The intellectual development of the technology acceptance model: A co-citation analysis

Hsiao, Chun-Hua; Yang, Chyan

doi:10.1016/j.ijinfomgt.2010.07.003

Cited by 187 publications

(119 citation statements)

References 111 publications

(162 reference statements)

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“…It focuses on the initial adoption of new technologies, but researchers have extended it to examine continued use over time and to account for the confirmation or disconfirmation users' expectations (Bhattacherjee, 2001;Venkatesh, Thong, Chan, Hu, & Brown, 2011) and the habits that people develop (Limayem, Hirt, & Cheung, 2007). For reviews of this research, see Hsiao and Yang (2011) and Turner, Kitchenham, Brereton, Charters, and Budgen (2010).…”

Section: Prior Research On Technology Usementioning

confidence: 99%

Demystifying the Link between Social Media Addiction and Sharing without Verification: The Role of Absentmindedness and Wellbeing

Dennis¹,

Clay²,

Ko³

2024

THCI

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Abstract:In this paper, we argue that one can understand the adoption and routine use of enterprise systems by examining the fit between the system and the social structures of the organization. We develop a model of the adoption and longterm use of enterprise systems based on sociological concepts (Lord Anthony Giddens' structuration theory) rather than the usual cognitive psychology concepts. We focus on the adoption and use of three versions of an enterprise KMS to support sales representatives at a multinational pharmaceutical firm. Our first study (a five-year case study of the KMS that went through one failed deployment and two successful ones) shows that the structures of signification, legitimation, and domination all influence loyal use, although domination may be less important. Our second study (a survey of 893 users at the firm) shows that the structures of signification, legitimation, and domination explain about 50 percent of the variance in ongoing loyal use but that their relative importance depends on the job experience of the users: signification and legitimation influence novices more, and signification and domination influence experts more. We believe that this parsimonious three-factor model offers a useful approach for future research and practice.

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Section: Prior Research On Technology Usementioning

confidence: 99%

Demystifying the Link between Social Media Addiction and Sharing without Verification: The Role of Absentmindedness and Wellbeing

Dennis¹,

Clay²,

Ko³

2024

THCI

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“…이러한 작업을 바탕으로 TAM은 국 내외 여러 학자들에 의해 1990년대 이후 새로운 디지털 미디어의 채택 행동을 설명하기 위해 사용되어 왔다 [21] . (SERVQUAL)이라고 불렀다 [46] .…”

Section: Sns 이용과 관련된 기존의 연구에서는 이용자의 Sns 이용 동기 및 참여행태를 보는 데 있어 정치․사회unclassified

The Effect of the SNS service and personal characteristics on Participation Intention

Oh¹,

Lee²,

An³

et al. 2017

JIIBC

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Recently, Due to advances in smart-phones and mobile devices, the use of SNS is increasing in recent years. Online networking is building new paradigms in terms of creating personal needs. Along with the nature of mobile devices, it is expected to have a lot of impact on SNS service participation. The study focused on the effect of SNS on SNS participation and ease of use of social characteristics and ease of use of SNS. A survey was conducted on a survey of SNS users and analyzed the data through the structural equations. The study found that the study of social networking was statistically significant in terms of the intent of identifying the usefulness of SNS and ease of use and ease of use.

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Section: Introductionmentioning

confidence: 99%

“…This AMT subset is referred to as Shop Floor Manufacturing Technologies (SFMT) for this research. Focusing on SFMT mitigates the moderating impact of technology type (King and He, 2006;Hsiao and Yang, 2011).A Supplier Support Technology Adoption Model was developed and tested to determine the value of AMT supplier support. Results indicate that supplier support facilitates successful technology adoption.…”

mentioning

confidence: 99%

“…This subgroup of technologies is labeled Shop Floor Manufacturing Technologies (SFMT), relatively consistent with the manufacturing technologies category of AMT suggested by Boyer et al (Boyer et al, 1997). An AMT subset was selected because context matters when exploring technology adoption (Hsiao and Yang, 2011). Potential moderating impacts of user and usage type (King and He, 2006), and technology type (Schepers and Wetzels, 2007) were mitigated by focusing on SFMT.…”

mentioning

confidence: 99%

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The Value Contribution of Manufacturing Technology Suppliers

Scannell

Peterson²,

Curkovic

2013

JBAR

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This research examined the value of advanced manufacturing technology (AMT) supplier support by testing a structural model that relates need for support with actual support received, and the impact of that support on implementation, operational and business success. Current research is expanded by simultaneously testing the relationship between these factors in a single model. The recent adoption of a specific subset of AMT was the unit of analysis. The proposed model has good statistical fit and the four hypotheses were supported. Firms adopting new manufacturing technologies benefit from collaborative relationships with manufacturing technology suppliers, suggesting that the service capabilities of technology suppliers be critically evaluated during supplier and AMT selection. Companies use AMT to achieve higher performance on multiple competitive dimensions and to drive business outcomes (Zhang et al., 2006). However, some AMT adoption processes fail to deliver the planned benefits (Baldwin and Lin, 2002;Percival, 2009) AMT refers to a range of computer controlled technologies and organizational processes used to develop and produce a product (Lewis and Boyer, 2002;Small, 2007). This research focuses on a subset of AMT: computerized numerical control (CNC) machines, direct numerical control (DNC) machines, material working lasers, and robots. This AMT subset is referred to as Shop Floor Manufacturing Technologies (SFMT) for this research. Focusing on SFMT mitigates the moderating impact of technology type (King and He, 2006;Hsiao and Yang, 2011).A Supplier Support Technology Adoption Model was developed and tested to determine the value of AMT supplier support. Results indicate that supplier support facilitates successful technology adoption. Further, technology implementation success is associated with eventual operational success which in turn is positively associated with business performance success. These results suggest that companies should critically evaluate the need for supplier support prior to selecting an AMT. The following section reviews the literature to develop the research model and hypotheses. The research methodology is then discussed, followed by a presentation of the results. The discussion section presents managerial implications, limitations of the research, and future research directions. Review of the literature and model developmentAMT includes a variety of computer-based systems and organizational practices that are used in the development and production of a product (Lewis and Boyer, 2002;Small, 2007). AMT has been categorized by function: stand-alone

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The intellectual development of the technology acceptance model: A co-citation analysis

Cited by 187 publications

References 111 publications

Demystifying the Link between Social Media Addiction and Sharing without Verification: The Role of Absentmindedness and Wellbeing

Demystifying the Link between Social Media Addiction and Sharing without Verification: The Role of Absentmindedness and Wellbeing

The Effect of the SNS service and personal characteristics on Participation Intention

The Value Contribution of Manufacturing Technology Suppliers

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