BUILDING MARKETING EXTERNALITIES BUILDING MARKETING EXTERNALITIES TO IMPROVE AGRIBUSINESS CLUSTERS TO 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

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).

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

• 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:

• 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).

Theoretical model and hypothesis

Geographical Proximity

Social proximity

Marketing externalities

Cognitive proximity

Organizationalproximity

Institutional proximity

Proposed model

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 externalitiesH2.2: Social proximity is positively related to marketing externalitiesH2.3: Organizational proximity is positively related to marketing externalitiesH2.4: Institutional proximity is positively related to marketing externalities

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.

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)

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

CONSTRUCTCRONBACH´S

ALPHAAVE 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

Results: Field validation surveyUniverse: 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

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

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

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.

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