The Influence of Logistics Technology Innovation on the Efficiency of Operations in Small and Medium-Sized Businesses in Thailand
Abstract
Logistics technology innovation include technology for moving materials and products, such as robotics and automated logistics systems; technology used to transmit information that enables real-time data exchange to optimize material movement; and technology to assist in decision-making as artificial intelligence enhances decision-making. These technologies include the use of digital transformation, automation, and enhanced decision-making tools to increase the efficiency of supply chain operations. This study aimed to examine how environmental factors (legal regulations, market competition, and stakeholder involvement) influence the operational efficiency of small and medium-sized enterprises in Thailand, with logistics technology innovation serving as a mediating factor, and to propose strategic guidelines for improving business performance through innovation. Data were collected from 400 small and medium-sized businesses in the Eastern Special Development Zone which are Chachoengsao, Chonburi, and Rayong provinces. A purposive sampling method was used to select enterprises in logistics-related industries, followed by convenience sampling for survey distribution. The investigation was carried out utilizing structural equation modeling. The findings revealed that environmental variables have a considerable impact on operational efficiency, with logistics technology innovation serving as a mediating variable. The direct effect of environmental factors on innovation technology was strong (β = 0.73), while innovation technology had a significant positive effect on operational efficiency (β = 0.37). Product movement technologies, including robots and automated vehicles, had the greatest influence (β = 0.62), followed by digital data transmission technologies (β = 0.34) and decision support systems (β = 0.06). These results imply that small and medium-sized businesses should emphasize logistics automation, artificial intelligence-driven decision-making, and digital data sharing platforms to increase efficiency. This study offers important insights for corporate executives and politicians in creating a favorable climate.
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Journal of Applied Data Sciences
ISSN | : | 2723-6471 (Online) |
Organized by | : | Computer Science and Systems Information Technology, King Abdulaziz University, Kingdom of Saudi Arabia. |
Website | : | http://bright-journal.org/JADS |
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