Remarkable Growth In Recent Years Research Articles

Serving the unserved: a market segmentation, price discrimination based customer-centeric approach to home loans in india

The housing finance sector in India has witnessed remarkable growth in recent years, yet a significant portion of the population remains excluded from accessing formal home loan facilities. This master thesis report aims to address this gap by proposing a customer-centric approach to home loans, utilizing market segmentation and price discrimination strategies to serve the unserved segment of the market effectively. The study begins by identifying the need to bridge the gap in home loan accessibility and explores the reasons behind the exclusion of certain demographic groups. Through a comprehensive literature review, the report examines existing research on home loans, market segmentation, price discrimination, and customer-centric approaches in the financial services industry. The research methodology employed in this study utilizes a mixed-methods approach, combining qualitative and quantitative techniques to gather insights into the preferences, challenges, and perceptions of potential home loan borrowers. A carefully designed sampling plan ensures the representativeness and reliability of the data collected. Data analysis reveals patterns and trends within the home loan market, shedding light on the effectiveness of different segmentation and pricing strategies in reaching the unserved population. The questionnaire used for data collection is provided in the report, along with a discussion of the limitations, challenges, and barriers encountered during the research process. In conclusion, the report summarizes key findings and recommends strategies for policymakers, financial institutions, and other stakeholders to enhance inclusivity and efficiency in the home loan sector. By adopting a customer-centric approach and leveraging market segmentation and price discrimination techniques, the goal of serving the unserved can be achieved, contributing to greater financial inclusion and societal welfare.

Scalable business models for startups in renewable energy: Strategies for using GIS technology to enhance SME scaling

The renewable energy sector has witnessed remarkable growth in recent years, driven by global efforts to mitigate climate change and transition towards sustainable energy sources. Startups play a crucial role in this transition, often pioneering innovative solutions and technologies. However, for these startups to thrive and contribute significantly to the renewable energy landscape, scalable business models are essential. This abstract explores strategies for leveraging Geographic Information System (GIS) technology to enhance scalability in small and medium-sized enterprise (SME) startups operating in the renewable energy sector. GIS technology offers a powerful framework for analyzing and visualizing spatial data, providing valuable insights into site selection, resource assessment, and infrastructure planning. By integrating GIS into their business models, startups can optimize operations, reduce costs, and accelerate growth. This review discusses various strategies for utilizing GIS technology, including market analysis, site suitability assessment, supply chain optimization, and infrastructure planning. Drawing on case studies and industry examples, this review highlights the effectiveness of GIS in enhancing scalability for renewable energy startups. It also addresses the challenges and limitations associated with GIS implementation, such as technical complexities, data accessibility, and cost considerations. Furthermore, this review discusses emerging trends in GIS technology and their potential impact on the renewable energy sector, offering insights into future opportunities for startups. In conclusion, this review emphasizes the importance of GIS technology in facilitating scalable business models for renewable energy startups. By harnessing the power of GIS, SMEs can unlock new growth opportunities, drive innovation, and contribute significantly to the transition towards a sustainable energy future. Keywords: Scalable Business Models, Startups, Renewable Energy, GIS Technology, SME Scaling.

VTuber for Streamers: Exploring the Role of Social Presence in the Visual Representation of Streamers

ABSTRACT Livestreaming has experienced remarkable growth in recent years, marked notably by the rise of VTubers. VTubers are face-tracking avatars capable of replacing a streamer’s actual face. In order to delve deeper into this trend, this study examines how the visual representation of a streamer affects audience perception. An online experiment was conducted, involving three-group comparisons within a between-subjects design, with 413 undergraduate students in the U.S. The primary findings reveal that, in comparison to utilizing VTubers, both displaying a streamer’s real face and opting not to show a face enhance the social presence of the streamer, consequently leading to more favorable perceptions of the streamer. This study underscores the mediating role of social presence in shaping audience perceptions of streamers and underscores the necessity of exploring potential non-linear relationships between a streamer’s visual representation and social presence.

