Research and analysis

Exploring behavioural barriers to investment in DCMS sectors

Published 10 July 2025

Report authors:

• Nida Broughton
• Bálint Dercsényi
• Eva Kolker
• Cindia Li
• Akila Ranganathan
• Rosario Ramos
• Hubert Wu

Executive summary

The UK Department for Culture, Media and Sport (DCMS) commissioned BIT (the Behavioural Insights Team) to explore behavioural barriers to investment that businesses in DCMS sectors face. The project aimed to contribute to the evidence base supporting the UK government’s mission for kickstarting economic growth. The project included a desk research and data analysis phase followed by a qualitative research phase.

Our desk research and survey analysis found that the existing evidence base on investment barriers relevant to businesses in DCMS sectors was very limited in quantity, and where it existed, also varied in quality. For example, we found that existing surveys generally lacked specific evidence about DCMS sectors. Where non-survey evidence on investment barriers in DCMS sectors existed, evidence was often focused on the creative industries. And, importantly for this project, behavioural barriers were often overlooked. Given the paucity of existing evidence, we created a bespoke investment barrier framework and asset classification list by combining insights from both the investment and behavioural science literature to guide our subsequent research (see Figure 2).

In our qualitative research, we explored business leaders’ understanding of investment, as well as their perceptions of the barriers to investment, guided by the classifications in Figure 2. We mapped our findings on the barriers to investment along a conceptual ‘investment journey’, divided into five steps, starting from the intention to invest through to implementing an investment decision. An overview of our findings can be found in Table 2. We found that DCMS business leaders faced behavioural barriers along each step of the investment journey. Some of these barriers were shared across businesses regardless of business size and sector, such as lack of time and headspace (known as ‘cognitive capacity’) to seek out and plan investments. For others, we found variations in the barriers faced depending on business size: for example, we found that micro and small businesses tended not do quantitative evaluations and forecasting to evaluate investment options, while for medium sized businesses, the barrier was not that they did not do these activities, but rather than they found them difficult to perform.

We also found differences in how barriers presented across for-profit and not-for-profit businesses. For example, while both for-profit businesses and not-for-profit businesses lacked an awareness of or were suspicious of diversifying their funding sources, this manifested differently across businesses of different types. For-profit micro businesses tended to favour personal savings or recent profits for financing, while not-for-profit businesses tended to focus on government grants and fundraising. Given that not-for-profit businesses make up the majority not only of civil society organisations, but likely also a significant share of organisations in the cultural, sport, and tourism sectors, understanding how behavioural barriers differ across for profit and not-for-profit organisations will be an important consideration for DCMS.

While our desk research and survey analysis found the existing evidence base about investment barriers relevant to businesses in DCMS sectors was limited and our qualitative research was not designed to produce generalisable findings, we think our findings confirm that behavioural barriers are relevant and impactful. Overall, this research contributes to the emerging evidence base that behavioural barriers may significantly impact the effectiveness of policies and programmes aimed at boosting investment. Overcoming these barriers likely requires a better understanding and segmentation of businesses based on characteristics such as size and profit orientation.

To that end, we have produced two sets of recommendations:

Our recommendations for future research focus:

• 1. Obtain data access to existing high-quality investment barriers research that allows analysis of businesses in DCMS sectors – request access to survey data from existing surveys that appear to have collected data at the sectoral level (e.g. 2023 Finance and Investment Decisions Survey) to enable DCMS-specific analysis.
• 2. Incorporate conceptual frameworks for individual-level behavioural barriers and asset subcategories into future DCMS research related to investment – use the taxonomy of behavioural investment barriers, asset classification list, and conceptual investment journey developed as part of this project to enhance future research design.

Our recommended policy directions, rather than being prescriptive, outline how policy may be improved if behavioural barriers prove widespread among UK businesses more generally and can serve as informed hypotheses for future research to explore:

• 3. Ensure communications do not assume growth and profit are primary motivators and use messengers trusted by the target population – appeal to motivations such as work-life balance for micro businesses or providing better services for beneficiaries for charities, while using trusted messengers to enhance credibility.
• 4. Make existing programmes and services more visible, easier to access, and less ‘shrouded’ – increase visibility and accessibility of existing support programmes by reducing administrative burdens and helping businesses identify quality providers in their sectors through ‘deshrouding’.
• 5. Promote investment for charities by sharing good practice – work with the Charity Commission to develop guidance and case studies demonstrating how investments can support charitable purposes.
• 6. Improve quantitative skills for evaluating investment options – address the capability gap in micro enterprises through educational programmes focused on building skills for quantitative evaluation and forecasting of investment outcomes.
• 7. Contribute to initiatives aiming to understand what works to improve management practices – ensure broader government initiatives that aim to improve management practices look to address behavioural barriers including inertia, status quo bias and present bias.

