Survival

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calculating machines, freezers, guided missiles, paints, radars, radio transmitters, televisions, pneumatic tyres and windshield wipers. Non-shakeout products included lasers, pens, shampoo, cryogenic tanks, tapes, transistors and zippers. The shakeout products showed a longer duration of exit than predicted by the overshooting model and the non-shakeout products showed persistence in entry and exit inconsistent with the overshooting model. Alternative explanations are thus needed.

The second class of explanations assumes that shakeout is caused by technological developments and thus excessive entry and shakeout do not have a causal link but rather they correlate. Utterback and Suárez (1993) explain shakeout based on the dominant design and the transition that it brings about in innovative activities. Firms that are unable to move towards greater product standardisation and process innovation will not succeed in competition against those who make the transition and they will eventually die. In the Jovanovic and MacDonald (1994) model shakeout is the result of a single major refinement innovation that substantially increases the optimum firm size. As many firms ramp up production to exploit such scale economies the market is overflowed and price drops.

This causes many firms to exit. Klepper‘s (2002a) theory, on the other hand, is based on dynamic increasing returns to R&D. As large firms benefit most from R&D due to their large output they also tend to perform the most R&D. This gives the incumbents an ever increasing advantage over entrants as they tend to have grown larger and have had more time to perform R&D. The later entrants find it hard to catch up in size and as the price continues to fall the smallest firms and least able innovators exit.

As the shakeout has taken its course the industry reaches ―ultimate structure‖ that is determined by the sequence of events traversed (Gort and Klepper 1982). Utterback and Suárez (1993) call it a point of stability where few large firms have standardised products and stable market shares. For them this is not in any way an ultimate structure but a situation that is waiting for the next technological discontinuity.

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These regularities in survival rates mean that the maturing of an industry does not necessarily create a barrier to entry but a barrier to survival (Audretsch 1995a) or a barrier to growth (Bartelsman et al. 2005). According to Audretsch (1995a) the barrier consists of scale economies and product differentiation. Bartelsman et al. (2005) have found similar churning rates across ten OECD countries. In most of them about 20% of firms enter and exit most markets every year and around 20-40% of entering firms fail within the first two years. There may be barriers to growth instead of barriers to entry.

The advantage of early entrants is explained with cumulative learning, economies of scale in production and cost spreading in R&D. According to Nelson (1995) before the dominant design emerges there is no advantage of incumbency. Afterwards cumulative learning by incumbent firms puts entrants increasingly at disadvantage. Suárez and Utterback (1995), on the other hand, argue that those firms that enter prior to the emergence of the dominant design benefit from being able to experiment with different product designs during the era of ferment. Kim and Park (2006) refer to the superior resources gained due to early entry as a birthright. In their study on the telecom shakeout reputation and brand were found to be the key ingredients of birthright. Thus, in addition to learning inside the firm, learning by consumers may give an advantage to early entrants.

Learning is related to both technology and market. The commercialisation of new products requires knowledge about the market and skills in distribution, marketing and so on. Nerkar and Roberts (2004) argue that there are complementarities among technological and product-market experience.

In their study the success of pharmaceutical product introductions increased with both. According to Christensen and Rosenbloom‘s (1995) study on the disk drive industry incumbents led in all kinds of innovations, at component and architectural levels, competence-enhancing and competence- destroying, incremental and radical, as long as the innovations addressed previously known consumer needs. According to Rothaermel and Hill‘s (2005) findings on four industries, incumbents have an advantage over new entrants even with competence-destroying product innovations as long as the commercialisation of new products requires specialised market related competencies. Similarly Tripsas (1997) using data from the typesetter industry found that specialised complementary assets buffer incumbents against the effects of competence destruction.

Levinthal (1991) on the other hand argues that prior success simply buffers firms against selection pressures. Surviving organisations tend to be the ones that were successful in prior periods.

Economies of scale and process technology development further exacerbate the entrants‘

difficulties. In addition, cost of entry increases with the investment levels required by efficient scale. (Nelson 1995) In Cefis and Marsili‘s (2005) study innovators had a higher survival rate than non-innovators. Process innovations especially increased the chances of survival independent of age and size. Klepper and Simons (2000a) found that larger firms tend to be at the technological frontier and for this reason they have higher survival rates. Also, among firms that were at the technological frontier the larger ones tended to have higher survival rates. Firm size had a much smaller effect on the hazard rate of a firm not at the technological frontier which suggests that the technological advance related to large firms is more important for survival than other effects of large size. In the

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same vein Banbury and Mitchell (1995) found that the ability to perform incremental innovations is critical for the survival of firms.

