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Purpose: This study differentiates pure impulse buying behaviour from suggestive impulse buying behaviour in using mobile shopping applications (apps). This study aims to assess the moderating effects of instant discount and cashback promotional offers along with the mediating effects of impulse buying intention (IBI) and user satisfaction (US), using the app stimuli (performance expectancy, effort expectancy, layout, atmosphere, privacy and security). Design/methodology/approach: The study was done in three stages: analysis of variance, followed by structural equation modelling (SEM) and paired t-tests. Findings: The results showed that instant discounts and cashback offers are different from each other for the mediating variable IBI. The SEM results for pure impulse buying showed that, except for layout, the remaining variables have a positive relationship with IBI. For suggestive impulse buying, effort expectancy and layout were significantly related to both the mediating variables. Finally, pure and suggestive impulse buying behaviour showed significant differences. Originality/value: Previous studies have looked into impulse buying in its generic sense and not through the "types" of impulse buying they were measuring. As impulse buying behaviour is a predominant theme for discussion today, marketing professionals and researchers must comprehend the impact of app stimuli in the context of select types of impulse buying behaviour. [ABSTRACT FROM AUTHOR]

This study constructed a research framework for exploring the relationship between the three dimensions of app quality (system quality, information quality, and service quality), flow experience, brand trust, and intention to transact based on the business‐to‐consumer e‐commerce platform. The proposed model was tested by analyzing questionnaire survey data from a sample of 503 consumers with experience of mobile online shopping using the variance‐based structural equation modeling technique. The results showed that all three dimensions of app quality were positively associated with flow experience and brand trust. Flow experience was positively associated with intention to transact. The effect of brand trust on consumers' intention to transact was greater than that of flow experience, suggesting that when shopping on a mobile app platform, consumers may be more concerned about trusting the brand than about pleasure in making a purchase decision. The results enrich business‐to‐consumer e‐commerce theory and provide meaningful managerial implications. [ABSTRACT FROM AUTHOR]

The primary objective of this article is to attempt to assess the role of ICT in shaping more environmentally friendly and sustainable consumer behaviour in buying, selling, exchanging and recycling clothes, shoes and accessories. The research questions were related to the impact of ICT technologies, particularly mobile applications and websites offering vintage items, on the development of sustainable behaviour related to online shopping and increasing awareness regarding environmentally friendly consumer behaviour. This research problem is particularly relevant given the economic, energy, political and environmental crises in selected countries: Poland, Spain and Turkey. The comparison was made at the turn of December 2022 and January 2023, in the situation of a deepening economic crisis in the examined countries, stimulated by progressive political crises, inflation and the war in Ukraine. The data were collected using a survey distributed using CAWI (Computer-Assisted Website Interview) technique on the servers of the Faculty of Management of the University of Warsaw. In total, there were 353 respondents who completed the entire survey, out of which 114 survey participants were from Poland, 151 from Türkiye and 88 from Spain. The limitation of the work was that the survey was conducted with the participation of the representatives of an academic environment and the results were used for a comparison of only three selected countries. Nevertheless, its innovation consists in the fact that the authors compare, for the first time in the literature, the opinions of respondents on Internet applications concerning supporting and shaping more environmentally friendly and sustainable consumer behaviour in culturally diverse countries, under different crisis conditions. The results of the conducted survey concerning clothing and footwear consumption can be useful for practitioners to point to possible strategies to raise consumer awareness and shape more sustainable consumer behaviour in culturally diverse countries located in different geographical regions using ICT technologies. [ABSTRACT FROM AUTHOR]

In-store grocery shopping is still widely preferred by consumers despite the rising popularity of online grocery shopping. Moreover, hardware-based in-store navigation systems and shopping list applications such as Walmart's Store Map, Kroger's Kroger Edge, and Amazon Go have been developed by supermarkets to address the inefficiencies in shopping. But even so, the current systems' cost-effectiveness, optimization capability, and scalability are still an issue. In order to address the existing problems, this study investigates the optimization of grocery shopping by proposing a proximity-driven dynamic sorting algorithm with the assistance of machine learning. This research method provides us with an analysis of the impact and effectiveness of the two machine learning models or ML-DProSA variants—agglomerative hierarchical and affinity propagation clustering algorithms—in different setups and configurations on the performance of the grocery shoppers in a simulation environment patterned from the actual supermarket. The unique shopping patterns of a grocery shopper and the proximity of items based on timestamps are utilized in sorting grocery items, consequently reducing the distance traveled. Our findings reveal that both algorithms reduce dwell times for grocery shoppers compared to having an unsorted grocery shopping list. Ultimately, this research with the ML-DProSA's optimization capabilities aims to be the foundation in providing a mobile application for grocery shopping in any grocery stores. [ABSTRACT FROM AUTHOR]

