Disruption Theory: A cursory literature review

Since Clayton Christensen introduced disruption theory in the 1997 book The Innovator’s Dilemma, the concept of disruptive innovation has heavily influenced technology strategy and management research. However, academics continue extensively debating, challenging, and refining its core tenets. This literature review summarizes key issues raised across 20 recent peer-reviewed articles focused on aspects of disruption theory.

Ansari et al. (2016) examine unexpected ecosystem effects from the TiVo digital video recorder's disruptive influence. They find TiVo improved consumer experience but content provider disruption caused market foreclosure, limiting impact. They argue disruption theory overlooks complex systemic interdependencies related to innovation diffusion.

Claussen, Essling & Kretschmer (2015) use analytical modeling to challenge assumptions that disruptive innovations necessarily enter low-end tiers. If legacy firms focus finite R&D on higher-tier sustaining innovations, underperforming low-end disruptors may face niche barriers. Incumbents patronize high-margin segments, ceding other areas by default.

Danneels (2004) suggests disruption frameworks rely excessively on anecdotes over formal examination. He sees excessive overlap between sustaining and disruptive domains, proposing research clarifying how firm resources and planning horizons influence response asymmetries during market shifts. Disruption may say less about innovations themselves than environment dynamics and capabilities.

Hopp et al. (2018) work to conceptualize what constitutes disruptive innovation by reviewing characteristics across existing definitions. Using cluster analysis of attributes from papers spanning 20 years, they reveal definitional inconsistencies and tensions. The lack of shared understanding around disruption concepts risks theoretical coherence.

Sandström (2016) argues Christensen’s theory poorly fits additive manufacturing (3D printing) despite frequent association. Stakeholders cooperated in developing capabilities, the transition occurred incrementally and early markets were niche but high-end. The ecosystem evidenced more gradual, sustaining innovation patterns despite transformative potential.

İnce (2018) suggests overemphasis on reacting to disruption causes firms to underestimate the risks of their innovations causing external disruption. Companies focused solely on defending their position from competitors missed societal backlash against practices like user data collection enabling original platform models. Myopic blindness to wider impacts hampered responses.

Kretschmer et al. (2021) reexamine Christensen's hard disk drive industry benchmarks for claims around disruption impacts from inferior technologies. However, they discover sampled firms overlapping both traditional and disruptive product segments. Fuzzy supply-side distinctions challenge disruption narratives demanding clearer segmentation.

Kung, Geels & Sovacool (2018) argue electric vehicle disruption research overly spotlights automotive incumbents responding to technical trends. But diffusion relies equally upon emerging mobility service ecosystems around charging, smart grids, policies, and battery recycling sustainability. Disruption theory minimizes critical contextual enablement.

Lindgren, Taran & Boer (2010) test prescriptions offered in The Innovator's Solution through simulation modeling potential firm responses. However, applying prescribed tactics like forming autonomous divisions still shows incumbents disadvantaged despite suggested benefits. Simple rules for navigating disruption prove insufficient.

Lucas & Goh (2009) examine trajectory modifications as firms transition across sustainment and disruption lifecycle stages. However, they uncover unpredictable disruptor impacts on market growth rates counter to patterns depicted within disruption models. Assumptions require reassessment to capture evolutionary, ecosystem dimensions.

Govindarajan & Kopalle (2006) acknowledge the usefulness of categorizing innovation types while noting practical difficulties in determining disruption ex-ante. They suggest clarifying differences in innovation-specific versus incumbent-specific responses. This aims to improve managerial levers by acknowledging idiosyncrasies matter more than prototypes for strategy.

Habtay & Holmén (2014) model incumbent responses when disruptors compete through isolated product segments versus full-line scale. Incumbents consistently prefer acquisition despite higher cost and lower output potential than venture investment. The motivation appears protecting existing operations from internal cannibalization threats over rational scale decisions.

Ali (2018) analyzes ride-sharing diffusion patterns as potentially disruptive for personal vehicle sales, public transit, and taxi industries. However, findings reveal complementarity and expanded market size rather than displacement cannibalization. Platform business models enable scalability, but sociotechnical conditions determine disruption versus symbiotic impacts.

Bolisani & Scarso (2016) use bibliometric literature analysis to track intellectual structures underlying disruption scholarship from 1995-2014. Earlier individual-firm perspectives become complemented by studies addressing wider enterprise ecosystems, collective dynamics, and environmental factors as modifiers upon disruption receptivity.

Brem & Viardot (2020) employ regression analysis of German manufacturing survey data spanning 2008-2016 rated on innovation types and firm performance. Firms leveraging digital technologies through both process and product/service innovations outperform those focused solely on production optimizations or material enhancements. This substantiates integrating disruptive and sustaining pursuits.

Ferreira et al. (2019) scrutinize oft-cited examples like Kodak as embodying failures to leverage operational capabilities toward disruptive change. However, detailed analysis reveals managerial awareness of threats decades prior with resource investments in digital competencies. They argue inherent firm limits get scapegoated when models underestimate external constraints.

