Bioeconomy as a Complex Adaptive System of Sustainable Development


Journal of International Business Research and Marketing
Volume 2, Issue 2, January 2017, Pages 7-10

Bioeconomy as a Complex Adaptive System of Sustainable Development

DOI: 10.18775/jibrm.1849-8558.2015.22.3001

Mariusz Maciejczak

Faculty of Economic Sciences, Warsaw University of Life Sciences – SGGW, Poland

Abstract: The bioeconomy is widely understood as an economic system that combines in a synergic way both natural resources and technologies, together with markets, people and policies. There are established links between old industries traditionally based on natural resources and new ones those previously had no direct relations. As a result, one industry utilizes the by-products of another very often closing the loop of circularity. The paper describes this system in a dynamic perspective, as a complex adaptive system. Complexity results from the inter-relationship and inter-action of system’s elements and between a system and its environment. Based on the empirical evidences from the European Union it is argued that bioeconomy as a platform networking several branches of economy could adapt to the changes that take place in the environment.

Keywords: Bioeconomy, Complex adaptive systems, Renewable resources

Bioeconomy as a Complex Adaptive System of Sustainable Development

1. Introduction

The concept of bioeconomy is recognized as not only a promise but also a solid and realistic foundation for achieving the sustainability needs worldwide. The basic assumption of this concept is to connect different socio-economic processes both from low tech and high tech sectors which focus on the utilization of renewable resources through application of appropriate knowledge and innovative technologies. As a result, there are delivered products and services, which lead to fulfilling goals that are considered  important from private and public perspectives. The bioeconomy is also perceived as a system that combines natural resources with technologies and other elements of the economic system such as markets, consumers, institutions or policies. Within bioeconomy system, there are build connections between industries and sectors in order to establish symbiotic relationships where one industry utilizes the by-products of another. As such bioeconomy is perceived very holistically in a wide systemic approach.

However, it is necessary to see this system not in a static way but applies more dynamic approach (Maciejczak M. and Hofreiter K., 2013). This is due to the dynamic and turbulent internal and external changes that practically prevent the achievement of Pareto optimum. Therefore, bioeconomy can be considered as a complex adaptive system. Complexity economics is considered as a mirror inversion of neoclassical theory (Levin R., 2000). Complex adaptive systems from economic perspective are characterized by Miller and Page (2007) by three main factors. Firstly, the complex economy is never in equilibrium but is constantly subjected to shocks, both exogenous and endogenous, that affect its short-term movements.  Secondly, the classical law of one price fails, and there are observed short term price deviations. Finally, complex adaptive systems rarely, if ever, achieve the sort of optimality.

It seems necessary to approach economic analysis of bioeconomy from a network, rather than a production and utility function perspective when one deals with complex systems. It is argued that dynamic systems are able to adapt in and evolve with a changing environment (Golebiewska B., 2014).

2. Literature review

In the social sciences, it is agreed that the complexity results from the inter-relationship, inter-action, and inter-connectivity of elements within a  system  and  between  a  system  and  its  environment  (Levin  R.,  2000; Mitchel M., 2011). As such, systems are able to adopt and become known as  Complex  Adaptive  Systems  (CAS).  According  to  Miller  and  Page (2007),  CAS  are  dynamic  systems  able  to  adapt  in  and  evolve  with  a changing  environment.  As  argued  by  Cham  (2001),  it  is  important  to realize that there is no separation between a system and its environment in the idea that a system always adapts to a changing environment. Rather, the system is closely linked with all other related systems making up an ecosystem. Within such a context, change needs to be seen in terms of co-evolution with all other related systems, rather than as adaptation to a separate and distinct environment (Vanberg V.J., 2004). Axelrod (1997) argues  that  what  distinguish  a  CAS  from  a  pure  multi-agent  system (MAS)  are:  the  focus  on  top-level  properties  and  features  like  self-similarity,  complexity,  emergence  and  self-organization.  A  MAS is defined as a system composed of multiple interacting agents; where the agents, as well as the system, are adaptive and the system is self-similar.

CAS is recognized as a complex, self-similar collectivity of interacting adaptive agents. Complex Adaptive Systems are characterized by a high degree  of  adaptive  capacity,  giving  them  resilience  in  the  face  of perturbation.  Communication  and  cooperation  take  place  on  all  levels, from the agent to the system level. Levin (2000) defines CAS systems in 8 Journal of International Business Research and Marketing terms  of  three  properties:  diversity  and  individuality  of  components, localized  interactions  among  these  components  and  an  autonomous process that uses outcomes of those interactions to select a subset of those components for replication or enhancement.

