Search Results (172)

Women in emerging economies face unique constraints rooted in cultural norms, socio-economic disparities, and limited access to education and technology. Narrowing the digital gender gap by ensuring access to financial services may reduce the economic inequalities for women in these countries. This study examines the influence of digital finance in narrowing the gender gap, guided by the research question: To what extent do digital financial services contribute to narrowing the gender gap in access to and usage of financial services in low-and middle-income economies? Gender inclusion was measured by the ratio of accounts owned by women over the total number of accounts. Digital financial inclusion was constructed based on eight components: mobile money account, storing money in financial institutions, Internet access, mobile phone owned, savings, savings in financial institutions, making or receiving a digital payment, and mobile phone or use of the Internet for shopping. A Bayesian regression approach was computed using the Global Findex Database data for 73 countries classified as low and lower-middle-income economies from 2011 to 2022. The Machine Learning approach evaluates the model’s ability to predict women’s autonomy and the role of digital finance. The results show that digital financial services would reduce the gender gap in low-income economies while augmenting the number of open accounts, especially for women. The results aid in the establishment of policies to reduce the gender gap. These results are relevant to the UNSDG agenda, mainly Goal 5 and Goal 10. Full article

The Internet Shopping Optimization Problem with multiple item Units looks for the best selection of stores where to buy various or individual units in a required list of items to minimize the final purchase cost. The problem belongs to the most challenging complexity class of optimization problems (NP-Hard). This paper adds to the already complex problem a more difficult situation with a second objective conflicting with the purchase cost minimization. As far as we know, this is the first state-of-the-art proposal with conflicting objectives for the Internet Shopping Optimization Problem or its variants. The objective in conflict with the minimization of the purchase final cost is the cash-back or reward points on personal or corporate credit cards, the most common payment method for online purchases. Due to the nature of the conflicting objectives, this paper proposes using evolutionary multi-objective optimization algorithms. We perform an experimental comparison using eight algorithms from the literature. The experimental results show that NSGA-II achieves the best overall performance for the studied instances from the state of the art. Full article

In recent years, there has been a sharp increase in the number of online fraud cases. However, research on crime geography has paid little attention to online crimes, especially to the influencing factors behind their spatial distributions. Online fraud is closely related to people’s daily internet use. The existing literature has explored the impact of internet use on online crimes based on small samples of individual interviews. There is a lack of large-scale studies from a community perspective. This study applies the routine activity theory to online activities to test the relationship between online fraud alert data and the usage durations of different types of mobile phone users’ applications (apps) for communities in ZG City. It builds negative binomial regression models for analyzing the impact of the usage of different types of apps on the spatial distribution of online fraud. The results reveal that the online fraud crime rate and the online time spent on a financial management app share the most similar spatial distribution. While financial management, online education, transportation, and search engine app usages have a significant positive association with online fraud, the use of a financial management app has the greatest impact. Additionally, time spent on social media, online shopping and entertainment, and mobile reading apps have a significant negative association with online fraud. As not all online activities lead to cybercrime, crime prevention efforts should target specific types of apps, such as financial management, online education, transportation, and search engines. Full article

Background: Vast spatial mobility changes happened globally during the COVID-19 pandemic, profoundly affecting older adults’ well-being and active aging experience. This study aims to examine how the virtual environment and cyberspace, in conjunction with the physical and social neighbourhood environments, influence outdoor activities and spatial mobility for older immigrants. Methods: Four online focus groups were conducted with 25 older Chinese immigrants aged 65 and over in the Greater Toronto Area, Canada. The focus groups explored coping strategies during the pandemic and spatial mobility patterns related to different activity types such as grocery shopping, leisure activities and physical exercises, social and familial activities, and healthcare. Qualitative thematic analysis was conducted guided by the neighbourhood and health theoretical framework. Results: The overall engagement of older Chinese immigrants in various types of outdoor activities declined drastically and the spatial mobility pattern was complex. This change was shaped largely by the intersecting physical/built (e.g., residential conditions, access to public spaces), social (e.g., social support, interpersonal cohesion) and virtual (e.g., online communities and internet-based resources) environmental factors, as well as individual risk perceptions towards COVID-19 and public health interventions during the pandemic. Conclusions: Virtual environment emerged as an important domain that compensates for the heavily reduced spatial mobility of the group during the pandemic. It functioned as a vital channel for older Chinese immigrants to sustain the necessary leisure, social, and healthcare-related activities and maintain well-being during the pandemic. The study provides implications for addressing neighbourhood-level factors in policymaking and implementing initiatives to enhance active ageing experience of older Chinese immigrants. Full article

