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.

This study examines destination image (DI) formation through user-generated web contents. Recently, web contents developed by peers have become one of the most popular information sources for travel planning purposes. After conducting a content analysis and text mining of a sample of 1033 blog articles (2009–2013), this study found that attraction to images of activities and positive/negative impressions with five categories (attraction, shopping, food and beverage, accommodation and transportation) form travellers’ DI. The study results suggest that traveller-generated web contents can be especially useful for DI analyses in marketing and management. This study also highlights the importance of understanding DI formation from traveller-generated contents and the challenges for those in tourism marketing to narrow the gap.

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.

Knowledge management (KM) is a core competency that determines the success of small and medium-sized enterprises (SMEs) in this knowledge-based economy. Instead of competing on the basis of physical and financial capital, the success of SMEs is influenced by the knowledge, experience and skills of the owners and its employees. Unfortunately, many SMEs are still struggling with KM implementation due to lacking a comprehensive KM framework. This study aims to identify enablers for KM success and build up a framework for KM implementation in service and product oriented SMEs. By using multiple research methods, this study collects data from SMEs in Taiwan to prove our suggested enablers and reference KM framework. The suggested framework can provide useful assistance and guidance for holistic KM solutions. The K-object concept, which adopted the XML standard, may become a significant managerial and technical element in the KM practice. The enhanced KM framework mandates every employee’s participation in knowledge activities, not just some elite knowledge workers. The findings provide useful implications for researchers and practitioners by providing useful templates for implementing KM initiatives in different industries and more comprehensive framework for KM implementation in different types of SMEs.

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.