Day  (1994)  argues  that  when  thinking  of  the  economy  as  a  complex system  of  elements  the  appropriate  construct  to  understand  it  is  the network. It is because the generated added value does not just come from the  elements  contained  in  the  firm  but  from  the  connections  that  are forged between them. As networks evolve and produce more and better ranges of  products  using  more  productive  processes,  there  is observed increasing value added. As shown by Vanberg (2004) firms are bundles of network connections, as are economies. Such networks cannot be fully connected or be maximally efficient, because an economic system is not a machine. Networks are constantly being created and destroyed, along with products and organizations (Jackson M. and Watts A., 2002; Rosser J., 1999).

3. Research Methodology

The  presented  research  are  based  on  the  heterodox  assumptions  of deductive and descriptive reasoning, and the secondary data were coming from the Bioeconomy Observatory of the European Commission, using the data management tool DataM2, which is capturing statistics related to bioeconomy.

4. Research Results

From the point of view of economic theory, as stressed out by Metcalfe et al.  (2006), complex  systems  theory  is,  essentially,  a  body  of  theory about connections, distinguishing it from conventional economic theory which  is  concerned  with  elements,  supplemented  by  very  strong assumptions about connections. Component structures in such systems evolve through a process of specialization and integration as well as the process of innovation diffusion. Foster (2004) distinguished four general properties of  an  economic  complex  adaptive  system,  which  includes structure, its components, connections and evolution in the historical time domain.

Having in mind the above discriminants of the bioeconomy (Maciejczak M., 2015), and agreeing that as an economic system it has a network and complex structure as well as is influenced by the path dependency, one could distinguish its following properties:

1) agents – as every system the bioeconomy should be recognized as a set of economic agents performing different functions, not only devoted to supply and demand but also aimed to deliver knowledge or institutional framework;

2) connections – every agent in the bioeconomy system performs the role that  results  are  transmitted  by  the  links,  also  with  feedback  loops, established in the networks, which are subject to constant changes;

3) transformations – this characteristic is crucial for bioeconomy as much as crucial are renewable resources and knowledge, which both are used as basic sources for any bio-processes  which create private and public value added;

4) openness – this approach enables to obliterate the boundaries between the agent – a firm and its environment, making them more permeable, and thanks  to  that,  transfer  innovations  inward  and  outward;  firms  could become more innovative cooperating with partners by sharing risk and sharing reward;

5) evolution – the network of bioeconomy is subject to constant changes, which  not  only  influence  its  development  but  are  influenced  by  all historical changes.

Figure  1  presents  the  conceptual  model  of  bioeconomy  as  a  complex system.  Such system is  built  of  agents,  which  are  connected.  In such system  products  and  services  are  generated  from  application  of knowledge and innovative technologies into production processes which is based on renewable sources of biomass. By application of non-linear models of progress development and innovation diffusion as well as being pulled by the market, the bioeconomy system can generate products and services essential from private and public point of view. Both, private and public institutions finance and govern its functioning and growth.

Figure 1: The conceptual model of bioeconomy as a complex system. Source: author’s construction

Is,  however,  the  bioeconomy  not  only  complex  but  also  adaptive?  To answer  this  question,  two  synergetic  arguments  can  be  used.  First,  is describing  the  evolution  of  the  bioeconomy  concept.  The  second  is showing  how  path  dependency  resulted  in  the  primary  production  of energy from renewable sources.

In one of the first policy agendas of the bioeconomy, namely the Cologne Paper (European Commission, 2007) bioeconomy is recognized as the production of renewable biological resources and their conversion into food, feed, bio – based products and bioenergy. Here, is provided very narrow  approach  which  is  encompassing  the  classical  production function. In 2012, the European Commission stressed out that production paradigms of bioeconomy those should rely on biological processes and, as with natural ecosystems, use natural inputs, expend minimum amounts of  energy  and  do not  produce  waste  as all  materials  discarded  by  one process are inputs for another process and are re-used in the ecosystem (European Commission, 2012). In the evolution of bioeconomy concept in Europe it could be observed the focus is not only on production but also on energy savings and circularity of renewable resources, i.e. wastes.

In  2015  the  Council  of  Nordic  States  –  Norden,  pointed  out  that bioeconomy is a sustainable production and use of natural resources, with a  cross-sectorial  and  systematic  approach,  with  a  basis  in  circular economy (The Council of Nordic States, 2015). In this definition, being an  example  of  the  broadest  approach,  are  emphasized  the  elements of governance of production and circularity of the system.

