Adapt fast or die slowly: Complex adaptive business models at Cisco Systems

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Industrial high-tech markets are characterized by profound levels of market and technological uncertainty and so firms herein must navigate extraordinarily dynamic and fast-moving environments. In such settings, traditional top-down modes of strategic planning are ill-suited to generate the flexibility and speed of change necessary for firms to maintain environmental fitness over time. Survival requires that significant decision-making powers necessarily be located on the operational periphery of the firm. To understand how the resultant multiplicity of micro-strategizing and decision-making might engender macro-level change(s) to business models, we conduct a cross-sectional case study of two business models at Cisco Systems. After problematizing two broad strands of extant theory, we conjecture that a rival theory – complexity theory – might allow us to better explain how Cisco's business models evolve in practice and we utilize our case study to test this conjecture. We find that the business models studied have the capacity to change themselves spontaneously and autonomously from executive-led decisions in response to external stimuli. We offer a novel theoretical insight by postulating the existence of complex adaptive business models and we advance knowledge in a way that is useful for practitioners by suggesting they perceive themselves as facilitators and orchestrators of business models rather than owners or even controllers of them.

LanguageEnglish
Pages102-115
Number of pages14
JournalIndustrial Marketing Management
Volume77
Early online date12 Dec 2018
DOIs
Publication statusPublished - Feb 2019

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Business model
Decision making
Top-down
Fitness
Complexity theory
Market uncertainty
Strategic planning
Technological uncertainty
Controller
Multiplicity
Facilitators
Strategizing
High-tech
Owners

Cite this

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Adapt fast or die slowly : Complex adaptive business models at Cisco Systems. / Groeger, Lars; Bruce, Kyle; Rolfe, Iain.

In: Industrial Marketing Management, Vol. 77, 02.2019, p. 102-115.

Research output: Contribution to journalArticleResearchpeer-review

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