Mobile Fashion Research Articles

Human Activity Recognition Using Smartphones With WiFi Signals

In this article, we present a work using a smartphone with an off-the-shelf WiFi router for human activity recognition with various scales. The router serves as a hotspot for transmitting WiFi packets. The smartphone is configured with customized firmware and developed software for capturing WiFi channel state information (CSI) data. We extract the features from the CSI data associated with specific human activities, and utilize the features to classify the activities using machine learning models. To evaluate the system performance, we test 20 types of human activities with different scales including seven small motions, four medium motions, and nine big motions. We recruit 60 participants and spend 140 hours for data collection at various experimental settings, and have 36 000 data points collected in total. Furthermore, for comparison, we adopt three distinct machine learning models, including convolutional neural networks (CNNs), decision tree, and long short-term memory. The results demonstrate that our system can predict these human activities with an overall accuracy of 97.25%. Specifically, our system achieves a mean accuracy of 97.57% for recognizing small-scale motions that are particularly useful for gesture recognition. We then consider the adaptability of the machine learning algorithms in classifying the motions, where CNN achieves the best predicting accuracy. As a result, our system enables human activity recognition in a more ubiquitous and mobile fashion that can potentially enhance a wide range of applications such as gesture control, sign language recognition, etc.

시장전문성이 패션 모바일 앱 특성, 만족, 모바일 쇼핑지속의도에 미치는 영향

Background/Objective: This study aims to examine the effect of market mavenship on fashion mobile app characteristics, satisfaction, and continued shopping intention.
 Methods: In this study, data on 234 individuals in their 20s and older were collected through a questionnaire-based survey. The data were analyzed through frequency, factor, reliability, cluster, t-test, ANOVA, Ducan test, and regression analyses using SPSS 27.0 statistical program.
 Results: First, two factors, including speed and ease of use, for fashion product mobile shopping app were extracted, and consumer satisfaction, including product, app, and overall satisfaction, was thoroughly examined. Second, groups with high market mavenship had higher perception of fashion mobile app characteristics and higher overall satisfaction, including product and app, and mobile shopping persistence than groups with low market mavenship. Third, this study examined how market mavenship influences the speed and ease of using apps and the relationship between market mavenship, app characteristics, satisfaction, and continued shopping intention. App satisfaction had a great influence on the order of market mavenship, speed, and ease of use, which, in turn, influenced mobile shopping persistence. Fourth, there was a difference between demographic variables and app usage in terms of job and app-down status. Additionally, when downloading and using a fashion app, market mavenship, speed, ease of use, satisfaction, product satisfaction, app satisfaction, and continued shopping intention were higher than for those who did not download the app.
 Conclusion/Implications: These results concluded that fashion mobile app characteristics and market mavenship are useful variables for understanding mobile consumer behavior.

Enhancing User Experience in Fashion m-Retail: Mapping Shopping User Journey Using Google Analytics, Eye Tracking Technology and Retrospective Think Aloud Interview

With increased mobile traffic to fashion retailers’ websites, conversion rates are lower than for desktop users. Mobile consumers more readily abandon retailers if not satisfied with their shopping experience. There is a dearth of literature involving Google Analytics to analyze digital consumer shopping behavior and customer journeys. Retailers need to innovate the ways they approach the vast amount of digital analytics data. This research highlights the need for continuous auditing of Google Analytics data to ensure retailers understand the behavior of their mobile consumers and respond to their needs accordingly. A multi-method research design incorporated mobile fashion consumer data from Google Analytics, innovative mobile eye tracking technology and retrospective think aloud. A comparison of consumer shopping journeys showed that a Digital User Journey Mapping Framework based on eye tracking data can be used to audit Google Analytics datasets and to understand what elements of the fashion retailer’s website consumers prefer to interact with. Retrospective think aloud interviews complementing eye tracking experiments define how digital user experience can be improved in fashion m-retail. The shopping journey map framework can be used for mobile fashion consumer behavior analysis, auditing Google Analytics datasets and enhancing digital user experience.

