Loading...

Diffusion of Service Innovation. Innovation patterns of the Netflix and Uber services

Research Paper (undergraduate) 2017 30 Pages

Communications - Multimedia, Internet, New Technologies

Excerpt

Content

Tables, figures and equations

1 Services - Theoretical background 1.1 Services – characteristics and definition 1.2 The service-dominant logic

2 Innovation – Theoretical background 2.1 Innovation term and the traditional innovation process 2.2 Approaches to innovation diffusion 2.3 Service innovation approach to innovation diffusion

3 Examples: The innovations and diffusions of Netflix and Uber

4 Conclusion

References

Appendix

Appendix I – Further explanations on the S-D logic

Appendix II – Product Life Cycle and Hype Cycle

Appendix III – The Bass Model

Appendix IV – The service innovation patterns and roles

Appendix V –Innovation dimensions vs. innovation patterns matrix

Tables, figures and equations

Figure 1: Traditional Innovation process and the 3rd generation Stage-Gate-Model (Source: Own depiction after Disselkamp, 2012, p. 95; Cooper et al., 2002).

Figure 2: Technology and diffusion curve (Source: own depiction in relation to Meade and Islam, 2008; Tidd and Bessant, 2013, pp. 370).

Figure 3: Adoptions influencing variables (Source: own depiction after Tidd and Bessant, 2013, pp. 373-376).

Figure 4: Rogers' adaption process (Source: Rogers, 2003, pp. 163).

Figure 5: Rogers’ diffusion process of innovations and characterization of the adopter groups (Source: own depiction after Rogers, 2013).

Figure 6: Four dimensional service innovation model (Source: den Hertog and Bilderbeek, 1999, p. 5).

Figure 7: Six dimensional model of service innovation and the (dynamic) capabilities for realizing new service experiences and solutions (Source: den Hertog, van der Aa and de Jong, 2010, p. 493).

Figure 8: Used service innovation dimensions and capabilities by Uber throughout their history as of December 2016 (Source: own depiction with elements from den Hertog, van der Aa and de Jong, 2010; Hartmans and McAlone, 2016; Wikipedia contributors, 2016).

Figure 9: Used service innovation dimensions and capabilities by Netflix throughout their history as of January 2016 (Source: own depiction with elements from den Hertog, van der Aa and de Jong, 2010; Shih, Kaufmann and Spinola, 2009; Popper, 2016).

Figure A- 1: Product lifecycle (Source: own depiction after Kotler and Armstrong, 2000).

Figure A- 2: Hype cycle for emerging technologies (Source: Gartner, 2014).

Figure A- 3: Patterns of services innovation and their player specific roles specific roles (Source: den Hertog and Bilderbeek, 1999, p. 13).

Table 1: Characteristics of the innovation itself (Source: Tidd and Bessant, 2013, pp. 373-376).

Table 2: Comparison of conceptual perspectives for innovation in services (Source: Morrar, 2014, p. 9).

Table 3: Dimensions of service innovations (Source: Miles, 2008, p. 112). 11

Table A- 1: Description of the innovation patterns (Source: den Hertog and Bilderbeek, 1999, pp. 10-14).

Table A- 2: Innovation dimensions vs. innovation patterns matrix (Source:Own depection after den Hertog and Bilderbeek, 1999).

Equation A-1: Bass Model (Source: Bass, 1969)

1 Services - Theoretical background

In this part of this work the theoretical background of services, its’ definition and characteristics and the general view on businesses and marketing of services is shortly discussed.

1.1 Services – characteristics and definition

The academic body primarily focuses on three dimensions when arguing about definitions of services. These dimensions are (Bruhn, 2016):

- Potential: Services are recognized as potentials or abilities of a provider created by humans or machines to provide specific deeds. - Process: The interpretation as an activity that results in material or immaterial effects. Those serve the needs of third parties. Characteristic is that production and sales are happening at the same time (Uno-Actu principle). - Results: The result of the service provision process is intangible.

However, multiple authors have done work on the characteristics of services and therefore come up in the process with further characteristics for services. More or less, these services are the implicit in the dimension Bruhn (2016) mentioned, but for a clearer differentiation there shall be mentioned here (Gallouj and Weinstein, 1997; Gallouj, 2002; Miles, 2008; Gallouj and Savona, 2009; Morrar, 2014):

- Intangibility – the output of a service often can’t be measured. - Production and consumption cannot be separated – referring to the Uno-Actu-Principle customers become ‘co-producer’s - Heterogeneity – The output of a service cannot be fully predetermined In that extend that even the value contributed by the ‘co-producer’ shapes the outcome of the service - Perishability – Storage and usage postponement of services are not possible.

A synopsis of these dimensions finally results ultimately in a definition for services that is highly useful for marketing analyses and therefore in service of this paper as it later on analyses the market diffusion of distinct services.

