Open AccessStrengthening institutions theory on modification of technology acceptance model: A study of financial information system for local government
Author(s) -
Fauzi Fauzi,
Citrawati Jatiningrum
Publication year - 2021
Publication title -
journal of socioeconomics and development
Language(s) - English
Resource type - Journals
ISSN - 2615-6075
DOI - 10.31328/jsed.v4i1.2254
Subject(s) - incentive , technology acceptance model , government (linguistics) , affect (linguistics) , quality (philosophy) , sample (material) , motivation theory , reinforcement , theory of planned behavior , business , local government , institutional theory , usability , knowledge management , public economics , psychology , computer science , economics , microeconomics , management , social psychology , political science , public administration , human–computer interaction , linguistics , philosophy , chemistry , control (management) , communication , epistemology , chromatography
The financial information system for local Government or SIPKD regulation in Indonesia are mandatory. There have been several innovations on it, but in practice mostly they were not effective in term of user acceptance due to several obstacles. This study investigates the modified Technology Acceptance Model (TAM) theory proposed with the institutional strengthening theory on the user performance of SIPKD. Supported by the sample of 556 SIPKD users from the Lampung Provincial Government, the results showed that all constructs are associated in accordance with the theory and concept of TAM. The quality of training had a dominant effect on the ease of use and usefulness. Related to the reinforcement theory, the results showed that facilitating conditions and incentives affect the performance of SIPKD users. Meanwhile, institutional pressure did not show its role to improve the performance of users. The main findings revealed that the TAM model becomes more perfect when imbued with the reinforcement theory. These results suggest that information system acceptance is higher when reinforcement theory is able to manipulate the cognitive of users to further improve their individual performance.JEL Classification E60; H83; M48