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Drawing upon resource-based view (RBV) and attribution theoretical lenses, this chapter provides a paradigm for examining the interplay among environmental investment towards green innovation, environmental disclosure as well as firm performance using the structural equation modelling (SEM) methodology. This chapter demonstrate a growing environmental awareness among stakeholders of the relevance of environmental performance to share value. It is also suggested that the mediating power of environmental disclosure between environmental investment and firm value as well as incremental goodwill is crucial. The findings of this chapter provide critical implications for several stakeholders that if environmental performance is hypothesised to affect the firm's value, companies may take proactive measures to avert potential environmental-related violations. Besides, investors may trade based on the evidence as to how firm value and its goodwill from acquisition will be affected by news of its environmental performance.

The Chinese data setting allows researchers to explore the influence of local versus national (central) government ownership on companies. This study aims to examine the influence of government ownership (local versus national) and auditor choice (choosing larger or smaller firms) on audit pricing in China.

This study executed three panel data regressions to examine the two hypotheses using 19,626 observations from 2009 to 2017 in the Chinese data setting. This study also uses the Sobel test to investigate the moderating effect of auditor choice.

This study first examines whether choosing a large audit firm positively influences audit pricing and whether listed state-owned enterprises (SOEs) charge less audit fees to audit firms after controlling for various variables. However, the interaction influence of government ownership and audit firm size on audit pricing is positive, suggesting that a large audit firm charges a client company more, even if the client is an SOE. More importantly, when we divide SOEs into national- and local-SOEs, the results of the influence of auditor choice, government ownership and the interaction of government ownership on audit pricing are consistent (plus, minus, plus), and audit firms charge local-SOEs less than national-SOEs. Furthermore, from the additional analysis, this study finds that the strong auditor type has a moderate effect on the case of local-SOEs on audit pricing and local-SOEs choose smaller auditors.

Research on the differences between local and national government ownership is limited. This study adds empirical results from this perspective. In particular, the findings suggest a further audit pricing research direction to consider the influence of client companies’ ownership types and auditor choice, especially in countries with planned economies.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

This study aims to test the impact of digital skills on the entrepreneurial intentions of last-year undergraduate students in Jordanian universities, especially after the Coronavirus disease pandemic and the digital transformation in education and business patterns. In addition, it aims to assess the role of entrepreneurial alertness as a mediator and entrepreneurship education as a moderator in the relationship between the independent and dependent variables.

The quantitative study used a questionnaire distributed to 401 students from different Jordanian universities. The data was collected over 2 months and two structural equation models were developed using AMOS 25 to examine the relationship.

A significant negative relationship was found between digital skills and entrepreneurial intentions of last-year undergraduate students in Jordanian universities post-coronavirus disease 2019 (COVID-19) pandemic. A fully mediating role of the alertness variable has appeared in addition to a significant moderating role of entrepreneurship education.

This is the first study that attempts to investigate the impact of digital skills on students' entrepreneurial intentions in Jordan after the COVID-19 pandemic, In addition, it is one of the few studies that assess the mediator's and moderator's effects on the same conditions. Finally, the study provided a review of the definitions and models used as part of the contribution to upcoming reviews.

The study aims to examine the association between the sustainable development triangle and real earnings management (REM) and the moderating role of business innovation.

The study was based on the quadruple bottom line approach to measuring corporate sustainable development. For the REM, Roychowdhury model is used to identify the practices. The study used panel data using 740 firm-year observations from non-financial listed companies in the Nigerian market from 2011 to 2020, collected from the Nigeria Stock Exchange.

The study finds a negative influence on the association of economic, environmental, social and governance (EESG) on REM in related party transactions. Thus, by regressing the three different components of REM separately, then EESG will have strongest impact as well. The study suggests a bidirectional association between EESG and REM. Furthermore, the study finds that business innovation strengthens the negative association between EESG and REM. The study concludes that sustainable companies in the Nigerian public market are less liable to practice REM.

The study examines only non-financial listed companies quoted on the Nigeria Stock Exchange, which restricts the generalization of the findings.

The findings of the study should be of immense value to the investors who need comprehensive appraisal of earnings quality to enhance sustainable development strategies for sustainable business innovation among Nigeria firms. Thus, sustainability and innovation can serve as the principles for supporting developing countries impacted by the COVID-19 pandemic and supporting a sustainable development.

The study will be of immense value to policymakers, regulators and standard setters who demand for facts insightful of business practices and reporting behaviors for sustainable development.

Existing studies have mainly focused on triple bottom line. This study adds to the existing body of literature on the Quadruple bottom line in an African market. More so, the study investigates the impact of business innovation on the relationship between economic, environmental, social and governance and real earnings management, which was rarely investigated in the prior literature.

Waiting for a bus may represent a period of intense exposure to traffic particles in hot and noisy conditions in the street. To lessen the particle load and tackle heat in bus stops a shelter was equipped with an electrostatic precipitator and a three-step adiabatic cooling system capable of dynamically adjust its operation according to actual conditions. This study evaluates the effectiveness of the Airbitat Oasis Smart Bus Stop, as the shelter was called, to provide clean and cool air.

The particle exposure experienced in this innovative shelter was contrasted with that in a conventional shelter located right next to it. Mass concentrations of fine particles and black carbon, and particle number concentration (as a proxy of ultrafine particles) were simultaneously measured in both shelters. Air temperature, relative humidity and noise level were also measured.

The new shelter did not perform as expected. It only slightly reduced the abundance of fine particles (−6.5%), but not of ultrafine particles and black carbon. Similarly, it reduced air temperature (−1 °C), but increased relative humidity (3%). Its operation did not generate additional noise.

The shelter's poor performance was presumably due to design flaws induced by a lack of knowledge on traffic particles and fluid dynamics in urban environments. This is an example where harnessing technology without understanding the problem to solve does not work.

It is uncommon to come across case studies like this one in which the performance and effectiveness of urban infrastructure can be assessed under real-life service settings.

In recent years, counterproductive knowledge behavior (CKB) and its types have received increasing interest in knowledge management as the degree of knowledge sharing and innovation in enterprises continues to increase. A rapidly growing number of studies have shed light on the important antecedents and consequences of employees’ CKB. However, the various labels, conceptualizations and operationalizations of CKB have fragmented this body of research. This study aims to systematically integrate the effects of the six types of organizational characteristics on CKB and further draws more general conclusions based on the results of previous studies.

Based on a survey of 103 effect values responsible for 52 CKB samples, the authors use the ABC theory to explore the effects of the six types of organizational characteristics on CKB. Moderator analysis were performed to resolve inconsistencies in empirical studies and understand the contexts under which CKB has the strongest or weakest effect.

The results showed that task interdependence and a positive organizational atmosphere, in general, negatively affect employees’ CKB in the moderation analysis. In contrast, workplace discomfort, negative organizational atmosphere, internal competition and time pressure positively and partly affect employees’ CKB. The direction and magnitude of these effects were affected by emotional factors, knowledge personnel types and sample sources. Discussing the theoretical, methodological and practical implications of these findings can offer a guiding framework for future research.

Better control of employees’ CKB is not achieved by adjusting organizational characteristics alone but by combining personal characteristics and mood changes with it to balance organizational characteristics and CKB. Furthermore, the large-sample joint study integrated the conceptual definition of CKB. The multivariate data study provided more reliable conclusions and a solid theoretical foundation for CKB research areas.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.