Customer Characteristics Research Articles

Exploring the impact of robot interaction on learning engagement: a comparative study of two multi-modal robots

In recent years, there has been a growing interest in using robots within educational environments due to their potential to augment student engagement and motivation. However, current research has not adequately addressed the effectiveness of these robots in facilitating inclusive learning for diverse student populations, particularly those with dyslexia. This study proposes an inclusive learning system developed on two multi-modal robots, Kebbi and Minibo, with interactive (i.e., movable hands) and straightforward features. The system integrates various interactive elements, such as animations, songs, dance, gestures, and touch, to enhance students’ learning engagement, interaction, and motivation and cater to their diverse needs. The study aims to examine the influence of different features from two unique multi-modal robots on the engagement levels of students with/without dyslexia and their needs when engaging with robot learning. Two research questions are posed: (1) What are the features of multi-modal robots that could effectively improve the learning engagements of students with/without dyslexia? (2) What are the needs of students with/without dyslexia when engaging with robot learning? To this end, a comparative study is conducted where 64 students participate in a five-day robot-led training program, while another 73 students receive traditional teacher-led training. Pre/post questionnaires are administered to evaluate students’ engagement levels, and semi-structured interviews are conducted to obtain additional insights. The findings reveal that students with dyslexia are better suited to the interactive and multi-modal features of Kebbi. In contrast, students without dyslexia may prefer the more straightforward features of Minibo, which can still effectively promote engagement and learning. Multi-modal robots can boost engagement and motivation in students with and without dyslexia through novelty and cognitive load management. Emotional connections and interactive elements, such as empathetic and customizable features, enhance engagement and improve learning outcomes.

Extending product offers with product-related services: the value of configurators

A significant part of traditional manufacturing companies’ value propositions is provided through product-related services, such as transport, packaging, documentation, installation, and after-sales support. However, for many companies, it is challenging to manage such services. To address this issue, this paper investigates the usefulness of configurators in supporting this task. Specifically, product configurators are widely used in product development and sales processes in engineer-to-order (ETO) companies, where they have produced many benefits. To investigate the feasibility of product-related service configurators (PSCs) in manufacturing companies, this paper develops an approach to developing and implementing PSCs. The approach is tested in a case study to investigate its usefulness and the effects of applying PSCs. The study demonstrates the usefulness of the proposed approach and reveals three main types of benefits from PSCs: (1) increased product-related service cost transparency, (2) improved product-related service offerings based on customer characteristics, and (3) more standardised and structured product-related service specifications.

Enhancing Financial Literacy in Young Adults: An Android-Based Personal Finance Management Tool

This study details the design, development, and evaluation of an Android-based personal finance management application tailored for young adults in higher education. Addressing unique financial challenges such as limited experience and fluctuating income, the application incorporates features like income tracking, expense monitoring, budgeting, and financial goal-setting. Developed using the Waterfall methodology, the app includes secure login, intuitive transaction management, customizable goals, budget projections, and automated notifications to encourage financial discipline. Usability evaluations with 50 users revealed an overall satisfaction score of 4.6/5, classifying the app as "Excellent." Users praised the intuitive design, accurate tracking, and motivational reminders, while also suggesting additional customization and deeper financial analysis for future updates. This study demonstrates the potential of targeted digital tools to foster financial literacy and resilience, offering evidence that personalized technology can significantly improve financial behaviors in young adults. Future research will explore enhanced customization and AI-driven features to further refine the application’s impact.

