The purpose of this paper is to address how marketing assets and resources of the firm perform under different product (brand) innovation conditions using the dynamic marketing capabilities (DMC) research perspective. The study contributes to the DMC research stream showing the effects and performance of heterogeneous firm drivers and resources. Academic research to date has paid a little attention to the interrelationship between market share as a performance metric, dynamic capabilities and product (brand) innovation. The current study bridges this knowledge gap by empirically validating the effects of DMC on market share performance output using panel data for 753 retail food brands.
The model was initially fitted with the β regression analysis and cluster analysis in the second step of the estimation procedure. The results of simulation by Monte Carlo experimentation are discussed.
The findings show that firms leverage their marketing capabilities unequally in the multi-brand portfolios, which leads to an unequal intra-firm distribution of assets and resources. The research contributes to the understanding of the brand competitive dynamics and appropriate deployment of assets and resources for improved firm performance.
These findings are useful for both academics and practitioners because they address new and future research. In doing so, the authors advance the firm performance and branding literature with extension in the DMC literature.
Comments and suggestions from Richard Priem and Luis Martins on earlier versions of the manuscript are highly appreciated. The authors are grateful to the participants of the 12 Global Brand Conference (Kalmar) for their valuable insights. The authors thank the editor for his commitment and two anonymous reviewers for detail comments and constructive criticism, which helped to improve the manuscript. All mistakes and misunderstandings are of the authors.
Davcik, N. and Grigoriou, N. (2019), "How an unequal intra-firm resources distribution affect market share", Marketing Intelligence & Planning, Vol. 38 No. 2, pp. 167-180. https://doi.org/10.1108/MIP-03-2019-0170Download as .RIS
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