scholarly journals Assessing Determinants of Continuance Intention towards Personal Cloud Services: Extending UTAUT2 with Technology Readiness

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 467
Author(s):  
Shih-Chih Chen ◽  
Shing-Han Li ◽  
Shih-Chi Liu ◽  
David C. Yen ◽  
Athapol Ruangkanjanases
Keyword(s):  
Rapid Development ◽  
Cloud Service ◽  
Individual Characteristics ◽  
Partial Least Square ◽  
Cloud Services ◽  
Least Square ◽  
Information And Communications Technology ◽  
Technology Readiness ◽  
Continuance Intention ◽  
Systems Research

In addition to the rapid development of global information and communications technology (ICT) and the Internet, recent rapid growth in cloud computing technology represents another important trend. Individual continuance intention towards information technology is a critical area in which information systems research can be performed. This study aims to develop an integrated model designed to explain and predict an individual’s continuance intention towards personal cloud services based on the concepts of technology readiness (TR) and the unified theory of acceptance and use of technology 2 (UTAUT2), moderated by gender, age, and experience of personal cloud services. The key results of the partial least square test largely support the proposed model’s validity and the significant impact of effort expectancy, social influence, hedonic motivation, price value, habit, and technology readiness on continuance intention towards personal cloud services. In addition to providing symmetric theoretical support with the proposed model and transforming the individual characteristics of TR into UTAUT2, this study could be used to enhance and analyze users’ adoption of personal cloud services and also increase the symmetry of the model’s explanation and prediction. The findings from this research contribute to providing practical implications and academic resources as well as improving our understanding of personal cloud service applications.

Temperature distribution estimation via data-driven model and adaptive Kalman filter in modular data centers

2020 ◽  
Vol 234 (7) ◽  
pp. 809-819
Author(s):  
Kai Jiang ◽  
Shizhu Shi ◽  
Hosein Moazanigoodarzi ◽  
Chuan Hu ◽  
Souvik Pal ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Temperature Distribution ◽  
Data Centers ◽  
Rapid Development ◽  
Partial Least Square ◽  
Least Square ◽  
Information And Communications Technology ◽  
Data Driven ◽  
Adaptive Kalman Filter ◽  
Cooling Unit

With the rapid development of information and communications technology, increasing number of data centers is required to support the cloud computing, and critical web-based services that run our daily lives. The conventional cloud data centers usually adopt computer room air conditioner or inRow units as the cooling sytem, while the rack mountable cooling unit is a more promising equipment due to the economy, exact controllability, flexibility, and scalability. To ensure the efficiency of control system in rack mountable cooling unit and the security of servers in the data centers, the information of temperature distribution is very essential. Basically, the temperature distribution could be obtained through physical sensors easily. However, considering the cost of whole system and the burden of fault diagnosis in sensor networks, the number of temperature sensors should be kept down to a bare minimum. Therefore, it is necessary to develop an effective and real-time observer to estimate the temperature distribution in the system. Besides, due to the complex air flow and heat transfer in the container, it is quite difficult to construct a physics model. To this end, a novel observer embracing data-driven model and adaptive Kalman filter is proposed in this work. Auto regression exogenous model is adopted as the framework of data-driven model, and the model is identified through a algorithm of partial least square. Moreover, to represent the nonlinear behaviors in the system, fuzzy c-means is applied for data classification and getting multiple local linear models. Finally, adaptive Kalman filter is utilized to estimate the temperature distribution on the basis of proposed data-driven model. The estimation results based on experimental data indicate the performance of proposed approach is remarkable.

