The Impact Rules of Recommendation Sources for Adoption Intention of Micro-blog Based on DRSA with Flow Network Graph

Purpose This study aims to evaluate the role of personality in digital library systems (DLS) adoption intention among Generation Z (Gen-Z) students. The study uses the unified theory of acceptance and use of technology-2 and the five-factor model to investigate personality’s influence on Gen-Z’s DLS adoption intention. Design/methodology/approach The study is a descriptive causal investigation based on primary data collected through a self-administered survey using pre-validated tools. The study uses structural equation modeling to investigate personality dimensions’ direct and moderating effect on the dependent, independent variables and their relation. Findings The study results indicate that personality has no significant influence on Gen-Z’s DLS adoption, suggesting the ubiquity and inevitability of technology in current times. Also, only performance expectancy had a considerable impact on DLS adoption among Gen-Z going to college – a deviation from past studies where multiple independent variables have influenced DLS adoption when examined from different technology adoption model angles. Research limitations/implications The current research is done on Gen-Z, and thus the results are ideographic to the cohort. Practical implications The results of the study can be used to effectively design and communicate technology-enabled information solutions among the Cohort. Social implications The results of the study help better understand the factors affecting the technology adoption intentions of Gen-Z. Such understanding can help in better design and implementation of technology-enabled solutions for the cohort, maximizing such system adoption and its effective and efficient utilization. Originality/value The study explores the impact of personality on DLS adoption intentions, hitherto unexplored. The research also focuses on Gen-Z – a cohort born in a technology-enabled world whose attitude and preferences towards technology might differ. The study’s findings will help understand the influence of personality on DLS adoption among the Gen-Z and can be used to design, promote and evaluate such systems.

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Examining Consumers’ Adoption of Wearable Healthcare Technology: The Role of Health Attributes

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16132257 ◽

2019 ◽

Vol 16 (13) ◽

pp. 2257 ◽

Cited By ~ 12

Author(s):

Man Lai Cheung ◽

Ka Yin Chau ◽

Michael Huen Sum Lam ◽

Gary Tse ◽

Ka Yan Ho ◽

...

Keyword(s):

Health Beliefs ◽

Reference Group ◽

Influential Factors ◽

Perceived Usefulness ◽

Future Research ◽

Healthcare Technology ◽

Consumer Innovativeness ◽

Technology Products ◽

The Impact ◽

Adoption Intention

With the advancement of information technology, wearable healthcare technology has emerged as one of the promising technologies to improve the wellbeing of individuals. However, the adoption of wearable healthcare technology has lagged when compared to other well-established durable technology products, such as smartphones and tablets, because of the inadequate knowledge of the antecedents of adoption intention. The aim of this paper is to address an identified gap in the literature by empirically testing a theoretical model for examining the impact of consumers’ health beliefs, health information accuracy, and the privacy protection of wearable healthcare technology on perceived usefulness. Importantly, this study also examines the influences of perceived usefulness, consumer innovativeness, and reference group influence on the adoption intention of wearable healthcare technology. The model seeks to enhance understanding of the influential factors in adopting wearable healthcare technology. Finally, suggestions for future research for the empirical investigation of the model are provided.

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The impact of community containment implementation timing on the spread of COVID-19: A simulation study

F1000Research ◽

10.12688/f1000research.24156.1 ◽

2020 ◽

Vol 9 ◽

pp. 452 ◽

Cited By ~ 1

Author(s):

Attayeb Mohsen ◽

Ahmed Alarabi

Keyword(s):

