VGTU Journals (Vilnius Gediminas Technical University - Vilnius Tech)
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Impact of physical vanity, achievement vanity and brand equity on the consumption of luxury skincare products
No full textThe aim of this study is to evaluate the influence of physical Vanity, achievement vanity, and brand equity on luxury consumption in the skincare industry, considering the promising US$13.9 billion beauty and personal care market in India, as estimated by Euromonitor International. Data were collected from 200 male and female participants in the National Capital Region of Delhi, India, belonging to various geographic groups and income levels. Confirmatory factor analysis was utilized to assess the relationship between observed and latent variables, while regression analysis was employed to determine the impact of physical Vanity, achievement vanity, and brand equity on luxury consumption. The study reveals that physical Vanity, achievement vanity, and brand equity positively affect luxury product consumption, with brand equity having the most significant impact. The associations between luxury consumption and physical Vanity, achievement vanity, and brand equity were found to be statistically meaningful. The findings offer valuable insights for skincare market marketers, allowing them to identify opportunities and strategize to capture untapped markets in the country. Additionally, the results enable them to understand the relative influence of the three factors – physical Vanity, achievement vanity, and brand equity – on luxury consumption. This research contributes to the understanding of the positive effects of physical Vanity, achievement vanity, and brand equity on luxury product consumption. The survey-based approach offers a comprehensive yet succinct overview of the existing literature and its implications, benefiting both luxury brand managers and future researchers
Assessment of sustainable road transport in Lithuania
No full textRoad transport plays an important role in our lives. In Lithuania, passenger road transport accounted for more than 47% in 2022, and freight road transport more than 87% of the transport sector. Up to 15% of the Lithuanian population works in this sector (in 2020). However, road transport is one of the most polluting. In 2021, it represented 72% of all greenhouse gas emissions from EU domestic and international transport. In order to solve this problem, the EU plans to ban the sale of vehicles with internal combustion engines by 2035. So, the question arises: what challenges will the country’s transport sector face, what measures/innovations will it adopt to reduce greenhouse gas emissions? To answer this question, the article analyzes the road transport sector and identifies measures to improve the sustainability of the sector, increase turnover, and observes the impact of those measures on road transport turnover. The purpose of the research is to determine the factors affecting the circulation of passengers and cargo by road transport based on scientific literature and to empirically verify their influence on the sustainability of the country. In order to achieve the set goal, the analysis is carried out in two blocks: the study of the turnover of road transport cargo and the study of the turnover of road transport passengers. The following methods are used for the research: correlation regression analysis, forecasting. The research results are important for policy makers and practitioners in the context of sustainable transport development
Exploration of social dimensions of sustainable behavior
No full textAs climate change and inequality spur interest in sustainable lifestyles, insufficient attention focuses on the social dimension encompassing equity and wellbeing-oriented conduct. Limited measurements capture facets like frugality, sufficiency, and altruism, obscuring motivational nuances. Addressing persistent gaps, this exploratory sequential mixed-methods research developed and validated a multidimensional scale assessing components of individual social sustainability behavior. The initial qualitative generation of 167 items from established surveys enabled breadth. An expert review panel then evaluated content validity quantitatively through statistical relevance ratings and qualitatively via open-ended feedback on gaps and terminology issues to refine facets. Analyses informed iterative adjustments, resulting in a 45-item pool demonstrating sound psychometric properties. Quantitative techniques found strong internal reliability (α >.80) and confirmed dimensionality in distributing items across volunteering, charitable giving, conscious consumption, lifestyle simplicity, equity promotion, and community building sub-scales. Confirmatory factor analysis met thresholds for acceptable model fit. Qualitative inputs crucially enhanced practical resonance and specificity. Findings provide initial evidence of a valid, generalizable measurement of the social sustainability domain, encompassing cooperative civic engagement, frugality, and lifestyle moderation behaviors on the individual level. The parsimonious instrument promises utility for research and community initiatives advancing this complementary sustainability facet. Practical implications and scholarly contributions are discussed
Corporate social responsibility, work engagement and hospital image: the roles of hospital reputation, organizational trust and information technology application
