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The purpose of this paper is to examine whether Korean multinational corporations (MNCs) in the electronics and steel industries do shift their production across their foreign subsidiaries, located in different countries, as exchange rates fluctuate in foreign countries.

A case study was taken as a qualitative methodology to examine whether MNCs actually shift their production as multinational operational flexibility perspective predicts.

From a case study of two Korean MNCs (LG Electronics and POSCO), it was found that even facing heightened production costs associated with host country currency appreciation, Korean MNCs do not shift their production to less costly locations due to industrial characteristics, limited capacity, and high tariff barriers. It was also found that they reduce the production costs internally and they also negotiate the costs with employees and suppliers to adjust the production costs associated with appreciated currency.

Our findings imply that certain industrial and environmental constraints make it difficult for MNCs to take flexible actions as multinational operational flexibility perspective predicts. The findings also shed additional light on the less‐explored argument over operational flexibility and vertical integration associated with cross‐country shifts of value chain activities, including production or sales.

Almost all literature taking the multinational operation flexibility view argues that MNCs are able to shift their productions for their own benefits. However, the authors of this paper find from their case studies that firms take advantage of other methods than production shifts in their responses to exchange rate fluctuations in their host countries. Thus this study gives an insight into when and how firms behave as the theory predicts.

The purpose of this paper is to present detailed algorithms for simulation of individual and group control of production wells in hydrocarbon reservoirs which are implemented in a finite volume-based reservoir simulator.

The algorithm for individual control is described for the multi-lateral multi-connection ones based on the multi-segment model considering cross-flow. Moreover, a general group control algorithm is proposed which can be coupled with any well model that can handle a constraint and returns the flow rates. The performance of oil production process based on the group control criteria is investigated and compared for various cases.

The proposed algorithm for group control of production wells is a non-optimization iterative scheme converging within a few number of iterations. The numerical results of many computer runs indicate that the nominal power of the production wells, in general, is the best group control criterion for the proposed algorithm. The production well group control with a proper criterion can generally improve the oil recovery process at negligible computational costs when compared with individual control of production wells.

Although the group control algorithm is implemented for both production and injection wells in the developed simulator, the numerical algorithm is here described only for production wells to provide more details.

The proposed algorithm can be coupled with any well model providing the fluid flow rates and can be efficiently used for group control of production wells. In addition, the calculated flow rates of the production wells based on the group control algorithm can be used as candidate solutions for the optimizer in the simulation-optimization models. It may reduce the total number of iterations and consequently the computational cost of the simulation-optimization models for the well control problem.

A complete and detailed description of ingredients of an efficient well group control algorithm for the hydrocarbon reservoir is presented. Five group control criteria are extracted from the physical, geometrical and operating conditions of the wells/reservoir. These are the target rate, weighted potential, ultimate rate and introduced nominal power of the production wells. The performance of the group control of production wells with different group control criteria is compared in three different oil production scenarios from a black-oil and highly heterogeneous reservoir.

This paper deals with the production and preventive maintenance planning control problem for a multi‐machine flexible manufacturing system (FMS). A two‐level hierarchical control model is developed according to the discrepancy between the time scale of the discounting cost event and one of the machine state processes. The proposed model extends the classical singular perturbation approach by considering age‐dependent machine failure rates and controlling both production and preventive maintenance rates. We replace the stochastic optimal control problem by a deterministic one termed limiting control problem. With this approach, we compute an age‐dependent near‐optimal control policy of the stochastic initial control problem from the optimal solution of the equivalent limiting control problem. A numerical example is used to illustrate the procedure and to show the reduction of the control problem size.

The purpose of this paper is to investigate the effects of macroeconomic indicators (the interest rate and the industrial production) on Vietnamese stock prices. The paper examines how US macroeconomic indicators affect Vietnamese stock prices.

The authors use monthly time series data covering the period from January 2001 to April 2008. The methodology introduced by Nasseh and Strauss and Canova and de Nicolo to investigate the linkage between stock prices and macroeconomic indicators.

This paper provides the first empirical evidence that there are statistically significant associations among the domestic production sector, money markets, and stock prices in Viet Nam. Another novel finding is that the US macroeconomic fundamentals significantly affect Vietnamese stock prices. Finally, the results show that the influence of the US real sector is stronger than that of the money market.

Since prior research has focused on developed economies, the authors strongly believe that this paper provides a novel contribution to the existing literature as the authors are the first to examine this issue in Viet Nam.

The demand variability in case of assembly line operations can be absorbed either by multi‐skilling of operators on the line, empowering them to handle a wider mix of work‐elements or by holding finished goods inventory. This paper examines trade‐offs between these two groups of policies by developing a simulation‐based model. Four policies are evaluated and their cost implications examined to enable decision makers to choose the best policy depending upon the situation specific parameters. A case study to illustrate the proposed model is presented and results are found to be insightful. A methodology to identify training needs in case of multi‐skilling is also developed.

Due to considerable contributions of the construction industry to the global carbon emissions, a great deal of attention is placed on possible incorporation of carbon footprint minimization as an important objective in the planning of construction operations. The purpose of this paper is to present a framework to estimate and minimize the carbon emissions of the concrete placing operation through identifying the optimal number of pumps and the inter-arrival time of truck mixers.

