scholarly journals Explaining Mobile Commerce Usage Intention Based on Technology Acceptance Models in a Developing Market Context

2021 ◽  
Vol 33 (1) ◽  
pp. 25-40
Author(s):  
Luis Edwin Chimborazo ◽  
Marta Frasquet ◽  
Alejandro Mollá
Author(s):  
H. Hung

The Internet has undoubtedly introduced a significant wave of changes. The increased electronic transmission capacity and technology further paves a superhighway towards unrestricted communication networks (Chircu & Kauffman, 2000; Cowles, Kiecker, & Little, 2002). It is estimated that by 2007, the total number of Internet users in the world will be over 1.4 billion and the percentage of wireless users is projected to take up about 57% of the vast number (Magura, 2003). Most people anticipate that the next-generation commerce will emerge from traditional commerce to PC-based e-commerce, and eventually to mobile commerce (Ellis-Chadwick, McHardy, & Wiesnhofer, 2000, Miller, 2002, Watson, Pitt, Berthon, & Zinkhan, 2002).Mobile commerce (m-commerce) is an extension, rather than a complete replacement, of PC-based electronic commerce. It allows users to interact with other users or businesses in a wireless mode, anytime and anywhere (Balasubramanian, Peterson, & Jarvenpaa, 2002; Samuelsson & Dholakia, 2003). It is very likely that PC-based e-commerce will still prevail for a relatively long period of time in spite of the trend that more and more people will choose to adopt m-commerce for their purchases (Miller, 2002).The focus of our article is on the consumers’ adoption of m-commerce devices (MCDs), which are equipment and technologies that facilitate users to make use of m-commerce. MCDs include mobile phones, personal digital assistants (PDA), portable computer notebooks, Bluetooth, WAP, and other facilities that can have access to the wireless networks. We expect that the heading towards a world of mobile networks and wireless devices, which will present a new perspective of time and space, is definitely on its way. Several basic questions about m-commerce devices will be addressed in this article. First, why should consumers adopt MCDs? What will be the influencing factors for consideration? Are these MCDs easy to use and proven to be useful? Second, how do the MCDs compare with the devices for other types of commerce, such as e-commerce or traditional mail order? Consumers will only adopt MCDs when there are some potential significant advantages when comparing to old devices for other types of commerce. There is still a lack of comprehensive framework within which the adoption of MCDs can be evaluated. Traditional viewpoints regarding this issue, especially those that are based on technology acceptance models, will need to be revisited and revised when consumers are considering such an adoption. In this article, we propose a framework for identifying the various influencing factors of the adoption of MCD, as well as the antecedents of these influencing factors. Because of the need of the standardization of the application, interface, and inter-connectivity of all hardware and software relevant to the adoption and usage of MCDs, our proposed framework will have some global implications (Zwass, 1996). Our conceptual framework can, therefore, make significant contributions to a more in-depth understanding in the spread and acceptability of m-commerce through knowing why and how relevant MCDs are adopted. While using technology acceptance models (TAMs) as our primary reference, we also incorporate the important implications of an options model into our basic framework of analyzing consumers’ adoption of MCDs. Based on our theoretical framework, we identify four influencing factors - merits, maturity, maneuverability, and mentality - which we consider to be relevant to the decision of consumers in adopting MCDs. We also identify two generic antecedents of these influencing factors - mobility and matching. We plan to investigate the extent of influence of these influencing factors and their antecedents, which will affect consumers’ adoption decisions of MCDs. Figure 1 is a graphical representation of our conceptual model of the adoption of MCDs by consumers.