This study explores how gamification impacts retail customer experience, emphasizing the need for businesses to differentiate in competitive markets. Gamification involves using game design elements in non-game contexts. The research presents a unique gamified shopping system using location-based (Beacon) technologies with a mobile application. This system engages customers through interactive games and challenges in specific store locations. With a sample size of 25, this study aimed to address the following research questions: What gamifying methods could be applied in a real store? What impact does gamification have on customer experience in a real-store shopping context? What role could gamification play in motivating customers to have an eco-friendly purchasing experience? The application includes features like a suggestion page, puzzle, scoreboard, and a points-based reward system. Study findings showed a significant positive correlation between gamification strategies and customer experience, which aligns with the self-determination theory. The app also integrates eco-friendly features and social interaction elements for an innovative and environmentally friendly approach to enhancing the retail customer experience. This study presents a practical example of gamifying methods integrated into a real store environment, which has the potential to boost the shopping experience for customers and shoppers and protect the environment. [ABSTRACT FROM AUTHOR]

Businesses add gamification to their mobile shopping applications to increase customer interaction and their continuance intention. It has been observed that, with gamification based mobile shopping activities, consumers have positive experiences, and their customer loyalty has increased. Therefore, it is crucial to research the effects of gamification content used in mobile shopping applications on consumers' tendencies to use or not use technology. This research aims to determine the effect of gamification activities offered in mobile shopping applications on users' perceived ease of use, perceived usefulness, attitude, and intention using the Technology Acceptance Model (TAM). The research used a convenience sample of 442 mobile shopping applications users living in Turkey and an online survey method was used to collect the research data. Considering the analyses of the research, the relationship levels between the variables were determined. There are significant relationships between PEOU and GAM (r =.939), PU and PEOU (r =.874), ATT and PU (r =.827), INT and ATT (r =.969). Reliability and validity analyses were applied. The factor loadings of the scales, and AVE value above.50, Cronbach's Alpha (Cα), and CR value above.70 were considered statistically reliable and valid. The technique of structural equation modeling (SEM) was used to estimate the variables' effect and mediation levels. Then, it was found that perceived ease of use had a positive and significant mediating effect (β =.339) between gamification and attitude variables. Similarly, perceived usefulness had a positive and significant (β =.827) mediating effect between gamification and attitude variables. [ABSTRACT FROM AUTHOR]

Purpose: The present study aims to propose a framework elucidating the attributes of mobile augmented reality (AR) shopping apps (i.e., spatial presence, perceived personalization and perceived intrusiveness) and how they translate to downstream consumer-related outcomes (i.e., immersion, psychological ownership and stickiness to the retailer). Design/methodology/approach: By conducting a questionnaire-based survey, 308 responses were collected, and the data were submitted to partial least square structural equation modeling (PLS-SEM) and artificial neural network (ANN) analyses. Findings: A few important findings were generated from the present study. First, attributes of mobile augmented reality shopping apps (i.e., spatial presence, perceived personalization and perceived intrusiveness) influence stickiness to the retailer through immersion and consumer empowerment in serial. Second, immersion positively influences psychological ownership. Third, the optimum stimulation level moderates the relationship between spatial presence and immersion. Lastly, a post-hoc exploratory finding yielded by the multigroup analysis uncovered the moderating effect of gender. Originality/value: This study offers a novel contribution to the smart retail literature by investigating the role of mobile AR shopping apps in predicting consumers' stickiness to the retailer. A holistic framework elucidating the serial mediating effect of immersion and consumer empowerment, and the moderating roles of optimum stimulation level and gender were validated. [ABSTRACT FROM AUTHOR]

To understand how hedonic shopping orientation affects the desire to reuse mobile applications, this study will examine the mediating impact of the need for mobile app atmosphere as well as the moderating role of mobile irritation. 222 consumers who used mobile applications for their shopping provided information via an online survey. Process Macro testing was done on the research model. The test results indicate that there is a strong beneficial impact of hedonic shopping orientation on the intention to reuse mobile apps. Simultaneously, hedonic shopping orientation has a considerable impact on the intention to reuse mobile apps due to the positive mediating role of the need for mobile app atmosphere and the negative moderating influence of mobile irritation. This study presents implications for mobile app retailing and expands the field of research on mobile shopping behavior. Important information is also provided for mobile customers who have a hedonic shopping orientation. [ABSTRACT FROM AUTHOR]

Purpose: The primary purpose of this study is to examine the relationship between conumers' emotional attachment towards fashion apps and positive behavioral outcomes, such as e-WoM and repurchase intention. The study also aims to explore how e-servicescape, customer experience and perceived value of online shopping influence this relationships. Design/methodology/approach: The study has used quantitative research methods to collect data from a sample of 484 consumers who had previous experience of purchasing using fashion apps. Data were collected from university students enrolled in university in Gujarat, India using an online self-administered questionnaire. The data are analyzed using structure equation modeling to determine the relationships between the variables under investigation. Findings: The results demonstrate relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM. The study found support for hypotheses 1, 2 and 3, highlighting the influence of e-servicescape, customer experience and perceived value of online shopping in developing emotional attachment with fashion apps. The study also confirmed hypotheses 5 and 6, which suggest that consumers who have a stronger emotional attachment to fashion apps are more likely to intend to repurchase fashion products and engage in positive electronic word-of-mouth behavior for fashion brands. Originality/value: In today's digital age, fashion apps are vital for fashion retailers to remain competitive and offer their customers a smooth and immersive shopping experience. Given the potential impact of fashion apps on the customer behavior, it is essential to investigate the relationship relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM in the context of fashion apps. The findings of the study are expected to contribute to the understanding of consumer behavior in the context of fashion apps and e-commerce more broadly. The results may also provide insights into how fashion retailers can improve their online presence and customer experiences to increase emotional attachment and positive behavioral outcomes. Practical implications: The results of this study have several implications for online retail managers and fashion app developers. The study provides strong support for the idea that the extent to which online customers feel emotionally attached to fashion apps is strongly related to their e-WoM and repurchase intention. Moreover, the results of the study suggest that online retailers who are looking to cultivate emotional connections with consumers through fashion apps should prioritize three key areas: e-servicescape, customer experience and perceived value of online shopping. [ABSTRACT FROM AUTHOR]

