Search results for: research data

Authors: Bisola Stella Sonde

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Digital innovation has emerged as a pivotal driver of business transformation in the contemporary landscape. This case study research explores the dynamic interplay between digital innovation and the profound metamorphosis of businesses across industries. It delves into the multifaceted dimensions of digital innovation, elucidating its impact on organizational structures, customer experiences, and operational paradigms. The study investigates real-world instances of businesses harnessing digital technologies to enhance their competitiveness, agility, and sustainability. It scrutinizes the strategic adoption of digital platforms, data analytics, artificial intelligence, and emerging technologies as catalysts for transformative change. The cases encompass a diverse spectrum of industries, spanning from traditional enterprises to disruptive startups, offering insights into the universal relevance of digital innovation. Moreover, the research scrutinizes the challenges and opportunities posed by the digital era, shedding light on the intricacies of managing cultural shifts, data privacy, and cybersecurity concerns in the pursuit of innovation. It unveils the strategies that organizations employ to adapt, thrive, and lead in the era of digital disruption. In summary, this case study research underscores the imperative of embracing digital innovation as a cornerstone of business transformation. It offers a comprehensive exploration of the contemporary digital landscape, offering valuable lessons for organizations striving to navigate the ever-evolving terrain of the digital age.

Keywords: business transformation, digital innovation, emerging technologies, organizational structures

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Authors: Artem Nuriev, Olga Zaitseva

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This paper is devoted to the study of a viscous incompressible flow around a circular cylinder performing harmonic oscillations, especially the steady streaming phenomenon. The research methodology is based on the asymptotic explanation method combined with the computational bifurcation analysis. Present studies allow to identify several regimes of the secondary streaming with different flow structures. The results of the research are in good agreement with experimental and numerical simulation data.

Keywords: oscillating cylinder, secondary streaming, flow regimes, asymptotic and bifurcation analysis

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Authors: Mubarak Saadu Nabunkari, Abdullahi Abdu Ibrahim, Muhammad Ilyas

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This study looks at how Internet of Things (IoT) devices are used in healthcare to monitor and treat patients better. However, using these devices in healthcare comes with security problems. The research explores using Security Information and Event Management (SIEM) systems with healthcare IoT devices to solve these security challenges. Reviewing existing literature shows the current state of IoT security and emphasizes the need for better protection. The main worry is that healthcare IoT devices can be easily hacked, putting patient data and device functionality at risk. To address this, the research suggests a detailed security framework designed for these devices. This framework, based on literature and best practices, includes important security measures like authentication, data encryption, access controls, and anomaly detection. Adding SIEM systems to this framework helps detect threats in real time and respond quickly to incidents, making healthcare IoT devices more secure. The study highlights the importance of this integration and offers guidance for implementing healthcare IoT securely, efficiently, and effectively.

Keywords: cyber security, threat intelligence, forensics, heath care

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Authors: Muhadam Labolo, Mughny Ibtisyam Mukhlis, Zulkarnaen, Safira Maulida Rahman Soulisa

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This research is motivated by one of the functions of government is a regulatory function. Aceh Province, especially in Banda Aceh City has special autonomy, one of them is in the application of Islamic law, but when the law implemented to the citizen, there are many problems happens. One of the problems faced by the Government and people of Banda Aceh was Seclusion. Seclusion/nasty silent act between two people mukallafor more of the opposite sex who is not mahram or without marriage. This study aims to determine and analyze how the effectiveness of the policy as well as enabling and inhibiting factors of Qanun Number 14 of 2003 On Khalwat (nasty) in sharia Islam Islamic law in the city of Banda Aceh. This type of research is qualitative research method is a descriptive and inductive approach. The source of data used is People, Problem, Phenomenon, and programs, while the data collection through field studies and literature such as interviews, observation, and documentation. The results of this study were analyzed by using data reduction, display data, conclusions, and verification. The results showed that the Qanun Number 14 of 2003 on Khalwat (nasty) in the establishment of Islamic law in Banda Aceh is still not effective. It is seen from the high number of violations seclusion committed by Banda Aceh citizen, especially among teenagers, lack of socialization, as well as a lack of budgetary support for the implementation of Islamic Law in Banda Aceh. The supporting factors are 1) Coordination and communication among agencies had been walking steadily. 2) Facilities and infrastructure Syar'iah Court of Banda Aceh and the Office of Sharia Islam Banda Aceh that very good. 3) The Cultural majority of the people of Banda Aceh that support. Inhibiting factors: 1) There are no written duties of each institution for the prosecution case Seclusion. 2) The lack of socialization programs. 3) Lack of facilities and infrastructure Municipal Police Unit and the WH less. 4) Lack of control by the family. 5) The absence of training for officials Municipal Police Units and the Wilayatul Hisbah Banda Aceh.

