In the digital economy era, small service business struggle to compete in a rapidly changing and dynamic market. Therefore, through digital transformation (DT), small service business seek to increase their competitive advantage, improve business performance, and achieve business growth. Having limited resources and capabilities, small service business must deal with several barriers and challenges. This study aims to discover the barriers, and the roles of government, for digital transformation in small service business. This study applied a qualitative approach involving semi-structured in-depth interviews with top management of small service business. Then, we employed the content analysis method to examine interview data and construct a model. This research reveals four main barriers to digital transformation in small service business: lack of funding, lack of digital capability, lack of human resources, and technical barriers. We found there are four government roles for supporting digital transformation in small service business: build a digital platform for small service business, promote mobile/digital payment, provide digital training, and build a digital collaboration ecosystem. Additionally, based on this study’s findings, a model for barriers and government support of digital transformation in small service business is presented. This study contributes to the conceptual framework and management implications in the digital transformation field. The study’s findings provide insights to practitioners and suggest that the government could alter the current policies and programs to support digital transformation in small service business.

Small and medium-sized businesses (SMEs) are frequently exposed to a variety of difficulties during global epidemic crises like coronavirus (COVID-19), which may even threaten their lives. The purpose of this study explores the influencing factors of Taiwan’s companies between small and medium-sized enterprises and micro-enterprises on the choice of the cross-border e-commerce platform. The findings are defined as taking into account small and medium-sized businesses and microenterprises when choosing cross-border e-commerce through a literature review and an examination of secondary data among the 10 participating businesses through interviews in various regions and business sectors in Taiwan. In this case we used study-based research, which included five small, medium-sized, and micro-enterprises, as well as five cross-border e-commerce projects and the company’s management senior officers. According to the study’s emphasis on the economic, social, technological, and legal aspects of various firms, these factors lead to a variety of decisions regarding the best cross-border e-commerce platform. The case study approach was utilized in this investigation to confirm the consideration of micro-and small-sized businesses that took part in cross-border e-commerce project counseling. This study summarizes five types of enterprises with different capabilities: product enhancement, marketing enhancement, cross-border potential, knowledge-based enhancement, and cross-border start-up. According to the results, it was found that different enterprise capabilities will affect the choice of cross-border e-commerce platforms. These five capabilities also have different types of consideration factors; among them, SMEs pay attention to marketing, pricing, market analysis, culture, customer service, payment, logistics, certification, taxation, etc. In addition to theoretical implications, this research also gives small and medium enterprises and micro-enterprises practice when choosing cross-border e-commerce platform, as well as suggestions for future research.

Micro-enterprises are critical to the national economy in many countries, although they have many limitations. Therefore, governments have proposed many policies and programs to generate and enhance micro-enterprises’ growth to assure national economies’ growth and sustainability. This study evolves an index to evaluate growth in science and technological innovation among micro-enterprises that participated in collaborative innovation through a counselling program. The results not only define growth indicators through a literature review but also examine evidence of growth among 10 micro-enterprises through interviewing subjects located in various regions in Taiwan and related to different industries. This study uses multiple case study methods and data statistics to verify growth indicators; this reveals that micro-enterprises focusing on collaborative technological innovation demonstrated an increasing trend toward this study’s chosen growth indicators in a majority of cases. According to the survey results, nine indicators lead to positive growth. Finally, after establishing growth assessment indicators, the data collected from an empirical investigation proves the indicators’ credibility. The study then discusses the chosen cases’ experiences with growth and presents managerial implications.

Purpose: The purpose of this paper is to prove the importance of both cluster leadership and identification on cluster innovation. Design/methodology/approach: The case studies presented in this study involve a cluster by micro-enterprises in Yilan, Taiwan. Data collected during interviews, observations and secondary data provide understanding and practices for the impact of cluster identification on cluster innovation. Findings: This study proved: first, the importance of cluster identification on innovation by representing the need of consensus and collaboration of the members in conducting innovation actions; and second, the cluster identification is influenced by the cluster leadership by showing high satisfaction of the leader, close interaction between the members and high identification with the cluster. Research limitations/implications: This study predicts the ongoing cluster innovation activities will be achieved due to the transformational leadership and high cluster identification. Originality/value: This study enriches the factors of cluster innovation accomplishment and proposes the important of cluster identification, which has not been discussed much in the past.

This study explores big data gathered from motor production lines to gain a better understanding of production line issues. Motor products from Solen Electric Company’s motor production lines were used to predict failure points based on big data analytics, where 3606 datapoints from the company’s testing equipment were statistically analyzed. The current study focused on secondary data and expert interview results to further define the relevant statistical dimensions. Only 14 of the original 88 detection parameters were required for monitoring the production line. The relationships between these parameters and the relevant motor components were established to indicate how an abnormal reading may be interpreted to quickly resolve an issue. Thus, a theoretical model for the monitoring of the motor production line was proposed. Further implications and practical suggestions are also offered to improve the production lines. This study explores big data analysis and smart manufacturing and demonstrates the promise of these technologies in improving production line efficiency and reducing waste to promote sustainable production goals. Big data thus constitute the core technology for advancing production lines into Industry 4.0 and promoting industry sustainability.

In this study, the factors that affect the implementation of intelligent systems in motor production lines are analyzed. A motor production line located in Vietnam is used as the research object. The research methods include secondary data collection, field study, and interviews. This study demonstrates the following: firstly, the implementation of intelligent systems in motor production lines is heading toward Industry 4.0. Secondly, it is proposed that three functional systems—robot arm, image recognition, and big data analysis—can be introduced in the motor production line. This study analyzes the process involved in coil and motor production lines and attempts to combine intelligent system functions. It is expected that in the future, manpower will be reduced, production line productivity will increase, and intelligent production lines will be proposed. The factors that affect the introduction of intelligent systems in motor production lines are improved, and the importance of intelligent systems, which has been rarely considered in previous studies, is highlighted. In the implementation criteria of the intelligent system in the process management of the motor production line, this study provides some suggestions (to coil and motor assembly line) for the production process management. These suggestions can be provided as a reference for production lines that acquaint with intelligent systems.