Modeling End-users’ Acceptance of a Knowledge Authoring Tool

2006 ◽  
Vol 45 (05) ◽  
pp. 528-535 ◽  
Author(s):  
G. Del Fiol ◽  
R. A. Rocha ◽  
N. C. Hulse
Keyword(s):  
Technology Acceptance ◽  
Knowledge Base ◽  
Behavioral Intentions ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Online Survey ◽  
Knowledge Bases ◽  
End Users ◽  
Authoring Tool ◽  
Equation Modeling

Summary Objectives: Knowledge bases comprise a vital component in the classic medical expert system model, yet the knowledge acquisition process by which they are created has been characterized as highly iterative and labor-intensive. The difficulty of this process underscores the importance of knowledge authoring tools that satisfy the demands of end-users. The authors hypothesize that the acceptability of a knowledge authoring tool for the creation of medical knowledge base content can be predicted by an accepted model in the information technology (IT) field, specifically the Technology Acceptance Model (TAM). Methods: An online survey was conducted amongst knowledge base authors who had previously established experience with the authoring tool software. The Likert-based questions in the survey were patterned directly after accepted TAM constructs with minor modifications to particularize them to the software being used. The results were analyzed using structural equation modeling. Results: The TAM performed well in predicting end-users’ behavioral intentions to use the knowledge authoring tool. Five out of seven goodness-of-fit statistics indicate that the model represents the behavioral intentions of the authors well. All but one of the hypothesized relationships specified by the TAM were significant with p values less than 0.05. Conclusions: The TAM provides an adequate means by which development teams can anticipate and better understand what aspects of a knowledge authoring tool are most important to their target audience. Further research involving other behavioral models and an expanded user base will be necessary to better understand the scope of issues that factor into acceptability.

Factors Influencing the Use of Smartphones for Programing: A Structural Equation Modeling Approach

2020 ◽  
Vol 17 (05) ◽  
pp. 2050032
Author(s):  
Asim Suleman A. Alwabel ◽  
Said S. Al-Gahtani ◽  
Ahmed Talab
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
End Users ◽  
Ease Of Use ◽  
Decision Makers ◽  
Equation Modeling ◽  
External Control ◽  
Factors Affecting ◽  
Hand Tool ◽  
Acceptance Model

The ubiquitous application of smartphones and their advanced development have created an opportunity for using them as coding platforms. In this study, we compared between the use of personal computers (PCs) and smartphones to investigate the factors affecting the use of smartphones in programing. The behavioral intentions of smartphone end-users are inspired by the ease of use perception, enjoyment perception, programing anxiety, perception of external control, and smartphone design aesthetics. Although the [Formula: see text] value of the smartphone model was lower than that of the PC model, the end-users’ adoption decisions could have shifted toward accepting the use of smartphones for programing had their decisions been free of enforcement. In this study, design aesthetics and programing anxiety were introduced to Technology Acceptance Model 3 in an Arabic environment. Additionally, the model was creatively applied for guiding practitioners in two situations. First, when organizations are in the quest for emerging technology to replace the legacy technology, they might apply the presented side-by-side comparison of the use of PCs with that of smartphones in programing. Second, at a time when decision makers analyze what might hinder the adoption of a recently introduced technology, the model can be a successful hand tool guiding the top management in identifying technology acceptance interventions, an approach this research revealed. Furthermore, in this paper, the research implications and recommendations are presented for technology practitioners and designers.

Adoption of mobile banking services

2019 ◽  
Vol 37 (5) ◽  
pp. 1165-1189 ◽  
Author(s):  
Apostolos Giovanis ◽  
Pinelopi Athanasopoulou ◽  
Costas Assimakopoulos ◽  
Christos Sarmaniotis
Keyword(s):  
Theory Of Planned Behavior ◽  
Technology Acceptance ◽  
Planned Behavior ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Explanatory Power ◽  
Equation Modeling ◽  
Mobile Banking ◽  
Content Type

