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Article
Publication date: 1 April 1993

Colin Armistead and John Mapes

Reports the results of a survey of manufacturing managers to assesstheir perception of the changing manufacturing task and the role of themanufacturing manager. Within this…

1849

Abstract

Reports the results of a survey of manufacturing managers to assess their perception of the changing manufacturing task and the role of the manufacturing manager. Within this context investigates the contribution of new manufacturing techniques and approaches, the involvement of manufacturing staff in service factory roles and the steps to increase integration across the value chain on manufacturing performance.

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Logistics Information Management, vol. 6 no. 4
Type: Research Article
ISSN: 0957-6053

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Article
Publication date: 1 February 1992

Colin Armistead and John Mapes

Describes how the increasing emphasis on customer service‐basedperformance measures changes the way in which we need to manageoperations along the total supply chain from raw…

518

Abstract

Describes how the increasing emphasis on customer service‐based performance measures changes the way in which we need to manage operations along the total supply chain from raw materials to end user. Senior managers at Caterpillar, General Motors, ICL, Philips and Rank Xerox were interviewed about the steps that they have taken to achieve greater supply chain integration and the problems to be overcome before further progress can be achieved. Describes the changes that have been necessary to achieve greater supply chain integration and discusses the likely impact of these changes on the future role of the operations manager.

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Logistics Information Management, vol. 5 no. 2
Type: Research Article
ISSN: 0957-6053

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Article
Publication date: 1 October 1993

John Mapes

When a production system is operating at close to capacity then,after a period of high demand, it may take some time to restore stocksto the level necessary to provide a given…

552

Abstract

When a production system is operating at close to capacity then, after a period of high demand, it may take some time to restore stocks to the level necessary to provide a given level of stockout risk. During this period the risk of a stockout will be higher than intended. Uses simulation to show how customer service levels fall dramatically as average production levels approach available capacity and to determine the increases in levels of safety stock necessary to maintain desired customer service levels when capacity is limited.

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International Journal of Operations & Production Management, vol. 13 no. 10
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 1 July 2000

John Mapes, Marek Szwejczewski and Colin New

This report presents the preliminary findings of a research study to determine the factors which enable a manufacturing plant to simultaneously achieve high labour productivity…

2218

Abstract

This report presents the preliminary findings of a research study to determine the factors which enable a manufacturing plant to simultaneously achieve high labour productivity, fast, reliable delivery and high quality consistency. The conclusions are based on analysis of a database containing details of 953 manufacturing plants in the UK. Based on the performance measures mentioned above, a composite performance measure was calculated for each plant in the database. The plants were then divided into groups of high performers, medium performers and low performers. Using statistical analysis, those differences between the high and low‐performing plants that were significant were identified. The main factors differentiating high‐performing plants from the rest were those associated with low process variability, high schedule stability and more reliable deliveries by suppliers.

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International Journal of Operations & Production Management, vol. 20 no. 7
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 1 October 1997

John Mapes, Colin New and Marek Szwejczewski

A sample of 782 manufacturing plants drawn from the UK Best Factor Awards database was used to investigate the nature of trade‐offs between different measures of manufacturing…

2820

Abstract

A sample of 782 manufacturing plants drawn from the UK Best Factor Awards database was used to investigate the nature of trade‐offs between different measures of manufacturing performance. Each plant was ranked within its industry on each performance measure, a high ranking indicating good performance on that measure and a low ranking indicating poor performance. By comparing the ranking of each plant within its industry on each performance measure it was possible to determine the extent to which good performance on one measure was correlated with good performance on other measures. Rankings on added value per employee £, quality consistency, delivery reliability, speed of delivery and the rate of new product introduction were positively correlated, suggesting that good performance on each of these factors is associated with good performance on the rest. Only the extent to which a plant exhibited product variety showed conventional trade‐off characteristics, being negatively correlated with rankings on added value per employee £ and the rate of new product introduction. This implies that, provided that individual operating units can be organized so that each is focused on a relatively narrow product range, trade‐offs can be avoided.