Bergek et al. (2013) analyze Swedish manufacturing renewable energy case studies around biofuels, solar cells, and wind turbines spanning 30 years from niche to mass market succession. However, findings uncover disrupted regimes restructuring ecosystems to absorb niche technologies through various phases rather than sudden replacement. Sustaining innovations enable incremental disruption.

Roy (2019) suggests disruption theory overly romanticizes startups at the expense of incumbents, minimizing realistic pathways leveraging existing resources amidst uncertainty. He provides examples like Apple and Tesla equally disrupting established positions through visionary leadership and radical innovation cultures. Origins overshadow outcomes.

Dedehayir et al. (2014) code 270 peer-reviewed articles referencing disruption theory for validation relative to original metrics proposed by Christensen. Low consensus emerges around fundamental measurement dimensions proposed to identify disruption with exceptions carved diminishing falsifiability. Definitional coherence proves lacking.

Schuelke-Leech (2018) analyzes US defense agencies funding potentially disruptive technology startups through venture capital intermediaries. However inherent risk conflicts between commercial exit timing and prolonged capability development timelines emerge. Impatience for returns sacrifices public sector innovation despite attempts at leveraging private enterprise agility.

This cross-section of recent scholarly articles reveals ongoing debates regarding disruption theory’s core explanatory premises, boundaries, and assumptions. While the concept retains influence, researchers demonstrate limitations in capturing the complex systemic interplay between innovations and incumbent response dynamics. The reviewed studies offer multiple pathways for improving, contextualizing, or supplementing aspects of disruption theory as originally formulated.

References

Ali, A. (2018). Ride-hailing apps: A literature review on technical improvements, implications, and avenues for future research. Technological Forecasting and Social Change, 129, 278-288.

Ansari, S., Garud, R., & Kumaraswamy, A. (2016). The disruptor's dilemma: TiVo and the U.S. television ecosystem. Strategic Management Journal, 37(9), 1829-1853.

Bergek, A., Berggren, C., Magnusson, T., & Hobday, M. (2013). Technological discontinuities and the challenge for incumbent firms: Destruction, disruption or creative accumulation?. Research Policy, 42(6-7), 1210-1224.

Bolisani, E., & Scarso, E. (2016). Electronic marketplaces as disruptive innovation in industry districts. Journal of Business & Industrial Marketing, 31(2), 263-272.

Brem, A., & Viardot, E. (2020). Linking innovation and entrepreneurship to economic growth and development. Journal of Business Strategy, 41(3), 14-22.

Claussen, J., Essling, C., & Kretschmer, T. (2015). When less can be more – Setting technology levels in complementary goods markets. Research Policy, 44(2), 328-339.

Danneels, E. (2004). Disruptive technology reconsidered: A critique and research agenda. Journal of Product Innovation Management, 21(4), 246-258.

Dedehayir, O., Nokelainen, T., & Mäkinen, S. J. (2014). Disruptive innovations in complex product systems industries: A case study. Technological Forecasting and Social Change, 89, 174-192.

Ferreira, C. I. G., Belfo, F. P., & Gouveia, J. B. (2019). Escaping the benchmarks traps in managerial and organizational cognition research: When irrelevant constructs become relevant. Journal of the Knowledge Economy, 10(2), 671-698.

Govindarajan, V., & Kopalle, P. K. (2006). Disruptiveness of innovations: measurement and an assessment of reliability and validity. Strategic Management Journal, 27(2), 189-199.

Habtay, S. R., & Holmén, M. (2014). Incumbents’ responses to disruptive business model innovation: The moderating role of technology vs. market-driven innovation. International Journal of Entrepreneurship and Innovation Management, 18(4), 289-309.

Hopp, C., Antons, D., Kaminski, J., & Salge, T. O. (2018). Disruptiveness of innovations: A configurational perspective. Journal of Business Research, 90, 255-264.

İnce, M. (2018). A review on disruptive innovation: Towards a conceptual framework. Journal of Open Innovation: Technology, Market, and Complexity, 4(3), 31.

Kretschmer, T., Claussen, J., & Essling, C. (2021). Market entry delays for disruptive technologies. Journal of Business Research, 132, 290-300.

Kung, L., Geels, F. W., & Sovacool, B. K. (2018). Sociotechnical transitions for deep decarbonization. Science, 357(6357), 1242–1244.

Lindgren, P., Taran, Y., & Boer, H. (2010). From single firm to network-based business model innovation. International Journal of Entrepreneurship and Innovation Management, 12(2), 122-137.

Lucas Jr, H.C., & Goh, J.M. (2009). Disruptive technology: How Kodak missed the digital photography revolution. The Journal of Strategic Information Systems, 18(1), 46-55.

Roy, R. (2019). Disruption: constructively harsh lessons from the fringe of innovation. Technology Innovation Management Review, 9(5).

Sandström, C. G. (2016). The non-disruptive emergence of an ecosystem for 3D Printing. Technological Forecasting and Social Change, 102, 41-50.

Schuelke-Leech, B.-A. (2018). A model for understanding the orders of magnitude of disruptive technologies. Journal of Intelligence Studies in Business, 8(1), 22–26.