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It has been six months from the time the first case was registered, and nations are still working on counter steering regulations. The proposed model in the paper encompasses a novel methodology to equip systems with artificial intelligence and computational audition techniques over voice recognition for detecting the symptoms. Regular and irregular speech/voice patterns are recognized using in-built tools and devices on a hand-held device. Phenomenal patterns can be contextually varied among normal and presence of asymptotic symptoms.

The lives of patients and healthy beings are seriously affected with various precautionary measures and social distancing. The spread of virus infection is mitigated with necessary actions by governments and nations. Resulting in increased death ratio, the novel coronavirus is certainly a serious pandemic which spreads with unhygienic practices and contact with air-borne droplets of infected patients. With minimal measures to detect the symptoms from the early onset and the rise of asymptotic outcomes, coronavirus becomes even difficult for detection and diagnosis.

A number of significant parameters are considered for the analysis, and they are dry cough, wet cough, sneezing, speech under a blocked nose or cold, sleeplessness, pain in chests, eating behaviours and other potential cases of the disease. Risk- and symptom-based measurements are imposed to deliver a symptom subsiding diagnosis plan. Monitoring and tracking down the symptoms inflicted areas, social distancing and its outcomes, treatments, planning and delivery of healthy food intake, immunity improvement measures are other areas of potential guidelines to mitigate the disease.

This paper also lists the challenges in actual scenarios for a solution to work satisfactorily. Emphasizing on the early detection of symptoms, this work highlights the importance of such a mechanism in the absence of medication or vaccine and demand for large-scale screening. A mobile and ubiquitous application is definitely a useful measure of alerting the officials to take necessary actions by eliminating the expensive modes of tests and medical investigations.

A magnetorheological knee prosthesis is presented that automatically adapts knee damping to the gait of the amputee using only local sensing of knee force, torque, and position. To assess the clinical effects of the user‐adaptive knee prosthesis, kinematic gait data were collected on four unilateral trans‐femoral amputees. Using the user‐adaptive knee and a conventional, non‐adaptive knee, gait kinematics were evaluated on both affected and unaffected sides. Results were compared to the kinematics of 12 age, weight and height matched normals. We find that the user‐adaptive knee successfully controls early stance damping, enabling amputee to undergo biologically‐realistic, early stance knee flexion. These results indicate that a user‐adaptive control scheme and local mechanical sensing are all that is required for amputees to walk with an increased level of biological realism compared to mechanically passive prosthetic systems.

The purpose of this paper is to examine the factors that influence enterprise resource planning (ERP) effectiveness within the context of emergency service organizations. Drawing on information systems (IS) effectiveness, ERP implementation and job satisfaction literature, the authors posit that user involvement, top management involvement and training satisfaction are the antecedents to perceived job satisfaction, and perceived job satisfaction leads to ERP effectiveness in emergency service organizations.

Survey methodology is used for collecting data for this research, and the PLS-SEM technique is used for analysis.

Results indicate users will be more satisfied with their training if their inputs are taken into account during their training and the top management is actively involved during the training process. Further, if the users perceive that they are adequately trained, they will be more satisfied with their jobs in using ERP, which will also lead to more effective ERP usage in emergency service operations.

The focus of this study is on a single emergency service organization and thus may not be generalizable to other sectors. The authors extend ERP research to the context of emergency service organizations and thus add to the literature on ERP and emergency services. They conceptualize perceived job satisfaction to integrate roles, teamwork, supervisor and their perception regarding their potential to grow in the organization.

The managerial contribution of this research is to identify the motivational aspects and provide practical insights into the effective use of ERP systems for emergency service organizations. From a managerial perspective, the study provides a framework for both IS and emergency service providers/executives to understand and evaluate the factors that help them use ERP effectively in their firms.

This study extends the knowledge of ERP systems. While most of the ERP research focuses on implementation, the authors’ focus is on the effective use of ERP in emergency service organizations. They focus on identifying key factors that are important to using ERP effectively, specifically in emergency service organizations.

Information security is a growing issue that impacts organizations in virtually all industries, and data breaches impact millions of customers and cost organizations millions of dollars. Within the past several years alone, huge data breaches have been experienced by organizations such as Marriot, Equifax, eBay, JP Morgan Chase, Home Depot, Target and Yahoo, the latter of which impacted three billion users. This study aims to examine the utilization of pre-employment screening to identify potential hires that may require enhanced information security training to avoid such costs.

The authors hypothesize that an individual’s work ethic predicts a person’s information security behavior. The authors test this hypothesis using structural equation modeling with bootstrapping techniques.

