Adoption of Industry 4.0 technologies by organizations: a maturity levels perspective

Determinants of Generative AI System Adoption and Usage Behavior in Korean Companies: Applying the UTAUT Model

This study addresses the academic gap in the adoption of generative AI systems by investigating the factors influencing technology acceptance and usage behavior in Korean firms. Although recent advancements in AI are accelerating digital transformation and innovation, empirical research on the adoption of these systems remains scarce. To fill this gap, this study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) model, surveying 300 employees from both large and small enterprises in South Korea. The findings reveal that effort expectancy and social influence significantly influence employees' behavioral intention to use generative AI systems. Specifically, effort expectancy plays a critical role in the early stages of adoption, while social influence, including support from supervisors and peers, strongly drives the adoption process. In contrast, performance expectancy and facilitating conditions show no significant impact. The study also highlights the differential effects of age and work experience on behavioral intention and usage behavior. For older employees, social support is a key factor in technology acceptance, whereas employees with more experience exhibit a more positive attitude toward adopting new technologies. Conversely, facilitating conditions are more critical for younger employees. This study contributes to the understanding of the interaction between various factors in AI technology adoption and offers strategic insights for the successful implementation of AI systems in Korean companies.

Construction 4.0 technology evaluation using fuzzy TOPSIS: comparison between sustainability and resiliency, well-being, productivity, safety, and integrity

This study aims to compare the impact of Construction 4.0 technologies on different organizational core values, focusing on sustainability and resiliency, well-being, productivity, safety, and integrity. To achieve that aim, the study objectives are the following: (i) identify the critical Construction 4.0 technologies between core values; (ii) appraise overlapping critical Construction 4.0 technologies between core values; (iii) examine the ranking performance of Construction 4.0 technologies between core values; and (iv) analyze the interrelationships between Construction 4.0 technologies and core values. First, twelve Construction 4.0 technologies were identified from a national strategic plan. Then, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) that incorporates subjective and objective weights was used to evaluate the impact of the Construction 4.0 technologies on the five core values. Finally, the collected data was analyzed using the following techniques: fuzzy TOPSIS, normalization, overlap analysis, agreement analysis, sensitivity analysis, ranking comparison, and Spearman correlation. The study findings reveal four critical Construction 4.0 technologies that enhance all five core values: building information modeling (BIM), Internet of Things (IoT), big data and predictive analytics, and autonomous construction. Also, there is a high agreement on the Construction 4.0 technologies that enhance well-being and productivity. Lastly, artificial intelligence (AI) has the highest number of very strong relationships among the core values. The originality of this paper lies in its comprehensive comparison of the impact of Construction 4.0 technologies on multiple organizational core values. The study findings provide valuable insights in making strategic decisions in adopting Construction 4.0 technologies.

mHealth Technology Experiences of Middle-Aged and Older Individuals With Visual Impairments: Cross-Sectional Interview Study

BACKGROUND

Current mobile health (mHealth) technology is predominantly designed with a visual orientation, often resulting in user interfaces that are inaccessible to visually impaired users. While mHealth technology offers potential for facilitating chronic illness management and enhancing health behaviors among visually impaired older populations, understanding its usage remains limited.

OBJECTIVE

This qualitative research aimed to explore the mHealth technology experiences of middle-aged and older individuals with visual impairments including the accessibility and usability issues they faced.

METHODS

The qualitative exploration was structured using the mHealth for Older Users framework. Cross-sectional interviews were conducted via Zoom between June 1 and July 31, 2023, using an interview protocol for data collection. A thematic analysis approach was employed to analyze the transcribed interview scripts.

RESULTS

Of the 7 participants who took part in the Zoom interviews, 3 were men and 4 were women, with ages ranging from 53 to 70 years. Most participants adopted mHealth apps and wearable devices for promoting health. They exhibited 3 distinct adoption patterns. Seven themes were emerged from the perceived challenges in using mHealth technologies: (1) a scarcity of accessible user manuals, (2) user interfaces that are not visually impaired-friendly, (3) health data visualizations that are not accessible, (4) unintuitive arrangement of app content, (5) health information that is challenging to comprehend, (6) cognitive overload caused by an excess of audible information, and (7) skepticism regarding the accuracy of health records. mHealth technologies seem to positively affect the health and health management of participants.

CONCLUSIONS

Design considerations for mHealth technologies should consider individuals' disabilities and chronic conditions and should emphasize the importance of providing accessible manuals and training opportunities when introducing new mHealth solutions.