The Acceptance of Human Resource Information System (HRIS) Usage for Small and Medium-sized Enterprises (SMEs) in Bangkok and Surrounding Area
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This research aimed to: 1) investigate the levels of opinion on factors influencing technology acceptance, 2) analyze the relationships between these acceptance variables, and 3) test the goodness-of-fit of a causal relationship model for the adoption of Human Resource Information Systems (HRIS) in Bangkok and its surrounding areas. A mixed methods approach, combining quantitative and qualitative methodologies, was employed. For the quantitative component, a survey was administered to a sample of 500 entrepreneurs from Small and Medium-sized Enterprises (SMEs) via online questionnaires. The collected data were analyzed using descriptive statistics and Structural Equation Modeling (SEM) with AMOS software. For the qualitative component, semi-structured, in-depth interviews were conducted with 30 key informants. The findings revealed that the sample group held a highly positive opinion regarding the use of ready-made software. The factors with the most significant weights were effectiveness (0.935), perceived ease of use (0.945), intention to use (0.935), and usage behavior (0.935). Users perceived that the system helped reduce costs, save time, minimize errors, and enhance decision-making accuracy, while also effectively supporting future analysis and planning. Furthermore, the model's fit with the empirical data was deemed acceptable across all measured indices (CMIN/df = 1.977, CFI = .984, NFI = .968, TLI = .982, RMSEA = .044). Hypothesis testing confirmed that all proposed hypotheses were supported, indicating the model's suitability in explaining the acceptance behavior of HRIS within the context of SMEs in the studied region. These findings contribute to the HRIS adoption literature by providing an empirically validated model that integrates system effectiveness with traditional technology acceptance factors, specifically tailored to the unique operational context of SMEs in an emerging urban economy.
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