Internet finance is China’s newest hot topic in its booming economy. Success story of entrepreneurial ventures such as Alibaba have paved way for numerous entrepreneurs to establish innovative start-ups and enterprises. Presently, number of up and coming small and medium enterprises (SMEs) is above 80% of all new enterprises in China, involving 39 major categories of industrial sectors. Such enterprises are hugely backed by Internet finance companies for funding and easy transactions. It is important to develop efficient methodology and improve existing ones for credit assessment so as to aid Internet finance companies in making effective and symmetric funding decisions. To evaluate the performance of SMEs effectively, we propose an Internet finance credit index system, which includes financial, credit, enterprise development and Internet financial status. We combine the Analytic Hierarchy Process (AHP) and data envelopment analysis (DEA) to form a unified evaluation framework, which has the ability to address the subjective (AHP) and the objective (DEA) concerns, respectively. The proposed framework can assist Internet finance organizations to develop a transparent, unbiased and integrated framework for evaluating credit index of SMEs and start-ups. The result of our framework identifies the most important characteristics of SMEs and start-ups which contribute to overall credit rating, provides valuable references for Internet financial organization to make better resource allocation (funding decisions). The framework for credit evaluation also provides start-ups and SMEs an insight into improving their credit rating.
Technological innovation as one of the most important competitive strategies for companies has attracted the attentions of companies and governments. In this paper, we present an evaluation method based on data and judgments to rank the technological innovation capability and technological innovation efficiency of enterprises of various sizes in China. Furthermore, based on the efficiency measures, we design a model for the government to optimally allocate innovation resource to businesses, i.e. prioritize public expenditures dedicated to innovation. In evaluating the efficiency of industrial enterprises, we employ the “input-process-output” perspective to identify multiple criteria. We also take into account the cost of technological innovation in efficiency assessment. The optimization model proposed for government is to maximize the overall efficiency of resources utilization. We adopt the genetic algorithm as the solution methodology to solve the optimization model. Simulation is conducted to validate the model and the algorithm. The research framework proposed in paper can be adapted for government in many countries to better distribute resources for technological innovation and development.
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