Variable Segments Research Articles

Stock Portfolio Analysis with Machine Learning Algorithmic Approach for Smart Investment Decisions

This study investigates the application of machine learning algorithms in stock portfolio analysis within the Indonesia Stock Exchange (IDX) and their impact on investment decision-making. By engaging 500 respondents from diverse market segments, including retail investors, institutional investors, and stock traders, the research provides a comprehensive overview of adopting and utilising machine learning technologies in the Indonesian stock market. The findings reveal that over 80% of respondents have integrated machine learning algorithms into their investment strategies. The algorithms are applied in various capacities: 45% of respondents use them for portfolio risk analysis, 30% for stock price prediction, and 25% for identifying new investment opportunities. Preferences for specific algorithms vary, with regression, Support Vector Machines (SVM), and Random Forest emerging as the most used tools. The integration of machine learning was strongly associated with improved investment decisions, as more than 60% of respondents reported enhanced portfolio performance and greater accuracy in their decision-making. These results highlight the transformative potential of machine learning algorithms in enabling more innovative and more adaptive investment strategies.

Secrets to why consumers skip ads: The moderating role of personality traits

ABSTRACT In an era where online video advertising is paramount for engaging audience attention, YouTube emerges as a leading platform, drawing a vast spectrum of viewers. Despite its reach, the efficacy of video ads is often compromised by viewer tendencies to skip or avoid content perceived as irrelevant, intrusive, or irritating. This investigation delves into the nuanced personalities of individuals predisposed to dismissing YouTube video advertisements. Our comprehensive analysis uncovers a significant correlation between the perception of ad irrelevance and intrusiveness and the inclination to skip ads. Furthermore, we reveal that conscientiousness and neuroticism intensify the adverse effects of perceived irrelevance and intrusiveness on ad avoidance behaviors. In contrast, traits such as extraversion, agreeableness, and openness to experience mitigate these negative perceptions, suggesting a complex interplay between personality and ad reception. This study not only elucidates the dynamics of viewer engagement with online video ads but also offers valuable insights for advertisers aiming to tailor content more effectively to diverse audience segments.

Comparative study of the diversity of amino acids on human leucocyte antigen class II molecules in patients with acquired aplastic anaemia.

Human leucocyte antigen (HLA) class II molecules are critically involved in the pathology of acquired aplastic anaemia (AA) by regulating the immune response and autoreactive T cell-mediated haematopoietic cell death. In the study, amino acid residue variation and molecular structure of HLA class II have been initially investigated in 96 patients with AA. The frequencies of residues 9 and 57 in pocket 9 (P9) in DQB1, and amino acid positions 9, 11, 13, 16, 26, 38, 67 and 71 in the P4, P6 and P9 pockets in DRB1 were more prevalent among AA patients. By applying a multivariate recursive approach, the DRβ-Gln-16 (OR = 3.003, 95% CI = 1.468-6.145, pc = 0.003), DRβ-Ala-71 (OR = 1.924, 95% CI = 1.233-3.002, pc = 0.004) in P4/P7 and DQβ-Asp-57 (OR = 3.483, 95% CI = 1.079-11.242, pc = 0.037) in P9, these critical residues were significantly discovered as risk amino acid residues on the onset of AA, as well as associated with PNH-type cells and pathological somatic or cytogenetic mutations. In silico structural model analysis showed that identified DRβ-Ala-71 and DQβ-Asp-57 within the antigen-binding groove interacting with a more variable antigenic segments, may impact the repertoire of peptides presented, influence the interface HLA-antigen-T-cell receptor β (TCR β). These findings provided light on the immunogenetic pathophysiology of AA aetiology and their potential impact on upcoming immunotherapies.