Data analysis suggests that certain dimensions of work ethic do indeed predict information security posture, and thus, simple pre-employment screening techniques (i.e. questionnaires) can aid in identifying potential security threats.

The findings provide a tool for identifying problematic employee security posture prior to hiring, which may be useful in identifying training needs for new hires.

The findings provide a tool for identifying problematic employee security posture prior to hiring, which may be useful in identifying training needs for new hires.

This study aims to investigate the effect of Shariah-compliant status and Shariah regulation on initial public offering (IPO) underpricing in Pakistan.

Besides the ordinary least square’s method, this study used quantile least squares as a robust approach and stepwise regression for further analysis to investigate the underpricing phenomenon in Pakistan. Data of 84 IPOs listed on Pakistan Stock Exchange from January 2000 to December 2018 were collected to determine the impact of Shariah-compliant status and Shariah regulation on IPO underpricing.

Results of the study show that Shariah-compliant status has a negative relationship but Shariah regulation has a positive relationship with IPO underpricing. Hence, it is contended that Shariah-compliant firms have lower asset volatility and uncertainty than non-Shariah-compliant firms because of less information asymmetry, resulting in lower underpricing. These Shariah-compliant firms provide signals of high-quality IPOs as they must comply with the strict guidelines issued by the Securities Exchange Commission of Pakistan in addition to being considered as amicable by investors. Further, this study suggests that investors are more attracted to Shariah-compliant firms than non-Shariah-compliant ones.

This study’s offers limited consideration of nonfinancial and financial characteristics that could influence the decision of investors to subscribe to IPOs. Besides, future studies could consider the screening benchmarks; for instance, debt and cash may explain the intensity of IPO initial return in Pakistan.

The present work empirically investigated the influence of Shariah-compliant status and Shariah regulation on IPO underpricing in Pakistan’s IPO market, which has been scarcely covered in the existing literature.

This paper aims to examine the mediating role of occupational stress in addressing the missing gap between organisational intelligence (OI) traits and digital government service quality.

By employing multistage cluster sampling, a total of 394 responses from the Malaysian service providers at federal government agencies were obtained. For data analysis, the partial least square structural equation modelling (PLS-SEM) approach with a disjoint two-stage approach was employed to assess the proposed higher-order model. The analysis was carried out to examine how occupational stress mediates the relationship between OI traits at each component level and digital service quality.

Occupational stress mediates the relationship between OI traits at the third-order component level and digital service quality. At the second-order component level, only the employee-oriented OI traits exhibit a significant indirect effect on the digital government service quality. Narrowing down to the first order component level, two OI traits, namely “Alignment and Congruence”, and “Heart” demonstrate significant indirect effects in the mediation analysis.

By incorporating the organisational model of stress (OMS) with public service-dominant logic (PSDL), this paper takes an approach to revitalise the stressors and individual-level performance used in a traditional work setting. Precisely, it examines how digital service quality is influenced by today's high-performing public organisation stressors (OI traits) along with non-technical element (occupational stress). More importantly, digital government service quality was examined from a less emphasised perspective, namely the supply side or service providers’ standpoint in sustaining the digital government service performance.

In today’s fast-paced and interconnected market, companies must adapt to the evolving demands of their customers. Therefore, it is essential to examine the impact of online reviews on potential customers' intent to purchase. This study seeks to identify the characteristics of electronic word-of-mouth (eWOM) that influence a buyer’s intention to purchase goods and services.

We used the snowball sampling method to collect data using a pre-tested survey instrument with a five-point Likert scale. We received 696 usable responses. We conducted assumption tests to ensure that we could use covariance-based structural equation modelling (CB-SEM) for data analysis. The collected data were analysed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to compute the latent variables. We then tested our research hypotheses using CB-SEM.

Eight latent constructs – perceived persuasion, perceived information, image aesthetics, ease_of_experience, eWOM_credibility, eWOM_usefulness and eWOM_adoption – have been identified, which determine the influence of eWOM on purchase intent (PI) for both tangible and experiential products. Though the structural model emerged relatively similar, the constructs had differential impacts on PI for commodities and services. The perceived information quality and source trustworthiness had a greater impact on eWOM credibility in the case of services than in the case of commodities, while image aesthetics played a more crucial role in determining the eWOM credibility for commodities than services. In both cases, credible eWOM was found useful, but a persuasive eWOM influenced its perceived usefulness more in the case of commodities. The likelihood of adopting a useful eWOM and converting it to positive PI is present in the case of both services and commodities, but the impact is much higher in the case of services.

The study has examined the interplay of three theoretical consumer behaviour models: elaboration likelihood model (ELM), stimulus-organism-response model (SOR), and information adoption model (IAM). Thus, it adds to the existing literature on the characteristics of eWOM that influence the PI of online buyers.