Keywords: effectiveness, Islamic Sharia, Khalwat, Qanun

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Authors: Kwaku Damoah

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This study presents a comprehensive data-driven analysis to understand the evolution of adverse events (AEs) in pharmacovigilance. Utilizing data from the FDA Adverse Event Reporting System (FAERS), we employed three analytical methods: rank-based, frequency-based, and percentage change analyses. These methods assessed temporal trends and patterns in AE reporting, focusing on various drug-active ingredients and patient demographics. Our findings reveal significant trends in AE occurrences, with both increasing and decreasing patterns from 2000 to 2023. This research highlights the importance of continuous monitoring and advanced analysis in pharmacovigilance, offering valuable insights for healthcare professionals and policymakers to enhance drug safety.

Keywords: event analysis, FDA adverse event reporting system, pharmacovigilance, temporal trend analysis

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Authors: Giulia Leoni, Cristina Florio

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The paper aims to investigate the factors driving the increasing alignment of Italian earnings management (EM) research to US research on the same field. After characterizing the progressive similarity of Italian EM research with respect to US one by means of an historical comparison, the paper relies on a subsequent secondary source analysis to detect the possible causes of said alignment. Once identified that the alignment increased along three subsequent periods, the paper analyses and discusses this incremental similarity according to new institutional sociology (NIS) and highlights the presence of different combination of isomorphic pressures that help explaining this incremental similarity. The paper contributes to the institutional literature by providing evidence of isomorphism in academic research; it also contributes to accounting research by indicating the forces that are able to drive change and development in accounting research at national and international level. The paper also enlarges the explanatory value of NIS in alternative contexts, like academic accounting research.

Keywords: accounting research, earnings management, international comparison, Italy, new institutional sociology, US

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Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

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It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

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Authors: Rais Yusoh, Rosli Saad, Mokhtar Saidin, Fauzi Andika, Sabiu Bala Muhammad

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Resistivity and seismic refraction profiling have become a common method in pre-investigations for visualizing subsurface structure. The integration of the methods could reduce an interpretation ambiguity. Both methods have their individual software packages for data inversion, but potential to combine certain geophysical methods are restricted; however, the research algorithms that have this functionality was existed and are evaluated personally. The interpretation of subsurface were improve by combining inversion data from both methods by influence each other models using closure coupling; thus, by implementing both methods to support each other which could improve the subsurface interpretation. These methods were applied on a field dataset from a pre-investigation for archeology in finding the ancient river. There were no major changes in the inverted model by combining data inversion for this archetype which probably due to complex geology. The combine data analysis provides an additional technique for interpretation such as an alluvium, which can have strong influence on the ancient river findings.

Keywords: ancient river, combine inversion, resistivity, seismic refraction

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Authors: Mohd Adib Abd Muin, Shuhairimi Abdullah, Azizan Bahari

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Problem: The research problem is lacking of model on social entrepreneurship that focus on Islamic perspective. Objective: The objective of this paper is to analyse the existing model on social entrepreneurship and to identify the research gap on Islamic perspective from existing models. Research Methodology: The research method used in this study is literature review and comparative analysis from 6 existing models of social entrepreneurship. Finding: The research finding shows that 6 existing models on social entrepreneurship has been analysed and it shows that the existing models on social entrepreneurship do not emphasize on Islamic perspective.

Keywords: social entrepreneurship, Islamic perspective, research gap, business management

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Authors: Seyed Reza Agha Seyed Hosseini, Nicolas Hamelin

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Many marketing executives are looking for a comprehensive plan for delivering quality services and products that will create a distinct and unforgettable long-term experience for customers in dealing with their brand. Various brand management experts believe that a company looking to enhance its brand experience in the minds of customers should have a plan to increase customer satisfaction as well as customer loyalty. The purpose of this research was to investigate the role of brand experience in customer satisfaction and customer loyalty in Ayandeh Bank branches in Tehran. The study employed a quantitative methodology. For data gathering, a questionnaire was utilised to measure all the variables of the research. The statistical population of the study consisted of all the customers of Ayandeh Bank branches in Tehran, and the study data was gathered from 400 respondents. The findings indicate that brand experience has a direct and meaningful impact on customer satisfaction and customer loyalty, and, furthermore, that customer satisfaction has a direct and significant effect on customer loyalty in the branches of Ayandeh Bank in Tehran.

