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An integrated intuitionistic fuzzy (IF) modelling-based framework for examining the performance analysis of a packaging unit (PU) in three different stages has been proposed.

For the series and parallel configuration of PU, a mathematical model based on the intuitionistic fuzzy Lambda–Tau (IFLT) approach was developed in order to calculate various reliability parameters at various spreads. For determining membership and non-membership function-based reliability parameters for the top event, AND/OR gate transitions expression was employed.

For 15%–30% spread, unit’s availability for the membership function falls by 0.006442%, and it falls even more by 0.014907% with an increase in spread from 30% to 45%. In contrast, for 15%–30% spread, the availability of non-membership function-based systems reduces by 0.007491% and further diminishes. Risk analysis has presented applying an emerging approach called intuitionistic fuzzy failure mode and effect analysis (IFFMEA). For each of the stated failure causes, the output values of the intuitionistic fuzzy hybrid weighted Euclidean distance (IFHWED)-based IFFMEA have been tabulated. Failure causes like HP1, MT6, FB9, EL16, DR23, GR27, categorized under subsystems, namely hopper, motor, fluidized bed dryer, distributor, grader and bin, respectively, with corresponding IFFMEA output scores 1.0975, 1.0190, 0.8543, 1.0228, 0.9026, 1.0021, were the most critical one to contribute in the system’s failure.

The limitation of the proposed framework lies in the fact that the results obtained for both reliability and risk aspects mainly depend on the correctness of raw data provided by the experts. Also, an approximate model of PU is obtained from plant experts to carry performance analysis, and hence more attention is required in constructing the model. Under IFLT, reliability parameters of PU have been calculated at various spreads to study and analyse the failure behaviour of the unit for both membership and non-membership function in the IFS of [0.6,0.8]. For both membership- and non-membership-based results, availability of the considered system shows decreasing trend. To improve the performance of the considered system, risk assessment was carried using IFFMEA technique, ranking all the critical failure causes against IFHWED score value, on which more attention should be paid so as to avoid sudden failure of unit.

The livelihood of millions of farmers and workers depends on sugar industries. So perpetual running of these industries is very important from this viewpoint. On the basis of findings of reliability parameters, the maintenance manager could frame a correct maintenance policy for long-run availability of the sugar mills. This long-run availability will generate revenue, which, in turn, will ensure the livelihood of the farmers.

Mathematical modelling of the considered unit has been done applying basic expressions of AND/OR gate. IFTOPSIS approach has been implemented for ranking result comparison obtained under IFFMEA approach. Eventually, sensitivity analysis was also presented to demonstrate the stability of ranking of failure causes of PU.

This study aims to explore the role of the green market (GM) and green innovation (GI) towards green entrepreneurship (GE) and sustainable development (SD).

Based on cross-sectional data, the researchers used quantitative methods in this study to confirm the conceptual framework. The researchers used a questionnaire to collect the data obtained from Pakistan's knowledge-based companies (KBCs). In total, the researchers used 192 usable samples to deliver the findings.

The researchers used structural equation modeling (SEM) to ensure the model's fitness and as a basis for this study's hypotheses. The findings highlight that the GM factors, such as green product (GP), green design (GD), green supply chain (GSC) and green production (GPN) have a positive and significant effect GM factors, such as on both GE and SD. Further, GI is, also, a significant predictor of GE and SD. Finally, this study's findings show that GE has a predictive role of towards SD.

This study's findings create a source of attention for individuals to preserve the GM's natural resources. Further, mainly in developing contexts like Pakistan, the addition of the GI factor and the GM towards GE and SD contribute to the depth of the existing literature.

By integrating factors, such as innovation toward GE and SD, this study's findings provide an original contribution to the empirical evidence.

The purpose of this study is to examine the impact of country-level governance on sustainability performance, taking into account the effect of sustainable development goals (SDGs) and board characteristics.

This study uses panel data analysis using fixed effect models to investigate the influence of country-level governance on sustainability performance while considering the effect of SDGs and board characteristics. The sample comprises 8,273 firms across 41 countries during the period spanning from 2016 to 2021. The sample is divided into two categories based on the score of SDGs.

The findings of this study show that countries with high SDGs score have better overall country-level governance and board attributes which have a statistically significant positive impact on sustainability performance. However, for those countries with low SDGs, political stability shows a statistically insignificant and negative impact on sustainability performance, while government effectiveness indicates a statistically insignificant positive impact on sustainability performance.

This study contributes to the literature by providing empirical evidence on the relationship between country-level governance, SDGs, board characteristics and sustainability performance. The study also highlights the importance of considering the effect of SDGs on the relationship between country-level governance and sustainability performance. The findings of this study could be useful for policymakers and firms in improving their sustainability performance and contributing to sustainable development.

