Search Results (15)

This paper examines a number of features of online retailing and e-commerce, with a special focus on important topics including consumer behavior, multichannel marketing, and customer relationship management (CRM). According to existing research, online sales have several advantages for businesses, especially those with physical locations, such as better inventory control and increased profitability. The difficulties of integrating offline and online channels, maintaining consumer loyalty, and competing globally are all deeply analyzed. Small-business-specific CRM methods and innovative algorithms show improvements in client happiness and targeting. The study shows how e-commerce adoption and client loyalty are shaped by cultural variables, trust, and personalization. By covering the gaps in research on growing and regional markets, this review offers thorough insights into how online shopping is changing and how these changes affect retail tactics. Full article

To effectively address the challenges of imbalanced equipment utilization, frequent congestion, and poor economic benefits faced by charging and swapping stations (ICSSs), this paper innovatively proposes a comprehensive scheduling strategy that combines user behavior regulation and battery management. In terms of user regulation, an intention-reshaping model for changing user cognition is proposed to equalize the use of charging and swapping (CAS) equipment, easing ICSS congestion. Moreover, an off-station scheduling model for electric vehicles (EVs) is developed to enhance overall ICSS revenue. Within the battery management terms, the suggested inventory battery threshold adjustment method and charging strategy by charging time segmentation are employed to ensure consistent inventory battery supply and cost-effective battery charging. Finally, a two-stage scheduling strategy of in-station and off-station scheduling is suggested for the ICSS, and an improved northern goshawk optimization algorithm (INGO) is used to solve it. The results showed that this strategy reduced the overall congestion of ICSSs by 34% and increased the average annual net revenue by 64%. The goal of alleviating congestion and improving the economic efficiency of ICSSs has been achieved. Full article

In the rapidly evolving domain of large-scale retail data systems, envisioning and simulating future consumer transactions has become a crucial area of interest. It offers significant potential to fortify demand forecasting and fine-tune inventory management. This paper presents an innovative application of Generative Adversarial Networks (GANs) to generate synthetic retail transaction data, specifically focusing on a novel system architecture that combines consumer behavior modeling with stock-keeping unit (SKU) availability constraints to address real-world assortment optimization challenges. We diverge from conventional methodologies by integrating SKU data into our GAN architecture and using more sophisticated embedding methods (e.g., hyper-graphs). This design choice enables our system to generate not only simulated consumer purchase behaviors but also reflects the dynamic interplay between consumer behavior and SKU availability—an aspect often overlooked, among others, because of data scarcity in legacy retail simulation models. Our GAN model generates transactions under stock constraints, pioneering a resourceful experimental system with practical implications for real-world retail operation and strategy. Preliminary results demonstrate enhanced realism in simulated transactions measured by comparing generated items with real ones using methods employed earlier in related studies. This underscores the potential for more accurate predictive modeling. Full article

Multidisciplinary collaboration is key to strengthening the evidence base for multifaceted illness prevention interventions. We bring together health economics and behavioral science to explore the well-being benefits and social cost–benefit of volunteer gardening at an accredited botanic garden, Wales, UK. A health economics-informed social return on investment (SROI) evaluation was combined with the assessment of volunteers’ basic psychological needs (autonomy, competence, and relatedness), connection to nature, and their interrelatedness in this innovative nature-based intervention study. Pre- and post-volunteering outcome data were collected using the Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS), the ICEpop CAPability measure for Adults (ICECAP-A), the 12-item diary version of the Basic Psychological Need Satisfaction and Frustration Scale (BPNSNF), the Nature Connection Index (NCI), and a bespoke Client Service Receipt Inventory (CSRI). Results indicate that volunteer gardening can provide well-being benefits to participants and cost savings to the NHS. The well-being benefits observed were estimated to generate social value in the range of GBP 4.02 to GBP 5.43 for every GBP 1 invested. This study contributes to the evidence base that simple nature-based interventions such as volunteer gardening could offer low-cost supportive environments that deliver significant well-being benefits and associated social value to local communities, including a reduced burden on overstretched local healthcare services. Full article

In the post-COVID-19 era, education requires teachers to engage learners across diverse learning environments (at school or other formal institutions, at home, outdoors, or in virtual environments) using innovative learning strategies. To meet these challenges, teachers must upskill their creativity and strengthen their pedagogical digital competencies and knowledge management skills. This study introduces the innovative teacher training and support (TTS-IPCD) model to enhance teachers’ creativity and pedagogical digital competencies. This research involved a sample of 350 teachers from 75 primary and secondary schools over a four-year period. Teachers’ creativity was measured using the Kirton Adaption–Innovation Inventory (KAI), assessing key metrics such as problem-solving flexibility, openness to change, and inclination toward novel approaches. Quantitative analysis was conducted using an independent samples t-test to evaluate teacher creativity changes. The results indicated that the TTS-IPCD model enhanced teacher creativity in the direction of a stronger propensity toward innovative behaviors, including embracing diversity and change in their work, solving problems through novel approaches, and adopting a holistic perspective rather than strictly adhering to established routines. Furthermore, the TTS-IPCD model improved teamwork and collaboration, contributing to the development of more adaptive and innovative learning environments. These findings highlight the importance of continuous professional development of teachers focused on creative pedagogy and digital competencies to equip teachers for the evolving educational landscape. Full article

