Hasil untuk "Commerce"

B. Mahadevan

Anol Bhattacherjee

Chang Liu, Jack T. Marchewka, June Lu et al.

Yao-bin Lu, Ling Zhao, Bin Wang

Dianne Cyr, Milena M. Head, Alex Ivanov

M. Ghobakhloo, Daniel Arias-Aranda, Jose Benitez-Amado

Yi-Shun Wang

M. Eid

Toh Tsu Wei, G. Marthandan, A. Chong et al.

Anh Nu Nguyet Nguyen, Ninh Van Nguyen

Purpose: The objective of this study is to explore and comprehend the factors from the perceived environment that impact travellers' attitudes and trust in agritourism at farms integrated with aquaculture, which have been creatively adapted for tourism purposes. These findings contribute to understanding how agritourism fosters rural innovation and sustainable development by transforming traditional agricultural practices into diversified tourism experiences. The findings of the study could demonstrate that certain outcomes play a crucial role in the successful innovation of rural areas. Methodology/design/approach: The study extensively utilized the Theory of Planned Behavior framework to develop its measurement constructs. Data collection occurred in regions where tourists frequented farms that combine aquaculture with traditional farming practices, yielding a total sample size of 332 respondents. The data were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, employing the SmartPLS software version 4.0.9.2. Results: The results identified factors perceived environmentally positive influence on personal perception. Attitude and trust were found to mediate the relationships between perceived environment and revisit intention, with the mediating effect of attitude being stronger than that of trust. Originality of the research: Visitor attitudes significantly determine the innovation from making farms, orchards, aquaculture areas to the experiential tourism business. Successful innovations, such as enhancing rural incomes and sustaining agricultural livelihoods through agritourism transformation, are significantly driven by positive visitor perceptions and trust.

Dimas Mukhtar, Ali Muhammad

The purpose of this study was to determine the communication strategy of correctional guardians in shaping the self-concept of child prisoners and to find out the factors that cause negative self-concept in child prisoners while undergoing coaching at the Tangerang Class I Child Special Development Institution. This research uses qualitative research methods with a phenomenological approach. This study concludes that the correctional guardian, in developing a communication strategy, uses the stages of knowing the audience, compiling messages, determining methods, and using media. However, in its implementation, improvement efforts are needed so that the formation of a positive self-concept in child prisoners becomes more optimal. The factors that form the negative self-concept of child prisoners while undergoing coaching are social stigma, lack of closeness with parents, lack of access to psychological support, and not forming warm and personal communication and connections with correctional guardians. It is recommended that the Special Development Institute for Children Class I, Tangerang, in this case, can carry out special training for correctional guardians in communicating effectively with child prisoners. Keywords : Communication Strategy; Self-Concept; Child Prisoners; Correctional Guardians

Ognjen Radišić-Aberger, Peter Burggräf, Fabian Steinberg et al.

By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering change (EC) process. Here, failing to adhere to planned implementation dates can have severe impacts on assembly lines, and it is paramount that potential negative cases are identified as early as possible. Current PBPM research, however, has seldomly investigated the predictive performance of machine learning approaches and their applicability at early process steps, let alone for the EC process. In our research, we show that given adequate feature encoding, shallow learners can accurately predict schedule adherence after process initialisation. Based on EC data from an automotive manufacturer, we provide a case sensitive performance overview on algorithm-encoding combinations. For that, three algorithms (XGBoost, Random Forest, LSTM) were combined with four encoding techniques. The encoding techniques used were the two common aggregation-based and index-based last state encoding, and two new combinations of these, which we term advanced aggregation-based and complex aggregation-based encoding. The study indicates that XGBoost-index-encoded approaches outclass regarding average predictive performance, whereas Random-Forest-aggregation-encoded approaches perform better regarding temporal stability due to reduced influence by dynamic features. Our research provides a case-based reasoning approach for deciding on which algorithm-encoding combination and evaluation metrics to apply. In doing so, we provide a blueprint for an early warning and monitoring method within the EC process and other similarly complex processes.

Norah Saleh Alghamdi, Mohammed Zakariah, Achyut Shankar et al.

Heart disease continues to be a prominent cause of death globally, emphasizing the critical requirement for precise prediction techniques and prompt therapies. This research presents a new method that utilizes the collective capabilities of autoencoder and DenseNet architectures to predict heart illness. Our study is based on the Heart Disease UCI Cleveland dataset, which includes 13 variables that cover clinical and demographic parameters such as age, sex, cholesterol levels, and exercise-induced angina. The dataset presents issues due to its varied attribute types, including category and numerical variables. Furthermore, our approach tackles these difficulties by utilizing a dense autoencoder model, which produced exceptional outcomes. The Model attained a mean accuracy of 99.67% on the Heart Disease UCI Cleveland dataset. Further testing showed it was resilient, with a test accuracy of 99.99%. In addition, the Model demonstrated outstanding macro precision, macro recall, and macro F1 score, with percentages of 99.98%, 99.97%, and 99.96%, respectively. In addition, our results indicate that combining autoencoder and DenseNet designs shows potential for predicting cardiac disease, with substantial enhancements in accuracy and performance metrics compared to current approaches. This methodology can improve clinical decision-making and patient outcomes in cardiovascular care by accurately finding and defining complex patterns within the data. Notwithstanding these encouraging outcomes, our investigation has constraints. The specific attributes of the dataset utilized may limit the applicability of our findings. Subsequent studies could examine the suitability of our method for various datasets and analyze supplementary variables that may improve forecast precision. Furthermore, it is necessary to conduct prospective validation studies to evaluate our strategy’s practical effectiveness in clinical environments.