Challenges and Opportunities in Implementing Disability Rights: Policy Evaluation and Access To Welfare For Persons With Disabilities

Persons with disabilities represent a diverse segment of society, facing unique challenges in accessing public services such as education, healthcare, and employment. In response, Indonesia ratified the Convention on the Rights of Persons with Disabilities (CRPD) through Law No. 19 of 2011, which serves to promote, protect, and ensure equal rights and fundamental freedoms for individuals with disabilities. This commitment led to the enactment of Law No. 8 of 2016, replacing an earlier, more compassionate framework with one emphasizing equality and the protection of rights for persons with disabilities. The law defines individuals with disabilities as those facing long-term physical, intellectual, mental, or sensory limitations and emphasizes the necessity of special protections to uphold their rights and prevent discrimination. The method used in this study is a normative legal research method. This study evaluates the effectiveness of disability rights protection policies in Indonesia, revealing significant challenges despite the legal framework established by Law No. 19 of 2011. Access to education, healthcare, and employment remains limited due to inadequate facilities, discriminatory practices, and social stigma. Effective solutions require strengthening the legal framework, increasing awareness, and involving the disability community in policy planning. Furthermore, robust monitoring and enforcement mechanisms are essential for safeguarding rights. To enhance protections, improved coordination among ministries, ongoing training for service providers, inclusive education practices, and recognition of employers who hire individuals with disabilities are critical. These measures are vital for fostering a more equitable society and ensuring the rights of persons with disabilities are upheld sustainably.

SAMCT: Segment Any CT Allowing Labor-Free Task-Indicator Prompts.

Segment anything model (SAM), a foundation model with superior versatility and generalization across diverse segmentation tasks, has attracted widespread attention in medical imaging. However, it has been proved that SAM would encounter severe performance degradation due to the lack of medical knowledge in training and local feature encoding. Though several SAM-based models have been proposed for tuning SAM in medical imaging, they still suffer from insufficient feature extraction and highly rely on high-quality prompts. In this paper, we propose a powerful foundation model SAMCT allowing labor-free prompts and train it on a collected large CT dataset consisting of 1.1M CT images and 5M masks from public datasets. Specifically, based on SAM, SAMCT is further equipped with a U-shaped CNN image encoder, a cross-branch interaction module, and a task-indicator prompt encoder. The U-shaped CNN image encoder works in parallel with the ViT image encoder in SAM to supplement local features. Cross-branch interaction enhances the feature expression capability of the CNN image encoder and the ViT image encoder by exchanging global perception and local features from one to the other. The task-indicator prompt encoder is a plug-and-play component to effortlessly encode task-related indicators into prompt embeddings. In this way, SAMCT can work in an automatic manner in addition to the semi-automatic interactive strategy in SAM. Extensive experiments demonstrate the superiority of SAMCT against the state-of-the-art task-specific and SAM-based medical foundation models on various tasks. The code, data, and model checkpoints are available at https://github.com/xianlin7/SAMCT.

Contemporary Homeschooling, Persistent Debates, and the Need for a New Generation of Research

ABSTRACT Homeschooling has grown into a large and highly diverse segment of American education. However, empirical studies of homeschooling have remained methodologically underdeveloped. The purpose of this article is to chart an agenda for a new generation of research on homeschooling. A narrative review of quantitative research published since 2000 is undertaken to identify gaps in the current evidence base. This review indicated that prior work is generally limited by small samples, uniform operationalizing of homeschool practice, and cross-sectional data sources. This article then concludes by describing strategies that researchers can use to address the limitations of previous studies.

A IMPORTÂNCIA DA INTELIGÊNCIA EMPRESARIAL NO PROCESSO DE TOMADA DE DECISÃO DA EMPRESA X DE PINHALZINHO-SC

Over the years, companies are going through various organizational change processes, many transformations are taking place, and one of them is the insertion of technologies in the most diverse business segments. Information technology and business intelligence, Busines Intligence (BI), is becoming loyal and a great ally when it comes to strategy and decision making. Organizations are using such technologies as a support tool in the way they administer and manage their processes and businesses. These tools assist in the analysis of data and results that companies have, providing safer and more assertive decision making, in addition to offering greater security to owners. This study seeks to analyze the importance of this theme in the organizational environment of company X, located in the municipality of Pinhalzinho-SC. The data for this article were collected through an interview with the owners of the organization. In addition to doing an analysis on the subject, one of the objectives of this work is to present an improvement proposal for the company.