PHARAOH: A collaborative crowdsourcing platform for phenotyping and regional analysis of histology

Deep learning has proven capable of automating key aspects of histopathologic analysis. However, its context-specific nature and continued reliance on large expert-annotated training datasets hinders the development of a critical mass of applications to garner widespread adoption in clinical/research workflows. Here, we present an online collaborative platform that streamlines tissue image annotation to promote the development and sharing of custom computer vision models for PHenotyping And Regional Analysis Of Histology (PHARAOH; https://www.pathologyreports.ai/). Specifically, PHARAOH uses a weakly supervised, human-in-the-loop learning framework whereby patch-level image features are leveraged to organize large swaths of tissue into morphologically-uniform clusters for batched annotation by human experts. By providing cluster-level labels on only a handful of cases, we show how custom PHARAOH models can be developed efficiently and used to guide the quantification of cellular features that correlate with molecular, pathologic and patient outcome data. Moreover, by using our PHARAOH pipeline, we showcase how correlation of cohort-level cytoarchitectural features with accompanying biological and outcome data can help systematically devise interpretable morphometric models of disease. Both the custom model design and feature extraction pipelines are amenable to crowdsourcing, positioning PHARAOH to become a fully scalable, systems-level solution for the expansion, generalization and cataloging of computational pathology applications.

Mobile home delivery parcel lockers

The demand for last-mile parcel delivery services is expected to increase. Great efforts are therefore being made to develop new ideas for more efficient last-mile delivery. One of the more recent concepts are Mobile Parcel Lockers (MPL), which can be easily repositioned to meet the actual daily demand for deliveries. In this work, we introduce the Mobile Home Delivery Parcel Locker (MHDPL) problem. Therein, a single vehicle can provide both, MPL service and Attended Home Deliveries (AHD), the current industry standard. Hence, the MHDPL problem integrates two characteristics: the simultaneous delivery of many customers as with MPLs, and the delivery of particularly remote customers in a short time as with AHDs. We present a mathematical formulation and propose an Iterated Local Search (ILS) as a solution approach. Since our ILS works on a time-space network, we introduce new problem and network-specific operators. The performance of the ILS is evaluated and the efficiency of the new service is analyzed in terms of various instance and customer characteristics, comparing it to dedicated MPL and AHD services. Our computational analysis reveals that the combination of services has economic potential and satisfies customer preferences more effectively. According to our study, an average MHDPL vehicle can serve 21% more customers than a comparable AHD vehicle.

Measuring Agile Project Management Effectiveness with the Application of Customer Characteristics, Organizational Influence and Project Management Methodologies in Indonesia

This paper focuses on quantitative research with constructs such as customer characteristics, organizational influence, and project management methodologies, and how the constructs affect their relationship with the dependent variable of agile project management effectiveness. Additionally, partial least squares structural equation modeling or PLS-SEM is employed for this study as the tool to analyze data. Furthermore, 156 data samples were gathered for this study which mainly aims for APM practitioners in Indonesia. The findings of this study indicate that customer characteristics do not support APM effectiveness and the moderating variable of PM methodology between the relationship of customer characteristics and APM effectiveness is not supported. However, the results of this study can conclude that customer characteristics positively affect organizational influence. While organizational influence does positively support APM effectiveness. To improve research on APM effectiveness in Indonesia, this study contributes to laying the preliminary work for future research.

A New Integrated Criteria Weighting Approach for Determining Production Priority in Demand Management

In the demand management process; it is tried to balance the customers' needs with the company's supply possibilities. Effective demand management starts with effective stock control and tracking of customer orders and ends with customer satisfaction. Correctly determining production priorities is one of the ways to increase customer satisfaction. In this context, a new approach has been developed to determine the production priority needed in the demand management process. A new integrated approach based on Multi-Criteria Decision Making (MCDM) is proposed to determine production priorities. In the first stage of this three-stage approach, customer alternatives are determined. In the second stage, production priority criteria are determined depending on customer characteristics. In the third stage; with LBWA (Level Based Weight Assessment) and CRITIC (The Criteria Importance Through Intercriteria Correlation) methods, objective and subjective criterion weights are calculated by considering expert opinions and real data. Then, integrated criterion weights are determined with the SOWIA (Subjective and Objective Weight Integrated Approach) method using objective and subjective criterion weights. In the literature; few studies determine production priority using the MCDM method. Additionally, no study has been found in the literature in which quantitative and qualitative methods are used integrated in the ceramic industry. Therefore, it is thought that this study will contribute to the literature.