In this research, two new methods for solving the Internet shopping optimization problem with sensitive prices are proposed, incorporating adaptive adjustment of control parameters. This problem is classified as NP-hard and is relevant to current electronic commerce. The first proposed solution method corresponds to a Memetic Algorithm incorporating improved local search and adaptive adjustment of control parameters. The second proposed solution method is a particle swarm optimization algorithm that adds a technique for diversification and adaptive adjustment of control parameters. We assess the effectiveness of the proposed algorithms by comparing them with the Branch and Bound algorithm, which presents the most favorable outcomes of the state-of-the-art method. Nine instances of three different sizes are used: small, medium, and large. For performance validation, the Wilcoxon and Friedman non-parametric tests are applied. The results show that the proposed algorithms exhibit comparable performance and outperform the Branch and Bound algorithm. Full article

In recent years, the digital creative industry has manifested a vigorous growth trend along with the continuous upgrading of the Internet and the leap of the national economy. This research identifies the spatial distribution characteristics of digital creative enterprises in Shenzhen, employs big data of spatial information of various facilities such as transportation and commerce as the driving factor to construct a model, takes 1 km grid as the fundamental research unit, and explores the influence mechanism of enterprise location selection through methods like OLS and MGWR. The results are as follows: (1) The overall spatial distribution characteristics of digital creative industry are characterized by “widely distributed throughout the city, with a high concentration within the customs and a weak dispersion outside the customs”. (2) The factors of park foundation, production service, public service and life service exert a significant influence on the spatial distribution of digital creative industries in Shenzhen. Among them, the density of shopping facilities, staff, hotel and bus station exhibits a highly obvious spatial heterogeneity in terms of the influence on enterprise location. (3) The correlation of local scale factors is high and the influence range is precise, which frequently presents complex correlation outcomes in small scales such as streets or communities. Full article

This paper presents a review of the technologies and services associated with online grocery shopping. The progress in the field of online grocery shopping has been very rapid in recent years. Hence, there was a need to systematize knowledge about the latest various solutions used in this topic. The authors searched the internet, focusing on websites of different supermarkets, shops, and other services that offer online shopping, as well as reviewed scientific papers. Based on the collected material, the authors created four thematic parts, which include: (1) supermarket services; (2) dedicated grocery delivery services and farm-to-table; (3) shopping in Virtual Reality and the metaverse; smart devices and (4) AI in food ordering—the last part includes smart devices, such as smart refrigerators, ovens, their functionality, and the services connected with them. The authors refer to 243 sources. The research includes the three following objectives: (1) exploring and presenting the emerging applied ways of online grocery shopping, (2) exploring and presenting the latest technological advances related to the digitalization of grocery shopping, (3) discussing the upcoming technologies, services, and methods in online grocery shopping. This paper provides knowledge about a wide range of solutions offered by both supermarkets and stores (e.g., shopping applications, VR applications, metaverse shopping) and other companies (e.g., deliveries, product tracking), highlighting the numerous functions available thanks to smart devices (e.g., voice control, own shopping lists, control of products, their quantities and expiration dates, management of user preferences, and many more). This paper also discusses social issues related to the presented solutions, such as their influence on consumer behavior, barriers to adoption, and the associated challenges. Full article

Lean manufacturing focuses on perfection, trying to eliminate all types of Muda (waste), Mura (inconsistency), Muri (overburden), defects, injuries, and accidents through a continuous improvement process. Assembly lines are the final stages of manufacturing before the product is delivered to customers. Kata methodology provides a practical approach to achieving perfection in assembly lines, but its effectiveness is often hindered by delays in data collection, analysis, and diagnostics. In this study, we address these challenges by leveraging industrial internet of things (IIoT) solutions in an industrial setting. The research question of this paper is as follows: “Why was the full potential of traditional Kata to achieve assembly line perfection not realized, and will IIoT-integrated Kata address the limitations of the traditional Kata?” We demonstrate the integration of IIoT and Kata methodology in a factory assembling automobile heating, ventilation, and air conditioning (HVAC) systems to enhance assembly line productivity. We observe that the integration of IIoT with Kata methodology not only addresses existing limitations but drives substantial gains in assembly line performance. We validate improvements in both productivity and efficiency through quantitative and qualitative outcomes. We underscore the pivotal role of real-time data for Kata’s effectiveness, discuss the process for digital transformation, and explain the need for data monetization. We recommend the development of an IIoT-savvy workforce, traceability of 4M (men, method, materials, and machine), and present the task scorecards and dashboards for real-time monitoring and decision-making. We highlight the positive impact of IIoT-enabled traceability on overall equipment effectiveness (OEE). The company reduced its workforce from 15 to 13 operators, increased OEE from 75% to 85%, and improved average throughput from 60 to 90 assemblies per hour. The time for traceability of 4M (men, machines, material, and method) was reduced from hours to minutes. The factory eliminated 350 paper documents to achieve a paperless shop floor. This real-world case study serves as a model for companies looking to transition from traditional continuous improvement processes to IIoT-supported lean manufacturing. Full article

