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The motivation of the paper is to find out the influence of demographic characteristic factors on employees’ career promotion in China’s state-owned enterprises and study the relationship between promotion mechanism and enterprise benefits. More than 6,500 pieces of human resource data from China’s state-owned enterprises were studied. Logistic regression is adopted to analyze the correlation between demographic characteristics and promotion. Meanwhile, different data mining methods are used to summarize the characteristics of promotion. On this basis, this study uses the principal-agent model of game theory to analyze the profits of employees and enterprises under different promotion mechanisms and demonstrates the conditions for enterprises to obtain the maximum benefit from the employees’ promotion. The results provide a theoretical reference for the assessment indicator selection of enterprise promotion and help executives better understand the impact of promotion mechanism on enterprises and employees. The application of results can reduce the information asymmetry in promotion incentive, prevent the emergence of adverse selection, and achieve a win-win situation for enterprises and employees.

The telecommunications industry has been undergoing tremendous technological changes, and owning to continuous technological advancement, it has maintained sustained prosperity and development. In this paper, the interplay between technology, market and government in telecommunications is discussed briefly, and then we introduce technology and government into the traditional SCP (Structure — Conduct — Performance) paradigm to develop an industry analysis framework called TG-M(SCP) (Technology — Government — Market (Structure — Conduct — Performance)). Based on this framework, we present the spiral co-evolution model which elaborates on the interaction mechanism of technological innovation with government regulation and market dynamics from the perspective of industry evolution. Our study indicates that the development of the telecommunications industry is the result of the coevolution of technology, government regulation and market forces, and among the three actors, technology is the fundamental driving force. Relative to the "invisible hand" (market) and "visible hand" (government), we conceptualize technology as the "third hand", which fundamentally drives the development of telecommunications industry in coordination with the other two hands. We also provide several policy implications regarding these findings.

Against the background of increasingly mature mobile internet eco-system, internet companies have been continuing pursuing the innovation of internet applications. The action has brought about not only more clicks from the netizens but also gave rise to mounting network burden. Telecom service providers are now faced with the dual pressure from both the soaring broadband building and maintenance costs as well as the declining traditional operating revenues. They wish to find a way to abolish the previous unified pricing model and shift it into the differential charging model by offering graded data flow services. Consequently, the controversy over “net neutrality” has been aroused in the whole society. In this article we analyze the optimum prices in different stages of the internet eco-system, and establish two-sided market model for further research.

We compared individual and joint risk-based decision making using the Balloon Analogue Risk Task, with a focus on participants' (160 Chinese men) emotional experience during decision making and their Big Five personality traits as measured by the NEO Five-Factor Inventory. We found that, compared with the individual decision-making process, making a joint decision led to reduced risk taking and increased earnings, and brought a greater sense of control, stronger feelings of achievement and happiness, and a reduced sense of regret for the participants. The Big Five personality traits of the participants were related to their risk-based decision making; participants tended to act differently according to their personality traits during individual and joint decision making. Our findings show that, compared with individual decision making, joint decision making has many advantages.

Along with the continuous development of wireless communication technology and popularization of multi- mode terminal, the seamless fusion of various heterogeneous wireless networks has gradually become the trend of net- work development. The diversified forms of network access enable the multi-mode terminal to dynamically select the ac- cess network with the highest utility value to obtain network service according to specific standard. The study selects a typical heterogeneous network scenario, abstracts users' network selection process to be group game model, adopts the evolutionary methods, and then studies user's network selection process through replicator dynamics. On the basis of it, it puts forwards a kind of network selection algorithm in the view of replicator dynamics and verifies its algorithm perfor- mance through simulation results, and then analyzes the impact of different factors on evolutionary equilibrium in detail.

Increasing popularity of spectrum-based services brings the striking contradictions between the limited spectrum resource and its increasing demands. This paper puts forward an approach to forecast the future spectrum demand and its economic value, so as to offer a scientific basis for spectrum regulators to resolve this contradiction effectively and make a long-term spectrum-use plan. Specifically, this paper analyzes the driving factors of spectrum demand firstly, based on which a forecasting model is constructed to predict the spectrum demand and its deficit/surplus in the next few years. Then, a forecasting model to measure the economic value of spectrum is proposed based on marginal opportunity cost theory, and the indifference curve is introduced to show the economic value generated by additional spectrum. Additionally, an empirical study is conducted to forecast the spectrum demand and its economic value for China in the next 10 years according to the proposed method. The results of this study show that spectrum deficit is a trend in future and releasing additional spectrum will bring China huge economic benefits.

The paper designs a demand forecast system for online retailers based on big data and the theory of consumer behavior on the purpose of improving regional forecasting accuracy as well as shortening the forecasting periods. The necessity and the urgency of strengthening e-commerce enterprises' forecasting abilities are emphasized from the perspective of enterprises and consumers. Analysis and design process make use of the concepts of Engel-Kollat-Blackwell Model to put forward a framework composed of four phased prediction, which are the Initial Demand, the Possible Demand, the Core Demand and the Effective Demand. The further discussion then details how online retailers could implement this big-data-based system to cope with various shopping scenarios, such as the New Arrival periods and the November 11 Singles' Day shopping spree. By restating theoretical innovation in the field of demand forecasting research, the paper concludes with an outlook of potential improvement of the architecture and the direction of related practices.