TECHNOLOGIES FOR CREATING A BRAND IN THE SERVICE SECTOR OF A MASTER BROW ARTIST

The brand plays an important role, especially in the field of beauty and style services. This article discusses the technologies for creating a brand in the field of services of a master eyebrow artist, which include not only the development of a unique visual style and logo, but also the formation of values and a unique brand offer that distinguish it from competitors. This also includes creating a target audience, identifying key customer characteristics and preferences, and developing marketing and communication strategies aimed at attracting and retaining the target audience. The key technologies in this field are the analysis of the market and competitors, the study of the needs and preferences of customers, as well as the use of various marketing and promotion tools and methods to create a unique and recognizable brand of the eyebrow master.

Developing an AI Tool for Forest Monitoring: Introducing SylvaMind AI

Global forests face increasing threats from deforestation, biodiversity loss, and climate change, necessitating innovative tools for effective monitoring and management. Traditional forest monitoring methods, which rely heavily on manual fieldwork and labor-intensive data processing, are often inadequate for addressing the scale and complexity of these challenges. Advanced tools leveraging artificial intelligence (AI) and remote sensing have emerged as critical solutions, offering timely, accurate, and actionable insights to enable efficient ecosystem monitoring, threat detection, and sustainable management practices. This paper introduces SylvaMind AI, an advanced platform that integrates satellite imagery, deep learning frameworks, and geospatial analysis within a user-friendly interface, which was built using Python for backend systems and deep learning pipelines, alongside tools like Pandas, Rasterio, and TensorFlow for data preprocessing and predictive modelling. The platform processes high-resolution data from Sentinel-2 and Landsat missions for feature extraction and predictive modelling. SylvaMind AI offers two modelling approaches: an automated option for non-technical users and a customizable feature for researchers with specialized needs. Using these approaches, we developed a predictive canopy height model for a study area. The results demonstrated the platform's ability to capture underlying forest patterns and provide detailed insights into canopy height distribution, particularly for medium to high canopies (>25m). This underscores its strength in modeling structural complexity in dense forests. However, the model showed limitations in representing smaller trees, attributed to insufficient training data. SylvaMind AI holds immense potential in transforming forest monitoring by leveraging advanced geospatial data, AI, and intuitive design to address critical challenges in sustainable forest management.

The Impact of Gamified Therapy on Physical, Cognitive, & Emotional Outcomes in Children with Cerebral Palsy: A Case Study Analysis

Background: Cerebral palsy (CP) is a neurological disorder affecting motor, cognitive, and social development in children. Traditional therapies often struggle with engagement and adherence. This study evaluates a novel gamified treatment developed with the SHIFT Framework to improve outcomes in children with CP. Methods: A case study design assessed the effects of gamified therapy on seven children with various types and severities of CP. The intervention used the SHIFT Framework to include engaging game elements and customizable features. Assessments before and after the intervention measured hand-eye coordination, balance, motor skills, cognitive engagement, motivation, and emotional well-being using appropriate statistical methods. Results: Post-intervention, all cases showed improved motor skills, coordination, balance, cognitive engagement, and emotional states. Increased levels of attention, motivation, and persistence were noted, alongside enhanced therapy engagement. Statistical analysis revealed significant improvements (p<0.05) in most parameters. Conclusion: The gamified therapy approach using the SHIFT Framework effectively enhanced physical, cognitive, and emotional outcomes for children with CP. The engaging, personalized intervention improved motivation, adherence, and functional outcomes, particularly in cognitive aspects relevant to intellectual disabilities associated with CP. Further studies with larger cohorts and extended follow-ups are necessary to confirm these results and expand on the therapy’s applicability in CP management.