Utilization of Hibiscus, Tamarind and Carob in Production of Low Calories Healthy Soft Drinks

The demand for carbonated beverages is increasing, offering opportunities to develop drinks with significant health benefits. Beverages containing carob, tamarind and hibiscus offer multiple nutritional and functional benefits and can serve as healthy alternatives to other soft drinks on the market. This is particularly important given the high sugar and calorie content of traditional soft drinks, which has been linked to increased issues associated with obesity, type 2 diabetes, osteoporosis and cardiovascular disease globally. The focus of the current work is to evaluate low-calorie soft drinks made from hibiscus, tamarind and carob and sweetened with erythritol that cater to diverse consumer segments, including diabetics and health-conscious individuals. Hibiscus, tamarind and carob extracts were sweetened with 0.5, 1 and 1.5 g erythritol sugar/200 ml carbonated beverage. The results showed that the alcoholic extract from hibiscus cups gave the highest content of phenols and flavonoids (70.3 mg gallic/g on DW and 7.8 mg catechin/g on DW), followed by carob pod alcoholic extract (19.3 mg gallic/g on DW) and tamarind alcoholic extract (11.6 mg gallic/g on DW). Tamarind gave a higher content of flavonoids (2.3 mg/g) than carob (1.2 mg/g); however, carob pods had the highest antioxidant activity (91.92%), followed by tamarind pulp (87.66%) and hibiscus cups (79.76%). The soft drinks of hibiscus and tamarind sweetened with erythritol at 1.5 g/200 ml gave the best sensory properties compared with control (adjusted by sucrose at 12% brix) and others concentrations used of erythritol sugar at (0.5 and 1.5 g /200 ml carbonated beverage). Carob pods soft drink sweetened with 0.5 g erythritol /200 ml gave the best sensory characteristics compared to the control sample and others concentrations of erythritol sugar at (1 and 1.5 g /200 ml carbonated beverage), which may be due to the high content of sugars in carob. Hibiscus carbonated beverage outperformed tamarind in terms of overall acceptability and carob carbonated beverage was the least acceptable in terms of sensory properties. Carob carbonated beverage recorded the highest antioxidant activity (90.9%) and phenolic content while representing the second highest in terms of flavonoids. Tamarind carbonated beverage ranked second in terms of antioxidant activity (86.0%) and phenolic content although it ranked first in terms of flavonoids. Hibiscus carbonated beverage recorded the lowest content in terms of antioxidant activity (79.36%), phenolic compounds and flavonoids. Hibiscus, tamarind and carob are a great choice for the production of carbonated beverages because they give the beverage desirable nutritional, cosmetic and medicinal qualities. Moreover, the simplicity of production and availability of raw materials allows for the stimulation of the economy by reducing dependence on multinational companies offering unhealthy or industrialized soft drinks.

Voice Unbound: The Impact of Localization and Experience on Continuous Personal Voice Assistant Usage and Its Drivers

This research explores the key factors driving the continuous use of Personal Voice Assistants (PVAs), particularly emphasising the roles of localization and experience in shaping these behaviours. Data has been gathered from 1041 PVA users through an online survey. By integrating psychological (Attitude, Enjoyment, and Personal Innovativeness), technological (Perceived Ease of Use and Usefulness), and social (Subjective Social Norms) factors, the study uncovers the complex mechanisms that influence users’ continued usage intentions towards PVAs. It also examines how localization and experience moderate these relationships, offering key insights for developers and marketers to optimise users’ continuous usage and expand market reach by effectively targeting diverse consumer segments. Further, qualitative insights reveal user needs and barriers, offering a deeper understanding of user expectations. The study also highlights several promising avenues for future research to further examine evolving dynamics between users and PVAs.

