The role of overseas Chinese investment in the emerging countries of Southeast and East Asia: A Confucian model of the foreign direct investment decision-making process using factors unconsidered in the West

The purpose of this study was to gain a better understanding of the foreign direct investment location decision making process through the examination of non-Western investors and their investment strategies in non-traditional markets. This was accomplished through in-depth personal interviews with 50 Overseas Chinese business owners and executives in several different industries from Hong Kong, Singapore, Taiwan, Malaysia, and Thailand about 97 separate investment projects in Southeast and East Asia, including The Philippines, Malaysia, Hong Kong, Singapore, Vietnam, India, Pakistan, South Korea, Australia, Indonesia, Cambodia, Thailand, Burma, Taiwan, and Mainland China.^ Traditional factors utilized in Western models of the foreign direct investment decision making process are reviewed, as well as literature on Asian management systems and the current state of business practices in emerging countries of Southeast and East Asia. Because of the lack of institutionalization in these markets and the strong influences of Confucian and patriarchal value systems on the Overseas Chinese, it was suspected that while some aspects of Western rational economic models of foreign direct investment are utilized, these models are insufficient in this context, and thus are not fully generalizable to the unique conditions of the Overseas Chinese business network in the region without further modification.^ Thus, other factors based on a Confucian value system need to be integrated into these models. Results from the analysis of structured interviews suggest Overseas Chinese businesses rely more heavily on their network and traditional Confucian values than rational economic factors when making their foreign direct investment location decisions in emerging countries in Asia. This effect is moderated by the firm's industry and the age of the firm's owners. ^

An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

Joint Compensation of I/Q Impairments and PA Nonlinearity for Concurrent Dual-Band Transmitters using Two-Box Model

A novel two-box model for joint compensation of nonlinear distortion introduced from both in-phase/quadrature modulator and power amplifier is proposed for concurrent dual-band wireless transmitters. Compensation of nonlinear distortion is accomplished in two phases, where phases are identified separately. It is shown that complexity of the digital predistortion is reduced. The performance of the proposed model is evaluated in terms of ACPR, EVM and NMSE improvements using 1.4 MHz LTE and WCDMA signals.

A MODEL FOR EVALUATING IMPACT OF BUSINESS PROCESS MANAGEMENT IN ORGANIZATIONAL PERFORMANCE

Business Process Management (BPM) is able to organize and frame a company focusing in the improvement or assurance of performance in order to gain competitive advantage. Although it is believed that BPM improves various aspects of organizational performance, there has been a lack of empirical evidence about this. The present study has the purpose to develop a model to show the impact of business process management in organizational performance. To accomplish that, the theoretical basis required to know the elements that configurate BPM and the measures that can evaluate the BPM success on organizational performance is built through a systematic literature review (SLR). Then, a research model is proposed according to SLR results. Empirical data will be collected from a survey of  larg and mid-sized industrial and service companies headquartered in Brazil. A quantitative analysis will be performed using structural equation modeling (SEM) to show if the direct effects among BPM and organizational performance can be considered statistically significant. At the end will discuss these results and their managerial and cientific implications.Keywords: Business process management (BPM). Organizational performance. Firm performance. Business models. Structural Equation Modeling. Systematic Literature Review.

Property cash flow studies : focusing on model consistency and data accuracy

The high degree of variability and inconsistency in cash flow study usage by property professionals demands improvement in knowledge and processes. Until recently limited research was being undertaken on the use of cash flow studies in property valuations but the growing acceptance of this approach for major investment valuations has resulted in renewed interest in this topic. Studies on valuation variations identify data accuracy, model consistency and bias as major concerns. In cash flow studies there are practical problems with the input data and the consistency of the models. This study will refer to the recent literature and identify the major factors in model inconsistency and data selection. A detailed case study will be used to examine the effects of changes in structure and inputs. The key variable inputs will be identified and proposals developed to improve the selection process for these key variables. The variables will be selected with the aid of sensitivity studies and alternative ways of quantifying the key variables explained. The paper recommends, with reservations, the use of probability profiles of the variables and the incorporation of this data in simulation exercises. The use of Monte Carlo simulation is demonstrated and the factors influencing the structure of the probability distributions of the key variables are outline. This study relates to ongoing research into functional performance of commercial property within an Australian Cooperative Research Centre.

Critical success factors of process modeling for enterprise systems

The integrated and process oriented nature of Enterprise Systems (ES) has led organizations to use process modeling as an aid in managing these systems. Enterprise Systems success factor studies explicitly and implicitly state the importance of process modeling and its contribution to overall Enterprise System success. However, no empirical evidence exists on how to conduct process modeling successfully and possibly differentially in the main phases of the ES life-cycle. This paper reports on an empirical investigation of the factors that influence process modeling success. An a-priori model with 8 candidate success factors has been developed to this stage. This paper introduces the research context and objectives, describes the research design and the derived model, and concludes by looking ahead to the next phases of the research design.

Understanding the Main Phases of Developing a Maturity Assessment Model

Practitioners and academics have developed numerous maturity models for many domains in order to measure competency. These initiatives have often been influenced by the Capability Maturity Model. However, an accumulative effort has not been made to generalize the phases of developing a maturity model in any domain. This paper proposes such a methodology and outlines the main phases of generic model development. The proposed methodology is illustrated with the help of examples from two advanced maturity models in the domains of Business Process Management and Knowledge Management.

Process modelling for enterprise systems: Factors critical to success

A range of influences, both technical and organizational, has encouraged the widespread adoption of Enterprise Systems (ES). The integrated and process-oriented nature of Enterprise Systems has led organizations to use process modelling as a means of managing the complexity of these systems, and to aid in achieving business goals. Past research illustrates how process modelling is applied across different Enterprise Systems lifecycle phases. However, no empirical evidence exists to evaluate what factors are essential for a successful process modelling initiative, in general or in an ES context. This research-in-progress paper reports on an empirical investigation of the factors that influence process modelling success. It presents an a-priori process modelling critical-success-factors-model, describes its derivation, and concludes with an outlook to the next stages of the research.

A model for assessing and correcting construction project health

Abstract Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.

Business process modeling : current issues and future challenges

Business process modeling has undoubtedly emerged as a popular and relevant practice in Information Systems. Despite being an actively researched field, anecdotal evidence and experiences suggest that the focus of the research community is not always well aligned with the needs of industry. The main aim of this paper is, accordingly, to explore the current issues and the future challenges in business process modeling, as perceived by three key stakeholder groups (academics, practitioners, and tool vendors). We present the results of a global Delphi study with these three groups of stakeholders, and discuss the findings and their implications for research and practice. Our findings suggest that the critical areas of concern are standardization of modeling approaches, identification of the value proposition of business process modeling, and model-driven process execution. These areas are also expected to persist as business process modeling roadblocks in the future.