This study explores the affordances of "scan and go" apps and their influence on the flow experience of retail customers to provide a unique insight into user–technology interaction. Through a constructivist ethnographic approach, the research examines how users' socially constructed perceptions and interpretations shape these interactions, and it emphasizes the role of the material and social environment. The research innovatively conceptualizes affordances as a flow process; it introduces an affordances flow funnel that encompasses three distinct stages: perceived affordances, actualized affordances, and affordance dichotomy. By following this process, the study improves understanding of user emotions and behaviors that range from apathy to excitement, from gratification to provocation, and from abandonment to absorption. Findings underline the importance of equipping users with support to navigate technological and environmental constraints, thereby ensuring successful affordance actualization. The research contributes to the literature by revealing a new affordance type, namely affordance dichotomy, and offers valuable insights for marketers and developers to enhance user experiences and absorption behavior. Recognizing its focus on scan and go apps within supermarket contexts, the study invites future research to extend this understanding to different contexts and technologies. [ABSTRACT FROM AUTHOR]

Click-through rate (CTR) prediction plays a crucial role in online services and applications, such as online shopping and advertising. The performance of CTR prediction can have a direct impact on user experience and the revenue of the online platforms. For CTR prediction models, self-attention-based methods have been widely applied to this field. Recent works generally adopted the Transformer architecture, where the self-attention mechanism can capture the global dependencies of the user's historical interactions and predict the next item. Despite the effectiveness of self-attention methods in modeling sequential user behaviors, most sequential recommenders hardly exploit feature interaction techniques to extract high-order feature combinations. In this paper, we propose a Feature-Interaction-Enhanced Sequence Model (FESeq), which integrates feature interaction and the sequential recommendation model in a cascading structure. Specifically, the interacting layer in FESeq is an automatic feature engineering step for the Transformer model. Then, we add a linear time interval embedding layer and a positional embedding layer to the Transformer in the sequence-refiner layer to learn both the time intervals and the position information in the user's sequence behaviors. We also design an attention-based sequence pooling layer that can model the relevance of the user's historical behaviors and the target item representation through scaled bilinear attention. Our experiments show that the proposed method beats all the baselines on both public and industrial datasets. [ABSTRACT FROM AUTHOR]

The goal of this article is to uncover the innovative changes that have emerged in Tourist Information Centres (TICs) in Lithuania as a result of the COVID-19 pandemic. The article is based on the assessment of primary research data collected through completed in-depth questionnaires. The research results revealed that a significant number of TICs transformed their activities while adapting them to local tourists. TICs introduced new products, attractions, and services, updated webpages and mobile applications, and created online souvenir shops. The research results indicated that, because of the lockdown, some state tourism institutions in the regions, along with local service providers, experienced a 'renaissance' and a successful period. New products and services were essential for the tourism sector's survival, and the majority of them continue to be used in the post-COVID reality, providing opportunities for greater resilience and reduced dependence on unexpected circumstances in the future. This article addresses discussion points related to general changes in tourism services in the context of resilience and the application of innovations. Additionally, the article introduces the concept of Re-tourism, which adds value to the development of the theoretical framework for post-COVID tourism. [ABSTRACT FROM AUTHOR]

The study investigates how value‐in‐use generated on branded mobile apps from supermarkets affects brand satisfaction and loyalty through two models. The first model assesses how value‐in‐use dimensions (i.e., personalization, experience, and relationship) affect the outcomes, and the mediation of satisfaction and the moderation of age on those relations. The second model decomposes experience and relationship into subdimensions. The Structural equation modeling results show that personalization, experience, and relationship influence satisfaction, although experience has a negative effect. Age moderates the relations, where younger individuals value personalization and older individuals value experience and relationship. Regarding the individual subdimensions, only behavioral experience, and app trust and commitment are relevant for satisfaction, whereas behavioral experience has a negative effect. In both models, satisfaction significantly influences loyalty and mostly acts as a full mediator. Two FGDs were conducted to understand the negative effect of experience on brand satisfaction. The results show that experience is mostly utilitarian with grocery apps and apps that require increased effort yield less satisfaction. The study enriches the literature on Service‐Dominant Logic and value‐in‐use. The findings can provide managers with insights on using branded grocery apps to enhance the value co‐created between the consumer and firm. [ABSTRACT FROM AUTHOR]

