This study aims to: (1) analyze the need for digital marketing capabilities in Thai MSME; (2) develop an online digital marketing course; and (3) enhance Thai MSME’s digital marketing capabilities, particularly in Thailand’s manufacturing sectors. The survey was conducted using questionnaires distributed to a sample group of 400 digital marketing staff, executives, or business owners, complemented by in-depth interviews with marketing experts, business managers, and owners, totaling 10 participants. The research findings reveal a significant demand for digital marketing skills among MSME entrepreneurs in the manufacturing sector. The top three skills identified as most crucial for enhancement are: (1) communication and marketing information presentation skills; (2) brand building and public relations; and (3) video marketing execution. The study further revealed that the design of the digital marketing course, along with the developed online learning platform, attracted and successfully enrolled 104 MSMEs who participated in the online program. The pre- and post-training assessment results demonstrated a statistically significant difference in test scores, with a mean post-training score of 16.10 ( Mean = 16.10, S.D. = 1.396), representing a notable increase from the pre-training mean score of 6.47 ( Mean = 6.47, S.D. = 3.634) at the 0.05 significance level. Furthermore, the results of the follow-up evaluation on the application of acquired knowledge revealed that the overall level of knowledge and skills application is at its highest, with an average score of 4.64. This indicates that the developed course and online learning platform effectively enhance learners’ knowledge.
Language is fundamental to human communication, allowing individuals to express and exchange ideas, thoughts, and emotions. In early childhood, some children experience communication disorders that impede their ability to articulate words correctly, posing significant challenges to their learning and development. This issue is exacerbated in developing countries, where limited resources and a lack of technological tools hinder access to effective speech therapy. Traditional speech therapy remains vital, but the latest technological advancements have introduced robotic assistants to enhance therapy for communication disorders. Despite their potential, these technologies are often inaccessible in developing regions due to high production costs and a lack of sustainable manufacturing models. For these reasons, this paper presents “FONA,” a robotic assistant that employs rule-based expert systems to provide tactile, auditory, and visual stimuli. FONA supports children aged 3 to 6 in speech therapy by delivering exercises such as syllable production, word formation, and pictographic storytelling of various phonemes. Notably, FONA was successfully tested on children with cochlear implants, reducing the number of sessions required to produce isolated phonemes. The paper also introduces an innovative analysis of the Make To Order (MTO) manufacturing system for producing FONA in developing countries. This analysis explores two key perspectives: collaborative networks and entrepreneurship, offering a sustainable production model. In a pilot experiment, FONA significantly improved children’s attention spans, increasing the period by 17 min. Furthermore, the economic analysis demonstrates that producing FONA through collaborative networks can significantly reduce costs, making it more accessible to institutions in developing countries. The findings suggest that the project is viable for a five-year period, providing a sustainable and effective solution for addressing communication disorders in children.
In recent years, the environment in the manufacturing industry has become strongly competitive, which is why companies have found it necessary to constantly adjust their strategies and take actions aimed at improving their performance and competitiveness in a sustainable way to grow and remain in the market. Therefore, this paper aims to present an analysis to explain the current situation in the manufacturing industry in Aguascalientes, Mexico, by means of a survey in which product eco-innovation (PEI), process eco-innovation (PrEI) and organizational eco-innovation (OEI) and its effect on environmental performance (EP) and sustainable competitive performance (SCP) were measured. The results show that (EP) is positively and significantly influenced by (PEI) and (PrEI), while no significant influence is found for (OE). Furthermore, it is confirmed that environmental performance positively and significantly influences (SCP). The findings obtained from this study point to the relevance of promoting eco-innovation activities in the manufacturing sector, as this will ensure sustainable competitiveness.
A precise risk assessment in a production line constitutes a significant item to identify susceptible areas where there is a possibility of product quality degradation. This also applies to the precast concrete production line in Indonesia that has a spun pile product. Based on a risk assessment activity conducted in this study, it is proposed to build a traceability model in order to maintain and even improve the spun pile product quality in Indonesia. The approach used was the Neural Network of the perceptron model for weighing and will result in a defined traceability path in the context of reducing defects and even failed spun pile products. The simulation result showed that the model has been able to detect risky path possibilities to reduce product quality. The accumulation result of high-risk and medium-risk paths in this study showed that closer to product finalization, the risk will be higher. It is evident that when assessing Indicators, the order from the highest accumulation value first is Curing & Demolding and Stressing & Spinning at 29% each, Casting at 14%, Forming & Setting at 14%, and lastly Cutting & Heading at 14%. Regarding the risk assessment for activities, the first position is Curing & Demolding and Stressing & Spinning with 30% each, the second is Casting and Forming & Setting with 15% each, and the third is Cutting & Heading with 10%.
Development of technologies and innovations encouraged companies to look for and implement innovative solutions in their practice seeking not only to increase the efficiency of activity but also towards sustainability. In this context, the aim of the research is to reveal innovative solutions for the improvement of the warehousing processes towards sustainability in the case of manufacturing companies. The methodological setup consists of two steps. First, a comprehensive literature analysis was conducted seeking to reveal and present a theoretical model based on the conceptual framework on this topic. Then, a semi-structured interview was conducted with 8 managers holding managerial positions in four Lithuanian manufacturing companies. The manufacturing companies were chosen for the research due to their durable experience in the market, which use advanced warehouse management methods in their operations. Main findings showed, that innovative solutions such as Big Data Datasets, smart networks, Drones, Robots, Internet of Things and etc., are important for the efficient warehousing processes. Furthermore, it is also necessary to emphasize the benefits of implementing of innovative solutions in warehousing processes not only in economic terms, but also for solving of social and environmental issues towards sustainability. The novelty of this study lies in its dual objective of filling a theoretical gap and of drawing the attention of companies and policy makers to the importance of innovative solutions implementation in the warehousing process towards sustainability.
One of the main concerns in computer science today is integrating the Internet of Things (IoT) into manufacturing processes. This trend could influence a country’s strategy and policy development regarding technological infrastructure. However, despite extensive research on the implementation of IoT in manufacturing, no study has yet focused on the growing research interest in this topic. Based on 2487 papers indexed in the Scopus database between 2013 and 2023, this bibliometric review examines current trends and patterns in IoT research in manufacturing. The literature was selected and screened using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Data visualization was created using VOSviewer. The results show a notable increase in research papers centered around IoT in manufacturing. The findings reveal patterns and trends in IoT research publications in the manufacturing sector, author collaboration networks, country collaboration networks, and both established and newly trending topics surrounding IoT in the manufacturing industry.
Copyright © by EnPress Publisher. All rights reserved.