Development And Psychological For Digital Transformation In The Service Industry And Its Impact On Information Technology Management

Abstract

This study delves into the connections among latent variables: Information Indicator, Digital Literacy, Groups of Digital Systems, and Digital Infrastructure, and their influence on the dependent variable, "Digital Technology." To scrutinize the strength and direction of these associations, we employed a structural equation model, employing standardized regression coefficients (βi). We also examined intercepts (bi) to ascertain the expected value of "Digital Technology" when all independent latent variables are set to zero. The findings indicate that a one-standard-deviation increase in the Information Indicator corresponds to a 0.59 standard deviation increase in "Digital Technology." Similar interpretations apply to the other latent variables. The presence of Digital Literacy, effective Grouping of Digital Systems, and robust Digital Infrastructure have a positive impact on the adoption and implementation of digital technology in the service industry.

Additionally, we assessed the goodness-of-fit statistics of the model. The relative chi-square (χ²) value of 0.621 suggests that approximately 62.10% of the variance in "Digital Technology" can be accounted for by the combination of the latent variables. This R-squared value indicates a moderate to strong effect size, underscoring the substantial contribution of these latent variables to explaining "Digital Technology" adoption. However, the p-value for model fit stands at 0.733, which is relatively high, implying that the model's fit may not reach statistical significance at the commonly used significance level (α = 0.05). Nonetheless, it's essential to note that the p-value alone should not be the sole determinant of the model's validity. A comprehensive evaluation necessitates a thorough examination of other goodness-of-fit metrics.