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Ramp meters in the Twin Cities were turned off for 8 weeks in the Fall of 2000. This paper analyzes traffic data collected in this experiment on travel time variability with and without ramp metering for several representative freeways during the afternoon peak period. Travel time variability is generally reduced with metering. However, it is found that ramp meters are particularly helpful for long trips relative to short trips. The annual benefits from reducing travel time variability with meters are estimated to be $33.1 million, compared to the annual ramp metering costs of $2.6 million in the Twin Cities metro area. Thus, the impact on travel time variability should be captured in future ramp metering benefit/cost analysis.

The recent unprecedented levels reached by financial ratios have led to a re‐examination of their time‐series properties, with evidence of long memory and nonlinearity reported. The purpose of this paper is to re‐examine the nature of these series in the light of potential time‐variation in the unconditional mean.

The paper uses econometric techniques designed to capture fractional integration, nonlinearity and time‐variation in the unconditional mean level of a series.

Reported results support such time‐variation, with cyclical behaviour evident in the unconditional mean of each ratio. Evidence of nonlinearity is still apparent in the mean‐adjusted series.

A key result that arises is that accounting for this time‐variation appears to provide improved long horizon returns predictability.

The paper demonstrates that a nonlinear model incorporating a time‐varying mean improves returns predictability. This is of interest to market participants.

Various staff methodologies of a just‐in‐time (JIT) apparel assembly cell with various numbers of walking workers, and various levels of process time variation were discussed and evaluated by simulation models. Decouplers are placed between two workstations (or subcells) to improve capability and flexibility in an apparel cell. Decouplers enable JIT pull cells to operate with minimum stock‐on‐hand and allow parts and information to flow in opposite directions. Decouplers also provide the JIT pull cell with “make one, check one, and pass one on” capability. A manned assembly cell’s throughput rate depends on the number of workers in the cell and on the variation in each worker’s processing time. Normally, as the processing time variation increases, the throughput rate decreases. However, these simulation studies show that doubling the decoupler capacity increases the cell’s output, even as the processing time variation increases.

Addresses the dynamic, continual‐improvement nature of the JIT implementation process. Learning curves are incorporated to analyse the impact of continual reduction of processing time variation over time. The results provide valuable information on the relationship between the level of processing time variation, the output rate of the production system, and inventory between work processes. The methodology used in this study incorporates an additional dimension in analysing JIT. It also provides a general and effective tool for decision makers facing the complex task of implementing pull production processes.

The purpose of this paper is to provide some insights into the exchange rate exposure of Australian stock returns.

Using a dynamic econometric approach that allows for both asymmetry and time‐varying risk exposures in both the exchange rate variable and the market variable, a large sample of Australian firms were tested over the period of January 2001 and December 2005. The data were analysed using three different classification methods, forming portfolios according to industry sector, size deciles, and censoring deciles.

Although the evidence of exchange rate exposure is limited across the sample of industries, the following were found: a time‐varying asymmetric effect primarily in the utilities sector, time‐varying exposure in the materials and energy sectors, and an asymmetric effect in the technology sector. Further, some time‐varying asymmetric exchange rate exposure was found across most size and censoring deciles and also substantial evidence of a positive asymmetric effect in the market beta across all three classification methods.

This approach varies from previous studies in this area that only allow for asymmetry and time variation in exchange rate exposures. The paper also examines the Australian stock market, a market which has not been extensively tested in this area of empirical research.

The purpose of this study is to trace time variation paths in risk sensitivities of bank stock returns over the period of 1990-2014, which covers one of most serious financial crises in the history of the USA.

This study programs the flexible least squares (FLS) approach (Kalaba and Testfatsion, 1988, 1989 and 1990) with R, a free statistical computing and graphics software, to estimate the three-factor model developed by He and Reichert (2003) to examine changes in risk sensitivities of bank stocks to the stock market, bond market and real estate market.

Both FLS and ordinary least squares (OLS) results indicate that the bond market (interest rate) sensitivity of bank stock returns experiences dramatic changes. It is significantly positive before the 2006 subprime mortgage crisis (11/1990 to 5/2006), reduces to insignificant in a short period of 11/2006 to 10/2008 and turns into significantly negative during the period of 11/2008-11/2014. Further, results of this study indicate that bank stocks negatively respond to changes in housing prices in the period of 11/1990-1/1994 and after that the sensitivity turns into significantly positive. The significant shifts in risk sensitivities of banks stock returns coincide with alterations in long-term interest rates and monetary policy, especially the enormously stimulative monetary policy after the financial crisis in 2008.