Mobile shopping apps have experienced significant global growth due to the widespread adoption of mobile devices in everyday life. The exponential expansion of mobile shopping app usage has brought up both opportunities and challenges for service providers. For online businesses, maintaining their current users is a vital means of gaining a competitive edge. Hence, the primary objective of this research is to develop a conceptual model to examine the factors that influence users' intention to continue using mobile shopping apps. The Expectation-Confirmation Model (ECM) and the Theory of Network Externalities offer initial foundations for developing a unified conceptual model. This research has the potential to make a substantial contribution to the understanding of factors that influence continuance intention to use mobile shopping apps. It can benefit academicians, online businesses, service providers and mobile marketing practitioners. [ABSTRACT FROM AUTHOR]

In the current scenario use of the Internet for various online services is rising. We are doing online shopping, banking, booking, trading and accessing social networking site with the help of web applications or mobile apps. Database of the web application is the treasure which contains sensitive and valuable information of an individual such as personal, financial, medical and organization .This led to need for assuring confidentiality, Integrity, and availability of user data. Whether it’s a small or enterprise web application the data stored by that application is crucial. The motive of this paper is to explain sql Injection and SQL Injection attack process . It describes the impact of SQL Injection and types of SQL Injection attack and categorize it. At last it summarizes and review the analysis of SQL Injection detection and prevention technique according to each author on the basis of algorithm technique, dataset, platform used, results and future scope . This analytical review will be helpful to the researcher for further research in the interested area of SQL Injection. [ABSTRACT FROM AUTHOR]

User eXperience (UX) evaluations play an essential role in the software development process. As the results from such evaluations can drive future releases, it is necessary to identify which factors can substantially change users' judgments about their experience to have more precise results and understand UX better. This article investigates how interaction sequencing, previous experience, and the number of problems could affect overall satisfaction and the two main UX dimensions: pragmatic and hedonic. We employed three different evaluation methods to evaluate a chatbot-based mobile shopping application. The results revealed that participants with previous experience with similar apps tended to give lower ratings. We also found that as inspectors identify more problems, they tend to rate the pragmatic dimension lower. Finally, we did not identify a significant influence of interaction sequencing on UX evaluation. We discuss the reasons for these results, the implications for practitioners and researchers, and research opportunities. [ABSTRACT FROM AUTHOR]

Automatic Speaker Profiling (ASP), is concerned with estimating the physical traits of a person from their voice. These traits include gender, age, ethnicity, and physical parameters. Reliable ASP has a wide range of applications such as mobile shopping, customer service, robotics, forensics, security, and surveillance systems. Research in ASP has gained interest in the last decade, however, it was focused on different tasks individually, such as age, height, or gender. In this work, a review of existing studies on different tasks of speaker profiling is performed. These tasks include age estimation and classification, gender detection, height, and weight estimation This study aims to provide insight into the work of ASP, available datasets, feature extraction techniques, and learning models. Further, the performance of current speaker profiling systems is investigated. Finally, the challenges of speaker profiling are presented at the end of this review. [ABSTRACT FROM AUTHOR]

Mobile shopping application can provide retailers the opportunity for showcasing their brands and shopping experiences to the customers since the use of smartphones are increasing. Therefore, this study was conducted to determine the e-service quality of mobile commerce applications (MCA) in enhancing customer loyalty intention behaviour to purchase the product via MCA among online shoppers in Malaysia through the use of the adapted SERVQUAL model. Additionally, the mediating effect of customer satisfaction on the relationship between MCA service quality dimensions and customer loyalty intention behaviour was studied. A purposive sampling technique was used and 120 data were collected through an online survey. The results for direct testing demonstrate that all the SERVQUAL dimensions were significantly influenced customer satisfaction, except reliability, security and usability. Meanwhile, analysis results for the mediating effects demonstrate that customer satisfaction mediates the relationship of SERVQUAL dimensions (assurance, personalization, responsiveness and information quality) and customer loyalty intention. Even though the SERVQUAL dimensions tested in this study were significant, the effect size is rather small. Nevertheless, all these factors are important to be considered for the improvement of MCA, especially everyone is moving forward to a digital business environment and e-service is regarded to play an important role. [ABSTRACT FROM AUTHOR]

