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What about Design Newness? Investigating the Relevance of a Neglected Dimension of Product Innovativeness

2009· article· en· W2000954718 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Product Innovation Management · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicInnovation Diffusion and Forecasting
Canadian institutionsBerger (Canada)
Fundersnot available
KeywordsProduct (mathematics)New product developmentDimension (graph theory)MarketingProduct innovationArgument (complex analysis)Relevance (law)Product designBusinessProduct lifecyclePerspective (graphical)Industrial organizationComputer scienceMathematics

Abstract

fetched live from OpenAlex

In several industries, new products are very similar in functional features but compete on their unique design. Firms like Alessi, Apple, Bang & Olufsen, Dyson, or Kartell all follow a design‐driven innovation approach and use their products' visual appearance as the main mean for differentiation. In spite of this, design newness is never discussed among the dimensions of product innovativeness. Instead, conceptualizations of product innovativeness mostly focus on a product's technical newness or the changes it implies for the innovating firm or for the market it enters. This paper seeks to build an argument for why design newness should be considered as a dimension of product innovativeness. In addition to providing conceptual rationale, empirical evidence is offered on the influence of design newness on sales performance across a product's life cycle. To be able to put the findings into perspective, the performance effects of design newness are compared with those of technical newness. As several products exemplify that design newness and technical newness can go hand in hand, not only direct performance effects but also interaction effects between both newness dimensions are investigated. The arguments are tested on a sample of 157 new cars launched between 1978 and 2006 in Germany. The automobile industry is selected because of the strategic role of both technical and design aspects in product innovation. Putting a focus on this industry also has the advantage that historical information on car specifics and objective sales data over time are accessible. The results emphasize that both design and technical newness are important drivers of car sales. However, the effects differ widely across the product life cycle. While design newness has a positive impact right after the introduction and persists in strength over time, technical newness drives sales with a lagged effect and decreases toward the end of the life cycle. The test of a combined influence of design newness and technical newness on sales performance produces no significant results. These results open interesting avenues for future research on product innovativeness in general and design newness in particular. For management practice, the findings emphasize the importance of overall product innovativeness, clarify the different performance effects of design and technical newness across the product life cycle, and show the value of creating a unique visual product appearance to positively trigger product diffusion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.015
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.131
GPT teacher head0.367
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it