Scheduling Events and Activities Based on Mobile Application: Case study for Sultanate of Oman

This research paper presents the development of a public service application designed to schedule proposed activities and events. It provides all people, especially tourists, with the timings of various activities and events in the country. It will significantly and noticeably increase the number of tourists, enabling people to take their annual vacation to coincide with the timings of these events. The application aims to simplify planning and organizing various events by providing users with an intuitive platform to view, schedule and manage upcoming activities. The application allows individuals and organizations to create, manage, and collaborate on scheduled events through customizable features and notifications. This mobile application will help gather and schedule activities and events proposed to be held at a specific time in Oman shortly. It integrates geolocation services, user preferences, and real-time data to personalize tourist event recommendations. This approach ensures that tourists receive suggestions based on location and interests, making event discovery more tailored and dynamic. The results suggest that such a service-oriented application could significantly improve how people organize and interact with future events. It provides professional scheduling, organization of events, and people engagement. Clinical Impact: The application has the potential to transform the way tourists interact with local events, thereby boosting local tourism and economy.

A New Concept of Transforming Service: Impact of Generative Voice Chatbots on Customer Satisfaction and Banking Industry Productivity

This study examines the impact of implementing generative AI voice chatbots on customer expectations and satisfaction in the banking sectors of Kazakhstan, Russia, and Italy. To achieve this objective, this study conducted a survey of 253 customers from 35 commercial banks in Kazakhstan, Russia, and Italy from November 2023 to early April 2024. This study employed partial least squares structural equation modelling (PLS-SEM) to assess and validate the validity and reliability of the research model. The study integrates the Expectation Confirmation Model with AI components to analyze factors influencing customer satisfaction with AI-enabled digital banking services. Key findings indicate that expectation confirmation, perceived performance, visual attractiveness, problem-solving capabilities, and communication quality significantly affect customer satisfaction with AI chatbots. However, trendiness and customization features showed minimal impact. The research also explores how customer satisfaction and corporate reputation influence chatbot adoption. Additionally, the study investigates the relationship between chatbot adoption and productivity performance in banking operations. The study provides several policy recommendations, including enhancing perceived performance, expectation confirmation, communication quality, visual attractiveness, and corporate reputation, which can improve customer satisfaction and increase confidence in generative AI voice chatbots in the digital banking industry. Doi: 10.28991/ESJ-2024-08-06-09 Full Text: PDF

A novel inner-branched stent-graft to overcome narrowed lumen in branched endovascular aneurysm repair.

A narrowed patent aortic lumen (<25 mm) represents a challenging scenario frequently observed during thoraco-abdominal and abdominal aortic pathologies involving the visceral vessels. The paper aims to describe the characteristics of a novel tapered-shape inner-branched custom-made stent-graft designed to specifically address the narrowed patent aortic lumen and its applicability in a wider spectrum of aortic scenarios at the reno-visceral segment.

How does innovative customer knowledge influence electronic word-of-mouth recommendation behavior through egoistic and altruistic approaches? Testing a moderated mediation model

IntroductionAt present, innovative customer knowledge on social media platforms is mostly treated as a kind of “self-entertainment” activity content, and has not been effectively integrated and used by sales-oriented social media enterprises. As a result, the problem of electronic word-of-mouth recommendation reducing for such enterprises is more prominent. Theoretically, on the one hand, researches in the field of customer knowledge are mainly concentrated in the field of knowledge management led by the enterprise, which lacks to discuss the influence of innovative knowledge on electronic word-of-mouth recommendation behavior from the perspective of customer dominance. On the other hand, previous studies lack to explore the formation mechanism of electronic word-of-mouth recommendation behavior of innovative customers from the dual paths of altruism and egoism. The professional characteristics and social characteristics of innovative customers are not analyzed as boundary conditions. In this context, based on social learning theory and social identity theory, this study explores the influence mechanism of innovative customer knowledge on electronic word-of-mouth recommendation behavior.MethodsData were collected by Likert 5-level scale using questionnaire survey method. A total of 452 valid questionnaires were collected from Northeast, Northwest, East, North, Central, South and southwest China by random sampling method. SPSS21.0 software and Bootstrap (PROCESS3.0) program were used to analyze the multilevel linear regression, structural equation model and robustness test of the model.Results(1) Innovative customer knowledge had a significant positive impact on electronic word-of-mouth recommendation behavior and professional identity; (2) Professional identity had a significant positive effect on electronic word-of-mouth recommendation behavior; (3) Professional identity played mediating role between innovative customer knowledge and electronic word-of-mouth recommendation behavior; (4) Compared with high professional status and high social status, low professional status and low social status had a stronger moderating effect on the relationship between professional identity and electronic word-of-mouth recommendation behavior, and there was a moderated mediation effect.DiscussionInnovative customer knowledge generates electronic word-of-mouth recommendation behavior through two paths: altruism and egoism. These two paths are affected by the external characteristics of innovative customers, that is, professional characteristics and social characteristics have a moderating effect on them.