PurposeThe purpose of this paper is to investigate which of four well-established theoretical models (i.e. technology acceptance model, theory of planned behavior, unified theory of acceptance and use of technology, decomposed theory of planned behavior (DTPB)) best explains potential users’ behavioral intentions to adopt mobile banking (MB) services.Design/methodology/approachDrawing on data from 931 potential users in Greece, the structural equation modeling method was used to examine and compare the four models in goodness-of-fit, explanatory power and statistical significance of path coefficients.FindingsResults indicate that the best model is an extension of the DTPB with perceived risk (PR). Customers’ attitude, determined by three rationally-evaluated MB attributes (usefulness, easiness and compatibility), is the main driver of consumers’ intentions to adopt MB services. Additionally, consumers’ perceptions of availability of knowledge, resources and opportunities necessary for using the service, and the pressure of interpersonal and external social contexts toward the use of MB are the other two, less important, adoption drivers. Finally, PR negatively affects attitude formation and inhibits willingness to use MB services.Practical implicationsFindings can help marketers of financial institutions to select the more parsimonious model to develop appropriate marketing strategies to increase adoption rates of MB services.Originality/valueThis is the first study that compares the performance of four well-known innovation adoption models to explain consumers’ behavior in the MB context.

scholarly journals Extending of Technology Acceptance Model in Using Online Health Applications in The Covid-19 Pandemic Era

2021 ◽  
Vol 2 (9) ◽  
pp. 752-763
Author(s):  
Didik Setyawan ◽  
Muhammad Zul Ashari ◽  
Ariefah Yulandari
Keyword(s):  
Health Services ◽  
Social Influence ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Behavioral Intentions ◽  
Structural Equation ◽  
Equation Modeling ◽  
The People ◽  
Acceptance Model ◽  
Health Applications

The Covid-19 pandemic has changed behavior of the people in getting health services that switch to online ones. The study examines the extending of the Technology Acceptance Model (TAM) in using health applications. TAM is no longer relevant to be applied on the specific application studies. The expansion that carried out adds to the variables of social influence, feelings of anxiety, and availability of services in developing attitudes to influence behavioral intentions. Data collected using online questionnaires for users of the Halodoc application as many as 200 respondents. The results of hypothesis testing using the Structural Equation Modeling analysis with the AMOS method show that attitudes are the determinants in forming behavioral intentions which are influenced by perception of usefulness, ease of perception, social influence, and service availability, but not from the feelings of anxiety. These results indicate that individuals perceive Halodoc as providing benefits, easy to use, influencing environment, and well-available services. Therefore it can ignore the anxiety in using the Halodoc application during the Covid 19 pandemic to get health services.

scholarly journals Intentions of Environmentally Friendly Behavior Among Sports Club Members: An Empirical Test of the Theory of Planned Behavior Across Genders and Sports

2021 ◽  
Vol 3 ◽  
Author(s):  
Michael Braksiek ◽  
Tim F. Thormann ◽  
Pamela Wicker
Keyword(s):  
Theory Of Planned Behavior ◽  
Planned Behavior ◽  
Behavioral Intentions ◽  
Structural Equation ◽  
Online Survey ◽  
Empirical Test ◽  
Environmentally Friendly ◽  
Equation Modeling ◽  
Sports Club ◽  
Community Sports

Environmentally friendly behavior has become increasingly important in recent years to reduce the speed of climate change and its negative impacts. Individual behavior, including environmentally friendly behavior, is largely formed by behavioral intentions. This study draws on the theory of planned behavior to examine the effects of attitudes toward the behavior, subjective norms, and perceived behavioral control on intentions of environmentally friendly behavior. It also investigates differences between genders and among sports. The study is based on data from a nationwide online survey of community sports club members in Germany in five team/racket sports (n = 3,036). Existing measures to operationalize the constructs were adapted to the present research context. The data were analyzed using structural equation modeling. The results show that the theoretical assumptions of the theory of planned behavior were largely supported by the data, implying that the antecedents of environmentally friendly behavioral intentions can be applied to club members. Furthermore, gender- and sports-specific differences in the antecedents–intention relationship were detected. This study is among the first to examine environmentally friendly behavioral intentions in community sports clubs. It adds to an increasing body of research investigating environmental sustainability in sports.