As mentioned above, economies of scale cause the production within an industry to concentrate within a few firms, which contributes to the shakeout phenomenon. Economies of scale also create incentives for R&D as the larger the production capacity the larger the number of units over which costs can be spread. This means that as long as firms expect to benefit from R&D close to the time it is performed the firm‘s capacity has an effect on the incentive to undertake R&D (Cohen and Klepper 1996a). Thus larger firms have a stronger incentive to engage R&D. Cohen and Klepper (1996b) add that the cost spreading effect is particularly strong for process relative to product R&D.

Investments in R&D can also be rationalised through the lowering of variable costs with the expense of rising fixed costs. This way unit cost may decrease when the market and production capacity is large enough. (Shaked and Sutton 1987) The cost spreading effect has been found also to hold for advertising (Audretsch 1991).

The first-mover advantage is not universal. It is likely to occur when the pace of market evolution and the pace of technology evolution are both smooth (Suárez and Lanzolla 2007). Based on their study on the telecommunications equipment industry Dowling and Ruefli (1992) argue that technological innovation is a gateway to entry in a changing industry. Similarly Agarwal and Gort (1996) found that in technical products entrants often come with innovations that give them superior knowledge over incumbents. Entrants then have higher survival rates. For non-technical products learning by doing gives incumbents an edge over entrants. In addition to the difference between industries there is a difference between industry life-cycle stages. In the era of intense technological activity entrants enjoy a higher rate of survival as incumbents suffer from technological obsolescence (Agarwal 1996). Furthermore, Dowell and Swaminathan (2006) found that in the bicycle manufacturing industry earliest entrants had an advantage but only until the emergence of the dominant design. The incumbents found it hard to make the transition from their design to the dominant one as their search efforts tended to be local. Entry after the dominant design has emerged has the benefit of resolved uncertainty.

The threat of obsolescence comes from technological and organisational commitments that are hard to adjust as new opportunities emerge. Sørensen and Stuart (2000) state, based on their findings on semiconductors and biotechnology, that as organisations age they generate more innovations. The downside is that these innovations exhibit an increasing divergence between organizational competence and current environmental demands. On the other hand, Czarnitzki and Kraft (2004) offer empirical evidence that challengers invest more in R&D than the incumbents. Another story is the effect of stock market reactions on the ability of established firms to pursue novel innovative directions. Benner (2007) argues that incumbent firms are not as inertial as prior studies claim, but the institutional pressure of the stock market forces established firms to narrow their focus. Benner (2008) also found that securities analysts pay little attention to technological discontinuities and that analysts and investors tend to continue to reward incumbents for cash flows arising from focusing on existing business and technology despite the increasing certainty of technological obsolescence.

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The industry life-cycle theory suggests that whether the advantage is held by incumbents or new entrants is dependent on the stage of the life-cycle. According to Audretsch (1991), the technological regime affects the ability of new firms to survive over a fairly long period but has no influence in the short run. Under the routinised regime when scale economies and cumulative learning reign small firms are at a disadvantage. As entrants tend to be small they find it hard to survive. The entrepreneurial regime on the other hand is conducive to small firm innovation and thus the survival of entrants is more common. However, industry concentration may aid entrant survival over the short term as concentrated markets tend to have higher prices. (ibid.) Agarwal et al. (2002) have found that firms that enter during the mature phase suffer from significantly higher levels of mortality than the firms that enter during the industry growth phase.

However, as the mature phase begins the entrants of the previous period face a rising mortality rate.

Agarwal et al. (2002) conclude that the survival advantage of the growth phase seems to be related to the knowledge conditions of the entrepreneurial regime and lesser scale and resource requirements. Sarkar et al. (2006) combined the regime and R&D intensity within an industry in their analysis on entrant survival. They found that in general the survival rate of new entrants is higher during the entrepreneurial regime, but in addition high technological intensity (measured as R&D investment as percentage of sales) is required before the survival of small entrants is aided.

This confirms that small firms have an edge in innovation during the entrepreneurial regime.

