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The purpose of the paper is to design a nonlinear dynamic inversion (NDI) based robust fault-tolerant control (FTC) for aircraft longitudinal dynamics subject to system nonlinearities, aerodynamic parametric variations, external wind disturbances and fault/failure in actuator.

An uncertainty and disturbance estimator (UDE) technique is used to provide estimate of total disturbance enabling its rejection and thereby achieving robustness to the proposed NDI controller. As needed in the NDI design, the successive derivatives of the output are obtained through an UDE robustified observer making the design implementable. Further, a control allocation scheme consigns control command from primary actuator to the secondary one in the event of fault/failure in the primary actuator.

The robustness is achieved against the perturbations mentioned above in the presence of actuator fault/failure.

Lyapunov analysis proves practical stability of the controller–observer structure. The efficacy and superiority of the proposed design has been demonstrated through Monte-Carlo simulation.

Unlike in many FTC designs, robustness is provided against system nonlinearities, aerodynamic parametric variations, external wind disturbances and sinusoidal input disturbance using a single control law which caters for fault-free, as well as faulty actuator scenario.

The requirement of robust cooperative control is essential to achieve consensus between unmanned aerial vehicles (UAVs) operating in swarm formation. Often the performance of these swarm formations is affected by wind gust disturbances. This study proposes an effective robust consensus protocol, which will ensure the UAVs in swam formation to collectively meet the desired objective in real-time scenario.

In this work, the swarm of UAVs are modeled as multiagent systems by using the concepts of algebraic graph theory. To address the challenges of a complex and dynamic environment, an adaptive sliding mode control (SMC)-based consensus protocol is proposed. The closed loop stability analysis is established through Lyapunov theory.

The efficacy of the discussed robust consensus controller is analyzed through numerical simulations. Further, the quantitative analysis using Monte-Carlo simulations validates performance of the proposed robust consensus protocol. The presented consensus protocol can be easily implementable as robust flight controller for swarm of UAVs. Also, as the consensus theory is based on the algebraic graph theory, the proposed design is scalable for a large number of UAVs in swarm formation.

The proposed adaptive SMC achieves robust consensus of longitudinal dynamics states between all the UAVs by mitigating the effects of wind gust disturbances. Also, the adaptive SMC offers chattering-free control efforts.

Purpose: The goal of this study is to delve into the causes behind the Fintech sector’s rise in various areas and its prospects. Fintech is rapidly expanding because of government legislation, multiple schemes, consumer expectations, a cashless economy, digitisation, globalisation, innovation, and other drivers.

Need for the Study: Fintech firms are forming alliances with traditional financial organisations to stay afloat and compete. India is becoming a superpower regarding e-startups, especially unicorns. Many startups are undergoing initial public offerings (IPOs). Fintech is an emerging space in India, spreading its wings rapidly in every sector.

Methodology: This work is based on a literature review. It utilises secondary data from numerous research publications, magazines, newspapers, published reports, relevant websites, Forbes magazine articles, stories from The Economic Times, the RBI Portal, and information from StartupIndia, Assocham, and Pwc, among others, to develop a conceptual framework showing the growth drivers of Fintech.

Findings: The whole world has been affected severely due to COVID-19. Crisis always comes with some opportunity, and it is up to us how to turn the calamities into opportunities that further turn into innovation that has the power to lead the world. Fintech is that fruit that had been born normally but grew abnormally (tremendous growth) during the pandemic. Also, the roots are so deeper that they will flourish more and more. It has been found that the emergence of a cashless economy, ease of internet connectivity, etc., are the major factors that paved the way for growth for Fintech in India.

Practical Implications: This study contains the conceptual framework which can guide the stakeholders, policymakers, management teams, field experts, etc., in knowing about their area expertise and looking for improvement, if any.

Originality: There are many papers on the relationship between Fintech and financial inclusion, but this is the first study that builds the conceptual framework for the growth drivers of Fintech.

The scope of this study is to explore and summarize the pool of dimensions, models and measurement techniques of service quality used in healthcare services and to propose a comprehensive conceptual model for practitioners and researchers.

This research employs a comprehensive review of available literature by using multiple keywords on different electronic repositories using the recommendations of the PRISMA approach for the selection of articles. A critical analysis of available studies helped in compiling a list of core service quality dimensions in healthcare services.