Consumer acceptance of smart speakers: a mixed methods approach

2018 ◽  
Vol 12 (4) ◽  
pp. 418-431 ◽  
Author(s):  
Pascal Kowalczuk
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
Online Survey ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Smart Devices ◽  
Intention To Use ◽  
Content Type ◽  
Acceptance Model

PurposeVoice-activated smart speakers such as Amazon Echo and Google Home were recently developed and are gaining popularity. Understanding and theorizing the underlying mechanisms that encourage or impede consumers to use smart speakers is fundamental for enhancing acceptance and future development of these new devices. Therefore, building on technology acceptance research, this study aims to develop and test an acceptance model for investigating consumers’ intention to use smart speakers.Design/methodology/approachFirst, antecedents that may significantly affect the usage intention of smart speakers were identified through an explorative approach by a netnographic analysis of customer reviews (N= 2,186) and Twitter data (N= 899). Afterward, these results and contemporary literature were used to develop and validate an acceptance model for smart speakers. Structural equation modeling (SEM) was used to test the proposed hypotheses on data collected from 293 participants of an online survey.FindingsBesides perceived ease of use and perceived usefulness, the quality and diversity of a system, its enjoyment, consumer’s technology optimism and risk (surveillance anxiety and security/privacy risk) strongly affect the acceptance of smart speakers. Among these variables, enjoyment had the strongest effect on behavioral intention to use smart speakers.Originality/valueThis is the first study that incorporates netnography and SEM for investigating technology acceptance and applies it to the field of interactive smart devices.

Understanding Intention and Behavior Toward Online Purchase of Agriculture and Fisheries Products Using Extended Technology Acceptance Model

2021 ◽  
Vol 17 (4) ◽  
pp. 118-137
Author(s):  
Junrie B. Matias
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Online Survey ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Usage Behavior ◽  
Acceptance Model ◽  
And Behavior

This study investigates the factors affecting the usage behavior and intention towards online purchasing platforms in purchasing agriculture and fisheries products online based on the technology acceptance model. External factors adapted from current literature were integrated with the model to understand the consumer intention and behavior towards online purchasing. An online survey with 318 respondents was used to test the hypotheses of the theoretical model using partial least squares component-based structural equation modeling. Results show that trust is a significant predictor of usage behavior. Furthermore, the factors visibility, perceived risk, perceived value, and enjoyment have directly or indirectly influenced intention and usage behavior through trust, perceived ease of use, and perceived usefulness. The researcher considers this work to have contributed essential inputs to other researchers interested in studying the adoption of online purchasing in fisheries and agriculture products.

An acceptance model for smart watches

2015 ◽  
Vol 25 (4) ◽  
pp. 527-541 ◽  
Author(s):  
Ki Joon Kim ◽  
Dong-Hee Shin
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
Online Survey ◽  
Perceived Usefulness ◽  
Relative Advantage ◽  
Equation Modeling ◽  
Content Type ◽  
Psychological Determinants ◽  
Smart Watch ◽  
Acceptance Model

Purpose – The purpose of this paper is to identify the key psychological determinants of smart watch adoption (i.e. affective quality (AQ), relative advantage (RA), mobility (MB), availability (AV), subcultural appeal) and develops an extended technology acceptance model (TAM) that integrates the findings into the original TAM constructs. Design/methodology/approach – An online survey assessed the proposed psychological determinants of smart watch adoption. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were conducted on collected data (n=363) using the AMOS 22 statistical software. The reliability and validity of the measurement assessing the proposed factor structure were examined via CFA, while the strength and direction of the hypothesized causal paths among the constructs were analyzed via SEM. Findings – The AQ and RA of smart watches were found to be associated with perceived usefulness, while the sense of MB and AV induced by smart watches led to a greater perceived ease of the technology’s use. The results also indicated that the devices’ subcultural appeal and cost were notable antecedents of user attitude (AT) and intention to use, respectively. Originality/value – Though smart watches are becoming increasingly popular, empirical studies on user perceptions of and ATs toward – them remain preliminary. This paper is one of the first scholarly attempts at a systematic prediction of smart watch usage, with implications for the adoption of future wearable technology.

scholarly journals The Effect of League Brand on the Relationship Between the Team Brand and Behavioral Intentions: A Formative Approach Examining Brand Associations and Brand Relationships