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International Journal of Operations & Production Management, vol. 17 no. 10
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 10 August 2023

Zvi Schwartz, Jing Ma and Timothy Webb

Mean absolute percentage error (MAPE) is the primary forecast evaluation metric in hospitality and tourism research; however its main shortcoming is that it is asymmetric. The…

141

Abstract

Purpose

Mean absolute percentage error (MAPE) is the primary forecast evaluation metric in hospitality and tourism research; however its main shortcoming is that it is asymmetric. The asymmetry occurs due to over or under forecasts that introduce bias into forecast evaluation. This study aims to explore the nature of asymmetry and designs a new measure, one that reduces the asymmetric properties while maintaining MAPE’s scale-free and intuitive interpretation characteristics.

Design/methodology/approach

The study proposes and tests a new forecasting accuracy measure for hospitality revenue management (RM). A computer simulation is used to assess and demonstrate the problem of asymmetry when forecasting with MAPE, and the new measures’ (MSapeMER, that is, Mean of Selectively applied Absolute Percentage Error or Magnitude of Error Relative to the estimate) ability to reduce it. The MSapeMER’s effectiveness is empirically validated by using a large set of hotel forecasts.

Findings

The study demonstrates the ability of the MSapeMER to reduce the asymmetry bias generated by MAPE. Furthermore, this study demonstrates that MSapeMER is more effective than previous attempts to correct for asymmetry bias. The results show via simulation and empirical investigation that the error metric is more stable and less swayed by the presence of over and under forecasts.

Research limitations/implications

It is recommended that hospitality RM researchers and professionals adopt MSapeMER when using MAPE to evaluate forecasting performance. The MSapeMER removes the potential bias that MAPE invites due to its calculation and presence of over and under forecasts. Therefore, forecasting evaluations may be less affected by the presence of over and under forecasts and their ability to bias forecasting results.

Practical implications

Hospitality RM should adopt this measure when MAPE is used, to reduce biased decisions driven by the “asymmetry of MAPE.”

Originality/value

The MAPE error metric exhibits an asymmetry problem, and this paper proposes a more effective solution to reduce biased results with two major methodological contributions. It is first to systematically study the characteristics of MAPE’s asymmetry, while proposing and testing a measure that considerably reduces the amount of asymmetry. This is a critical contribution because MAPE is the primary forecasting metric in hospitality and tourism studies. The second methodological contribution is a procedure developed to “quantify” the asymmetry. The approach is demonstrated and allows future research to compare asymmetric characteristics among various accuracy measures.

Details

International Journal of Contemporary Hospitality Management, vol. 36 no. 6
Type: Research Article
ISSN: 0959-6119

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Publication date: 6 September 2019

Vivian M. Evangelista and Rommel G. Regis

Machine learning methods have recently gained attention in business applications. We will explore the suitability of machine learning methods, particularly support vector…

Abstract

Machine learning methods have recently gained attention in business applications. We will explore the suitability of machine learning methods, particularly support vector regression (SVR) and radial basis function (RBF) approximation, in forecasting company sales. We compare the one-step-ahead forecast accuracy of these machine learning methods with traditional statistical forecasting techniques such as moving average (MA), exponential smoothing, and linear and quadratic trend regression on quarterly sales data of 43 Fortune 500 companies. Moreover, we implement an additive seasonal adjustment procedure on the quarterly sales data of 28 of the Fortune 500 companies whose time series exhibited seasonality, referred to as the seasonal group. Furthermore, we prove a mathematical property of this seasonal adjustment procedure that is useful in interpreting the resulting time series model. Our results show that the Gaussian form of a moving RBF model, with or without seasonal adjustment, is a promising method for forecasting company sales. In particular, the moving RBF-Gaussian model with seasonal adjustment yields generally better mean absolute percentage error (MAPE) values than the other methods on the sales data of 28 companies in the seasonal group. In addition, it is competitive with single exponential smoothing and better than the other methods on the sales data of the other 15 companies in the non-seasonal group.

