Distributed Informal Information Systems for Innovation: an Empirical Study of the Role of Social Networks

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Distributed Informal Information Systems for Innovation: an Empirical Study of the Role of Social Networks

Vasco VasconcelosPedro CamposCENTERIS 2010 , October 2010


Motivation

- Innovation is essential to competitiveness and represents the way in which to anticipate, live with, or react to change (Ratti, 1991);

-Hakansson (1987), suggested a new perspective for Manegerial Sciences that sees innovation (and technological development in general) as a product of exchange among different agents (firms, individuals, in the network)

- Knowledge capture through the interaction of individuals is therefore accumulated in social networks.

- Information and Communication Technologies are frequently seen as an important enabler for such networks and a key factor in Economy;


Motivation

- Information technologies used for communicating and spreading innovation fall into two categories (McAfee, 2006): :

(i)direct channels : person to person communication, email, instant messaging, etc.• Low share and low communicability of information for the other agents involved

(ii)platforms: intranets, corporate web sites, corporate portals, etc.


Motivation

-Knowledge management Systems have tried to elicit Tacit knowledge

- TK is knowledge that is difficult to transfer to another person by means of writing it down or verbalising it. (ex, ability to ride a bicycle)

- TK, Best practices an relevant experience in the companies are often available to others in databases


Hypothesis

Social networks are used as Distributed Informal Information

Systems for Innovations by market research professionals


Networks and the Accumulation of the Stock of Knowledge

Campos (2008):

- In Economics, an inter-firm network is a set of firms (nodes) that interact through inter-firm relations (connections or links);

-Firms (the agents) contain cognitive attributes that help them build their own decisions;

-Connections are set up with other firms in order to establish production relationships, cooperation, etc.

Expected increase of profits and survival.


Distributed Informal Information Systems for Innovation (DIISI) and the Concepts of Innovation

-A Distributed Information System: multiple autonomous entities (individuals, organizations, computers, etc.) that communicate through various means, usually computer networks;

-Internet and the Web evolved to a platform for collaboration, sharing, innovation and user-created content—the so-called Web 2.0 environment (Lai & Turban, 2008);

-Includes social and business networks;

-Collective intelligence-Enterprise 2.0

(moving from data-centric to people-centric models)



“Distributed Informal Information Systems for Innovation” (DIISI):

-“Distributed”: the stock of knowledge is created through the interaction of the distributed agents at the micro-level (individuals) and spread at the macro level, with feedback to all agents in the network;

-“Informal”: in many situations, there is no intention a priori of creating a formal information system.


• Knowledge captured through the interaction of individuals is therefore accumulated in social networks.

• Informal structures of knowledge that is shared by firms or individuals (or both) can be seen as Distributed Informal Information Systems for Innovation.



-Corporate use of social media is quickly changing from an adoption stage to a paradigm focused on the comprehension of how people and institutions take advantage of it (Lenhart, 2009);

-Market Research Professionals need to embrace this new reality and mental models;

-Most common goals for the use of social networks for market research purposes (Chadwick (2006) and Day & Schoemaker (2006)):

-Finding Business Partners;-Academic;-New Business; -Benchmarking;-Find Human Resources;-Costumer Experience;-Concept Testing;-Product Development.



The creation of distributed informal information systems for innovation as emergent processes of the interaction in social networks

Benchmarking Concept Testing Product development

New Business

I N N O V A T I O N

(...)

Creation of Information Systems for InnovationCreation of Information

Systems for InnovationCreation of Information Systems for Innovation

Creation of Information Systems for InnovationCreation of Information

Systems for InnovationCreation of Information Systems for Innovation



Market research and Innovation: an empirical study of a possible DIISI

In order to capture the use of social networks, a survey was made:

• Target population: market research professionals;

• Four Social networks: Linkedin, Hi5, The Star Tracker and Twitter;

• To capture the innovation capabilities inherent to market research

professionals, we gather in-formation about eight main concepts: Finding Business Partners, Academic, New Business, Benchmarking, Find Human resources, Costumer experience, Concept testing and Product development.


Sample

9 Nationalities:

-Portuguese: 74,60%;

-American: 9,52%;

-Argentinian: 4,76%.


Sample

Professional headlines (19):

-Marketer: 17,74%;

-CEO: 11,29%;

-Business Manager: 9,68%;

-Teacher: 8,06%;

-Market Researcher: 8,06%.


Sample

Industries (15):

-IT: 26,98%;

-MKT and Info Management: 14,29%;

-Consulting: 9,52%;

-Banking: 7,94%;

-Education: 7,94%.