Keywords: brand experience, customer satisfaction, customer loyalty, bank

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Somkiat Korbuakaew, Bongkoch Puttawong

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This research aims to study the level of e-office system competence of Suan Sunandha Rajabhat University graded by age, education background, position and work experience. Sample of this research is 291 staff at Suan Sunandha Rajabhat University. Data were collected by questionnaire. Statistics used in the research are percentage, mean and standard deviation. The result shows that the overall competence of E-office System of the university staff is at average level. When considered in each aspect, it was found that competency level for creating-forwarding-signing documents is high, while competency level for booking meeting rooms, requesting for transportation service, blackboard system, public relations and making appointment and meeting are average.

Keywords: competence, e-office, education background, work experience

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Authors: Xiaoyu Sun

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In recent years, the rapid development of Artificial Intelligence (AI) has extensively promoted medicine, pharmaceutical, and other related fields. The medical research and development of artificial intelligence by scientific and commercial organizations are on the fast track. The ethics review is one of the critical procedures of registration to get the products approved and launched. However, the SOPs for ethics review is not enough to guide the healthy and rapid development of artificial intelligence in healthcare in China. Ethical Review Measures for Biomedical Research Involving Human Beings was enacted by the National Health Commission of the People's Republic of China (NHC) on December 1st, 2016. However, from a legislative design perspective, it was neither updated timely nor in line with the trends of AI international development. Therefore, it was great that NHC published a consultation paper on the updated version on March 16th, 2021. Based on the most updated laws and regulations in the States and EU, and in-depth-interviewed 11 subject matter experts in China, including lawmakers, regulators, and key members of ethics review committees, heads of Regulatory Affairs in SaMD industry, and data scientists, several suggestions were proposed on top of the updated version. Although the new version indicated that the Ethics Review Committees need to be created by National, Provincial and individual institute levels, the review authorities of different levels were not clarified. The suggestion is that the precise scope of review authorities for each level should be identified based on Risk Analysis and Management Model, such as the complicated leading technology, gene editing, should be reviewed by National Ethics Review Committees, it will be the job of individual institute Ethics Review Committees to review and approve the clinical study with less risk such as an innovative cream to treat acne. Furthermore, to standardize the research and development of artificial intelligence in healthcare in the age of AI, more clear guidance should be given to data security in the layers of data, algorithm, and application in the process of ethics review. In addition, transparency and responsibility, as two of six principles in the Rome Call for AI Ethics, could be further strengthened in the updated version. It is the shared goal among all countries to manage well and develop AI to benefit human beings. Learned from the other countries who have more learning and experience, China could be one of the most advanced countries in artificial intelligence in healthcare.

Keywords: biomedical research involving human beings, data security, ethics committees, ethical review, medical artificial intelligence

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Authors: Suzanne Overstreet-Juenke

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Disproportionate minority contact (DMC) is a salient issue that has been found at every stage of the decision-making process in the juvenile justice system. Existing research indicates that DMC influences adjudication for drug, property, and personal crimes. Because intimate partner violence (IPV) is a major public health problem and global concern, the current study examines DMC at adjudication among youth charged for crimes of interpersonal violence. This research uses administrative, Court Designated Worker (CDW) data collected from 2014 to 2016. The results are contextualized using Steffensmeier’s version of focal concerns theory of judicial decision-making. This study assesses race and two seriousness of offense measures to establish whether a link exists between race and adjudication. The results of the study is similar to prior research on the topic. These results are discussed in terms of policy implications, limitations, and future research.