No full textThis study investigates the mediating role of hospital reputation (HOR), organizational trust (ORT), and the moderating role of perceived usefulness of information technology application (ITA) in the relationship between corporate social responsibility (CSR), work engagement (WOE), and hospital image (HOI). Using survey data from 586 healthcare workers employed at public hospitals in Ho Chi Minh City, Vietnam, the study employs partial least squares structural equation modeling (PLS-SEM) to test the measures and hypotheses. The results reveal that effective CSR practices not only foster a positive work environment and enhance WOE but also significantly improve HOI. HOR and ORT partially mediate the impact of CSR on WOE and, alongside WOE, act as crucial mediators in the CSR-HOI relationship. These findings confirm that organizational reputation and trust are foundational to building sustainable relationships between organizations and employees while also strengthening the hospital’s image in the community. Furthermore, the study identifies perceived usefulness of ITA as a significant benefit that positively modifies the impact of CSR on HOI. From these results, practical managerial implications are proposed for hospital leaders to enhance WOE and HOI through the implementation of CSR and ITA practices
Effect of noise reduction on PLSR modeling in near infrared spectroscopy using denoising autoencoder
No full textIn this study, a deep learning-based denoising autoencoder approach is proposed to increase the robustness of near-infrared spectroscopy data to random noise and improve quantitative modeling accuracy. Artificial Gaussian noise at four different levels (10, 15, 20, and 25 dB) was added to the near-infrared spectra obtained from milk samples to mimic the real measurement conditions. The noisy spectra were denoised by processing with an autoencoder architecture consisting of fully connected layers. The noise removal performance is quantitatively evaluated with both theoretical and measured signal-to-noise ratio values. The results show that the AE model significantly improves the spectral signal quality at all signal-to-noise ratio levels. In particular, at the lowest signal-to-noise ratio level (10 dB), the signal-to-noise ratio value nearly tripled to 29.6 dB with the autoencoder. At all other levels, an average increase of 18-20 dB was observed in the signal-to-noise ratio of the denoised spectra. In the second stage of the study, Partial Least Squares Regression models were built using both the noisy and cleaned spectra and evaluated on the test set with root mean square error and coefficient of determination. The Partial Least Squares Regression models built with the denoised spectra achieved lower root mean square error and higher coefficient of determination values at all signal-to-noise ratio levels. Especially at the 10 dB signal-to-noise ratio level, the coefficient of determination value of the model increased from 0.44 to 0.71, while the root means square error decreased from 0.60 to 0.43. The results show that the deep learning-based AE architecture can effectively reduce random noise in near-infrared spectral data and significantly improve both spectral signal quality and quantitative modeling performance. This approach provides an effective solution to improve model reliability and accuracy in near-infrared spectroscopy analysis
Impact of the war in Ukraine on international trade trends
No full textThe ongoing war in Ukraine, which began in 2014, has significantly disrupted global trade, particularly in energy, agriculture, and supply chains. This study integrates economic, trade, and geopolitical theories with empirical data to analyse the conflict’s immediate and long-term effects on international trade. Key findings reveal a sharp decline in Ukraine’s agricultural exports, with grain and oilseed shipments dropping over 40% since 2022, exacerbating global shortages. Fertilizer exports from both Russia and Ukraine have also plummeted, causing a 70% increase in global prices and impacting agricultural productivity in countries like Bangladesh, Egypt, and India. In response, nations have reshuffled trade partnerships, with Egypt increasing wheat imports from India and Brazil, and Indonesia turning to Australia and China for fertilizers, albeit with higher costs and logistical challenges. The conflict has led to a 20% rise in global food prices, worsening food insecurity, especially in vulnerable regions. The study underscores the need for diversified supply sources, enhanced domestic agricultural production, and resilient supply chains to mitigate the impacts of geopolitical conflicts on global trade and food security.
Article in English.
Ukrainos karo įtaka tarptautinės prekybos tendencijoms
Santrauka
Besitęsiantis karas Ukrainoje, prasidėjęs 2014 metais, smarkiai sutrikdė pasaulinę prekybą, ypač energetikos, žemės ūkio ir tiekimo grandinių srityse. Šiame tyrime ekonominės, prekybos ir geopolitinės teorijos yra derinamos su empiriniais duomenimis, siekiant išanalizuoti konflikto tiesiogines ir ilgalaikes įtakas tarptautinei prekybai. Pagrindiniai tyrimo rezultatai atskleidžia staigų Ukrainos žemės ūkio eksporto mažėjimą, javų ir aliejinių sėklų eksportas nuo 2022 metų sumažėjo daugiau nei 40 %, dar labiau pablogindamas pasaulinį maisto produktų trūkumą. Trąšų eksportas tiek iš Rusijos, tiek iš Ukrainos taip pat smarkiai sumažėjo, dėl to pasaulinės kainos išaugo 70 % ir paveikė žemės ūkio produktyvumą tokiose šalyse kaip Bangladešas, Egiptas ir Indija. Į tai reaguodamos, šalys pergrupavo prekybos partnerystes, Egiptas padidino kviečių importą iš Indijos ir Brazilijos, o Indonezija kreipėsi į Australiją ir Kiniją dėl trąšų, nors tai ir kelia didesnes išlaidas bei logistinius iššūkius. Konfliktas lėmė 20 % pasaulinių maisto kainų kilimą, o tai dar labiau pablogino maisto saugumo situaciją, ypač pažeidžiamuose regionuose. Tyrime pabrėžiama būtinybė diversifikuoti tiekimo šaltinius, stiprinti vidaus žemės ūkio gamybą ir atsparias tiekimo grandines, siekiant sušvelninti geopolitinių konfliktų įtaką pasaulinei prekybai ir maisto saugumui.
