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Limited access to capital is a classic issue in and a burden to micro, small and medium enterprises (MSMEs) in Indonesia. The existence of the problem with information asymmetry and agency conflicts that are predominant at the level of small businesses, increasingly hampers the opportunity to obtain funds from various external sources. Especially for businesses that are at the pioneering stage, entrepreneurs are required to think creatively, have the courage to take risks, and be independent in fulfilling resources to realize business opportunities. The availability of funds certainly has an impact on business performance, either directly or indirectly. Based on a literature review, business performance is categorized into financial and non-financial dimensions with various measurement proxies. However, some of the models and measurements proposed are not always suitable in assessing the performance of MSMEs, especially in the startup phase. Therefore, this chapter concurrently describes the funding patterns and the funding alternatives to measure the performance of new businesses based on the existing literature. Theoretically, this research adds a perspective in the field of entrepreneurial finance regarding funding patterns that can be implemented by startup businesses in Indonesia and provides a proposal for measuring the concept of performance that is more adaptive and comprehensive for businesses in the startup stage. The implication of this research for entrepreneurs leads to the need to adjust funding decisions according to the changing stages of the business lifecycle and to expand the funding window to support the sustainability of small businesses.

With its worldwide fame for making action films, Hong Kong cinema has been defined as masculine. Action films, including the costumed martial arts films and the modern gangster films, have been a major genre in Hong Kong cinema from the 1960s on. Despite the dominant masculinity, women still play significant roles in some of these films. In fact, fighting women leave footprints in the history of Hong Kong cinema, which precede their counterparts in the West and even provide models for Hollywood after 2000.

This chapter focuses on the female characters portrayed by the acclaimed Hong Kong director Wong Kar-wai, whose works have an ambiguous connection to mainstream genres. He modifies Hong Kong action films and creates unconventional female characters such as the drug dealer in Chungking Express (1994), the killer dispatcher in Fallen Angels (1995), the swordswoman in Ashes of Time (1994), and the kung fu master in The Grandmaster (2013). Wong's films have been mush discussed in academia, but the gender images therein are quite ignored. With high intertextuality, these characters are used to question mainstream action films and redefine women's roles in male's cinematic space. In addition, via the writing of these women, Wong constructs an open and ambivalent post-colonial Hong Kong identity. This paper contextualises the figures of sword-wielding and gun-shooting women and examines how Wong Kar-wai deploys these images to articulate the cultural identity of a post-colonial city.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

The use of artificial intelligence (AI) in management research is still nascent and has primarily focused on content analyses of text data. Some method scholars have begun to discuss the potential benefits of far broader applications; however, these discussions have not led yet to a wave of corresponding AI applications by management researchers. This chapter explores the feasibility and the potential value of using AI for a very specific methodological task: the reliable and efficient capturing of higher-level psychological constructs in management research. It introduces the capturing of basic emotions and emotional authenticity of entrepreneurs based on their macro- and microfacial expressions during pitch presentations as an illustrative example of related AI opportunities and challenges. Thus, this chapter provides both motivation and guidance to management scholars for future applications of AI to advance management research.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.