The application of lasers in vital pulp therapy: clinical and radiographic outcomes

The main purpose of vital pulp therapy (VPT) is to preserve the integrity and function of the pulp. A wide variety of materials and techniques have been proposed to improve treatment outcomes, and among them, the utilization of lasers has gained significant attention. The application of lasers in different stages of VPT has witnessed remarkable growth in recent years, surpassing previous approaches.This study aimed to review the applications of lasers in different steps of VPT and evaluate associated clinical and radiographic outcomes. An electronic search using Scopus, MEDLINE, Web of Science and Google Scholar databases from 2000 to 2023 was carried out by two independent researchers. The focus was on human studies that examined the clinical and/or radiographic effects of different laser types in VPT. A total of 4243 studies were included in this narrative review article. Based on the compiled data, it can be concluded that although current literature suggests laser may be proposed as an adjunct modality for some procedural steps in VPT, more research with standardized methodologies and criteria is needed to obtain more reliable and conclusive results.

Using science as a differentiator in a crowded digital mental health market.

The digital mental health industry has seen remarkable growth in recent years. However, within this crowded landscape, many companies overlook a critical factor for gaining a competitive edge: the integration of science. In this context, "science" refers to the strategic collection and analysis of information (i.e., data) at digital mental health companies, aimed at guiding business decisions and achieving business objectives. This paper demonstrates that science is integral, yet underutilized in the digital mental health industry, with common misconceptions about its role. When science is integrated within a company, it enables them to (1) innovate, (2) understand customers, (3) make informed decisions, and (4) drive revenue. Digital mental health companies recognizing the multifaceted value of science may be better equipped for sustainable growth and success amid the crowded digital health market.

Comprehensive assessment of recent major chemical accidents in China and path to sustainable solutions

China’s chemical manufacturing sector has experienced remarkable growth in recent years, making it a global leader in chemical production. However, this rapid expansion has led to an increase in chemical accidents, particularly major chemical accidents (MCAs), resulting in significant casualties and property loss. This study focuses on MCAs that occurred in China between 2017 and 2022, using mathematical statistics. It examines various aspects of accidents, including the annual number of accidents and casualties, distribution across months, types of accidents, accident stages, direct causes of accidents, and geographical distribution of accidents. Furthermore, this study investigated the potential of using novel digital tools to enhance the safety of chemical production. By analysing the data and identifying trends, this study aims to contribute to the prevention of large-scale chemical disasters. Furthermore, it explores the implementation of smart management of chemical plants, utilising the Internet of Things (IoT) for example, to ensure the sustainable advancement of the chemical industry.

Sustainable packaging materials for fermented probiotic dairy or non-dairy food and beverage products: challenges and innovations

<abstract> <p>The food and beverage packaging industry has experienced remarkable growth in recent years. Particularly the requirement for appropriate packaging materials used for the sale of fermented products is boosted due to the rising acceptance of economical functional foods available to consumers on the shelves of their local supermarkets. The most popular nutraceutical foods with increased sales include natural yogurts, probiotic-rich milk, kefir, and other fermented food and beverage products. These items have mainly been produced from dairy-based or non-dairy raw materials to provide several product options for most consumers, including vegan and lactose-intolerant populations. Therefore, there is a need for an evaluation of the potential developments and prospects that characterize the growth of the food packaging industry in the global market. The article is based on a review of information from published research, encompassing current trends, emerging technologies, challenges, innovations, and sustainability initiatives for food industry packaging.</p> </abstract>

