843 resultados para Public relations strategy


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The present study demonstrates how consumers can suffer from sequential overchoice. Customizing a tailor-made suit from combined-attribute choices (e.g., deciding on color and fabric in combination) leads to less satisfaction and less additional consumption than customizing it from single-attribute choices (e.g., deciding on color, then on fabric). The effect is mediated by information overload and moderated by consideration set size.

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In eWOM the relationship between the consumer and the reviewer is weak. Still, the present study argues that social information, for example the reviewer`s user picture, influences the product evaluation. By applying balance theory we predict that the evaluation of the recommended product is a function of the induced attitude towards the reviewer and the valence of the review. By utilizing either positive or negative user pictures and either positive or negative reviews, we confirmed the hypothesized interaction. Consumers rated a negatively reviewed product more favorable when the reviewer used a negative user picture, compared to a positive user picture.

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When viewing web-consumer reviews consumers encounter the reviewers in an anonymous environment. Although their interactions are only virtual they still exchange social information, e.g. often reviewers refer to their proficiency or consumption motives within the review texts. Do these social information harm the viewers’ perception of the recommended products? The present study addresses this question by applying the paradigm of social comparison (Mussweiler, 2003) to web-consumer reviews. In a laboratory experiment with a student sample (n = 120) we manipulated the perceived similarity between reviewer and viewer and the perceived proficiency of the reviewer. A measurement of achievement goals (Elliott & McGregor, 2001) and average number of hours of study prior to the experiment allowed to introduce the reviewer as high [low] in proficiency and similar [dissimilar] in achievement goals. As predicted, the viewer’s evaluation of the recommended products differed as a function of this social information. Contrasting with the reviewer led to devaluing the products recommended by a proficient but dissimilar reviewer. However, against our prediction social comparison with the reviewer did not affect the viewer`s self-evaluation. Whether social information in web-product reviews affects the viewer`s self-evaluation and induces both social comparison processes remains an open question. Future studies aim to address this by manipulating the informational focus of the viewer, rather than the perceived similarity between viewer and reviewer. So far, the present study extends the application of social comparison to consumption environments and contributes to the understanding of the virtual social identity.

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This paper deals with scheduling batch (i.e., discontinuous), continuous, and semicontinuous production in process industries (e.g., chemical, pharmaceutical, or metal casting industries) where intermediate storage facilities and renewable resources (processing units and manpower) of limited capacity have to be observed. First, different storage configurations typical of process industries are discussed. Second, a basic scheduling problem covering the three above production modes is presented. Third, (exact and truncated) branch-and-bound methods for the basic scheduling problem and the special case of batch scheduling are proposed and subjected to an experimental performance analysis. The solution approach presented is flexible and in principle simple, and it can (approximately) solve relatively large problem instances with sufficient accuracy.

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Car manufacturers increasingly offer delivery programs for the factory pick-up of new cars. Such a program consists of a broad range of event-marketing activities. In this paper we investigate the problem of scheduling the delivery program activities of one day such that the sum of the customers’ waiting times is minimized. We show how to model this problem as a resource-constrained project scheduling problem with nonregular objective function, and we present a relaxation-based beam-search solution heuristic. The relaxations are solved by exploiting a duality relationship between temporal scheduling and min-cost network flow problems. This approach has been developed in cooperation with a German automaker. The performance of the heuristic has been evaluated based on practical and randomly generated test instances.

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We study a real-world scheduling problem arising in the context of a rolling ingots production. First we review the production process and discuss peculiarities that have to be observed when scheduling a given set of production orders on the production facilities. We then show how to model this scheduling problem using prescribed time lags between operations, different kinds of resources, and sequence-dependent changeovers. A branch-and-bound solution procedure is presented in the second part. The basic principle is to relax the resource constraints by assuming infinite resource availability. Resulting resource conflicts are then stepwise resolved by introducing precedence relationships among operations competing for the same resources. The algorithm has been implemented as a beam search heuristic enumerating alternative sets of precedence relationships.

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An Advanced Planning System (APS) offers support at all planning levels along the supply chain while observing limited resources. We consider an APS for process industries (e.g. chemical and pharmaceutical industries) consisting of the modules network design (for long–term decisions), supply network planning (for medium–term decisions), and detailed production scheduling (for short–term decisions). For each module, we outline the decision problem, discuss the specifi cs of process industries, and review state–of–the–art solution approaches. For the module detailed production scheduling, a new solution approach is proposed in the case of batch production, which can solve much larger practical problems than the methods known thus far. The new approach decomposes detailed production scheduling for batch production into batching and batch scheduling. The batching problem converts the primary requirements for products into individual batches, where the work load is to be minimized. We formulate the batching problem as a nonlinear mixed–integer program and transform it into a linear mixed–binary program of moderate size, which can be solved by standard software. The batch scheduling problem allocates the batches to scarce resources such as processing units, workers, and intermediate storage facilities, where some regular objective function like the makespan is to be minimized. The batch scheduling problem is modelled as a resource–constrained project scheduling problem, which can be solved by an efficient truncated branch–and–bound algorithm developed recently. The performance of the new solution procedures for batching and batch scheduling is demonstrated by solving several instances of a case study from process industries.

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We present results of a benchmark test evaluating the resource allocation capabilities of the project management software packages Acos Plus.1 8.2, CA SuperProject 5.0a, CS Project Professional 3.0, MS Project 2000, and Scitor Project Scheduler 8.0.1. The tests are based on 1560 instances of precedence– and resource–constrained project scheduling problems. For different complexity scenarios, we analyze the deviation of the makespan obtained by the software packages from the best feasible makespan known. Among the tested software packages, Acos Plus.1 and Project Scheduler show the best resource allocation performance. Moreover, our numerical analysis reveals a considerable performance gap between the implemented methods and state–of–the–art project scheduling algorithms, especially for large–sized problems. Thus, there is still a significant potential for improving solutions to resource allocation problems in practice.

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The paper deals with batch scheduling problems in process industries where final products arise from several successive chemical or physical transformations of raw materials using multi–purpose equipment. In batch production mode, the total requirements of intermediate and final products are partitioned into batches. The production start of a batch at a given level requires the availability of all input products. We consider the problem of scheduling the production of given batches such that the makespan is minimized. Constraints like minimum and maximum time lags between successive production levels, sequence–dependent facility setup times, finite intermediate storages, production breaks, and time–varying manpower contribute to the complexity of this problem. We propose a new solution approach using models and methods of resource–constrained project scheduling, which (approximately) solves problems of industrial size within a reasonable amount of time.

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This paper is concerned with the modelling of storage configurations for intermediate products in process industries. Those models form the basis of algorithms for scheduling chemical production plants. Different storage capacity settings (unlimited, finite, and no intermediate storage), storage homogeneity settings (dedicated and shared storage), and storage time settings (unlimited, finite, and no wait) are considered. We discuss a classification of storage constraints in batch scheduling and show how those constraints can be integrated into a general production scheduling model that is based on the concept of cumulative resources.