1. Introduction

The UK Department for Culture, Media, and Sport (DCMS) commissioned BIT (the Behavioural Insights Team) to explore behavioural barriers to investment within DCMS sectors. The project was designed to contribute to the evidence base supporting the UK government’s mission for Kickstarting Economic Growth. The Growth Mission has identified that low levels of private and public investment have led to low productivity and low growth in the UK (Prime Minister’s Office, 10 Downing Street, n.d.). For example, The Productivity Institute notes that “low investment is the proximate cause of low productivity and the UK’s weak growth performance” (Coyle et al., 2023). Increasing investment is thus a critical channel by which UK productivity may be improved through policy. The UK government Growth Mission’s overall goal is therefore to promote economic growth by increasing investment to promote productivity and drive up prosperity and living standards across the UK.

Businesses within DCMS sectors represent a wide variety of different types of businesses, stretching across the creative industries, cultural sectors, gambling, sports, tourism and civil society. These sectors determine vital areas of UK society, the country’s way of life, and its reputation abroad. Reflecting this is these industries’ economic significance: DCMS sectors contributed an estimated 9.3% of the UK economy in 2023 (DCMS 2025), and the Creative Industries have been identified as one of eight growth-driving sectors in the UK government’s Industrial Strategy (DBT, 2024). While historically these sectors had outpaced the broader UK economy in growth, they experienced a 9.0% decline from 2019 to 2023, compared to a 2.6% increase for the UK economy as a whole during the same period (DCMS, 2025).^{[footnote 1]} In addition, for many DCMS sectors, productivity (e.g. as measured by output per hour or role) is lower than the UK average (DCMS and DSIT, 2024). The significant contribution of DCMS sectors to the UK economy, coupled with recent downwards trends in growth and productivity, highlight the importance of understanding specific strategies to kickstart growth and productivity in these sectors and the benefits this will have to the UK more broadly. Encouraging DCMS businesses to invest in assets that will increase their productivity is one such strategy.

An important step in increasing investment is to identify and alleviate the barriers to it: for example, the government’s recent Industry Strategy Green Paper (‘Invest 2035’) highlights the importance of identifying such barriers and using policy to alleviate it (DBT, 2024). In recent years, many barriers to investment have been identified at a country level without regard to specific sectors. These barriers include factors like uncertainty (Coyle and Muhtar, 2023); access to finance (Bora et al., 2024), and the infrastructure and energy costs (Coyle et al., 2023).

While important to identify, economy-wide investment barriers can be of limited use to policy for two reasons. First, the prevalence and importance of these barriers may differ across sectors and firm types. Second, the way in which these barriers appear within sectors and affect firms may vary. A root cause of this problem is that what is meant by ‘investment’ can be very different depending on what business is being considered in question. For example, the notion of investment returns in many cultural sectors and civil society can be much broader than commercial profit.

Identifying investment barriers for DCMS sectors is therefore not only important to improving their productivity, but also requires an approach that identifies micro-level, ‘behavioural’ barriers that can capture the diversity in decisions, behaviours, and beliefs within businesses (e.g. attitudes toward growth) that affect their levels of investment. Examining the specific barriers facing the types of businesses within DCMS sectors – which range from gambling operators, historic sites, gyms, newspapers, bed and breakfasts, to charities – can help to uncover specific sectoral challenges that may not otherwise surface in economy-wide research.

What do we mean by behavioural barriers to investment

A behavioural barrier to investment refers to individual or group-level obstacles that stem from psychological, cognitive, and attitudinal factors affecting decision-making processes. These barriers often operate at the micro-level, reflecting the diversity in decisions, behaviours, beliefs and perceptions within businesses, such as specific attitudes toward growth. The concept extends beyond observable actions to include underlying psychological elements that influence investment decisions. Importantly, these behavioural factors can also manifest at the macroeconomic level, as seen in phenomena like ‘animal spirits’ that affect market confidence and investment patterns.

As well as capturing specific actions of firms and people with them, our definition of ‘behavioural’ investment barriers goes beyond these to also include psychological, cognitive and attitudinal factors that may also apply at the macroeconomic level (e.g. ‘animal spirits’). Evidence about such behavioural barriers may not only shed light on the macroeconomic investment barriers that may apply to all sectors, but may also identify new factors deterring investment that do not fit cleanly into existing work or may be specific to DCMS sectors. This in turn helps inform sector-specific solutions and policy to be developed.

2. Methods

The project included two distinct research phases:

• a desk research and data analysis phase, which focused on reviewing existing research on barriers to business investment overall (i.e. not specific to DCMS sectors) and summarising this into a framework of barriers to business investment
• a qualitative research phase, which involved semi-structured interviews with businesses in DCMS sectors

The desk research consolidated DCMS and BIT’s existing research on business investment behaviour and also reviewed research from other sources. The data analysis explored relevant survey data to identify trends in behavioural barriers both across the economy as a whole and in DCMS sectors in particular. This phase also produced a bespoke framework of barriers to business investment which we used to inform the design of our qualitative research materials for the semi-structured interviews.

