Relationship Determinants between AI Technology Adoption Behavior and Performance of Software Enterprises
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Abstract
With the continuous progress of science and technology, the arrival of artificial intelligence subverts the traditional industries. Enterprises urgently need to carry out technological innovation to reduce costs. The introduction of artificial intelligence technology can reduce workload and improve development efficiency for software enterprises. Reduce operating costs. This paper takes the software enterprise as the research object, takes the artificial intelligence as the independent variable and the software development cost as the dependent variable. The hypothesis is proposed through the four intermediate variables of development efficiency, management innovation, product quality, labor force and the degree of introduction of artificial intelligence. A total of 332 valid questionnaires were collected by using electronic questionnaires. The sample data are analyzed by Smartpls 3.0 software, and the data are analyzed by Algorithm, Bootstrapping, cross multiplication, structural equation and other methods. The results show that AI has a significant positive impact on software development cost, a significant positive impact on product quality, a significant positive impact on labor force, a significant positive impact on development efficiency, a significant positive impact on management innovation, and a significant positive impact on software development cost. Labor has a significant positive impact on software development costs. Development efficiency has a significant positive impact on software development cost. Management innovation has a significant positive impact on software development cost. Product quality plays an intermediary role between the introduction of artificial intelligence and the cost of software development. Development efficiency also plays an intermediary role between the introduction of artificial intelligence and the cost of software development. From the research, we know that the introduction of AI can enrich the theories of process reengineering, process optimization and management decision-making, and can also find the factors that affect output performance from the perspective of technological innovation to provide reference for future research.
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