Blockchain for building trust in genomic initiatives

AbstractThis commentary aims to share the current patient engagement context in genome initiatives within universal healthcare systems worldwide, focusing on the inclusivity of diverse population segments rather than just numerical metrics. It explores the relevance and potential replicability of these initiatives globally, questioning their efficacy in ensuring widespread citizen participation. Empirical evidence shows that hesitancy to opt into genome initiatives goes beyond demographic factors, with a significant portion of the population abstaining due to prevailing mistrust. Given the global aspiration for delivering precision healthcare and promoting a healthy lifestyle for all citizens, this paper investigates the multifaceted reasons behind this distrust. It underscores the need for policymakers to understand these reasons comprehensively and proposes a Blockchain‐based framework centered on trust‐building as a potential solution to enhance citizen engagement. The analysis of distrust factors and their impact on participation leads to the conclusion that decisive measures are necessary to improve the participatory landscape of genomic initiatives. The paper advocates for actions to enhance trust, thereby improving the current operational milieu of precision healthcare. The broader conclusion emphasizes the importance of trust‐building strategies in achieving the goal of fostering a healthy lifestyle for all citizens and provides a foundation for further development in this pioneering healthcare domain.

Sharing channel choices for electric vehicle battery manufacturers when considering range anxiety among heterogeneous consumers

PurposeThis study aims to investigate the optimal pricing decisions and shared channel strategy selection of battery manufacturers considering heterogeneous consumers' range anxiety.Design/methodology/approachAmidst the rapid growth of the electric vehicle sector, countries are promoting upgrades in the automotive industry. However, insufficient driving range causes consumer range anxiety. The study utilizes the Stackelberg game model to assess how range anxiety influences battery manufacturers' pricing and channel strategy decisions across three strategies.FindingsWe find that electric vehicle battery manufacturers' decisions to cooperate with third-party sharing platforms (TPSPs) are primarily influenced by fixed costs and consumer range anxiety levels. As range anxiety increases, the cost threshold for joining shared channels rises, reducing cooperation likelihood. However, considering diverse consumer needs, especially a higher proportion of leisure-oriented consumers, increases the likelihood of cooperation. Furthermore, higher battery quality makes direct participation in shared channels more probable.Originality/valueIn the electric vehicle industry, range anxiety is a significant concern. While existing literature focuses on its impact on consumer behavior and charging infrastructure, this study delves into battery manufacturers' strategic responses, offering insights into channel options and pricing strategies amidst diverse consumer segments.

Diverse perspectives on entrepreneurship: Analyzing gender and age-related differences in perceptions

Entrepreneurship is a key driver of economic growth, innovation, and social development, yet perceptions of entrepreneurship can vary significantly across different demographic groups. Understanding these variations is crucial for developing effective education and support systems. This study investigates the differences in perceptions of entrepreneurship among various gender and age groups, focusing on aspects such as career opportunities, financial readiness, the attractiveness of entrepreneurial ventures, skill requirements, economic impact, educational effectiveness, and gender-specific views on entrepreneurship. Using a quantitative research design, the study analyzed data collected from 300 entrepreneurs in Greater Noida through a structured questionnaire. Independent samples t-tests and ANOVA were employed to identify significant differences in perceptions across genders and age groups. The findings reveal notable differences in perceptions related to the effectiveness of entrepreneurship education and the role of women in entrepreneurship. Specifically, females demonstrated greater confidence in the ability of the education system to prepare individuals for entrepreneurial careers than males did. Additionally, significant differences in perceptions of entrepreneurial opportunities and support were observed between different age groups. These results highlight the need for tailored education programs and support systems that address the unique needs of diverse demographic segments. The study underscores the importance of promoting gender diversity and inclusivity in entrepreneurship to foster a more dynamic and innovative entrepreneurial ecosystem. By addressing the specific challenges and opportunities identified, policymakers and educators can develop more effective and inclusive strategies to support aspiring entrepreneurs. Future research should further explore the sociocultural and institutional factors influencing entrepreneurial perceptions to enhance the overall effectiveness of entrepreneurship initiatives.

