Christoph Teller*, Andrew Alexander and Arne Floh(*, corresponding author, c.teller@surrey.ac.uk)

Department of Marketing and Retail Management (University of Surrey)

Published in Industrial Marketing Management

(DOI: 10.0.3.248/j.indmarman.2015.07.010)

The Impact of Competition and Cooperation

on the Performance of a Retail Agglomeration and its Stores

Presentation of the paper

Download the paper from • Elsevier (incl. a Powerpoint presentation describing the paper), • the University of Surrey Repository (SRI) • and ResearchGate)

ReferenceTeller, Christoph, Alexander, Andrew, Floh, Arne. 2016. “The Impact of Competition and Cooperation on the Performance of a Retail Agglomeration and Its Stores.” Industrial Marketing Management, 52, pp. 6-17. DOI: 10.0.3.248/j.indmarman.2015.07.010.

How to get the paper?

Professor Christoph TellerChair in Retailing and MarketingHead of the Department of Marketing and Retail Management Web: http://www.surrey.ac.uk/sbs/people/christoph_teller/index.htm

Professor Andrew AlexanderChair in Retail ManagementSurrey Business School Web: http://www.surrey.ac.uk/sbs/people/andrew_alexander/

Dr Arne FlohSenior Lecturer in MarketingSurrey Business SchoolWeb: http://www.surrey.ac.uk/sbs/people/arne_floh/

Authors

• Competition and cooperation between stores increase agglomeration performance.

• There is a positive spill-over effect between agglomeration and store performance.

• Cooperation increases store performance indirectly via agglomeration performance.

• The spill-over effect nullifies competition’s negative impact on store performance.

• Coopetition capabilities of stores enhance competitiveness of an agglomeration.

Highlights

• Underpinning: Network theory in a service (delivery) context

• Aims: – (1) Evaluate the effects of competition and cooperation

on the performance of stores in agglomerations, (2) Assess the implications of competition and cooperation between stores in an agglomeration for the managers of the stores, and for those with direct managerial responsibility for the agglomeration itself

• Contribution to theory and practice: – Emphasis on the complexity of the competition and

cooperation between stores within an agglomeration, – Importance of effective co-management of competition

and cooperation by store and agglomeration managers.

Introduction – Aims and contribution

• Retail and service agglomerations represent retail and service stores located in close proximity to each other

• Nodes (i.e. stores) and actors (i.e. store managers), as representations of retail and service organisations, are embedded in a network of interconnected formal and informal relationships

• Agglomerations are (geographically bounded) networks (Håkansson & Ford, 2002) and in the eyes of consumers (horizontal) service delivery networks (Tax, McCutcheon, & Wilkinson, 2013)

Agglomerations as networks

StoreStore

StoreStore Store

Store

store

Store

Customers

StoreStore

(Retail and Service) Agglomeration

Inter-firm relationships:Cooperation and

CompetitionCooperative purchasing

Cooperative marketing and

operations

Suppliers of management, marketing and

operations service for

agglomerations

• Aim of (inter-organisational) networksis to maximise efficiencies, synergies and organisational learning by sharing resources (Chetty and Wilson, 2003) and to increase firm survival rates and the performance level of individual actors (Wilkinson and Young, 2002).

• Network synergies, (agglomeration or) spill-over effects (Teller and Schnedlitz, 2012) = positive effect of the network/alliance performance on organisational productivity (Oum et al., 2004)

• The whole set of service units (stores) contributes to a holistic customer experience that enhances those service units’ attractiveness to customers. This synergetic effect, drives the performance of agglomerations, which then spills over onto their stores (Swaminathan & Moorman, 2009)

• Extend of spill-over effect differs between more and less powerful stores (e.g., Finn & Louviere, 1996)

H1: The greater the agglomeration performance, the higher is the store performance.

Conceptual model – “network spill-over effect”

• Aim of network cooperations is to acquire resources, reduce uncertainty, enhance legitimacy and attain collective goals (Brass et al., 2004)

• Cooperation between the stores in agglomerations (e.g., collaborative funding, management of resources, formal and informal knowledge sharing) is one of the core capabilities of agglomerations, increasing their performance levels and thus competitiveness (Lavie, 2006; Teller & Schnedlitz, 2012)

• (Collaborative/central) management, marketing and promotion enhance attractiveness, performance and competitiveness (Teller and Elms, 2010; Warnaby et al., 2002, 2005)

H2: The greater the cooperation between stores in an agglomeration, the higher is the agglomeration performance.H3: The greater the cooperation between stores in an agglomeration, the higher is the store performance.

Conceptual model – “network cooperation effect”-

• Similar/common resources/capabilites and market commonalities increase competition within networks (Peng et al., 2012)

• Positive effect of a network of competitors on the financial performance of organisations (Luo et al., 2007)

• Competition enhances the attractiveness of agglomerations for customers, and thus their performance (Oppewal and Holyoake, 2004)

• Nevertheless, competition is not beneficial for all stores (Teller & Schnedlitz, 2012)

H4: The greater the competition between stores in an agglomeration, the higher is the agglomeration performance.H5: The greater the competition between stores in an agglomeration, the lower is the store performance.

