1000 resultados para Sales, François de


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Many international business (IB) studies have used foreign direct investment (FDI) stocks to measure the aggregate value-adding activity of multinational enterprises (MNE) affiliates in host countries. We argue that FDI stocks are a biased measure of that activity, because the degree to which they overestimate or underestimate affiliate activity varies systematically with host-country characteristics. First, most FDI into countries that serve as tax havens generate no actual productive activity; thus FDI stocks in such countries overestimate affiliate activity. Second, FDI stocks do not include locally raised external funds, funds widely used in countries with well-developed financial markets or volatile exchange rates, resulting in an underestimation of affiliate activity in such countries. Finally, the extent to which FDI translates into affiliate activity increases with affiliate labor productivity, so in countries where labor is more productive, FDI stocks also result in an underestimation of affiliate activity. We test these hypotheses by first regressing affiliate value-added and affiliate sales on FDI stocks to calculate a country-specific mismatch, and then by regressing this mismatch on a host country's tax haven status, level of financial market development, exchange rate volatility, and affiliate labor productivity. All hypotheses are supported, implying that FDI stocks are a biased measure of MNE affiliate activity, and hence that the results of FDI-data-based studies of such activity need to be reconsidered. [ABSTRACT FROM AUTHOR]

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The occurrence of symptoms in pollen allergy patients in urban areas may be affected by local environmental factors such as sources of pollution, natural and ornamental vegetation, local architecture impeding dispersion, etc. The aim of this study was to analyse the frequency of sensitization in pollen allergy patients and the relationship with antihistamine sales. For this study, a large number of clinical records, together with pharmaceutical and pollen data, were collected between 1999 and 2001 in the city of Córdoba, in the south of the Iberian Peninsula. Differences were observed in the symptoms suffered by pollen allergy patients in different areas of the city due to varying local emission of both biological and non-biological particles. Temporal distribution of symptoms over the three study years was influenced by meteorological factors, especially rainfall patterns; higher water supply to plants was associated with increased airborne pollen concentrations. Air pollution might be one of the main factors affecting the distribution of pollen allergy patients within the city. Recent years have seen a worsening of symptoms and increased sensitization to urban species such as plane-trees.

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Salespeople play a pivotal role in promoting new products. Therefore, managers need to know what control mechanism (i.e., output-based control, behavior-based control, or knowledge-based control) can improve their salespeople's new product sales performance. Furthermore, managers may be able to assist salespeople in performing better by having a strong market orientation. The literature has been inconsistent regarding the effects of sales management control mechanisms and has not yet incorporated market orientation into a sales management control framework. The current study surveyed 315 Taiwanese salespeople from publicly traded electronics companies with the aim of contributing to the sales management literature. The results show that sales management controls can directly affect salespeople's innovativeness, which, in turn, affects new product sales performance. However, sales management controls cannot affect performance directly. Furthermore, market orientation can positively moderate the relationship between salespeople's innovativeness and new product sales performance.

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Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

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W is the biggest electronic goods retailer in Portugal accounting with almost fifty percent of market share in its area. During the last years, many small W suppliers had to close their doors, and many others are in huge troubles. Among the reason for this situation, the huge bargaining power of W in the relationship seems crucial. The focus of the directed research will be in the after sales department where I did an internship from September 2014 to January 2015.