Fashion shopping on the go: A Dual-stage predictive-analytics SEM-ANN analysis on usage behaviour, experience response and cross-category usage

With the proliferation of mobile commerce, mobile shopping has become the buzzword in the electronic commerce industry. To examine the predictive factors that affect the usage behaviour, experience response, and cross-category usage in mobile fashion shopping, an integrated research framework, comprising of the Mobile Technology Acceptance Model and individual attributes in terms of lifestyle orientations was proposed. The quantitative data, derived from 500 qualified responses, collected through a survey questionnaire, was validated via a two-stage predictive-analytics SEM-ANN approach to identify the non-compensatory and non-linear relationship. All six of the ANN models showed consistent relationships and rankings with the SEM results. The findings imply that mobile commerce developers and designers should ensure that the functions provided can satisfy the evaluation criteria of users with different lifestyle orientations, whereby the advantages of the mobile commerce platforms should be highlighted in the marketing messages to drive first-time usage, as well as extended usage across different mobile commerce platforms (i.e., mobile sites and mobile applications) and product categories. From the theoretical perspective, the findings revealed the indirect influence of the individual attributes on the usage intention of innovative mobile technology. The research is also the first to adopt non-compensatory neural network analysis to compensate the linear SEM analysis in the study on mobile shopping of fashion products.

A simple cross-layer mechanism for congestion control and performance enhancement in a localized multiple wireless body area networks

Commercialization of the wireless body area network (WBAN) envisions future new normal for WBAN devices coexistence in a localized area. The coexistence may allow devices to freely change positions, associate, or dissociate with the neighbours as users interact. Devices’ interaction in a stationary or mobile fashion radiates heat and also competes for the limited network resources resulting to unreliable communication and other performance challenges. Besides alarming user safety, device mobility affects network performance through topology changes, which result to recursive link disconnections, energy waste, packet delay, degraded throughput, and congestion due to excessive control messaging during route repair. In this article, we propose WBAN performance optimization criteria focusing on improving energy efficiency, network throughput, and reducing the end to end delay in multiple existence schemes. Firstly, we propose an alternative routing algorithm, whose routing decision depends on a cost function considering the parameterized residue energy to node distance ratio, link energy reliability, and specific heat absorption in addition to node sequence number and hop count as fundamental route selection metrics. Secondly, we implement congestion control adaptation in the medium access control (IEEE 802.11MAC) mechanism, which improves throughput, reduces congestion, and delay. Due to link discontinuities during mobility, we demonstrate a comparative network performance to address the effect of WBAN speed at different hello intervals. The comparative analysis show, protocol implementation with a cross-layer approach outperforms the conventional protocol without MAC adaptations in terms of energy efficiency, network throughput, and a reduced end to end delay, by an average of 0.45%, 2.8%, and 13.7%, respectively.

Eye tracking technology to audit google analytics: Analysing digital consumer shopping journey in fashion m-retail

Rapid changes in digital consumer behaviour, influenced by exponential adoption of smartphones, require timely and sophisticated responses from retailers to these consumer needs. With a growing amount of big data available, fashion retailers need to innovate and develop more sophisticated analytics for new consumer behaviours such as m-commerce. This research has considered how Google Analytics data can be applied to develop customer journey maps to understand digital consumer behaviour. A multi-method research design was used, incorporating an innovative mobile eye tracking technology and mobile fashion consumer data from Google Analytics. Digital customers’ shopping journeys on the fashion retailer’s website were mapped using data sourced from eye tracking and Google Analytics, gathered in parallel. The comparison of these shopping journeys allowed a critical evaluation of the precision and usefulness of the Google Analytics database. Google Analytics tracked only half of the digital users’ activities, whereas eye tracking data documented digital consumers’ interaction with all elements of the fashion retailer’s website. The conclusion reached is that eye tracking can be used to audit the Google Analytics database for potential gaps in data and also to inform and improve marketing decision-making.

