History Repeating! Spatial Dynamics in Dutch Start‐Up Rates (1996–2013)

Abstract

The number of start-ups has skyrocketed in the Netherlands in the past ten years. Has this growth been accompanied by a shift in the spatial patterns of start-ups? This Windows on the Netherlands puts this question to the test and maps the dynamics in the spatial patterns of startups for the period 1996--2013. This is done at the disaggregated spatial level of the municipality. Even though we observe a slight shift of entrepreneurship to the east of the country, the overall spatial patterns in start-up intensity are highly stable: start-up rates are highest in the most urbanised municipalities. As the small spatial scale of analysis potentially allows for much variability, the found stability in the spatial patterns lends additional empirical support to the idea that patterns in start-up rates are highly persistent.

Entrepreneurial homeworkers

“…The regional entrepreneurship literature continues to grow rapidly, reflecting enduring interest in understanding entrepreneurs' venture location choices and the resulting implications for regional economic development. Recent research has analyzed, inter alia: the determinants of persistent differences in regional rates of entrepreneurship (Andersson and Koster 2010;Bishop and Shilcof 2017;Fotopoulos and Storey 2017;Koster and Hans 2017;Modrego et al 2017); regional firm entry and exit rates (Bishop and Shilcof 2017;Li 2017); the location and mobility of entrepreneurs (Di Addario and Vuri 2010; Kulchina 2016); regional knowledge spillovers as an entrepreneurship attractor (Audretsch et al 2006;Bonaccorsi et al 2014); and the concentration of entrepreneurship in neighborhoods, cities and clusters (Di Addario and Vuri 2010;Pe'er and Keil 2013). This valuable background has greatly enhanced our understanding of regional aspects of entrepreneurship.…”

Entrepreneurship in the Long-Run: Empirical Evidence and Historical Mechanisms

“…10 Correlation coefficients for regional start-up rates in successive years often assume values considerable above 0.9. As a result, regions 10 See Andersson and Koster (2011) for Sweden, Fritsch and Mueller (2007) and Fritsch and Kublina (2019) for Germany, Mueller et al (2008) and Fotopoulos (2014) for the UK, van Stel and Suddle (2008) and Koster and Hans (2017) for the Netherlands, Baptista et al (2008) for Portugal, Acs and Mueller (2008) and Qian (2022) for the US, and Kobayashi (2020) for Japan.…”

Data-Driven Decision Making: Qualitative Study at Digital Startup using Semantic Domain Analysis

“…It should come a little surprise that eventhough unicorn startups in Indonesia are on the rise, the development of new startups have decline over the past years [4]. Starting and closing a business is an ongoing process, and for startups, the failure rate can also reach 90% [5]. While there are many issues that can create or brake the success of startups, BI become increasingly important for company all size.…”