This paper aims to unearth the essential components of Six Sigma for successful deployment and sustainment of service quality in four different organizations in the United Arab Emirates (UAE). More specifically, the paper is intended to determine the motivation to apply Six Sigma, Voice of Customer, Key Performance Indicators (KPIs), Critical-to-Quality (CTQ), readiness factors, Critical Success Factors, sustainment measures, tools and techniques used, challenges/barriers and performance impact on the company.

An exploratory research methodology with multiple case study analyses was adopted to determine the answers to the research objectives. Four case studies from different service processes of four companies were analyzed. The case studies were collated from these companies via a case study protocol with pre-defined criteria.

The analysis shows that service operation improvement projects are primarily dependent on the voice of the internal customer, with return on investment in savings as the KPI of the process. Most organizations prefer cycle time and errors as the CTQs in the Six Sigma projects. Even novice users can effectively apply the Six Sigma methodology with external experts’ assistance, mentoring and interventions. Across the case studies, it is observed that the projects were successfully deployed due to the support of top management leadership, effective communication and cross-functional teams. Employee resistance to change is the common barrier observed during the case study analysis. Eventually, in all the four case studies, Six Sigma is executed with standard tools and techniques within the define, measure, analyze, improve, control (DMAIC) approach.

The present study’s findings cannot be generalized due to the limited number of case study analyses in different ecosystems in the UAE. The authors would like to analyse and report more case studies in service quality improvement through the Six Sigma methodology to comprehend and develop a generic roadmap for the deployment of Six Sigma in the UAE service industry.

The study’s findings provide insights into commonalities and differences between the essential factors of Six Sigma deployment and sustainability in UAE companies.

The study results might help the policymakers and key decision makers in UAE and other countries understand the effectiveness of Six Sigma in service quality improvement with its essential factors for deployment.

Nowadays, a prominent research area is the development of competitive advantages in companies, due to their environmental commitment and orientation. Based on resource-based view (RBV) and institutional theory (InT), this paper aims to investigate the influence of internal and external orientation on businesses' sustainable performance while considering the effect of sustainable supply chain management (SSCM) practices.

Data from 351 manufacturing companies in the Kingdom of Saudi Arabia have been collected and analysed through structural equation modelling (SEM) using the partial least squares (PLS) method.

The results indicated that both internal and external environmental orientation have important effects on SSCM practices, which in turn have a considerable beneficial effect on environmental, social and economic performance.

Although SSCM is constantly gaining ground in the literature, most SSCM research and models examine its effects, antecedents or motivation, mainly adopting a qualitative approach. Research on the topic adopting a large-scale empirical approach is still limited. In this context, this study contributes to the SSCM management literature by exploring the role of environmental orientation in facilitating the adoption of SSCM practices and improving companies' performance.

The financial system plays an essential role in facilitating the intermediation process for economic growth. Policymakers stress on achieving a well-developed and regulated financial system to achieve economic development and resiliency. Using data from the State of Qatar, this paper aims to examine the impact of financial development indicator on economic growth; the impact of financial development indicator on hydrocarbon and nonhydrocarbon sector; the impact of Islamic banking on hydrocarbon and nonhydrocarbon economic growth.

The research uses quarterly data from 2007 to 2019 and adopts autoregressive distributed lag cointegration techniques to test the long- and short-run dynamic relationship between various measures of financial development and economic growth.

The results present evidence of long-term cointegration between overall financial development indicator and economic growth. Furthermore, the authors document the existence of long-term relationship between financial development and nonhydrocarbon sector. However, there is a lack of evidence on the long-run relationship between financial development and the hydrocarbon sector. Notwithstanding, Islamic banking contributes to overall economic development, as well as to the nonhydrocarbon sector.

This paper offers policymakers with insights to evaluate measures to diversify the economy. It also assists decision-makers in promoting Islamic finance, particularly to the banking sector as a vital contributor to economic growth.

To the best of the author’s knowledge, this paper is the first to evaluate financial development and economic growth for the case of Qatar in light of recent developments in Islamic finance.

In the final step, the trust model is applied to the on-demand federated multipath distance vector routing protocol (AOMDV) to introduce path trust as a foundation for routing selection in the route discovery phase, construct a trusted path, and implement a path warning mechanism to detect malicious nodes in the route maintenance phase, respectively.

A trust-based on-demand multipath distance vector routing protocol is being developed to address the problem of flying ad-hoc network being subjected to internal attacks and experiencing frequent connection interruptions. Following the construction of the node trust assessment model and the presentation of trust evaluation criteria, the data packet forwarding rate, trusted interaction degree and detection packet receipt rate are discussed. In the next step, the direct trust degree of the adaptive fuzzy trust aggregation network compute node is constructed. After then, rely on the indirect trust degree of neighbouring nodes to calculate the trust degree of the node in the network. Design a trust fluctuation penalty mechanism, as a second step, to defend against the switch attack in the trust model.