Ryan Joseph CALINAO, Ryan GAMOSO

The study explores the influence of vividness, content quality, and system quality in virtual reality (VR) experiences on guests’ behavioural intentions in the hotel industry in the National Capital Region. It specifically examines how these factors affect guests’ engagement and decision-making processes. Using the Partial Least Square with Hierarchical Component Model Analysis, the results highlight the importance of immersive and high-quality VR content in enhancing guest experiences and influencing their future behaviours, such as revisiting or recommending the hotels. Additionally, the study underscores the role of system quality in ensuring a seamless and engaging VR experience. The findings through the use of the mediating effect, suggest that investment in superior VR technology can be a strategic tool for hotels to differentiate themselves in a competitive market and align with evolving consumer preferences as well as the cognitive absorption of the hotel guests.

Paulo Duarte, Cristina Estevão, Ana María Campón-Cerro et al.

The hospitality and travel sector has been one of the most affected sectors by Covid-19, which has resulted in a significant increase in the literature addressing the impact of the health crisis on tourism activities and tourists’ perceptions and behaviours. Traditionally, socio-demographic variables have been instrumental in understanding consumers’ needs and desires. However, during the pandemic, it has been unveiled that social and economic profiles have started to influence how tourists make decisions. Since studies on the changes in hotel choice during and after Covid-19 are still scarce, this article aims to assess the influence of socio-demographic variables on hotel choice based on data collected during the peak phase of the Covid-19 pandemic. A quantitative study was conducted using an online questionnaire that reached an international sample of 1113 individuals. The ANOVA and the t-test analysis results point out that socio-demographic variables under study are responsible for several differences in the evaluation of hotels. These findings reinforce socio-demographic attributes’ capability to understand customers’ preferences and decision-making despite the context.

Nikola Stakić, Lidija Barjaktarović

Research Question: The paper investigates various ESG (Environmental, Social and Governance) related practices within the leading European banking groups (BGs) present in Serbian banking sector (SBS), including their financial performances. Motivation: The goal of the research was to explore approach habits to sustainable business between the leading European BGs present in the SBS. It should have in mind that SBS are in compliance with their headquarter/major shareholder. The rising global worry about ESG issues and its overall impact forces banking business model to use holistic approach, including the plug-in of sustainability and responsible behaviours. The paper draws on sustainable banking surveys of Aracil et al. (2021) and Stefanovic et al. (2021) in Business-Case domain, applying them on SBS with introduction of 3 comparable sustainable indicators (environmental loans, reduction of tCO2, community investments). It is the first study which takes in respect ESG elements of principal BGs in SBS, with the comprehensive analysis of subject’s legislative framework. Idea: The core idea of the paper was to empirically investigate the sustainable practice in SBS, based on different banks’ reports and publications, including disclosed ESG indicators. E-loans (EL) and profitability indicators were examined individually as dependent variables since other ESG and financial (solvency, financial stability and efficiency) variables served as independent ones. Data: Analysis was conducted using data of 4 European active BGs on SBS, in the period of 2015-2021, due to fact that there was the lack of quantitative metrics and non-uniform reporting practice. Tools: Statistical analysis (descriptive statistics, correlation, regression test utilizing ANOVA), were used to draw conclusions about the relationship variables, particularly correlation between ESG variables and profitability ratios. Findings: The study showed for analyzed BGs that: (1) they had unique ESG practice, based on global standards and EBA (European Banking Authority) regulation; (2) they had good credit risk management including E-risks in practice; (3) sustainability had significant inter-connectedness among ESG constituents, as well as with some of the financial metrics; (4) statistical significance of ESG metrics for EL; however similar findings are missing when it comes to association between financial performance (in terms of profitability) and ESG practice. Contribution: The paper introduces and expands existing research related to sustainable banking on SBS for further education of all stakeholders.

Francisco Segundo Mogollón García, Linda Diana Becerra Rojas, Sonia Magali Núñez Puse et al.