INVESTING IN CRYPTOCURRENCY AS AN ALTERNATIVE WAY OF FINANCIAL INVESTMENTS

In the realm of finance, cryptocurrency has emerged as a captivating alternative to traditional investment avenues, such as stocks, bonds, and real estate. Its decentralized nature, unfettered by government or financial institution control, presents a unique proposition in the world of wealth management. The allure of cryptocurrency lies in its potential for substantial returns. Its value has experienced remarkable growth in recent years, offering investors the prospect of significant financial gains. Additionally, cryptocurrency serves as a valuable tool for portfolio diversification, as its performance is often uncorrelated with traditional asset classes. Moreover, cryptocurrency boasts portability and accessibility, making it a convenient and inclusive investment option. Its digital nature allows for seamless storage and transferability, while its global reach enables anyone with an internet connection to participate in the cryptocurrency ecosystem. However, alongside these potential benefits, cryptocurrency also harbors inherent risks. Its volatility poses a challenge, as its value can fluctuate dramatically in a short period. Regulatory uncertainty looms, as governments worldwide grapple with the implications of cryptocurrency and may impose restrictive measures. Furthermore, security concerns persist, as cryptocurrency exchanges and wallets have fallen prey to cyberattacks, jeopardizing investors' assets. In light of these considerations, investing in cryptocurrency demands a thoughtful approach. Investors must carefully assess their risk tolerance and align their investment goals with the inherent risks associated with cryptocurrency. Thorough research and a well-diversified portfolio are crucial for navigating the complexities of this emerging asset class. The purpose of the article is to analyze the profitability and safety of investments in cryptocurrency and study the different methods associated with it.

Instant testing and non-contact diagnosis for photovoltaic cells using K-means clustering and associated hyperspectral imaging

Renewable energy, particularly solar energy, has experienced remarkable growth in recent years. However, the integrity of solar photovoltaic (PV) cells can degrade over time, necessitating non-destructive testing and evaluation (NDT-NDE) for quality control during production and in-service inspection. Hyperspectral (HS) imaging has emerged as a promising technique for defect identification in PV cells based on their spectral signatures. This study utilizes a HS imager to establish a diffuse reflectance spectra signature for two groups of PV cells: working and non-working. A non-contact photoluminescence imaging-based methodology is employed, using a halogen lamp as an illumination source to replicate sunlight. Our findings reveal that non-working PV regions can be differentiated from working regions within the 400–600 nm wavelength range, with an optimal candidate peak frequency of 450 nm. To accurately group active PV regions in the constructed HS images at 450 nm, we employ an image processing strategy that combines K-means clustering (K-mc) with contour delineation. Specifically, K-mc with K = 8 is used to efficiently and precisely group active PV regions. We demonstrate the effectiveness of this proposed approach and compare it with traditional infrared (IR) imaging techniques. This imaging clustering approach can be implemented using a conventional camera and a 450 nm wavelength filter for NDT-NDE on exterior-mounted PV panels. Overall, the proposed HS imaging technique, coupled with K-mc, offers a rapid and effective means of identifying defects in PV cells, outperforming conventional IR imaging techniques. This advancement contributes to increased efficiency and extended lifespan of solar PV panels.

Diabetes Detection Models in Mexican Patients by Combining Machine Learning Algorithms and Feature Selection Techniques for Clinical and Paraclinical Attributes: A Comparative Evaluation.

The development of medical diagnostic models to support healthcare professionals has witnessed remarkable growth in recent years. Among the prevalent health conditions affecting the global population, diabetes stands out as a significant concern. In the domain of diabetes diagnosis, machine learning algorithms have been widely explored for generating disease detection models, leveraging diverse datasets primarily derived from clinical studies. The performance of these models heavily relies on the selection of the classifier algorithm and the quality of the dataset. Therefore, optimizing the input data by selecting relevant features becomes essential for accurate classification. This research presents a comprehensive investigation into diabetes detection models by integrating two feature selection techniques: the Akaike information criterion and genetic algorithms. These techniques are combined with six prominent classifier algorithms, including support vector machine, random forest, k-nearest neighbor, gradient boosting, extra trees, and naive Bayes. By leveraging clinical and paraclinical features, the generated models are evaluated and compared to existing approaches. The results demonstrate superior performance, surpassing accuracies of 94%. Furthermore, the use of feature selection techniques allows for working with a reduced dataset. The significance of feature selection is underscored in this study, showcasing its pivotal role in enhancing the performance of diabetes detection models. By judiciously selecting relevant features, this approach contributes to the advancement of medical diagnostic capabilities and empowers healthcare professionals in making informed decisions regarding diabetes diagnosis and treatment.

