Mobile Commerce Applications Research Articles

Validity of Wearable Trackers for Measuring Steps, Energy Expenditure and Heart Rate in Korean Elderly

PURPOSE: This study aimed to assess the validity of a physical activity tracking device by comparing physical activity data from older adults, including the number of steps, energy expenditure, and heart rate (HR), with data obtained from research accelerometers, wearable watches, and mobile apps.METHODS: A total of 24 healthy older adults (aged 65-79 years) wore a wearable tracking device and used a respiratory gas analyzer while walking and running on a treadmill at speeds of 3.8 km/h, 4.8 km/h, 5.6 km/h, 6.4 km/h, and 8.0 km/h, in a randomized order. This study evaluated seven wearable devices: one research accelerometer (ActiGraph GT3X+), five smartwatches/fitness trackers (Samsung Galaxy Watch Active 2, Fitbit Versa 2, Xiaomi Mi Band 4, Garmin Forerunner 945, and Apple Watch Series 2), and one mobile application. Step counts were measured directly, HR was compared using a Polar H7 HR Sensor, and energy expenditure was assessed using a Quarkb2 respiratory gas analyzer.RESULTS: Commercial wearable watches and mobile applications were more accurate than research-grade accelerometers for monitoring steps during walking and running in older adults. HR measurements from wearable watches were more accurate than those from reference devices. Although energy expenditure measurements from mobile applications and wearable watches were less accurate than measurements of steps and HRs their accuracy was comparable to that of research-grade accelerometers.CONCLUSIONS: This study provides insights into the strengths of using wearable devices in healthcare and fitness fields, which seek to monitor and actively manage the physical activity of older adults using wearable trackers.

Analysis of User Journey Mapping Factors to Enhance User Experience in the Tokopedia Mobile E-Commerce Application

Analysis of User Journey Mapping Factors to Enhance User Experience in the Tokopedia Mobile E-Commerce Application

Investigating the Effect of m-Commerce Application’s Functional and Non-Functional Attributes on Usability and Continuance Intention

The development of mobile commerce (m-commerce) applications has indicated a shift in goals from ease-of-use to sustainable use in the future. This shift has prompted changes in the combination of attributes that constitute the usability of m-commerce applications. This study developed an m-commerce usability model that combines functional and non-functional attributes. The research data was collected using questionnaires distributed to users living in Jakarta and was processed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. The results demonstrate that efficiency, satisfaction, and effectiveness can explain the usability of m-commerce applications. This study proved that three non-functional usability attributes – productivity, navigation, and memorability – have a positive effect on efficiency, while two functional attributes of usability – content and security – positively influence effectiveness. The study further proved that beside non-functional attributes, functional attributes also play an important role in increasing the user experience in the m-commerce context and thereby contribute to improving the usability of m-commerce systems and the continuance intention. The overall results of the study can be used in developing strategies for m-commerce application developers to design applications that can satisfy users and help them complete their tasks correctly and efficiently.

Reordering Functions in Mobiles Apps for Reduced Size and Faster Start-Up

Function layout, also known as function reordering or function placement, is one of the most effective profile-guided compiler optimizations. By reordering functions in a binary, compilers can improve the performance of large-scale applications or reduce the compressed size of mobile applications. Although the technique has been extensively studied in the context of large-scale binaries, no study has thoroughly investigated function layout algorithms on mobile applications. In this article, we develop the first principled solution for optimizing function layouts in the mobile space. To this end, we identify two key optimization goals: reducing the compressed code size and improving the cold start-up time of a mobile application. Then, we propose a formal model for the layout problem, whose objective closely matches our goals, and a novel algorithm for optimizing the layout. The method is inspired by the classic balanced graph partitioning problem. We have carefully engineered and implemented the algorithm in an open-source compiler, Low-level Virtual Machine (LLVM). An extensive evaluation of the new method on large commercial mobile applications demonstrates improvements in start-up time and compressed size compared to the state-of-the-art approach. 1

Factors Influencing the Use of Mobile Social Commerce Application with UTAUT2 Extended Model

