A Simulation Framework for Technology Adoption Decision Making in Construction Management: A Composite Model

2019 ◽  
Author(s):  
Chukwuma Nnaji ◽  
Ifeanyi Okpala ◽  
Sungjin Kim
Keyword(s):  
Decision Making ◽  
Technology Adoption ◽  
Construction Management ◽  
Composite Model ◽  
Simulation Framework ◽  
Adoption Decision

Development and Application of Safety Technology Adoption Decision-Making Tool

2020 ◽  
Vol 146 (4) ◽  
pp. 04020028 ◽  
Author(s):  
Chukwuma Nnaji ◽  
John Gambatese ◽  
Ali Karakhan ◽  
Robert Osei-Kyei
Keyword(s):  
Decision Making ◽  
Technology Adoption ◽  
Adoption Decision ◽  
Safety Technology ◽  
Decision Making Tool

Digital technology utilisation decisions for facilitating the implementation of Industry 4.0 technologies

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Samad M.E. Sepasgozar
Keyword(s):  
Decision Making ◽  
Technology Adoption ◽  
Construction Industry ◽  
Industry 4.0 ◽  
Active Role ◽  
Final Decision ◽  
Content Type ◽  
Adoption Decision ◽  
Construction Companies ◽  
Multi Stage

Purpose Emerging Construction Industry 4.0 technologies raise serious questions for construction companies when deciding whether to adopt or reject emerging technologies. Vendors seek to understand what factors are involved in how construction companies make these decisions and how they might vary across different companies. This paper aims to present a systematic, technology adoption decision-making framework for the construction industry which includes the key steps required for the final decision being made by companies up to the commencement of the operation of the technology. Design/methodology/approach A total of 123 experienced practitioners were interviewed to identify a broad range of tasks relevant to decision-making. Participants known as customers or vendors were chosen to validate the findings of each group by using data triangulation methods. A systematic thematic analysis method was applied in the NVivo environment to analyse the data. Findings This study identifies the active role of vendors who need to understand how their customers arrive at decisions to increase the rate of technology adoption. This paper also provides insights to new companies and late adopters (reported greater than 50%) about how others arrived at their decisions. Originality/value Unlike other technology adoption models, this paper investigates vendors’ corresponding interactions during the decision-making process. This paper also goes beyond previous studies, which focussed on the individual customer’s intention to use a specific technology at a single-stage by developing a multi-stage framework to enable understanding the details of the decision process at the organisational level.

Construction of a technology adoption decision-making model and its extension to understanding herd behavior

2015 ◽  
Vol 89 ◽  
pp. 471-486 ◽  
Author(s):  
Jing Gu ◽  
Lu Li ◽  
Zeshui Xu ◽  
Hamido Fujita
Keyword(s):  
Decision Making ◽  
Technology Adoption ◽  
Herd Behavior ◽  
Adoption Decision ◽  
Decision Making Model

scholarly journals A Study of Quality Indicator Model of Large-Scale Open Source Software Projects for Adoption Decision-making

2020 ◽  
Vol 176 ◽  
pp. 3665-3672
Author(s):  
Shinji Akatsu ◽  
Ayako Masuda ◽  
Tsuyoshi Shida ◽  
Kazuhiko Tsuda
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Quality Indicator ◽  
Large Scale ◽  
Software Projects ◽  
Adoption Decision ◽  
Indicator Model

scholarly journals Empirical examination of decision making core technology adoption theory to explain youth preferences for HIV preventive actions

2014 ◽  
Author(s):  
◽  
Njabulo Samson Melusi Shongwe
Keyword(s):  
Decision Making ◽  
Information System ◽  
Technology Adoption ◽  
Predictive Power ◽  
Core Model ◽  
Adoption Theory ◽  
Preventive Actions ◽  
Core Technology ◽  
The Relationship ◽  
Action Intention

This study reports on the application of decision making core technology adoption theory to empirically examine youth preferences for Human Immunodeficiency Virus (HIV) preventive actions. In order to contribute to the open discourse on whether technology adoption rate is higher for male or female, goal desire, goal intention, action desire and action intention elements of decision making core theory were tested. A mobile health information system was implemented as an HIV information disseminating tool and used for experimentation to determine adoption by youths. A dataset of 118 pupils from two high schools was used for pilot investigation. A dataset of 292 undergraduate youths aged 10-24 years from two universities in South Africa was generated to validate the research model. The Partial Least Square (PLS) analytic modelling technique was used to determine the predictive power of decision making core model from the input dataset. Results of experimentation show that regardless of the gender youth accepts to use mobile information system to access HIV information. The predictive power of the decision making core model was found to be independent of gender factor, which was also not found to moderate the relationship between Perceived Behavioural Control (PBC) and action intention. In addition, gender was not found to moderate the order of importance in factors that predict youth preferences for HIV preventive action. PBC, action desire and goal desire were selected as the most important predictors of HIV preventive actions. The factor of action desire was found to mediate the relationship between PBC and action intention such that the mediation effect was stronger for male youth (68%) than for female youth (19%). Finally, the decision making core model better predicted youth preferences for HIV preventive actions as compared to two models based on Theory of Reason Action (TRA) and Theory of Planned Behaviour (TPB)

Managing conflicting issues: a decision‐making tool for technology adoption by VSEs

2001 ◽  
Vol 20 (10) ◽  
pp. 830-841 ◽  
Author(s):  
Toby Harfield ◽  
Phil Driver ◽  
C.P. Beukman
Keyword(s):  
Decision Making ◽  
Technology Adoption ◽  
Decision Making Tool

Technology Adoption

2021 ◽  
pp. 96-119
Author(s):  
Saeed Alzahrani ◽  
Tugrul U. Daim
Keyword(s):  
Technology Adoption ◽  
Influencing Factors ◽  
Consumer Attitudes ◽  
Adoption Decision ◽  
Intention To Adopt ◽  
Factors Influencing ◽  
Depth Analysis ◽  
Hierarchical Decision ◽  
New Form ◽  
Hierarchical Decision Model

Cryptocurrency has emerged in recent years as a new form of money. With the wave of cryptocurrency developments and wild attention, it is essential to understand consumer attitudes toward the adoption of the cryptocurrency and the factors influencing their decisions. Thus, the chapter aims to fill a gap in the current literature by examining the factors that influence the user's intention to adopt cryptocurrency. This adoption is a purchasing decision where users make a decision based on a set of factors that matters to them. This chapter uses a hierarchical decision model (HDM) to understand the user decision to adopt cryptocurrency. The model proposes four main perspectives that influence the adoption decision: economic, technical, social, and personal. This study aims at providing an in-depth analysis of the factors influencing the adoption of cryptocurrency as well as the ranking of these influencing factors based on the quantification of the users' judgments.

Sign in / Sign up

Export Citation Format

Share Document