiversity and conservation;
Smart energy solutions and access;
Green materials and technologies;
Green financial, policy, and regulatory standards.

Prof. Dr. V. Ravi.
Prof. Dr. Suresh Subramoniam
Prof. Dr. Bijulal D.
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

sustainable development
triple bottom line
sustainability framework
modelling sustainability
sustainability metrics
conceptual framework
sustainable practices.

Published Papers (10 papers)

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Research

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17 pages, 533 KiB

Open AccessArticle

The Road to Sustainable Logistics: Using the Fuzzy Nonlinear Multi-Objective Optimization Model to Build Photovoltaic Stations in Taiwan’s Logistics Centers

by Huai-Tien Wang, Kang-Lin Chiang, Nang-Fei Pan and Yu-Feng Lin

Sustainability 2023, 15(23), 16449; https://doi.org/10.3390/su152316449 - 30 Nov 2023

Viewed by 572

Abstract

In Taiwan, numerous company logistics centers have embraced installing solar photovoltaic power stations (SPPSs) on their rooftops. The primary objective of this study is to expedite the generation of green electricity for sale, bolstering the logistics center’s income and enhancing its environmental, social, and governance (ESG) profile. How can we secure solar photovoltaic power station (SPPS) projects with expedited construction timelines, reduced investment costs, and heightened quality aligned with the long-term ESG objectives? The study applies the critical path method (CPM) to determine the item’s path. Next, the mothed leverages Zimmermann’s mathematical models for nonlinear multi-objectives and Yager’s fuzzy sets to enhance project efficiency, minimizing completion time and cost while maximizing the quality ratio. Subsequently, the project uses Liou and Wang’s defuzzification values and incorporates Dong’s fuzzy to accelerate calculations. In this case, Project HP’s item J, the construction time is reduced from 24.3 to 3.2 days, ensuring that construction quality meets an 85% standard. Item J necessitates expanding the fuzzy cost interval (4549.90, 15,416.65, 26,283.41) (it refers to a scope of possible costs). It becomes evident that construction time plays a pivotal role in controlling costs. For Project HP’s item H, the unit time quality decision ranges from TWD 238,000 to 240,000, to turn into a cost interval of TWD 215,100, 239,000, and 262,900. Consequently, cost transformation transitions from an active to a more passive role, with quality and construction time becoming the driving components. This study uses a fuzzy nonlinear multi-objective model to guide the decision analysis of SPPSs within logistics centers. This strategy enables decision-makers to streamline logistics center operations, ensuring time, cost, and quality (TCQ) alignment during SPPS installation, thereby advancing ESG sustainability goals. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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26 pages, 2305 KiB

Open AccessArticle

Predictive Analytics and Machine Learning for Real-Time Supply Chain Risk Mitigation and Agility

by Abeer Aljohani

Sustainability 2023, 15(20), 15088; https://doi.org/10.3390/su152015088 - 20 Oct 2023

Cited by 1 | Viewed by 9664

Abstract

Supply chain agility has become a key success factor for businesses trying to handle upheavals and uncertainty in today’s quickly changing business environment. Proactive risk reduction is essential for achieving this agility. To facilitate real-time risk prevention and improve agility, this research study proposes an innovative strategy that makes use of machine learning as well as predictive analytics approaches. Traditional supply chain risk management frequently uses post-event analysis as well as historical data, which restricts its ability to address real-time interruptions. This research, on the other hand, promotes a futuristic methodology that uses predictive analytics to foresee possible disruptions. Based on contextual and historical data, machine learning models can be trained to find patterns and correlations as well as anomalies that point to imminent dangers. Organizations can identify risks as they arise and take preventative measures by incorporating these models into a real-time monitoring system. This study examines numerous predictive analytics methods, showing how they can be used to spot supply chain risks. These methods include time series analysis and anomaly detection as well as natural language processing. Additionally, risk assessment models are continuously improved and optimized using machine learning algorithms, assuring their accuracy and adaptability in changing contexts. This research clarifies the symbiotic relationship among predictive analytics and machine learning as well as supply chain agility using a synthesis of theoretical discourse and practical evidence. Case studies from various sectors highlight the usefulness and advantages of the suggested strategy. The advantages of this novel technique include improved risk visibility and quicker response times as well as the capacity to quickly modify operations. The development of a holistic framework that incorporates predictive analytics and machine learning into risk management procedures, setting the path for real-time risk identification as well as mitigation, is one of the theoretical contributions. On the practical side, the case studies offered in this paper show the actual benefits as well as the adaptability of the proposed approach across a wide range of businesses. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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22 pages, 1015 KiB

