Abstract: This work explores the inter-region investment
behaviors of Integrated Circuit (IC) design industry from Taiwan to
China using the amount of foreign direct investment (FDI). According
to the mutual dependence among different IC design industrial
locations, Lotka-Volterra model is utilized to explore the FDI
interactions between South and East China. Effects of inter-regional
collaborations on FDI flows into China are considered. The analysis
results show that FDIs into South China for IC design industry
significantly inspire the subsequent FDIs into East China, while FDIs
into East China for Taiwan’s IC design industry significantly hinder
the subsequent FDIs into South China. Because the supply chain along
IC industry includes upstream IC design, midstream manufacturing, as
well as downstream packing and testing enterprises, IC design industry
has to cooperate with IC manufacturing, packaging and testing
industries in the same area to form a strong IC industrial cluster.
Taiwan’s IC design industry implement the largest FDI amount into
East China and the second largest FDI amount into South China
among the four regions: North, East, Mid-West and South China. If IC
design houses undertake more FDIs in South China, those in East
China are urged to incrementally implement more FDIs into East
China to maintain the competitive advantages of the IC supply chain in
East China. On the other hand, as the FDIs in East China rise, the FDIs
in South China will successively decline since capitals have
concentrated in East China. In addition, this investigation proves that
the prediction of Lotka-Volterra model in FDI trends is accurate
because the industrial interactions between the two regions are
included. Finally, this work confirms that the FDI flows cannot reach a
stable equilibrium point, so the FDI inflows into East and South China
will expand in the future.
Abstract: Previous studies on financial distress prediction choose
the conventional failing and non-failing dichotomy; however, the
distressed extent differs substantially among different financial
distress events. To solve the problem, “non-distressed”, “slightlydistressed”
and “reorganization and bankruptcy” are used in our article
to approximate the continuum of corporate financial health. This paper
explains different financial distress events using the two-stage method.
First, this investigation adopts firm-specific financial ratios, corporate
governance and market factors to measure the probability of various
financial distress events based on multinomial logit models.
Specifically, the bootstrapping simulation is performed to examine the
difference of estimated misclassifying cost (EMC). Second, this work
further applies macroeconomic factors to establish the credit cycle
index and determines the distressed cut-off indicator of the two-stage
models using such index. Two different models, one-stage and
two-stage prediction models are developed to forecast financial
distress, and the results acquired from different models are compared
with each other, and with the collected data. The findings show that the
one-stage model has the lower misclassification error rate than the
two-stage model. The one-stage model is more accurate than the
two-stage model.
Abstract: Prior research has not effectively investigated how the
profitability of Chinese branches affect FDIs in China [1, 2], so this
study for the first time incorporates realistic earnings information
to systematically investigate effects of innovation, imitation, and
profit factors of FDI diffusions from Taiwan to China. Our nonlinear
least square (NLS) model, which incorporates earnings factors,
forms a nonlinear ordinary differential equation (ODE) in numerical
simulation programs. The model parameters are obtained through
a genetic algorithms (GA) technique and then optimized with the
collected data for the best accuracy. Particularly, Taiwanese regulatory
FDI restrictions are also considered in our modified model to meet
the realistic conditions. To validate the model-s effectiveness, this
investigation compares the prediction accuracy of modified model
with the conventional diffusion model, which does not take account
of the profitability factors.
The results clearly demonstrate the internal influence to be positive,
as early FDI adopters- consistent praises of FDI attract potential firms
to make the same move. The former erects a behavior model for the
latter to imitate their foreign investment decision. Particularly, the
results of modified diffusion models show that the earnings from
Chinese branches are positively related to the internal influence. In
general, the imitating tendency of potential consumers is substantially
hindered by the losses in the Chinese branches, and these firms would
invest less into China. The FDI inflow extension depends on earnings
of Chinese branches, and companies will adjust their FDI strategies
based on the returns. Since this research has proved that earning is
an influential factor on FDI dynamics, our revised model explicitly
performs superior in prediction ability than conventional diffusion
model.