Abstract
GIS is often used in companies where employees already use enterprise information systems/enterprise resource planning (ERP) systems and where both systems are used simultaneously. This article is a research study of GIS acceptance by users using GIS, not as a stand-alone tool, but as an integrated tool into the ERP system. The research was conducted using the Technology Acceptance Model (TAM), one of the most often used research models for researching behavioral intention and actual use of information systems. For this research study, TAM has been modified and extended with external factors. The main research objective is to identify determinants of GIS acceptance and the attitude of individuals toward using GIS integrated with ERP systems. The structural equation model with partial least squares (PLS) method was used to analyze collected survey data. The study researched 12 external factors in the TAM model, out of which 10 were found significant. The most important factors that impact behavioral intention to use ERP-GIS systems are perceived usefulness of ERP-GIS systems and attitude toward using GIS, followed by education and training about ERP-GIS systems and perceived enjoyment using ERP-GIS systems.
Highlights
Geographic information systems (GIS) have become very important tools in many areas in recent years, including resource management and utilization in many industries [1]
When researching acceptance of GIS using Technology Acceptance Model (TAM), we found that there are studies that report about the adoption of GIS by users, they do not relate to GIS integration with enterprise resource planning (ERP) systems, but merely to the acceptance of GIS as such
The Partial Least Squares Structural Equation Modeling (PLS-SEM) method has become interesting among researchers
Summary
Geographic information systems (GIS) have become very important tools in many areas in recent years, including resource management and utilization in many industries [1]. GISs are sometimes referred to as computer tools, but sometimes they are defined as information systems consisting of software and database [2]. Raster data can be distinguished by the content—, i.e., imagery, height models, land use classes, population data, temperature, etc. Vector data ( referred to as feature data) represent individual objects that are modeled as geometries of a certain location and depend on the geometric dimension of the objects modeled [4]. Their functionality to capture, analyze, visualize, and model territories with large volumes of spatial data open many possibilities for their use in different areas. Besides environmental issues (e.g., weather forecasting climatic change [5], flood modeling [6]), there are several areas of economic issues (e.g., cost–distance analysis and optimal routes, location–allocation analysis, land suitability modeling, etc.) (for example [7,8,9,10])
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