Factors Influencing the Planned Adoption of Continuous Monitoring Technology

Gonzalez, George C.; Sharma, Pratyush Nidhi; Galletta, Dennis F.

doi:10.2308/isys-50259

Cited by 28 publications

(15 citation statements)

References 37 publications

(46 reference statements)

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“…The UTAUT synthesizes known conditions for assessment of the likelihood of technology adoption (Venkatesh et al 2003) and highlights the need for a structural framework that guides the adoption and utilization of technology in firms. Gonzalez et al (2012) used the UTAUT to explore the intention of businesses to adopt continuous monitoring technology(CMT) and assumed that the intentions of the organization are dependent on the intentions of the individuals in the firm and eliminated individual demographics from their UTAUT. Their findings are in line with the TAM assertion that PU is the most significant factor in the adoption of new technology, where performance expectancy is equivalent to PU but on the firm level.…”

Section: The Unified Theory Of Adoption and Utilization Of Technology (Utaut)mentioning

confidence: 99%

“…Their findings are in line with the TAM assertion that PU is the most significant factor in the adoption of new technology, where performance expectancy is equivalent to PU but on the firm level. Facilitating conditions and social influence were also determinants of CMT adoption and effort expectancy was found to not be significant in its adoption (Gonzalez et al 2012). Venkatesh et al (2012) established UTAUT2 incorporating constructs to better explain the consumer's adoption of technology.…”

Section: The Unified Theory Of Adoption and Utilization Of Technology (Utaut)mentioning

confidence: 99%

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Extended Technology Acceptance Model (TAM) for adoption of Information and Communications Technology (ICT) in the US Construction Industry

Sorce¹,

Issa²

2021

ITcon

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The global economic impact of the construction industry cannot be overstated. The use of information and communications technology (ICT) offers a potential for massive cost savings and increases in productivity. Unfortunately, the US construction industry lags behind most other US industries in the implementation of ICT. This research sets out to understand what factors improve the use and adoption of ICT in the US construction industry by applying the Technology Acceptance Model (TAM) developed by Davis (1989). The TAM recognized a relationship with actual use of technology based on the premise of behavioral intent (BI) and intended use and that user perceived usefulness (PU) leads to intended use, which translates to actual use. The TAM also recognizes that user perceived ease of use (PEOU) supports the premise of PU enhancing intended use by increasing the PU. This research used independent variables from previous research to serve as a basis for establishing a benchmark for US construction firms. Seventy-six US construction professionals were surveyed for this study. The results showed that the US construction industry follows the TAM model in that if the technology is perceived to be useful it will be adopted, and this seems to be supported by PEOU. Application of this extended TAM in the US construction industry will help companies predict the successful adoption and use of ICT, allowing managers to make more informed decisions in the adoption process.

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Section: The Unified Theory Of Adoption and Utilization Of Technology (Utaut)mentioning

confidence: 99%

Section: The Unified Theory Of Adoption and Utilization Of Technology (Utaut)mentioning

confidence: 99%

Extended Technology Acceptance Model (TAM) for adoption of Information and Communications Technology (ICT) in the US Construction Industry

Sorce¹,

Issa²

2021

ITcon

View full text Add to dashboard Cite

show abstract

“…According to Venkatesh et al (2003), social influence measures the extent to which significant others such as family, friends, and media influence a person's intention to adopt the technology. Gonzalez et al (2012) indicated that social influence has a significant effect on behavioral intention. This is consistent with the findings of Venkatesh et al (2011), Escobar-Rodríguez & Carvajal-Trujillo (2014, Hendarman and Tjakraatmadja (2014), Ifinedo (2012), Isaac et al (2017), Martins et al (2014).…”

Section: Social Influence (Si)mentioning

confidence: 99%

Modeling e-commerce adoption factors among Gen-Z in a developing country: the case of Ghana