Simulation Model ◽

Disease Outbreaks ◽

Simulation Method ◽

Final Outcome ◽

Disease Spread ◽

Network Graph ◽

Real World Data ◽

Infectious Disease Outbreaks ◽

Spread Parameters ◽

The Impact

Background: Community containment is one of the common methods used to mitigate infectious disease outbreaks. The effectiveness of such a method depends on how strictly it is applied and the timing of its implementation. An early start and being strict is very effective; however, at the same time, it impacts freedom and economic opportunity. Here we created a simulation model to understand the effect of the starting day of community containment on the ﬁnal outcome, that is, the number of those infected, hospitalized and those that died, as we followed the dynamics of COVID-19 pandemic. Methods: We used a stochastic recursive simulation method to apply disease outbreak dynamics measures of COVID-19 as an example to simulate disease spread. Parameters are allowed to be randomly assigned between higher and lower values obtained from published COVID-19 literature. Results: We simulated the dynamics of COVID-19 spread, calculated the number of active infections, hospitalizations and deaths as the outcome of our simulation and compared these results with real world data. We also represented the details of the spread in a network graph structure, and shared the code for the simulation model to be used for examining other variables. Conclusions: Early implementation of community containment has a big impact on the ﬁnal outcome of an outbreak.

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Examining the Attitude-Behavior Gap and Adoption Intention of SHS Technology

International Journal of Applied Business Research ◽

10.35313/ijabr.v3i1.119 ◽

2021 ◽

pp. 14-24

Author(s):

Zefanya Alanza Christabel Loveldy

Keyword(s):

Social Influence ◽

Green Technology ◽

Partial Least Square ◽

Least Square ◽

Radiation Level ◽

Factors Affecting ◽

Intention To Adopt ◽

Attitude Behavior ◽

The Impact ◽

Adoption Intention

Current fuel-based electricity used to fulfill household electricity needs becomes a reason that worsens the global warming. Even though Indonesia is benefited from abundant solar radiation level, the utilization of solar energy as one possible solution is still very poor. This unused eco-friendly energy needs to be investigated by examining consumers’ intention to adopt Solar House System (SHS) technology along with factors affecting it. This study uses Behavioral Reasoning Theory (BRT) consists of values, reasons for adoption, reasons against adoption, attitude, and social influence as variables to predict adoption intention. Further, Partial Least Square Modeling is used to test the hypotheses after collecting 428 data by distributing questionnaire in Bandung Area. The result reveals that social influence is found to play the most significant role in predicting SHS adoption intention, attitude, reasons for adoption, and values. Thus, this study extents our understanding of attitude-behavior gap in the context of green technology as well as the impact of social influence.

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Abstract P214: Social Network Analysis of a Community Aphasia Group Pre- And Post-Covid: Implications for Future Planning

Stroke ◽

10.1161/str.52.suppl_1.p214 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Tom Sather ◽

Anna Livera

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Time Frame ◽

Directed Network ◽

Negative Consequences ◽

Network Graph ◽

Future Planning ◽

Network Characteristics ◽

The Impact

Introduction: Among the many negative consequences of aphasia is an altered social network. Social network analysis supports an objective, quantitative evaluation of social networks among individuals with aphasia along with potential impacts of social programming and interventions on an individual’s social network. Social network analysis may also support better understanding of the impact of Covid on individuals with aphasia. Aims: This pilot evaluation utilized social network analysis via R to evaluate the social network characteristics of a community-based aphasia network across a 12-month pre-Covid period. Social network aphasia group data for a standard duration of time pre- and post-Covid were also compared to identify potential social implications of Covid in a population already at higher risk for reduced social interactions. This presentation will also provide fundamental concepts relevant to social network analysis for those interested in pursuing such analysis in further depth. Methods: Twelve months of pre-Covid aphasia group program attendance data were examined using the visNetwork R package. An additional six months of Covid-era time frame data were also analyzed.The primary relationship function of “ a attended b” (where a = individual participant and b = event/setting) was used in the analysis. Multiple social network characteristics were analyzed and displayed including node, edgeness, directionality, weight, and centrality indices across individuals with aphasia, care partners and community members and settings. Results and Conclusions: Network analysis reveals a directed network graph with primarily unidirectional relationships. There is an emergence of several aphasia group participant behavior types, both pre- and post-Covid, relevant for future planning including: communities of individuals who have similar behaviors in terms of type of event attendance; key individuals who are "heavy users" of various services in terms of frequency and breadth of event attendance; and peripheral users who use only one service. Post-Covid social network implications are discussed including supports to mitigate negative impacts of Covid on social network composition.

