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Home Alone:Innovation and sales growth intentions among the solo self-emplyed
Home Alone: Innovation and sales
growth intentions among the solo self-
Areti Gkypali and Stephen Roper
Enterprise Research Centre and Warwick Business School,
University of Warwick, Coventry, CV4 7AL.
Proportion of the self-employed
who are ‘solo’
40.0 50.0 60.0 70.0 80.0 90.0 100.0
Source: Eurostat labour market statistics database, 2015.
Distribution of sales per employee
by sizeband (£000pa, 2015)
Solo SE Micro Small Medium
£000 pa £000 pa £000 pa £000 pa
1% 7.00 8.33 6.67 6.92
5% 10.00 16.00 10.67 10.00
10% 15.00 21.43 15.00 14.00
25% 30.00 40.00 28.57 25.00
50% 50.00 75.00 60.00 53.33
75% 100.00 130.00 106.38 107.42
90% 160.00 200.00 180.00 187.50
95% 250.00 250.00 250.00 240.00
99% 300.00 350.00 333.33 347.83
Source: LSBS 2015
• For the solo self employed (who intend to remain solo) growth can only come
through increased sales (or reduced costs). But how do they chase growth? What
shapes their strategies for innovation?
• Only one prior study of innovation by the solo self-employed of which we are
aware: de Vries and Kosters 2014 who studied innovation among 1,400 solo self-
employed in the Netherlands in 2010
– Locational factors proved relatively unimportant for product/service innovation but were
more significant in terms of process changes.
– In terms of the business, the type of work being undertaken, and co-operation for innovation
were also significant influences.
– At the individual level, education and ambition were strongly related to innovation propensity
with age, gender and intrinsic motivation having little significant influence.
• Here, we use data from the first wave (2015) of the Longitudinal Small Business
– Explore what shapes the growth strategies of solo self-employed
– Test a version of the theory of planned behaviour augmented with adaptive expectations
Theory and key hypotheses
• The theory of planned behaviour suggests a link between beliefs or
aspirations and future actions
• -> H1: The solo self-employed with stronger growth aspirations will
have stronger future innovation intentions.
• But argue here too that individual’s prior experience or success will
also shape their future intentions. This leads to:
• H2a: Positive experience in innovation will increase individuals’
sales growth intentions
• H2b: Prior experience of a growth episode will increase individuals’
sales growth intentions
Data and methods
• LSBS survey data for around 4,000 solo self-employed. Cross-sectional
analysis but some lag data in the survey
• Sales growth intention (cts) asks individuals ‘by approximately what
percentage do you aim to have grown your sales in three years’ time?’.
• Innovation intentions (binary) ‘Does your business plan to Develop and
launch new products/services over the next three years’
• Models are for IIt and GIt
• Probit: 𝑰𝑰 𝒕 = 𝜶 𝟎 + 𝜶 𝟏 𝑮𝑰 𝒕 + 𝜶 𝟐 𝑰𝑰 𝒕−𝟏 + 𝜶 𝟑 𝑿𝑳 𝒕 + 𝜶 𝟒 𝑪𝒐𝒏𝒕𝒓𝒐𝒍𝒔 𝒕 + 𝜺 𝟎
• Regression: 𝑮𝑰 𝒕 = 𝜷 𝟎 + 𝜷 𝟏 𝑮𝑰 𝒕−𝟏 + 𝜷 𝟐 𝑰𝑰 𝒕−𝟏 + 𝜷 𝟑 𝑪𝒐𝒏𝒕𝒓𝒐𝒍𝒔 𝒕 + 𝜺 𝟏
• Hypothesis tests are essentially:
– H1: 𝛼1 > 0 ; 𝐻2𝑎: 𝛽2 > 0 ; H2b: 𝛽1 > 0.
Illustrative probits for innovation
Illustrative (regression) models for
• Key empirical results:
(1) Growth and innovation intentions of solo self-employed strongly
linked to past experience
(2) Growth intentions negatively related to maturity of business
(3) Growth intentions positively related to social and network
• In conceptual terms (2), (3) are consistent with TPB. (1) suggests the
potential for a dynamic TPB which allows for learning and the
impact of prior experience on planned behaviours (or is this a
• In policy terms, finding (3) is interesting. Encouraging networking
among the solo self-employed may be one way to boost innovation
and growth intentions and increase productivity.