An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa

This paper tests whether housing prices in the five segments of the South African housing market, namely large-middle, medium-middle, small-middle, luxury and affordable, exhibit non-linearity based on smooth transition autoregressive (STAR) models estimated using quarterly data from 1970:Q2 to 2009:Q3. Findings point to an overwhelming evidence of non-linearity in these five segments based on in-sample evaluation of the linear and non-linear models. We next provide further support for non-linearity by comparing one- to four-quarters-ahead out-of-sample forecasts of the non-linear time series model with those of the classical and Bayesian versions of the linear autoregressive (AR) models for each of these segments, for the out-of-sample horizon 2001:Q1 to 2009:Q3, using the in-sample period 1970:Q2 to 2000:Q4. Our results indicate that barring the one-, two and four-step(s)-ahead forecasts of the small segment, the non-linear model always outperforms the linear models. In addition, given the existence of strong causal relationship amongst the house prices of the five segments, the multivariate versions of the linear (classical and Bayesian) and STAR (MSTAR) models were also estimated. The MSTAR always outperformed the best performing univariate and multivariate linear models. Thus, our results highlight the importance of accounting for non-linearity, as well as the possible interrelationship amongst the variables under consideration, especially for forecasting.     

Are supply chain management theories culturally constrained? An empirical assessment

Culture plays an increasingly important role in supply chain management as many manufacturing firms have linkages to suppliers and customers from various countries. In this paper we propose treating culture as an explanatory variable to test the assumption that existing theories are universally applicable. The primary research question was: Do purchasing theories built on samples from mainly North American companies with Anglo-Saxon cultures apply in other cultural contexts? We developed and tested a model where top management??s view of the purchasing function affects purchasing practices and manufacturing performance. The statistical results provide evidence that the engagement and efficacy of purchasing practices is highly dependent on culture. This finding has significant implications from the perspective of decision making in international supply chain management. Specifically, top managers across multiple cultures could decide to structure and evaluate the purchasing function similarly, but these decisions could lead to different practices and different outcomes depending on the culture.     

Learning to trust strangers: an evolutionary perspective

What if living in a relatively trustworthy society was sufficient to blindly trust strangers? In this paper we interpret generalized trust as a learning process and analyse the trust game paradox in light of the replicator dynamics. Given that trust inevitably implies doubts about others, we assume incomplete information and study the dynamics of trust in buyer-supplier purchase transactions. Considering a world made of ??good?? and ??bad?? suppliers, we show that the trust game admits a unique evolutionarily stable strategy: buyers may trust strangers if it is not too risky to do so. Examining the situation where some players may play either as trustor or as trustee we show that this result is robust.     

The out-of-sample forecasting performance of nonlinear models of regional housing prices in the US

This article provides out-of-sample forecasts of linear and nonlinear models of US and four Census subregions’ housing prices. The forecasts include the traditional point forecasts, but also include interval and density forecasts, of the housing price distributions. The nonlinear smooth-transition autoregressive model outperforms the linear autoregressive model in point forecasts at longer horizons, but the linear autoregressive and nonlinear smooth-transition autoregressive models perform equally at short horizons. In addition, we generally do not find major differences in performance for the interval and density forecasts between the linear and nonlinear models. Finally, in a dynamic 25-step ex-ante and interval forecasting design, we, once again, do not find major differences between the linear and nonlinear models. In sum, we conclude that when forecasting regional housing prices in the United States, generally the additional costs associated with nonlinear forecasts outweigh the benefits for forecasts only a few months into the future.     

Measuring portfolio strategic performance using key performance indicators

It is difficult to find indicators for measuring the achievement of objectives during the progress of project portfolios. This article presents an approach for developing key strategic perfor‐mance indicators considering this limitation. The indicators proposed help measure the achievement of a portfolio's strategic objectives taking into account the realization of key benefits. This approach helps identify strategic interdependences between projects that the portfolio is composed of, facilitating the understanding of how the performance of a single project affects the overall performance of a portfolio. The key perfor‐mance indicators can also be used for monitoring the materialization of risks and opportunities influencing the strategic performance of a portfolio.     

Global financial conditions,country spreads and macroeconomic fluctuations in emerging countries

This paper uses a panel structural vector autoregressive (VAR) model to investigate the extent to which global financial conditions, i.e., a global risk-free interest rate and global financial risk, and country spreads contribute to macroeconomic fluctuations in emerging countries. The main findings are: (1) global financial risk shocks explain about 20% of movements both in the country spread and in the aggregate activity in emerging economies. (2) The contribution of global risk-free interest rate shocks to macroeconomic fluctuations in emerging economies is negligible. Its role, which was emphasized in the literature, is taken up by global financial risk shocks. (3) Country spread shocks explain about 15 percent of the business cycles in emerging economies. (4) Interdependence between economic activity and the country spread is a key mechanism through which global financial shocks are transmitted to emerging economies.     

Managing uncertainty in on-demand air travel

Fractional management companies (FMCs) that provide on-demand air travel services experience frequent changes in aircraft availability and flight requests. We propose scheduling heuristics which are both cost-effective and persistent (i.e., close to the original schedule) to address the uncertainty. The heuristics include pro-actively enforcing idleness of aircraft in creating the original schedule, strategically repositioning aircraft to serve yet-unknown demand and dense scheduling. Computational experiments are conducted in a simulator that mimics FMCs’ daily operations. Simulation results quantify the value of each heuristic, which can be easily incorporated into existing computational methods used in FMCs for static scheduling problems.     

The more contagion effect on emerging markets: The evidence of DCC-GARCH model

The paper aims to test the existence of financial contagion between foreign exchange markets of several emerging and developed countries during the U.S. subprime crisis. As a result of DCC-GARCH analysis, we find the evidence of contagion during U.S. subprime crisis for most of the developed and emerging countries. Another finding is that emerging markets seem to be the most influenced by the contagion effects during U.S. subprime crisis. Since financial contagion is important for monetary policy, risk measurement, asset pricing and portfolio allocation, the findings of paper may be interest of policy makers, investors and portfolio managers.     

An analysis of snow options for ski resort establishments

This study proposes a pricing method for put options on snow level for tourism establishments operating in Palandoken ski resort in the east of Turkey. In the calculation of put prices historical densities and Edgeworth adjusted densities methods together with Alaton, Djehiche, and Stillberger (2002) method have been applied. The findings show that there may be significant differences in the prices calculated by the three different methods, hence enabling both parties, i.e. buyers and sellers, with bases in the negotiation process. As the study is primarily aimed at providing a framework for pricing put options on snow levels in general, it is expected that it would be of use not only for this particular ski resort but also for various ski resorts in the world.     

The impacts of Radio Frequency Identification (RFID) technology on supply chain costs

Radio Frequency Identification (RFID) is regarded as a promising technology for the optimization of supply chain processes since it improves manufacturing and retail operations from forecasting demand to planning, managing inventory, and distribution. This study uses a simulation model to calculate the expected benefits of an integrated RFID system on a three-echelon supply chain obtained through performance increases in efficiency, accuracy, visibility, and security level. The study investigates how the product value, lead time, and demand uncertainty affect the performance of the integrated RFID supply chain in terms of cost factors at the echelon level.