Financial technologies metamorphose economies with customer-focused innovation. In this way, financial inclusion is fostered and economic growth is increased. However, risks, trust issues, and ethical concerns stem from the faster advancement of digital technologies and expanding financial innovation. Thus, this paper aims to understand the risks and barriers associated with FinTech and consumer adoption, focussing on the impact of digitalization on financial products/services’ acceptance. The research investigates the impact of digitalization on financial services and the recognition of the role played in the global economy by FinTech. For this reason, the regression analysis was used to explore the influence and correlation of various variables on FinTech in Central and Eastern European (CEE) countries, such as Internet usage, online shopping, paying bills via the Internet, and making and receiving digital payments. The results show differences between three clusters of CEEs in terms of FinTech adoption. While several past studies have explored the advantages of FinTech, few studies have investigated the risks associated with its adoption, trust, and barriers to its usage in different country contexts. The present paper fills the gap by analysing the data on Internet usage, online shopping, paying bills via Internet, and sending or receiving digital payments in CEE countries. The study recommends that FinTech companies share information online not only to present their offerings to users, but also to promote financial education through clear and straightforward communication about the features of their services. This approach can indirectly benefit society by contributing to financial development, inclusion, social stability, and, consequently, sustainable development. Full article

This paper explores consumer decision making, particularly focusing on the increasing prevalence of choices on the Internet such as online shopping. Examining the fundamental question of how individuals decide how to decide, our paper draws upon the effort–accuracy framework. This framework indicates that people typically consider both the cognitive effort associated with employing a specific decision strategy and the decision quality (i.e., accuracy) implied by using a particular strategy. However, decision strategies with high accuracy imply high effort. Empirical evidence shows that people often use decision strategies that require little effort. As a result, accuracy is often not high. Against this backdrop, this paper introduces a quantitative approach leveraging principal component analysis (PCA) as a decision support tool. Based on a simulation study, the approach demonstrates that it is possible to maintain high accuracy with significantly reduced effort in multi-attribute decision situations where attribute information is available in a quantitative format. This demonstration is based on the example of two decision strategies, which are both theoretically and practically highly relevant: the multi-attribute utility model (MAU) and the elimination-by-aspects strategy (EBA). By employing PCA for dimensionality reduction, the approach becomes particularly advantageous for online shops and online comparison portals, presenting users with concise yet accurate information. It is important to emphasize that our PCA approach is designed for data with a natural ordering, primarily focusing on quantitative variables. Consequently, decision situations where qualitative variables (e.g., product design or color) play a role in the decision-making process will need further exploration in future studies. However, we present a first solution to this problem so that our approach, based on this solution, can be implemented by online shops and online comparison portals in the near future. Full article

This study examines the relationships between socio-demographic factors, purchase frequency, internet expertise, and unethical return behavior in apparel e-commerce, with a particular focus on the act of wardrobing—wearing and then returning used apparel. The research involved a survey of 1026 online apparel consumers from Portugal and the Czech Republic. The results show that frequent buyers, internet-savvy users, women and younger e-consumers report more satisfactory return experiences. However, several e-consumers engage in wardrobe shopping, with higher rates observed among males, internet-savvy users and youth. There are differences between the countries studied: in the Czech sample, men and advanced internet users are more likely to engage in wardrobing, while in the Portuguese sample, it is more prevalent among younger e-consumers. The results also document that, overall, men are seven times more likely to practice unethical return, while increasing age decreases the likelihood. The originality of the study lies in its approach and findings, which contribute to the understanding of post-purchase behavior and moral hazards in e-commerce and highlight the need for retailers to balance return policies that prevent abuse while maintaining customer satisfaction. Recommendations are made for improving loyalty programs and personalizing the e-shopping experience to minimize returns and promote ethical consumer behavior. Further research is suggested to develop these findings and improve return management in apparel e-commerce. Full article

