Fractional Variational Iteration Method for Fractional Nonlinear Differential Equations

Recently, fractional differential equations have been investigated via the famous variational iteration method. However, all the previous works avoid the term of fractional derivative and handle them as a restricted variation. In order to overcome such shortcomings, a fractional variational iteration method is proposed. The Lagrange multipliers can be identified explicitly based on fractional variational theory.Comment: 12 pages, 1 figure

"Foreign Direct Investment and the Performance of MNCs: Taiwanese Firms' in People's Republic of China and Southeast Asia"

This study draws upon a firm level database from Taiwan to study the foreign direct investment (FDI) behavior of firms. An econometric model based on economic theories of the MNC behavior is used for carrying out the empirical analysis. The performance of Taiwanese firms with FDI in Mainland China(PRC) and South-East Asia can be explained by this model that focuses upon capital utilitization, management experience, industrial and macroeconomic environment. The results show that the higher the asset utilization efficiency, the better is the subsidiary performance. Furthermore, the more sound the fundamental macroeconomic and other conditions in countries invested and the lower the labor cost, the better is the operational performance of the subsidiary companies. Also the higher the industrial market value and the more abundant the capital of the parent company, the better is the subsidiary performance. However, the results do not settle definitively whether management capability increases the subsidiary performance. There is no statistically significant influence of the management capability of an MNC from Taiwan engaging in foreign direct investment on its subsidiaries' performance.

De‑globalization, International Trade Protectionism, and the Reconfigurations of Global Value Chains

Peer reviewedPublisher PD

Game Theory Based Correlated Privacy Preserving Analysis in Big Data

Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors’ privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments