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Circular Economy Practices in the Context of Emerging Economies

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A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 12091

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Dr. Sadia Samar Ali

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Guest Editor

Associate Professor, Department of Industrial Engineering, Faculty of Engineering, King Abdul Aziz University, Jeddah, Saudi Arabia
Interests: optimization; inventory management; production planning; production management; lean manufacturing; sustainable supply chain; industry 4.0 practices

Prof. Dr. Gerhard-Wilhelm Weber

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Guest Editor

1. Faculty of Engineering Management, Chair of Marketing and Economic Engineering, Poznan University of Technology, 60-965 Poznan, Poland
2. IAM (UME), METU, No: 1, 06800 Ankara, Turkey
Interests: bioinformatics; artificial intelligence; energy; modeling; machine learning prediction
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Dr. Erfan Babaee Tirkolaee

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Department of Industrial Engineering, Istinye University, Istanbul 34396, Turkey
Interests: supply chain management; waste management; sustainable development; artificial intelligence
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Dr. Alireza Goli

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Guest Editor

Department of Industrial Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
Interests: meta-heuristic algorithm; supply chain management; production planning; sustainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Circular economy (CE) is a key solution to dealing with resource crises, in terms of waste produced and the resources consumed. It reduces the need for raw materials by making better use of existing ones. There is a growing need in the CE for organizational culture to change toward sustainability. Supply chains can benefit from a circular economy, which requires a paradigm shift from conventional to sustainable practices. Due to this concern, CE integration has become one of the most critical strategies in developing sustainable supply chains. In order to contribute to the attainment of sustainability objectives in emerging economics, CE is committed to ensuring sustainable resource management strategies for more efficient resource utilization to preserve the environment, social conditions, and the economy. A sustainable circular economy (SCE), which combines a CE and sustainability, can contribute to energy recovery, resource efficiency, economic growth, sustained consumption, and circularity at the macro-level. Digitalisation and smart technologies can promote the transition to a SCE, while businesses can perform more efficient, effective, smart, inclusive, and sustainable operations by integrating smart enabling technologies into SCE. Getting organizations on board with Industry 4.0 will only be possible if they are motivated by a clear understanding of its strategic significance related to SCE. Smart sustainable circular economy (SSCE) is crucial for management to devote time and resources to knowledge management programs, training, and education. For SSCE to succeed, it is necessary to identify employees with the appropriate background for implementing advanced technologies. During the CE adaptation process to SSCE, organisations should also understand the importance of interfacing with humans and machines.

There are different perspectives on the CE, which include, but are not limited to, the following:

Identifying sustainability criteria for CE in emerging economies;
Establishing sustainable operations in the context of Industry 4.0 and CE;
Role of smart supply chain in the circular economy;
CE application challenges in sustainable supply chains;
Application of CE and industry 4.0 driven technologies in the food supply chain;
Application of smart circularity practices in the sustainable supply chain management;
Optimizing sustainable supply chain models for CE framework;
CE and sustainable supply chain challenges;
CE strategies for net zero transition;
Advanced analytics ai/ml models for SSCE 4.0 development.

Dr. Sadia Samar Ali
Prof. Dr. Gerhard-Wilhelm Weber
Dr. Erfan Babaee Tirkolaee
Dr. Alireza Goli
Guest Editors

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Keywords

circular economy
sustainable circular economy
smart sustainable circular economy
advanced analytical models
AI/ML Methods
emerging economics
MCDM techniques

Published Papers (7 papers)

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Editorial

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3 pages, 161 KiB

Open AccessEditorial

Circular Economy Practices in the Context of Emerging Economies

by Sadia Samar Ali, Gerhard-Wilhelm Weber, Erfan Babaee Tirkolaee and Alireza Goli

Sustainability 2024, 16(4), 1417; https://0-doi-org.brum.beds.ac.uk/10.3390/su16041417 - 07 Feb 2024

Viewed by 448

Abstract

A circular economy (CE) is a key solution to dealing with resource crises in terms of waste produced and the resources consumed [...] Full article

(This article belongs to the Special Issue Circular Economy Practices in the Context of Emerging Economies)

Research

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20 pages, 1287 KiB

Open AccessArticle

Economic and Environmental Efficiencies of Organizations: Role of Technological Advancements and Circular Economy Practices

by Syed Khusro Chishty

Sustainability 2023, 15(22), 15935; https://0-doi-org.brum.beds.ac.uk/10.3390/su152215935 - 14 Nov 2023

