Growing Small Business and the Economy Through Clustering

Small and medium businesses have difficulty getting past a critical threshold that allows them to grow in the market. Helping them collaborate with like-minded businesses helps their growth potential. A paper by Dhakal, et. al. (2013) discusses an open-innovation concept of living labs that allows stakeholders and customers to engage in the co-creation process together. They studied a cluster in Australia to show how this enhances business development and the economic engine.  

A living lab is a user-centered open innovation ecosystem (Hippel, 1986).  It uses modern technology to foster communication between stakeholders and customers to co-develop products.  The natural environment becomes the testing grounds for new products and services and this allows users to offer feedback on the success of changes and provide ideas on how to improve on the products and services. 

It provides a collaborative space (virtual or physical) that distributes problem-solving tools, capacities, and responsibilities to the end user to create greater innovation (van der Valt et. al., 2009).  This innovation is used to enhance the offerings of companies through enhanced products and services. In this context, innovation is seen as enhanced discovery whereby innovation equals invention plus exploitation (Roberts, 2007). 

Before an open innovation living-lab can be successful the stakeholders will need to agree on joint goals, and focus on the resolving of problems in the real world (Bergyall-Karaborn, et. al., 2009).  This process allows stakeholders to work collaboratively on developing products and consideration customer feedback to enhance their offerings. The information is shared among the stakeholders to further develop mutual products and services. 

When living labs have the right stakeholders and functionally work well together, each of the businesses receives a benefit for both the co-creation product/service as well as gain important knowledge for the enhancement of other products/services. When innovations are significant, it can have an impact on the regional well-being and local employment opportunities (Keniry, et. al. 2003). 

Living labs are beneficial to enhancing knowledge clusters. Clusters are defined as “a geographically proximate group of interconnected companies and associated institutions in a particular field, linked by commonalities and complementarities (Porter, 1998, p. 4). Cluster members need a way to communication to foster mutual growth. Greater growth contributes to the functionality of a larger economic hub.

The authors found that geographical togetherness of small businesses form around competence similarities. To enhance the local interaction it is possible to use open innovation (i.e. living labs) to further their growth. It requires a method operationalizing processes and developing mechanisms that help further innovation. Organizations that willingly collaborate around certain key objectives with other stakeholders and use customer feedback to enhance their products are likely to reap growth while the region experiences greater economic enhancement. 

Bergvall-Kåreborn, B., et. al. (2009). A Milieu for Innovation – Defining Living-Labs. In K. R. E. Huizingh, S. Conn, M. Torkkeli and I. Bitran (eds) Proceedings of the 2nd ISPIM Innovation Symposium: Simulating recovery - the Role of innovation management, New York City, USA. 6-9 December 2009.

Dhakal. et. al. (2013). The innovation potential of living-labs to strengthen small and medium enterprises in regional Australia. Australasian Journal of Regional Studies, 19 (3). 

Keniry, J., et. al. (2003). Regional Business – A Plan for Action, Department of Transport and Regional Services, Canberra.

Porter, M. (1998). Clusters and competition new agendas for companies, governments, and institutions. In M. Porter (Ed) On Competition (pp. 197-287), Harvard Business School, Boston.

Von Hippel, E. (1986). Lead users: a source of novel product concepts. Management Science 32, 791–805.

The Economic Theory of Chaos: Controlling the Uncontrollable

Chaos is a natural part of our lives and is prevalent in anything from weather patterns to economics. In order to understand the unpredictable nature of life and fluctuations in normal development through time Chaos Theory came into being. "Discoveries in quantum physics, biology, and chaos theory enable us to deal successfully with change and uncertainty in our organizations and our lives....the new science radically alters our understanding of the world, and it can teach us to live and work well together in these chaotic times" (Wheatley, 2009). Originally used in weather patterns and physics the theory has been applied to understanding and minimizing economic crisis.

