999 resultados para Sales, Assensio , Obispo de Barcelona


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Current models of sales force strategy imply formidable information processing demands, which leads us to take a cognitive approach to studying the issue of sales force strategy. We focus on how top-level executives use mental models of sales force performance to simplify the issue of sales force strategy. We interviewed 74 senior executives responsible for their firms’ selling function using the repertory grid approach, as this methodology has been shown to be particularly effective at uncovering the collective cognitive maps on which executives’ decisions and behaviors are based. Executives identified a broad set of 37 strategic concepts that they felt distinguish the sales force efforts of directly competing companies. A second set of sales executives classified the 37 concepts into capabilities, resources, and organizational context concepts. Based on the classification results and feedback from both sets of executives, we developed research propositions for examining sales force strategy and provide directions for future research.

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Adaptive selling (AS) and customer-oriented selling (COS) constitute two key customer-directed selling behaviors for the success of the modern sales force. However, knowledge regarding the organizational factors that can induce salespeople to engage in those behaviors is strikingly limited. Against this background, we develop a comprehensive model that delineates the influences of formal and informal sales controls on AS and COS and, through them, on sales unit effectiveness. Based on a sample of sales managers in a major European Union country, we present new evidence that (a) formal and informal sales controls exert differential impact on salespeople's AS and COS behaviors; (b) AS directly and positively influences sales unit effectiveness; (c) COS affects sales unit effectiveness only indirectly, i.e. by fostering AS; and (d) outcome and cultural controls directly improve sales unit effectiveness. We conclude with a discussion of our findings for academics and practitioners.

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This paper uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting US home sales. The benchmark Bayesian model includes home sales, the price of homes, the mortgage rate, real personal disposable income, and the unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.

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Meir Kayserling

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Heinrich Graetz

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Meir Kayserling

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Fil: Sbordelati, Andrea Verónica.