EVALUATING THE CHARACTERISTICS OF THE VTSM SPECTRUM SENSING METHOD IN COGNITIVE RADIO NETWORKS

The article investigates the complexities associated with spectrum analysis in cognitive radio networks (CRNs). It begins by acknowledging the evolving challenges of spectrum sensing due to the dynamic nature of wireless environments and the increasing demand for efficient spectrum utilization. The study thoroughly examines various traditional spectrum sensing methods, including Energy Detector Based Sensing, Waveform-Based Sensing, Cyclostationarity-Based Sensing, and Matched Filtering. The focus of the research is on the Variable Time Segment Monitoring (VTSM) method, a novel approach that optimizes spectrum sensing by dynamically adjusting the time segments used for analyzing spectral characteristics. The paper highlights the VTSM method's ability to enhance detection accuracy and reduce false alarms by adapting to different signal environments, making it particularly suited for complex and dynamic CRN scenarios. Furthermore, the article compares VTSM with traditional methods across key performance metrics such as detection accuracy, false alarm rate, latency, and computational complexity. The analysis reveals that while traditional methods have their strengths, VTSM offers a balanced approach, combining flexibility, accuracy, and moderate computational demands, thereby providing a versatile solution for modern spectrum sensing challenges. The findings contribute to the broader understanding and advancement of cognitive radio technologies, supporting the development of more robust and efficient spectrum sensing solutions, which are crucial for optimizing network performance and ensuring reliable communication in increasingly congested and complex wireless environments. The article concludes by emphasizing the importance of selecting the appropriate spectrum sensing method based on the specific requirements of the CRN application, considering factors such as accuracy, computational resources, and environmental dynamics. The findings contribute to the broader understanding and advancement of cognitive radio technologies, supporting the development of more robust and efficient spectrum sensing solutions.

Penerapan Algoritma Clustering untuk Segmentasi Pelanggan E-commerce berdasarkan Data Pembelian dan Aktivitas

In the current digital era, e-commerce has become one of the main pillars of global trade. With the ever-increasing amount of transaction and user activity data, e-commerce companies are faced with the challenge of understanding and managing diverse customer segments more effectively. This paper discusses the application of clustering algorithms for e-commerce customer segmentation based on purchasing data and user activity. The aim of this research is to identify homogeneous customer groups to support more targeted marketing strategies and increase customer retention. The problem faced is how to process big data originating from user transactions and activities on e-commerce platforms, as well as how to identify patterns that are useful for customer segmentation. The data used in this research includes purchase history, frequency of visits, length of time spent on the site, and interactions with certain products. The solution method applied in this research is the clustering algorithm, especially K-Means and DBSCAN. K-Means is used to group data into a predetermined number of clusters based on the Euclidean distance between data points. Meanwhile, DBSCAN is used to identify clusters with high density and separate data that is considered noise or outliers. Data preprocessing is carried out to clean and normalize the data before being applied to the clustering algorithm. Validation of clustering results is carried out using metrics such as Silhouette Score and Davies-Bouldin Index. The research results show that by applying the clustering algorithm, customers can be grouped into several segments that have similar characteristics. For example, we found groups of customers with high purchase frequency but low transaction value, as well as other groups with high transaction value but low purchase frequency. This information is very useful for companies to design more effective marketing strategies, such as special offers for customers with high transaction values ​​or loyalty programs for customers with high purchasing frequency. The conclusion of this research is that clustering algorithms can be a very effective tool in e-commerce customer segmentation, allowing companies to understand customer behavior patterns and develop more targeted and effective marketing strategies. Thus, implementing this method is expected to improve business performance and overall customer satisfaction.

Comparison of B Cell Variable Region Gene Segment Characteristics in Neuro-autoantibodies.