TRACKS AND TRAILS OF ED-TECH FIRMS IN INDIA

The Indian educational technology (Edtech) industry has been experiencing remarkable growth in recent years, driven by a range of factors, including increased demand, investor interest, and mergers and acquisitions. The COVID-19 pandemic has also played a significant role in accelerating the growth of the industry. With the closure of schools and universities during lockdowns, there was a surge in demand for online education solutions. In India, the growth rate of edtech firms decreased during the year 2022. An analysis of customer reviews from 2020 to 2022 are used in this article to determine why edtech firms succeed and fail.

Creation, Analysis and Evaluation of AnnoMI, a Dataset of Expert-Annotated Counselling Dialogues

Research on the analysis of counselling conversations through natural language processing methods has seen remarkable growth in recent years. However, the potential of this field is still greatly limited by the lack of access to publicly available therapy dialogues, especially those with expert annotations, but it has been alleviated thanks to the recent release of AnnoMI, the first publicly and freely available conversation dataset of 133 faithfully transcribed and expert-annotated demonstrations of high- and low-quality motivational interviewing (MI)—an effective therapy strategy that evokes client motivation for positive change. In this work, we introduce new expert-annotated utterance attributes to AnnoMI and describe the entire data collection process in more detail, including dialogue source selection, transcription, annotation, and post-processing. Based on the expert annotations on key MI aspects, we carry out thorough analyses of AnnoMI with respect to counselling-related properties on the utterance, conversation, and corpus levels. Furthermore, we introduce utterance-level prediction tasks with potential real-world impacts and build baseline models. Finally, we examine the performance of the models on dialogues of different topics and probe the generalisability of the models to unseen topics.

Determining the optimal release time of movies: A study of movie and market characteristics

The over-the-top (OTT) industry has witnessed remarkable growth in recent years with a sharp increase in the number of subscribers, leading to increased competition among OTT platforms to acquire movie rights. Consequently, the gap between the theatrical and OTT releases has been diminishing over the last few years. An early release of a movie on an OTT platform fetches a higher distribution fee for a movie distributor (MD), however, it reduces the MD’s revenue from the theatrical release. Therefore, it becomes critical for the MD to determine the optimal release time and distribution fee combination. In this paper, we analytically solve the MD’s decision problem and provide a detailed analysis of how the optimal release time varies with changes in platform characteristics such as the proportion of ad revenue and the platform’s risk profile, movie characteristics such as success factor and suitability for OTT, and market characteristics such as broadband penetration, piracy rate and customers’ preferences for viewing channels. We compare our results with the actual release times of 243 movies released during 2015–2022. We find that the optimal release time increases with ad revenue proportion, broadband penetration, and piracy rate, whereas the optimal fee reduces non-linearly with release time and depends on OTT’s risk profile. Our findings also indicate that the optimal release time reduces for movies that do not provide any additional utility for theater goers, and as customers’ preference towards OTT increases. Our work provides much-needed guidelines for professionals dealing with movie releases on OTTs.

