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The paper aims at addressing the following research questions: does institutional quality improve countries' environmental efficiency? And which pillars of institutional quality improve countries' environmental efficiency?

By specifying a directional distance function in the context of stochastic frontier method where GHG emissions are considered as the bad output and the GDP is referred as the desirable one, the work computes the environmental efficiency into the appraisal of a production function for the European countries over three decades.

According to the countries' performance, the findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries. In this environmental context, the role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries.

This article attempts to analyze the role of different dimensions of institutional quality in different European countries' performance – in terms of mitigating GHGs (undesirable output) – while trying to raise their economic performance through their GDP (desirable output).

1. The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

2. We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

3. The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

4. The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

Contemporary technological disruptions are espoused as though they stimulate sustainable growth in the built environment through the Green Internet of Things (G-IoT). Learning from discipline-specific experiences, this paper articulates recent advancements in the knowledge and concepts of G-IoT in relation to the construction and smart city sectors. It provides a scoping review for G-IoT as an overlooked dimension. Attention was paid to modern circularity, cleaner production and sustainability as key benefits of G-IoT adoption in line with the United Nations’ Sustainable Development Goals (UN-SDGs). In addition, this study also investigates the current application and adoption strategies of G-IoT.

This study uses the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) review approach. Resources are drawn from Scopus and Web of Science repositories using apt search strings that reflect applications of G-IoT in the built environment in relation to construction management, urban planning, societies and infrastructure. Thematic analysis was used to analyze pertinent themes in the retrieved articles.

G-IoT is an overlooked dimension in construction and smart cities so far. Thirty-three scholarly articles were reviewed from a total of 82 articles retrieved, from which five themes were identified: G-IoT in buildings, computing, sustainability, waste management and tracking and monitoring. Among other applications, findings show that G-IoT is prominent in smart urban services, healthcare, traffic management, green computing, environmental protection, site safety and waste management. Applicable strategies to hasten adoption include raising awareness, financial incentives, dedicated work approaches, G-IoT technologies and purposeful capacity building among stakeholders. The future of G-IoT in construction and smart city research is in smart drones, building information modeling, digital twins, 3D printing, green computing, robotics and policies that incentivize adoption.

This study adds to the normative literature on envisioning potential strategies for adoption and the future of G-IoT in construction and smart cities as an overlooked dimension. No previous study to date has reviewed pertinent literature in this area, intending to investigate the current applications, adoption strategies and future direction of G-IoT in construction and smart cities. Researchers can expand on the current study by exploring the identified G-IoT applications and adoption strategies in detail, and practitioners can develop implementation policies, regulations and guidelines for holistic G-IoT adoption.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

This study aims to explore the empirical correlation between patient flow issues, quality of green health services and patient satisfaction in specialist medical department factors from patients’ perspectives as service consumers.

This research is a type of nonintervention empirical research that uses an open survey to explore the views and experiences of users of specialist medical department services. The targeted population is hospital patients included in the top five national PERSI (Indonesian Hospital Association) Award 2022 Green Hospital Category, with a total number of respondents of 572 people. This study uses the partial least square-structural equation modeling analysis method with the SmartPLS application.

Patient flow problems generally affect the quality of eco-friendly health services, except for the waiting time problem, which affects service quality. It should be understood as a top priority for patients to receive services from medical specialists without risking time as a core service aspect from the patient’s perspective. In addition, all variables in eco-friendly hospital services affect patient satisfaction, except in the case of visits to specialist medical departments, which do not affect medical support services and hospital practices that are responsive to the delivery of care services resulting from medical support services that are inseparable in integrated services as well as health care following medical ethics.

This study has a novelty in understanding the implications of green practice in determining patient satisfaction in medical specialist department as the epicenter of hospital services and the main object of assessment for the quality of hospital services.

The current chapter proposes a theoretical framework to assess the sustainability of economic growth in the Gulf Cooperation Council (GCC) States. The authors integrate insights from endogenous growth models and consider the unique socioeconomic characteristics of the GCC region to provide a comprehensive and tailored approach to understanding the determinants of economic growth and formulating effective policy measures to foster sustainable development and growth. This chapter highlights the environmental challenges faced by GCC; based on this, the authors suggested indicators to construct a theoretical framework (Economic Growth, Climatic Indicators, Energy Indicators, Social Indicators, and Economic Resources Indicators). The authors propose that policymakers and researchers in GCC States should take these factors into account when devising policies or conducting research aimed at fostering sustainable economic growth. Overall, this chapter presents significant insights for policymakers, researchers, and stakeholders involved in promoting the sustainable economic advancement of the GCC States.

This study’s aim is to introduce a high-performance sorbent for the removal of both anionic (Congo red; CR) and cationic (methylene blue; MB) dyes from aqueous solutions.

Sodium silicate is adopted as a substrate for GO and AgNPs with positive charge are used as modifiers. The synthesized nanocomposite is characterized by FTIR, FESEM, EDS, BET and XRD techniques. Then, some of the most effective parameters on the removal of CR and MB dyes such as solution pH, sorbent dose, adsorption equilibrium time, primary dye concentration and salt effect are optimized using the spectrophotometry technique.