Crafting experiential value via smartphone apps channel

2017 ◽  
Vol 35 (5) ◽  
pp. 688-702 ◽  
Author(s):  
Sajad Rezaei ◽  
Naser Valaei
Keyword(s):  
Rapid Development ◽  
Measurement Model ◽  
Partial Least Square ◽  
Least Square ◽  
Smartphone Apps ◽  
Continuance Intention ◽  
Content Type ◽  
Experiential Value ◽  
The Impact ◽  
The Relationship

Purpose The purpose of this paper is to investigate the impact of post-usage usefulness (PUU), experiential value, and apps channel satisfaction on consumer continuance intention in using the smartphone apps retail channel for shopping activities. The study proposes that experiential value mediates both the relationship between PUU and apps channel satisfaction and the relationship between PUU and apps channel continuance intention. Design/methodology/approach A total of 467 valid questionnaires were received from Malaysian experienced smartphone apps shoppers (minimum of six months experience) from pure play apps retailers to empirically test the model. For the assessment of the measurement model and structural relationships, partial least square path modelling approach was performed. Findings The hypotheses testing imply that all direct hypotheses between latent constructs are supported. Experiential value partially mediates the relationship between PUU and apps channel satisfaction and the hypothesis on its mediation role on the relationship between PUU and apps channel continuance intention is rejected. Originality/value Despite the rapid development of information technology, a few research uncovered how businesses can create value through smartphone apps channel. Rather than focussing exclusively on online retailing, physical stores and e-commerce in general as a retail distribution strategy, this study empirically uncovered that value creation process could be achieved through smartphone apps channel.

scholarly journals Uncovering the Providers’ Continuance Intention of Participation in the Sharing Economy: A Moderated Mediation Model

2021 ◽  
Vol 13 (9) ◽  
pp. 5095
Author(s):  
Jiang Jiang ◽  
Rui Feng ◽  
Eldon Y. Li
Keyword(s):  
Sharing Economy ◽  
Economic Benefits ◽  
Peer To Peer ◽  
Partial Least Square ◽  
Least Square ◽  
Mediating Effect ◽  
Utilization Efficiency ◽  
Continuance Intention ◽  
Hedonic Value ◽  
Ride Sharing

The sharing economy has evolved into a promising business concept that enables individuals to share their idle resources, improving resource utilization efficiency commercially. Recently, it has gained enormous academic attention. However, little concern has been given to the behavior of individual providers on the supply side. This paper aims to uncover the motivational and trust-based providers’ continuance intention of participation in the context of peer-to-peer ride-sharing services. Based on the survey data from 202 providers and the partial least-square analysis, we confirm the mediating effect of attitude in the relationships between participation continuance intention; trust; and three motivational dimensions: economic benefits, social–hedonic value, and sustainability. We further confirm the moderating effects of innovativeness using PROCESS. The results show that economic benefits, social–hedonic value, and sustainability significantly affect providers’ participation continuance intention. Moreover, attitudes toward the sharing economy play a complementary partial-mediating role in the relationships from economic benefits and social–hedonic value to participation continuance intention, which is negatively moderated by innovativeness. Trust does not significantly affect providers’ attitude toward the sharing economy and participation continuance intention in the peer-to-peer ride-sharing context.

scholarly journals Analisis penerimaan pengguna aplikasi e-Kinerja dengan metode TRAM dan EUCS pada kepolisian

Teknologi ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 93-109
Author(s):  
Anthony Eko Hadisuwarno ◽  
◽  
Rahadian Bisma ◽  
Keyword(s):  
Theoretical Model ◽  
User Satisfaction ◽  
Structural Equation ◽  
Sampling Technique ◽  
User Acceptance ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Technology Readiness ◽  
Acceptance Model

This study aims to determine user acceptance and what factors influence user acceptance of E-Kinerja. The theoretical model used is a combination of the theoretical model of technology adoption of TRAM (Technology Readiness Acceptance Model) and EUCS (End User Computing Satisfaction). For example, the intention to use variable in the TRAM (Technology Readiness Acceptance Model) model is used as a link between the two models in this study. This research was conducted in Sidoarjo Police by using a questionnaire that was distributed directly as a source of data with probability sampling technique involving the participation of 229 respondents from Sidoarjo Police as members of the e-Kinerja application. The data analysis technique used is PLS-SEM (Partial Least Square-Structural Equation Modeling). The results of this study state that there are seven positive and ten negative hypotheses. The findings of this study are the user's intention to positively influence user satisfaction in using the e-Kinerja application which can be interpreted that the user feels satisfied and accepts the e-Kinerja application as an information system that can help reporting and calculating the performance of each member of the Sidoarjo Police.

scholarly journals Video Cloud Services for Hospitals: Designing an End-to-End Cloud Service Platform for Medical Video Storage and Secure Access