The introduction of mobile shopping apps has resulted in the growth of impulse buying or excessive compulsion, especially in the fashion industry. This paper aims to establish a relationship between app stimuli (including performance expectancy, effort expectancy, atmosphere, layout, and privacy and security) and impulse buying behaviour. Besides this, it also examines the moderating effects of the video product presentation and product scarcity claim and the mediating effects of impulse buying intention and user satisfaction. The study was carried out in two phases. In the first phase, a paired t-test analysis was carried out to compare the mean of each set. This was followed by multi-group structural equation modelling to check the model's validity. The results show that while video product presentation produced a significant difference between impulse buying intention and impulse buying behaviour for both the male and female respondents, scarcity claims achieved positive results only for male participants. The SEM results, meanwhile, demonstrated that both the mediating variables bear a relationship to performance expectancy, privacy and security, and impulse buying behaviour. However, effort expectancy was only related to impulse buying intention, while atmosphere and layout were exclusively associated with user satisfaction. Based on the findings of the study, theoretical and managerial implications are presented. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the popularity of the Internet and smartphones, many stores are launching mobile APPs to make shopping more convenient for consumers. A new business model, Online to Offline (O2O), is becoming more popular in different businesses. More consumers are using APPs to buy things in physical stores. Therefore, based on the Value-based Adoption Model (VAM), the study aims to investigate the factors that influence the APP-adoption intention of consumers. Specifically, the current study attempts to investigate the relationships between promotional benefits, technicality, value perception, and adoption intention among mobile APP users. With a sample of 200 participants who are using McDonald's mobile APP in Vietnam, this study conducted a quantitative research method, using regression analysis for hypothesis testing. The findings show that the benefits of sales promotion (savings, quality, convenience, and value expression) from the providers and the APP's technicality have a significant influence on consumers' APP-value perception and APP adoption intention. Besides, value perception has a positive influence on consumers' intention to adopt mobile APPs. The findings provide implications for practitioners to develop and apply new mobile APPs from the perspective of improving consumers' value cognition. [ABSTRACT FROM AUTHOR]

Haptics are innovative sensory-enabling technologies that can be used to improve consumers' online shopping experiences. These technologies can be used in addition to other actual sensory stimulation, such as visual and auditory. However, little is known of how the addition of haptics affects consumers' mobile shopping behavior. Therefore, this article examines the effect of the presence of haptic feedback (i.e., vibrations) when shopping on a retailer mobile app. Drawing on the results of three quantitative studies, the findings show that the presence of haptic feedback influences consumer behavior, but consumers' perceptions modify the outcome, which is also moderated by individual need for touch. Moreover, the findings herein show a sequential mediating effect of psychological and affective variables on purchasing outcomes. These findings therefore stress the importance of considering haptics as a potential economic value for online shopping. Accordingly, we suggest that retailers should be more aware of their online sensory strategies and think about disclaimers and personalizing the consumer interface (e.g., turning off the haptic feedback). [ABSTRACT FROM AUTHOR]

Usability is one of the most important characteristics of software applications, especially when it comes to mobile shopping applications. There is a great deal of shift from traditional shopping to online shopping because it benefits both parties i.e., customers as well as businessmen. In such a scenario, the usability factor can play a very vital role in the business industry. If a client stops using a mobile shopping app because it is not user-friendly, it can badly damage the annual revenues especially when hundreds of alternatives are available and there is tough competition. Therefore, to keep existing customers intact and to attract new customers, it is very important to provide a user-friendly mobile app to customers. This paper considers a large variety of online customers with diverse requirements. background and constraints and evaluate the usability of existing mobile e-commerce apps to identify the problems people face with existing applications and do a systematic review of existing shopping apps. Then, we propose a personalized and adaptive usability model for mobile commerce apps considering the neglected user type i.e., illiterates and people with tactile disabilities. The proposed model LRAP is a layered approach from generalization to specification and it can be considered an extension of the famous PACMAD usability model. Besides this, we also suggest a combining score tool which will be helpful in measuring the usability of any app. Participant-based usability evaluation is the major technique used to identify the design problems in existing mobile commerce apps. Major design issues identified in mobile commerce apps include poor navigation and lack of personalization for illiterates and people with tactile disabilities. [ABSTRACT FROM AUTHOR]

This study investigates the transformative effect of the COVID-19 pandemic on the development and implementation of advanced technologies in the Czech Republic's assisted retail sector. The pandemic accelerated digital transformation across industries, and retail was no exception. The enforced changes in shopping habits and safety measures have led to a surge in the demand for technology-driven solutions in retail, pushing businesses towards innovation to ensure continuity and resilience. The paper analyzes both qualitative and quantitative data gathered from various assisted retail businesses in the Czech Republic. The research employs a mixed-method approach, incorporating case studies, surveys, and statistical analysis to provide comprehensive insights into the swift technological transformations. The findings indicate a significant increase in the adoption of technologies such as contactless payments, augmented reality (AR), artificial intelligence (AI), and machine learning (ML) in retail operations. It further reveals the increased use of e-commerce platforms, digital marketing strategies, and mobile applications to promote contactless shopping. A notable aspect of the study is the rise of voice-assisted shopping, demonstrating a technological shift towards more personalized and efficient customer service. The implications of these findings suggest that the pandemic-induced circumstances have revolutionized retail technology in the Czech Republic. It also hints at the potential for other industries to learn from the strategies deployed in this sector. The study concludes by emphasizing the need for further research to assess the sustainability and long-term impact of these new technologies post-pandemic. [ABSTRACT FROM AUTHOR]