Open AccessArticle

How Does the Digital Capability Advantage Affect Green Supply Chain Innovation? An Inter-Organizational Learning Perspective

by Jianqi Qiao, Suicheng Li, Su Xiong and Na Li

Sustainability 2023, 15(15), 11583; https://doi.org/10.3390/su151511583 - 27 Jul 2023

Cited by 2 | Viewed by 1917

Abstract

Green supply chain innovation has gained significant attention from academics and practitioners due to its ability to mitigate chain liability risks, meet consumer environmental demands, and create sustainable competitive advantages. Digital technology, a valuable tool for enhancing organizational information processing capabilities, plays a crucial role in promoting successful green supply chain innovation. However, existing research has a limited understanding of how digital capability advantage influences green supply chain innovation. Therefore, based on an inter-organizational learning perspective, this study aims to explore the impact of digital capability advantage on green supply chain innovation and examine the mediating role of green supply chain learning (green supplier learning and green customer learning). The survey results from 221 Chinese manufacturing firms indicate that digital capability advantages contribute directly and positively to green supply chain innovation and also indirectly enhance it through green supplier learning and green customer learning. This study establishes the positive relationship between digital capability advantages and green supply chain innovation and highlights the mediating role of green supplier learning and green customer learning. The research conclusions not only enhance our understanding of the factors and key success paths of green supply chain innovation from a digital perspective but also provide theoretical guidance for its effective implementation in manufacturing firms. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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19 pages, 1205 KiB

Open AccessArticle

Open Innovation Intellectual Property Risk Maturity Model: An Approach to Measure Intellectual Property Risks of Software Firms Engaged in Open Innovation

by B. Senakumari Arunnima, Dharmaseelan Bijulal and R. Sudhir Kumar

Sustainability 2023, 15(14), 11036; https://doi.org/10.3390/su151411036 - 14 Jul 2023

Viewed by 1491

Abstract

Open innovation (OI) is key to sustainable product development and is increasingly gaining significance as the preferred model of innovation across industries. When compared to closed innovation, the protection of intellectual property (IP) that is created in open innovation is complex. For organisations engaging in OI, a sound IP management policy focusing on IP risk reduction plays a significant role in ensuring their sustained growth. Assessing the risks that are involved in IP management will enable firms to devise appropriate IP management strategies, which would ensure sufficient protection of an IP that is created in an OI model. Studies indicate that the risks which are associated with IP and risk management processes also vary with company segments that range from start-ups to micro, small, medium, and large organisations. This paper proposes an open innovation IP risk assessment model to compute the open innovation intellectual property risk score (OIIPRS) by employing an analytic hierarchy process. The OIIPRS indicates the IP risk levels of an organisation when it engages in open innovation with other organisations. The factors contributing to IP risk are identified and further classified as configurable IP risk factors, and the impact of these factors for the various company segments is also factored in when computing the OIIPRS. Further, an OI IP risk maturity model (OIIPRMM) is proposed. This model depicts the IP risk maturity of organisations based on the computed OIIPRS on an IP risk continuum, which categorises firms into five levels of IP risk maturity. The software firms can make use of the OIIPRMM to assess the level of IP risk and adopt proactive IP protection mechanisms while collaborating with other organisations. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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20 pages, 1285 KiB

Open AccessArticle

Innovation Capabilities as a Mediator between Business Analytics and Firm Performance

by Thamir Hamad Alaskar

Sustainability 2023, 15(6), 5522; https://doi.org/10.3390/su15065522 - 21 Mar 2023