Conceptual model – “network competition effect”

Conceptual model

Cooperation (ξ1)

Competition (ξ2)

Store performance(η2)

H3 ([+] γ21)H2 ([+] γ11)

Agglomeration performance

(η1)H1 ([+] β21)

H5 ([-] γ22)H4 ([+] γ12)

NB: This depiction focuses on the key effects proposed in the paper. Please refer to the paper regarding moderation effects and the inclusion of control variables

• Survey: Self-administered questionnaire• Key informants: Store managers • Populations of interest: All retail/service stores in three

distinctive inner-city agglomerations– AGG1, supraregional and dominant high

street with 320 stores (usable questionnaires, n, 170; 53%); – AGG2, upmarket inner city retail cluster:

160 stores (n, 64; 40%);– AGG3, second-order high street: 147 stores

(n, 43; 29%);• Survey process: Store visit, identification of informants, pre-

notification and distribution, after 10 days collection and check – three waves

Methodology

Cooperation within the network

(agglomeration) (ξ1)

Competition within the network (agglomeration)

(ξ2)

Performance of the network

(agglomeration)(η1)

Performance of the node (store)

(η2)

x14

x13

x12

x11

x24

x23

x22

x21

y13

y12

y11

y23

y22

y21

3

5

5

3

5

5

Vorhies and Morgan, 2005Bell et al., 2010

Vorhies and Morgan, 2005Bell et al., 2010

Morgan et al., 2003

Prahinski and Benton, 2004

Factor loadingsλ xn,yn>.7

t-values>1.96(Hulland, 1999)

Internal Consistencyαξn,ηn>.7

(Nunnally, 1978)Composite reliability

ρξn,ηn>.7(Fornell and Larcker, 1981)

Convergent validityAVEξn,ηn>.5

(Bagozzi and Yi, 1988)Discriminant validity

FLR<1(Fornell and Larcker, 1981)

COOPETITION

Outer/measurement model

Structural effects Coefficient(p-value, effect size)

H1: Agglomeration performance (η1)Store performance (2) β21 .460***(s)

H2: Cooperation (1) Agglomeration performance (1) γ11 .217***(m)

H3: Cooperation (1)Store performance (2) γ21 .078ns(w)

H4: Competition (2)Agglomeration performance (1) γ12 .231***(m)

H5: Competition (2)Store performance (2) γ22 -.138*(w)

Total effects (direct plus indirect effects) Coefficient

H2: Cooperation (1) Store performance (2) γ21+γ11*β21

(Mediator, η1)

.178**(m)

H5: Competition (2) Store performance (2) γ22+γ21*β21

(Mediator, η1)

-.032ns(w)

Notes: *, t-values significant at p<.05 level (**, p<.01; ***, p<.001); t-values calculated by applying a bootstrapping procedure with 1,000 subsamples (Chin, 1998); (w), weak effect (f2-value ~.02), (m), moderate effect (f2-value ~.15); s, strong effect (f2-value ~.35); coefficients of determination, , .260; , .207.

Results – structural effects (direct)

Cooperation within the agglomeration

(ξ1)

Competition within the agglomeration

(ξ2)

Performance of the store

(η2)

Performance of the agglomeration

(η1)

Confirm: H1, H2, H4, H5

Reject: H3,

COOPETITION β21, 460***(s)

γ12, .231***(m)

γ11, .217***(m)

γ21, .078ns(w)

γ22, -.138*(w)

Cooperation increases agglomeration performance directly and store performance indirectly (mediation through agglomeration performance)

- Competition increases agglomeration performance directly and store performance indirectly (mediation through agglomeration performance)- The negative effect of competition on store performance is nullified.

The performance spills over to the store performance

!!! Not significant difference between different types of agglomerations and stores!!!

• Success (failure) can breed success (failure): Spill-over effect between agglomeration/network and store/node performance (confirms: Wilkinson and Young, 2002; Teller and Schnedlitz, 2012)

• Sleeping with the “frenemy” …: Coopetiton increases agglomeration/network performance (confirms: Peng et al., 2012) and thus

– Competition (confirms: Luo et al., 2007; Oppewal and Holyoake, 2004) and

– Cooperation (confirms: Swaminathan and Moorman, 2009; Brass et al., 2004; Teller and Elms, 2010) simultaneously.

• …for the greater good …: Coopetition does not translate into store/node performance DIRECTLY but is mediated by network performance (confirms: Peng et al., 2012; partly disconfirms: Oum et al., 2004)

Theoretical implications

• Shared fate of stores within agglomerations• Call for more collaboration (management, marketing,

promotion, infrastructural services etc.), rationale for investment• The bright side, for stores, of competition in agglomerations • Coopetition – a promising mind-set in /strategy for evolved

agglomerations (borderless networks)

Practical implications

• Replication in other settings: agglomeration formats, locational alliances, countries

• Extension of the model– Antecedents of cooperation and competition

(coopetition)– Antecedents of agglomeration/store performance

• Test of causality of spill-over effects

Outlook

Questions, observations, comments … c.teller@surrey.ac.uk

Reference: Teller, Christoph, Alexander, Andrew, Floh, Arne. 2016. The Impact of Competition and Cooperation on the Performance of a Retail Agglomeration and Its Stores. Industrial Marketing Management, 52, pp. 6-17. DOI: 10.0.3.248/j.indmarman.2015.07.010.