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For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

Facility management gained profound importance due to the increasing complexity of different systems and the cost of operation and maintenance. However, due to the increasing complexity of different systems, facility managers may suffer from a lack of information. The purpose of this paper is to propose a new facility management approach that links segmented assets to the vital data required for managing facilities.

Automatic point cloud segmentation is one of the most crucial processes required for modelling building facilities. In this research, laser scanning is used for point cloud acquisition. The research utilises region growing algorithm, colour-based region-growing algorithm and Euclidean cluster algorithm.

A case study is worked out to test the accuracy of the considered point cloud segmentation algorithms utilising metrics precision, recall and F-score. The results indicate that Euclidean cluster extraction and region growing algorithm revealed high accuracy for segmentation.

The research presents a comparative approach for selecting the most appropriate segmentation approach required for accurate modelling. As such, the segmented assets can be linked easily with the data required for facility management.

With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.

This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.

Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.

This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.

Analysis of architectural space is commonly conducted by examining architectural drawings that project spatial information by means of walls and partitions. To capture the lived experience of space, which is richer than what we can see from drawings, a new method is proposed to quantify the cognitive dimension of space and re-present it as an audible format.

Using an urban vernacular house in Seoul as a case study, this research takes a syntactic approach to quantify one's changing perception through their movement from the main gate to the most private reception room. Based on Luigi Moretti's theory of hollow space, a new method is proposed to measure the level of spatial pressure exerted on a navigating body. The numerical data of spatial pressure are then converted to a sound using musical techniques of the chromatic scale and chorale textures.

Building on Moretti's abstract concept, it has been shown that a rule-based quantification of users' spatial perception is possible. In addition, unlike conventional approaches of treating architecture as a static entity, this study showed an alternative approach to represent it as a sequence of sensorial experience that can be readily converted to a sound of music.

This research developed a quantification method to measure the perception of pressure inside buildings by revisiting Luigi Moretti's theory proposed in 1952. It has been also demonstrated that the visual stimuli in space can be translated into an audible experience. This new method is applicable to a wide range of buildings including important historic architecture.

This paper aims to present a comprehensive overview of the emergence and significance of digital payments, focusing on their impact on competitiveness and the need for policy interventions. In addition, it explores the design of policies that promote the adoption of digital payments, highlighting the benefits they offer to providers and users.

The paper examines the technological advances that have driven the growth of digital payment systems. It identifies key requirements for successful adoption and discusses the associated risks, along with potential strategies to mitigate these risks.

The findings emphasize the importance of responsible implementation and safeguarding the well-being of end users to fully realize the benefits of digital payment adoption. Understanding the inherent risks and establishing effective risk mitigation mechanisms are crucial. This necessitates the development of appropriate infrastructure to support the provision of digital payment services.

More research is needed to gain deeper insights into how emerging global trends in financial technology should be analyzed and understood by policymakers, service providers and users.

The findings of this study can guide policymakers, private sector managers and consumers in comprehending the effects of emerging digitalization trends and determining their adoption responses accordingly.

This paper stands out as one of the few research contributions that provide comprehensive and actionable policy recommendations to facilitate a smooth transition to a digital payments ecosystem that benefits all stakeholders.

This paper aims to conduct a systematic literature review on the fintech services and financial inclusion of the developing nations that particularly focuses on lower middle-income group nations (LMIGN) and upper middle-income group nations (UMIGN) to highlight the research areas that have not received attention and present opportunities for future research.

This paper adopts a systematic approach to examine 65 research articles published from 2016 to 2021, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The study identifies research gaps in two key themes: backward and outward linkages. In backward linkages, the literature on UMIGN should pay attention to the behavioural patterns associated with lending, investment and market provision-related fintech services. Further research is needed to understand the relationship between fintech services on the usage and quality dimension of financial inclusion in both LMIGN and UMIGN. For outward linkages, future research work should explore the role of fintech and financial inclusion in the development of LMIGN. This study provides valuable insights and guides future research directions by comprehensively mapping the existing studies.

This study does not use quantitative tools, such as meta and bibliometric analysis, to validate the findings.

