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The main aim of this study is to understand the role of smart technologies and show the rankings of various smart technologies in collection and classification of electronic waste (e-waste).

This study presents a framework integrating the concepts of collection and classification mechanisms and smart technologies. The criteria set includes three main, which are economic, social and environmental criteria, including a total of 15 subcriteria. Smart technologies identified in this study were robotics, multiagent systems, autonomous tools, smart vehicles, data-driven technologies, Internet of things (IOT), cloud computing and big data analytics. The weights of all criteria were found using fuzzy analytic network process (ANP), and the scores of smart technologies which were useful for collection and classification of e-waste were calculated using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR).

The most important criterion was found as collection cost, followed by pollution prevention and control, storage/holding cost and greenhouse gas emissions in collection and classification of e-waste. Autonomous tools were found as the best smart technology for collection and classification of e-waste, followed by robotics and smart vehicles.

The originality of the study is to propose a framework, which integrates the collection and classification of e-waste and smart technologies.

To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

Loneliness and social isolation are risk factors for morbidity and mortality and a growing health concern. Peer support is an intervention that has shown efficacy in the wider health-care arena. However, little is known about its effectiveness when working with adults and adolescents experiencing these issues. The purpose of this study is to conduct a scoping review on loneliness and social isolation in adult and youth populations.

A preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews was conducted. Five databases, Web of Science, Academic Search Complete, Embase, PsycINFO and Scopus were searched for peer-reviewed literature published in English from inception to 2023.

The search yielded 2,402 articles of which (N = 12) met the inclusion criteria for this review. Peer support interventions for loneliness and social isolation are a relatively new topic of interest for academics. However, it is apparent that loneliness and social isolation cut across populations experiencing various health and social issues. More experiential research is needed to evidence the effectiveness of peer support in these areas with both adults and adolescents. Emerging areas of interest include the use of technology to deliver interventions and the use of technology to facilitate peer support implementation with populations difficult to reach.

Peer support may be a promising social intervention to help those experiencing loneliness and social isolation associated with a range of health conditions. However, further research needs to be undertaken in this emerging area of practice.

Loneliness and social isolation are of increasing concern. To the best of the authors’ knowledge, this is the first scoping review conducted in this area

Rapid innovation and developments in personal electronic technology have encouraged users to change users' devices more frequently than ever, which has resulted in creating a massive increase in the amount of electronic waste. The study focuses on identifying the barriers to closed-loop supply chain (CLSC) in the electronic industry.

A framework for analyzing the relationships among CLSC adoption barriers is designed. The authors adopted the decision-making trial and evaluation laboratory (DEMATEL) technique to determine the critical barriers of electronic CLSC from the opinion of experts in the field.

The outcome from the analysis suggests that cost barriers, financial barrier, process barriers and supplier-side barriers are the main causal factors that prevent the adoption and implementation of e-waste CLSC. The causal relationship indicates that financial barrier is the most influential factor, while phycological barrier is the most flexible barrier to the adoption of e-waste CLSC.

This study is restricted to CLSC adoption barriers in the electronic industry by evaluating 36 sub-barriers grouped into 8 main dimensions related to different members of the supply chain.

Closed-loop adoption barriers have been proposed to understand the crucial barriers to implementation of CLSC in the electronic industry. The cause-and-effect relationship indicates the critical factors to be improved to increase adoption of e-waste CLSC, helping managers and regulatory bodies to mitigate the problem areas.

This study contributes to the literature on CLSC by adopting a multi-criteria decision-making (MCDM) technique which captures the critical barriers of e-waste CLSC adoption in Indian scenario.

The purpose of this paper is to evaluate the barriers militating against the adoption of robotics in the construction industry.

Robotics implementation barriers were obtained from the previous studies and then through questionnaire survey construction stakeholders in Nigeria evaluate these barriers. Consequently, these barriers were examined via the exploratory factor analysis (EFA) technique. Furthermore, a model of these barriers was implemented by means of a partial least square structural equation modeling (PLS-SEM).

The EFA results showed that these barriers could be categorized into two: cost and technology. Results obtained from the proposed model showed that platform tools were crucial tools for implementing cloud computing.

The novelty of this research work will be provided a solid foundation for critically assessing and appreciating the different barriers affecting the adoption of robotics.