In recent years, China's e-commerce has made great progress, and the growth trend of online shopping is obvious. However, China's online sales are far below half of the United States. One of the important reasons is the privacy risks of e-commerce and insufficient consumer trust, but it still hinders the development of e-commerce online shopping applications. According to the trust survey, interaction is an important condition for generating trust and an important element. However, in the existing e-commerce trust surveys, the impact of interaction is analyzed, but few surveys only have an impact on consumers' shopping tendency. Therefore, this article considers the importance of reliability of e-commerce online shopping applications, as well as issues related to consumer privacy protection between blockchain and mobile clients. On this basis, this article explores the impact of consumer platform based shopping websites on reliability and the factors and mechanisms of consumer shopping behavior through theoretical analysis and empirical research, and designs a survey validation table for blockchain and mobile client privacy protection. The shopping direction identification system of e-commerce consumers has to some extent made up for the shortcomings of previous empirical research on e-commerce trust behavior. In the field of consumer research, e-commerce has the importance of becoming a specific practical indicator. [ABSTRACT FROM AUTHOR]

News aggregator apps have become one of the major channels for acquiring information for the Chinese. The number of users is increasing but literature on the user experience (UX) of these apps from the perspective of human-computer interaction remains dearth. In study 1, a completely randomized between-participant experiment with prior experience of news aggregator apps (with prior experience vs. without prior experience) as the independent variable was conducted to investigate its effects on the UX of news aggregator app's functions, including browsing news, searching news, watching short videos, interacting with news, personalized page setup and online shopping. UX was operationalized as perceived usefulness, ease of use, and satisfaction. Results indicated that the experienced users perceived lower levels of usefulness when they used the app to browse news, watch short videos, interact with news and set up the page than inexperienced users. Experienced users also perceived lower levels of ease of use when watching short videos. In addition, veteran users reported lower satisfaction levels when browsing the news. To explore the reason behind this phenomenon, a sentiment analysis (study 2) was conducted on the reports submitted by participants in the experienced group during the training sessions. It was found that the experienced group overall reported negative sentiment scores, and the results indicated positive trends of correlation between the sentiment score and the UX. The current research provides a more nuanced understanding of the effect of prior experience on the UX of news aggregator apps. [ABSTRACT FROM AUTHOR]

After the isolation caused by the pandemic, the entertainment sector has been forced to change the way it markets its products and services, and users have been adapting to the change. The objective of this research article is to provide added value and innovation to the advertising promotions of movies in the premiere, through the development of a mobile application based on augmented reality to improve customers’ shopping experience. For which the Agile Mobile-D Methodology was used for the development of the application and the results were studied using 5 indicators: Time to choose a movie, where an improvement of 38.26% was obtained compared to the Pre-Test; regarding the indicator time to acquire information about the movie, an improvement of 81.33% was obtained. 33%; concerning the third indicator, time to initiate the purchase, an improvement of 88% was obtained; concerning the fourth indicator, time to obtain a reminder, an improvement of 83.33% was obtained, making the time with the use of the application shorter; finally, concerning the customer satisfaction indicator, 73% of the users who used the application rated their experience as between satisfied and very satisfied. [ABSTRACT FROM AUTHOR]

With the considerable growth in the information and communication technology (ICT), several smartphone-based mobility platforms have already sprung up and they have the potential of transforming the mobility ecosystem completely. However, there is close to no knowledge available about how ICT-based smartphone apps meant for day-to-day trip planning tasks are being used across various user groups and how they influence travel outcomes, especially in Indian cities. Therefore, this study is an effort to close this gap by gathering data from the city of Bhopal and carrying out an exploratory statistical analysis on the usage of smartphone apps for different types of trip planning purposes, as well as their influence on travel outcomes. The study provides empirical evidence of relationships between smartphone app usage for trip planning (such as departure time, destination selection, mode selection, route selection, communicating and coordinating trips, and performing tasks online rather than visiting) and the resulting travel outcomes, such as kilometres travelled by vehicle (for purposes, such as work/education, shopping, and recreation), social gatherings, new destinations, and group trips. The chi-square test has been used to test and interpret several socioeconomic variables that could influence this relationship, such as gender, age, income, etc. The study's findings provide important behavioural insights that may be useful in policy discussions. [ABSTRACT FROM AUTHOR]

Different versions of mobile operating systems or shopping apps enable different functionalities and information flows, thus creating various mobile shopping environments. In general, up‐to‐date versions provide better information flows and richer functionalities. However, mobile operating systems and shopping apps affect consumer behavior through different mechanisms. An up‐to‐date mobile operating system reduces the system response time, while an up‐to‐date shopping app improves algorithms for better search accuracy. The former encourages consumer explore and search, whereas the latter improves consumer search efficiency and reduces chances for consumers to discover more products. Using a unique large‐scale clickstream data set from a mobile commerce retailer, we examine the effect of mobile operating system and app versions on consumer search and impulse purchase behaviors in mobile commerce. Our results show that consumers with an up‐to‐date mobile operating system or a previous version of a shopping app conduct more searches in terms of increased product page views and time spent on product pages, which results in a higher probability of consumer impulse purchase. However, consumers' search for individual products is not affected by versions. Surprisingly, though more page views or time spent may boost purchases, we find that consumer search affects impulse purchases nonlinearly in that page views and time spent have a decreasing rate of impact. Our computations show that using an up‐to‐date operating system increases consumer search activities by 60.45 product pages or 521.30 seconds spent browsing compared to using a previous version of an operation system. Using an up‐to‐date app decreases consumer search activities by 129.34 product pages or 1446.48 seconds spent browsing compared to using a previous version of a mobile app. [ABSTRACT FROM AUTHOR]