10.2196/18139 ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. e18139
Author(s):  
Piotr Pawałowski ◽  
Cezary Mazurek ◽  
Mikołaj Leszczuk ◽  
Jean-Marie Moureaux ◽  
Amine Chaabouni
Keyword(s):  
Video Quality ◽  
Cloud Service ◽  
Video Data ◽  
Cloud Services ◽  
Information And Communications Technology ◽  
Video Encoding ◽  
Rapid Expansion ◽  
Long Run ◽  
Generic Architecture ◽  
End To End

The amount of medical video data that has to be securely stored has been growing exponentially. This rapid expansion is mainly caused by the introduction of higher video resolution such as 4K and 8K to medical devices and the growing usage of telemedicine services, along with a general trend toward increasing transparency with respect to medical treatment, resulting in more and more medical procedures being recorded. Such video data, as medical data, must be maintained for many years, resulting in datasets at the exabytes scale that each hospital must be able to store in the future. Currently, hospitals do not have the required information and communications technology infrastructure to handle such large amounts of data in the long run. In this paper, we discuss the challenges and possible solutions to this problem. We propose a generic architecture for a holistic, end-to-end recording and storage platform for hospitals, define crucial components, and identify existing and future solutions to address all parts of the system. This paper focuses mostly on the recording part of the system by introducing the major challenges in the area of bioinformatics, with particular focus on three major areas: video encoding, video quality, and video metadata.

Relationship among Project Management Processes and Knowledge Repository for Project Success

2016 ◽  
Vol 12 (4) ◽  
pp. 16-30
Author(s):  
Samer Alhawari
Keyword(s):  
Project Management ◽  
Quantitative Research ◽  
Project Success ◽  
Partial Least Square ◽  
Least Square ◽  
Information And Communications Technology ◽  
Research Approach ◽  
Knowledge Repository ◽  
Key Factor ◽  
Survey Strategy

Knowledge repository is becoming a key factor within organizations as it can maximize the probability and impact of Information and Communications Technology (ICT) project success. Therefore, project management (PM) processes and knowledge repository are widely used in ICT projects to improve the degree of project success. The purpose of this paper is to suggest a model that defines how the combination of PM processes and knowledge repository would successfully support project success. This paper adapts the quantitative research approach by using the survey strategy which is conducted through questionnaires collected from 320 people working in ICT companies in Jordan. The researchers utilized the Smart Partial Least Square (PLS) as an analysis technique to test all hypotheses. The findings suggest that there is a positive effect of adapting the PM processes in improving the project success mediation by the knowledge repository.

Using near infrared spectroscopy to determine moisture and starch content of corn processing products

2017 ◽  
Vol 25 (5) ◽  
pp. 348-359 ◽  
Author(s):  
Ye Chen ◽  
Lauren Delaney ◽  
Susan Johnson ◽  
Paige Wendland ◽  
Rogerio Prata
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Starch Content ◽  
Rapid Development ◽  
Partial Least Square ◽  
Least Square ◽  
Operational Parameters ◽  
Corn Flour ◽  
Analytical Technique

Due to the rapid development of the corn-to-ethanol industry, the demand for process monitoring has led to the gradual substitution of traditional analytical techniques with fast and non-destructive methods such as near infrared spectroscopy. In this study, the feasibility of using Fourier transform–near infrared technology as an analytical tool to predict operational parameters (dry solids, starch, carbohydrate, and ethanol content) was investigated. Corn flour, liquefied mash, fermented mash, and distiller’s dried grains with solubles were selected to represent the feedstock, two intermediate products, and one primary co-product of corn-to-ethanol plants, respectively. Multivariate partial least square calibration models were developed to correlate near infrared spectra to the corresponding analytical values. The validation results indicate that near infrared models can be developed that will predict various parameters accurately (root mean square error of prediction: 0.16–1.14%, residual predictive deviation: 3.0–6.3). Measurement of starch or carbohydrate content in corn flour or distiller’s dried grains with solubles is challenging due to low accuracy of wet chemistry methods as well as sample complexity. The study demonstrated that near infrared spectroscopy, a high-throughput analytical technique, has the potential to replace the enzymatic assay.