Autoimmune pediatric neurologic diseases have variable phenotypes and presentations, making diagnosis challenging. The pathologic mechanisms are also distinct, including cell-mediated and Ab-mediated autoimmunity, paraneoplastic syndromes, and postinfectious processes. In recent years a number of studies have described the characteristics of the autoantibodies involved in a number of these diseases. Some of the described Abs use a restricted set of variable gene segments. We sought to compare the Ab characteristics of autoantibodies related to some of the more common disorders to discover whether specific Ab signatures are universally associated with neuroautoimmune diseases. We initially performed a literature review to summarize the Ab characteristics of autoantibodies related to some of the more common disorders, including N-methyl-d-aspartate receptor (NMDAR) and leucine-rich, glioma-inactivated 1 (LGI-1). Next, we performed data analysis from selected studies that sequenced Ig genes to further characterize NMDAR and LGI-1 autoantibodies including CDR3 length distribution, variable gene sequence usage, and isotype use. We found that CDR3 length of NMDAR autoantibodies was normally distributed whereas the CDR3 length distribution of LGI-1 autoantibodies was skewed, suggesting that there is no global structural restriction on types of autoantibodies that can cause encephalitis. We also found that IgG1-IgG3 were the main NMDAR autoantibody isotypes detected, while IgG4 was the major isotype used in autoantibodies from LGI-1 encephalitis. These findings are useful for our understanding of autoimmune encephalitis and will help facilitate better diagnosis and treatment of these conditions in the future.

Political and Intercultural Communication in Determining Presidential Candidates in the Indonesian Elections 2024

This study explores the dynamics of political communication in Indonesia, focusing on the 2024 presidential elections. As the country prepares for the presidential election in February 2024, since the general election is a form of post-reformation democratic process implementation that began in 1998, the process of forming political coalitions has become a significant aspect of the political landscape. Utilizing a phenomenological approach, the research examines the interplay between three distinct political cultures—parochial, subject, and participant—and their influence on voter engagement and candidate selection. Through in-depth interviews and participatory observation, the study reveals how political parties can tailor their communication strategies to resonate with diverse voter segments, thereby enhancing electoral participation and fostering a more inclusive democratic process. The findings highlight significant implications for political actors and scholars alike. By recognizing the unique characteristics and needs of each political culture, parties can develop effective coalition-building strategies that bridge cultural divides and mobilize support across Indonesia's heterogeneous electorate. This research not only fills existing gaps in the literature regarding the role of intercultural communication in Indonesian politics but also provides practical recommendations for political parties aiming to improve their engagement with voters. Ultimately, the study underscores the critical importance of adaptive communication strategies in promoting a more informed, engaged, and representative democratic system in Indonesia. Keywords: Elections, intercultural communication, political communication, political parties, presidential candidate.

Customer Acceptance for Self-Service Technologies in Malaysian Fast-Food Restaurants: An Empirical Study

Recently, the fast-food industry has witnessed an increase in adopting self-service technologies (SSTs) intended to offer customers increased convenience and efficiency. This study seeks to find out the factors influencing customer acceptance of SST in fast food restaurants in Melaka, Malaysia, using the Technology Acceptance Model. For that purpose, a structured questionnaire was presented to 350 customers of fast food and this data was analyzed by descriptive and inferential statistics. A test of the hypotheses revealed that perceived ease of use (PEOU) and perceived usefulness (PU) are highly significant predictors of customers' attitudes toward using SSTs (ATU). More specifically, PU indicates stronger effects on acceptance such that customers are more willing to use SSTs when obvious practical benefits would be achieved from them regarding faster services and greater accuracy in placing orders. The findings also indicate that younger, highly educated customers with previous experience with SSTs are more likely to accept this innovation. These insights go a long way in helping the operator of fast food to design a better customer experience using technology-driven solutions. This covers the improvement of user interfaces, the emphasis on the practical benefits of SSTs, and tailoring marketing strategies to diverse customer segments.