This study programs the FLS approach with R and uses the FLS approach to demonstrate the time variation paths of risk sensitivities of bank stocks over a period that covers the 2008 financial crisis. The OLS results verify the significant shifts in risk sensitivities suggested by the FLS estimates.

This paper proposes a knowledge management approach for managing uncertainty in manufacturing enterprises.

The knowledge management approach consists of a knowledge‐enriched manufacturing system, which is modelled using SIMAN simulation language and programmed using Visual Basic applications. A knowledge‐based planning module and an execution platform are simulated so that signals could be transferred, and configuration to the planned parameters could be made, in order to minimise variations due to uncertainties. A reference architecture and intelligent agent are created to store tacit knowledge and create explicit knowledge, respectively.

Manufacturing enterprises should use both tacit knowledge about uncertainties and buffering and dampening techniques, simultaneously with the explicit knowledge that is generated by the intelligent agent, for managing uncertainty. The design of the knowledge management approach enables easy integration with material requirements planning, manufacturing resource planning or enterprise resource planning systems, and complements with the adoption of advanced technology.

A new concept – management by valued‐added urgency, emerges that underpins the knowledge management approach. It is grounded from the previous literature on managing uncertainty classified into: masking approach; standardising approach; prioritising approach; and optimising approach and extended Westbrook's priority management theory. This concept focuses selectively on value‐added changes that need to be made to counteract variations caused by significant uncertainty.

The problem of assembly line balancing is to assign different tasks to individual workstations for ensuring the sum of task times at any station not exceeding the station time. Standard minute time is generally used in the clothing industry as a predictor of sewing speed and production efficiency. In the clothing industry, the standard minute time derived from the work study methods is generally assumed as a constant for line balancing. However, a lot of factors cause variations on operational time of the same task such as the fabrics and sub‐materials, performance of the machinery, working environment and quality level of the product. With the aid of an illustrating example selected from a men’s shirt manufacturing factory, the effect of time variations for assembly line balancing has been studied in this paper.

The purpose of this paper is to estimate volatility in African stock markets (ASMs), taking account of periodic level shifts in the mean level of volatility, where the regime shifts are determined endogenously.

Volatility estimates are incorporated into standard volatility models to assess the impact of structural breaks on volatility persistence, long memory and forecasting performance for ASMs.

The results presented here indeed suggest that persistence and long memory in volatility are overestimated when regime shifts are not accounted for. In particular, application of breakpoint tests and a moving average procedure suggest that unconditional volatility displays substantial time variation.

A modification of the standard generalised autoregressive conditional heteroscedasticity model to allow for time variation in the unconditional variance generates improved volatility forecasting performance for some African markets.

This paper describes one of the first studies to incorporate endogenously determined regime shifts into volatility estimates and assess the impact of structural breaks on volatility persistence, long memory and forecasting performance for ASMs.

This study reexamines fiscal deficit sustainability in South Africa.

The study applies three cointegration testing approaches, namely testing for multiple structural changes in a cointegrated regression model, time-varying cointegration test and asymmetric cointegration test.

The results point to the existence of a level relationship between government revenue and spending. In addition, the long-run equilibrium relationship between government revenue and spending in South Africa is found to be characterized by breaks. As such, assuming a constant cointegrating slope may be misleading. Results from time-varying cointegration and an estimation of a cointegrated two-break model indicate that cointegrating coefficient has been time-varying but has remained less than 1 for the entire study period, indicating that fiscal deficits have been weakly sustainable. This finding is also confirmed by the results from an estimated asymmetric error correction model.

In view of the findings, authorities should put in place policies to improve the fiscal budgetary stance and reinforce the sustainability of the fiscal deficits in South Africa. Among other things, South Africa could undertake reforms to state-owned companies to reduce their reliance on public funds, slow down the pace of the public sector wage growth and devise effective economic measures to boost long-term growth. In addition, tax compliance and other revenue collection measures should be enhanced for additional tax revenue.

The contribution of this study is twofold; first, the study uses a long series of annual data spanning over a century, from 1913 to 2020. Indeed, cointegration is better modeled using long spans of time series data. Second, to examine the existence of a level relationship between spending and revenue, the study uses cointegration tests which allow capturing time-variation in the cointegrating slope coefficient, and accounting for asymmetries in the relationship between government spending and revenue. It is important to allow for time-variation in the cointegrating slope coefficient, especially when it has been hardly treated in the empirical literature on fiscal deficit sustainability. Allowing for time-variation in the cointegrating slope coefficient helps us to analyze fiscal deficit sustainability by periods of time. Indeed, the degree of fiscal sustainability can change from one time period to another.