A Typology of Attitudes towards the E-Bike against the Background of the Traditional Bicycle and the Car

Although it is generally accepted that innovators and early adopters have a particular influence on the uptake of electric bikes, other groups, whose reactions to innovation have not been studied, are perhaps wrongly marginalised. Such individuals, often relying on stereotypes, also need to be included in researchers’ scope of interest. Therefore, the aim of the CAWI survey was to determine the attitudes of respondents, both users and non-users of electric bikes, and on this basis to classify by k-means analysis the attitudes towards the e-bike compared to the traditional bicycle and the car. The results obtained show a large variation between the designated classes. What most of them have in common is a strong attachment to the private car, which is typical for the cycling culture of this part of Europe, but the psycho-physical characteristics of the surveyed remain the strongest differentiating factor. Therefore, in the light of the opinions collected, it seems that the group Gadget lovers 1 and 2, whose share was about one-quarter of the total number surveyed, may be the most inclined to change their transport behaviour. This means that the e-bike, as an innovation, can overcome a critical discontinuity stage on the innovation diffusion curve in the Innovation Adaptation Lifecycle (IAL).

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Theoretical notes regarding the practical application of Stafford Beer’s viable system model

Kybernetes ◽

10.1108/k-02-2017-0069 ◽

2018 ◽

Vol 47 (2) ◽

pp. 262-272 ◽

Cited By ~ 4

Author(s):

Markus Orengo

Keyword(s):

System Model ◽

Practical Application ◽

Viable System Model ◽

Content Type ◽

Early Adopters ◽

Practical Applications ◽

Diffusion Curve ◽

Viable System ◽

Societal Problems ◽

Practical Implications

Purpose This paper aims to capture current difficulties with the practical application of the viable system model (VSM). On this basis, a set of suggestions toward a more effective application of the model is made. Design/methodology/approach The study is based on observations from practical applications of the VSM, systematically collected by the author. Findings The paper suggests that the VSM is currently stuck in the typical chasm of a bell-shaped diffusion curve. The paper makes six propositions to smoother pass from the early adopters to the early majority. Research limitations/implications The six findings imply various research efforts. Practical implications In contrast to frequent claims that VSM should be made accessible easily to a larger number of people, the paper suggests that a smaller number of better trained VSM experts support a larger number of managers with a more generic know how. Social implications A more focused but broader application of the VSM may lead to better societal organizations and therefore to a more efficient effective solution of societal problems. Originality/value The paper suggests to tighten the focus of the VSM to the very abstract topic of judging variety balances and at the same time to better connect the model with the suite of established methods and tools in management. This is a contrast to other attempts, which either simplify the VSM or extend it into a comprehensive methodology.

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Networks, Homophily, and the Spread of Innovations

The Connected Past ◽

10.1093/oso/9780198748519.003.0016 ◽

2016 ◽

Author(s):

Anne Kandler ◽

Fabio Caccioli

Keyword(s):

Case Studies ◽

Innovation Diffusion ◽

Spatial Dynamics ◽

Population Level ◽

Travelling Wave ◽

Cultural Traditions ◽

Individual Level ◽

General Acceptance ◽

Diffusion Curve ◽

The Individual

The question of how and why innovations spread through populations has been the focus of extensive research in various scientific disciplines over recent decades. Generally, innovation diffusion is defined as the process whereby a few members of a social system initially adopt an innovation, then over time more individuals adopt until all (or most) members have adopted the new idea (e.g. Rogers 2003; Ryan and Gross 1943; Valente 1993). Anthropologists and archaeologists have argued that this process is one of the most important processes in cultural evolution (Richerson et al. 1996) and much work has been devoted to describing and analysing the temporal and spatial patterns of the spread of novel techniques and ideas from a particular source to their present distributions. Classic case studies include the spread of agricultural inventions such as hybrid corn (e.g. Griliches 1957; Ryan and Gross 1943), the spread of historic gravestone motifs in New England (Dethlefsen and Deetz 1966; Scholnick 2012), and the spread of bow and arrow technology (Bettinger and Eerkins 1999). (For a more comprehensive list see Rogers and Shoemaker (1971) who reviewed 1,500 studies of innovation diffusion.) Interestingly, the temporal diffusion dynamic in almost all case studies is characterized by an S-shaped diffusion curve describing the fraction of the population which has adopted the innovation at a certain point in time. Similarly, the spatial dynamics tend to resemble travelling wave-like patterns (see Steele 2009 for examples). The basic puzzle posed by innovation diffusion is the observed lag between an innovation’s first appearance and its general acceptance within a population (Young 2009). In other words, what are the individual-level mechanisms that give rise to the observed population-level pattern? Again, scientific fields as diverse as economics/marketing science (e.g. Bass 1969; Van den Bulte and Stremersch 2004; Young 2009), geography (e.g. Hägerstrand 1967), or social science (e.g. Henrich 2001; Steele 2009; Valente 1996; Watts 2002) offer interesting insights into this question without reaching a consensus about the general nature of individual adoption decisions. In archaeological and anthropological applications, population-level patterns inferred from the archaeological record, such as adoption curves, are often the only direct evidence about past cultural traditions (Shennan 2011).

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