Perceived Usefulness and Risks and Behavioral Intentions of Mobile Fashion Apps -Focus Group Interviews with Chinese Students Studying in Korea-

Perceived Usefulness and Risks and Behavioral Intentions of Mobile Fashion Apps -Focus Group Interviews with Chinese Students Studying in Korea-

비콘을 활용한 모바일 패션 O2O 서비스의 행동유도성(어포던스) 형성 연구

본 연구에서는 현재 비콘 O2O 서비스에서 요구되고 있는 어포던스(행동유동성) 형성요인을 구체적으로 고찰하고, 이를 기반으로 향후 비콘 O2O 서비스의 극대화를 위한 소비자 활용지각과 행위유도에 대한 방향을 제안하고 하였으며, 이러한 결과는 비콘 O2O 사용자의 서비스 극대화를 위해 비콘 O2O 서비스의 콘텐츠의 기능적 요소, 행위자의 감각적 상황, 정보의 인지적 요소에 대한 활용지각(지각된 가치, 지각된 유용성, 지각된 상호작용성) 및 행위의도에 대한 방향을 제공하는 시사점을 제공하게 될 것이다. 이에 본 연구에서는 비콘활용 모바일 패션 O2O 정보 서비스를 경험한 사용자 400명을 표본으로 선정하고, SPSS 23.0, AMOS 23.0을 활용하여 신뢰성, 타당도검증, 측정모형분석 및 경로분석을 수행하여 연구문제를 검증하였다. 본 연구의 결과는 다음과 같다. 첫째, 패션 O2O 서비스의 행동유도성(어포던스) 형성요인과 활용지각 요인들 간의 경로 관계 분석결과, 행위자의 행동가능성, 심리가능성, 지각가능성은 지각된 가치 관계에서 모두 유의한 영향을 미쳤으며, 행위자의 행동가능성, 심리가능성, 지각가능성은 지각된 유용성에 모두 유의한 영향을 미쳤다. 둘째, 패션 O2O 서비스의 활용지각과 행위의도 요인들 간의 경로관계 분석결과, 지각된 가치와 지각된 유용성 관계, 지각된 가치와 지각된 상호작용성 관계, 지각된 유용성과 지각된 상호작용성 관계, 지각된 상호작용성과 행위의도 관계에서 모두 유의한 영향을 미쳤다. 이를 통해 패션기업의 비콘 O2O 서비스 전략을 어포던스(행동유도성) 특성에 따라 조정할 수 있는 여건을 마련하고 성과를 극대화 할 수 있을 것이다.

Impacts of self-monitoring tendency and mobile phone dependency on salence of mobile phone case product attributes

Prevalent usage of mobile devices among consumers has been well recognized and this is especially imperative among young adult consumers. The mobile phone became the gateway of their communication, media consumption, retail transaction, education, and (virtual) social life. However, there is little empirical research explaining the dynamics behind the psychological underpinning of young adult consumers, specifi­cally Generation Y, to understand their usages and dependency on mobile phones. This study, therefore, aims to unveil antecedents and consequences of Gen Y consumers’ mobile phone dependency from a media psychological perspective. We developed a conceptual model based on theory of self-monitoring (Snyder 1974, 1987), extended self-concept (Belk, 1988), and media dependency theory (Ball-Rokeach & Defluer, 1976). Four hundred ninety-eight students in the U.S. provided usable responses to our pencil-and-paper survey. Causal modeling analysis results demonstrated that both ability to modify one’s behavior and sensitivity to cues for social appropriate behavior dimensions of the self-monitoring tendency positively predicted one’s level of fashion involvement, which in turn positively predicted his/her mobile phone dependency. Individual’s mobile phone dependency, fashion involvement and self-monitoring’s ability dimension exhibited positive and direct impact on one’s perception of the salience of mobile phone case product attributes. Based on the findings, we provided pragmatic and theoretical implications for the industry and academia.