The authors successfully achieved notable maximum adsorption capacities (Qmax) of CR and MB, which were 41.15 and 37.04 mg g⁻¹, respectively. The required equilibrium times for maximum efficiency of the developed sorbent were 10 and 15 min for CR and MB dyes, respectively. Adsorption equilibrium data present a good correlation with Langmuir isotherm, with a correlation coefficient of R2 = 0.9924 for CR and R2 = 0.9904 for MB, and kinetic studies prove that the dye adsorption process follows pseudo second-order models (CR R2 = 0.9986 and MB R2 = 0.9967).

The results showed that the proposed mechanism for the function of the developed sorbent in dye adsorption was based on physical and multilayer adsorption for both dyes onto the active sites of non-homogeneous sorbent.

The as-prepared nano-adsorbent has a high ability to remove both cationic and anionic dyes; moreover, to the high efficiency of the adsorbent, it has been tried to make its synthesis steps as simple as possible using inexpensive and available materials.

The purpose of this study is to determine the characteristics of the studies in terms of country, participant profile and methodology, as well as to determine what the Internet of Things (IoT) is currently contributing to higher education.

The study was developed following the methodology supported by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and the PICOS strategy, retrieving scientific literature from Web of Science, Scopus, ERIC and Google Scholar. Of the 237 studies that the search yielded, 11 were included.

The results showed that among the opportunities offered by IoT is that it not only brings the introduction of information and communication technology into the classroom, but also enhances student interest, thus, improving the quality of teaching in higher education. On the other hand, one of the challenges it faces is the attitude of teachers towards its adoption, as well as the level of digital competence of teachers.

This study presents how higher education institutions are including the IoT in their educational activities. The IoT refers to a network of digital interconnectivity between devices, people and the internet itself that enables the exchange of data between them, allowing key information about the use and performance of devices and objects to be captured to detect patterns, make recommendations, improve efficiency and create better user experiences.

The potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.

The black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.

Through the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.

All things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

The basis for this study on electronic transferable records (ETRs) in the context of digitalizing cross-border trade is established in this chapter. It illustrates how the growing trend toward paperless trade and technological improvements is changing trade operations. This chapter focuses on the need to look into ETRs because of their capacity to influence business transactions while navigating complex legal issues. The specific goals of the study are outlined, including a review of the advantages, legality, difficulties and best practices of ETRs. This study aims to shed light on the possible advantages and disadvantages of ETRs, the legal framework that controls their use and the best practices for their efficient implementation. This study also seeks to provide informative recommendations for businesses and people that are considering using ETRs.

This study explores the evolving world of ETRs and their crucial function in international trade. Multidimensional technique is used to examine the transformative potential of ETRs from a variety of research angles. The research design is based on a comprehensive evaluation of the literature that includes a wide range of reliable sources, including academic papers, business reports and legal documents. The comprehensive retrieval of essential material is ensured through keyword searches in renowned academic databases and industry resources. The qualitative synthesis of secondary sources further enhances this methodology and allows for a complex examination of the implications of ETRs. The case study analysis provides practical information on the benefits, hazards and practical applications of ETRs. Multifaceted aspects are uncovered via a thematic approach and qualitative investigation, including potential advantages, hazards, implementation plans and regulatory frameworks.

ETRs offer a range of potential advantages for cross-border trade, encompassing augmented efficiency, reduced costs and heightened security. Nonetheless, their implementation also presents legal challenges and risks, spanning security and privacy concerns, legal ambiguities and technical complexities. Consequently, it is crucial for individuals and businesses to meticulously assess and mitigate these risks through the integration of robust security protocols, staying informed about legal developments and adhering to pertinent regulatory stipulations. In spite of these hurdles, the trajectory of ETR adoption is anticipated to remain on an upward trajectory, driven by increasing recognition of their potential benefits and the concurrent evolution of legal frameworks and technical standards.

Research limitations included the following: lack of adoption of ETRs internationally; and legal diversity and different legal systems results in different consideration of the ETRs. It makes reaching a unified ETR system more difficult.

It is necessary to develop clear policies and procedures and establish well-defined policies and procedures governing ETR use. These should encompass security guidelines, data protection measures and adherence to legal mandates. Regular review and updates are imperative. Stay current on legal developments: In light of the continuously evolving legal and regulatory landscape pertaining to ETRs, businesses and individuals must stay abreast of pertinent changes and seek professional counsel when necessary. Collaborate with partners and stakeholders: To ensure harmonization and standardization in ETR deployment, active collaboration with partners, regulators and industry associations is vital.

Enhance awareness and education: Investment in awareness and educational initiatives is crucial. Decision-makers should organize training programs, workshops and seminars to enhance understanding of ETRs’ potential benefits in cross-border trade among stakeholders. Socially, the use of ETR can achieve several political advantages for the society. It minimizes risks of corruption through enhancing tracing and auditing abilities for relevant authorities making it more difficult to engage in corrupt practices. That can promote integrity within government and public procurement system.

The development of standardized technical frameworks and interoperable platforms for ETRs could enhance their seamless integration into existing trade systems. Additionally, investigating the integration of emerging technologies like blockchain, IoT and AI into ETR ecosystems could unlock innovative solutions to security, authenticity and data management concerns. This study examines how ETRs can radically alter how trade is conducted on a global scale. This paper examines ETRs’ role in improving cross-border trade digitization by examining their advantages, legal difficulties and implementation techniques. The conclusions will aid firms, decision-makers and attorneys in navigating the constantly changing world of trade agreements. The study’s ultimate goal is to offer takeaways that support effective, secure and legally compliant integration of ETRs, ensuring that they operate as a catalyst for improved global trade efficacy and efficiency.