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Rinke, Wolfram
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Official Name
Rinke, Wolfram
Alternative Name
Rinke, Wolfram C.
Main Affiliation
ÖGAI Österreichische Gesellschaft für Artificial Intelligence
AAWE American Association of Wine Economists
Akademische Titel
Dipl.-Ing.
Email
wolfram.rinke@fh-burgenland.at
ORCID
Scopus Author ID
57203619840
Status
staff
Research Outputs
Now showing 1 - 10 of 17
- PublicationUsing Data Mining to Determine Attachment Factors in Tourism: Gauging Affective Consumer Behaviour(2013-11)
; ; 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.112 1 - PublicationDo corporately organized wine producers cope better with unfavorable weather conditions than private wine estates? Hedonic pricing models for South African winesIn our research we want to estimate the effect of changing weather conditions on south African wine prices for both, small wine estates and corporately organized producers and to compare these results. We assume that the latter cope better with unfavourable weather conditions than private wine estates, whereas beneficial weather will be favourable for both of them. We focus on the South African domestic wine market, as prices on export markets are additionally influenced by other factors, such as marketing strategies, certifications, mark ups of wholesalers or retailers etc.
429 784 - PublicationAre South African grape growers aware of their climatic comparative advantages for growing certain grape varieties? A hedonic approach applying machine learningWe assume that each region has its own competitive advantage in growing certain grape varieties, as all varieties have different capabilities to cope with specific weather or climate conditions. In this paper we first analyze the effects of annual weather changes on yields in order to find, which weather is advantageous for which grape variety. This analysis should lead to some kind of ideal weather scenario for each grape variety (like dry and sunny with small rain etc.). In as second step the changing weather conditions in each region are reconciled with these scenarios in order to give recommendations where different grape varieties should be grown. In the third step we compare our recommendations with the distribution of grape varieties in South African wine regions and the uprooting and planting behavior of grape growers.
567 962 - PublicationBachelor Software Engineering und vernetzte Systeme Praxisprojekte 2023Inventory Management / Pegelhub – Die zentrale Datendrehscheibe für Pegeldaten / Schulgong – Neuentwicklung des altbekannten Pausengongs / Digitalisierung der Auswertung des Wissenstests der Feuerwehrjugend / Einrichtung einer Zeitreihendatenbank mit Benutzeroberfläche bei der FB
74 480 - PublicationConsumer preferences for certified wines in France: A comparison of sustainable labels(Firenze University Press, 2021)
; 89 1Scopus© Citations 10 - PublicationHave consumers escaped from COVID-19 restrictions by seeking variety? A Machine Learning approach analyzing wine purchase behavior in the United States(2023)
; Ho, Shuay-tsyrThe COVID-19 pandemic itself constitutes an environment for people to experience the potential loss of control and freedom due to social distancing measures and other government orders. Variety-seeking has been treated as a mechanism to regain a sense of self-control. Using Machine Learning model and household-level data with a focus on the wine market in the United States, this study showcases the changing variety-seeking behavior over the pandemic year of 2020, in which people’s perception of the status of restriction measures influences the degree of their use of variety-seeking behavior as a coping strategy. It is the shopping pattern and store environments that drive the behavioral responses in wine purchases to freedom-limited circumstances. Coupon use is associated with a lower variety-seeking tendency at the beginning of the stay-at-home order, but the variety level resumes when more time has passed in the restriction periods. Variety-seeking tendency increases with shopping frequency at the beginning of the social distancing measure but decreases to a level lower than all the non-restriction periods.11 1 - PublicationPricing Models for German Wine: Hedonic Regression vs. Machine LearningThis article examines whether there are different hedonic price models for different German wines by grape variety, and identifies influential factors that focus on weather variables and direct and indirect quality measures for wine prices. A log linear regression model is first applied only for Riesling, and then machine learning is used to find hedonic price models for Riesling, Silvaner, Pinot Blanc, and Pinot Noir. Machine learning exhibits slightly greater explanatory power, suggests adding additional variables, and allows for a more detailed interpretation of results. Gault&Millau points are shown to have a significant positive impact on German wine prices. The log linear approach suggests a huge effect of different quality categories on the wine prices for Riesling with the highest price premiums for Auslese and “Beerenauslese/Trockenbeerenauslese/Eiswein (Batbaice),” while the machine learning model shows, that additionally the alcohol level has a positive effect on wines in the quality categories “QbA,” “Kabinett,” and “Spätlese,” and a mostly negative one in the categories “Auslese” and “Batbaice.” Weather variables exert different affects per grape variety, but all grape varieties have problems coping with rising maximum temperatures in the winter and with rising minimum and maximum temperatures in the harvest season.
738 2Scopus© Citations 10 - PublicationKnowledge Extraction and Advanced Analyses Through Inverse Modelling Using Artificial Neural NetworksUsing 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.
132 2 - PublicationBachelor Software Engineering und vernetzte Systeme Praxisprojekte 2022Entwicklung eines Tools zur Organisierung von Curricula / Modernisierung einer bestehenden IoT-Plattform bei FIB / Inventarmanagement / Pegelhub - Die zentrale Datendrehscheibe für Pegeldaten
109 462 - PublicationIdentifying relationships between place and experience parameters and consumer evaluations in a wine tourism contextTourism 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?
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