Insights from the evaluation of a persuasive intervention for absent-minded smartphone use

ABSTRACT Problematic smartphone use (PSU) is a growing concern that hurts users' daily lives and activities. Previous studies have emphasised the importance of developing mindfulness and self-efficacy concerning smartphone use rather than solely focussing on reducing usage. However, there has been little research developing and evaluating digital interventions specifically targeting absent-minded smartphone use. There is also little knowledge on how best mindfulness practice using digital technologies can be integrated with persuasive designs which have been widely studied and implemented for behaviour change. In this paper, we developed a live wallpaper application for Android lock and home screens as a mindfulness-based intervention for absent-minded smartphone use. The application was evaluated over two weeks with 121 participants. This was followed by a semi-structured interview with 15 participants. The results of our analysis show that the intervention reduced absent-minded smartphone use overall. While participants found the various features (especially the customisation features) of the intervention to be persuasive, we found no correlation between perceived persuasiveness and behaviour change. This work provides valuable insights for advancing human-computer interaction (HCI) research on PSU. Additionally, the results raise important questions for future research, such as the relationship between perceived persuasiveness and behaviour change. Finally, we contribute to the discussion on the applications of mindfulness in persuasive technology, challenges and future research areas.

EFL Students’ Perception Towards Kahoot! as A Gamification Tool in English Learning

Technology in education forces teachers to modify their teaching strategies by implementing gamification as a tool in teaching and learning process. Kahoot is a popular gamification tool in English learning. Using a qualitative research design, this study aimed to determine the EFL students' perception of the gamification tool in an English learning environment. Thirty-six (36) students of 10th grade from a public senior high school in Semarang, Central Java, Indonesia. The participants were asked to complete a closed-ended questionnaire using Google Forms to gain information about their perceptions of the educational environment. The findings revealed that the students generally have a positive perception of Kahoot! as a gamification tool in the English learning process. The interactive and competitive nature of the quizzes increases students' motivation and engagement in the learning process, which can enhance students' engagement and motivation in the classroom. The students generally perceive Kahoot! as an effective, fun, and effective educational environment that enhances students' learning experience and creates a vibrant and engaging classroom environment. By combining motivation, collaboration, competition, fun, interest, excitement, and an energetic environment, Kahoot! can enhance the English learning experience, promote interaction and collaboration, and offer customizable features.

Research on Credit Card Fraud Risk Identification Based on Integrated Logistic Regression Model

Effectively identifying credit card fraud using machine learning methods is a significant issue in the financial sector. In this context, machine learning models encounter challenges such as the imbalanced distribution of sample data labels and the high dimensionality of customer feature sets. Addressing these two critical factors, this paper develops an enhanced method for the logistic regression model. This approach not only balances the sample label distribution through resampling but also mitigates the estimation issues arising from the curse of dimensionality. Furthermore, the proposed method addresses the coverage issue of the entire feature set. It solves that resampling can only partially address the curse of dimensionality problem and employs L1 regularization for each logistic regression submodel to further alleviate this issue. Results from simulation experiments and real-world data analysis demonstrate that the proposed method is competitive with logistic regression and several classical classification techniques. This method is not only effective in resolving credit card fraud risks but also has the potential to be extended to other domains.