Keywords: race, disproportionate minority contact, focal concerns theory, juvenile

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Authors: Esmail Sadipour

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The use of social networks is increasing day by day in all societies. The purpose of this research was to know the relationship between the use of social networks (Instagram, WhatsApp, and Telegram) with executive functions and academic performance in first-year female high school students. This research was applied in terms of purpose, quantitative in terms of data type, and correlational in terms of technique. The population of this research consisted of all female high school students in the first year of district 2 of Tehran. Using Green's formula, the sample size of 150 people was determined and selected by cluster random method. In this way, from all 17 high schools in district 2 of Tehran, 5 high schools were selected by a simple random method and then one class was selected from each high school, and a total of 155 students were selected. To measure the use of social networks, a researcher-made questionnaire was used, the Barclay test (2012) was used for executive functions, and last semester's GPA was used for academic performance. Pearson's correlation coefficient and multivariate regression were used to analyze the data. The results showed that there is a negative relationship between the amount of use of social networks and self-control, self-motivation and time self-management. In other words, the more the use of social networks, the fewer executive functions of students, self-control, self-motivation, and self-management of their time. Also, with the increase in the use of social networks, the academic performance of students has decreased.

Keywords: social networks, executive function, academic performance, working memory

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Olivia Rybak-Karkosz

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This paper aims to present the results of scientific research on family resemblance in the handwriting of painters. Such a problem is known in handwriting analysis, but it was never a research subject in the scope of painters' signatures on works of art. For this research, the author chose Jacek, and Rafał Malczewski (father and son) as many of their paintings are in museums, and most of them are signed. The aim was to create a catalogue of traits similar to the handwriting of both artists. Such data could be helpful for the expert’s opinion in the decision-making process to establish whether the signature is authentic and, if so, whether it is the artist whose signature is analysed, not the other family member. There are known examples of relatives of the artists who signed their works. Many of them were artists themselves. For instance Andrzej Wróblewski’s mother, Krystyna was a printmaker. To save his legacy, she signed many of her son’s works after his death using his name. This research methodology consisted of completing representative samples of signatures of both artists, which were collected in selected Polish museums. Then a catalogue of traits was created using a forensic handwriting graphic-comparative method (graphic method). The paper contains a concluding statement that it could be one of the elements of research in an expert’s analysis of the authenticity of the signature on paintings.

Keywords: artist’s signatures, authenticity of an artwork, forensic handwriting analysis, graphic-comparative method

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Authors: Shunyi Yang, Jingjing Yan, Siyu Dong, Xiangguo Cui

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Current architectural façade design practices incorporate various daylighting and solar radiation analysis methods. These emphasize the impact of geometry on façade design. There is scope to extend this knowledge into methods that address material translucency, porosity, and form. Such approaches can also achieve these conditions through adaptive robotic manufacturing approaches that exploit material dynamics within the design, and alleviate fabrication waste from molds, ultimately accelerating the autonomous manufacturing system. Besides analyzing the environmental solar radiant in building facade design, there is also a vacancy research area of how lighting effects can be precisely controlled by engaging the instant real-time data-driven robot control and manipulating the material properties. Ceramics carries a wide range of transmittance and deformation potentials for robotics control with the research of its material property. This paper presents one semi-autonomous system that engages with real-time data-driven robotics control, hardware kit design, environmental building studies, human interaction, and exploratory research and experiments. Our objectives are to investigate the relationship between different clay bodies or ceramics’ physio-material properties and their transmittance; to explore the feedback system of instant lighting data in robotic fabrication to achieve precise lighting effect; to design the sufficient end effector and robot behaviors for different stages of deformation. We experiment with architectural clay, as the material of the façade that is potentially translucent at a certain stage can respond to light. Studying the relationship between form, material properties, and porosity can help create different interior and exterior light effects and provide façade solutions for specific architectural functions. The key idea is to maximize the utilization of in-progress robotics fabrication and ceramics materiality to create a highly integrated autonomous system for lighting facade design and manufacture.

