Generating travel-related contents through mobile social tourism: Does privacy paradox persist?

Expanding the UTAUT2 framework to determine the drivers of mobile shopping behaviour among older adults

In the current severe aging of the population, the problem of "digital divide" of the elderly has become increasingly prominent, and the elderly market represents a vast demographic that is increasingly becoming an important customer segment for mobile shopping in the future. However, there is currently insufficient attention given to the research on mobile shopping behavior among older adults. This study tries to answer what are the driving factors of mobile phone shopping behavior among the elderly? The purpose of this study is to analyze the factors that drive the elderly's mobile phone shopping behavior, and to establish a mobile phone shopping acceptance model for the elderly to predict the factors of the elderly's behavioral intention of using smart phones. Based on the second edition of Unified Theory of Acceptance and Use of Technology theory (UTAUT 2), this study proposed a mobile phone shopping acceptance model for the elderly. The study collected valid data from 389 Chinese elderly people through questionnaires and analyzed them using structural equation models. The results showed that utilitarian, anxiety, trust, performance expectancy, effort expectancy, social influence, facilitating conditions and habit directly impact the older adults' intention to engage in mobile shopping. Additionally, facilitating conditions, habit and the older adults' intention to engage in mobile shopping act as driving factors for actual use behavior. This study further expands the UTAUT theoretical model, provides a theoretical basis for the research of mobile shopping behavior of the elderly, and enricues the application groups and fields of the UTAUT theoretical model. The results of this study provide inspiration for the development, design and marketing of age-appropriate mobile shopping products, and contribute to the realization and further adoption of age-appropriate mobile shopping, and also contribute to promoting the active aging of the elderly.

Digital Students' Satisfaction With and Intention to Use Online Teaching Modes, Role of Big Five Personality Traits

During the COVID-19 pandemic, online teaching modes were found vital to continue students' learning process, but sustainable implementation of online teaching models is an area of concern for policymakers. Psychiatrists are also eager to know students' behavior toward learning and modes of teaching during COVID-19. We have drawn a model based on the big five personality traits to study students' satisfaction with online teaching modes and their adoption intentions toward online teaching modes. We have collected data from 718 bachelor's and master's level students from four different universities. We have applied the SEM-ANN dual-stage approach to test personality traits' influence and ranked them based on their normalized importance. The results revealed that agreeableness, conscientiousness, neuroticism, and openness positively influence students' satisfaction with online teaching models, but that extraversion negatively influences their satisfaction. Agreeableness, extraversion, and neuroticism positively impact, but openness negatively influences. Conscientiousness does not affect adoption intention. Furthermore, agreeableness is the most significant, and conscientiousness is the least important factor for students to adopt online teaching modes. The findings of the study have useful perceptiveness for educational policymakers, academics, and psychiatrists.

M-commerce adoption among youths in Malaysia: Dataset article

The covid-19 pandemic which took the world by storm changed our behaviour towards m-commerce with enforced movement restrictions across the world. This dataset documents the factors of consideration among Malaysian youths (age 15 to 24 years old) in their intention to adopt m-commerce. Collected from October to November 2020, a total of 396 useable responses were finalized. The questionnaire consists of individual demographic variables and factors which influence the intention of youths to adopt m-commerce in Malaysia. The dataset of demographics and m-commerce related variables can be used to further explore the correlations and description of variables. The dataset is valuable for m-commerce service providers and future works of literature in understanding the behaviour of youths and hence increase the adoption rate of m-commerce among youths.

Using the Extended Acceptance Model to Understand Continuance Intention of Dockless Bike-Sharing

Despite the fact that dockless bike-sharing (DBS) usage first experienced explosive growth, its continuous usage rate remains low. The ultimate success of a DBS service is more dependent on its continued usage rather than its initial adoption. Following the extended technology acceptance model (TAM), this study aims to explore factors that influence the continuance intention of DBS users. The framework of research was validated using a sample of 369 DBS users in China. The results show that perceived usefulness and perceived ease of use positively influence a user’s intention to continue using DBS. Both descriptive social norms and injunctive social norms are positively related to the continuance intention of DBS users. Moreover, environmental concern significantly affects the continuance intention of a user indirectly via perceived usefulness and perceived ease of use. Furthermore, the extended TAM has stronger prediction ability than the original TAM in the context of DBS services.

