The Role of Personal Factors in the Location Decision of Software Services Start-up Firms

Abstract

This paper explores the factors which influence the business location decisions of start-ups, focusing in particular on the role of personal factors. Established explanations of industry location emphasize proximity to firms in the same or related industries and proximity to a wider set of business services, though recent research suggests that personal factors may play an important role in explanations of industry location—particularly in technology-enabled sectors. A survey of 97 new firms, founded between 2008 and 2012, in the Irish software services sector, shows that the business location decision is influenced by the personal motivation of entrepreneurs to attain a desired quality of life, and that this outweighs economic factors such as proximity to firms within the same or related industries, proximity to a broader set of supporting business services, infrastructure or the availability of government support schemes. Personal factors are particularly important to firms located outside the Dublin metropolitan area and to home-based businesses. This has important policy implications for national and regional governments seeking to encourage entrepreneurship in technology-enabled service sectors.

Keywords:

• industry location
• software services
• cloud computing
• spatial planning
• entrepreneurship policy

Disclosure Statement

No potential conflict of interest was reported by the authors.

Funding

The research undertaken in this paper was supported by the Irish Centre for Cloud Computing and Commerce, a national Technology Centre funded by Enterprise Ireland and the Irish Industrial Development Authority.

Notes

1. Similarly, the Keeble and Nachum (2001) study of 300 business services SMEs across South East England identifies the co-existence of a Central London neo-Marshallian cluster which benefits from proximity to clients and collective learning, and a decentralized pattern of business services firms across South East England which operates independently of the London cluster.

2. The National Institute of Standards and Technology (NIST) defines cloud computing as “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction” (Mell & Grance, 2011, p. 2). Cloud computing is regularly cited within the European Union (EU) as a strategic economic enabler contributing to GDP, employment and innovation (Etro, 2009; Pierre Audoin Consultants, 2010; Deloitte, 2011; IDC, 2012; Leimbach et al., 2014).

3. Bieri provides a review of empirical studies assessing the relationship between Florida's creative class theory and economic growth (2010).

4. In the terminology of the OECD–EU definition of cities in Europe, the urban centre population size of Dublin is ranked as extra-large (XL: 500,000–1,000,000). One Irish city (Cork) is ranked as medium (M: 100,000–250,000) and three (Galway, Limerick and Waterford) as small (S: 50,000–100,000). See Dijkstra and Poelman (2012) for further details: http://ec.europa.eu/regional_policy/sources/docgener/focus/2012_01_city.pdf

5. See, for example, Rubalcaba and Gago (2003) and Camacho-Ballesta et al. (2014). The NUTS is a geocode standard developed and regulated by the EU for referencing the subdivisions of EU member states. NUTS 2 is the second sub-level of the statistical hierarchy. The number of NUTS 2 regions within a given EU member states varies considerably in terms of population density and surface area: with Germany (39), UK (37), France (27) and Italy (21) comprising the largest number of NUTS 2 regions, while Portugal (7), Denmark (5), Finland (5) and Ireland (2), for example, comprise considerably fewer. See http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/introduction for further details.

6. Accelerator programmes are typically mentoring programmes of a 3–6-month duration provided for a cohort of companies in exchange for an equity share. Incubator programmes generally last for a longer duration and provide mentorship and support for individual companies (Bound & Miller, 2011).