Scale-ups and High-Growth Firms

Table of Contents

1. Frontmatter

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2. Chapter 1. Introduction and Motivation

   • Open Access

   Alex Coad, Anders Bornhäll, Sven-Olov Daunfeldt, Alexander McKelvie

   Abstract

   The book begins with an introduction to research on High-Growth Firms and scale-ups, focusing on the development of the literature, and observing that early work on scale-ups focused on anecdotal evidence and case studies. In contrast, this book seeks to develop a rigorous and general definition of scale-ups that is amenable to being applied to datasets of firm populations from different countries and time periods.

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3. Chapter 2. Firm Growth, and High-Growth Firms

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   Alex Coad, Anders Bornhäll, Sven-Olov Daunfeldt, Alexander McKelvie

   Abstract

   This chapter discusses previous research into firm growth. In particular, Eurostat and the OECD proposed an indicator of High-Growth Firms in 2007 that has helped develop the field of HGF research, because having a standardized HGF definition fostered comparisons of research findings and cumulativeness of knowledge.

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4. Chapter 3. Stages of Growth Models

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   Alex Coad, Anders Bornhäll, Sven-Olov Daunfeldt, Alexander McKelvie

   Abstract

   Stages of growth models are important for understanding scale-ups. One of the differences between scale-ups and HGFs is that research on HGFs does not take growth stages into account, as long as growth is fast enough. This chapter presents Steve Blank’s 4-stage model of firm growth, where scaling up is stage 3. Hence, scaling-up does not occur directly at birth, among the youngest firms, but preparation is needed before scaling up. Differences between scaling up and so-called blitz-scaling are also discussed.

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5. Chapter 4. Eight Propositions About Scale-ups

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   Alex Coad, Anders Bornhäll, Sven-Olov Daunfeldt, Alexander McKelvie

   Abstract

   This chapter pushes further in our investigation of the nature of scale-ups by introducing the following eight propositions about scale-ups: (1) a scale up is a concept born of practitioners, not academics; (2) scale-ups are not just in the IT sector, but may be enabled by IT; (3) a scale-up is a qualitative concept from a ‘stages-of-growth’ model; (4) scaling up involves structural transformation; (5) a scale-up does not exist anywhere in a pure form; (6) scale-ups differ by degree, not by kind; (7) many scale-ups are exceptions; and (8) there may never be a standardized empirical definition of scale-up. Each of these eight propositions was either not clear, or was misunderstood, in some previous work.

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6. Chapter 5. Theoretical Definition of a Scale-up

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   Alex Coad, Anders Bornhäll, Sven-Olov Daunfeldt, Alexander McKelvie

   Abstract

   This chapter draws on the literature to develop our theoretical definition of a scale-up. A critical discussion of previous literature helps distinguish between aspects that are essential or unnecessary for a definition of a scale-up. We then put forward the following five suggestions for a theoretical definition of a scale-up: (1) Scale-ups are in all sectors, not just IT; (2) Scale-ups have relatively high levels of spending on marketing and sales; (3) Scale-ups have low marginal costs of production; (4) Scale-ups are young, but not too young; (5) In defining scale-ups, we start from the set of HGFs. The chapter ends with our own theoretical definition of a scale-up.

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7. Chapter 6. Empirical Definition of a Scale-up

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   Alex Coad, Anders Bornhäll, Sven-Olov Daunfeldt, Alexander McKelvie

   Abstract

   This book distinguishes between a theoretical definition and an empirical definition. The theoretical definition seeks to clarify the concept of a scale-up in the minds of readers, using familiar theoretical concepts (such as marginal cost) that may be prohibitively difficult to measure in standard datasets, because the theoretical ideas do not map neatly into empirical variables. An empirical definition is stated in terms of empirically relevant variables and concepts such as growth rates, growth indicators, and other variables that are found in available datasets. This chapter develops the empirical definition. It starts by stating four desirable properties of an empirical definition, and proceeds in 2 steps: Step 1 involves taking the subset of HGFs; and Step 2 involves selecting scale-ups from among non-scale-up HGFs on the basis of seven proposed conditions.

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8. Chapter 7. In Search of Scale-ups: Empirical Analysis

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   Alex Coad, Anders Bornhäll, Sven-Olov Daunfeldt, Alexander McKelvie

   Abstract

   This chapter takes our empirical definition of scale-up to the data: Swedish register data on over 700,000 firms for the period 1997–2001. 1.28% of firms meet the HGF criteria. Among these HGFs, it is rare for a firm to satisfy all 7 scale-up conditions (in line with the idea of ‘too many exceptions’). 25.89% of HGFs satisfy 5 or more of the 7 conditions for scale-ups, while 60.75% of HGFs satisfy 4 out of 7 conditions. Our analysis highlighted how missing values can cause problems when investigating which HGFs are scale-ups.

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9. Chapter 8. Concluding Remarks

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   Alex Coad, Anders Bornhäll, Sven-Olov Daunfeldt, Alexander McKelvie

   Abstract

   This chapter closes the book with a brief summary of the book’s purpose, and a brief statement of the theoretical and empirical definitions of scale-ups. While we argue that our book is timely, we also acknowledge the limitations of our book, chief among which is the data limitation of missing values affecting our empirical analysis.

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