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Work-related generative artificial intelligence adoption and employee-perceived organisational performance in Thailand's manufacturing industry
(2026-10-01)
Yudhistyra, Wecka Imam
;
Srinuan, Chalita
Generative Artificial Intelligence (GenAI) is increasingly integrated into organisational work processes, yet its implications for manufacturing firms cannot be inferred from adoption intention or usage frequency alone. In contrast to deterministic workplace technologies, GenAI produces probabilistic and context-responsive outputs whose organisational value depends on employees' ability to evaluate, interpret, and apply generated content effectively. This research examines how work-related GenAI use is associated with employee perceptions of GenAI-enabled organisational performance in Thailand's manufacturing sector. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, the Human-Centred Design paradigm, and Knowledge Management theory, the research develops a framework in which perceived usability, knowledge acquisition, knowledge application, and performance expectancy influence behavioural intention, which subsequently affects use behaviour and employee-perceived GenAI-enabled organisational performance. Survey data from 381 manufacturing employees with prior GenAI experience were analysed using Partial Least Squares Structural Equation Modelling. Bayesian Network (BN) algorithms were subsequently employed to refine the theoretical structure by identifying conditional dependencies beyond the hypothesised model, while Artificial Neural Networks and Importance-Performance Map Analysis provided complementary predictive and managerial insights. The results support all hypothesised relationships. The BN-refined model further identifies direct links between knowledge application, performance expectancy, and organisational performance, suggesting that, in addition to adoption and use, GenAI-derived value also depends on employees' capacity to translate AI-generated knowledge into workplace outcomes. The findings advance technology adoption research by developing and validating a GenAI-specific extension of the UTAUT that integrates human-centred design and knowledge management perspectives. The research further demonstrates that organisational value is realised through a sequential pathway linking adoption antecedents, behavioural intention, and use behaviour, while providing policy-relevant evidence on workforce-driven AI adoption in an emerging economy undergoing digital transformation.
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University lecturers’ perceptions on digital transformation and knowledge management for teaching innovation
(2026-01-01)
Songkram, Noawanit
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Shidiq, Galih Albarra
;
Winarto
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Taweejamsup, Suphasit
;
Songkram, Nutthakorn
This study used the qualitative design to investigate the perceptions of 33 university lecturers through semi-structured interviews and observations conducted after a professional development program in Indonesia. Thematic analysis discovered three interconnected dimensions shaping innovation in teaching: (1) supportive institutional environments that promote responsible behaviour, teamwork, and collaboration; (2) acquisition and application of new knowledge through digital tools and collegial learning; and (3) integration of technological innovation to improve teaching efficiency, creativity, and multidisciplinary engagement. The findings indicate that effective knowledge management enhances lecturers’ ability to adapt digital pedagogies, share expertise, and sustain innovation practices. The implications of this study include developing professional learning communities, improving digital literacy programs, and aligning institutional policies to support innovation in teaching. These insights extend global understanding of how universities in emerging contexts can strategically integrate technology and knowledge management to advance educational innovation.
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Adoption of industry-oriented enterprise resource planning systems: A rigorous empirical research in the mining industry leveraging PLS-SEM and artificial neural networks models
(2025-12-01)
Yudhistyra, Wecka Imam
;
Srinuan, Chalita
Enhancing operational efficiency and enabling digital transformation in the mining industry can be effectively pursued through the implementation of Enterprise Resource Planning (ERP) systems. However, there remains a significant lack of empirical research to guide successful ERP adoption within the underexplored mining sector in developing countries, contexts often characterized by harsh operational conditions, cultural resistance to change, and limited innovation. This research aims to raise awareness and facilitate effective ERP adoption by identifying, analyzing, and critically assessing the key determinants influencing ERP system uptake in the mining industry. Data were collected from 278 employees across mining organizations in Indonesia and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), complemented by Artificial Neural Network (ANN) models to improve predictive accuracy and uncover both linear and non-linear relationships. The empirical findings reveal that employee perceptions, attitudes, and organizational factors significantly shape ERP adoption behaviors. Notably, organizational size emerged as the most influential predictor, surpassing even employee attitudes and perceptions, highlighting that institutional readiness could play a more decisive role than individual user disposition. This research contributes to academic literature by offering a data-driven framework tailored to the mining industry's operational and cultural dynamics in developing economies. Moreover, it provides actionable insights for policymakers, IT leaders, and practitioners seeking to design effective technology adoption strategies that support sustainable digital transformation through ERP integration.