Ring: A Lightweight and Versatile Cross-Platform Dynamic Programming Language Developed Using Visual Programming

New programming languages are often designed to keep up with technological advancements and project requirements while also learning from previous attempts and introducing more powerful expression mechanisms. However, most existing dynamic programming languages rely on English keywords and lack features that facilitate easy translation of language syntax. Additionally, maintaining multiple implementations of the same language for different platforms, such as desktops and microcontrollers, can lead to inconsistencies and fragmented features. Furthermore, they usually do not use visual programming to fully implement the compiler and virtual machine. In this research paper, we introduce Ring—a dynamically-typed language with a lightweight implementation. However, it boasts several advantages, including a rich and versatile standard library and direct support for classes and object-oriented programming. The Ring language offers customization features. For instance, it allows easy modification of the language syntax multiple times, enabling programming by writing code using Arabic, English, or other keywords. Additionally, the language permits the creation of domain-specific languages through new features that extend object-oriented programming, allowing for specialized languages resembling CSS or Supernova. In the era of the Internet of Things, instead of creating another language implementation to support microcontrollers, the same Ring implementation allows us to create projects and applications for desktops, the web, WebAssembly, Android, or Raspberry Pi Pico. The Ring Compiler and Virtual Machine are designed using the PWCT Visual Programming language based on ANSI C. The visual implementation is composed of 18,945 components that generate 24,743 lines of code, which increases the abstraction level by approximately 23.5% and hides unnecessary details.

Creating a Quasi-Resonant Induction Cooktop Integrating Zero-Voltage Switching (ZVS) and Load Management

This study aims to elucidate the development and construction of a durable induction cooktop, with key considerations including efficiency, power customization, and safety features. The intricate processes involved in crafting a 3.5 kW induction burner are thoroughly examined, encompassing simulations for quasi-resonant inverters, the meticulous selection of induction coils and capacitors, the implementation of practical Analog-to-Digital Converter (ADC) filtration, pulse width modulation (PWM) driving techniques, and the integration of protection mechanisms. Leveraging an ARM-based microcontroller enabled the attainment of diverse objectives such as Zero-Voltage Switching (ZVS), safeguarding IGBTs, facilitating user interaction through a user-friendly interface, and enabling load detection capabilities. Furthermore, the capability to gauge and adjust output power based on user preferences was incorporated. Subsequently, rigorous testing was conducted to evaluate the functionality and applicability of the device in real-world scenarios.

Elevating Vocational Training: The Power of Learning Management Systems in Shaping Digital Skills

This article examines the impact of Learning Management Systems (LMS) on the development of learners' technological skills within the context of vocational training. Drawing on an analysis of pedagogical practices and recent studies, it explores how the use of LMS facilitates the acquisition of digital skills essential for the employability of future professionals. The article highlights the advantages of LMS in terms of personalized learning paths, flexible access to content, and tracking of learners' progress. It also discusses the challenges associated with the adoption of LMS, particularly in terms of faculty training and technological integration. The findings of this study emphasize that LMS are not just content management tools, but they play a central role in preparing learners to meet the technological requirements of the current job market. The customization features of LMS allow learners to engage with content in a way that suits their individual learning styles and pace. This personalized approach can lead to more effective skill development and a deeper understanding of technological concepts. Furthermore, the flexibility offered by LMS in accessing learning materials enables learners to engage with the content at their convenience, which is particularly beneficial for individuals balancing work and study commitments. Additionally, the ability to track learners' progress through LMS provides valuable insights for educators to tailor their teaching methods and interventions to address specific areas of need. However, the adoption of LMS also presents challenges, particularly in ensuring that educators are proficient in utilizing the technology to its full potential. Effective training and support for faculty members are crucial in maximizing the benefits of LMS for skill development. Furthermore, integrating LMS into existing educational systems requires careful planning and consideration to ensure seamless implementation and usability. In conclusion, this article underscores the significant role of LMS in fostering the technological skills of learners in vocational training. By leveraging the capabilities of LMS, educational institutions can better prepare their students for the demands of the contemporary workforce, ultimately enhancing their employability and competitiveness in the job market.