This paper presents a comprehensive account of different dimensions and their measurement items used by various researchers to assess service quality in healthcare systems. Most of the researchers have used SERVQUAL model either in its original or modified form while the others have proposed and used totally different dimensions to assess the service quality in healthcare. Many dimensions are just an existing dimension of SERVQUAL that has undergone a name change while others are completely new. The dimensions used by many researchers have items drawn from more than one dimension of SERVQUAL model. The availability of so many dimensions and models adds to the confusion that researchers and practicing managers experience when determining the appropriate model to be used in their work. To mitigate this confusion, there is a need to develop a comprehensive model; the current work is an attempt to meet this need. Through our analysis, we identify four major service quality dimensions: clinical quality, infrastructural quality, relationship and managerial quality and propose a model named CIRMQUAL.

After exploring all available models in the domain of healthcare, this research presents the best possible areas to enhance the quality of healthcare services. It also enhances the research insights for academicians and working professionals by developing and proposing a comprehensive model for measuring healthcare service quality. The proposed model covers almost all of the service quality dimensions used by other researchers and will make the choice of dimensions/model easy for the future researchers/practitioners interested in measuring and improving the quality of services offered by their healthcare units. Such a comprehensive model has not been developed by any researcher thus far.

Theory of Constraints (TOC), though a well-established process improvement methodology in manufacturing, is still a novel philosophy for healthcare and an exhaustive review of literature is needed to summarize the key findings of various researchers. Such a review can provide a direction to the researchers and academicians interested in exploring the application of TOC in the healthcare sector. This paper aims to review the existing literature of TOC tools and techniques applied to the healthcare environment, and to investigate motivating factors, benefits and key gaps for identifying directions for future research in the domain of healthcare.

In this paper, different electronic repositories were searched using multiple keywords. The current study identified 36 articles published between January 1999 to mid-2021 to conceptualize and summarize the research questions used in the study. Descriptive analysis along with pictorial representations have been used for better visualization of work.

This paper presents a thorough literature review of TOC in healthcare and identifies the evolution, current trends, tools used, nature of services chosen for application and research gaps and recommends future direction for research. A variety of motivating factors and benefits of TOC in healthcare are identified. Another key finding of this study is that almost all implementations listed in literature reported positive outcomes and substantial improvements in the performance of the healthcare unit chosen for study.

This paper provides valuable insight to researchers, practitioners and policymakers on the potential of TOC to improve quality of services, flow of patients, revenues, process efficiency and cost reduction in different health care settings. A number of findings and suggestions compiled in the paper from literature study can be used for diagnosing, learning and making substantial changes in healthcare. The methodologies used by different researchers were analysed and combined to propose a generic step by step procedure to apply TOC. This methodology will guide the practising managers about the appropriate tools of TOC for their specific need.

Good health is always the first desire of all men and women around the globe. The global aim of healthcare is to quickly cure more patients and ensure healthier population both today and in future. This article will work as a foundation for future applications of TOC in healthcare and guide upcoming applications in the booming healthcare sector. The paper will help the healthcare managers in serving a greater number of patients with limited available resources.

This paper provides original collaborative work compiled by the authors. Since no comprehensive systematic review of TOC in healthcare has been reported earlier, this study would be a valuable asset for researchers in this field. A model has been presented that links various benefits with one another and clarifies the need to focus on process improvement which naturally results in these benefits. Similarly, a model has been presented to guide the users in implementation of TOC in healthcare.

The objective of this work is twofold: firstly, to develop a model for assessing healthcare service quality (HSQ), and secondly, to evaluate the effectiveness of machine learning algorithms in predicting the quality of healthcare services.

In this study, a comprehensive literature review has been performed to identify key quality dimensions in the healthcare services domain. Delphi’s method has been used to confirm the criticality of these dimensions based on experts’ opinions and proposed a novel CIRMQUAL model. Factor analysis techniques have been used to further validate the CIRMQUAL model. Using the data collected through a questionnaire survey, a number of machine learning models have been developed to predict the customer satisfaction level based on the service quality (SQ) performance of a healthcare unit on different dimensions of the CIRMQUAL model.

The study developed a CIRMQUAL model with 14 dimensions (quality of care, safety and security, skill and conduct, staff attitude, tangibles, quality of the atmosphere, patient rights, follow-up, communication, cost of treatment, availability of resources, accessibility, waiting time and services), and these dimensions have been clubbed into four major dimensions, i.e. clinical quality, infrastructural quality, relationship and managerial quality. Furthermore, the application of machine learning algorithms has demonstrated significant accuracy in predicting SQ, highlighting its ability to improve healthcare services and the satisfaction level of patients.