Keywords: light transmittance, data-driven fabrication, computational design, computer vision, gamification for manufacturing

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Authors: Bitopi Dutta

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Development Induced Displacement (DID) of subaltern groups has been an issue of intense debate in India. This research will do a gender analysis of displacement induced by the mining projects in tribal indigenous societies of North East India, centering on the primary research question which is 'How does DID reorder gendered relationship in tribal matrilineal societies?' This paper will not focus primarily on the impacts of the displacement induced by coal mining on indigenous tribal women in the North East India; it will rather study 'what' are the processes that lead to these transformations and 'how' do they operate. In doing so, the paper will locate the cracks in traditional social systems that the discourse of displacement manipulates for its own benefit. DID in this sense will not only be understood as only physical displacement, but also as social and cultural displacement. The study will cover one matrilineal tribe in the state of Meghalaya in the North East India affected by several coal mining projects in the last 30 years. In-depth unstructured interviews used to collect life narratives will be the primary mode of data collection because the indigenous culture of the tribes in Meghalaya, including the matrilineal tribes, is based on oral history where knowledge and experiences produced under a tradition of oral history exist in a continuum. This is unlike modern societies which produce knowledge in a compartmentalized system. An interview guide designed around specific themes will be used rather than specific questions to ensure the flow of narratives from the interviewee. In addition to this, a number of focus groups will be held. The data collected through the life narrative will be supplemented and contextualized through documentary research using government data, and local media sources of the region.

Keywords: displacement, gender-relations, matriliny, mining

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Authors: Masomeh Jamshid Nejad

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Nowadays, statistical literacy is no longer a necessary skill but an essential skill with broad applications across diverse fields, especially in operational decision areas such as business management, finance, and economics. As such, learning and deep understanding of statistical concepts are essential in the context of business studies. One of the crucial topics in statistical theory and its application is the normal distribution, often called a bell-shaped curve. To interpret data and conduct hypothesis tests, comprehending the properties of normal distribution (the mean and standard deviation) is essential for business students. This requires undergraduate students in the field of economics and business management to visualize and work with data following a normal distribution. Since technology is interconnected with education these days, it is important to teach statistics topics in the context of Python, R-studio, and Microsoft Excel to undergraduate students. This research endeavours to shed light on the effect of Excel-based instruction on learners’ knowledge of statistics, specifically the central concept of normal distribution. As such, two groups of undergraduate students (from the Business Management program) were compared in this research study. One group underwent Excel-based instruction and another group relied only on traditional teaching methods. We analyzed experiential data and BBA participants’ responses to statistic-related questions focusing on the normal distribution, including its key attributes, such as the mean and standard deviation. The results of our study indicate that exposing students to Excel-based learning supports learners in comprehending statistical concepts more effectively compared with the other group of learners (teaching with the traditional method). In addition, students in the context of Excel-based instruction showed ability in picturing and interpreting data concentrated on normal distribution.

Keywords: statistics, excel-based instruction, data visualization, pedagogy

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Authors: Pei-Ti Hsu, I-Ju Chen, Jeu-Jung Chen, Cheng-Fen Chang, Shiu-Yan Yang

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Taiwan now is an aging society Research on the elderly should not be confined to caring for seniors, but should also be focused on ways to improve health and the quality of life. Senior citizens who participate in volunteer services could become less lonely, have new growth opportunities, and regain a sense of accomplishment. Thus, the question of how to get the elderly to participate in volunteer service is worth exploring. Apply the Transtheoretical Model to understand stages of change in regular volunteer service and voluntary service behaviour among the seniors. 1525 adults over the age of 65 from the Renai district of Keelung City were interviewed. The research tool was a self-constructed questionnaire and individual interviews were conducted to collect data. Then the data was processed and analyzed using the IBM SPSS Statistics 20 (Windows version) statistical software program. In the past six months, research subjects averaged 9.92 days of volunteer services. A majority of these elderly individuals had no intention to change their regular volunteer services. We discovered that during the maintenance stage, the self-efficacy for volunteer services was higher than during all other stages, but self-perceived barriers were less during the preparation stage and action stage. Self-perceived benefits were found to have an important predictive power for those with regular volunteer service behaviors in the previous stage, and self-efficacy was found to have an important predictive power for those with regular volunteer service behaviors in later stages. The research results support the conclusion that community nursing staff should group elders based on their regular volunteer services change stages and design appropriate behavioral change strategies.

Keywords: seniors, stages of change in regular volunteer services, volunteer service behavior, self-efficacy, self-perceived benefits

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Authors: Busra Gulnihan Dascıoglu, Ozalp Vayvay, Zeynep Tugce Kalender

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Humanitarian supply chain management has gain popularity in recent years in research fields. The aim of this paper is to review the literature on humanitarian operations and crisis/disaster management from 2010 to latest researches in order to identify the current research and to provide direction for future research in this growing field. Researches are classified considering the research publication year, research fields. Articles from humanitarian supply chain management were reviewed, keywords were identified within a disaster management lifecycle framework. Research gaps are identified for future research areas.