Cited by 5 | Viewed by 1837

Abstract

Although business analytics (BA) play an important role in improving firm performance, various firms struggle to deliver their full benefits. Many researchers have investigated the capabilities required to achieve better value through BA, but none have addressed the impact of innovation capabilities as a contextual variable mediating the effects on firm performance. By adopting the Technology-Organization-Environment (TOE) framework, this study suggests a model to evaluate the impact of BA capabilities on firm performance and addresses the mediating role of innovation capabilities. A quantitative approach was adopted for data collection and analysis. Based on 386 surveys of BA experts at Saudi Arabian firms and the use of PLS-SEM to test and validate the model. The results show that organizational factors have a highly significant impact on firm performance. While IT infrastructure and information quality as technological factors showed no significant and positive effect. Furthermore, the findings revealed that innovation capabilities positively mediate the link between IT infrastructure and information quality and firm performance as it affects directly and indirectly firm performance. The findings of this study contribute to the literature by addressing the research gap in BA in the Saudi Arabia context. Moreover, the study result stressing about the role of innovation capabilities on the BA capabilities and the importance of considering the interaction between TOE factors. However, research was carried out within one developing country (Saudi Arabia), which might restrict the findings’ generalizability of the study, and the results must be generalized with care to avoid issues such as structural and cultural variances between developed and developing countries. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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12 pages, 256 KiB

Open AccessArticle

Industrial Robots, Economic Growth, and Sustainable Development in an Aging Society

by Chi Gong, Xianghui Yang, Hongru Tan and Xiaoye Lu

Sustainability 2023, 15(5), 4590; https://doi.org/10.3390/su15054590 - 4 Mar 2023

Cited by 2 | Viewed by 2621

Abstract

The impact of industrial robots and aging on economic growth is analyzed using both theoretical and empirical models in this paper. An aging mechanism is integrated into the task model and Solow model, which integrates the existing relationship between industrial robots and economic growth. Our data come from the International Robot Federation, Penn World Table, and the World Bank, and we obtain robot usage data and macroeconomic data for 77 countries and regions between 1993 and 2019. We found that industrial robots can stimulate economic growth, but aging does not affect it. It is worth noting that aging has more adverse effects on economies using industrial robots than economies without industrial robots. Further, according to mechanism analysis, the main channel of economic growth is industrial robots replacing labor, followed by improving total factor productivity (TFP), a measure of technological change in an economy. Given endogenous problems, the results are still stable. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

23 pages, 4718 KiB

Open AccessArticle

Research on Coordination in a Dual-Channel Green Supply Chain under Live Streaming Mode

by Tianwen Chen, Ronghu Zhou, Changqing Liu and Xiang Xu

Sustainability 2023, 15(1), 878; https://doi.org/10.3390/su15010878 - 3 Jan 2023

Cited by 3 | Viewed by 2169

Abstract

In this paper, we study the coordination issue in a dual-channel green supply chain with one manufacturer and one retailer. The demand in the traditional channel is assumed to be dependent on retail price, sales effort and green degree. Due to the characteristic of live broadcast selling, the demand in the direct channel is assumed to be dependent on price and discount. On the basis of analyzing price, sales effort and green degree strategies in the supply chain under the centralized model, two decentralized models and two coordination models are presented. Moreover, we prove the feasibility of sharing the R&D costs of the green degree and sales effort costs of the advertisement (CS-GS) contract through bargaining problems achieving a win-win situation, but the revenue sharing and wholesale price (RSC) contract commonly used cannot efficiently coordinate the supply chain. Finally, numerical analysis is given to show the impacts of coordination contracts on the supply chain’s performance as well as the impacts of parameters on profits and decisions in the four models. It reveals that the CS-GS contract can not only help to improve the green degree and the price of the product, but also improve the profitability of all supply chain members. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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23 pages, 3532 KiB

Open AccessArticle

Modelling the Returnable Transport Items (RTI) Short-Term Planning Problem

by Najoua Lakhmi, Evren Sahin and Yves Dallery

Sustainability 2022, 14(24), 16796; https://doi.org/10.3390/su142416796 - 14 Dec 2022