Business organizations have huge potential to increase their customer base by offering e-commerce services, especially in the post-pandemic era. Ensuring secure e-commerce applications plays an important role in increasing customer base. To develop appropriate policies and secure technological infrastructures, business organizations first need to establish an understanding of the reservations of their customers toward e-commerce, as well as their perception of security and privacy of e-commerce applications. In this paper, we present the results of an empirical study of e-commerce customers conducted in Pakistan to gain an insight into their mindset on using e-commerce applications. An online questionnaire was set up to collect data, which were analyzed using the partial least squares method with SmartPLS software. The empirical findings highlight that customers' concerns about credit card usage, concerns over information security, motivational factors for shopping offered by business organizations, customer trustworthiness, and user's feelings about the reputation of e-commerce impact their perception of security of online data and trust in an e-commerce application. The results of this study can help organizations in Pakistan to develop policies and improve technological infrastructures by adopting emerging technologies and digital forensics. [ABSTRACT FROM AUTHOR]

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In the evolving landscape of poverty research, especially in China, the focus has shifted from eliminating absolute poverty to relieving relative poverty. Although much of the existing studies have begun to use built environment big data, such as remote sensing and street view imagery, to measure poverty, peoples' consumption, an essential indicator of poverty receives less attention. This study delves into the relationship and spatial disparity between poverty measured by consumer big data and multidimensional poverty measured based on the census data. We investigated 1731 communities in Guangzhou as case study regions and combined their residents' mobile phone metadata and spatial cost of living data as the input consumer big data. Then, we constructed Index of Multiple Deprivation (IMD) levels based on the census data and built random forest classification model based on our consumer big data to predict IMD level at community level. The result shows that the predicted poverty of 81.11% communities were generally consistent with the IMD level, indicating that the consumer big data poverty mapping provided a viable poverty measurement from consumer behavior perspective. The SHapley Additive exPlanations' values result shows that Pinduoduo (a low-cost online shopping mobile application) contributes the most to predicted poverty from consumer behavior. For spatial disparities, poverty mapping based on consumer big data is more sensitive to the poverty in suburban developing neighborhoods and affordable housing communities compared with the IMD. The urban poverty mapping based on consumer big data offers a timely portray of communities' socio-economic challenges and consumption-related poverty, and provides support and evidence for accurate urban poverty alleviation strategies. • Innovatively employed consumer big data to spatially measure urban poverty. • Pinduoduo, fashion businesses, and mobile phone communication expenses are critical factors in identifying urban poverty. • Revealed potentially latent poverty in urban central and peripheral communities based on consumer big data. • Analyzed the mechanism of consumer big data for poverty estimation by analyzing individual communities. [ABSTRACT FROM AUTHOR]

This paper aims to examine the main challenges encountered by mobile grocery-shopping applications' (MGSAs) users, wherein the analysis is based on the review comments for three popular MGSAs deployed by main grocery retailers in Europe. The research methodology used was qualitative in the form of a cross-sectional inductive approach, allowing for the identification of the main issues encountered by users and their classification into four categories for a more straightforward presentation. The research findings indicate that despite the below-average level of digital literacy, customers are trying to use MGSAs efficiently and are proposing different areas of improvement, such as the design, the general functionality of the applications, and other factors regarding the specific functionalities of MGSAs. The findings may be leveraged by grocery retailers to exploit this market efficiently in a post-pandemic context; moreover, the study's results could provide meaningful knowledge to the mobile retail industry, as the detailed insights offer adequate support for enhancing mobile-shopping (m-shopping) applications. [ABSTRACT FROM AUTHOR]

Designers are challenged to create sustainable products that succeed in the marketplace, often relying on life cycle analyses to identify engineered sustainable features while neglecting perceived-as-sustainable (PAS) features. PAS features may not contribute to engineered sustainability but are identified by customers as sustainable. In previous papers, we proposed methods for extracting PAS features from online reviews using machine learning techniques and validating them using collage placement techniques. We demonstrated our methods using French presses (and other products). In this paper, we combined design and marketing approaches to test previously extracted PAS features in terms of purchasing products that include PAS features, as compared to others that do not. We built a simulated Amazon shopping experience using incentive alignment and constructed a within-subject, fractional factorial design with a variety of product features and physical appearances. We collected data on purchase intent, willingness to pay, and sustainability rating. We found that participants opted to purchase products with PAS features more often than products with features that are not PAS, termed "dummy" features. Participants also indicated they were willing to pay more for products with PAS features and rated those products as more sustainable, despite the features not contributing to engineered sustainability. Our findings demonstrate the potential value of identifying and including PAS features in sustainable products and a new application for shopping simulation experiments in design research. We recommend that sustainable designers include both engineered and PAS features in sustainable products to align with customer needs, drive purchasing decisions, and potentially increase profitability. [ABSTRACT FROM AUTHOR]

