Entry, Exit and Innovation over the Industry Life Cycle in Converging Sectors: An Analysis of the Smartphone Industry

Abstract

This paper examines the digital convergence process that led to the development of the smartphone sector and the dynamics of entry, exit and innovation over the industry life cycle. We have verified, by a historical-longitudinal study, if several empirical regularities that characterize the evolution of firms and industries over time have distinguished also an industry born from a sectoral convergence process. From the analysis it emerged that the evolution of market sales and of product innovation in the smartphone industry, as well as firms entry and exit dynamics, are consistent with the evolutionary model identified by technology management and industry life cycle studies. It has also been found that the convergence process has favored the entry and the survival of new entrants, compared to the incumbent firms, coming from the native converging sectors – that of Personal digital assistants and of Mobile (feature) phones – from which the smartphone industry originated. Keywords: industry convergence, industry life cycle, entry and exit, innovation processes, smartphones 1. Introduction It is now generally recognized in the academic literature that the structural and competitive characteristics of industries vary over time. The results of numerous empirical studies have shown here that the sectors tend mainly to evolve following a life cycle characterized by a series of empirical regularities concerning how entry, exit, market structure, and technological change vary from the birth of industries through to maturity (Klepper, 1996). A full understanding of the mechanisms underlying the evolutionary dynamics at the sectoral level require the use of different study perspectives, which provided complementary reading keys. Over time, we have witnessed a strong rapprochement between research on the subject carried out in the field of evolutionary economics (Nelson & Winter, 1982; Gort & Klepper, 1982; Klepper, 1996, 1997) and technology management studies (Abernathy, 1978; Abernathy & Utterback, 1978; Utterback & Suarez, 1993; Tushman & Anderson, 1986, Anderson & Tushman, 1990; Audretsch, 1991, 1995, 1997). Although there are some interpretative differences between the two perspectives, especially as regards to the notion of dominant design (Klepper, 1996; Klepper & Simon, 1996), their integrated use has allowed us to understand that the typology of knowledge and skills that fuel the industrial innovation processes influence in a decisive way the evolution of the industrial demography and of the sectoral competitive dynamics (Breschi, Malerba, & Orsenigo, 2000; Agarwal, Sarkar, & Echambadi, 2002; Garavaglia, 2004). It is in particular with the introduction of the concept of ‘industry technological regime’ (Nelson & Winter, 1982) – which refers to the knowledge environment in which firms operate – that firmly states in the literature an evolutionary model based on the idea that the specific pattern of innovative activities in an industry are closely related to the generational processes of variety and selection. Precisely linked to the theoretical approach of technological regimes, Anderson and Thusman (1986; 1990), based on the examination of various industries, propose an evolutionary model of technological change that allows the interpretation of the industry evolution on the basis of ‘technological discontinuities’ which occur over time. In particular they describe the different effects that two types of technological discontinuities (competence-destroying and competence-enhancing) may have on changes in industrial structures. Always starting from the assumptions underlying the evolutionary model of technological regimes, Audretsch (1995, 1997) considers that the arrangements in which firms and industries tend to evolve depend on differences in knowledge conditions and technology that underlie the specific industry. The scholar, however, extends its ijbm.ccsenet.org International Journal of Business and Management Vol. 15, No. 12; 2020 152 interpretative value highlighting that the dynamic patterns of firms may vary not only over time, but also from industry to industry, in relation to the different technological opportunities that occur at the sectoral level. Starting from these studies, further analysis has been carried out that have deepened the examination of how technological cycles condition the form and level of competition, the attractiveness of entry and industry structures (among the others: Agarwal et al., 2002; Dinlersoz & MacDonald, 2009; Bos, Economidou, & Sanders, 2013). The results of the research that has studied the relationship between innovation and industrial evolution over time have indirectly provided new interpretative keys to shed light on one of the main sectoral transformation events on which in recent years has been focusing the attention of the studies in the managerial economic field. This refers to the phenomenon of industrial convergence, which has led to the confluence and merging of many separate markets, especially in digital sectors (Yoffie, 1997). The convergence processes have in fact determined significant breaks in production and technological architecture in many areas, often causing a redefinition of the structural characteristics of the converging sectors and, therefore, of the relative industry life cycle curves (Hacklin, Marxt, & Fahrni, 2009; Lind, 2005). It was observed in this respect that the technological and market changes that characterize the sectors affected by convergence processes make sure that the industry life cycle curves of these sectors “form an entangled dimensional space of mutual convergences into each other” (Lind, 2005, p. 16). The management literature that has dealt with analyzing the phenomenon of convergence, although having examined its impact on the redefinition of sectoral boundaries and corporate strategies, does not seem to have sufficiently deepened the general theme of the rapport between industrial convergence, innovation processes and selective mechanisms that work to define the evolution of the industries involved in these processes. Indeed, it is possible to state that, despite the fact that the overall industry convergence is increasing over time, the understanding of this phenomenon is still limited (Kim et al., 2015), also because with time technology convergence is evolving into a more complex and heterogeneous form (Jeong, Kim, & Choi, 2015). For this reason, further exploratory and explanatory research is useful in understanding the consequences of convergence as a form of innovation and its impact on the evolution of convergent sectors (Hacklin et al., 2009). Hacklin (2008, p. 11), one of the first scholars to have adopted, in the study of the convergence processes, an evolutionary perspective based on the analysis of the industrial technological changes over time, observed in this regard that industrial and technological convergence have been studied during the growth stage, or during phases of maturity, “but an integrated, comprehensive view of the convergence process, which could be used for understanding and managing through similar innovation trajectories in the future, can be regarded as still missing” . He also noted that the study of industries where convergence development has reached a certain maturity (such as those of ICT macro-sector), might serve, in retrospect, as a basis for understanding the evolutionary dynamics in other sectors affected by the phenomenon of convergence. This research work provides an original contribution in this direction. It was in fact analyzed the evolution over time of one of the sectors which in recent years has been most influenced by the digital convergence process, that of the mobile phones. This process brought the creation of a new related sector, that of smartphones, leading to radical changes in the structural and competitive characteristics of a series of sectors concerned, with different intensities and times, from the effects of this process. The overall objective of the work was therefore to analyze the processing phases of digital convergence that determined the birth and development of the smartphone sector and the dynamics of entry, exit and innovation over the industry life cycle. The use of a longitudinal analysis approach, based on the study of the historical sequence of events that led to the emergence and development of the smartphone industry over a period of more than 20 years, permits us to verify if some empirical regularities that characterize the evolution of firms and industries over time have characterized also the evolution of an industry born out of a sectoral convergence process. This is a relevant research question. As observed by Giachetti and Marchi (2010), research is in fact necessary to fill the gaps of classical industry life cycle model, especially when industry evolution is affected by disruptive events like those driven by technological convergence, as happened in the last years in the mobile phone industry. In this direction, this study offers several specific contributions. First, we examine the evolution of the smartphone industry, defined on the basis of sales data, to verify if it is in line with the evolutionary model that emerged from the product and industry life cycle studies. Secondly, we analyse the entry and exit processes over the industry life cycle of the smartphone industry and verify if the technological discontinuities that created the conditions for the development of this new converging industry have favored the entry, the survival and the competitive positioning of new entrants, compared to the incumbent firms, coming from the native converging sectors. Third, we analyze the evolution of product innovation over time in the smartphone industry to verify if it is consistent with the standard ijbm.ccsenet.org International Journal of Business and Management Vol. 15, No. 12; 2020 153 technological change identified by technol