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THE IMPACT OF CONSPICUOUS CONSUMPTION AND PERCEIVED VALUE ON NEW PRODUCT ADOPTION INTENTION

Global Fashion Management Conference ◽

10.15444/gfmc2019.04.07.02 ◽

2019 ◽

Vol 2019 ◽

pp. 441-441

Author(s):

Meixiang Cui ◽

◽

Subin Im

Keyword(s):

Perceived Value ◽

Conspicuous Consumption ◽

New Product ◽

Product Adoption ◽

New Product Adoption ◽

The Impact ◽

Adoption Intention

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Co-creation in hotel service innovation using smart phone apps: an empirical study

International Journal of Contemporary Hospitality Management ◽

10.1108/ijchm-12-2015-0681 ◽

2017 ◽

Vol 29 (10) ◽

pp. 2647-2667 ◽

Cited By ~ 24

Author(s):

Bijoylaxmi Sarmah ◽

Shampy Kamboj ◽

Zillur Rahman

Keyword(s):

Smart Phone ◽

Service Innovation ◽

Content Type ◽

Technology Application ◽

Luxury Hotels ◽

Service Staff ◽

Hotel Service ◽

Luxury Hotel ◽

The Impact ◽

Adoption Intention

Purpose The purpose of this study is to extend and revise the basic technology-based service (TBS) adoption model in luxury hotels in India using smart phone apps, and to analyse the impact of the guests’ innovativeness, willingness to co-create, need for interaction and involvement on their adoption intention towards co-creatively developed new services. Design/methodology/approach Data were collected through online and field surveys from luxury hotel guests, resulting into 229 valid responses. A data analysis was done by applying the confirmatory factor analysis along with structure equation modelling. Findings The findings of this study indicate that both guests’ innovativeness and need for interaction with service staff significantly affect their involvement. A guest’s willingness to co-create acts as a partial mediator between his/her innovativeness and intention to adopt co-creatively developed new services. Research limitations/implications Use of smart phone apps by hotel guests to co-create new services and their intentions to adopt such services have been examined in the context of luxury hotels in India only and thereby limits generalization of results to other industry and country contexts. Practical implications The findings of this study would look to guide policy planners and hotel managers for implementing technology application in the co-creative hotel service innovation. Originality/value The need for interaction and customer involvement have been added as two supportive variables to the basic TBS model to analyse the adoption intention of luxury hotel guests. This is a new addition to existing literature, as majority of empirical studies in this field are from industries other than hospitality and with differing contexts.

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Informing learning design through analytics: Applying network graph analysis

Australasian Journal of Educational Technology ◽

10.14742/ajet.3767 ◽

2018 ◽

Vol 34 (2) ◽

Cited By ~ 16

Author(s):

Dirk Ifenthaler ◽

David Gibson ◽

Eva Dobozy

Keyword(s):

Learning Environments ◽

Learning Analytics ◽

Graph Analysis ◽

Learning Design ◽

Digital Learning ◽

Time Data ◽

Network Graph ◽

Dynamic Learning ◽

The Impact

Learning design has traditionally been thought of as an activity occurring prior to the presentation of a learning experience or a description of that activity. With the advent of near real-time data and new opportunities of representing the decisions and actions of learners in digital learning environments, learning designers can now apply dynamic learning analytics information on the fly in order to evaluate learner characteristics, examine learning designs, analyse the effectiveness of learning materials and tasks, adjust difficulty levels, and measure the impact of interventions and feedback. In a case study with 3550 users, the navigation sequence and network graph analysis demonstrate a potential application of learning analytics design. Implications based on the case study show that integration of analytics data into the design of learning environments is a promising approach.

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