Exploring factors influencing technology adoption rate at the macro level: A predictive model

2021 ◽  
pp. 101826
Author(s):  
D. Hooks ◽  
Z. Davis ◽  
V. Agrawal ◽  
Z. Li
Author(s):  
Nurul Huda ◽  
Budi Suharjo ◽  
Ani Suryani

Although Indonesia has the largest rubber plantation in the world, the productivity is still very low. About 85% of the plantation belongs to the majority of farmers whose adoption level of cultivation technology is still low. This study aimed to determine the internal and external characteristics that greatly affect the level of farmers' adoption of technology in rubber cultivation to come up with the formulation of development strategy in the management of rubber plantation in Teweh Tengah Sub-district, Barito Utara regency. Processing and data analysis was done by analysis of descriptive and inferential statistics using the percentage distribution tables, Chi-square statistical analysis, correspondence analysis and logit analysis. Descriptively, the technology adoption rate of rubber farmers was categorized as 54% low, 40% moderate and 6% high. A Chi-Square test showed a correlation between the level of adoption by gender, age, course/training, Information Seeking activities of cultivation technology, Extension Support, Farmer Group Support, and Government support. The analysis result of Logit Method of Stepwise showed that there were two characteristics of internal and external variables that influenced the adoption rate of rubber cultivation technology: Support of Farmer Groups and Activities of Seeking for Cultivation Technology Information. A strategy for the development of rubber plantation Management should be based on growth, strengthening and development of farmer groups. The support of farmer groups can foster the process of increasing the information and skills for farmers. Development strategy included establishment and institutional development. improvement and development of information for farmer groups.Key words: Logit Regression, Rubber Plantation, Technology Adoption, farmer group


Author(s):  
Saeed Alzahrani ◽  
Tugrul U. Daim

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.


Author(s):  
Jeanne C. Samuel

This article proposes a hypothetical model for determining rate of diffusion of an innovation in a system. The model modifies Everett Rogers’ S-curve using an index created from Gartner’s hype cycle phases. Rogers’ model for technology innovation adoption demonstrates that cumulative technology diffusion in a system from zero through the late majority adopters’ phase forms a curve resembling the letter “S”. Hype cycles analyze the five emotional stages technology adopters go through from over-enthusiasm (hype) though disappointment until it plateaus (beginning of mainstream adoption). When numbers assigned to the phases of adoption from the hype cycle are used as multipliers and applied to the cumulative adoption data of an innovation (Rogers’ S-curve), the “S” becomes a “J”. With the J-curve you can determine the rate of innovation diffusion in an organization.


2013 ◽  
Vol 137 (12) ◽  
pp. 1723-1732 ◽  
Author(s):  
Stanley J. Robboy ◽  
Sally Weintraub ◽  
Andrew E. Horvath ◽  
Bradden W. Jensen ◽  
C. Bruce Alexander ◽  
...  

1989 ◽  
Vol 15 (6) ◽  
pp. 687-697 ◽  
Author(s):  
Jeffrey A. Miller ◽  
Gary S. Cohen ◽  
Raphael Warshaw ◽  
John C. Thornton ◽  
Kaye H. Kilburn

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