Factors affecting the adoption of fashion mobile shopping applications

ABSTRACTFashion is ever-changing; almost every age and gender of a person is interested to know and wear the latest trend. Initially, people were dependent on the brick and mortar stores, followed by the launch and success of e-commerce, which changed the game by making people sit at home and shop. The launch of Mobile Shopping Apps have not only simplified the shopping but have also enhanced the whole shopping experience. So far there have been researches done on m-commerce in general. In this study, we examine the factors influencing the adoption of Fashion mobile shopping apps (FMSA) using extended UTAUT model. A thorough survey was conducted with a sample of 209 participants. The questionnaire was designed using established scales. Statistical tools were used to analyze the data. Out of ten identified variables except Physical Appearance and Social Influence, all others i.e. Performance Expectancy, Personal Innovativeness, Effort Expectancy, Facilitating Conditions, Hedonic Motivation, Habit, Price Value, and Behavioural Intentions showed significant influence on use behavior.

Understanding Compulsive Buying Behavior of Mobile Shoppers for Fashion Products

This study investigated main and interaction effects of materialistic values, self-depreciation and use intensity of mobile fashion applications on...

Beyond Brick and Mortar: The Experiences of U.S. Female Mobile Fashion Truck Entrepreneurs

The purpose of this study was to gain an understanding of the mobile fashion truck phenomenon from a female entrepreneur's perspective. This study provides insight into the unique strategies of this business format, while highlighting the motivations and challenges. Data collection took place through in‐depth interviews with eight female fashion truck entrepreneurs. Five key themes were developed from the data. The themes revealed that female fashion truck entrepreneurs viewed their mobile businesses as a means to deliver unique products and experiences, as well as being a flexible business model. A conceptual model is proposed to further illustrate the key motivations and challenges of the entrepreneurs.

The Effect of Consumer Characteristics on Mobile Fashion Shopping -Focusing on Market Mavenship, Innovativeness, Purchase Experience-

The Effect of Consumer Characteristics on Mobile Fashion Shopping -Focusing on Market Mavenship, Innovativeness, Purchase Experience-

No exchange, same pain, no gain: Risk-reward of wearable healthcare disclosure of health personally identifiable information for enhanced pain treatment.

Wearable technologies have created fascinating opportunities for patients to treat chronic pain in a discreet, mobile fashion. However, many of these health wearables require patients to disclose sensitive information, including health information (e.g., heart rate, glucose levels) and personal information (location, email, name, etc.). Individuals using wearables for treatment of chronic pain may sacrifice social health elements, including their privacy, in exchange for better physical and mental health. Utilizing communication privacy management, a popular disclosure theory, this article explores the policy and ethical ramifications of patients disclosing sensitive health information in exchange for better health treatment and relief of chronic pain. The article identifies scenarios where a user must disclose information, and what factors motivate or dissuade disclosure, and ultimately the use of a health wearable. Practical implications of this conceptual article include an improved understanding of how and why consumers may disclose personal data to health wearables, and potential impacts for public policy and ethics regarding how wearables and their manufacturers entice disclosure of private health information.

비콘기반 모바일 패션 O2O 서비스 활성화를 위한 정보품질특성 연구

비콘기반 모바일 패션 O2O 서비스 활성화를 위한 정보품질특성 연구

The Study of Data Quality Characteristics for the Development of Mobile Fashion O2O Service using Beacon

The Study of Data Quality Characteristics for the Development of Mobile Fashion O2O Service using Beacon

The Effects of Using O2O Fashion Mobile Commerce on Consumers` Attitudes and Intentions Focused on the characteristics - of consumers and O2O mobile commerce-

The Effects of Using O2O Fashion Mobile Commerce on Consumers` Attitudes and Intentions Focused on the characteristics - of consumers and O2O mobile commerce-