Background: Mobile social commerce is a collection of e-commerce activities accessed via mobile devices and supported by users actively engaging in commercial activities on social media. As a country with a substantial number of social media users, Indonesia has sufficient opportunities to implement mobile social commerce as application for online shopping. Objective: This study aimed to identify the factors influencing the use of mobile social commerce for online shopping, using Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). In this context, some variables were excluded, namely user behavior, price value, and moderating variables (age, gender, and experience). Additional variables considered included price saving orientation (PSO), privacy concerns (PC), social commerce construct (SCC), social support (SS), and trust (TR). Methods: Data were collected by distributing questionnaires to respondents who had used mobile social commerce for shopping, resulting in 320 collected responses. Furthermore, the collected data were analyzed using Partial Least Square-Structural Equation Modeling (PLS-SEM) method through SmartPLS 3.3.3 application. Results: The results showed that among the 17 proposed hypotheses, 6 were rejected, while 11 were accepted. Conclusion: In conclusion, the factors influencing the use of mobile social commerce consisted of effort expectancy, habit, hedonic motivation, SCC, SS, and PC. Therefore, future studies should concentrate on exploring the continued intention of users towards mobile social commerce application. Keywords: Mobile Social Commerce, Privacy Concern, Social Construct, Social Support, UTAUT

Configuring mobile app update strategy for growth: An empirical analysis of a landscape search model

PurposeThis study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.Design/methodology/approachUsing a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.FindingsThis study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.Originality/valueThis study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.

Mobile Commerce Application and Services – A Study on Customer Perception

The recent years have seen an explosive growth in the mobile phone industry. The concept of anytime and anywhere internet facility with an inexpensive and comparatively smaller computing infrastructure is the driving force towards mobile commerce. With the advancements in the Wireless communication, mobile commerce has become a new paradigm for personal communication without any constraints in location. The present study for customer awareness and facing problems at mobile commerce applications. Consumers have embraced the web based e commerce in their day to day life in such a way that they cannot think of doing their tasks without any electronic channel and this has made businesses to extend their services beyond electronic channel into mobile channel. This study results that Mobile commerce play important role infecting human life. Mobile Commerce’s future seems to be extremely safe. In the previous few years it has been seen that the potential of M-commerce has paved a way to new emerging practices for businesses in today’s world and India is also showing the positive prints of adaptation of M-commerce platform for the same.

A Mobile-Based Used Vehicle Buying System Implementation

Aspect-oriented software is characterized by enhanced reusability and maintainability compared to object-oriented software. In aspect-oriented software development, concerns scattered across objects are separated and modularized into aspects. This research is motivated by the buyer's mistrust in used vehicle transactions due to concerns over potential fraud. To address this, the study proposes designing an e-commerce application that facilitates interactions between prospective vehicle sellers and buyers, alleviating transactional apprehensions. The analysis and design phases of the software development cycle employ Use Cases to facilitate the identification and separation of concerns. Use Cases are chosen for their direct illustration of user-system interactions. The case study focuses on a mobile e-commerce application for used vehicle sellers and buyers. The research aims to analyze the impact of consumer motivation, perceived quality, and consumer attitudes on the decision to purchase used vehicles. The findings are expected to aid sellers in marketing their vehicles and assist buyers in making informed purchasing decisions

Deciphering the resistance behaviours towards mobile commerce applications: A Mobile Commerce Applications Resistance Theory (MOCART)

Over the last decade, mobile commerce (m-commerce) has disrupted the existing business industries via various m-commerce applications. Although the popularity of m-commerce applications such as mobile payment and mobile shopping has been growing substantially, it was reported that some mobile users are still resisting m-commerce applications on a worldwide basis. To explain the multifaceted resistance behaviours of mobile users (i.e., rejection, postponement, or opposition) towards m-commerce applications, this study builds a holistic framework named the M-Commerce Applications Resistance Theory (MOCART) by extending the Innovation Resistance Theory (comprises passive innovation resistance and active innovation resistance) with mobile users' information privacy concerns and mobile technostress. Subsequently, the MOCART is empirically verified with 1050 responses collected through a quota sampling technique. The empirical results support the rigorously established MOCART, suggesting that mobile users’ information privacy concerns, mobile technostress, and passive innovation resistance are the antecedents of active innovation resistance, which drives all three types of resistance behaviour towards m-commerce applications. Considering this, several crucial theoretical and practical implications of the MOCART are discussed.