Before understanding the theory it is important to first have a grasp of the field of economics. "Economics, if it is to be a science at all, must be a mathematical science … mechanics of utility and self-interest"(Jevons, 1924). The very purpose of economic models is to predict, explain and potentially forecast economic conditions. As a science it is subject to the same scrutiny of validity, relevance, and significance as other fields of study. Economics is used to explain everything from individual transactions to the cost of your student loans.

In most economic theories the individual agent is the central component. The economy can be seen as an analysis of how these agents influence each other through evaluations of worth.  When the agents continually evaluate each other they create what is called "the market". Analysis often focuses on the similarities and patterns of society as they relate to the price of commodities and goods. The French mathematician Henri Poincaré believed that people do not act alone but constantly watch each other to make decisions (Colander, 2011).

Economics is also often seen in terms of equilibrium in efficiency of functioning. “A characteristic feature that distinguishes economics from other scientific fields is that, for us, the equations of equilibrium constitute the center of our discipline. Other sciences, such as physics or even ecology, put comparatively more emphasis on the determination of dynamic laws of change” (Mas-Colell, Whinston & Green, 1995). Equilibrium can be seen as homeostasis where prices, supply, demand, activity, unemployment and other factors are accurate and on autopilot. This is where the market can self-regulate and the forces are in balance. Yet such equilibrium doesn't necessarily indicate stability of a system so Chaos Theory can help further explanations of systematic behavior.

When the system is out of balance a concept called Chaos Theory may be more accurate in predicting and controlling the outcome. According to Faggini and Parziale (2011) Chaos Theory represents, "a shift in thinking about methods to study economic activity and in the explanation of economic phenomena such as fluctuations, instability, crisis, and depressions."  The theory attempts to explain and understand market fluctuations ranging from hiccups to depressions in order to lessen their impact.

Through Chaos Theory it has been postulated by Ott, Grebogi and Yorke that small adjustments in the market can change the course of a natural economic system without having to change the fundamental principles (1990). In essence, as fluctuations occur it takes much less effort to adjust the system than attempting to control the whole system throughout its movement. Think of how thrusters on a spaceship can adjust the path of the flight with minimal energy by doing so when the ship first moves off course. Thus controlling chaotic fluctuations within the economic system relies in part on a number of principles (Faggini & Parziale, 2011):

1.) The fluctuations in chaos can be exploited for greater growth that would not be possible in less chaotic systems.

2.) Control based upon the sensitivities of initial conditions can create higher levels of efficiency.

3.) The amount of government adjustment in policy would be lessor than under traditional models that require an abundance of resources.

Chaos Theory includes the concept that pure control of an economic system is difficult, unrealistic, or impossible. Thus trying to obtain a perfectly controlled outcome would be costly and expensive in the long run. Under this theory it is wiser for a government to make small and incremental changes during times of fluctuation and chaos that help use attraction to obtain desired outcomes versus more common highly engaged adjustments.

One of the most difficult aspects of predicting and adjusting the economy is that such systems are large and complex. They are not rational human beings even if rational human beings are behind its face plate. Furthermore, in order to determine when a system is going into chaos it is necessary to have a reasonable benchmark of its homeostatic course of development. This can be difficult due to inadequate tools used to measure current economic systems full of fluctuating noise.




Colander, D. (2011). The economics profession, the financial crisis, and method. Journal of Economic Methodology, 17 (4).

Faggini, M. & Parziale, A. (2012). The failure of economic theory. Lessons from chaos theory. Modern Economy, 3. 

Jevons, W. (1924). The theory of political economy. London Journal, 57 (2).

Mas-Colell, M., Whinston, M. & Green. Microeconomic Theory. Oxford University Press; Oxford

Ott, E., Grebogi, C. & Yorke, J. (1990). "Controlling Chaos," physical review letters, 64 (11).


Wheatley, M. (2009). Leadership and the new science: discovering order in a chaotic world (Third Edition). San Francisco: Berrett-Koehler Publishers.