Sustainability issues are crucial in today’s competitive environment. The integration of technology plays a vital role in the attainment of sustainability objectives. The study aims to investigate the relationship between green intellectual capital (IC), green information systems (IS), green management initiatives (GMI) and green technology adoption in light of natural resource-orchestration theory (ROT). Moreover, digital technology adoption mediates between green IC, green IS, GMI and sustainable performance. Finally, digital transformation strategy is used as a moderator between green technology adoption and sustainable performance.

A sample of 484 managers from automobile manufacturing companies was used in this study to evaluate the proposed relationships using the Structural Equation Modeling (SEM) methodology.

Findings reveal that green IC, green IS and GMI significantly influence green technology adoption. Besides, green technology adoption plays a crucial role in improving sustainable performance. Moreover, green technology adoption significantly mediates between green IC, green IS, GMI and sustainable performance. Finally, a digital transformation strategy significantly strengthens the relationship between green technology adoption and sustainable performance.

The organizations need green technology adoption to address environmental concerns, respond to consumer demand, achieve cost savings and comply with government regulations. Besides, in decision-making, organizations must focus on green IC, green IS, GMI, green technology adoption and digital transformation strategy to boost sustainable performance.

The originality of this study lies in its use of the natural ROT as a framework to examine the impact of multiple green resources on green technology adoption, leading to sustainable performance. Digital transformation strategy is used as a moderator between green technology adoption and sustainable performance. This study provides a comprehensive and integrated perspective on the subject with empirical evidence and relevant insights, contributing to the advancement of the field.

Misinformation surrounding the Sustainable Development Goals (SDGs) has contributed to the formation of misbeliefs among the public. The purpose of this paper is to investigate public sentiment and misbeliefs about the SDGs on the YouTube platform.

The authors extracted 8,016 comments from YouTube videos associated with SDGs. The authors used a pre-trained Python library NRC lexicon for sentiment and emotion analysis, and to extract latent topics, the authors used BERTopic for topic modeling.

The authors found eight emotions, with negativity outweighing positivity, in the comment section. In addition, the authors identified the top 20 topics discussing various SDGs and SDG-related misbeliefs.

The authors reported topics related to public misbeliefs about SDGs and associated keywords. These keywords can be used to formulate social media content moderation strategies to screen out content that creates these misbeliefs. The result of hierarchical clustering can be used to devise and optimize response strategies by governments and policymakers to counter public misbeliefs.

This study represents an initial endeavor to gain a deeper understanding of the public’s misbeliefs regarding SDGs. The authors identified novel misbeliefs about SDGs that previous literature has not studied. Furthermore, the authors introduce an algorithm BERTopic for topic modeling that leverages transformer architecture for context-aware topic modeling.

The purpose of the research was to evaluate the relationship between income and the recycled materials used in order to rate the business related to circular repair services under the burden of economic development in the countries of the European Union.

The analytical processes explore data from 2010 to 2020. The countries were divided into clusters according to economic maturity (Human Development Index (HDI), real Gross domestic product (GDP) per capita). Subsequently, the relationships were evaluated through the income indicators (for the 13 population groups), and the circular materials use rate indicator. The three indicators decomposed into five specific metrics were employed. The commonly applied characteristics of the descriptive analysis, Pearson's correlation coefficient and the panel regression analysis were engaged in the investigation.

The results demonstrated the vast disparities between income and circular materials use. In the more economically developed countries, their levels were twice higher as the less-developed countries. However, there is a meaningful positive relationship between them. The greatest attention was paid to the panel regression analysis applied to the relationship between income and circular economy (CE) use. The results showed that in a majority of the cases (different income categories), there is a significant positive relationship. When comparing the outcomes of the regression models between the groups of the countries according to their economic development, a closer relationship was clearly demonstrated in the countries with a lower level of development (Bulgaria, Romania, Croatia, Hungary).

Besides the specific strengths, the study also shows some limitations identified mainly on the data side. The latest data on the consumption of circular materials come from 2020, so they do not cover the period related to the pandemic crisis. It is believed that there may have been some changes in income during the pandemic, and they may have harmed CE. Furthermore, there is to note that some limitations occur in the analytical process. The incompleteness of the data can also be included here as certain data is not available; hence, it was estimated directly by the Eurostat statistical authority.

At the same time, the following are currently considered among the primary barriers: financial restrictions, insufficient infrastructure, weak government support and obstacles on the global market. Consumers, industry leaders and the government are the most influential stakeholder groups in overcoming barriers. Higher demand for repair services will also initiate further development of business activities in this area at various regional levels. Progress in the repair services economy will continue to require extensive efforts in the future. Systematic coordination of activities at multiple levels of government together with manufacturers, designers, educational institutions, community institutions and individuals will be essential.