Distribution network redesign under flexible conditions for short-term location planning

E-commerce has experienced a remarkable growth in recent years. This trend is gradually driving retailers to shift from typical warehouse rental contracts with rigid conditions and long-term commitments to flexible alternatives that provide storage space on demand. This strategy gives retailers the ability to respond dynamically to variations in demand, thereby improving customer service. In this paper, we address this trend by considering a two-echelon, multi-commodity distribution network operated by a retailer and whose configuration can be changed over a multi-period planning horizon. Location decisions concern the intermediate facilities and are framed by flexible and scalable conditions. Accordingly, the retailer needs to decide which company-owned facilities should be retained, and where, when and for how long new facilities should be leased from a set of potential sites with given capacities. In this setting, a facility can be leased at the same location for several non-consecutive periods. In addition to location decisions, also procurement, inventory, and distribution decisions need to be made to satisfy customer demand at minimum total cost. We develop a mixed-integer linear programming formulation for this problem and propose various families of additional inequalities that prove to be very useful to find high-quality solutions. To measure the impact of the new business model, we also consider alternative approaches with limited flexibility and scalability that are frequently encountered in practice. Our computational study gives useful insights on the trade-offs achieved by each of the different approaches with respect to total cost, network redesign decisions, and various logistics functions.

Mechanical Performance of 3D-Printed Biocompatible Polycarbonate for Biomechanical Applications.

Additive manufacturing has experienced remarkable growth in recent years due to the customisation, precision, and cost savings compared to conventional manufacturing techniques. In parallel, materials with great potential have been developed, such as PC-ISO polycarbonate, which has biocompatibility certifications for use in the biomedical industry. However, many of these synthetic materials are not capable of meeting the mechanical stresses to which the biological structure of the human body is naturally subjected. In this study, an exhaustive characterisation of the PC-ISO was carried out, including an investigation on the influence of the printing parameters by fused filament fabrication on its mechanical behaviour. It was found that the effect of the combination of the printing parameters does not have a notable impact on the mass, cost, and manufacturing time of the specimens; however, it is relevant when determining the tensile, bending, shear, impact, and fatigue strengths. The best combinations for its application in biomechanics are proposed, and the need to combine PC-ISO with other materials to achieve the necessary strengths for functioning as a bone scaffold is demonstrated.

Performance evaluation of PV penetration at different locations in a LV distribution network connected with an off-load tap changing transformer

<span>Solar photovoltaic (PV) power generation has shown a worldwide remarkable growth in recent years. In order to achieve the increasing energy demand, a large number of residential PV units are connected to the low voltage (LV) distribution networks. However, high integration of solar PV could cause negative impacts on distribution grids leading to violations of limits and standards. The voltage rise has been recognized as one of the major implications of increased PV integration, which could significantly restrict the capacity of the distribution network to support higher PV penetration levels. This study addresses the performance of the off-load tap changing transformer under high solar PV penetration and a detailed analysis has been carried out to examine the maximum allowable PV penetration at discrete tap positions of the transformer. The maximum PV penetration has been determined by ensuring that all nodal voltages adhere to grid voltage statutory limits. The simulation results demonstrate that the first two tap positions could be adopted to control the grid voltage under higher PV penetrations thus facilitating further PV influx into the existing network.</span>

Cycloaddition of Strained Cyclic Alkenes and Ortho-Quinones: A Distortion/Interaction Analysis.

The chemistry of strained unsaturated cyclic compounds has experienced remarkable growth in recent years via the development of metal–free click reactions. Among these reactions, the cycloaddition of cyclopropenes and their analogues to ortho-quinones has been established as a highly promising click reaction. The present work investigates the mechanism involved in the cycloaddition of strained dienes to ortho-quinones and structural factors that would influence this reaction. For this purpose, we use B97D density functional theory calculations throughout, and for relevant cases, we use spin component–scaled MP2 calculations and single–point domain-based local pair natural orbital coupled cluster (DLPNO-CCSD(T)) calculations. The outcomes are analyzed in detail using the distortion/interaction model, and suggestions for future experimental work are made.