The study aims at determining the predictors of mobile grocery shopping applications (MGSAs) acceptance and their impact on behavioral intention to use MGSA during COVID-19 outbreaks. Based on the technology acceptance model and theory of planned behavior, we analyzed the influence of social distancing, fear of COVID-19, subjective norms, shopping attitudes, ease of use, usefulness on behavioral intention to use MGSAs. Data were collected from 565 users and analyzed with structured equation modeling (SEM) using SMART PLS 3 software. Findings depicted that shopping attitudes were predicted by subjective norms, ease of use, and usefulness. In contrast, behavioral intention is predicted by subjective norms, attitudes, ease of use, usefulness, fear of COVID-19, and social distancing. The study contributes to the extant literature incorporating fear of COVID-19 and social distancing as psychological and situational variables into the technology acceptance model and theory of planned behavior, which may guide the marketing practitioners to promote online sales in an unprecedented situation. [ABSTRACT FROM AUTHOR]

The main rationale of this research is the impact of in application mobile marketing strategies to purchase behaviour and consumers engagement as mediation relation. The study are filling the gaps and to enabling this study in Nigeria context of both existing evidence and its practical applications. The Role of Contemporary Mobile Marketing Strategies is acutely; how businesses deal with their consumers need by using different tools such as Campaigns, Promotions, Vouchers, Feeds. The Role of Contemporary Mobile Marketing Strategies frameworks like the following customer service activities regard for the rights of customers, offering quality services and products and giving info that's useful? and truthful?. The population for this research is all the residence in Nigeria who used Mobile apps for shopping. According to the reports, there are around 106 million of adults as estimated population and the targeted sample size is 385 subjects that respect the Kerjici and Morgan formula, but the plan is to collect 150% of the sample to secure enough proper sample after data screening. Data obtained from the survey is analysed by utilizing the software Statistical Package for the Social Sciences (SPSS 25) and SmartPLS 2.0. Based on the research objective, prediction and theory development, then the appropriate method is PLS-SEM. [ABSTRACT FROM AUTHOR]

To succeed in a rapidly growing mobile commerce environment, understanding the continuous usage intentions of mobile customers is critical, as it is associated with the customer retention rate. The foundation of future continuous app usage is influenced by superior customer experience. However, previous researchers have not addressed customer experience of mobile apps in the context of continuous usage, adequately. Moreover, today's app users tend to drop app usage soon after first-time use, even if they had accepted apps earlier. This behaviour enhances the significance of identifying the determinants of continuous usage intention of mobile apps. This quantitative study used the convenience sampling method to collect data by distributing online questionnaires. The researchers received 392 responses from shopping app users in the Western Province, during the COVID-19 pandemic in Sri Lanka. The structural equation modeling method was used to analyse the data. The findings reveal that customer experience, task-technology fitness, and satisfaction significantly influence continuous intention, while perceived usefulness is insignificant. The results also reveal that app design, security and customer services are the most influential influencers of customer experience. The findings also highlighted the mediating effect of customer satisfaction. The study also pointed out to a reluctance of Sri Lankan customers to use mobile apps continuously for online shopping. The findings are helpful for online market stakeholders to understand the antecedents of customer retention and to make critical decisions to ensure their survival in the mobile industry. Since the study of customer experience is a long-term process, future researchers can scrutinise how each phase of the customer online journey influences continuous usage intention. These scholars can also integrate customer demographic variables to examine how they affect the continuous usage intention. [ABSTRACT FROM AUTHOR]

The article reports that the U.S. e-commerce sector has expanded steadily since the beginning of the twenty-first century. Topics include examines in 2020, this sector accounted for several percentage of total retail sales nearing the global average of several percentage and represent increase over 2019; and considered a significant component underpinning this momentum is the growth of online food retailers and ordering services.

The growth of E-Commerce in the Philippines has shifted dramatically at an unprecedented pace during the COVID-19 pandemic, forcing consumers to shop online. The change in consumer behavior created a domino effect both for physical stores and e-commerce platforms. With the impact on the said area, the study focused on Shopee’s big online shopping events that make the platform the #1 Online Shopping Application in the Philippines as of 2020. The study empirically observed and analyzed how the factors influenced users to participate and develop their purchase intentions, considering the ongoing pandemic, allowing the researchers to identify the gaps in an online event. The factors that were observed are Celebrity Endorsers & Social Media Influencers, Advertising Appeal, Creative Sales Promotion/s, and Timing. The study used an online survey questionnaire, allowing the researchers to gather quantitative data through Likert Scale questions or statements that asked the respondents to answer based on their level of agreement. The effectiveness of each factor and its influence on purchase intention were determined by performing Descriptive Statistics and Regression Analysis as it was revealed that creative sales promotions (offering free vouchers, providing promotional codes, discount deals, etc.) to consumers and timing of events have a significant effect on Shopee users’ purchase intention, which are ideal for marketers to use as tools to develop effective marketing strategies to attract and persuade consumers to purchase products. However, Celebrity Endorsers & Social Media Influencers and Advertising Appeal are not significant or have no influence on online shoppers’ intention to purchase. As these may not be the ideal marketing tools or strategies to persuade consumers to buy, these can be relevant when it comes to building brand image and increasing brand awareness. The findings provided online businesses with insights to influence users’ purchase intent during online shopping event sales. [ABSTRACT FROM AUTHOR]