Table 1: Contribution of the bioeconomy sub-sectors in the European Union’s economy in 2012

Sector Annual turnover (€ billion) Value added

(€ billion)

Employment (1000 s)
Agriculture 404 157 10200
Food and beverage 1040 207 468
Agro-industrial products 231 62 2092
Fisheries and aquaculture 36.6 9.7 199
Forestry logging 42 22 636
Wood-based industry 473 136 3452
Bio-chemicals 50 120
Bioplastics 0.4 1.4
Biolubricants 0.4 0.6
Biosolvents 0.4 0.4
Biosurfactants 0.7 0.9
Enzymes 1.2
Biopharmaceuticals 30 50 142
Biofuels 16 132
Total 2357 21790

Source: author’s construction based on Eurostat data

Bioeconomy is already one of the biggest and important components of the EU economy. The data shown for 2012 indicate that the EU bio-based economy turnover reached about 2.4 billion euro, with almost 22 million persons employed (Table 1). As the concept of bioeconomy evolved into use not only of primary sources of biomass, such as wood or agricultural crops  and  residues  but  also  biomass  from  renewable  wastes,  such products  were  increasingly  gaining  higher  shares  in  the  energy production.  What  is  important,  the  bioeconomy  sector  consumes  a biomass not only from plant and livestock agricultural production, incl. post-harvest residues as well as from wood and aquatic productions, but also from wastes.

In  this  context,  municipal  solid  wastes  (MSW)  becoming  as  an  ugly duckling  transforming  into  the  golden  swan.  This  kind  of  wastes  was forgotten by the economic theories and excluded by the businesses as not too much useful. Nowadays MSW is considered as a significant source of renewable  resources  and  energy  meeting  growing  needs  arising  from sustainable  concerns.  Specifically,  MSW  is  waste  generated  by commercial and household sources that are collected and either recycled, incinerated,  or  disposed  of  in  MSW  landfills.  However, circularity approaches  ‘design  out’  waste  and  typically  involve  innovation throughout the value chain, rather than relying solely on solutions at the end of life of a product. Closing the loop and implementing the concept of  circularity  in  the  economy  is  becoming  a  strategic  goal  to  many economies. In the European Union “A zero waste program for Europe” as well  “An  EU  action  plan  for  the  Circular  Economy”  and  many  other actions  were  undertaken  in  order  to  ensure  more  circularity  in  the economies  of  the  Member  States.  The circularity  in  their  economic systems should be focused on keeping the added value in products for as long as possible, ensuring their highest utility, and eliminate waste.

The circularity should accordingly be seen as a part of the broader concept of bioeconomy.  It  is  an  important  contribution  to  development  of  a sustainable, low carbon and resource efficient system in which steps are taken to maintain products, materials, and resources in the economy for as  long  as  possible  and  accordingly  to  measures  are  implemented  to minimizes the waste generation.

It  is  important  to  stress  out  that  industries  already  recognize  the opportunities  for  making  the  use  of  such  approach  and  improve  the resource productivity. As an example, can be mentioned the steps towards efficient utilization of resources from MSW. The main benefit from such measures is the reduction of the needs for primary production based input needs.  Therefore,  as  stressed  out  by  European  Environmental  Agency (2016) recycling and incineration towards energy recovering becomes an important part of MSW management in many European countries, incl. Belgium, The Netherlands or Germany.

5. Conclusion

This paper aimed to make an attempt to present and analyze bioeconomy as a complex adaptive system in the context of sustainable development. The performed analysis allows for the following conclusions:

  1. The classical  perspectives  of  perceiving  and,  as  a  consequence, analyzing  economy  are  changing  from  market  approach  of  static equilibriums into industrial organizations of dynamic networks.
  2. Bioeconomy as a concept gaining more and more attention of society, business, politics, and academy could and should also be analyzed from the perspective of  more  heterodox  approaches,  including  industrial organization.
  3. Bioeconomy can be presented as the complex adaptive system. The system, which using path dependency and connections between agents participating in evolving networks, is able not only to produce high added value but also adapt to the changing environment.
  4. As an adaptive  system  bioeconomy  sector  dynamically  changes seeking for new sources of incising productivity and efficiency according to  sustainability  needs,  which  exemplification  could  be the  concept  of circularity and use of wastes.
  5. It is advisable that further research on bioeconomy as complex adaptive system should be undertaken, in order to present all spectrum of issues related to its key properties distinguished in this paper and beyond.


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Early version of this paper was presented at the 2016 International Conference “Economic science for rural development” organized by LLU ESAF in Jelgava, Latvia, 21-22.04.2016. The Author wishes to thank anonymous conference’s reviewers as well as peer reviewers from Department of Economics and Management of Warsaw University of Life Sciences – SGGW for they valuable comments and remarks.


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