The proposed framework integrates discrete event simulation and multi-objective optimization to estimate and minimize the carbon emission, costs and production rate of the concrete placing operation. An actual construction project is used to demonstrate the application of the proposed framework. Furthermore, a sensitivity analysis is performed to investigate the sensitivity of the results to variations in modeling parameters including the ratio of idle to non-idle emission rates of equipment and the activity duration distributions.

The results of the case study highlight that variations in the number of pumps and inter-arrival time of truck mixers significantly affect the carbon emissions, cost and production rate of the concrete placing operation. Furthermore, the results of the sensitivity analysis show that variations in the ratio of idle to non-idle emission rates for pumps and truck mixers have little effects on the selected setting for the project. This is contrary to the effect of uncertainty in the activity duration distributions, which was found to be significant.

Results of this study provide an insight into the trade-off between carbon emissions, cost and production rate of the concrete placing operation.

This research has addressed a quantitative approach for improving energy management through applying statistical techniques aimed at identifying and controlling factors linked to energy consumption rates at manufacturing plants. The paper presents analysis and results of multiple linear regression models used to establish the significance of a number of energy related management factors in controlling energy usage. Regression models constructed for this purpose proved the existence of statistically valid relationships between electrical energy consumption and maintenance and production management factors, namely, failure rate and production rate, where R² values of the magnitude of 65 per cent were obtained. Furthermore, an economical treatment based on the derived regression models was formulated and demonstrated that effective management practices associated with proper maintenance, cost accounting and reporting systems can result in highly significant savings in energy usage.

This paper assesses the projected growth of food supply relative to population growth and estimated food demand growth over the next four decades.

World population projections are analyzed for the main developed and developing regions. Implied food demand growth is then compared to grain and oilseed supply projections from a few of the most reliable sources. Three of these are 10-year projections and two extend to 2030 and 2050. To the extent possible, comparisons are made among the alternative projections. Conclusions about food availability and prices are finally drawn.

Meeting the growth in demand for food, feed, and biofuels to 2050 will not be a steep hill to climb, but there will need to be continued private and public investment in technology to induce increased production growth rates through productivity enhancements and increased purchased inputs.

The main food security challenge of the future, as in the present, is not insufficient production but rather increasing access and reducing vulnerability for food insecure households. The dominance of future population growth in the food insecure regions of Africa makes this challenge even more critical between now and 2050 and even more so in the years beyond 2050 when climate change effects on resource constraints will be more severe.

Although research attention has been given to the modelling process for simultaneous demand‐output management in manufacturing systems, little interest has been demonstrated in service organisations despite the fact that such organisations face unique conditions that further complicate the demand‐output management issue. In response to this lack of emphasis, we review the relevant research from both marketing and operations management and present a cost‐effectiveness model for balancing demand and service output.

The authors empirically aim to study the implications of uncertainty generated by oil price volatility on some key macroeconomic variables, including production, exchange rates and interest rates, of both oil-exporting and oil-importing countries. Using a block exogeneity structural Vector Auto Regression (VAR) model that mutes the effects of domestic variables on global factors and that is suitable for small open economies because of significant differences in the responses of domestic production in oil-importing countries will most likely decrease through reducing planning horizons, postponing investment projects and relocating resources more inefficiently.

The authors integrated into the structural vector autoregressive (SVAR) model the block exogeneity feature since all the countries in this study are small open economies that cannot influence the global economic variables. The block exogeneity feature imposes the restriction that the domestic variables have neither a contemporaneous nor a lagged impact on the global variables. This model has eight variables: oil price volatility, world demand and federal funds rate as the global variables; and domestic production, monetary aggregate, inflation rate, exchange rate and interest rate as domestic variables. The authors assemble the data for 12 developing countries for which the necessary data for the analysis are available: six oil exporting countries (Russia, Saudi Arabia, Iran, Kazakhstan, Mexico and Colombia) and six oil importing countries (Turkey, India, Philippines, Poland, South Africa and Indonesia).

The results point out significant differences in the responses of macroeconomic variables to oil price volatility shocks between oil-exporting and oil-importing countries. Furthermore, the local currencies of these countries depreciate due to concerns about possible current account worsening. In response to the shock, domestic interest rates are reduced so as to alleviate the negative exposure of the shock on domestic economic activity. While domestic production in some oil-exporting countries (i.e. Russia, Saudi Arabia and Iran) increases during oil price uncertainty; in some other countries (i.e. Mexico, Kazakhstan and Colombia), domestic production decreases.

Several components of the study contribute to its novelty. One of them is the period under consideration. The time frame that encompasses the most significant geopolitical and financial events, such as the Middle East Spring and the global financial crisis of 2007–2008. The research was conducted using the block-exogeneity SVAR model, which includes 12 oil exporting and importing developing countries. With this model, the global dynamics, particularly the energy market, that these nations may influence and are influenced by, i.e. global and nonglobal factors can be constrained. This makes it easy to determine the various effects prices have on macroeconomic variables.

1. Oil prices and volatility still matter to the global economy

2. Monetary and fiscal policy interventions in response to oil price volatility create uncertainty and impede investment activity

3. The response of macroeconomic variables to volatility shocks in oil prices varies across oil importers and exporters

4. Interest rates help stabilize production in oil-importing economies that have well-functioning financial markets

Oil prices and volatility still matter to the global economy

Monetary and fiscal policy interventions in response to oil price volatility create uncertainty and impede investment activity

The response of macroeconomic variables to volatility shocks in oil prices varies across oil importers and exporters

Interest rates help stabilize production in oil-importing economies that have well-functioning financial markets