The definition Bruhn is providing in his textbooks with Meffert (2009) and ultimately in this online source (2016) is adopted for readability and language purposes:

Services are independent, marketable deeds linked to the provision and / or use of capacities while external factors (those that are not within the sphere of influence of the service provider) are combined with the internal factors (those that are within the sphere of influence of the service provider) during the creation process with the aim of achieving beneficial effects on external factors, on people and their objects.

The characteristics seem to be highly dominated by the intangibility and the Uno-Actu-principle. This is the reason that the marketing of services especially cares about these process variables by adding 1 (Personal) or even 3 additional P (Physics, Personal, Process) to the leading framework of the 4 P of marketing (Bruhn, 2016; Meffert and Bruhn, 2009).

1.2 The service-dominant logic

Vargo and Lusch (2004, as cited in Maglana, 2007) had a breakthrough when speaking about the term service as they proposed a new understanding of goods and services in the marketing discipline. Their core statement is that services are more prevalent than goods whereas goods should be simply viewed as means of the firm to conduct a service. In their point of view the production of goods only serves as a means of “transmitting” services to the customer. The service-dominant logic (S-D logic) for an exemplary car manufacturer would state, their business is neither manufacturing nor selling cars, but providing mobility services to the consumer through their cars. Thus, the S-D logic reverses the importance of the terms “service” and “goods” while stating that both remain important.

Important characteristics of the S-D logic are the strong integration of the customer as co-producer, creating strong communication bonds and even enabling new businesses (Maglana, 2007). Another aspect is the change between operand and operant and the resources (Constantin and Lusch, 1994). For further explanations on the S-D logic see Appendix I.

2 Innovation – Theoretical background

This part of the work looks at the term and process of innovation, then turns to traditional patterns and approaches to innovation diffusion and describes distinct service innovation approaches to that lead towards an understanding of the diffusion of services.

2.1 Innovation term and the traditional innovation process

The term innovation is used here in all its’ different approaches by the respective researchers as this is another concept to broad to look at in the terms of this work. The author however defines it as the application of better solutions that meet new requirements, unarticulated needs, or existing market needs through the application of inventions in that particular field (Maranville, 1992; Specht, 2016).

Abbildung in dieser Leseprobe nicht enthalten

Figure 1: Traditional Innovation process and the 3rd generation Stage-Gate-Model (Source: Own depiction after Disselkamp, 2012, p. 95; Cooper et al., 2002).

The process of innovation is usually depicted as a static one that happens within the organization. However newest practical and theoretical approaches have opened the process towards outside sources. This openness is limited mostly to the first stages that consider idea creation, called ‘fuzzy front end”. Although there are many mechanisms to manage the process and funnel the innovation effort, e.g. Stage-Gate-Model evaluation routines, there was little to no effort on gaining feedback from firsthand contributors outside or within the firm, as this would be costly and involve a change management process. This is called the funnel paradigm (Disselkamp, 2012). The latest version (3rd generation) of the Stage-Gate-Model, an innovation management approach, features constant user feedback, although stops after the phase of market launch (Cooper et al., 2002). For a comparison of the traditional and the newest Stage Gate Process see figure 1.

2.2 Approaches to innovation diffusion

First of all, it seems to be important to clarify the terms of diffusion and adoption, as these terms are often used interchangeably. While diffusion describes the spread over entire markets, adoption refers to individual purchase decisions. This shows that they are related, but have to be distinguished. Adoption focuses on the individual level and this individual‘s decisions concerning the purchase and use of an offering. It is a mental process of either positive (adoption) or negative (rejection) outcome (Bähr-Seppelfricke 1999). The aggregation of individuals’ decisions is carried out by the diffusion on market-level (Rogers, 2003).

Diffusion, as Rogers puts it (2003, p. 5), means:„The Process by which an innovation is communicated through certain channels over time among the members of a social system”.

In 1962, Everett Rogers (cited as Rogers, 2003 in a more recent edition) proposed that the life cycle of innovations can be described using the ‘s-curve’ or ‘diffusion curve’. This diffusion research examines how ideas are spread among groups of people. Accordingly diffusion is determined by the conditions that increase or decrease the likelihood that members of a given culture will adopt an innovation, a new idea, product or practice. In the early stage of a particular innovation, the rate of adoption is low; however the diffusion rate accelerates until a market’s majority is reached. The S-curve model or diffusion-curve assumes that innovations spread by information transmission and geographical proximity. The s-curve can be seen in relation to the technology lifecycle or technology s-curve. This model assumes that every technology has a technological ceiling according to its degree of advancement. Therefore, at the end of an S-curve, old technologies are replaced by new ones. Consequently, the model is used for detecting technological shifts and supports reasonable decisions (Foster, 1986; Tidd and Bessant, 2013). The curves can be seen in figure 2.