Sample

Education Level:

-University Graduate: 58,73%;

-Masters or Doctorate: 31,75%;

-High-school Graduate: 6,35%;

-College Graduate: 3,17%.


Findings

Use of social networks:

-22,22% never use them;

-11,11% use them frequently or all the time;

Use of social networks (per industry):

-Pharmaceutical/NPO: never use social networks;

-Building Materials (50%), Consulting (42,86%) and Consumer Goods (40%) never use social networks;

-Wed Development (100%) and Education (60%) use social media on a permanent/continuous basis;

-11,11% of Marketing and Information Management Professionals claim never to use social networks for research.


Most Frequently Used Social Networks in Market Research

Overall:

Linkedin is the most used: 58,73%;

Never used by 16,66%.

Facebook: 46,03%;

Twitter: 31,75%.


Most Frequently Used Social Networks in Market Research

By industry/service:

-Foods & Beverages: -Facebook (50%);-Hi5 (50%);

-Trade Publishing:-Facebook (50%);-SecondLife (50%);

-Import/Export:-Facebook (50%);-Twitter (50%);

-Education:-Twitter (26,67%);-Linkedin (33,33%);

-Marketing Info Management:-Linkedin (37,50%);-TheStarTracker (20%).


Goals of Using Social Networks for Market Research

-Linkedin:-Idea Generation (27,78%);-Concept Testing (13,39%);(Only one used for finding Human Resources and new business partners);

-Hi5: Generating Ideas (100%);

-Facebook: Idea Generation/Consumer Experience (33,33%);

-Twitter:-Idea Generation (30%);-Consumer Experience (33%);-Concept Testing (14,81%);-Product Development (11,11%);

-TheStarTracker:-Idea Generation (33,33%);-Product Development(33,33%);-Consumer Experience (33,33%);


Goals of Using Social Networks for Market Research

-Benchmarking:-MySpace (33,33%);-Twitter (5%);-Delicous (100%);-Facebook (37,03%);

-Finding new business partners and new business opportunities are poorly mentioned.


Perceived Advantages of the Use of Social Networks for Market Research


Perceived Advantages of the Use of Social Networks for Market Research


Concluding Remarks

i. Nearly 80% of the respondents use one or more social networks for market research purposes; these numbers indicate the importance and dimension of this phenomenon in which social networks are seen as a new market research tools, even though its use is not always consistent;

ii. Several social networks are used, with different goals;

iii. Social networks, while market research tools pass up some gaps or weaknesses found in more “traditional” research methodologies: they allow a vision of the consumer as a dynamic entity, inserted in mutually influential groups, providing richer information;


Concluding Remarks

iv. Data retrieved is sometimes fuzzy and difficult to analyze;

v. The use of social networks (and social media) allows professionals to create and develop relationships and networks from which they can extract, mash-up and analyze data from several relevant sources, and maintain contact with those sources for long-term useful information for their business, in the same way intranets do inside companies;

vi. Within this community of users, and due to the interaction of the accumulated stock of knowledge emerging at the individual (micro) level, a new DIISI was observed in the sample. In this case, the scope of the DIISI was limited to the sample of market research professionals that use social networks for innovation purposes such as the ones stated by Chadwick (2006) and Day & Schoemaker (2006).


References

• Campos, P., Brazdil, P., Brito, P., “Organizational survival in cooperation networks: the case of automobile manufacturing”, in L. Camarinha-Matos, H. Afsarmanesh, and M. Ollus (editors), Network-Centric Collaboration and Supporting Frameworks, Springer, 2006, pp. 77-84

• Chadwick, S.: Client-driven change: The impact of Changes in Client Needs on the Research Industry. International Journal of Market Research, 48, 391–414 (2006)

• Day, G.S. & Schoemaker, P.J.H.: Peripheral Vision: Detecting the Weak Signals that will Break or Make your Company, Cambridge, MA, Harvard Business School Press (2006)

• Hakansson, H.: Industrial Technological Development: a Network Approach, London, Croom Helm (1987)

• Lenhart, A.: The Democratization of Online Social Networks, Pew Internet &American Life Project, October 8(2009)

• McAfee, A.: MIT Sloan Management Review, Enterprise 2.0: The Dawn of Emergent Collaboration, Vol. 47, No.3. Spring (2006)

• Ratti, R.: Small and Medium-Size Enterprises, Local. Synergies, and Spatial Cycles of Innovation, in R. Camagni (editor), Innovation Networks: Spatial Perspectives, London, Belhaven Press, pp.71–88 (1991)

Technology

Distributed Informal Information Systems for Innovation: an Empirical Study of the Role of Social Networks