When business model innovation enters a market, incumbents will watch whether their peers adopt the new innovation and whether such adoption has negative results before deciding to make the commitment to assimilate the innovation into their own business model.
Business model innovation (BMI), which introduces significantly new ways of doing or structuring business activities, can disrupt an industry and threaten incumbents whose success is built on the currently dominant business model. However, the assimilation of an innovative upstart’s novel business model is fraught with uncertainty for incumbents, who must ask themselves whether the new business model is viable and, if so, whether they have the capabilities to adopt the new model.
To answer these questions, incumbents can look to their peers to see how they might be reacting to the upstart business model. This leads to an effect known evocatively as “organizational herding.” If a peer or several peers start to adopt the BMI, this can encourage other peers to join them, which, in turn, encourages even more peers to follow suit.
Significant research exists on organizational herding, notably in the context of product innovation. Assimilating a new business model, however, requires a significantly more substantive level of investment, time, and risk.
A new study highlights different factors that can influence organizational adoption and herding in response to business model innovation.
The study is based on one of the most significant and ultimately successful business model innovations in the history of business: Amazon’s introduction of online retailing, also known as e-tailing, which would eventually change the face of business.
Using firm data from Compustat and other sources, the study examined the responses of 387 incumbent brick-and-mortar retailers, including many well-known brands such as Wal-Mart, Best Buy, and Gap, to Amazon’s bold and disruptive business model.
The research revealed that both the actions that peers take (peer behaviour) and the results of those actions (peer outcome) can influence incumbent decisions. In this study, peer behaviour referred to peer decisions to adopt the innovation, while peer outcome referred to the negative consequences of those decisions. The researchers used delisting from the stock market for financial distress reasons as their measure of a negative outcome.
The study highlighted two other factors that played in the organizational herding response to Amazon: time and peer type.
From 1995–2001, Amazon’s Internet retailing business model was innovative but not profitable. Amazon started turning a profit in 2002, and after surviving the 2002-2002 dot.com crash, it has been making a substantial profit ever since. The researchers thus divided their data between two-time regimes the first covering the years 1995–2001 and the second covering the years 2002-2018 and found differences in organizational herding between the two.
In the years 1995–2001, Amazon’s non-profitable years, peer behaviour (adopting e-tailing) was likely to influence incumbents to attempt online retailing. On the other hand, negative peer outcomes—including eventual delistings influenced incumbents to avoid the new online retailing business model.
In the years 2002–2018, when Amazon had become profitable and online retailing was becoming established, the dynamics changed. Peer adoption had no influence on the adoption decisions of incumbents. At the same time, however, the negative peer outcomes—an average of 15% of firms delisted after adopting e-tailing—failed to deter incumbents from launching online retailing as they had in the first-time regime. The rapid growth of e-commerce sales, and the success of Amazon in particular may provide some explanation. The research also revealed that incumbents could identify and ignore firms that had launched e-tailing as a last-minute, desperate attempt to avoid bankruptcy.
The type of peer also made a difference. The researchers considered two types of peers: similar and top performing. Similar peers sold the same products and had a generally similar level of market capitalization. Top performing peers consisted of peer firms with a significantly higher level of market capitalization, thus benefiting from more resources and a large customer base.
In terms of peer behaviour, e-tailing activity by both types of peers influenced the decisions of incumbents to launch e-tailing. On the other hand, incumbents tended to ignore the negative outcomes of their similar peers but would be influenced to avoid e-tailing by the negative outcomes of top-performing peers. The reason is that given the resources available to top-performing peers, incumbents would assume that any negative outcome revealed a deficiency in the BMI.
This paper presents parameters that managers may want to take into account as they assess peer reactions to a business model innovation. The first is to focus on peer outcomes as well as peer behaviours. The second is to differentiate between similar and top-performer peers. The third is to consider the maturity of the innovation. Ignoring in the later stages of innovation the failure of similar peer firms that latch on to a new business model at the last minute is an example of the practical nuances highlighted in this research that can guide managers when confronted with new and uncertain innovation in their markets.
Guneet Nagpal’s profile at Ivey Business School
Ruby Lee’s profile at Florida State University College of Business
Rajdeep Grewal’s profile at UNC Kenan-Flagler Business School
Organizational Herding and Business Model Innovation Adoption. Guneet Kaur Nagpal, Ruby Lee, and Rajdeep Grewal. SSRN Working Paper 4487514 (June 21, 2023). Available at SSRN: https://ssrn.com/abstract=4487514 or http://dx.doi.org/10.2139/ssrn.4487514
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