Inspiration for these approaches is taken from product lifecycle concept (see Appendix II).

Abbildung in dieser Leseprobe nicht enthalten

Figure 2: Technology and diffusion curve (Source: own depiction in relation to Meade and Islam, 2008; Tidd and Bessant, 2013, pp. 370).

Enriching these approaches, especially Rogers’, adoption‘s influencing variables are defined by researchers and can be grouped into three clusters (see figure 3). However there is little consensus regarding the relative importance of each variable (Tidd and Bessant, 2013).

The characteristics of the innovation itself, the first of the three clusters, are explained in table 1.

Abbildung in dieser Leseprobe nicht enthalten

Figure 3: Adoptions influencing variables (Source: own depiction after Tidd and Bessant, 2013, pp. 373-376).

Table 1: Characteristics of the innovation itself (Source: Tidd and Bessant, 2013, pp. 373-376).

Abbildung in dieser Leseprobe nicht enthalten

Rogers‘ adoption process (see figure 4) can be modeled along five different stages and is based on models of buying behavior from consumer‘s research. The different stages do not necessarily mean a strict sequential process. Before a consumer deals cognitively with the decision to adopt an innovation, he has to overcome an awareness barrier consisting of knowledge and persuasion. For deriving a decision, individuals compare the perceived information with the personal situation. The implementation and confirmation influence decisions in later equal situations (Rogers, 2003).

Abbildung in dieser Leseprobe nicht enthalten

Figure 4: Rogers' adaption process (Source: Rogers, 2003, pp. 163).

As not all individuals adopt innovations in a social system at the same time, the diffusion of innovations does not work at once. Instead, they tend to adopt in a time sequence, and can be classified into adopter categories based upon how long it takes them to begin using the new idea. For marketing purposes, it can be very useful marketing activities to be able to identify which category certain individuals belong to (Tidd and Bessant, 2013; Rogers, 2003). The criterion for adopter categorization is innovativeness. This is defined as the degree to which an individual is relatively early in adopting a new idea. Innovativeness is considered "relative" so that an individual has either more or less of it than others in a social system. (Rogers, 2003). The diffusion curve and the underlying adopter categorization can be seen in figure 5.

The transition into the between early adopters and early majority (imitation phase) can cause a shift in attention. Whilst early adopters may have emphasized technical performance, the later adopters are more likely to be concerned with price or convenience (Rogers, 2003). Moore (1991) says this is the phase of crossing the chasm. Research by Frattini (2014 et al.) shows that the subsequent successful diffusion of an innovation into the mainstream market has very little to do with the product itself, and much more with the positive acceptance of early adopters. However, the epidemic approach of the shown models has been criticized because it assumes that all potential adopters are similar and have the same needs (this assumption evens allows a mathematical approach to it, see Appendix III), which is unrealistic. Rogers (2003) has identified a number of shortcomings of research and practice:

- Assumption of a linear, unidirectional communication activity
- Assumption one-to-many communication
- Strong Action-Orientation
- Assuming adoption as the dependent variable
- Assuming rapid diffusion across a social system - neglecting the prevention for bad innovations

Abbildung in dieser Leseprobe nicht enthalten

Figure 5: Rogers’ diffusion process of innovations and characterization of the adopter groups (Source: own depiction after Rogers, 2013).

2.3 Service innovation approach to innovation diffusion

Taking the regards of Rogers (2003) to acclaim, the service innovation approach has to be even more complex than the under 2.1 shown approach. This becomes especially important for the benefits and the general shift in thinking stated in 1.2 and the characteristics of services shown in 1.1.

While the body of research that deals with the frameworks describing the organizational approach to service innovation has come to a rather broad conclusion of at least seven different approaches (Miles, n.d.; 2008), Service innovation studies have come up with three essential ways of how services are actually innovated (Morrar, 2014; for a specific distinction see table 2):

- Demarcation: the service-based approach (Gallouj, 1994) – Inventing new frameworks for service innovation
- Integration: the Integrative approach (Gallouj and Weinstein, 1997) – Consolidating frameworks to fit on both technological and service innovation
- Assimilation: the traditional approach (Djellal and Gallouj, 2010) – Dealing with services as with technological goods.

[...]

Details

Pages
30
Year
2017
ISBN (eBook)
9783668431843
ISBN (Book)
9783668431850
File size
7.7 MB
Language
English
Catalog Number
v358172
Institution / College
University of Malta – Edward de Bono Institute
Grade
2,3
Tags
Netflix Uber Innovationen Innovation Innovationmanagement service service innovation pattern capabilities

Author

Share

Previous

Title: Diffusion of Service Innovation. Innovation patterns of the Netflix and Uber services