Viewed by 1574

Abstract

There are two concepts which encompass the new business order worldwide; this has vast implications, especially in the Indian business scenario. The first blanket is the phenomena of digitalization which was present in the undercurrents of all the business activities from the past two decades, and second one is circular economy practices. But in today’s Indian scenario, after the popular reform of “Notebandi”, forcing digitalization of the currency puts it to the forefront of all economic activities, especially in India. The economic reform of demonetization highlighted digitalization of economic transactions in the public eye. The phenomenon of digitalization is commonly referred to as the bundle of novel technologies that aim to improve things constantly. Organizations must take advantage of emerging technology to ensure that operations are both economically and environmentally feasible. Technologies based on sustainable solutions might aid companies in becoming more sustainable and economical. Therefore, this research is derived through the desire to measure the economic and environmental performance and how they were influenced by technology and circular practices of Indian Fast Moving Consumer Goods (FMCG) companies as they are most suited for this research. The sample (n = 203) was derived from senior managers of these companies. The study utilized Structural Equation Modeling (SEM) approach to analyze the results, it was found that digital transformation and circular economy practices are pervasive in nature and influence both Economic and Environmental performance of Indian FMCG companies. One of the main contributions of the study is that it also examines the relationship between technological advancements and economic and environmental performance directly; to date, there is not a single study, to the author’s knowledge, to have studied this relationship. Full article

(This article belongs to the Special Issue Circular Economy Practices in the Context of Emerging Economies)

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17 pages, 918 KiB

Open AccessArticle

Evaluating the Sustainability of Fashion Brands Using a Neutrosophical ORESTE Approach

by Saliha Karadayi-Usta and Erfan Babaee Tirkolaee

Sustainability 2023, 15(19), 14406; https://0-doi-org.brum.beds.ac.uk/10.3390/su151914406 - 30 Sep 2023

Viewed by 1356

Abstract

The fashion industry represents a significant source of consumerism within the global economy and requires substantial funding, eco-friendly practices, and ethical attitudes towards human capital, which are the triple bottom line of sustainability. Conscious customers are the key to reshaping the fashion industry by shopping and supporting fashion brands that adopt sustainable practices. Thus, the purpose of this study is to extract the factors affecting the decision-making process of conscious customers in selecting fashion brands adopting ethical and sustainable implementations, to present a case study covering alternative fashion brands, and to evaluate them in terms of sustainability measures. A bibliometric analysis is conducted within the scope of this research to address the most suitable and original decision-making technique; hence, a novel neutrosophic set-based ORESTE approach is proposed to rank the alternative brands. Next, after reaching the case study findings, a sensitivity analysis is conducted to illustrate the parameter changes’ impact on the result in order to validate the findings’ outcomes. Thus, this paper contributes to the literature by proposing a novel approach as an alternative to Besson ranking, extracting sustainable and ethical fashion practices of brands, and identifying the related reports and websites as references to measure sustainability in the fashion industry. The practitioners and managers can comprehend the factors to be taken into consideration by assessing the sustainability status of the particular fashion enterprises and can examine their positions in the global market within their competitors. Full article

(This article belongs to the Special Issue Circular Economy Practices in the Context of Emerging Economies)

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19 pages, 1532 KiB

Open AccessArticle

Oil Demand Forecasting in Importing and Exporting Countries: AI-Based Analysis of Endogenous and Exogenous Factors

by Hui Zhu

Sustainability 2023, 15(18), 13592; https://0-doi-org.brum.beds.ac.uk/10.3390/su151813592 - 12 Sep 2023

Viewed by 2115

Abstract

Given the prevalence of the digital world, artificial intelligence (AI) stands out as one of the most prominent technologies for demand prediction. Although numerous studies have explored energy demand forecasting using machine learning models, previous research has been limited to incorporating either a country’s macroeconomic characteristics or exogenous elements as input variables. The simultaneous consideration of both endogenous and exogenous economic elements in demand forecasting has been disregarded. Furthermore, the stability of machine learning models for energy exporters and importers facing varying uncertainties has not been adequately examined. Therefore, this study aims to address these gaps by investigating these issues comprehensively. To accomplish this objective, data from 30 countries spanning the period from 2000 to 2020 was selected. In predicting oil demand, endogenous economic variables, such as carbon emissions, income level, energy price, gross domestic product (GDP), population growth, urbanization, trade liberalization, inflation, foreign direct investment (FDI), and financial development, were considered alongside exogenous factors, including energy sanctions and the COVID-19 pandemic. The findings indicate that among the input variables examined in demand forecasting, oil sanctions and the COVID-19 pandemic have had the most significant impact on reducing oil demand, while trade liberalization has proven to be the most influential factor in increasing oil demand. Furthermore, the support vector regression (SVR) model outperforms other models in terms of lower prediction error, as revealed by the error assessment of statistical models and AI in forecasting oil demand. Additionally, when comparing the stability of models in oil exporting and importing countries facing different levels of demand uncertainty, the SVR model demonstrates higher stability compared to other models. Full article

(This article belongs to the Special Issue Circular Economy Practices in the Context of Emerging Economies)

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19 pages, 941 KiB

Open AccessArticle

Enhancing Business Performance through Circular Economy: A Comprehensive Mathematical Model and Statistical Analysis

by Xiaoli Feng and Alireza Goli

Sustainability 2023, 15(16), 12631; https://0-doi-org.brum.beds.ac.uk/10.3390/su151612631 - 21 Aug 2023

