Search results

This work aims to increase the service level and to reduce the inventory costs by combining the forecast and inventory model into one consistent forecast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used to identify, estimate, and predict the demand as well as optimize the inventory decision of intermittent demand series. In an extensive simulation study the new model is compared with a wide range of conventional forecast/inventory model combinations. By using the consistent approach, the mean inventory level is lowered whereas the service level is increased. Additionally, a modern multi-criteria inventory classification scheme is presented to distinguish different demand series clusters. Contents Classification Approaches to Identify Intermittent Demand Series Consistent Forecast-Based Inventory Model Extensive Comparison of the Inventory Performance Among Different Forecast/Inventory Model Combinations Target Group Students and researchers interested in business analytics and operations management Inventory managers and supply chain experts The Author Dr. Torben Engelmeyer works as a research assistant at the chair of International Economics - University of Wuppertal, Germany.

This article analyses the existing possibilities for using Standard Statistical Methods and Artificial Intelligence Methods for a short-term forecast and simulation of demand in the field of telecommunications. The most widespread methods are based on Time Series Analysis. Nowadays, approaches based on Artificial Intelligence Methods, including Neural Networks, are booming. Separate approaches will be used in the study of Demand Modelling in Telecommunications, and the results of these models will be compared with actual guaranteed values. Then we will examine the quality of Neural Network models.

'Forecasting tourism demand' is a text that no tourism professional can afford to be without. The tourism industry has experienced an overwhelming boom over recent years, and being able to predict future trends as accurately as possible is vital in the struggle to stay one step ahead of the competition. Building on the success of 'Practical Tourism Forecasting' this text looks at 13 methods of forecasting and with a user friendly style, 'Forecasting Tourism Demand' guides the reader through each method, highlighting its strengths and weaknesses and explaining how it can be applied to the touri

I present a theory of random consumer demand. The primitive is a collection of probability distributions on budgets. Axioms constrain these distributions, including analogues of preference axioms, such as transitivity, monotonicity and convexity. Results establish a complete representation of theoretically consistent demand. The theory's purpose is empirical application. To this end, the theory has desirable properties. Intrinsically stochastic, econometricians can apply it without adding extrinsic randomness in the form of errors. Random demand is parsimoniously represented by a single function on the consumption set. Finally, there exist practical methods for inference based on the theory, described in a companion paper.

Explores NATO's expanded influence now reaching as far as the Kyrgyz Republic and Tajikistan as well as the ironies of its predicted demise at the same time that it is experiencing global demand for its services as the unique supplier of western liberal and democratic norms through political and military means. But NATO's new activism may also be pointing toward a lack of Western strategy that discriminates between worthwhile and impractical operations by balancing political ends with military means, and this may lead to circumstances where NATO can no longer sustain its own multiple engagements. Adapted from the source document.

In this essay, the discussion proceeds from the public image of the functionary at the end of the Rákosi era, through the Kádárist policies of 'new sobriety' disciplining the functionary in order not to irritate and provoke the rest of society, to the new contrat sociale established by the mid-1960s in which the party-state apparatus class and the commoners join one another in pursuing shared (consumerist) ideas of good life and happiness, within the constraints and coping with the conditions of demand side abundance (the tension between consumerist aspirations, desires and an economy of sustained shortages). The article draws on archival sources as well as texts from contemporary cabarets and an analysis of the 1964 feature film, Don't Waste the Gas!, and its manuscript.

The Ethical Demand (1956) by K. E. Logstrup is one of the great works of modern moral philosophy: it is presented here in a new translation with introduction and notes. Logstrup sees morality in terms of our vulnerability to each other and how this gives rise to an 'ethical demand' on us to care for each other.

Supply chain professionals: master pioneering techniques for integrating demand and supply, and create demand forecasts that are far more accurate and useful! In Demand and Supply Integration, Dr. Mark Moon presents the specific design characteristics of a world-class demand forecasting management process, showing how to effectively integrate demand forecasting within a comprehensive Demand and Supply Integration (DSI) process. Writing for supply chain professionals in any business, government agency, or military procurement organization, Moon explains what DSI is, how it differs from approaches such as SandOP, and how to recognize the symptoms of failures to sufficiently integrate demand and supply. He outlines the key characteristics of successful DSI implementations, shows how to approach Demand Forecasting as a management process, and guides you through understanding, selecting, and applying the best available qualitative and quantitative forecasting techniques. You'll learn how to thoroughly reflect market intelligence in your forecasts; measure your forecasting performance; implement state-of-the-art demand forecasting systems; manage Demand Reviews, and much more.