Keywords: crisis, disaster, humanitarian supply chain management, relief operations

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Muhammad Sulman, Tabinda Khurshid, Afsheen Masood

Abstract:

The current research focused on determining the factors that determine the brand loyalty in consumers. It was hypothesized that there are certain demographical features that lead the consumers to adhere more towards certain brands. Cross-sectional research design was used. The sample for the current research comprised of participants (N=500) from age group 16 to 55 years. The data was collected through self-constructed demographic questionnaire as well as from a self-constructed Brand Loyalty Questionnaire. Brand Loyalty Questionnaire was adapted after taking permission from researchers. A pilot study was conducted to chalk out all the ambiguities of the questionnaire. The final version was administered on 250 participants. The descriptive and inferential analyses were carried on through SPSS version 24.00 to explore the factors that determine Brand Loyalty. The findings revealed that there is a relationship between brand loyalty and brand loyalty demographics and certain factors emerged as significant predictors of brand loyalty in young and middle aged consumers. The research findings carry strong implications for organizational and consumer psychologists in particular and for professionals in marketing and policy making in general.

Keywords: consumers, consumer psychologists, marketing, organizational, policy making

Procedia PDF Downloads 268

Authors: Jan-Peter Mund, Christian Kind

Abstract:

In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

Procedia PDF Downloads 84

Authors: Sudaporn Arundee

Abstract:

The purposes of this research were to study in three areas: (1) to study political understanding and participating of the constitutional monarchy, (2) to study the level of participation. This paper drew upon data collected from 395 Dusit residents by using questionnaire. In addition, a simple random sampling was utilized to collect data. The findings revealed that 94 percent of respondents had a very good understanding of constitution monarchy with a mean of 4.8. However, the respondents overall had a very low level of participation with the mean score of 1.69 and standard deviation of .719.

Keywords: political participation, constitutional monarchy, management and social sciences

Procedia PDF Downloads 248

Authors: Abdullah Pandang, Mantasiah Rivai, Nur Fadhilah Umar, Azam Arifyadi

Abstract:

This study aims to measure the validity of the politeness behaviour scale and obtain a model that fits the scale. The researcher developed the Politeness Behavior on Communicating (PBC) scale. The research method uses descriptive quantitative by developing the PBC scale. The population in this study were students in three provinces, namely South Sulawesi, West Sulawesi, and Central Sulawesi, recorded in the 2022/2023 academic year. The sampling technique used stratified random sampling by determining the number of samples using the Slovin formula. The sample of this research is 1200 students. This research instrument uses the PBC scale, which consists of 5 (five) indicators: self-regulation of compensation behaviour, self-efficacy of compensation behaviour, fulfilment of social expectations, positive feedback, and no strings attached. The PBC scale consists of 34 statement items. The data analysis technique is divided into two types: the validity test on the correlated item values and the item reliability test referring to Cronbach's and McDonald's alpha standards using the JASP application. Furthermore, the data were analyzed using confirmatory factor analysis (CFA) and exploratory factor analysis (EFA). The results showed that the adaptation of the Politeness Behavior on Communicating (PBC) scale was on the Fit Index with a chi-square value (711,800/375), RMSEA (0.53), GFI (0.990), CFI (0.987), GFI (0.985).

Keywords: polite behavior in communicating, positive communication, exploration factor analysis, confirmatory factor analysis

Procedia PDF Downloads 117

Authors: Somsak Klaysung

Abstract:

This study aims to investigate the comparison of brands equity between Samsung and Apple from students of Suan Sunandha Rajabhat University. The research method will using quantitative research, data was collected by questionnaires distributed to communication of arts students in the faculty of management science of Suan Sunandha Rajabhat University for 100 samples by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic is t-test for hypothesis testing. The results showed that brands equity between Apple and Samsung brand have the ability to recognize brand from the customer by perceived value of the uniqueness of brand and recall when in a situation that must be purchased (Salience), which is the lowest level in branding and consumers can recognize the capacity of the product (Judgment) and opinions about the quality and reliability when it comes to mobile phones Apple and Samsung brand are not different.

Keywords: Apple and Samsung brand, brand equity, judgment, performance, resonance, salience

Procedia PDF Downloads 211