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Factors Influencing Shoppers’ Behavioral Intention to Purchase Smart Phones: Digital Transformation Through YouTube User Generated Content
(2022-01-01)
Thirakulwanich, Anuphat
;
Sawmong, Sudaporn
This study explored the factors that influence shoppers’ behavioral intention to purchase smartphones based on User Generated Content on the YouTube platform. The study was underpinned by two critical theories which include; Extended Technology Acceptance Model (TAM) and Source Credibility Theory to understand how UGC on YouTube was applicable in influencing purchase decisions. The independent variables were UGC, perceived credibility, and perceived usefulness. The study adopted a quantitative descriptive survey research design. A questionnaire was used to collect data from a sample size of 442 YouTube users in Thailand and the data were analyzed using SEM. The findings revealed that user-generated content on YouTube has a positive effect on perceived credibility, perceived usefulness, and behavioral intention to purchase smartphones. It also showed that perceived usefulness and perceived credibility have a positive effect on behavioral intention to purchase smartphones. Ultimately, the study also found that UGC on YouTube has an indirect and significant effect on behavioral intention to purchase smartphones mediated for both perceived usefulness and perceived credibility. The study recommends that future studies should consider different social media platforms where UGC are available to test for consistency, and also incorporate a mixed method of research involving qualitative data that will allow respondents to provide clarifications for their decisions. A few imitations of the study could be highlighted. The first limitation is within the scope of the study, from the fact that the study’s focus was on one social media channel – YouTube. The study focused more on the user-generated content on YouTube and added two more variables (perceived credibility and perceived usefulness).
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Circular Economy of Steel Recycling Companies in Thailand
(2021-11-01)
Taghipour, Amirhossein
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Akkalatham, Wareerath
The new “circular economy” model would revolutionize the economy. It should also be noted that several business models will be needed to optimize their efficiency and overlap as the system evolves over its lifetime. The business model of the circular economy is based on the principle of “value creation” of the conventional economy. In this study, we interviewed 67 managers from the steel industry in Thailand. Statistically, 71.2% of respondents felt that steel consumers would be able to pay a higher price for clean goods. Also, 87% believe that governments must contribute to the development of the circular economy. They said that their group also organizes training activities for educating the workforce. Moreover, 80.1% indicated that their organization must inform management and workers of the value of the circular economy. Accordingly, 64.7% of respondents stated that there is no government funding for scrap metal recycling. Overall, 36.3% of people felt there was a shortage of scrap metal work.
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Digital transformation SCM in view of Covid-19 from Thailand SMEs perspective
(2021-01-01)
Khalid, Bilal
;
Naumova, Elena
Digital transformation involves the use of digital technologies to reorganize the operational processes and make them more effective and efficient. The article covers the problem of digital transformation of supply chain management (SCM) due to the changing business environment, and the desire to meet the customers' demand. The authors prove that the supply chain management processes are altered, such as reduction of product design and a manufacturing period, faster delivery of products to customers, easily meeting the preferences and demands of customers and faster and effective decision-making supported by big data and analytical decision techniques. In Thailand, digital transformation has been considered critical, particularly with the SMEs, which account for a significant proportion of the country's GDP. Some of the techniques that should be involved in the digitalization process include adoption of a learning culture, roadmap to development, creation of awareness, collaboration and support. In the wake of COVID-19, digital transformation has proved more essential through e-commerce and online transactions. Within this COVID-19 pandemic period and in future, the software and applications that could be used by SMEs in their process of digitalization include 3D-printers, Computer Aided Manufacturing (CAM), Computer Aided Design (CAD), Product Lifecycle Management (PLC), Customer Relationship Management programs, Virtual Assistance, Artificial Intelligence, Total Quality Management (TQM), Just in Time (JIT), Just in Time (JIT), Lean Manufacturing (LM) among others. Some of the initiatives that could be implemented by the government include developing legal and regulatory framework of SMEs, supporting digitalization of SCM.

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