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Source publication
Radical innovations pose a great challenge for strategic management. Innovation management has traditionally approached change with static methods relying on information on capabilities, strategy and markets. We introduce a system dynamics model to describe how learning changes the dynamics of innovation management. We use a post radical innovation...
Context in source publication
Context 1
... and disruptive refer to the effect where a radical innovation disrupts the balance of a given industry or market by superseding the previous dominant design, thus creating a discontinuity in the evolution of the industry. This paper adopts the typology presented by Chandy and Tellis (1998), where the dimensions of change are change in markets or in technology (Table 1). The technological aspect of change is defined as newness of technology compared to the products currently on markets. ...
Citations
... Technology epiphanies happen when consumption attitudes drastically change with fundamental product differentiation that serves as a catalyst in purchasing behavior and hence reshape the rules of the competition (Verganti, 2011). This kind of innovation emerges in a radical change in customer benefit package and a different or wider meaning behind it (Kortelainen et al., 2010). Technology-push innovation occurs when a radical change in technology does not bring significant changes in the meaning of a product in use. ...
The purpose of this paper is to shed light on the digital transformation of LEGO and to figure it out in innovation-oriented growth decisions. To this end, the study here examines the transformation process of the company from diversification to smart specialization strategy in more detail. Besides, where digital architecture for toys requires many innovations at the same time, authors discuss what LEGO does to add value. More importantly, the typologies of innovation strategy elucidate the changes and improvements that foster digital transformation.
... The system dynamics simulation has proved its usefulness in military, logistics, management, and organisational studies (see, for examples and overview, e.g. Gary et al., 2008;Harrison et al., 2007;Kortelainen et al., 2010;Sterman, 2000). In entrepreneurial studies, system dynamics modelling has been used for analysing the decision-making process (Kefan et al., 2011) and studying the influence of fairness perceptions on the cooperation between new ventures and universities (van Burg and van Oorschot, 2013). ...
The importance of entrepreneurship for economic development and overall social well-being is widely recognised by researchers, experts, and policy makers. Researchers have identified a variety of endogenous and exogenous determinants, such as individual-level factors, external macro-level factors, and country-level cultural factors, which can moderate the raise in entrepreneurial activity. From the other side, there is a feedback loop between entrepreneurship affecting economic growth and being, in turn, affected by country wealth. The main objective of this study is to build a model to capture the relationship between entrepreneurship and external macro-level determinants, and to explore the possible effects of changes in entrepreneurship supply-and-demand factors. The research applies system dynamics simulation and proposes a dynamic macro-level model of entrepreneurship. The model equations are developed based on regression analysis. The results show that although entrepreneurship does have a positive impact on the economy, this effect can be mitigated by other factors. Furthermore, even though an improvement in the external determinants level results in increased entrepreneurship activity and consequent economic growth over a longer period, the effect may depend on factors such as overall country population development, and especially the proportion of adult populations, institutional factors, and individual intentions towards entrepreneurship.
... A¯rm's stock of resources is created by the accumulation of stock over time, a similar phenomenon to the one that is central in system dynamic modeling. However, in our previous e®ort to model strategic management and management of technology on the basis of system dynamics [Kortelainen et al. (2010)], we found that the structure of the model was strongly restricted by the limitations set by the system dynamic modeling technique. For this reason, the new prospect of agent-based modeling became attractive, as it o®ers a more°exible structure for the models. ...
Understanding the sources of sustained competitive advantage is the fundamental task of strategic management research. An interesting concept of fast strategy has emerged, which builds a firm's competitiveness from its ability to react to change more rapidly than its competitors. We approach this concept with a simulation model based on a hybrid modeling technique. The simulation model is used to test the profitability of the fast strategy concept in different business environment conditions. The theoretical finding of our study supports the fast strategy concept and shows that there are some internal and external factors that control the value of agility. The methodological finding of this work is that the hybrid modeling technique offers an interesting platform for understanding the effects of environmental dynamics in strategic and technology management research.
... This research continues on the track laid by Kortelainen et al. (2008), where the study focused on the link between profitability and a firm's learning efficiency. Compared to the previous research, this paper introduces a new model linking the capabilities and profitability of a firm. ...
... has contributed to the structure of the model and position our research more closely to the surrounding literature. We start by discussing the relationship between the capabilities and competitiveness of a firm as presented in the RBV of the firm. We will also elaborate on the definition of learning as we understand it in the context of this paper. Kortelainen et al. (2008) discuss their position in defining radical innovation, and they have chosen to use the definition commonly used in the marketing literature after Chandy and Tellis (1998), where the classifying factors are the newness of introduced technology and customer value of the offering. As discussed previously, several researchers have repeatedl ...
Technological change and especially radical changes are a major source of uncertainty for strategic management of technology. The traditional approach to this problem has been a race to be the first mover to the markets. We look at this situation through the lens of the Resource Based View, and study how the innovation and imitation strategies pay off under different industry conditions. The resource based view of the firm proposes that the competitiveness of industrial companies depends on their ability to manage portfolios of rare and valuable resources. Learning is an important mechanism in resource development and management. We develop a system dynamic model to understand the linkage between learning and profitability under different conditions set by resource appropriability and transferability. The research problem is to examine how profitable the innovator and imitator are in different industry conditions after the radical innovation is launched to the market. The setting informs the industrial manager whether it is economically feasible to open up the R&D to external influences in a situation of discontinuous change, given the industry parameters. The results show that expected profit varies strongly depending on ability to learn from different sources. Strategies based on external learning performed better in open and less protected market environment and internal learning became more interesting when resources could be efficiently protected.
Purpose
– The purpose of this paper is to investigate the drivers that induce companies to change their rules for managing product development. Most companies use a form of rule-based management approach, but surprisingly little is known about what makes companies change these rules. Furthermore, this management technology also has developed over time into different versions, but what drives firms from one version to another has only been suggested, not empirically studied.
Design/methodology/approach
– The dynamics of the rules of five companies are analyzed over a period of more than ten years based on three rounds of interviews with 40 managers.
Findings
– Previous research has assumed that the dynamics of product development rules are based on internal learning processes, and that increasingly competent management will stimulate the implementation of newer and more complex rule regimes. However, the analysis here indicates that there are different drivers, both internal and external, that cause companies to adopt new rules or modify their existing ones, such as changes in organizational structures, organizational conflicts and changes in ownership or strategy. In addition, contrary to the predictions in previous research, companies sometimes move back and forth between different generations of rules. Companies that have moved to a more flexible third generation of rules might revert to their second generation rules, or supplement their flexibility with an increased level of management control and information systems. A model is proposed to explain the relationship between the drivers of rule change and the actual dynamics of rules, incorporating two sets of moderators: organizational moderators and rule-related moderators.
Research limitations/implications
– The findings indicate that many factors influence the modification of rules, and that there is no simple linear progression from one generation to another. Organizational learning is one among several other factors that influences the dynamics of rules for managing product development. Further research is needed to explore the dynamic relationship between different factors, the proposed moderators and changes to rules. Lack of historical record keeping in companies puts special requirements on research concerning rules.
Practical implications
– Companies need to consider how and why their present versions of rules have emerged, whether or not the existing rules can actually solve the challenges they face today, whether or not the rules support the intended company strategy, and what mechanisms influence their product development rules.
Originality/value
– A great deal of research has investigated the relationship between the uses of structured rule-based approaches to manage product development, but little is known about what makes these rules change. This is the first study to uncover the multitude of drivers that stimulate change in product development rules and to suggest sets of moderators that influence the outcome.
