2 resultados para Optimization of product process

em Academic Archive On-line (Jönköping University; Sweden)


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Background: To align with the new trend of using social media in the marketing mix, product placement has been adapted to social media platforms as one strategy to create attention. Especially on Instagram, product placements have gained popularity among companies. While scholars have focused on measuring the effectiveness of the strategy, suggesting that credibility is one component necessary for success, a gap in the research is illuminated when focusing on what makes a product placement on Instagram credible. Previous studies regarding credibility and its relation to traditional media have concluded that there are some factors essential in consumers’ credibility evaluation process. Since social media differs from traditional media, there was a need to investigate the applicability of credibility to the social media platform Instagram. Purpose: The purpose of this thesis was to examine key factors of product placement on Instagram that influence credibility. Method: To meet the purpose of this thesis a study with a mixed method research design was conducted. The qualitative data was collected through semi-structured interviews with the intention to discover how consumers evaluate credibility. The scales and items developed from the findings of the qualitative study were tested using a questionnaire to identify which factors that have the most influence on consumers’ credibility assessment. Conclusions: The overall findings indicate that consumers evaluate credibility based upon source, message and receiver characteristics. The empirical evidence suggests that the Expertise of influencer, Professionalism of picture, Trustworthiness of influencer, Connection to influencer and Causes of irritation are the factors that have the most influence on consumers’ credibility assessment of product placement on Instagram. The findings further implies that it is not only the factor itself that influence, credibility can additionally be transferred from one factor to another.

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The usage of multi material structures in industry, especially in the automotive industry are increasing. To overcome the difficulties in joining these structures, adhesives have several benefits over traditional joining methods. Therefore, accurate simulations of the entire process of fracture including the adhesive layer is crucial. In this paper, material parameters of a previously developed meso mechanical finite element (FE) model of a thin adhesive layer are optimized using the Strength Pareto Evolutionary Algorithm (SPEA2). Objective functions are defined as the error between experimental data and simulation data. The experimental data is provided by previously performed experiments where an adhesive layer was loaded in monotonically increasing peel and shear. Two objective functions are dependent on 9 model parameters (decision variables) in total and are evaluated by running two FEsimulations, one is loading the adhesive layer in peel and the other in shear. The original study converted the two objective functions into one function that resulted in one optimal solution. In this study, however, a Pareto frontis obtained by employing the SPEA2 algorithm. Thus, more insight into the material model, objective functions, optimal solutions and decision space is acquired using the Pareto front. We compare the results and show good agreement with the experimental data.