Socioeconomic characteristics such as sex, age and education represent crucial predictors of consumer behavior. Therefore, the authors would like to focus future research on analyzing these characteristics and examine all the conceptual frameworks of consumer behavior and its positioning in detail within CE and the strategies related to the repair service. Discussing this issue through follow-up research will allow for solving complex transformational and political tasks related to the repair service strategies within CE. It will also inspire the discussion frameworks and multidisciplinary solutions to this issue affecting the fields of human geography, sociological, ethnographic and political sciences.

In less-developed countries, wage change can have a more substantial impact on the development of the CE. Also, a closer relationship between business in the field of repair services with income and the use of circular materials was manifested in the same way.

User acceptance is a necessary precondition to implementing self-driving buses as a solution to public transport challenges. Focusing on potential users in a real-life setting, this paper aims to analyze the factors that affect their willingness to use public autonomous shuttles (PASs) as well as their word-of-mouth (WOM) intentions.

Grounded on Unified Theory of Acceptance and Use of Technology (UTAUT2), the study was carried out on a sample of 318 potential users in a real-life setting. The hypothesized relationships were tested using partial least squares structural equation modeling (PLS-SEM).

The study reveals that performance expectancy, facilitating conditions, hedonic motivation and trust are significant predictors of PAS usage intention, which is, in turn, related to WOM communication. Additionally, the factors that impact the intention to use a PAS are found to exert an indirect effect on WOM, mediated by usage intention.

This study includes practical insights for transport decision-makers on PAS service design, marketing campaigns and WOM monitoring.

While extant research focuses on passengers who have tried autonomous shuttles in experimental settings, this article adopts the perspective of potential users who have no previous experience with these vehicles and identifies the link between usage intention and WOM communication in a real-life traffic environment.

若要引入自動駕駛巴士來解決公共交通的問題和挑戰,一個必不可少的先決條件是得到用戶的認可。本研究透過重點分析活在真實生活環境中的潛在用戶,來探討影響他們使用公共自動交通工具的意願和口碑動機的各個因素。

本研究以延伸整合型科技接受模式為基礎,對一個涵蓋處身於真實生活環境中318名潛在用戶的樣本進行分析和探討。研究人員以偏最小平方法的結構方程模型 (PLS-SEM), 去測試各個被假設的關聯。

研究結果顯示,績效期望、有利條件、享樂動機和信任均明顯能夠預測人們使用公共自動交通工具的意願,而人們使用公共自動交通工具的意願又反過來與口碑溝通有所相關。另外,研究人員發現,影響人們使用公共自動交通工具意願的各個因素,對口碑會產生間接的影響,而使用意願是會起著調節作用的。

現存的學術研究均聚焦分析那些曾於實驗設置下坐過自動交通工具的人士,而本研究卻採用從未坐過自動交通工具人士的角度來進行分析與探討,並且找出了於實際的交通環境裡、使用意願與口碑溝通之間的關聯。

本研究提供的啟示,對有關公共自動交通工具服務設計、市場營銷活動和口碑監督工作的運輸決策者來說頗具實務意義。

In recent years, researchers and practitioners have paid a great deal of attention to the circular economy (CE) due to its potential social and environmental benefits. However, limited attention has been devoted in the literature to studying the barriers to CE implementation in the apparel retail industry in emerging and developing nations besides China. Consequently, the purpose of this paper is to analyse the barriers to implementing CE in the Indian garment retail market.

This exploratory study uses a comprehensive literature analysis to identify the micro-level impediments to CE adoption in India's garment retail industry. The study aims to identify these barriers using a Delphi process, consisting of three stages. The first stage involves literature reviews and expert opinions, while the second and third stages involve survey methods with 14 industry professionals and academics. The use of the two primary data sources allows for triangulation of the data, which improves the validity of the findings and enables broader conclusions to be drawn from the results.

This study indicates that the top three challenges to implementing CE principles in the Indian apparel retail industry are “standards and regulation barriers” (84%), “strategic barriers” (82%) and “supply chain management and technology barriers” (79%). Strategies for overcoming these obstacles include gaining top management support, coordinating supply chain components, training and employee motivation.

This study considers only Indian apparel retail industry, and the practical implications could potentially limit the study to emerging Asian economies.

To the best of the authors’ knowledge, this is the first research of its type to explore CE obstacles at the organizational level in the Indian garment retail business. Thus, it contributes to a greater understanding of the topic and enables practitioners to develop effective policies and business strategies for CE and sustainability.