2017 ◽  
Vol 31 (4) ◽  
pp. 317-332 ◽  
Author(s):  
Thilo Kunkel ◽  
Daniel C. Funk ◽  
Daniel Lock
Keyword(s):  
Behavioral Intentions ◽  
Structural Equation ◽  
Online Survey ◽  
Equation Modeling ◽  
Brand Associations ◽  
Brand Association ◽  
Professional Soccer ◽  
Team Brand ◽  
The Relationship

Understanding the role of the league brand on consumers’ support for individual teams is important for the successful management and marketing of both leagues and teams. In the current research, brand architecture and brand association literature are integrated to examine the role of the league brand on the relationship between the team brand and team-related behavior. Data from an online survey of professional soccer league consumers (N = 414) were analyzed using structural equation modeling with bootstrapping procedures. The relationship between the team brand and team-related behavior was partially mediated by the league brand. Findings of this research contribute new knowledge by empirically demonstrating that characteristics of the league brand have an influence on team-related behavioral intentions. Furthermore, we contribute a different analytical approach for brand association research using formative indicators to measure team and league brand associations. In the managerial implications, we outline how league managers can support individual teams and how team managers can leverage off the league brand to attract consumers.

Understanding the emergence of wearable devices as next-generation tools for health communication

2016 ◽  
Vol 29 (4) ◽  
pp. 717-732 ◽  
Author(s):  
Eunil Park ◽  
Ki Joon Kim ◽  
Sang Jib Kwon
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
Online Survey ◽  
Structural Model ◽  
Reliability And Validity ◽  
Wearable Devices ◽  
Motivational Factors ◽  
Equation Modeling ◽  
Adoption Process ◽  
Content Type

Purpose The purpose of this paper is to identify motivational factors for using wearable healthcare devices and examine the process by which these factors are integrated with the technology acceptance model (TAM) and contribute to the adoption of the devices. Design/methodology/approach An online survey assessed the proposed motivational factors for the adoption of wearable healthcare devices. Confirmatory factor analysis and structural equation modeling were conducted on collected data (n=877) to demonstrate the reliability and validity of the measurement and structural model. Findings Perceived control and interactivity of wearable healthcare devices as well as users’ innovative tendencies are positively associated with usage intention, while perceived cost has no significant effects on user intention to use the devices. The results also supported the explanatory strength and predictability of TAM. Originality/value Although the promising role of wearable devices in healthcare industries has gained much consumer attention, limited empirical investigations have been conducted on explicating how user attitude and usage intention are shaped regarding the devices. This study serves as one of the first attempts to empirically examine the adoption process, with implications for the future usage of wearable technology in the healthcare context.

scholarly journals SMUPI-BIS: a synthesis model for users’ perceived impact of business intelligence systems

2021 ◽  
Vol 21 (3) ◽  
pp. 1856
Author(s):  
Intedhar Shakir Nasir ◽  
Ayad Hameed Mousa ◽  
Ihab L. Hussein Alsammak
Keyword(s):  
Technology Acceptance ◽  
Business Intelligence ◽  
Structural Equation ◽  
Information Quality ◽  
Success Factors ◽  
End Users ◽  
Equation Modeling ◽  
Intelligence System ◽  
Business Intelligence Systems ◽  
Perceived Impact

Business intelligence is a collection of methodologies, methods, architectures, and technologies that convert raw data into significant and useful information used by organizations to enable more effective strategic, tactical, and operational insights and decision-making.  In spite of several studies have examined the critical success factors and development of business intelligence System, but few relevant studies have investigated perceptions of end-users Business Intelligence Systems. Furthermore, none of those studies was performed in a Higher Education Sector in Iraq. Consequently, the study aims to determine the business intelligence system features influencing perceived impact end users’ and of using business intelligence systems in Iraqi educational institutes. A technology acceptance model and technology organization environment framework were syntheses as a basis to develop a research model for business intelligence users' perceived impact and adopt of business intelligence systems named (SMUPI-BIS). Later, an online instrument (questionnaire) was designed to gather data from the business intelligence system users in five Iraqi universities. Twenty-one hypotheses were proposed and later tested. Then, for data analysis, the authors used several methods such as hierarchical regression, one-way ANOVA, descriptive statistics as well as structural equation modeling (SEM). The main outcomes of this study suggest that decision support, information quality, and real-time reporting are the most significant system characteristics influencing end users' perceived impact and their usage of business intelligence systems.

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