Agricultural specialists' intention toward precision agriculture technologies: Integrating innovation characteristics to technology acceptance model

Environmental technology is a major determinant for paradigm shift in agriculture and environmental improvement. Precision agriculture technologies are designed to provide extensive information and data to assist farmers when making site-specific management decisions. The paper aims to investigate intention and attitude toward adoption of precision agriculture technologies among agricultural specialists in Iran. A survey using stratified random sampling was used to collect data. Structural equation modeling using LISREL software was used to analyze data. The results showed that observability, triability and attitude to use positively affect intention to adoption of precision agriculture technologies. Attitude to use is the most important determinant of intention. Also, perceived ease of use and perceived usefulness indirectly influence the intention to adoption through attitude to use.

[1]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .

[2]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[3]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[4]  Robert D. Grisso,et al.  Precision Farming. A Comprehensive Approach , 2005 .

[5]  Fred D. Davis.  A technology acceptance model for empirically testing new end-user information systems : theory and results , 1985 .

[6]  Jin-Sung Kim,et al.  Exploring the user interface of negotiation support systems from the user acceptance perspective , 2007, Comput. Hum. Behav..

[7]  Mun Y. Yi,et al.  Understanding information technology acceptance by individual professionals: Toward an integrative view , 2006, Inf. Manag..

[8]  A. Adrian,et al.  Producers' perceptions and attitudes toward precision agriculture technologies , 2005 .

[9]  Detmar W. Straub,et al.  Structural Equation Modeling and Regression: Guidelines for Research Practice , 2000, Commun. Assoc. Inf. Syst..

[10]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[11]  Naveen Donthu,et al.  Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics , 2006 .

[12]  Roger J. Calantone,et al.  International Technology Adoption , 1994 .

[13]  J. Lowenberg-DeBoer,et al.  Risk Management Potential of Precision Farming Technologies , 1999, Journal of Agricultural and Applied Economics.

[14]  Jen-Her Wu,et al.  What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model , 2005, Inf. Manag..

[15]  J. Gibson,et al.  Conceptualizing Sustainable Agriculture: Iran as an Illustrative Case , 2005 .

[16]  Marios Koufaris,et al.  Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior , 2002, Inf. Syst. Res..

[17]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[18]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[19]  Karl G. Jöreskog,et al.  Lisrel 8: Structural Equation Modeling With the Simplis Command Language , 1993 .

[20]  James A. Larson,et al.  Precision Farming by Cotton Producers in Twelve Southern States: Results from the 2009 Southern Cotton Precision Farming Survey , 2006 .

[21]  Ewald Schnug,et al.  Temporal Erosion-Induced Soil Degradation and Yield Loss , 2001 .

[22]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[23]  I. Ajzen.  The theory of planned behavior , 1991 .

[24]  Cheng-Kiang Farn,et al.  Acceptance of electronic tax filing: A study of taxpayer intentions , 2006, Inf. Manag..