Color Matters: A Study Exploring the Influence of Packaging Colors on University Students’ Perceptions and Willingness to Pay for Organic Pasta

The organic food market’s rapid expansion necessitates an understanding of factors influencing consumer behavior. This paper investigates the impact of packaging colors on perceptions and willingness to pay (WTP) for organic foods, utilizing an experimental auction among university students. Drawing on previous research, we explore how colors influence perceived healthiness, premiumness, trust, and sustainability. The results indicate nuanced responses to different colors, emphasizing the need for businesses to adopt tailored packaging strategies. White and green dominate organic food packaging, aligning with associations of freshness and health. However, the study uncovers varied consumer responses, suggesting a more intricate relationship between color, trust, premiumness, and healthiness perceptions. Demographic factors such as age, gender, income, and residence areas influence WTP for organic foods with different colors, emphasizing the importance of diverse consumer segments in marketing strategies. Trust and perceived premiumness significantly influence WTP, highlighting their pivotal role in consumer valuation. The results highlight that green packaging builds trust among non-organic buyers, while organic buyers are influenced by a broader range of colors that emphasize premiumness and healthiness. The study concludes that businesses in the organic food market should carefully consider color choices in branding and packaging to effectively communicate product qualities and align with consumer values.

Research into intergenerational differences among Chinese female tourists consuming Thai cosmetics

Consumers, particularly women, pursue beauty and health in order to uphold their image within society, which has contributed to consistent demand for cosmetics. The cosmetics market, driven by globalization and cultural exchange, sees Thai cosmetics gaining popularity among Chinese women. There has been a significant rise in the popularity of Thai cosmetics, known for their natural ingredients and innovative formulations. With a growing interest in cross-cultural consumer behaviour, particularly in the context of skincare and make-up products, understanding how different age groups perceive and choose Thai cosmetics is crucial for effective marketing strategies. The main issue is the development of consumer preferences over time among Chinese women who have only recently been given the opportunity to choose among many brands. This qualitative study explores the intergenerational differences in Chinese female consumers’ preferences for Thai cosmetics, aiming to uncover rich insights into their perceptions, attitudes, and behaviours. The target population is female Chinese who have visited Thailand and purchased or used Thai-branded cosmetics. Key themes emerge regarding the perception of product efficacy, the cultural authenticity and the role of digital media and trends in influencing product choices. Findings highlight nuanced generational preferences, with older cohorts emphasizing trust and familiarity with established brands, while younger cohorts prioritize innovation, sustainability, and personalized beauty experiences. These insights provide valuable implications for marketers seeking to tailor strategies and product offerings to engage effectively diverse generational segments within the competitive cosmetics market.

Unlocking Tourism Diversity in Winter: Clusters of Tourists in Lisbon Based on Motivations, Profiles, and Behaviour

Recent trends in Lisbon's winter tourism indicate a shift towards off-peak travel, attracting diverse visitors with its rich cultural heritage, sustainable initiatives, and extended stay options for digital nomads. The city's culinary scene, arts, wellness activities, and tech-driven tourism options enhance its appeal. Aligned with these recent trends, tourism in Lisbon's region during the winter season presents a unique and dynamic landscape influenced by a wide range of motivations, tourist profiles, and travel behaviours. This study aims to define distinctive clusters of winter tourists in Lisbon by analysing these key variables, providing valuable insights specific to the winter travel context. Based on a compiled dataset from the winter season in Lisbon, this study delves into examining the factors driving tourist visits, encompassing socio-economic backgrounds, travel frequency, and age demographics. We aim to reveal the distinctive subgroups that define Lisbon's winter tourist population, employing data analysis techniques such as cluster analysis. From an academic perspective, this study offers a novel tourist segmentation model based on motivations, profiles, and behaviour. This model enriches the existing body of knowledge in tourism studies, providing a valuable reference for future research. For tourism agents in Lisbon, this study provides actionable insights to enhance strategic decision-making. By segmenting winter tourists, they can tailor marketing strategies and product development to cater to diverse tourist segments. Moreover, this approach can lead to economic benefits, optimising resource allocation, and revenue generation.