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Understanding Competing Web Application Platforms: An Extended Theory of Planned Behavior and its Relative Model | IEEE Journals & Magazine | IEEE Xplore

Understanding Competing Web Application Platforms: An Extended Theory of Planned Behavior and its Relative Model


Abstract:

Despite many competing software systems being offered by different vendors, studies in information technology (IT) adoption rarely look at the adoption of competing produ...Show More

Abstract:

Despite many competing software systems being offered by different vendors, studies in information technology (IT) adoption rarely look at the adoption of competing products. We develop an extended theory of planned behavior (TPB), drawn from social psychology and marketing theories, to predict choice intention and subsequently the choice of two products. The extended TPB is used to compare the two products in a single analysis using relative values. The study is set in the context of two web application platforms: Microsoft and Java. A survey shows that the relative model can explain a high percentage of the variance in choice intention and actual choice. The results suggest that each product may have its own forte, with a different set of important factors. Applying the relative model to examine competing products can capture different dimensions and strengths to differentiate impacts on choice of alternative products. Factors that appear to be important for single-product analyses may not be important in a relative analysis. This highlights the importance of having a relative model study over separate single-product studies.
Published in: IEEE Transactions on Engineering Management ( Volume: 58, Issue: 1, February 2011)
Page(s): 21 - 35
Date of Publication: 09 September 2010

ISSN Information:

Citations are not available for this document.

I. Introduction

Though information technology (IT) acceptance is one of the most mature research topics in the information systems field, researchers in this field have largely ignored the acceptance of alternative products. The effects of alternative products on intention and the influence of predicting very specific IT product acceptance have also been largely unexplored by researchers in this field. For instance, some studies have looked at the acceptance of Word, WordPerfect, Lotus 1-2-3, Excel, or Math Explorer [1]–[5]. Researchers in the field of psychology have pointed out that measuring a very specific product may trigger subjects to think of other alternative products [6]–[8]. When subjects are asked for a very specific product such as Word Perfect, they may compare their evaluations with other alternatives (e.g., Microsoft Word). Therefore, single-product studies may yield conclusions that are incomplete without data about the competing alternative. Motivated by these factors, this research seeks to understand the factors affecting the choice of IT products by examining intentions of alternative products.

Cites in Papers - |

Cites in Papers - IEEE (4)

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1.
Min-Jhih Cheng, Shiu-Wan Hung, Her-Her Tsai, Yin-Chen Chou, "Fostering Environmentally Responsible Consumer Behavior: A Hierarchical Approach Toward Smartphone Recycling", IEEE Transactions on Engineering Management, vol.69, no.5, pp.2326-2336, 2022.
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3.
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Cites in Papers - Other Publishers (11)

1.
Xiao-Liang Shen, Yang-Jun Li, Yongqiang Sun, Feng Wang, "Good for Use, but Better for Choice: A Relative Model of Competing Social Networking Services", Information & Management, pp.103448, 2021.
2.
Jitendra Yadav, Madhvendra Misra, Nripendra P. Rana, Kuldeep Singh, Sam Goundar, "Netizens' behavior towards a blockchain-based esports framework: a TPB and machine learning integrated approach", International Journal of Sports Marketing and Sponsorship, vol.ahead-of-print, no.ahead-of-print, 2021.
3.
Jérémie Katembo Kavota, Jean Robert Kala Kamdjoug, Samuel Fosso Wamba, "Social media and disaster management: Case of the north and south Kivu regions in the Democratic Republic of the Congo", International Journal of Information Management, pp.102068, 2020.
4.
Khaoula Ben Zarb, Khaoula Ben Zarb, Catherinne De La Robertie, Catherinne De La Robertie, Samia Karoui Zouaoui, Samia Karoui Zouaoui, "Leadership ambidextre: resultats d?une etude qualitative exploratoire", @GRH, vol.n?30, no.1, pp.105, 2019.
5.
Wenhui Fu, Qiang Wang, Xiande Zhao, "Platform-based service innovation and system design: a literature review", Industrial Management & Data Systems, 2018.
6.
Azzah Al Maskari, Technology Adoption and Social Issues, pp.46, 2018.
7.
Jin Ho Kim, Weiru Chen, "Research Topic Analysis in Engineering Management Using a Latent Dirichlet Allocation Model", Journal of Industrial Integration and Management, vol.03, no.04, pp.1850016, 2018.
8.
Julia Mueller, Birgit Renzl, Matthias Georg Will, "Ambidextrous leadership: a meta-review applying static and dynamic multi-level perspectives", Review of Managerial Science, 2018.
9.
Hayden Wimmer, Cheryl Aasheim, "Examining Factors that Influence Intent to Adopt Data Science", Journal of Computer Information Systems, pp.1, 2017.
10.
Azzah Al Maskari, Information Seeking Behavior and Technology Adoption: Theories and Trends, pp.237, 2015.
11.
Meeta Dasgupta, "Unveiling Technology Acquisition and Deployment Decisions for Technological Innovation: An Exploratory Study in Indian Power Distribution Firms", International Journal of Innovation and Technology Management, vol.11, no.06, pp.1450041, 2014.
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References

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