Do firms’ investments in digital technologies leave a footprint in their growth aspirations? We employ a unique survey of more than 4,000 firms in Sweden to investigate whether firms that invest in software development are more likely to aspire to grow. There is a positive relationship between software development and growth aspirations, and firms that develop software are particularly more likely to aspire to grow through internationalization, i.e. expanding on new markets within as well as outside the European Union. Even after controlling for innovation, the result shows that for a wide array of firms, software development has become an essential input in the pursuit of growth and internationalization.

Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are recognized to have significant effects on industry and business dynamics, not least because of its impact on the preconditions for entrepreneurship. There is yet a lack of knowledge of GenAI as a theme in entrepreneurship research. This paper presents a systematic literature review aimed at identifying and analysing the evolving landscape of research on the effects of GenAI on entrepreneurship. We analyse 83 peer-reviewed articles obtained from leading academic databases: Web of Science and Scopus. Using natural language processing and unsupervised machine learning techniques with TF-IDF vectorization, Principal Component Analysis (PCA), and hierarchical clustering, five major thematic clusters are identified: (1) Digital Transformation & Behavioural Models, (2) GenAI-Enhanced Education & Learning Systems, (3) Sustainable Innovation & Strategic AI Impact, (4) Business Models & Market Trends, and (5) Data-Driven Technological Trends in Entrepreneurship. Based on the review, we discuss future research directions, gaps in the current literature as well as ethical concerns raised in the literature. We pinpoint the need for more “macro-level” research on GenAI and LLMs as external enablers for entrepreneurship and research on effective regulatory frameworks that facilitate business experimentation, innovation and further technology development.

This dissertation explores the relationship between digital technologies and firm performance. It draws on recent research in the fields of innovation and digitalisation and studies the relationship between software development and firms' capabilities to innovate, internationalise, and develop growth aspirations. The main aim is to go beyond the indicators of digital technology use and instead study the development of software and the intentions behind developing it. The thesis studies the link between software development and firm characteristics. The dissertation consists of four distinct yet interrelated papers, each addressing the different aspects of this relationship. 

Paper I provides an insight into the role of software in digital transformation, comparing it to Research and Development (R&D) investments and highlighting software development as a critical component of innovation that contributes to firms’ competitive advantage in the economy. Paper II finds evidence in favour of a ‘software-biased’ shift in innovation and empirically shows the link between software development and the propensity to introduce innovations and have higher innovation sales. Paper III studies the link between growth aspirations and software development, showing that software development is essential for developing growth aspirations and aspiring for international growth. The final paper examines the determinants of internationalisation, revealing a positive relationship between software development and firms' propensity to engage in export and import activities. This finding suggests a complementarity of software development when navigating the complexities of global markets. 

The dissertation contributes to the understanding of software development’s role across firms. It highlights the strategic value of software not just as an operational tool but as an input for building competitive advantage and prospects for innovation, internationalisation, and growth aspirations.

Software is at the core of digitalisation and is often claimed to play a central role in innovation and in shaping competition across industries and firms. There are yet few studies of the extent and nature of software development across firms. We employ a unique firm-level survey comprising 3,929 firms across Sweden to analyse the distribution and characteristics of firms that invest in software development and the orientation of their investments. The results confirm that software development activities are present in most industries, but heterogeneously distributed across firms. Internal software development is associated with innovation-oriented large firms in high-tech and knowledge-intensive industries, and is often affiliated with MNEs. The results suggest that software development is comparable to R&D investments and constitutes an example of digital innovation. This strengthens the value of studying software development activities to understand how firms invest in and build competitive advantage in the digitalised economy. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

In this paper, we propose a novel method for high-growth firm prediction by minimizing a cost function using a Genetic Algorithm (GA). To achieve it, the GA is used to search to find a set of important variables which provide the best fit for machine learning models so that accurate predictions can be made for high-growth firm prediction. The GA is employed to optimize the mean square error (MSE) between the accurate results and the predicted results of the machine learning methods by evolving the initially generated binary solutions through iterations. The proposed method obtains the best fitting set of variables for the machine learning methods for high-growth firm prediction. Four different machine learning methods which are Support Vector Machines (SVM), Logistic Regression, Random Forest (RF) and K-Nearest Neighbor (K-NN) have been employed with the GA and experimental results show that using RF with the GA achieves the best accuracy results with 94.93%. © 2022 IEEE.

A number of scholars and industry professionals have claimed that there has been a ‘software-biased shift’ in the nature and direction of innovation, in that software development is a core part of innovation activities in firms across a wide array of industries. Empirical firm-level evidence of such a shift is still scant. In this paper, we employ new and unique firm-level survey data on the frequency and nature of software development among firms in Sweden, matched with the Community Innovation Survey (CIS). We find robust evidence supporting a software bias in innovation, in that software development is associated with a higher likelihood of introducing innovations, as well as higher innovation sales among firms in both manufacturing and service industries. Furthermore, this positive relationship is stronger for firms that employ in-house software developers than for those that only use external developers, suggesting that there is a hierarchy but possibly also a complementarity between in-house and external software development. We also find support for complementarity between software-based technology and human capital; the estimated marginal effect of software development on innovation is particularly strong for firms that combine in-house software development with a highly educated workforce in both STEM and other disciplines. © 2021