Eisingerich, Andreas Benedikt

2013-11, Stöckl, Albert, Rinke, Wolfram, Eisingerich, Andreas Benedikt

Tourism experiences inevitably evoke affective consumer reactions i.e. pleasure or displeasure. Their impacts on consumer satisfaction and emotional attachment to places in a tourism, leisure or recreational context are subsequently of crucial importance in tourism marketing. Earlier research on this topic shows that the stimulus of an affective tourism experience may extend far beyond short-term effects such as satisfaction. Therefore, long-term customer relationships i.e. attachment have to be investigated more closely, especially with respect to the interrelationships among influencing factors.

2016, Stöckl, Albert, Rinke, Wolfram, Eisingerich, Andreas Benedikt

Tourism experiences in viticultural areas tend to evoke strong positive and affective consumer reactions (Yuan et al., 2008). Ideally they lead to sentiments such as pleasure, satisfaction, nostalgia, or even emotional attachment (Gross & Brown, 2006; Hammitt, Backlund, & Bixler, 2006). Studies show that satisfaction is strongly related to attachment to a certain place (Williams & Huffman, 1986) and pleasure (Orth et al., 2011) and can lead to consumer loyalty (Dodd, 2000; Alexandris, Kouthouris & Meligdis, 2006) as well as greater spending (Moore & Graefe 1994; Dodd, 2000; Kyle, Absher & Graefe, 2003). In addition, research showed that visitors who are familiar with a region, i.e., they have visited the destination before, are more likely to develop strong attachment to that place over time (Williams, Patterson & Roggenbuck 1992). In order to analyse consumers and their wine-tourism related reactions of place and wine-tourism-experience evoked reactions and perceptions, the overarching research question of this study consequently is: Which relationships between place and experience parameters and consumer evaluations can be detected in a wine-tourism context?

2016, Stöckl, Albert, Rinke, Wolfram, Eisingerich, Andreas Benedikt

2014-05-14, Rinke, Wolfram, Stöckl, Albert, Eisingerich, Andreas Benedikt

2016-05, Rinke, Wolfram C., Stöckl, Albert, Eisingerich, Andreas Benedikt

Using artificial neural networks (ANN) to model an observed process is state of the art in engineering and is receiving more and more attention in social or marketing research. As shown in previous publications static data analytics, like an ANN based dependency matrix (DM), creates a better understanding of the relationship between dependant and independent variables of the observed system. To gain a better understanding of the behaviour and dynamics of an observed system a further step has been taken. . This is accomplished by transforming the ANN-DM into its open form equivalent. This is represented by several ANN models, one for each observed model parameter. An algorithm, which was published by the author, can be used for this transformation. The final result makes it possible to study the dynamic relationships between all parameters, including simulation and conclusions on its inverted model behaviour. The author will show based on an example from tourism marketing, how this inverse modelling approach can be applied and what new knowledge can be extracted from the achieved simulation results. The conclusion is that ANN based algorithms makes it possible to model an observed system in a static but also in a dynamic way. Inverting the model generates a deeper insight view and additional knowledge about an observed system. The resulting applications range from supporting strategic decisions to predictive control or model based simulation.