Pobee

2021

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A cross-sectional data were gathered from 522 Gen Z population in the most populous and industrious regions in Ghana. Partial Least Square-Structural Equation Modelling (PLS-SEM) was employed to assess the hypothesized relationships. MOST IMPORTANT RESULTSThe findings indicate that effort expectancy, facilitating conditions, information quality, and system quality significantly affect the behavioral intention to adopt e-commerce among gen Z in Ghana. However, performance expectancy, social influence, and service quality had an insignificant effect on behavioral intention. This study is one of the few that have integrated the UTAUT model with DeLone and McLean IS success model to investigate e-commerce adoption. In a developing country context, and to the best of the author's knowledge, this is the first research to investigate the e-commerce adoption of a particular generation (Gen Z) in Ghana. RECOMMENDATIONSThe paper concludes that the ease of using online shopping applications, the readiness and availability of support service for online purchases, information quality, and the efficiency and reliability of e-commerce systems significantly influence gen Z adoption of e-commerce. As a result, e-vendors and website business designers should ensure that the design and layout of e-commerce websites must be easy for consumers to navigate, provide a 24-hour consumer support system, and ensure efficiency and reliability of the e-commerce system.

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“…Jadi media massa dan advertensi dapat berperan dalam menciptakan kesadaran dan pengetahuan, penyuluhan berguna untuk memersuasi, pengaruh antar pribadi berfungsi bagi keputusan untuk menerima atau menolak inovasi dan pengalaman dalam menggunakan inovasi dapat menjadi sumber konfirmasi untuk menerapkan inovasi atau sebaliknya dan secara tegas terjadi juga dengan variabel-variabel sistem sosial yang berperan terutama pada tahap awal ( pengetahuan) dan tahap berikutnya (H.R. Burhan Bungin,2006); pengaruh sosial terhadap rencana adopsi teknologi berkelanjutan (Gonzalez, Sharma, & Galletta, 2012).…”

Section: Pendahuluanunclassified

Inovasi Dan Difusi Pencegahan Covid-19 Di Kalangan Mahasiswa

et al. 2021

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Mahasiswa jurusan pendidikan matematika Unversitas Halu Oleo eksistensinya sebagai agen perubahan memiliki peran dan tanggungjawab besar bersama dalam rangka giat memutus rantai wabah Covid-19 mendukung kebijakan pemerintah sesuai rekomendasi WHO tentang beberapa langkah dasar untuk membantu mencegah penyebaran Covid-19. Kegiatan ini bertujuan mendeskripsikan (1) proses difusi hasil-hasil inovasi media poster dan video mahasiswa dalam pencegahan penyebaran Covid-19 kepada warga di lingkungan masing-masing dan warga net (netizen); (2) penerimaan media poster dan video hasil inovasi oleh warga di lingkungan masing-masing dan warga net (netizen) melalui saluran media sosial. Pelaksanaan kegiatan terdiri atas 3 tahapan: (1) persiapan, (2) pelaksanaan, dan (3) monitoring pelaksanaan dan evaluasi daya tolak/penerimaan didasarkan pada bentuk-bentuk respon, dan sikap masyarakat terhadap hasil-hasil inovasi. Proses difusi hasil inovasi poster dan video pencegahan penyebaran Covid-19 melibatkan komunikasi interpersonal dan media massa serta terjadi komunikasi inovasi pada sistem sosial masyarakat setempat dan warga net (netizen).

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Factors Influencing the Planned Adoption of Continuous Monitoring Technology

Cited by 28 publications

References 37 publications

Extended Technology Acceptance Model (TAM) for adoption of Information and Communications Technology (ICT) in the US Construction Industry

Extended Technology Acceptance Model (TAM) for adoption of Information and Communications Technology (ICT) in the US Construction Industry

Modeling e-commerce adoption factors among Gen-Z in a developing country: the case of Ghana

Inovasi Dan Difusi Pencegahan Covid-19 Di Kalangan Mahasiswa

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