scholarly journals A Pro-Environmental Reasoned Action Model for Measuring Citizens’ Intentions regarding Ecolabel Product Usage

2016 ◽  
Vol 8 (11) ◽  
pp. 1165 ◽  
Author(s):  
Reny Nadlifatin ◽  
Shu-Chiang Lin ◽  
Yulia Rachmaniati ◽  
Satria Persada ◽  
Mohammad Razif
Author(s):  
James Jaccard

The reasoned action model (RAM) of Fishbein and Ajzen has been highly influential in the social and health sciences. This article describes three areas for future research that should expand its explanatory power. One area of research focuses on an idiographic RAM that encourages researchers to pursue the estimation of RAM parameters on a per-individual level rather than through traditional nomothetic modeling. The second area encourages scientists to develop a split-second RAM, that is, a RAM that can provide perspectives on the split-second decisions people make in everyday life. Integration of the RAM with models of working (short-term) memory is stressed. The third area for research encourages scientists to develop a multioption RAM that incorporates and is responsive to the choices that people make when confronted with multiple alternatives. This perspective stresses the need to apply the RAM to the full range of behavioral options that are available to people as they contemplate performing one behavior versus another. Perspectives for theoretical advancement in each area are developed.


Author(s):  
Maria Teresa Martín ◽  
Maria Victoria Román ◽  
Manuel Recio

During the last few decades, various theoretical developments have been carried out with a view to describing the characteristic and distinct behavioral process that lies under any adoption of technological services and products. These developments are based mainly on the Social Psychology approach. There are three extensive theories within the field of Social Psychology whose ultimate purpose has been to define the internal psychological factors that explain human behavior: the expectancy-value theory, the cognitive dissonance theory, and the self-perception theory. While the expectancy-value theory has been widely used in the research of adoption and usage of information systems, the other two theories have been less recognized. Of all expectancy-value theory models, we should draw our attention to the reasoned action model (Azjen & Fishbein, 1980), because it underlies many of the studies on usage of technology. The planned behavior model (Azjen, 1985, 1991) represents a reformulation of the reasoned action model, justified by the existence of conducts that, albeit in part, a person cannot voluntarily keep under control. A rough description of both models is presented in this chapter, inasmuch as they served as a basis for the construction of the technology acceptance model (Davis, 1989; Davis, Bagozzi & Warshaw, 1989), known as one of the main models for the technology readiness concept. The technology acceptance model seems to possess a similar or even better explicating power than its predecessors (Davis et al., 1989; Mathieson, 1991; Taylor & Todd, 1995a; Chau & Hu, 2002).


Author(s):  
Christopher L. Thomas ◽  
Kristie Allen

The current study was designed to investigate the influence of COVID-19-related worry and online learning attitudes on enrollment behavior using the Reasoned Action Model. Participants (N = 246) completed measures of other-focused COVID-19 worry, self-focused COVID-19 worry, attitudes, perceived normative pressure, perceived behavioral control, and behavioral intention during the Spring and Summer 2020 academic semesters. Additionally, participants allowed us access to their university records to determine their enrollment status during the Fall 2020 semester. Mediation analysis results indicated the relationship between other-focused COVID-19 worry and enrollment intention was mediated by both perceived normative pressure and perceived behavioral control. Further, behavioral intention was found to share a positive relationship with enrollment behavior. Our discussion focuses on how the findings of the current research can be used to enhance student enrollment and retention.


2008 ◽  
Vol 11 (3) ◽  
pp. A167
Author(s):  
R Khanna ◽  
V Scott ◽  
J Kavookjian ◽  
KM Kamal ◽  
LA Miller ◽  
...  

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