When compared to the lightweight trust-enhanced routing protocol (TEAOMDV), it significantly improves the data packet delivery rate and throughput of the network significantly.

Additionally, it reduces the amount of routing overhead and the average end-to-end delay.

This study aims to study the distribution characteristics of antibiotic resistance in direct-eating food and analysis of Citrobacter freundii genome and pathogenicity. Residual antibiotics and antibiotic resistance genes (ARGs) in the environment severely threaten human health and the ecological environment. The diseases caused by foodborne pathogenic bacteria are increasing daily, and the enhancement of antibiotic resistance of pathogenic bacteria poses many difficulties in the treatment of disease.

In this study, six fresh fruits and vegetable samples were selected for isolation and identification of culturable bacteria and analysis of antibiotic resistance. The whole genome of Citrobacter freundii isolated from cucumber was sequenced and analyzed by Oxford Nanopore sequencing.

The results show that 270 strains of bacteria were identified in 6 samples. From 12 samples of direct food, 2 kinds of probiotics and 10 kinds of opportunistic pathogens were screened. The proportion of Citrobacter freundii screened from cucumber was significantly higher than that from other samples, and it showed resistance to a variety of antibiotics. Whole genome sequencing showed that Citrobacter freundii was composed of a circular chromosome containing signal peptides, transmembrane proteins and transporters that could induce antibiotic efflux, indicating that Citrobacter freundii had strong adaptability to the environment. The detection of genes encoding carbohydrate active enzymes is more beneficial to the growth and reproduction of Citrobacter freundii in crops. A total of 29 kinds of ARGs were detected in Citrobacter freundii, mainly conferring resistance to fluoroquinolones, aminoglycosides, carbapenem, cephalosporins and macrolides. The main mechanisms are the change in antibiotic targets and efflux pumps, the change in cell permeability and the inactivation of antibiotics and the detection of virulence factors and ARGs, further indicating the serious risk to human health.

The detection of genomic islands and prophages increases the risk of horizontal transfer of virulence factors and ARGs, which spreads the drug resistance of bacteria and pathogenic bacteria more widely.

This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the continuous development of various technologies for autonomous vehicles, the LIDAR-based Simultaneous localization and mapping (SLAM) system is becoming increasingly important. However, in SLAM systems, effectively addressing the challenges of point cloud degradation scenarios is essential for accurate localization and mapping, with dynamic obstacle removal being a key component.

This paper proposes a method that combines adaptive feature extraction and loop closure detection algorithms to address this challenge. In the SLAM system, the ground point cloud and non-ground point cloud are separated to reduce the impact of noise. And based on the cylindrical projection image of the point cloud, the intensity features are adaptively extracted, the degradation direction is determined by the degradation factor and the intensity features are matched with the map to correct the degraded pose. Moreover, through the difference in raster distribution of the point clouds before and after two frames in the loop process, the dynamic point clouds are identified and removed, and the map is updated.

Experimental results show that the method has good performance. The absolute displacement accuracy of the laser odometer is improved by 27.1%, the relative displacement accuracy is improved by 33.5% and the relative angle accuracy is improved by 23.8% after using the adaptive intensity feature extraction method. The position error is reduced by 30% after removing the dynamic target.

Compared with LiDAR odometry and mapping algorithm, the method has greater robustness and accuracy in mapping and localization.

This chapter The Grass Is Greener Where You Water It! delves deeper into explicating Employee Green Behaviour (EGB), which outlines the eco-friendly behaviours practiced by employees. The section provides a more thorough explanation of EGB, including its origins, theoretical foundations, and practical applications in a social and physical environment to create environmentally conscious workplaces. The in-role and extra-role of EGB are discussed to strengthen its execution, and its significance considering the present ecological exigency. This chapter outlines the five-features-hierarchical framework for EGB: Sustainability Initiatives, Non-Harmful Action, Resource Conservation, Peer Influence, and Individual Commitment. The environmental history, ecosystems, and biodiversity and their interaction with humans from the ancient period to the present day are provided. The later unit explores organizational plans to encourage EGB, focussing on the role of HR policies, practices, and systems in nurturing the culture of sustainability within organizations. This chapter reviews current studies on EGB, emphasizing the role of employee engagement, transformational environmental leadership, and corporate culture in promoting green practices. It contributes to the academic literature by analyzing EGB, its relevance, and the effects it can have on organizations and society. It is a great tool for academics, government officials, and business heads to make workplaces environmentally friendly.