Actors and innovators in the bioeconomy 219
This population was further pared down (removing 200 entities) in order to
exclude the non- organic sections of the population and to focus on the area
of bioenergy and circular economy related to organic waste.
11.3.2.1.3 CONFIRMATION By ASSOCIATION
To ensure that we had not excluded any target entities, a final analysis of the
population was conducted. Here we use two registers of entities that have a
strong but more nominal association with the bioeconomy. The so- called
‘Biodirectory’, which originated in 2016, showcased 80 entities that had been
involved in research programmes into sustainable technologies including
those funded under the Centres for Research- Based Innovation (SFI) and the
BIOTEK2021 Programme (BIOTEK2021, 2018). Half of these entities
overlap with either the project data or the patent- data already presented.
The other Biodirectory entities overlap with our final source, namely the
relevant branch organisations from the Norwegian Confederation of Companies (NHO) and the Federation of Norwegian Industries (Norsk Industri,
2018). Branch organisations were included in dialogue with the organisations
themselves and include those dedicated to wood processing, recycling,
seafood and aquaculture, as well as the broad category of food and beverages.
More than half of the members fit other identifiers in our approach. The
remaining entities are less certain and can be excluded depending on what
NIoBE is being used for.
11.3.2.2 The Norwegian Inventory of Bioeconomy Entities (NIoBE)
In the first stage, we once again focused on improving the ‘recall’ of the identification procedure by casting our nets wide enough that we did not prematurely exclude potential candidates of the ‘true population’. This stage yielded
a gross population of 2,792 entities, which can be considered an upper bound
for the population. The overall population entities may be narrowed according to the focus of the analysis. For example, firms that are identified through
more than one lens arguably yield the most robust identifier and could be the
focus. In other cases, a broader population may be useful.
In the subsequent step, we collected a variety of information on this
gross population. The industrial affiliations of the entities by NACE or by
other markers of activities, such as the trade descriptions found in financial
data in the AMADEUS dataset that Bureau van Dijk harvests from company
annual reports (Nelson & Rosenberg, 1993), provide information about the
activities of the firms: this is instrumental information that can be used to
make informed decisions about which types of firms fall outside the boundaries of the circular economy. On this basis the firms were first graded by
their apparent relevance to the circular bioeconomy (core, secondary, periphery) and then arranged according to the six categories studied in this
project: breweries, aquaculture, dairy, meat processing, waste processing, as
This population was further pared down (removing 200 entities) in order to
exclude the non- organic sections of the population and to focus on the area
of bioenergy and circular economy related to organic waste.
11.3.2.1.3 CONFIRMATION By ASSOCIATION
To ensure that we had not excluded any target entities, a final analysis of the
population was conducted. Here we use two registers of entities that have a
strong but more nominal association with the bioeconomy. The so- called
‘Biodirectory’, which originated in 2016, showcased 80 entities that had been
involved in research programmes into sustainable technologies including
those funded under the Centres for Research- Based Innovation (SFI) and the
BIOTEK2021 Programme (BIOTEK2021, 2018). Half of these entities
overlap with either the project data or the patent- data already presented.
The other Biodirectory entities overlap with our final source, namely the
relevant branch organisations from the Norwegian Confederation of Companies (NHO) and the Federation of Norwegian Industries (Norsk Industri,
2018). Branch organisations were included in dialogue with the organisations
themselves and include those dedicated to wood processing, recycling,
seafood and aquaculture, as well as the broad category of food and beverages.
More than half of the members fit other identifiers in our approach. The
remaining entities are less certain and can be excluded depending on what
NIoBE is being used for.
11.3.2.2 The Norwegian Inventory of Bioeconomy Entities (NIoBE)
In the first stage, we once again focused on improving the ‘recall’ of the identification procedure by casting our nets wide enough that we did not prematurely exclude potential candidates of the ‘true population’. This stage yielded
a gross population of 2,792 entities, which can be considered an upper bound
for the population. The overall population entities may be narrowed according to the focus of the analysis. For example, firms that are identified through
more than one lens arguably yield the most robust identifier and could be the
focus. In other cases, a broader population may be useful.
In the subsequent step, we collected a variety of information on this
gross population. The industrial affiliations of the entities by NACE or by
other markers of activities, such as the trade descriptions found in financial
data in the AMADEUS dataset that Bureau van Dijk harvests from company
annual reports (Nelson & Rosenberg, 1993), provide information about the
activities of the firms: this is instrumental information that can be used to
make informed decisions about which types of firms fall outside the boundaries of the circular economy. On this basis the firms were first graded by
their apparent relevance to the circular bioeconomy (core, secondary, periphery) and then arranged according to the six categories studied in this
project: breweries, aquaculture, dairy, meat processing, waste processing, as