Cited by 1 | Viewed by 2002

Abstract

In today’s dynamic and competitive free market, businesses strive to gain a distinct competitive advantage, enabling them to seize opportunities and overcome potential threats. Achieving and sustaining superior performance has become a fundamental objective for companies. Accordingly, the main objective and contribution of this research is to delve into the profound impact of circular economy practices, which are known to foster sustainability and resource efficiency, on financial performance—an essential metric for evaluating a company’s success. Through the development of a proposed mathematical model, we simulate and quantify the influence of circular economy practices on financial outcomes, capturing the intricate relationship between the two. Employing state-of-the-art optimization methods and statistical analysis, our analysis reveals that the implementation of circular economy principles significantly impacts financial performance, contributing to 15.7% of its variance. Interestingly, production diversity, while critical for corporate governance, does not exert a statistically significant influence on financial performance. Notably, although production diversity remains a pivotal aspect of effective corporate governance, our analysis indicates that it does not wield a statistically significant impact on financial performance. Moreover, the combined synergy of circular economy practices and financial performance unveils a noteworthy 24.8% variance in overall company performance, underscoring the intricate interdependence of these pivotal elements. By harnessing state-of-the-art modeling techniques and meticulous analysis, this research yields profound insights into the intricate interplay between circular economy practices and financial performance. This illumination empowers businesses to discern potential pathways for harnessing competitive advantages and nurturing sustainable growth in the dynamic tapestry of today’s business landscape. Full article

(This article belongs to the Special Issue Circular Economy Practices in the Context of Emerging Economies)

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22 pages, 1582 KiB

Open AccessArticle

Evaluating the Enablers of Green Entrepreneurship in Circular Economy: Organizational Enablers in Focus

by Maryam Soleimani, Elahe Mollaei, Mojgan Hamidi Beinabaj and Aidin Salamzadeh

Sustainability 2023, 15(14), 11253; https://0-doi-org.brum.beds.ac.uk/10.3390/su151411253 - 19 Jul 2023

Cited by 1 | Viewed by 1817

Abstract

In recent decades, green entrepreneurship has been at the center of attention as an effective strategy to maintain sustainability and create a competitive advantage for organizations in a circular economy. However, the successful implementation of this strategy requires organizations to have internal enablers. This study endeavored to identify and evaluate organizational enablers for green entrepreneurship in manufacturing Small and Medium Enterprises (SMEs) in Iran. Identifying organizational enablers can help SMEs in facilitating the conditions for adopting green entrepreneurship. To these ends, organizational enablers were extracted by reviewing the literature and then, using the viewpoints of 17 active experts in different industries in SMEs, they were classified. In the next step, the “Best Worst Method” was employed to prioritize the identified enablers (5 factors) and sub-enablers (20 factors). The contextual hierarchical relationships between these factors were identified through the “Interpretive Structural Modeling” method. Using the Matrix of Cross-Impact Multiplications Applied to Classification (MICMAC) analysis, the driving and dependence powers of organizational enablers were computed and the enablers were clustered. Based on the results, among the five enablers, three including total quality management, circular supply chain management, and corporate social responsibility were the most important from the point of view of the experts. Moreover, among the sub-enablers, strategic planning, green purchasing, and corporate social responsibility motivation were more important than other sub-enablers. The results of ISM analysis provided a seven-level hierarchical model and the relationships between them. The results of the MICMAC analysis led to the clustering of 20 organizational enablers in three main clusters: driving (nine factors), linkage (four factors), and dependent (seven factors). The results of this study provide practical suggestions for active senior managers to implement green entrepreneurship in SMEs. Full article

(This article belongs to the Special Issue Circular Economy Practices in the Context of Emerging Economies)

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13 pages, 265 KiB

Open AccessArticle

Corporate Sustainable Development from the Perspective of the Effect of Institutional Investors’ Shareholding on Earnings Management

by Shuo Zhao and Yang Zhao

Sustainability 2023, 15(2), 1281; https://0-doi-org.brum.beds.ac.uk/10.3390/su15021281 - 10 Jan 2023

Viewed by 1202

Abstract

To investigate the mechanism of improving corporate sustainable development, this paper uses the sample data of Shanghai and Shenzhen A-share listed companies between 2008–2017 and empirically investigates the effect of institutional investors’ shareholding on earnings management under sustainable development background. The results show that this shareholding significantly increases earnings management. After controlling the negative impact of earnings management on institutional investors and conducting GMM regression analysis, the shareholding and earnings management still present a significantly positive relation. Compared to unstable institutional investors, stable institutional investors have a relatively more effective supervision influence. This phenomenon indicates that China’s institutional investors do not effectively supervise the earnings management of listed companies. The research in this paper provides suggestions for the Chinese government to promote better corporate sustainable development policies in the capital market, such as improving the evaluation mechanism of institutional investors, further increasing other external supervision measures besides institutional investors for China’s capital market and encourage more stable institutional investors to participate in the capital market to reduce earnings manipulation. Full article

(This article belongs to the Special Issue Circular Economy Practices in the Context of Emerging Economies)

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