Details

Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78754-290-7

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Article
Publication date: 6 December 2021

Thomas R. O'Neal, John M. Dickens, Lance E. Champagne, Aaron V. Glassburner, Jason R. Anderson and Timothy W. Breitbach

Forecasting techniques improve supply chain resilience by ensuring that the correct parts are available when required. In addition, accurate forecasts conserve precious resources…

1031

Abstract

Purpose

Forecasting techniques improve supply chain resilience by ensuring that the correct parts are available when required. In addition, accurate forecasts conserve precious resources and money by avoiding new start contracts to produce unforeseen part requests, reducing labor intensive cannibalization actions and ensuring consistent transportation modality streams where changes incur cost. This study explores the effectiveness of the United States Air Force’s current flying hour-based demand forecast by comparing it with a sortie-based demand forecast to predict future spare part needs.

Design/methodology/approach

This study employs a correlation analysis to show that demand for reparable parts on certain aircraft has a stronger correlation to the number of sorties flown than the number of flying hours. The effect of using the number of sorties flown instead of flying hours is analyzed by employing sorties in the United States Air Force (USAF)’s current reparable parts forecasting model. A comparative analysis on D200 forecasting error is conducted across F-16 and B-52 fleets.

Findings

This study finds that the USAF could improve its reparable parts forecast, and subsequently part availability, by employing a sortie-based demand rate for particular aircraft such as the F-16. Additionally, our findings indicate that forecasts for reparable parts on aircraft with low sortie count flying profiles, such as the B-52 fleet, perform better modeling demand as a function of flying hours. Thus, evidence is provided that the Air Force should employ multiple forecasting techniques across its possessed, organically supported aircraft fleets. The improvement of the forecast and subsequent decrease in forecast error will be presented in the Results and Discussion section.

Research limitations/implications

This study is limited by the data-collection environment, which is only reported on an annual basis and is limited to 14 years of historical data. Furthermore, some observations were not included because significant data entry errors resulted in unusable observations.

Originality/value

There are few studies addressing the time measure of USAF reparable component failures. To the best of the authors’ knowledge, there are no studies that analyze spare component demand as a function of sortie numbers and compare the results of forecasts made on a sortie-based demand signal to the current flying hour-based approach to spare parts forecasting. The sortie-based forecast is a novel methodology and is shown to outperform the current flying hour-based method for some aircraft fleets.

Details

Journal of Defense Analytics and Logistics, vol. 5 no. 2
Type: Research Article
ISSN: 2399-6439

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Article
Publication date: 1 March 1990

Essam Mahmoud and C. Carl Pegels

A method is developed for evaluating forecasting models withrespect to both error and complexity in forecasting. Several types offorecasting accuracy measures (MSE, MPE, MAPE

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Abstract

A method is developed for evaluating forecasting models with respect to both error and complexity in forecasting. Several types of forecasting accuracy measures (MSE, MPE, MAPE, Theil′s U‐Statistic and a loss cost function) are examined and the approach is illustrated using short‐term forecasting methods, and weekly and four‐weekly data. The approach can, however, be applied equally to immediate, medium‐ and long‐term forecasting.

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International Journal of Operations & Production Management, vol. 10 no. 3
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 1 December 2001

Patrick J. Wilson and John Okunev

Over the last decade or so there has been an increased interest in combining the forecasts from different models. Pooling the forecast outcomes from different models has been…

997

Abstract

Over the last decade or so there has been an increased interest in combining the forecasts from different models. Pooling the forecast outcomes from different models has been shown to improve out‐of‐sample forecast test statistics beyond any of the individual component techniques. The discussion and practice of forecast combination has revolved around the pooling of results from individual forecasting methodologies. A different approach to forecast combination is followed in this paper. A method is used in which negatively correlated forecasts are combined to see if this offers improved out‐of‐sample forecasting performance in property markets. This is compared with the outcome from both the original model and with benchmark naïve forecasts over three 12‐month out‐of‐sample periods. The study will look at securitised property in three international property markets – the USA, the UK and Australia.

Details

Journal of Property Investment & Finance, vol. 19 no. 6
Type: Research Article
ISSN: 1463-578X

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