22 resultados para SUPPLY AND DEMAND


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Cities are oftentimes seen as undergoing a process of "emergence" in the "new economy." However, this process has largely remained empirically underdetermined. This article examines the intra-city geography of emerging businesses in newly dominant sectors of the urban economy. The change in dominant sectors coincides with a shift towards small- and medium-sized businesses, creating new economic opportunities for urban residential areas. The residential neighborhood is introduced as a place where supply and demand side drivers operate to attract or limit such new economic activity. Allen Scott's perspective of the cognitive-cultural economy is used to analyze which neighborhoods are flourishing sites of the cognitive-cultural sectors. His perspective on industries that are on the rise in urban environments and their growth potential proves very valuable. Social demographic characteristics on the level of the neighborhood are used as predictors of the composition of the local economy. The analyses show that in particular wealthy, gentrified neighborhoods are more prone than others to becoming "hubs" of the cognitive-cultural economy. However, disadvantaged neighborhoods may under certain conditions serve as incubators for business start-ups as they offer low-rent office spaces. This has important consequences for their future economic growth potential as well as the distribution of successful businesses in the city. © 2013 Urban Affairs Association.

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This paper details the development and evaluation of AstonTAC, an energy broker that successfully participated in the 2012 Power Trading Agent Competition (Power TAC). AstonTAC buys electrical energy from the wholesale market and sells it in the retail market. The main focus of the paper is on the broker’s bidding strategy in the wholesale market. In particular, it employs Markov Decision Processes (MDP) to purchase energy at low prices in a day-ahead power wholesale market, and keeps energy supply and demand balanced. Moreover, we explain how the agent uses Non-Homogeneous Hidden Markov Model (NHHMM) to forecast energy demand and price. An evaluation and analysis of the 2012 Power TAC finals show that AstonTAC is the only agent that can buy energy at low price in the wholesale market and keep energy imbalance low.

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The amplification of demand variation up a supply chain widely termed ‘the Bullwhip Effect’ is disruptive, costly and something that supply chain management generally seeks to minimise. Originally attributed to poor system design; deficiencies in policies, organisation structure and delays in material and information flow all lead to sub-optimal reorder point calculation. It has since been attributed to exogenous random factors such as: uncertainties in demand, supply and distribution lead time but these causes are not exclusive as academic and operational studies since have shown that orders and/or inventories can exhibit significant variability even if customer demand and lead time are deterministic. This increase in the range of possible causes of dynamic behaviour indicates that our understanding of the phenomenon is far from complete. One possible, yet previously unexplored, factor that may influence dynamic behaviour in supply chains is the application and operation of supply chain performance measures. Organisations monitoring and responding to their adopted key performance metrics will make operational changes and this action may influence the level of dynamics within the supply chain, possibly degrading the performance of the very system they were intended to measure. In order to explore this a plausible abstraction of the operational responses to the Supply Chain Council’s SCOR® (Supply Chain Operations Reference) model was incorporated into a classic Beer Game distribution representation, using the dynamic discrete event simulation software Simul8. During the simulation the five SCOR Supply Chain Performance Attributes: Reliability, Responsiveness, Flexibility, Cost and Utilisation were continuously monitored and compared to established targets. Operational adjustments to the; reorder point, transportation modes and production capacity (where appropriate) for three independent supply chain roles were made and the degree of dynamic behaviour in the Supply Chain measured, using the ratio of the standard deviation of upstream demand relative to the standard deviation of the downstream demand. Factors employed to build the detailed model include: variable retail demand, order transmission, transportation delays, production delays, capacity constraints demand multipliers and demand averaging periods. Five dimensions of supply chain performance were monitored independently in three autonomous supply chain roles and operational settings adjusted accordingly. Uniqueness of this research stems from the application of the five SCOR performance attributes with modelled operational responses in a dynamic discrete event simulation model. This project makes its primary contribution to knowledge by measuring the impact, on supply chain dynamics, of applying a representative performance measurement system.

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Manufacturer–reseller interactions are becoming more technology-enabled as channels of distribution increasingly utilize e-business tools on the Internet. This research examines the performance consequences for resellers as these technological advances are applied to distribution activities between channel members. Using a sample of 216 resellers of computer products, the research explores the impact of e-business tools in 2 areas of manufacturer–reseller interactions: supply tasks and demand tasks. The results suggest that e-business in supply tasks increases relationship coordination between manufacturer and reseller, whereas e-business in demand tasks increases coordination as well as conflict within the channel dyad. The increase of conflict constitutes a potential “dark side” of e-business in channel relationships that may provide an explanation for e-business implementation failures and negative returns on investment in technology.

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Benchmarking techniques have evolved over the years since Xerox’s pioneering visits to Japan in the late 1970s. The focus of benchmarking has also shifted during this period. By tracing in detail the evolution of benchmarking in one specific area of business activity, supply and distribution management, as seen by the participants in that evolution, creates a picture of a movement from single function, cost-focused, competitive benchmarking, through cross-functional, cross-sectoral, value-oriented benchmarking to process benchmarking. As process efficiency and effectiveness become the primary foci of benchmarking activities, the measurement parameters used to benchmark performance converge with the factors used in business process modelling. The possibility is therefore emerging of modelling business processes and then feeding the models with actual data from benchmarking exercises. This would overcome the most common criticism of benchmarking, namely that it intrinsically lacks the ability to move beyond current best practice. In fact the combined power of modelling and benchmarking may prove to be the basic building block of informed business process re-engineering.

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This paper is a cross-national study testing a framework relating cultural descriptive norms to entrepreneurship in a sample of 40 nations. Based on data from the Global Leadership and Organizational Behavior Effectiveness project, we identify two higher-order dimensions of culture – socially supportive culture (SSC) and performance-based culture (PBC) – and relate them to entrepreneurship rates and associated supply-side and demand-side variables available from the Global Entrepreneurship Monitor. Findings provide strong support for a social capital/SSC and supply-side variable explanation of entrepreneurship rate. PBC predicts demand-side variables, such as opportunity existence and the quality of formal institutions to support entrepreneurship.

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Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations.