Addressing a product management's orphan: How to externally implement product eliminations in a B2B setting

Prigge, Jana-Kristin; Homburg, Christian; Fürst, Andreas

doi:10.1016/j.indmarman.2017.09.015

Cited by 7 publications

(3 citation statements)

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“…However, a high number of features and the resulting multitude of functions indicates to consumers that the product will have a large number of decision and usage options for which they must invest considerable effort, time, and energy to understand and make full use of the product (Bettman et al, 1991;Iyengar & Lepper, 2000;Meyer et al, 2008). This argumentation is consistent with prior research showing that a high quantity of functions is associated with a large number of decision and usage options that decrease consumers' ability to understand and use the product (Ji et al, 2006;Preece et al, 2002), thereby causing them to infer high learning costs and develop fears of erroneous product use (Goodman & Irmak, 2013;Meyer et al, 2008). Thus, a feature-rich product likely overwhelms consumers, which can lead them to assume considerable difficulty of learning and using the product and thus decrease their expected product usability.…”

Section: Effects Of Number Of Product Featuressupporting

confidence: 79%

“…This research offers recommendations on how best to manage the complexity of products across different stages of the innovation process, thereby maximizing the probability of new product success rather than failure and elimination (Cooper, 1979;Prigge et al, 2018). It provides guidance on product design (i.e., how to configure the various complexity dimensions) before market launch, and after market launch, it offers advice on product advertising and selling (i.e., which messaging about these dimensions to send to target groups).…”

Section: Practical Implicationsmentioning

confidence: 99%

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How product complexity affects consumer adoption of new products: The role of feature heterogeneity and interrelatedness

Fürst

Pecornik

Hoyer

2023

J. of the Acad. Mark. Sci.

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Recent technological advancements allow companies to incorporate increasingly heterogeneous and interrelated features into their products, which heightens the products’ complexity. In four experimental studies conducted with two product categories, this article reveals similarities and differences in terms of how the heterogeneity and interrelatedness of product features influence consumer attitudes (i.e., expected product usability and capability) and, in turn, purchase intentions. Moreover, it shows that both neglected dimensions of product complexity affect the corresponding influence of the number of product features but do so in considerably different ways. The findings suggest that companies can foster consumer adoption by deemphasizing a product’s feature heterogeneity, thereby avoiding low expected product usability, and by emphasizing its feature interrelatedness, thereby promoting high expected product capability. This article provides insights into how companies can manage the complexity of products during both product design (i.e., before market launch) and product advertising and selling (i.e., after market launch).

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Section: Effects Of Number Of Product Featuressupporting

confidence: 79%

Section: Practical Implicationsmentioning

confidence: 99%

How product complexity affects consumer adoption of new products: The role of feature heterogeneity and interrelatedness

Fürst

Pecornik

Hoyer

2023

J. of the Acad. Mark. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Building on Jarvis, MacKenzie and , the proposed conceptual model incorporates five reflectively measured constructs, which represent perceptions and attitudes of individuals towards SM practices. Reflective measures are typically interchangeable and induce perceptual manifestations or 'reflection' of each underlying construct (see Diamantopoulos & Siguaw, 2006;Prigge, Homburg & Fürst, 2018) in contrast to formative measures that 'form' or 'build' the construct (see Diamantopoulos & Winklhofer, 2001;Menguc & Auh, 2008).…”

Section: Methodsmentioning

confidence: 99%