Viewed by 1519

Abstract

Returnable transport items (RTI) are used for the handling and transportation of products in the supply chain. Examples of RTIs include plastic polyboxes, stillages or pallets. We consider a network where RTIs are used by multiple suppliers to deliver parts packed in RTIs to multiple customers. We address the short-term planning of empty-RTI flows (i.e., reverse flows) which consists of optimizing the transportation routes used to return empty RTIs from customers to suppliers. A transportation route consists of one or several trucks traveling from a customer to a supplier at a given frequency. The RTI short-term planning problem is critical because it impacts the continuity of loaded-RTI flows and affects the transportation and shortage costs of empty RTIs incurred at the very-short-term. We study a heterogeneous fleet of automotive parts RTIs, under two configurations: pool RTIs, which are standard RTIs shared between suppliers, and dedicated RTIs that are specific to each supplier. To solve the short-term planning problem, we develop a two-step approach using mixed-integer linear programming (MILP) and a greedy heuristic. For pool RTIs, our models enable a reduction of 30% in the number of trucks used and 20% in the distance traveled. Furthermore, if dedicated and pool RTIs are jointly planned, this would enable a 9% gain in terms of transportation costs. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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21 pages, 3796 KiB

Open AccessArticle

Multi-Technology Driven R&D Cost Improvement Scheme and Application Utility of EESP in Energy-Intensive Manufacturing Industry

by Fangyuan Qian, Shuiye Niu and Yujuan Xi

Sustainability 2022, 14(10), 6282; https://doi.org/10.3390/su14106282 - 21 May 2022

Viewed by 1963

Abstract

Facing the sustainable use of electric power resources, many countries in the world focus on the R&D investment and application of electrochemical energy storage projects (i.e., EESP). However, the high R&D cost of EESP has been hindering large-scale industrial promotion in the energy-intensive manufacturing industry represented by the tobacco industry. Reducing and controlling the R&D cost has become an urgent problem to be solved. In this context, this paper innovatively proposes a multi-technology driven R&D cost improvement scheme, which integrates WBS (i.e., Work Breakdown Structure), EVM (i.e., Earned Value Method), BD (i.e., Big Data), and ML (i.e., Machine Learning) methods. Especially, the influence of R&D cost improvement on EESP application performance is discussed through mathematical model analysis. The research indicates that reducing EESP R&D costs can significantly improve the stability of EESP power supply, and ultimately improve the application value of EESP in energy-intensive manufacturing industries. The R&D cost management scheme and technical method proposed in this paper have important theoretical guiding values and practical significance for accelerating the large-scale application of EESP. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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Other

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21 pages, 7043 KiB

Open AccessEssay

Analysis of Factors Influencing the Corporate Performance of Listed Companies in China’s Agriculture and Forestry Sector Based on a Panel Threshold Model

by Yong Sun, Hui Liu, Jiwei Liu, Mingyu Sun and Qun Li

Sustainability 2023, 15(2), 923; https://doi.org/10.3390/su15020923 - 4 Jan 2023

Cited by 2 | Viewed by 1370

Abstract

The global food crisis caused by COVID-19 and the Russia–Ukraine conflict have made many countries around the world realize the significance of agroforestry to a country’s food security. However, China’s agroforestry R&D innovation is currently lagging behind in development, and some agricultural seeds are heavily dependent on foreign countries, which seriously affects China’s national food security. It is especially important to explore the reasons why China’s agroforestry R&D and innovation is lagging behind. As listed agroforestry companies face the market demand directly, there is an urgent need to study the R&D innovations of listed agroforestry companies at present. This paper analyzes the impacts of R&D innovation, corporate management and supply chain management on the corporate performance of listed agroforestry companies using the entropy weighting method, GMM estimation and panel threshold model, mainly by selecting annual panel data from CSMAR for the period 2010 to 2021. The following conclusions were drawn: (1) There is a nonlinear relationship between R&D innovation and firm performance, and a “U”-shaped relationship. This indicates that there is an entrance threshold for R&D innovation in the agroforestry industry, below which corporate performance does not improve. (2) There is a nonlinear relationship between corporate management and corporate performance, and a U-shaped relationship. (3) There is a nonlinear relationship between supply chain management and firm performance, with an inverted-U-shaped relationship. This paper explains the reasons for the slow development of R&D innovation in China’s agriculture and forestry industry and fills the gap in the theoretical study of the nonlinear relationship between R&D innovation and corporate performance of listed companies in China’s agriculture and forestry industry. Finally, this paper provides a theoretical basis for the decision making of government departments related to agriculture and forestry, and offers some suggestions for listed companies in agriculture and forestry to improve their corporate performance. Full article

(This article belongs to the Special Issue Managing Sustainable Development: Technology, Modelling & Applications)

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