Background: Innovation is a crucial issue in healthcare services since it can affect job-related variables such as productivity, satisfaction, and burnout. The aim of our study was to examine the impact of innovation support on quiet quitting, innovative behavior, and innovation outputs among nurses. Methods: We conducted a cross-sectional study in Greece during April 2024. We employed a convenience sample of nurses. We followed the reporting of observational studies in epidemiology (STROBE). We used the following instruments: (a) the innovation support inventory (ISI) to measure innovation support; (b) the quiet quitting scale (QQS) to measure quiet quitting; (c) the innovative behavior inventory (IBI) to measure innovative behavior; and (d) the innovation outputs (IO) scale to measure innovation outputs. Our study questionnaire was anonymous, and nurses gave their informed consent to participate. The Ethics Committee of the Faculty of Nursing, National and Kapodistrian University of Athens, approved our study protocol, while we followed the guidelines of the Declaration of Helsinki. Results: Our study population included 328 nurses with a mean age of 42.3 years (standard deviation: 9.7). Among them, 89.9% were females. Our multivariable analysis identified a negative relationship between innovation support and quiet quitting. Moreover, we found that managerial support and cultural support improved several aspects of innovative behavior, such as idea generation, idea search, idea communication, implementation starting activities, involving others, and overcoming obstacles. Additionally, managerial support improved innovation outputs. Conclusions: Our findings suggested the positive impact of innovation support on quiet quitting, innovative behavior, and innovation outputs among nurses. Organizations and nurses’ managers should establish an innovative working environment to improve nurses’ passion, motives, and productivity. Full article

Depression is a significant risk factor for other serious health conditions, such as heart failure, dementia, and diabetes. In this study, a quantitative method was developed to detect depressive states in individuals using electrocardiogram (ECG) and photoplethysmogram (PPG) signals. Data were obtained from 59 people affiliated with the high-specialized medical center of Bajio T1, which consists of medical professionals, administrative personnel, and service workers. Data were analyzed using the Beck Depression Inventory (BDI-II) to discern potential false positives. The statistical analyses performed elucidated distinctive features with variable behavior in response to diverse physical stimuli, which were adeptly processed through a machine learning classification framework. The method achieved an accuracy rate of up to 92% in the identification of depressive states, substantiating the potential of biophysical data in increasing the diagnostic process of depression. The results suggest that this method is innovative and has significant potential. With additional refinements, this approach could be utilized as a screening tool in psychiatry, incorporated into everyday devices for preventive diagnostics, and potentially lead to alarm systems for individuals with suicidal thoughts. Full article

In recent decades, climate change has demanded more and more attention. Consumers have the power to influence the carbon footprint of goods and services through their purchasing decisions, but to do this they need to learn more. To address this need, it is necessary to develop online questionnaires able to make people aware of which activities have a greater environmental impact in their daily lives. Focusing on this goal, we formulated two tools for quantifying an individual’s carbon footprint over a year. The innovativeness of these tools lies in being user-friendly and providing online open access to compilers, as well as using specific emission factors for the reference context. Specifically, we focused on the main emission sources: gas and electricity consumption, mobility, food, and waste. During these last years, the tools have been proposed to Italian students at different levels of education and to employees of Italian and international companies. The responses from 3260 users revealed an average annual direct carbon footprint per capita of about 5600 kg CO_2-eq, which, integrated with the estimate of indirect emissions, provides an estimate in good agreement with the value provided by the Italian National Inventory of greenhouse gases. With the developed tools, people are able to observe which sectors have the greatest impact and consequently are stimulated to emit less by adopting more sustainable behaviors. Full article

The manufacturing industry often faces challenges related to customer satisfaction, system degradation, product sustainability, inventory, and operation management. If not addressed, these challenges can be substantially harmful and costly for the sustainability of manufacturing plants. Paradigms, e.g., Industry 4.0 and smart manufacturing, provide effective and innovative solutions, aiming at managing manufacturing operations, and controlling the quality of completed goods offered to the customers. Aiming at that end, this paper endeavors to mitigate the described challenges in a multi-stage degrading manufacturing/remanufacturing system through the implementation of an intelligent machine learning-based decision-making mechanism. To carry out decision-making, reinforcement learning is coupled with lean green manufacturing. The scope of this implementation is the creation of a smart lean and sustainable production environment that has a minimal environmental impact. Considering the latter, this effort is made to reduce material consumption and extend the lifecycle of manufactured products using pull production, predictive maintenance, and circular economy strategies. To validate this, a well-defined experimental analysis meticulously investigates the behavior and performance of the proposed mechanism. Results obtained by this analysis support the presented reinforcement learning/ad hoc control mechanism’s capability and competence achieving both high system sustainability and enhanced material reuse. Full article