모바일 패션 쇼핑 특성이 관계 품질에 미치는 영향

This research analyzed the influence of mobile fashion shopping characteristics on customer loyalty through relationship quality. The data were collected subjects in their 20's-30's who had purchased fashion products using a mobile shopping channel. through an online survey using the self administered questionnaire. Exploratory and confirmative factor analysis were conducted to identify the dimensions of mobile fashion shopping characteristics and customer relationship variables. Mobile fashion shopping characteristics comprised four dimensions including tangibility, ubiquity, security and personalization. Customer relationship variables were identified as four dimensions such as satisfaction, trust commitment and loyalty. A structural equation modeling analysis was employed to examine the relationship between mobile fashion shopping characteristics, relationship quality and customer loyalty. Tangibility, ubiquity and security had a significantly positive impact on satisfaction and trust, but personalization had an influence on only satisfaction. Satisfaction had a significantly positive impact on commitment and loyalty. Trust had an influence on only commitment. In conclusion, relationship quality was found to be the appropriate model to explain the influence of mobile commerce characteristics on consumer' loyalty in mobile fashion shopping.

The Influences of Satisfaction with Technique and Channel Type of Mobile Fashion Advertisement on Purchase Intention by Consumer Demographic Characteristic

The Influences of Satisfaction with Technique and Channel Type of Mobile Fashion Advertisement on Purchase Intention by Consumer Demographic Characteristic

구매빈도에 따른 모바일 패션제품 구매에 대한 확장된 기술수용모델의 차이

본 연구는 모바일 환경에서 패션제품을 구매할 때 소비자의 구매의도에 영향을 주는 요인들로 구성한 확장된 기술수용모델(TAM: technology acceptance model)을 검증하고자 하였다. 모바일을 통해 최근 1년 동안패션제품을 구매한 빈도에 따라 구매빈도 고집단과 저집단으로 분류하여 확장된 TAM의 차이를 분석하였다. 스마트 폰을 사용하여 패션 브랜드나 쇼핑몰 앱, 유통업체 앱을 통해 패션제품을 구매한 경험이 있는 20∼30 대 성인을 대상으로 설문지 조사를 시행하였으며, 430부의 유효한 데이터를 이용하여 t-test, Amos 19.0을 이용한 다중집단 요인분석을 하였다. 분석 결과는 다음과 같다. 첫째, 확장된 TAM을 구성하는 변수들인 모바일 상거래 특성 요인들(보안성, 유희성, 개인화), 지각된 사용용이성(PEOU), 지각된 유용성(PU)에 있어서 구매빈도 고집단과 저집단 간에 유의한 차이가 있었다. 둘째, 확장된 TAM은 구매빈도 고집단/저집단의 구매의도를 설명하는데 적합한 모델로 확인되었다. 구매빈도 고집단에서는 개인화가 지각된 유용성에 주는 영향을제외한 모든 경로에서 유의한 영향을 나타냈으며, 저집단에서는 지각된 사용용이성이 구매의도에 주는 영향을 제외한 모든 경로에서 유의한 영향관계가 있는 것으로 나타났다. 셋째, 구매빈도 고집단과 저집단 간에확장된 TAM에 있어서 차이가 있는지를 분석한 결과 8개의 경로 중 4개의 경로에서 유의한 차이가 있음이입증되었다. 지각된 사용용이성이 지각된 유용성과 구매의도에 미치는 영향은 구매빈도 고집단이 저집단보다 높은 것으로 나타났고, 개인화가 지각된 유용성에 미치는 영향과 지각된 유용성이 구매의도에 미치는 영향은 구매빈도 저집단이 고집단보다 높은 것으로 확인되었다. 이와 같은 분석결과를 통해 소비자의 구매경험정도에 따라 구매행동에 차이가 있음을 확인할 수 있으므로, 모바일 마케터들은 소비자의 구매경험 수준에따른 차별화된 고객 관리를 할 필요가 있음을 시사한다.