El objetivo propuesto para esta investigación consistió en explicar cómo el acoso laboral puede convertirse en un elemento predictivo de la depresión en el sector Mype Región Piura-Perú. Para lograr dicho objetivo se utilizó un enfoque cuantitativo, empleando métodos matemáticos para la obtención de los resultados, apoyándose de un modelo de ecuaciones estructurales – SEM, en la que participaron 379 empresas (entre dueños, administradores y/o responsables). Los datos fueron cargados en SPSS (para análisis descriptivo) y Smartpls (modelamiento SEM), cuyos resultados estadísticos indicaron que las pruebas de normalidad, fiabilidad, validez (discriminante, convergente) y las pruebas de varianza, han respondido de manera singular (satisfactoria) al planteamiento del estudio, concluyendo que el acoso laboral se comporta de manera favorable como elemento predictivo de la depresión, es decir, el modelamiento basado en ecuaciones estructurales responde satisfactoriamente con la postura del investigador.

Ioana-Sorina ANDREICA (MIHUT), Liviu-Daniel DECEANU

The last three years were characterized by a climate of drastic change due to a cumulus of disturbances and crises, namely the COVID-19 pandemic, inflation, energy crisis, military conflicts, banking fragilities, populism, disinformation, and the idea of deglobalization. These types of events may be interpretated either as antecedents of new and complex categories of risks or as stimulus for certain risks that have long been ignored. One central focus for worldwide policymakers is presently the country risk with all its components (sovereign risk, political risk, market risk, or systemic risk). Furthermore, due to the increase in public and private debt, the risks to which economies are exposed have multiplied. Is this the end of an era or just a temporary disequilibrium? This is one of the key questions among economists, academics, and policy makers around the world. The main purpose of this research is to analyse whether the Russian invasion of Ukraine negatively impacted the country risk of countries situated in the geographical proximity of the conflict area (Romania, Bulgaria, Estonia, Hungary, Czechia, Latvia, Lithuania, Poland, and Slovakia), as well as to determine whether relevant macroeconomic indicators such as debt/GDP, GDP/capita, inflation, or trade openness were deteriorated due to the war. The findings of this research reveal that all the analysed macroeconomic indicators deteriorated as a consequence of the high degree of uncertainty concerning the future economic prospects of these countries, especially inflation and debt/GDP. The results also indicate that the country ratings of the investigated group of countries were severely impacted by the Russian invasion of Ukraine. Although data corresponding for year 2023 show a slight improvement, the existing uncertainty continues to generate a disruptive effect on the markets.

Donghee Don Shin

Social commerce (s-commerce), a new form of commerce that involves using social media, has been rapidly developing. While the adoption of social technology is well studied, new theoretical development is needed to explain the specific characteristics of s-commerce and their interactions with the user. This study analyses consumer behaviours in s-commerce, focusing on the role of social influence in s-commerce. A model is created to validate the relationship between the subjective norm and trust, social support, attitude, and intention. The results of the model show that the subjective norm is a key behavioural antecedent to use s-commerce. In the extended model, the moderating and mediating effects of the subjective norm on relationships among variables were found to be significant. The new set of variables adapted from previous research can be s-commerce-specific, acting as factors that enhance attitudes and behavioural intentions in s-commerce. The implications of the findings are discussed in terms of building a theory of social interaction and providing practical insights into developing user-centered s-commerce as a platform.

Vitalii Reikin

Стаття присвячена феномену харизматичного лідерства. Представлено різні дефініції досліджуваного поняття. Констатується факт існування термінологічної мозаїчності та відсутності універсального наукового підходу щодо дослідження міждисциплінарного феномену «харизматичне лідерство». Подано сукупність домінант, які в комплексі утворюють універсальне «ядро» харизматичного лідера: успішність, що може бути як причиною, так і наслідком реалізації особистісного потенціалу; володіння владою, що дає можливість впливати на оточення; наявність оригінального менталітету, що розкривається через антистереотипність, неповторність та унікальність, новаторський життєвий стиль. Виокремлено теорію трансформаційного лідерства, що грунтується на біхевіористичному підході та вирізняється методологічною розробленістю. Акцентовано увагу на поліаспектності феномену харизматичного лідерства, що не розділяється на автономні елементи. Оскільки харизматичні якості лідера проявляються, насамперед, на емоційному рівні, доводиться факт належності цього феномену переважно не до раціональної сфери із парадигмою «homo economicus», а до сучасного наукового мейнстриму: поведінкової економіки. Зосереджено увагу також на негативних аспектах харизматичного лідерства: маніпулювання, псевдохаризматичність, висока ймовірність узурації влади. В публікації здійснена спроба вирішення ключової проблеми: харизматичні ознаки лідера притаманні йому виключно від народження, чи є можливість набути їх в процесі особистого розвитку? Наведено авторський підхід: наявність природних харизматичних задатків в лідера є обов'язковою, але недостатньою умовою; повноцінна самореалізація харизматичної особи підлягає еволюційному коригуванню шляхом синтезу вроджених та набутих лідерських якостей. Тобто харизматичність ідентифікується і як природня якість, і як набута.