Spinal cord injury (SCI) consists of damage to any segment of the spinal cord extending to potential harm to nerves in the cauda equina. Rehabilitative efforts for SCI can involve conventional physiotherapy, innovative technologies, as well as cognitive treatment and psychological support. The aim of this study is to evaluate the feasibility of a dedicated, multidisciplinary, and integrated intervention path for SCI, encompassing both conventional and technological interventions, while observing their impact on cognitive, motor, and behavioral outcomes and the overall quality of life for individuals with SCI. Forty-two patients with SCI were included in the analysis utilizing electronic recovery system data. The treatment regimen included multidisciplinary rehabilitation approaches, such as traditional physiotherapy sessions, speech therapy, psychological support, robotic devices, advanced cognitive rehabilitation, and other interventions. Pre–post comparisons showed a significant improvement in lower limb function (Fugl Meyer Assessment-FMA < 0.001), global cognitive functioning (Montreal Cognitive Assessment-MoCA p < 0.001), and perceived quality of life at both a physical and mental level (Short Form-12-SF-12 p < 0.001). Furthermore, we found a significant reduction in depressive state (Beck Depression Inventory-BDI p < 0.001). In addition, we assessed patient satisfaction using the Short Form of the Patient Satisfaction Questionnaire (PSQ), offering insights into the subjective evaluation of the intervention. In conclusion, this retrospective study provides positive results in terms of improvements in motor function, cognitive functions, and quality of life, highlighting the importance of exploring multidisciplinary approaches. Full article

The cybersecurity landscape presents daunting challenges, particularly in the face of Denial of Service (DoS) attacks such as DoS Http Unbearable Load King (HULK) attacks and DoS GoldenEye attacks. These malicious tactics are designed to disrupt critical services by overwhelming web servers with malicious requests. In contrast to DoS attacks, there exists nefarious Operating System (OS) scanning, which exploits vulnerabilities in target systems. To provide further context, it is essential to clarify that NMAP, a widely utilized tool for identifying host OSes and vulnerabilities, is not inherently malicious but a dual-use tool with legitimate applications, such as asset inventory services in company networks. Additionally, Domain Name System (DNS) botnets can be incredibly damaging as they harness numerous compromised devices to inundate a target with malicious DNS traffic. This can disrupt online services, leading to downtime, financial losses, and reputational damage. Furthermore, DNS botnets can be used for other malicious activities like data exfiltration, spreading malware, or launching other cyberattacks, making them a versatile tool for cybercriminals. As attackers continually adapt and modify specific attributes to evade detection, our paper introduces an automated detection method that requires no expert input. This innovative approach identifies the distinct characteristics of DNS botnet attacks, DoS HULK attacks, DoS GoldenEye attacks, and OS-Scanning, explicitly using the NMAP tool, even when attackers alter their tactics. By harnessing a representative dataset, our proposed method ensures robust detection of such attacks against varying attack parameters or behavioral shifts. This heightened resilience significantly raises the bar for attackers attempting to conceal their malicious activities. Significantly, our approach delivered outstanding outcomes, with a mid 95% accuracy in categorizing NMAP OS scanning and DNS botnet attacks, and 100% for DoS HULK attacks and DoS GoldenEye attacks, proficiently discerning between malevolent and harmless network packets. Our code and the dataset are made publicly available. Full article

COVID-19 rapidly and extensively changed the normal everyday practices of societies, and there is no going back to the past. Universities also had to adapt and re-establish their normal routines, from policies to practices. In this article, we explore university students’ experiences of web-based learning, their well-being, and engagement during the pandemic. As a theoretical framework, we use the concept of the university student engagement inventory (USEI), which includes behavioral, cognitive, and emotional dimensions. The data were collected during the COVID-19 pandemic from university students (N = 35) via an online survey and analyzed using a thematic content analysis. According to the results, university students experienced well-designed and pedagogically implemented web-based learning, teaching and guidance to enhance their own learning, well-being, and engagement in their studies. This suggests that web-based solutions for academic learning are justified but need to consider a range of well-being and engagement factors. What is still needed are innovative solutions that are pedagogically justifiable and consider the digital and human dimensions sustainably. Full article