Determining the factors of m-wallets adoption. A twofold SEM-ANN approach

M-wallets are comparatively more advantageous and convenient than conventional payment systems as m-wallets allow users to avoid cash. The present research uses the diffusion of innovation theory as the base theory to propose a research model by incorporating constructs like convenience, perceived security, personal innovativeness, and perceived trust to investigate the determinants of consumers' intention-to-use m-wallets. A twofold approach comprising of Structural Equation Modelling-Artificial Neural Network (SEM-ANN) was used: First, partial least squares structural equation modelling (PLS-SEM) was employed to determine the significant determinants of intention-to-use. Second, the ANN approach was applied as robustness to corroborate the outcomes of PLS-SEM and to estimate the relative importance of the SEM-based significant determinants. Our findings confirmed that compatibility, ease of use, observability, convenience, relative advantage, personal innovativeness, perceived trust, and perceived security are the key elements that influence the intention-to-use m-wallets. Moreover, we ascertained that perceived security is the most influential predictor of intention-to-use. The outcomes of ANN have complemented the findings of PLS-SEM, but some differences were also exhibited in the order of influential factors. The study brings to fore significant insights and a set of suggestions for the companies carrying out the development, execution, and marketing of M-wallet services.

Factors influencing the young physicians’ intention to use Internet of Things (IoT) services in healthcare

The Internet of Things (IoT) enabled technologies to have proliferated due to their abilities to capture and exchange quality information. This empirical study aims to investigate the factors influencing the intention to use IoT services in healthcare by young physicians. An integrated model based on the theory of planned behaviour (TPB) and diffusion of innovations (DOI) theories are drawn upon and analyzed through a Structural Equation Modelling (SEM) with importance-performance map analysis (IPMA). Data were collected through a structured survey questionnaire. The results indicated that behavioural intention to use IoT in healthcare services vastly affected by the attitude and value co-creation. Attitude was found to be a principal determinant followed by the relative advantage towards behavioural intention to use IoT services. The novelty of this empirical study is that the proposed integrated model provides a meaningful application of the young physicians’ intention to use IoT in healthcare in developing countries.

A Dual-Stage SEM-ANN Analysis to Explore Consumer Adoption of Smart Wearable Healthcare Devices

Advances in information technology have included the development of smart wearable healthcare (SWH) devices that have potential benefits for consumer health. The adoption of SWH devices is limited, however, compared with other established digital technologies. This study examines the determinants of consumers’ adoption of SWH devices. A conceptual model is proposed that incorporates health (health beliefs and health information accuracy), and technology (compatibility and functional congruence) attributes into the technology acceptance model framework. The proposed model was tested in two steps. Structural equation modelling (SEM) was performed with 473 usable responses to test the hypothesized relationships. The artificial neural network (ANN) approach was then applied to validate the outcomes of Step 1. The SEM analysis indicates that all the hypothesized relationships are supported. The ANN analysis further validates the outcomes of the SEM. The findings of this study and the dual-stage SEM-ANN methodology will have a strong impact on the existing literature regarding SWH devices.

A Novel Structure of Blockchain Applied in Vaccine Quality Control: Double-Chain Structured Blockchain System for Vaccine Anticounterfeiting and Traceability

Background

Vaccine, as an irreplaceable means in herd immunization, is widely applied in prevention for communicable diseases. However, adverse impacts were frequently incurred by fake or expired vaccines in China. Given the necessity of vaccine anticounterfeiting, blockchain-based transaction platform could be practiced as a solution in addressing the issue; however, most of the available experiments focused on single-chain structured design with inventible limitations. Accordingly, exploration for the effectiveness and feasibility of mixed-chains structured platform for vaccine anticounterfeiting and tracing is essentially required.

Methods

Both public chain and private chain were inserted in anticounterfeiting and tracing platform designing process, which were subsequently simulated in Ethereum environment.

Results

By recording different information in public chain and private chain, partial information privacy protection requirements are realized. The transfer identification module realized the function of vaccine quality supervision and solves the problem of EPC label replication. Discussion. Compared with the traditional single-structured design, completeness information could be visited by all stakeholders in double-chain structure, including vaccine suppliers, National Medical Products Administration (NMPA), vaccine purchasers, and the vaccinated.

Conclusion

Double-chain structured system for vaccine anticounterfeiting and tracing is more effective.

Sustainable Destination Marketing Ecosystem through Smartphone-Based Social Media: The Consumers’ Acceptance Perspective

The growth of technological revolutions and the subsequent acceptance of smart devices has increased the influence of sustainable marketing activities in the tourism industry. Due to the explosion of mobile technologies (e.g., smartphones, tablets) and social media adoption, consumers have been able to use these technologies at any time for destination marketing. However, understanding consumers’ sustainable marketing experiences from a destination perspective is a complex issue. At the moment, very few studies have focused on the effectiveness of smartphone-based social media in destination marketing. Hence, the main purpose of this study is to explore how consumers interpret and utilize smartphone-based social media for sustainable destination marketing. This study proposes an integrated framework that consists of the mobile technology acceptance model (MTAM) and the social media-based interaction, trendiness, and electronic-word-of-mouth (e-WoM). A questionnaire survey was used to collect data (n = 365), and valid data were analyzed by the structural equation modeling (SEM) technique. The findings revealed that interaction, trendiness, and e-WoM indirectly affected satisfaction through mobile usefulness and mobile ease of use. At the same time, mobile usefulness and mobile ease of use directly affected satisfaction, which then significantly influenced the intention to utilize those factors towards sustainable destination marketing. This study highlights the technological affordances and the satisfaction of smartphone-based social media in sustainable marketing. Furthermore, the results can be used in the resource allocation process to ensure the success of the vision and mission of sustainable destination marketing efforts.