This research paper offers new perspectives that introduce a novel framework for analysing literature on fintech, financial inclusion and its impact on the overall development of UMIGN and LMIGN.

The primary objective of this study aims to intensively explore the environment of Indonesian regulations and laws related to the Islamic banking system and micro-, small- and medium-sized enterprises (MSME) and unveil the restrictive laws and regulatory flaws that potentially hinder the Islamic banking institution and MSME industry in achieving financial inclusion and promoting sustainable growth.

This paper implements a qualitative method by implementing a multi-case study research strategy, both from the Islamic banking institutions and the MSME industries. The data were gathered primarily through an interview approach by adopting purposive uncontrolled quota sampling.

The findings of this paper reveal two essential issues: First, the regulatory imbalances and restrictions could demotivate and hinder the efforts of Islamic banks in providing access to finance for the MSME segment, hence, encumbering the achievement of the financial inclusion agenda from the Islamic banking industry. Second, the flaws in MSME registration and taxation might discourage the formal MSMEs from extending their business license and prevent the informal MSME units from registering their business. This issue would potentially lower their chance of accessing external financing from the formal financial institutions and participating in supportive government programmes due to the absence of proper legality.

Since this paper only observed six Islamic banks and 22 MSME units in urban and rural locations in Indonesia using a case study approach, the empirical findings and case discussions were limited to those respective Islamic banks and MSME participants.

By referring to the recommendations as presented in this paper, two critical policy implications could be expected from adopting the proposed recommendations, among others: By addressing the issues of the regulatory imbalance associated with the Islamic banking industry and introduce the deregulatory policies on profit and loss sharing (PLS) scheme implementation, this approach will motivate the Islamic banking industry in serving the MSME sector better and provide greater access to financial services, particularly in using the PLS financing schemes. By resolving the problems on MSME registration and taxation, this strategy will enhance the sustainability of the formal MSMEs’ operation and encourage the informal ones to register, hence, improving their inclusion into the formal financing services and government assistance programmes.

The present study attempts to address the literature shortcomings and helps to fill the gaps – both theoretical and empirical – by incorporating the multi-case study among Indonesian Islamic banks and MSMEs to extensively explore the Indonesia regulatory environment pertaining to the Islamic banking system (supply-side) and MSMEs (demand-side), and thoroughly investigates and reveals the restrictive laws and regulatory flaws that could potentially hinder the Islamic banking institutions and MSME industries in attaining financial inclusion and contributing to sustainable development.

The purpose of this paper is to explore the reaction of Pakistani citizens toward online privacy in the context of the Pakistan Government's COVID-19 app privacy breach.

The authors implemented supervised and unsupervised machine learning methods, that is, topic modeling and sentiment analysis on Google app store user review data.

There was no visible concern shown by the citizens toward the COVID-19 app privacy breach, even though it was well highlighted in the news. Other studies have also indicated that concern for online privacy remains low in developing countries, which aligns with the findings of this paper.

Globally COVID-19 apps have been a cause of concern in terms of public privacy. To the best of the authors’ knowledge, this paper is the first in the Pakistani context to show the impact of a well-document privacy breach of a government COVID-19 app.

The UAE is among the fastest-growing facilities management (FM) markets globally. Nevertheless, conclusive evidence on this market is scarce in the literature. Therefore, this paper aims to provide an in-depth insight into the FM market in the UAE.

Fourteen interviewees were purposively selected to provide insight into FM status through their field experiences. A SWOT analysis of their answers held place.

Interviewees revealed that the main trends of FM in the UAE include interests in sustainability, integration of technology, health and safety, outsourcing FM, switching to total facilities management (TFM), and performance management systems use. Besides, the quality of the service in the FM market is driven by the real-estate boom, services sophistication, the increasing awareness of FM and focus on the quality of services. Furthermore, the interviews found that the recruitment of poorly skilled labors can threaten the FM market to meet the allocated budget, misperception of FM, the value of money, the lack of continuous follow-up with recent advancements in technologies and the lack of performance measurement models.

This paper highlights the major trends, drivers and threats of the FM market in the UAE, and the implications of its findings can direct FM organizations and researchers in their practices.