How Does Information Networking Create an Export Region?

Export driven economies fuel themselves through an octane boost of information. Information makes their way into opportunity finding, employment, and development. With the right methods of information transference regions can further develop their export driving economies by understanding how innovation fulfills demand-side and supply-side economics. Paul McPhee (2012) explores innovation strategy information spillover contributions as an important catalyst in simulating exports and employment. 

Local development exists within a national context. Local stakeholders and business members work together to create development. Local networks and supply chains also rely on greater information links in national networks to be successful (Bathelt, 2005).  In other words, there exists the tighter information transference within local networks and wider networks within the nation. Even though the author doesn’t state this it can also include information and resource vines throughout the globe.

This is demonstrated by international organizations that seek investment locations that have assets, organizational and institutional structures that support innovation information that fosters development (Paniccia, 2002).  As a bounded rationality such organizations draw in this information to create new products and services that have market relevancy. Without the information sources full development is not possible due to a lack of development feed.

We can find a number of examples within the market. In Australia clusters formed from networks of regionally based firms within the wine, fishing, film, education, and tourism industries that collaborate and innovate collectively and individually through alliance, commissions, federations, and associations (Roberts and Enright, 2004).  Each industry has the opportunity to work with other industries in both the local setting as well as the national setting to create new products and services. Local clusters exist within a wider national and international context.

The author found that information transference fostered exportation of products and services. A process of increasing the sourcing, generation, transferring, and sharing of information within regional networks is necessary to increase export related employment. This information is used for mutual development that impacts demand-side and then export-side growth.  When information transference speeds up the opportunities from growth and exportation also increase and this can lead to higher levels of regional employment.

Comment: The study lends support to the concept that tighter formations of economic vines exist in clusters and these clusters are woven into regional hubs that are connected to other hubs both within a nation as well as across the globe. The success of local economies is based in the ability to quickly and easily transfer information and resources through their economic hubs. These hubs use their resources to create newer and better products.

Bathelt, H. (2005) Cluster relations in the media industry: Exploring the ‘distanced neighbour’ paradox in Leipzig. Regional Studies, 39, pp. 105-127.

McPhee, P. (2012). Export driven regional development: a comparison of policies based on tiberi-vipraio-hodgkinson innovation strategies and networked information flows. Australasian Journal of Regional Studies, 18 (1). 

Pannicia, I. (2002) Industrial Districts: Evolution and Competitiveness in Italian Firms, Edwards Elgar, Cheltenham

Roberts, B. H. and Enright, M. (2004) Industry clusters in Australia: Recent trends and prospects. European Planning Studies, 12(1), pp. 99-121.

Social Networks Percolate Products and Opinions

Word of mouth fosters social learning about issues, products, and opportunities.  Friends that act and think alike often create clusters and these clusters can influence the purchasing choices as well as the decisions members make. Economists often have difficulty formulating how social networks formulate and influence people’s impressions of products and services. Research by Arthur Campbell (2013) sheds light on how word of mouth in social networks influences perception of value. 

When individuals are interested in a concept or product they are naturally more willing to engage in word of mouth. Generally, as a product’s price is lower it raises the interest level and the potential discussion of the product leading to more word of mouth activity. It is this interaction that brings to the forefront ideas, concepts, and discussions on products that are settled within a group. 

One of the difficult aspects of understanding social networks and diffusion is the complexity of the system.  Despite this complexity, it is known that as activity increases information is spread out to a wider group of people thereby creating more advertisement. The complexity has made chasing down the pieces of information and how they spread difficult.  Yet through models it is possible to understand the process of information peculation in an imperfect manner.

One potential way to look at how information is transferred is in a formula:

Ξ ⊆ { ( i, j ) | i ≠ j ∈ N }

Everyone is connected to a social network = ( N, Ξ )

Nodes = n

Relationship between individuals i and j = ( i, j ) ∈ Ξ

The probability of a person i passing out information = ν ( θ i , P )

The model is undirected in the sense that information can percolate anywhere. All of the consumers are uninformed and the chance that people will buy a product is based on a percentage of the amount of people that become informed. The timing of the model can be seen as-

(i) Each person in the population becomes informed with independent probability

ε ≈ 0 (later they may also become informed through advertising).

(ii) Informed individuals tell all their friends about the product through WOM

with probability ν ( θ i , P ) and purchase the product if θ i ≥ P.

(iii) Step 2 is repeated for newly informed consumers until there are no more

consumers being informed.

The model is impacted by availability of competitive products, information, pricing, and a whole array of other factors that go into the process. When a competitive product or alternative explanation is not available it will naturally impact the options and choices within the social network. Likewise, if more information about a product is available it can impact the eventual agreement and promotion of such products with the group. 

When companies advertise they often seek to hit specific components within the social networks. Those persons that are more socially connected will likely spread their impressions of the products or services more widely. This is a simple function of connectivity to other members and the ability to be an influencer within the network. Most of us would recognize the superstar promoters of products and services.

The paper finds a number of interesting associations of price, information/advertisement, and the connections of the network. Generally, as information passes through the network in “buzz” and in tight clusters the prices remain higher. However, if the information passes more slowly or in dispersed networks the prices will remain lower. Word of mouth is a medium that could be positive or negative in its impact. 

Thinking about how information moves through networks it is important to remember that members will engage in social learning based upon how they evaluate the products against each other. If popular opinion is that the product is not desirable it will hamper others from buying that product. It means that we are social creatures that evaluate the work of products based upon how others view those products within our networks. If their feedback is negative we will come to the conclusion that a product is less worthy. 

Such a model does not necessarily need to work with products alone but could be used within an organizational setting to understand how information moves quickly among members. Each person who obtains the information, evaluates it based upon their social schemata, and then promotes that viewpoint to others. If the information is of significant worth it will move faster while if it is of little worth it will spread slower.  One must have an internal gauge to think independently from their clustered networks and this is unlikely for the majority of the population as they are connected to clusters who think alike.  Thus, our opinions are often a direct result of our social networks.

Campbell, A. (2013). Word-of-mouth communication and percolation in social networks. American Economic Review, 103 (6).