scholarly journals Factors Affecting Continuance Intention of FinTech Payment among Millennials in Jakarta

2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Norma Diana ◽  
Farah Margaretha Leon
Keyword(s):  
Economic Benefits ◽  
Influential Factors ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Financial Risks ◽  
Continuance Intention ◽  
Security Risks ◽  
Operational Risks ◽  
Legal Risks

The background of this research is related to a phenomenon of millennials who prefer to change their financial behavior into cashless transactions from cash-based transactions. Factors of benefits (economic benefits, seamless transactions, and convenience) and risks (financial risks, legal risks, security risks, and operational risks) experienced by millennials are examined to observe their effects on the continuance intention of financial technology (FinTech) payment. FinTech users are classified into two types, namely early adopters and late adopters. This study examines the variables of continuance intention of FinTech payment, economic benefits, seamless transactions, convenience, financial risks, legal risks, security risks, operational risks, perceived benefits, and perceived risks simultaneously and is the first to be conducted on millennials in Jakarta. The methodology used was the Structural Equation Modeling-Partial Least Square. The data were collected through questionnaires distributed to 313 respondents. The results of this research show that convenience is the most influential benefit factor towards the continuance intention of FinTech payment. Operational risks are the only factor that do not significantly affect the continuance intention of FinTech payment. The differences between the effects of benefits and risks are found in both of the user types. The implication of this research is to further understand influential factors in millennials’ decisions to use FinTech payment services.

scholarly journals PENGARUH SPIRITUALITAS ISLAMI DI TEMPAT KERJA TERHADAP KOMITMEN NORMATIF DENGAN KARAKTERISTIK INDIVIDU SEBAGAI VARIABEL MODERATOR

IQTISHODUNA ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. 1-8
Author(s):  
Lailatul Istianah ◽  
Anang Kistyanto
Keyword(s):  
Individual Characteristics ◽  
Partial Least Square ◽  
Least Square ◽  
Normative Commitment ◽  
Moderating Role

This study was to analyze the effect of workplace Islamic spirituality, normative commitment, andindividual characteristics, as well as the moderating role of individual characteristics on workplace Islamicspirituality to normative commitment. Sample of this study were all nurses of the RSI Darus Syifa Surabayatotaling 67 nurses to 66 nurses from the calculation questionnaire back to the processed. Methods of thestatistical analysis that used were SEM Partial Least Square (PLS) with smartPLS 2.0 software. The result ofthis research explained that workplace Islamic spirituality positive and significant effect on normativecommitment. Individual characteristics not moderate the effect of workplace Islamic spirituality to normativecommitment.

scholarly journals The Intervening Effect of Current Knowledge Enhancement on Attitude and Intention to Choose Accounting Career

2019 ◽  
Vol 10 (2) ◽  
pp. 119-130
Author(s):  
Saarce Elsye Hatane ◽  
Felicia Jesslyn Setiono
Keyword(s):  
Significant Influence ◽  
Structural Equation ◽  
Current Knowledge ◽  
Learning Experience ◽  
Rapid Development ◽  
Educational Background ◽  
Equation Model ◽  
Partial Least Square ◽  
Least Square ◽  
Accounting Students

The purpose of this research was to examine the influence of attitude in accounting students to the intention to choose an accounting career. It was through the intention to increase current knowledge as an intervening variable. This research used a survey online method to test the research model, which was responded by a total of 503 accounting students across Java. Data analysis and hypothesis testing used partial least square as part of the structural equation model technique. According to their ages, the respondents were famous as the millennial generation in this era. The results of this research are in accordance with the Theory of Planned Behavior (TPB). It is proven that attitudes have a positive and significant influence on the intentions of accounting students in terms of increasing current knowledge and choosing accounting careers. This research also supports the Social Cognitive Career Theory (SCCT). There is evidence that educational background and learning experience can increase the intention of accounting students to pursue careers in accounting. The existence of different generations leads to different perceptions of students regarding accounting careers. Therefore, further research is needed to identify these differences. The results also suggest that accounting educators need to update their curriculum by adapting the current development and demands of graduates. Last, the rapid development of technology has had a significant influence on the accounting profession.

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