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Inner Strength Against Competitive Forces: Successful Site Selection for Franchise Network Expansion

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New Developments in the Theory of Networks

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

Abstract

For every franchise system, making the leap from the unknown to the commonplace requires a strategic plan for growth. The exogenous market perspective holds that evaluating market conditions is central to defining promising outlet locations since there are direct economic effects on performance arising specifically from location. The endogenous firm perspective (the resource-based view) and the social network approach together provide an inner strength perspective on interconnected firms; this perspective holds that access to internal and external resources offered at a certain spot determines site attractiveness, rather than location-specific market factors. This study combines both literature strands and, using a sample of 201 German franchisees, tests hypotheses (1) that explore which perspective dominates location decisions in practice, and (2) that seek to clarify the relevance of the decisive criteria for outlet performance. Results show that location decisions rely on both perspectives, yet, franchisee performance depends rather more on inner strength factors. We also find that expansion is better served by following a geographically dispersed cluster-approach, than by growing steadily from a baseline site.

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Notes

  1. 1.

    Some regard the late 1980s as the golden age of store location analysis, characterized by the “abandonment of the intuitive approach to location decision-making”. Yet in practice, the application of sophisticated models has always been limited (Birkin et al.).

  2. 2.

    See Huff’s (1964) early contribution, Craig et al. (1984), Ghosh and McLafferty (1987), Jones and Simmons (1990), Kelly et al. (1993), Christensen and Drejer (2005), Park and Khan (2006).

  3. 3.

    Examples of franchisees’ knowledge assets are local market know-how on marketing, human resources, quality control, or innovation capabilities that cannot easily be transferred and acquired by the franchisor (Windsperger 2004).

  4. 4.

    In a globalized world, where capital and knowledge travel at high speed, we would expect economic activity to spread over space. Yet, a tendency for geographic concentration occurs (“location paradox”). The reason may be that competitive advantage is local: due to frequent interaction opportunities in the vicinity, trust and the informal barter of know-how are decisively encouraged: “informal conversations were pervasive and served as an important source of up-to-date information about competitors, customers, markets, and technologies […] often of more value than more conventional but less timely forums such as industrial journals” (Enright 2000).

  5. 5.

    Since the number of ties a franchisee can entertain in the regional cluster directly depends on the number of franchisees present in the cluster, we cannot use this network characteristic to explain cluster size. Therefore, we focus on performance effects.

  6. 6.

    Some studies use sales growth in combination with data on market share, product innovation, or stock growth, none of which are useful in the case of the sample firms.

  7. 7.

    For the first system, we can obtain data on total sales of the previous business year and on franchisee satisfaction with their business performance. We use this data as additional dependent variables. Satisfaction items ask respondents to evaluate their recent performance relative to different comparison levels. Comparison levels are (1) alternative activities, (2) average industry sales growth, (3) own income expectations, and (4) own sales objectives. Anchoring success by reference to comparison levels is in line with Anderson and Narus (1990). The results of a principal component factor analysis show the four items to load highly on one factor. We build a scale that averages the sum of the scores on the four items, using equal weights. Cronbach’s alpha is 0.82. Inspections of item-to-total and inter-item correlations also provide support for scale reliability. The inner strength variables show the same significant results for satisfaction as well as for total sales as for growth; there are no significant results for market conditions.

  8. 8.

    The factor solution is robust (>93% explained variance, eigenvalue >1, KMO 0.79, significant Bartlett-test). Cronbach’s Alpha (0.73) and the inspection of item-to-total and inter-item correlations provide support for scale reliability. All variables are significant when introduced into Model 0 separately. Over 50% of the sample franchisees joined their system in the last ten years; we suggest that over time, market conditions do not vary dramatically.

  9. 9.

    We use costs as an instrument in the first stage of the 2SLS regression to estimate regional embeddedness. We measure costs using a business tax index as a proxy. This instrument fulfills the criteria of being both relevant and exogenous, as costs do influence location decisions – since tax affects franchisee profit – but do not influence the performance measure (sales growth) directly.

  10. 10.

    Still, we accept that some “basic standard” of economic characteristics (for total population or GDP e.g.) must exist in clusters so that the benefits of network resources can be used profitably.

  11. 11.

    This idea is supported by franchisee statements on their interaction structures. The interaction levels in both systems are high. The items for access to others’ support (item 1) and knowing others personally (item 2) correlate strongly with performance (−0.402, p <0.03; −0.367, p <0.02; both items are reverse-coded).

  12. 12.

    Distance to the nearest larger community is an explanatory variable for per capita sales for many city sizes (Ferber 1958). Regional clusters centering on larger communities provide a point of attraction, dragging demand within cluster boundaries. Population, however, is not uniformly distributed in space: total population usually increases with diminishing returns to scale from the clusters’ centre, as densely-populated regions are less likely to span a large (supraregional and above) than a small (regional) radius. For supraregional clusters, demand-dragging is thus less probable to result in significant performance-enhancing customer gains from outside the cluster.

  13. 13.

    A word of caution seems in order as regards infering processes from spatial patterns: Place versus periphery definitions are clearly imperfect. We explore mechanisms underlying superior performance of clustered franchisees, rather than try to define exact cluster ranges. Also, network and site characteristics are dynamic and path-dependent, which may alter a site’s attractiveness.

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Authors and Affiliations

  1. Institute of Strategic Management, Westfälische Wilhelms-Universität Münster, Leonardo-Campus 18, 48149, Münster, Germany

    Brinja Meiseberg

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  1. Thomas Ehrmann
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Correspondence to Brinja Meiseberg .

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Editors and Affiliations

  1. , School of Business and Economics, University of Jyväskylä, MaE, Jyväskylä, 40014, Finland

    Mika Tuunanen

  2. Fak. Sozial-u.Wirtschaftswiss., Inst. BWL / LS Organisation, Universität Wien, Brünner Str. 72, Wien, 1210, Austria

    Josef Windsperger

  3. Centre Recherche en Economic et, Management (CREM), Universite de Rennes 1, rue Jean Macé 11, Rennes CX, 35708, France

    Gérard Cliquet

  4. School of Management, Erasmus University Rotterdam, Burg. Oudlaan 50, Rotterdam, 3000 DR, Netherlands

    George Hendrikse

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Ehrmann, T., Meiseberg, B. (2011). Inner Strength Against Competitive Forces: Successful Site Selection for Franchise Network Expansion. In: Tuunanen, M., Windsperger, J., Cliquet, G., Hendrikse, G. (eds) New Developments in the Theory of Networks. Contributions to Management Science. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2615-9_7

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