Gang Kou's research while affiliated with Southwestern University of Finance and Economics and other places

... In addition, to reflect the stock market information contained in the text data for stock price movement prediction, the contextual information is identified through the contextual word embedding of the bidirectional encoder representations from transformers (BERT). The multimodal timeseries market signals from the price and text data affect the stocks [7]. After extracting the time-series features of the price data and sematic features of the text data, the extracted features are combined to create a mixed feature containing multimodal information. ...

... In the era of globalization, there are many factors affecting carbon dioxide emissions, such as ICTs, foreign direct investment, globalization and green investment (Usman et al., 2022a;Ke et al., 2022;Li et al., 2022). It is urgent to solve environmental problems and reduce carbon dioxide emissions. ...

... Therefore, the urgency of entrepreneurial social and financial literacy is a vital force of financial inclusion that affects the rural communities' financial accessibility (Hasan et al., 2021;Tufail et al., 2022). Sustainable financial inclusion is also becoming increasingly important in enhancing green socio-economic performance, competitiveness, and economic growth Wang et al., 2022). ...

... McNee et al. [4] first introduced the problem of citation recommendation [5] for research papers. In recent years, there has been a large number of studies which provide methods for recommending potential papers that are related to a specific research topic [6][7][8]. However, there are a lot of potential improvements that can be made to such works, and studies on this topic are classified as working on citation recommendation systems. ...

... Contreras et al. (2019) used bargaining theory to determine a set of weights in DEA to rank decision-making units agreeably. Li et al. (2021) represented a satisfaction degree bargaining game approach to determine the unique, stable, and fair cost allocation between DMUs with undesirable outputs. Using normalized weight sets and bargaining game, Wang et al. (2021) developed a novel DEA method for solving this issue with non-uniqueness of weights. ...

... We argue that time-series prediction models and other machine learning techniques may enhance decision-making in finance. We refer interested readers to recent reference books by Dixon et al. (2020) and Consoli et al. (2021), reviews by West and Bhattacharya (2016) and Henrique et al. (2019), and applications by Moubariki et al. (2019), Li et al. (2021), Kou et al. (2021b) and Manthoulis et al. (2021). ...

... The appropriate distribution of the resources or capacity of the company optimizes the organizational goals and assists it to reach its strategical targets. These resources can be machines of a workshop, [40][41][42][43][44][45][46][47][48][49][50][51][52][53]116 runways of an airport, 54-59 employees of a department, 60-66 processor units of a hardware-software systems, 67-72 investment approaches of project applications, [73][74][75][76][77] or attributes of a service, [78][79][80][81][82] where the goals here might be minimizing the number of the delivery delays, maximizing the utilization rate, minimizing the expenses, or minimizing the completion time of the tasks. The required components, materials, goods, services or products must be provided at the right time, in the right quantity, in the right condition, and at a reasonable price from the right source for each organization 83 for every type of organization to maintain their pro¯t margins and market shares alongside with their strategical management applications. ...

... Distance metric learning has aroused significant interest among scholars in machine learning and related fields [1][2][3]. This depends mainly on the intensification of the situation, as follows: Machine learning algorithms always rely on underlying distance metrics that represent important correlations in input data [4][5]. ...

... Before discussing the impact of fintech development on FTIE, we first verified its impact on FTIQ. As innovation acts as an output, innovation quantity, often measured by the number of patents [75], [76], is also one of the components of technological innovation efficiency. Due to the time lag effect of innovation activities, when measuring innovation efficiency, innovation output lags behind innovation input by one year. ...

... Scholars have widely adopted data envelopment analysis (DEA) models to evaluate the environmental performance of ISs [4]. However, traditional DEA models only consider initial inputs and final outputs, while the internal structures of decision-making DEA, as a nonparametric model that does not require the assumption of a production function in advance, has been widely used in efficiency assessment [13]. ...