The purpose of this study is to explore the key roles and functions of institutions or organizations in the process of the spatial activation and industrial transformation of leisure fishing villages and to summarize this operating model. This study takes Xunpu Village, Quanzhou City, Fujian Province as the research object, which is well-known for its recreational fisheries. It mainly uses case study methods and uses on-site surveys and interviews to understand the formation time, spatial distribution, and business type information of the Zanhuawei shops in Xunpu Village. Zanhuawei, which refers to the traditional hairstyle of Xunpu women, was later applied for national intangible cultural heritage status in China. After the outbreak, the spread of Zanhuawei on the Internet inspired a large number of tourists to visit Xunpu Village to experience Zanhuawei. The study found that (1) Zanhuawei industry replaced traditional fishery and became the leading industry type in Xunpu Village. (2) The operating model led by the government and integrating public and private funds has had a stimulating effect on the revitalization of local commercial and residential space, and a large number of idle spaces have been reactivated. (3) The cooperation model between a large number of investors and local fisherwomen has completely changed the economic model of the village. Zanhuawei industry mobilized all official and media resources to promote spatial activation at various scales, including regions, settlements and commercial spaces. Full article

The year is 2030. The internet has evolved into the metaverse. People navigate through advanced avatars, shop in digital marketplaces, and connect with others through extended reality social media platforms. Three-dimensional patient scans, multidisciplinary tele-collaborations, digital twins and metaverse health records are part of clinical practices. Younger generations regularly immerse themselves in virtual worlds, playing games and attending social events in the metaverse. This sounds like a sci-fi movie, but as the world embraces immersive technologies post-COVID-19, this future is not too far off. This article aims to provide a foundational background to immersive technologies and their applications and discuss their potential for transforming healthcare and education. Moreover, this article will introduce the metaverse ecosystem and characteristics, and its potential for health prevention, treatment, education, and research. Finally, this article will explore the synergy between generative artificial intelligence and the metaverse. As younger generations of healthcare professionals embrace this digital frontier, the metaverse’s potential in healthcare is definitely attractive. Mainstream adoption may take time, but it is imperative that healthcare professionals be equipped with interdisciplinary skills to navigate the plethora of immersive technologies in the future of healthcare. Full article

The unprecedented production and sharing of data, opinions, and comments among people on social media and the Internet in general has highlighted sentiment analysis (SA) as a key machine learning approach in scientific and market research. Sentiment analysis can extract sentiments and opinions from user-generated text, providing useful evidence for new product decision-making and effective customer relationship management. However, there are concerns about existing standard sentiment analysis tools regarding the generation of inaccurate sentiment classification results. The objective of this paper is to determine the efficiency of off-the-shelf sentiment analysis APIs in recognizing low-resource languages, such as Greek. Specifically, we examined whether sentiment analysis performed on 300 online ordering customer reviews using the Meaning Cloud web-based tool produced meaningful results with high accuracy. According to the results of this study, we found low agreement between the web-based and the actual raters in the food delivery services related data. However, the low accuracy of the results highlights the need for specialized sentiment analysis tools capable of recognizing only one low-resource language. Finally, the results highlight the necessity of developing specialized lexicons tailored not only to a specific language but also to a particular field, such as a specific type of restaurant or shop. Full article

This study aims to explore the effect of the e-servicescape on the emotional response and revisit intention of customers in an internet shopping mall (ISM) environment. The literature was reviewed on the e-servicescape, emotional response, and revisit intention in an internet shopping mall. A relevant model and hypothesis were established. For the empirical study, a survey form was developed and conducted on 150 customers with experience using a certain ISM. Reliability analysis and confirmatory factor analysis were performed using SPSS 27.0 and Amos 26.0 software, and the causal relationships were identified through structural equation modeling (SEM). Study results and implications were discussed and suggested. Among the factors of the e-servicescape in an ISM, aesthetics and surrounding elements did not have a significant effect on emotional responses, and spatial functionality showed a positive effect on emotional responses. Aesthetics had a weak negative effect on revisit intention. Surrounding elements and spatial functionality had no significant effect on revisit intention. The emotional response had a positive effect on revisit intention. This study identified the importance of the e-servicescape in the ISM environment and especially emphasized the importance of spatial functionality on the emotional response and aesthetics on revisit intention. This study presented several suggestions and implications to corporate managers regarding the development and management of the future ISM environment and other similar business settings. Full article