Managers of healthcare units work hard to identify and address the pain points of the patients and improve the working of the healthcare units being managed by them. The availability of many scales with numerous dimensions adds to their confusion in selecting a suitable scale. The current work addresses this confusion and provides four clear areas for assessing the quality of healthcare units. By using this scale, managers can assess the quality of services provided by them, identify the dimensions of low performance, plan and take suitable corrective actions to improve the performance of their healthcare units.

A comprehensive SQ model, i.e. CIRMQUAL has been proposed as a new scale to assess SQ in healthcare units. The model has been developed after analyzing the dimensions used by many researchers available in the literature. This model can be used by future researchers to assess the SQ in healthcare units. Moreover, an attempt has been made to use artificial intelligence-based techniques for predicting customer satisfaction. Such attempts are in the initial stage for healthcare sector. Future researchers can take this concept forward and test the applicability of different machine learning techniques in different functional areas of healthcare.

Good health is of utmost importance for all human beings. In spite of the expenditure of substantial time and efforts by various stakeholders, the service delivery doesn’t match the expectations of patients. Many times, the service providers are not aware of this dissatisfaction and specific aspects of service delivery that need to be improved to reduce dissatisfaction. The model proposed will help the service providers in this regard and the service providers will be able to take focused steps. Such initiatives will definitely improve patient’s satisfaction and their social well-being.

This work is unique because it uses a novel technique to redefine the quality of services in healthcare by using a dual methodology. The research presents a model that includes various factors and it is specially developed to evaluate the quality of services in healthcare settings. This study advances the area’s progress by implementing computational tools for accurate evaluation of HSQ. The healthcare decision-makers may use this novel perspective to evaluate and enhance the quality of service.

In early 2013, Mr. Deepak Kumar, Chairman and Group CEO of MakeMyTrip1 (MMT), summoned a meeting to discuss about redesigning the MMT Homepage2. It was a three-hour meeting at the Hindustan Conference Room at the company's head office in Gurgaon, India. Theis meeting was attended by key members of the homepage website redesign team comprising the CBO, Analytics head, User Experience (UX) head, Product head and the Tech head (CTO). As a pre-read for the meeting, Ajay Singh, Product Head, shared his findings3 that could help in defining the issues faced by visitors to the homepage of MMT.

In mid-2013 Deepak Kumar, Chairman and Group CEO of MakeMyTrip (MMT), was headed to the Hindustan conference room of the company's head office in Gurgaon, India, for deciding the new homepage design. A day earlier, Ajay, Product Head, had shared the consolidated results of the trials of different options (see Exhibit 1 for the results of testing the options) with the homepage website redesign team, responsible for the entire project. The team consisted of the head of business (CBO), the Analytics Head, the user experience (UX)head, the Product Head and the Tech Head (CTO).

Looking at the results, Deepak Kumar reflected that there were a lot of surprises in how the different options had performed. While the tracking tools in online businesses had a huge advantage over traditional businesses in that almost every customer interaction could be measured, there was still a lot of reading between the numbers that had to be done. Deepak was looking forward to a fruitful discussion to evaluate the options and finalise the new homepage design to be rolled out. As he opened the door to the conference room, he heard an excited chatter.

One week since the first meeting, Mr. Deepak Kumar, Chairman and Group CEO of MakeMyTrip (MMT), called a second meeting of the homepage website redesign team for redesigning the Home Page (see Exhibit 1 for the current Home Page)¹. This team comprised of the CBO, Analytics Head, User Experience (UX) Head, Product Head and the Tech Head (CTO). The second meeting was called to discuss and finalise the options of the Home Page design to be tested, the criteria to be used for choosing the best option, and the testing methodology.

The purpose of this paper is to examine the indirect effects of nutritional knowledge and attitude toward food label use on food label use through self-efficacy and trust, as well as whether gender moderates this relationship.

A sample of Indian adults with multiple chronic conditions was surveyed about their nutritional knowledge, attitude, self-efficacy and use of food labels. Hypotheses were tested using Hayes’s (2013) PROCESS macro for SPSS.

The results show that nutritional knowledge and attitude toward food label use positively predict food label use through self-efficacy and trust. However, these mediation effects are moderated by gender such that the indirect relationship is stronger among men than women.

Food marketers and government agencies engaged in nutrition education campaigns should aim to increase patients’ confidence in comprehending food label information.

Since food labels can be a valuable tool to help patients with chronic diseases to make informed decisions about their diet and lifestyle, regulators may consider mandating nutritional labels on foods to help them improve their food or dietary choices.

This study uniquely applies Fisher and Fisher’s (1992) information–motivation–behavioral skills model as a theoretical framework to examine the influence of nutrition knowledge and attitude toward food label use on food label usage of Indian patients with multiple chronic diseases.