Foodservice mobile application quality determinants’ impact on customer satisfaction and repeat usage intentions: The role of perceived risk

The current study aims to examine foodservice mobile commerce (MC) success model and investigate the relationships among its quality components, customer satisfaction, and repeat usage intentions in the restaurant context. The target population of the study was customers who had previous food delivery mobile application experience within the 12 months period. An online survey was conducted to collect the data and analyzed by the means of structural equation modeling. Ubiquitous connectivity, contextual offer, transaction accuracy, and content quality had significant positive impacts on customer satisfaction with food delivery mobile commerce application (MCA). The results also supported moderating effect of perceived risk on the relationship between customer satisfaction and repeat usage intentions. The study adds empirial evidence on the relationships between MCA quality components customer satisfaction. In addition, this study exaines the moderating role of perceived risk in the relationship between customer satisfaction and repeat usage intentions for food delivery mobile applications. The study can assist practitioners and MCA providers involved in the restaurant industry by showing how to configure quality components to satisfy customers and make them more willing to use food delivery mobile applications in casual dining restaurants.

Utilization of Data Science Analytics on Mobile Commerce Applications Marketing Strategies: An Example of the Influence of Personalized Offers on the Usage Intentions of Saudi Consumers

The integration of data science plays a vital role in the progression of mobile applications, as it enhances their overall effectiveness and provides users with more benefits. Data science tools have the potential to assist organizations in enhancing their brand marketing endeavors and providing personalized offers, therefore contributing to the overall improvement of consumer acquisition. Consequently, the primary objective of this research was to investigate the influence of the personalized offers aspect on users of mobile commerce applications in Saudi Arabia, in addition to the core elements of the technology acceptance model (TAM). The result of this study indicates that perceived usefulness exhibits the greatest degree of impact in influencing customer attitudes toward usage, with personalized offers following closely. The research further reveals that personalized offers exert a substantial favorable influence on customers’ attitudes towards their use. Additionally, the research reveals that personalized offers significantly influence individuals’ behavioral intentions concerning the use of m-commerce applications. This research offers significant insights that might inform future academic research in the field. Moreover, it provides app developers and enterprises with novel knowledge and comprehension to devise tactics that enhance the ongoing advancement of mobile commerce applications.

Customization at a glance: Investigating consumer experiences in mobile commerce applications

The study strives to examine how customization (CUS) affects customers' acceptance of m-commerce applications (MCA) and explore conditions where CUS would strengthen consumers' behavioral intention (BI). The study aimed to bring insights for mobile commerce applications by testing the unified theory of acceptance and use of technology 2 (UTAUT2) factors as mediators between customization and behavioral use. Our findings manifest that CUS positively impacts BI; this effect, meanwhile, has been partially mediated by the mediators illustrated in our model. Most importantly, all our evidence points out that CUS is key to understanding a customer's intention to adopt MCA. Unsurprisingly, products and services will be more helpful with CUS than with homogeneity in enhancing customers' BI to adopt MCA. Indeed, CUS's effect on BI is mediated by a wide range of mediated factors. Our results indicate that UTAUT2 factors influence customers' intentions to adopt MCA. Hence, this study considers it a significant value addition to the theory and practice.

Thermo-Pneumatic Artificial Muscle: Air-Based Thermo-Pneumatic Artificial Muscles for Pumpless Pneumatic Actuation.

To make robots more human-like and safer to use around humans, artificial muscles exhibiting compliance have gained significant attention from researchers. However, despite having excellent performance, pneumatic artificial muscles (PAMs) have failed to gain significant traction in commercial mobile applications due to their requirement to be tethered to a pneumatic source. This study presents a thermo-PAM called Thermo-PAM that relies on heating of a volume of air to produce a deformation. This allows for pneumatic actuation using only an electrical power source and thus enables pumpless pneumatic actuation. The actuator uses a high ratio between the heating volume and the deformable volume to produce a high actuation force throughout its entire motion and can produce either contractile or extension motions. The controllability of the actuator was demonstrated as well as its ability to handle heavy payloads. Moreover, it is possible to rely on either positive or negative pressure actuation modes where the positive pressure actuation mode actuates when heated and the negative pressure actuation mode relaxes when heated. The ability to use Thermo-PAMs for different modes of actuation with different operation methods makes the proposed actuator highly versatile and demonstrates its potential for advanced pumpless robotic applications.