COVID-19 has caused a public and international health emergency, leading to isolation and social distancing. These restrictions have had a significant impact on the caregivers of people with dementia, increasing the burden of patient management. The purpose of this study was to investigate the stress perceived by caregivers of patients with Alzheimer’s disease (AD) during the pandemic. We used a cross-sectional survey design to evaluate the caregivers’ psychological responses and coping strategies. Eighty-four caregivers of patients with a diagnosis of AD were involved in this study by completing an online questionnaire. They presented a high perception of stress (the Perceived Stress Scale mean ± DS: 33.5 ± 4.5), and their high burden in caring was mainly related to physical difficulties (Caregiver Burden Inventory–Physical Burden mean ± DS: 15.0 ± 2.1) and perception of loss of time (Caregiver Burden Inventory–Time-dependence Burden mean ± DS: 16.5 ± 1.4). Moreover, caregivers perceived their quality of life as very low (Short Form-12 Health Survey Physical mean ± DS: 13.5 ± 2.7; Short Form-12 Health Survey Mental Health mean ± DS: 16.4 ± 4.2). Finally, we found that participants mostly used dysfunctional coping strategies, such as avoidance strategies (Coping Orientation to Problem Experiences–Avoidance Strategies mean ± DS: 39.5 ± 7.1), but these strategies did not affect the stress level of caregivers. Given that caregivers present a high burden and stress, innovative tools could be a valuable solution to investigate and support their emotional and behavioral status during difficult periods, such as the COVID-19 pandemic. Full article

This study aimed to translate and validate the Satter Eating Competence Inventory (ecSI2.0^TM) from English to Brazilian Portuguese. The process included three steps: (i) translation and back-translation of the original ecSI2.0^TM to Brazilian Portuguese; (ii) evaluation of its reproducibility; (iii) a pilot study to validate the Brazilian version of the Satter Eating Competence Inventory (ecSI2.0^TMBR) for a selected sample of the Brazilian adult population (internal consistency and factor validity). The reproducibility (test–retest reliability) was verified using the intraclass correlation coefficient (ICC) obtained by the responses of 32 Brazilian adults. All domains of the ecSI2.0^TMBR and the total score showed ICC > 0.8. Considering the entire questionnaire, none of the domains presented significant divergences among the participants’ responses (p < 0.001). In the pilot study with 662 individuals, 74.9% (n= 496) were female, mean age was 40.33 ± 12.55, and they presented a higher level of schooling and income. Analyses revealed Cronbach’s alpha coefficients of 0.869 for the ecSI2.0^TMBR total scale, 0.793 for Eating Attitudes, 0.527 for Internal Regulation, 0.728 for Food Acceptance, and 0.822 for Contextual Skills. In general, the ecSI2.0™BR presented good acceptability, showing total floor and ceiling effects of ≤0.6%. Factor validity was examined by confirmatory factor analysis. The four domains presented a good fit in the confirmatory factor analysis: RMSEA = 0.0123 (95% CI: 0–0.0266); CFI = 0.998; χ² = 75.9; df = 69; p = 0.266. The ecSI2.0^TMBR is the first tool designed to measure eating competence (EC) in the Brazilian population, showing good reproducibility and internal consistency. We expect the ecSI2.0^TMBR will support innovative research to investigate the association of EC and health outcomes, as well as new strategies based on emerging behavioral theories to enhance nutritional education policy. Full article

To address the sustainability challenges related to travel behavior, technological innovations will not be enough. Behavioral changes are also called for. The aim of the present study is to examine the influence of sociodemography, geography, and personality on car driving and use of public transportation. Sociodemographic factors have been defined by age, gender, income, and education. Geographic factors have been studied through residential area (e.g., rural and urban areas). Personality has been studied through the Five-Factor-Model of personality—degree of Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. The analysis is based on a survey with 1812 respondents, representative for the Swedish population. Regarding sociodemographic factors, car driving is explained by being male, higher age, higher income, while use of public transportation is explained by lower age and higher education. The user profile of a car driver is the opposite to that of a public transport passenger when it comes to geographic factors; urban residential area explains public transportation while rural area explains car driving. Some personality factors are also opposites; a low degree of Openness and a high degree of Extraversion explain car driving, while a high degree of Openness and a low degree of Extraversion explain use of public transportation. Moreover, car driving is explained by a low degree of Neuroticism, while use of public transportation is explained by a low degree of Conscientiousness and a high degree of Agreeableness. Since sociodemography, geography, and personality influence how people process information and evaluate market propositions (e.g., products and services), the findings presented here are useful for policymakers and transportations planners who would like to change behavior from car driving to public transportation use. Caution should be taken in interpreting the relationship between personality traits and transportation modes, since the personality traits are measured by a short scale (i.e., Big Five Inventory (BFI)-10), with limitations in the factor structure for a representative sample of the Swedish population. Full article