Search results

The performance of thermal comfort utilising machine learning and its acceptability by students and other users at the Professor Sir Edouard Lim Fat Engineering Tower at the University of Mauritius are evaluated in this study. Students and building occupants were asked to fill out surveys on-site as data was gathered from sensors throughout the structure. The Thermal Sensation Vote (TSV) and other important data were collected through the surveys, including the effect of wind on thermal comfort. An adaptive model incorporating solar and wind effects was evaluated using multiple linear regression techniques and RStudio. Three models were used to evaluate thermal comfort, including the adaptive one. Numerous models were compared and evaluated in order to select the best one. It was found that the adaptive model (Model 1) was deemed to be the best model for its application. It was also found that Fanger's PMV/PPD (Model 2) was a very good approach to determining thermal comfort. Through thorough analysis, it was concluded that the range of air temperature and wind speed for thermal comfort was 25.830°C–28.0°C and 0.26 m/s to 0.42 m/s, respectively. In order for cities to remain secure, resilient and sustainable, it will be important to manage thermal comfort and reduce populations' exposure to heat stress (SDG 11). The achievement of income and productivity goals will be hampered if measures to protect populations from heat stress are not taken (SDG 8). Thermal regulation is also necessary for the provision of numerous health services (SDG 3).

Tourist guides undertake many versatile roles as a requirement of their profession. The realisation of these roles also affects the performance of the guide. Findings obtained from empirical evidence on the effects of the tour guide's performance on memorable tourism experiences and the intention to revisit the Cappadocia region shed light on the importance of these elements on each other. Accordingly, the primary purposes of this research are to measure the effect of tourist guides' performance on memorable tourism experiences and the impact of memorable tourism experiences on revisit intention (RVI). For these purposes, the survey technique obtained data from 569 domestic and foreign tourists who participated in guided tours in the Cappadocia region. According to the results of the research, it has been observed that the performance of the tourist guide influences the memorable tourism experience, and the memorable tourism experience affects RVI. In light of the results, suggestions to tourism stakeholders and researchers are listed.

Chatbot technology is growing swiftly across the banking and finance industry. The study aims to explore the influence of Task-Technology Fit (TTF), system suitability, perceived usefulness, social influence and satisfaction on respondents’ continuance intention among the chatbot-users. A total of 250 responses were collected using a structured questionnaire via social media across India. The measurement model was proposed based on the system usability (SUS) and TTF model with other constructs, and the hypothesis was tested using a structural equation model. The findings of the study highlighted and confirmed the association among five constructs: TTF, SUS, perceived usefulness, social influence, on satisfaction and continuance intention in the context of chatbots usage in banking.

Human evolution has witnessed the highest level of metamorphism overages. COVID-19 alarmed us when we were unceasingly running toward monetary benefits and money, the significance of health. That initiated the thought process of improvising the health and healthcare infrastructure, leading to the birth of the health cooperative as a reform. During the state of COVID services, operations of the hospital were unreachable due to the unavailability of doctors, facilities, hiked charges, and lack of insurance coverage made people disbelieve in the system. Many social activists propose the idea of healthcare cooperatives to foster healthcare needs. The study guides us to understand the roles of healthcare cooperatives like the establishment of service facilities, modernisation of existing facilities, expansion to various topographical locations, and healthcare education to the general public, repair, and renovate the instrumentation in the medical field. The study also finds the ways and means of self-sustainability of health cooperatives with dependency on government financial support during the initial take-off. The benefits of cooperatives contributing to the NDHM and supporting the development of healthcare infrastructure in rural areas. The study enables us to find the factors that healthcare cooperatives need to consider for providing the right benefit to the citizens and factors for the self-sustained and self-resilient mode of seamless operation. The study has two different data collecting instruments, one to collect the data from the public and other from healthcare professionals. The result of the study reveals the mechanisms through which healthcare cooperatives can provide well-structured healthcare support to the nation.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.