Christian Felzensztein on Marketing Externalities to Improve Agribusiness Clusters Competitiveness - A perspective from proximity, presented at the 15th TCI Global Conference, Basque Country 2012.

2. BUILDING MARKETING EXTERNALITIESBUILDING MARKETING EXTERNALITIES
TO IMPROVE AGRIBUSINESS CLUSTERSTO IMPROVE AGRIBUSINESS CLUSTERS
COMPETITIVENESS:COMPETITIVENESS:
A perspective from proximity
Christian Felzensztein PhD
Universidad Adolfo Ibañez, Chile
c.felzensztein@uai.cl
Cristian Geldes PhD
Universidad de La Serena, Chile
cgeldes@userena.cl
www.clusterinnovation.com

3. Introduction
• Cooperation between firms in marketing activities in industry
clusters settings is an area that only started to receive attention the
past decade, despite its importance to increase firms competitiveness
(Brow and Bell, 2001; Brown et al, 2010; Felzensztein et al, 2012).
• “Inter-firm marketing cooperation” has been considered as “active
externalities” in clusters and has been argued to include: joint
activities such as participation in trade fairs, market research, new
product development, trade missions to new markets, branding and
sales to local and foreign markets (Felzensztein et al, 2010).

4. Types of cluster externalities
Demand-side (market driven) externalities Supply-side (production driven)
externalities
Passive • Output multipliers
• Localized demand
• Increased market share
• Chance of discovery
• Credibility
• Informational spill over
• Specialized labor force
• Technological spill over
• Input multipliers
• Informational spill over
Active • Active joint marketing activity
o Trade fair participation
o Delegations to clients
o Trade missions
o Firm referrals
o Information
gathering/sharing
• Infrastructural support
• Joint research and development

5. • Social networks & geographical proximity are determinants of active
marketing externalities (Felzensztein & Gimmon, 2007; Felzensztein y Gimmon, 2009; Felzensztein et al,
2010a; Brown et al, 2010:).
(Felzensztein et al, 2010b: Long Range Planning)
1. What other factors affect marketing externalities?
2. What other dimensions of proximity can determine marketing externalities?
Research questions:

6. • Proximity approach from economic geography (Boschma and Frenken, 2010)
• Used to explain interrelations between actors, especially learning,
innovation and cooperation (Boschma; 2005, Cantiu, 2010)
• Key issue in industrial districs and clusters (Ozman; 2009)
• Different types of proximity (Knoben y Oerlemans, 2006)
• Studies analyze few types of proximities (Carbonara y Giannoccaro, 2010).
We propose to study relations between marketing externalities
(inter-firm marketing cooperation) in industry clusters and
proximity dimensions proposed by Boschma (2005).

7. Theoretical model and hypothesis
Geographical
Proximity
Social
proximity
Marketing
externalities
Cognitive
proximity
Organizational
proximity
Institutional
proximity
Proposed model

8. Hypothesis
H1: Geographical proximity facilitates positive relationship
between marketing externalities and non-spatial dimensions of
proximity
H2: Non-spatial proximities are positively related to marketing
externalities
H2.1: Cognitive proximity is positively related to marketing externalities
H2.2: Social proximity is positively related to marketing externalities
H2.3: Organizational proximity is positively related to marketing externalities
H2.4: Institutional proximity is positively related to marketing externalities

9. Research context
Chile is among the top 20 global exporters of agricultural and
forestry products, while accounting for about 10% of the and
10% of national employment.
Agribusiness cluster of "Province of Limarí” is a semi-arid land.
The main agricultural products are grapes, wine, avocados and
mandarins.

10. Method and data
• First stage: We propose and improve scales
to represent the constructs for interfirm
marketing cooperation and each dimension of
proximity proposed by Boschma (2005).
• Second stage: We validated scales with
Confirmatory Factory Analysis (CFA) and test
the interrelations between proximity and interfirm
marketing cooperation with two Structural
Equations Models (SEM).
On line survey to
1544 agribusiness
firms of Chile (119
answered)
Field survey to 312
firms of agribusiness
cluster (100%
answered)

11. Results: On line survey
• 1544 survey to agribusiness firms
• 162 answered (10,49%)
• 119 totally answered (7,71%)
• 25 items identified
• 4 constructs or latent variables
• CFA results
CONSTRUCT
CRONBACH´S
ALPHA
AVE CR MSV ASV
INTERFIRM MARKETING
COOPERATION
0.89 0.70 0.87 0.10 0.04
INSTITUTIONAL-COGNITIVE
PROXIMITY
0.83 0.46 0.87 0.34 0.26
SOCIAL PROXIMITY 0.59 0.47 0.73 0.40 0.09
ORGANIZATIONAL
PROXIMITY
0.75 0.54 0.82 0.40 0.13

12. Results: Field validation survey
Universe: 9,344
agribusiness firms
Stratificated by
“Comunas”
Convenience
sample (there is no a public
and official list of firms)
312 sampled (3,3%)
95% of confidence
and 5% error
4 latent variables
identified and 12
indicators or items

13. Results: SEM1. Interrelations between proximity
dimensions and marketing externalities or IMC

14. Results: SEM2. Interrelations between proximity
and marketing externalities or IMC (second
order)

15. Conclusions
• Our specific scale is a good means to measure the phenomena of proximity
and marketing externalities or interfirm marketing cooperation (high levels of
validity and reliability)
• Geographical proximity facilitates the relationship between non-spatial
dimensions of proximity and marketing externalities (H1), but:
• Only institutional proximity is positively related to marketing externalities
(H2.4). Organizational-cognitive proximity is negatively related to marketing
externalities (H2.1 y H2.3)
• As second order factor (SEM2), there is no statistically significant relation
stated between interfirm marketing cooperation and proximity.
• Other factors promote and facilitate joint activities between firms: i) trade
and business associations or the government (Porter, 1998; Andersson et al 2004; Ketels
et al, 2006), ii) external factors such as market opportunities or threats (Traill y
Meulenberg, 2002; Johnson et al, 2009; Capitanio et al, 2010) and iii) information and
communication technologies.

16. Implications
• Deeper analysis of the concept of marketing externalities
cooperation (joint activities that have more impact).
• Expand the research focus to the role of trade and business
associations and the government, the effects of communications
technologies and external factors such as market opportunities
and threats.
• For managers, develop activities to promote interfirm marketing
cooperation in clusters