Cefis and Marsili (2006) found that innovativeness conditions survival for firms of all sizes and ages but it is especially important for small and young firms. The survival rate of young, small and non-innovative firms is the lowest. Henderson‘s (1993) study on radical innovation in the photolithographic alignment equipment industry showed that incumbents invest more in incremental innovation which helps them to gain market share, but are less productive than entrants in producing radical innovations. Thus the incumbents also put a lot of effort into succeeding in radical innovations but their productivity in those efforts is significantly lower than that of new entrants. Once such radical innovation is introduced the first-mover advantage emerges again. In Ehrnberg and Sjöberg‘s (1995) classification technological discontinuities are categorised into either within old generic technology or new generic technology and either complementary or substituting. They find that the most disrupting kind of discontinuity, i.e. new generic technology and substituting, induces the greatest first-mover advantage. Furthermore, the faster the technology diffuses among customers the greater the advantage of first movers. This means that the radical innovations that are more easily produced by entrants than incumbents give the greatest first-mover advantage and thus the biggest lead.

Despite many studies on survival the factors that determine survival and non-survival are not completely known. In Willard and Cooper‘s (1985) study on the US colour television set industry shakeout the survivors were not determined by costs, prices or market shares. Furthermore, the survivors were following different kinds of strategies and many non-survivors were following strategies similar to those of survivors. Storey and Wynarczyk (1996) found that the talent of the entrepreneur does not explain survival and non-survival in micro firms. Christensen et al. (1998) on the other hand found that managerial choice rather than environmental factors determined survival in the disk drive industry. Firms that chose to incorporate the key elements of what became the

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dominant design had double the survival rate of firms that chose otherwise. To complicate things, Tegarden et al. (1999) found that in the personal computer industry firms that originally chose the

‗wrong‘ design were not doomed by that decision. Switching to the dominant design later on was also possible for later entrants and an increase in the chances of survival was thus attained.

In managerial writing the battle of incumbents and entrants has been a popular topic. D‘Aveni (1999) guides incumbents and challengers to take up different kinds of strategies in the face of a technological disruption. The proposition is that the incumbent should resort to a dampening strategy to exhaust the challengers with their resources whereas the challenger should take up a disruptive strategy and build a more flexible and creative organisation. Hill and Rothaermel (2003) suggest that incumbents can improve their chances of survival by, for example, investing in basic research to raise awareness on emergent technologies and employing a real options perspective for evaluating technology investment decisions. According to Stoelhorst (2002) an incumbent should invest in accessing knowledge of emerging technologies, strive to understand the market and possible applications, try to take the lead and build alliances and complementary assets.

Another question of interest in the survival pattern has been that of de novo and de alio entrants. De novo entrants are newly founded firms that do not have much experience to help them or to tie them down. De alio entrants are old firms that enter an industry through diversification. They thus have experience from a related industry or just generally of doing business. A common assumption is that pre-entry experience increases survival rates. For example, radio producers who entered the television industry had a higher survival rate than de novo entrants (Klepper 2002a). De alio entrants can also leverage complementary assets to overtake incumbents. This is how Nokia, Ericsson and Samsung overtook Motorola (He et al. 2006). In the early automobile industry de alio entrants performed better than de novo entrants, but the best of all were de novo firms founded by individuals who had previously worked for leading automobile firms (Klepper 2002b).

Furthermore, Agarwal (1997) found that de alio firms have lower hazard rates in earlier stages of the life-cycle but higher in the later stages. This is because they have a higher opportunity cost for staying in the market. Khessina and Carroll (2008) argue that the differences in product turn-around rate explain differential survival. De novo firms tend to introduce and kill products at a faster pace than de alio firms. This is because de novo firms are under more intense pressure to create a market identity. Bayus and Agarwal (2007), however, found that the advantage shifts from de alio entrants to de novo entrants in the later stages of the life-cycle. This is because later entering de novo firms are more likely to use the latest technology whereas de alio entrants settle for the industry standard.

Finally, survival has been conditioned to the size of the product portfolio and the pattern of the new product introductions. Dowell (2006) found that in general firms offering a greater number of different products have higher survival rates. Barnett and Freeman (2001) found that incremental approach to product introductions and a wide product portfolio advances survival whereas the introduction of several products at a time may be detrimental. Wezel and van Witteloostuijn (2006) on the other hand state that new product introductions increase the chances of survival only for those firms that already have a large portfolio. Firms with a small number of products risk failing with each new product. Furthermore, Dowell and Swaminathan (2000) point out that maintaining

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old product lines may be beneficial while introducing new ones but the firm suffers if such overlap is retained for an extended period of time. Jones (2003) argues that the entrants versus incumbents analysis of technological discontinuities should be complemented with analysis over product line strategies. He finds that the benefits of early entry can be traded off to some extent for investments and time put into the development of the product line strategy, i.e. modularity and platform.