Application of Unified Theory of Acceptance, Use of Technology Model and Delone & Mclean Success Model to Analyze Use Behavior in Mobile Commerce Applications

In order to assist businesses, create more efficient solutions and get the greatest benefits from these applications, this research was undertaken with the primary goal of identifying the elements that influence the behavior of utilizing food service applications and enhancing their use. Three variables from the Delone & Mclean IS Success Model and the measurement model, UTAUT, are used in this study's quantitative methodology. Users of food service applications on the island of Java make up the study's population. A total of 150 people responded to the samples. Purposive sampling was used to collect samples. Data analysis using SmartPLS version 4 and the PLS-SEM methodology. Five of the seven factors examined in the study of interest and usage behavior were found to be valid. This means that the use of food service applications can improve performance, assisted by supporting facilities and systems of good quality, so that it can affect the level of user acceptance of the food service application. This research can provide startups with an understanding of the factors that influence their application usage behavior, with the aim of increasing the acceptance and use of food service applications.

Why do mobile consumers resist mobile commerce applications? A hybrid fsQCA-ANN analysis

Since its inception, mobile commerce (m-commerce) has introduced many disruptive changes to the business world via various types of m-commerce applications, which refer to the novel applications of m-commerce in conducting tasks that require mobility, for instance, mobile payment and mobile shopping. In view that not all mobile consumers around the world are keen to adopt mobile commerce applications, this study seeks to clarify the roles of active innovation resistance barriers (comprising functional and psychological barriers) on three distinct forms of resistance behaviour exhibited by mobile consumers (i.e., rejection, postponement, or opposition) towards m-commerce applications through the theoretical lens of Innovation Resistance Theory. For this purpose, an asymmetric and non-linear model was built and analysed through a configurational approach complemented by machine learning. The results indicate that all active innovation resistance barriers matter but are not equally important in triggering the resistance behaviours. Theoretically, this study has advanced the Innovation Resistance Theory and enriched the existing literature on m-commerce applications resistance. Practically, to lower the resistance behaviours of mobile consumers towards m-commerce applications, practitioners are advised to prioritise strategies that could overcome the psychological barriers.

Evaluation of E-service Quality and its impact on Customer Satisfactions for Mobile Commerce Applications in Egypt

Evaluation of E-service Quality and its impact on Customer Satisfactions for Mobile Commerce Applications in Egypt

Evaluation of E-service Quality and its impact on Customer Satisfactions for Mobile Commerce Applications in Egypt

Evaluation of E-service Quality and its impact on Customer Satisfactions for Mobile Commerce Applications in Egypt

A hybrid model for aspect-based sentiment analysis on customer feedback: research on the mobile commerce sector in Vietnam

Feedback and comments on mobile commerce applications are extremely useful and valuable information sources that reflect the quality of products or services to determine whether data is positive or negative and help businesses monitor brand and product sentiment in customers’ feedback and understand customers’ needs. However, the increasing number of comments makes it increasingly difficult to understand customers using manual methods. To solve this problem, this study builds a hybrid research model based on aspect mining and comment classification for aspect-based sentiment analysis (ABSA) to deeply comprehend the customer and their experiences. Based on previous classification results, we first construct a dictionary of positive and negative words in the e-commerce field. Then, the POS tagging technique is applied for word classification in Vietnamese to extract aspects of model commerce related to positive or negative words. The model is implemented with machine and deep learning methods on a corpus comprising more than 1,000,000 customer opinions collected from Vietnam's four largest mobile commerce applications. Experimental results show that the Bi-LSTM method has the highest accuracy with 92.01%; it is selected for the proposed model to analyze the viewpoint of words on real data. The findings are that the proposed hybrid model can be applied to monitor online customer experience in real time, enable administrators to make timely and accurate decisions, and improve the quality of products and services to take a competitive advantage.

Design and implementation of mobile e-commerce application built on WAP mobile payment system

Design and implementation of mobile e-commerce application built on WAP mobile payment system

Customer Engagement, Customer Equity, and Their Influence on Consumer Repurchase Intention in E-Commerce Mobile Applications

The focus of this research is to determine the effect of customer engagement on repurchase intention using the customer equity dimension mediating the mobile e-commerce application at Shopee Indonesia company. Customer equity has three dimensions: value equity, brand equity, and relationship equity. The research approach is quantitative, with a purposive sampling technique, and the research sample is 160 respondents. This study identified modeling with Structural Equations Analysis (SEM) with SmartPLS 3.29. The findings of this study are that the variable customer engagement has a positive and significant effect on the dimensions of customer equity (value equity, brand equity, and relationship equity). Dimensions of customer equity (value equity, brand equity, and relationship equity) positively and significantly affect repurchase intention. Customer engagement has an indirect and significant positive effect on repurchase intentions mediated by customer equity dimensions (value equity, brand equity, and relationship equity).