Translating means-end research into advertising strategy using the meccas model

Eberhard, Daniel Mark

doi:10.3280/ecag2017-003003

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…In means‐end chain analysis, qualitative data are transformed into quantitative results which tends to have high levels of appeal for marketing research. Consequently many applications of means‐end chain analysis are found in market research covering product development and evaluation (Costa et al, 2004; Patrick & Xu, 2018; Reynolds & Phillips, 2009), advertising (Bech‐Larsen, 2001; Eberhard, 2017), and market segmentation (Grunert, 2019; Pezeshki et al, 2019; Ter Hofstede et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Methodological considerations on the means‐end chain analysis revisited

Kilwinger

Dam

2021

Psychology and Marketing

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Means‐end chain analysis has been applied in a wide range of disciplines to understand consumer behavior. Despite its widespread acceptance there is no standardized method to analyze data. The effects of different analyses on the results are largely unknown. This paper makes a contribution to the methodological debate by comparing different ways to analyze means‐end chain data. We find that (1) a construct that is not mentioned can still be important to a respondent; (2) coding constructs at the same basic level or condensing constructs at a superordinate level lead to different results and both an increase and decrease of information; (3) aggregating data can be based on different algorithms which influences the results. Among available software packages there is no consistency in the used algorithm; (4) before applying means‐end chain analysis in a new research area the validity of assumptions underlying the research model should be evaluated. We conclude there is no universal “best way” to means‐end chain analysis, the most suitable approach depends on the research question. Research concerning how products are evaluated can best apply number‐of‐respondents‐based aggregation and low levels of condensation. Research concerning why products are valued can best apply frequency‐of‐responses‐based aggregation and high levels of condensation.

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Section: Introductionmentioning

confidence: 99%

Methodological considerations on the means‐end chain analysis revisited

Kilwinger

Dam

2021

Psychology and Marketing

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“…In means-end chain analysis, qualitative data are transformed into quantitative results which tends to have high levels of appeal for marketing research. Consequently many applications of means-end chain analysis are found in market research covering product development and evaluation (Costa et al, 2004;Patrick & Xu, 2018;, advertising (Bech-Larsen, 2001;Eberhard, 2017), and market segmentation (Grunert, 2019;Pezeshki et al, 2019;Ter Hofstede et al, 1999).…”

Section: T R Od U Ct I O Nmentioning

confidence: 99%

Method matters : Exploration and reflection on the study of farmers’ demand for vegetatively propagated seed

Kilwinger¹

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Supporting such new theoretical perspectives on adoption requires methods that are capable of capturing new aspects they include. Currently, a household survey is the most common research method to understand farmers' adoption and demand of (vegetative propagated) planting material (Pircher and Almekinders, 2021; Walker and Alwang, appropriately developed, knowledge is truth, meaning it is certain, accurate and coherent with reality (Park et al., 2020). The other worldview takes the assumption that reality is subjectively created. This does not mean that the existence of an external reality is denied, but rather that each of us constructs their own reality through interpretation of perceptual experiences of this external world (Jonassen, 1991). How one constructs knowledge is a function of the prior experiences, mental structures, and beliefs that one uses to interpret objects and events.When studying something as complex as seed systems, which regard the interaction of aspects in the biophysical and social sphere, diverse epistemologies are needed. As an illustration for these different world views, and how they can be applicable to study a single object, we can use a plant. There is a common statement that says: 'there is no such thing as a weed, only plants growing in inconvenient places'. What is an inconvenient place for a plant to grow, is subjective. Similarly, it can be stated that there are no resources, resources 'become' at the moment value can be created from them (De Gregori, 1987;Zimmermann, 1933). Thus, there might be a single reality out there which includes the existence of a plant, but this plant can be regarded either as an inconvenience (then we call it a weed), a resource (then we call it a crop), or anything else based on its subjective value. The construction and transformation of 'things' into something valuable, worthless or even problematic is largely determined by societies norms and values, science, and technology. Research methods as the object of studyAcknowledging such different worldviews makes us further reflect on what research methods exactly are and do. One view of method is that reality has a definite form that is independent of the methods used to study it, and that the job of methods is to discover and describe this reality as best may be (Law, 2009). The social life of methods contests that research methods are merely tools to learn about the world which has definite features that can be reported and turned into data. According to Law et al. (2011), methods have a double social life. Methods are social because they are constituted by the social world, are created with a purpose, and reflect on the concern of their advocates. They are also social because they help constitute and organize the world. In

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