QR code and mobile payment: The disruptive forces in retail

The emergence of mobile payment (m-payment) resulted in the disruption of many sectors in the business sphere, particularly the retail industry. However, the acceptance of m-payment still has substantial room for improvement. Therefore, this study purports to ascertain the critical antecedents that impact the m-payment adoption intention, in particular the type of m-payment that utilizes the Quick Response (QR) code technology, through an extended Mobile Technology Acceptance Model. On top of offering several theoretical implications, numerous practical implications are also provided for stakeholders in the retail sector.

Innovation resistance theory perspective on the use of food delivery applications

Purpose

The current study tries to better understand the resistance toward food delivery applications (FDAs). This study has adapted the existing criteria to measure different consumer barriers toward FDAs. It also examined the relationships between various consumer barriers, intention to use FDAs and word-of-mouth (WOM).

Design/methodology/approach

This study utilized the innovation resistance theory (IRT) and a mixed-method approach comprised of qualitative essays submitted by 125 respondents and primary surveys (N = 366) of FDA users.

Findings

Tradition barrier (trust) shared a negative association with use intention, while image barrier (poor customer service) shared a negative association with WOM. The intention to use was positively associated with WOM. Additionally, the study results reveal that image barrier (poor customer experience) and value barrier (poor quality control) were, in fact, positively related to WOM. This study also discusses the managerial and theoretical implications of these findings and the scope for further research on FDAs.

Originality/value

FDAs have revolutionized the food delivery industry and made it more comfortable and convenient for the consumers. However, FDA service providers are facing challenges from both customers and restaurants. Although scholars investigated customer behavior toward FDAs, no prior study has focused on consumer barriers toward FDA usage.

The Role of Travel Motivations and Social Media Use in Consumer Interactive Behaviour: A Uses and Gratifications Perspective

This paper explores the influence of travel motivations and the gratification provided by social media in consumer stickiness to social media, intention to create user-generated content, and electronic word of mouth (eWOM) review adoption. The study follows a mixed-methods approach. First, a concept mapping study was undertaken to identify the main travel motivations and the gratifications provided by social media when consumers search for information on tourism destinations. A second study using structural equation modelling and SmartPLS 3.2.7 with a sample of 401 heavy users of social media showed the relationships between individual travel motivations and gratifications provided by social media and consumer stickiness, intention to share user-generated content (UGC), and eWOM review adoption.

Systematic Review of Smart Tourism Research

In recent decades, smart tourism has been attracting attention from practitioners and scholars. The current study used multiple analysis methods to conduct a systematic review of 124 related articles on smart tourism. Qualitative analysis was conducted to identify 10 categories of smart tourism articles. Results showed that the largest proportion focus on the influence of technology on tourists’ perceptions, behaviors, and experiences. Co-occurrence analysis was performed to investigate the development trend of keywords used by academics in the last five years, while co-authorship (country) analysis was conducted to examine the collaborative relationship between different countries. The research regions, industries, methods, and theories applied in these articles were also analyzed. Theoretical and practical/managerial implications, as well as future research directions, were provided.

Understanding Travelers’ Behavior for Sustainable Smart Tourism: A Technology Readiness Perspective

Smart tourism has contributed to making people’s travels easier and more enjoyable, but sometimes has a negative impact on their travel experience. The challenges travelers face while using smart devices have not been researched in detail and are relatively unknown. While most studies have considered the usefulness of smart devices in tourism, negative perceptions of smart tourism have rarely been discussed. Thus, this study investigates travelers’ risk perceptions of smart tourism from a technology readiness perspective. It examines the impact of optimism, innovativeness, insecurity, and discomfort on travelers’ usage intentions of smart devices through their perceived risks and benefits. To test the proposed model and corresponding hypotheses, a partial least squares analysis was performed on data collected from 250 survey respondents. The results showed that the perceived benefits of smart devices had a significant effect on usage intentions of smart devices while traveling. It was also confirmed that the influence of perceived risks depends on the characteristics of travelers. This study is significant as it is the first empirical study applying the TRI (Technology Readiness Index) model that examines the negative effects of smart devices on tourists during travel. The results of this study provide meaningful insights into smart tourism to companies and governments.