Reikšminiai žodžiai: pasaulinė prekyba, Ukrainos karas, trąšų ir kviečių rinkos nepastovumas, žemės ūkio eksportas, maisto saugumo įtaka
Convergence analysis of a class of iterative methods: a unified approach
No full textIn this paper, we study the convergence of a class of iterative methods for solving the system of nonlinear Banach space valued equations. We provide a unified local and semi-local convergence analysis for these methods. The convergence order of these methods are obtained using the conditions on the derivatives of the involved operator up to order 2 only. Further, we provide the number of iterations required to obtain the given accuracy of the solution. Various numerical examples including integral equations and Caputo fractional differential equations are considered to show the performance of our methods
Multidimensional cost analysis of Europe–Asia container transport routes
No full textIn this article, we propose a 3-dimensional framework for evaluating the costs of transporting goods between Europe and Asia, including direct transport, time, and Environmental Costs (ECs). We estimate the costs of alternative container transport routes, including direct sea transport via the Suez Canal Route (SCR) and the Northern Sea Route (NSR); direct rail connections via the Trans-Siberian Rail (TSR) and the Belt and Road Initiative (BRI), and intermodal transport options consisting of rail and sea transport legs. When considering environmental and Inventory Carrying Costs (ICs), the NSR is viable at least seasonally, whereas rail and intermodal alternatives remain more expensive. The results provide a robust estimate of the potential of alternative transport routes and modes. The inclusion of ECs in our analysis provides valuable new information to stakeholders on how to achieve the ambitious environmental goals while also considering the economic viability of different route options in Europe–Asia container trade
Tourists′ local buses ridership and pandemic resilience: a smart card data analysis in Southern Catalonia
No full textThe COVID-19 pandemic′s harmful effects have varied across economic sectors and been particularly adverse for the transport and tourism sectors. This article analyses the pandemic′s impact on tourists′ use of public transport since 2020, including its patterns of change and general decline, using data from more than 40000 smart card holders considered to be summertime users during the peak tourist season in Camp de Tarragona (Catalonia, Spain). 3 model-based clustering analyses of pre-pandemic data from 2019 were performed and used to classify data generated since the pandemic began in 2020. The 1st model included variables of each smart card′s volume of activity, the 2nd model analysed the concentration or spatial dispersion of validated uses of each card, and the 3rd model examined the temporal dimension of the use of smart cards depending on the defined objective. Among the major findings, the number of journeys plunged by 92% in summer 2020 – that is, by far more than throughout the year (64%), which suggests a higher loss of travellers linked with tourism activities (e.g., tourists, 2nd-residence owners, and workers in the tourism sector). Regarding the spatial dimension, patterns with minor reductions related to trips taken within cities (45%) or between major cities (78%). By contrast, travellers with sprawled patterns fell the use by 93%. Last, profiles obtained from variables of a temporary nature presented similar percentages of losses; the most significant losses were for use distributed throughout the day (91.81%) and throughout the night (90.12%). This article provides valuable insights into the pandemic′s varied effects on the use of public transport during peak season at a tourist destination, insights that could inform policies and actions to ensure a more robust response to future crises
Assessing sustainability in BRI railway projects with a novel integrated fuzzy methodology
No full textChina′s Belt and Road Initiative (BRI) and South–South cooperation have received universal concern over sovereignty and debt issue, despite their goal to promote development. In Africa, the rapid expansion of Chinese-funded railway projects has overtaken the development of systematic methods for evaluating sustainability, producing a serious gap in decision-making. To address this challenge, this study proposes an integrated methodological approach, i.e., Delphi, PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA), Logarithmic Percentage Change-Driven Objective Weighting (LOPCOW), and Evaluation Based on Distance from Average Solution (EDAS) methods within the p, q Rung Orthopair Fuzzy Sets (p, q ROFSs) to assess sustainability performance under high uncertainty. The findings indicate that trade facilitation, job creation, debt sustainability, accessibility and connectivity, and safety and security are the most significant criteria for sustainability. Among the projects assessed, the Nairobi – Mombasa Standard Gauge Railway (SGR) project exhibits greatest sustainability performance, followed by the Addis Ababa – Djibouti railway while others indicated weakened outcomes because of restricted freight integration. These findings recommend that future projects should prioritize powerful trade and freight connections, guarantee employment creation and skills transfer, and implementing financing models that safeguard debt sustainability. In doing so, policymakers, managers, and planners can reinforce regional integration, improve the long-term socio-economic advantages, and obtain the operational and financial viability of extensive railway investments in Africa