This study’s findings demonstrate how eWOM influences consumers' perceptions of the utility of goods and services, impacting their intention to purchase. It also provides valuable insights into marketing and consumer behaviour in the Indian market. Thus, this study assists marketers in adjusting their digital marketing strategies to ensure the effective use of eWOM characteristics to positively influence the PI of the target audience in the Indian market.

This research study examines the relationship between eWOM characteristics and PI for both goods and services sectors. Most existing literature is skewed towards specific service sectors, such as hospitality and health care. A generalised comparative study is what makes this research work unique.

This paper aims to examine the mediating role of occupational stress in addressing the missing link between organisational intelligence (OI) traits and digital government service quality and propose relevant strategies in sustaining the digital government service quality whilst enhancing the psychological well-being of the service providers.

This paper utilises a triangulation design approach to interpret the findings of the study and propose pertinent strategies. Firstly, we examined the mediating role of occupational stress in addressing the link between OI traits, and digital government service quality. Next, we examined the priority factors of OI traits and occupational stress to sustain the quality of digital government services via the Importance-Performance Map Analysis (IPMA). These findings were cross-examined with the code’s percentage generated from participants’ open-ended survey feedback on aspects that requires improvement in sustaining service quality.

In principle, occupational stress mediates the relationship between OI traits at the third-order component level and digital service quality. Analysis at the lower component level shows that the mediation effect of occupational stress is only significant in the presence of employee-oriented OI traits and “Alignment and Congruence”. Accordingly, the IPMA exhibited the importance of “Job engagement”, “Alignment and Congruence” and “Occupational Stress” in sustaining service quality. Conversely, code’s percentage analysis demonstrated the role of other insignificant traits such as “Leadership” and Appetite for Change and Knowledge Deployment’ in ensuring the sustainability of digital service quality.

By integrating the Organisational Model of Stress with Public Service-Dominant Logic, this paper rejuvenates the stressors utilised in a traditional work setup and widens the perspective of individual job performance to organisational level performance, to reflect the context of today’s public service delivery. We triangulated the outcome from mediation analysis, IPMA as well as open-ended feedback analysis and propose prioritisation on the aspects of “Employee-oriented traits”, “Psychological Well-being”, “Alignment and Congruence”, “Leadership” and “Appetite for Change and Knowledge Deployment” aspects for sustaining digital government service quality. Considering the significance of occupational stress in sustaining service quality in both quantitative and qualitative analysis, this paper also takes the approach of proposing a stress intervention program at the individual and organisational levels to manage the psychological well-being of the service providers.

In this chapter we discuss the dynamics of convergence-divergence between organic and non-organic farming systems. We are specifically interested in how and in what ways organic systems emerge into a new system that synthesizes the diverse qualities of competing systems. Or, will these systems continue to diverge because of their path dependencies and contradictory, unresolvable logics? Alternatively, are we confronted with conversion? Following a discussion of the origin of organic agriculture and the IFOAM Principles, we explore differentiation of two agricultural paradigms that was developed more than 20 years ago before the rise of GMOs. This comparison identifies the key features of both systems and a first interpretation on the potential of convergence-divergence. Third, we take a macro-look at agro-food chain that offers insights on the convergence-divergence potential in the context of global, economic, market, political, and societal dynamics. Fourth, we discuss convergence-divergence at the production level comparing the four agricultural systems. Finally, we reflect and assess on the explanatory potential of our study for the future development of organic and non-organic agriculture/farming. We conclude that there is more evidence for conversion than for convergence.

Purpose: Green computing is a way of using the computer resource in an eco-friendly while maintaining and decreasing the harmful environmental impact. Minimising toxic materials and reducing energy usage can also be used to recycle the product.

Need for the Study: The motivation of the study is to use green computing resources to decrease carbon emissions and their adverse effect on the environment.

Methodology: The study uses a qualitative method of collecting resources and data to address the opportunities, challenges, and future trends in green computing for Sustainable Future Technologies. The study focusses on multiple kinds of cloud computing services collected and executed into single remote servers. The service demand processor offers these services to the client per their needs. The simultaneous requests to access the cloud services, processing and expertly managing these requests by the processors are discussed and analysed.

Findings: The findings suggest that green computing is an upcoming and most promising area. The number of resources employed for green computing can be beneficial for lowering E-waste so that computing can be environmentally friendly and self-sustainable.

Practical Implications: Green computing applies across all industries and service sectors like healthcare, entertainment, tourism, and education. The convergence of technologies like Cloud Computing, AI, and Internet of Things (IoT) is greatly impacting Green Supply Chain Management (GSCM) market.