Exploring the factors that drive Use of Self-Service Technologies in Air-travel in an African country

Self-service technologies (SSTs) refer to technological interfaces that enable customers to produce a service independent of direct employee involvement. The use of SSTs in air-travel in African countries has seen remarkable growth in recent years, yet little is known about the factors that account for this. Using the unified theory of acceptance and use of technology as a theoretical lens, this study examines the factors that drive both behavioural intention to use and actual usage behaviour of three SSTs used in air-travel (self-booking, self-ticketing and self-check-in) in an African country. Data was obtained from 250 international air travellers in Ghana. Findings of the study revealed that social influence, facilitating conditions, and effort expectancy significantly impact behavioural intentions towards the use of air-travel SSTs. Also, behavioural intentions, user satisfaction and facilitating conditions were found to significantly impact SST usage behaviour. The study concludes by discussing the implications for research and practice.

Attractiveness of Foreign Direct Investment and Export Performance in Morocco: The Case of the Automotive Industry

<p><em>Thanks to its geopolitical position and its know-how, Morocco has established itself as a leader in the automotive sector on the continent. The Moroccan automotive industry has experienced remarkable growth in recent years. A dazzling progression that is not about to stop. Thus, Morocco has become the 28th largest car exporter in the world, first in North Africa and second on the African continent.</em></p><p><em>Its performance is particularly remarkable in terms of exports and job creation, for which the sector is growing at a double-digit rate with more than 80.000 people in 2016 compared to 39.131 in 2008. Cabling is the leading employer segment with nearly 69.5% in 2016, followed by seats and seat covers (9%) and automotive manufacturing (8.3%).</em></p><p><em>And with MAD58.8 billion in export sales in 2017, compared with MAD12.7 billion in 2007, the automotive sector is the leading export sector. This performance contributed to the overall evolution of Moroccan exports by nearly 36.7%. In 2017, the automotive sector became the country’s leading export sector for the fourth consecutive year. Its share rose to 23.6% in 2017 (5.5% of GDP) from 10.1% in 2007 (2.1% of GDP).</em></p><p><em>An analysis of Moroccan export markets by destination shows that France and Spain are Morocco’s main customers. Thus, cabling remains the main export segment to Spain. On the other hand, for France, Germany, Italy, Turkey and the United Kingdom, automotive manufacturing is the predominant branch in exports. Outside European countries, exports of vehicles produced in Morocco doubled to Algeria between 2016 and 2017, and have increased in recent years to Asian countries, mainly China.</em></p><p><em>Foreign direct investment income from the automotive industry rose sharply to MAD3.3 billion in 2017, up from MAD0.7 billion in 2010. France remains the leading direct investor in the automotive sector (82% in 2017), followed by the USA (8%) and the United Arab Emirates (UAE). Production and exports should continue to rise thanks to a MAD6 billion investment by PSA Peugeot Citroën, which will set up a plant in Morocco in the municipality of Ameur Seflia, in the Gharb Chrarda-Beni Hssen region, on the edge of the Atlantic Free Zone integrated industrial platform.</em></p>

Remittances and financial development in transition economies

Because of their sheer size and remarkable growth in recent years, remittances to developing and transition economies have attracted the attention of policy-makers and scholars. One region in which remittances have been growing and having a significant impact on local economies is Central and Eastern Europe and the former Soviet Union. The paper uses data on remittance flows to twenty-seven countries of the former Communist bloc during 1996–2013 and three distinct empirical econometric approaches to study the impact of remittances on financial systems. In particular, the research focuses on the link between remittances and various types of credits and deposits, using dynamic system generalised method of moments estimators to address the issue of reverse causality and allow for dynamic effects. This issue is important for the region, as economic and finance theory documents the growth-enhancing and poverty-reducing effects of financial development. The paper provides evidence of a robust, significant, and positive link between remittances and financial development. The link is especially strong in the ex-Soviet Union and in the case of private credit. The contribution of the present research to the literature is threefold: it is the first study to focus on a relatively homogeneous set of transition countries; the region it addresses is of particular interest because financial development in the region had to start before full-fledged formation of a market economy’s financial institutions; and it applies novel, high-quality data on bilateral remittances from Russia to a subsample of transition countries in the former Soviet Union.