Author(s):  
Anna M. H. Abrams ◽  
Pia S. C. Dautzenberg ◽  
Carla Jakobowsky ◽  
Stefan Ladwig ◽  
Astrid M. Rosenthal-von der Pütten

2012 ◽  
Vol 3 (2) ◽  
pp. 36-49 ◽  
Author(s):  
Emad Abu-Shanab ◽  
Osamah Ghaleb

This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived risks (security and privacy concerns) constructs to identify the impact of these factors on Jordanian users’ intentions to adopt mobile commerce (m-commerce). An empirical test was used utilizing 132 responses from students in two public universities in Jordan. Results indicated that perceived trust, perceived usefulness, and perceived ease of use are major influencers of mobile commerce adoption. On the other hand, perceived risk factors (security and privacy concerns) were not significant in this relation. Discussion, conclusion and future work are stated at the end of this paper.


2019 ◽  
Vol 23 (1) ◽  
pp. 7-16
Author(s):  
Robert J. Mills ◽  
Matthew E. Harris

As organizations continue to implement new technology solutions, the need for both technology training and examining technology acceptance of new implementations are necessary to determine the success or failure of a project. Unfortunately, instructional design considerations generally do not address technology acceptance, and leading technology acceptance models only classify training as an external variable or facilitating condition, with limited consideration in prior research. In this paper, we examine potential integration points between instructional design theory and technology acceptance. Specifically, we examine prior research on self-efficacy, Kirkpatrick’s Model for Evaluating Training, Merrill’s Component Display Theory, and Merrill’s First Principles of Instruction.


2018 ◽  
Vol 40 (4) ◽  
pp. 405-415 ◽  
Author(s):  
Manish Shirgaokar

Seniors (over 64 years) are a growing demographic. Some seniors risk social exclusion given the lack of transportation options. Using qualitative methods, I investigate how transportation network company (TNC) services such as Lyft and Uber present an alternative for seniors’ mobility in comparison to taxis. I use technology acceptance models as a lens and explore the challenges that TNC services present for seniors. This analysis suggests that emerging transportation services—including self-driving cars—may present a boon for seniors if stakeholders from the private and public sectors can increase the ease of use of these new forms of mobility.


2021 ◽  
pp. 147572572110371
Author(s):  
Sabrina Gado ◽  
Regina Kempen ◽  
Katharina Lingelbach ◽  
Tanja Bipp

Psychologists with their expertise in statistics and regarding human perception and behavior can contribute valuable insights to the development of innovative and useful artificial intelligence (AI) systems. Therefore, we need to raise attention and curiosity for AI and foster the willingness to engage with it among psychology students. This requires identifying approaches to integrate a general understanding of AI technology into formal psychological training and education. This study investigated to what extent psychology students currently accept and use AI and what affects their perception and usage. Therefore, an AI acceptance model based on established technology acceptance models was developed and tested in a sample of 218 psychology students. An acceptable fit with the data was found for an adapted version. Perceived usefulness and ease of use were most predictive for the students’ attitude towards AI; attitude itself, as well as perceived usefulness, social norm, and perceived knowledge, were predictors for the intention to use AI. In summary, we identified relevant factors for designing AI training approaches in psychology curricula. In this way, possible restraints regarding the use of AI can be reduced and its beneficial opportunities exploited in psychological contexts.


Author(s):  
Maddy Halbach ◽  
Tao Gong

The purpose of this study was to investigate the roles leadership behaviors have on technology acceptance models, focusing on bank leaders’ intention to use mobile-commerce. The study included responses from 101 senior-level managers working at FDIC-insured commercial banks in the United States. Three instruments including Kouzes and Posner’s (1987) leadership practice inventory (LPI), Wu and Wang’s (2005) mobile commerce technology acceptance model (MC-TAM), and Oreg’s (2003) resistance to change model (RTC) were employed. A correlation analysis revealed that two transformational leadership behaviors—model the way and enabling others to act—positively relate to behavioral intent to use mobile commerce. A regression analysis found that perceived compatibility, perceived usefulness, and perceived ease of use are positively related to the behavioral intent to use m-Commerce. However, the authors found that the RTC and LPI model cannot predict the willingness to use m-Commerce.


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