The qualitative research phase consisted of semi-structured interviews with a total of 18 micro, small, and medium-sized businesses across DCMS sectors. These interviews, and the analysis of insights from them contained in this report comprise the core of the project and its contribution to the evidence base about investment barriers.

Research aims and questions

Overall, the project aimed to address the following research questions:

Question 1. What are the behavioural barriers faced by DCMS businesses when deciding to invest?

• a. how do these vary by factors such as size, sector, and region?
• b. how do these compare to the UK more broadly?

Question 2. Which behavioural barriers are most prominent for DCMS businesses when investing?

• a. how do these vary by factors such as size, sector, and region?

Question 3. How might DCMS support businesses in overcoming these barriers?

2.2 Research methods

2.2.1 Desk research and data analysis methods

The project began with a review of surveys, reports, and relevant national statistical datasets. This desk research was aimed at supporting the subsequent qualitative research by deepening our understanding of the existing evidence about barriers to investment and sector-based insights relevant to DCMS. Further information about our methods in this part of the project can be found in Appendix A.

2.2.2 Qualitative research methods

The method used for the qualitative research phase was semi-structured interviews with businesses in DCMS sectors. Semi-structured interviews are guided conversations that follow a flexible set of pre-determined questions while allowing for follow-up questions and deviations to explore themes that may emerge in the interview itself in more depth. The use of semi-structured interviews enabled a deep and nuanced exploration of decision-making on investment, and our purposive sampling approach allowed us to speak to participants based on characteristics that we expected to influence views, behaviours and experiences with the topic.

2.2.2.1 Sample design and recruitment

This study employed a purposive sampling approach. BIT partnered with a trusted agency to recruit leaders of businesses and charities operating in sectors relevant to DCMS, aiming for diversity in size and location. A total of 18 organisations were recruited and interviewed, including 15 organisations from 5 DCMS sectors and 3 businesses operating in adjacent industries, for example, consulting firms specialising in one of the DCMS sectors. These businesses were categorised as ‘Other’ in the list below. An additional recruited participant has been excluded as they had no experience in making investment decisions.

The full breakdown per sector is the following:

• creative industries (3 businesses)
• tourism (3 businesses)
• civil society (3 charities)
• cultural (3 businesses)
• sport and gambling (3 businesses)
• other (3 businesses)

See Appendix B for an overview of the Standard Industrial Classification (SIC) codes used in recruitment screening to identify businesses from relevant sectors.

The sample comprised micro (1 to 10 employees and revenue of <£1.5m) (n=11), small (11-50 emp. and rev. of <£10m) (n=5), and medium-sized (50-249 emp. and rev. of <£40m) (n=2) enterprises.

Large organisations (with more 250+ employees and revenue of >£40m) were intentionally excluded, as the study aimed to focus on the unique barriers to investments SMEs face, which make up the vast majority of UK businesses. Participants were selected from across the UK, with the majority based in London or the East/Southeast of England (n=15). Six of the 18 participants interviewed were women (see the Limitations section for more details on how the characteristics of the sample might have impacted the insights generated).

Throughout this report, we sometimes refer to research participants as ‘businesses’ or ‘business leaders’, which, for the purposes of this report, include civil society organisations and their leaders as well. When a finding is only relevant to a certain sector, for example, only civil society, we highlight this explicitly.

2.2.2.2 Data collection

The interviews were conducted by video call in January and February 2025 and lasted around 45 minutes. The interviews explored investing within the participant’s business, barriers to investment at the individual, organisational, and macro levels, and reflections on ways to make investment easier.

2.2.2.3 Analysis

Interview recordings were transcribed and analysed using the Framework approach, which allows for themes to be identified in a transparent and structured way. This involved creating an analytical framework containing key information on participants’ businesses (industry, employee count, revenue, and region) and key topics of interest guided by the topic guide and research questions. The interview data was then summarised in the appropriate cells. Thematic analysis was undertaken to identify the range of concepts and themes from across the sample, and how these vary across business size, region, and industry.

2.2.3 Ethics and quality assurance

The project was assessed as having low ethical risk per BIT’s internal ethics assessment, and therefore did not receive an enhanced ethical review.^{[footnote 2]}

Information on the research background, data handling, and safeguarding was provided to participants prior to the interviews, with written consent obtained in advance. Verbal consent was reaffirmed at the beginning of each interview.

Key materials used throughout the research, including the interview topic guide and analysis framework, as well as this report, underwent internal review and were subject to BIT’s quality assurance processes, the latter of which involves independent review by senior policy and research staff and which is based on the peer-review process used by academic journals.

2.3 Limitations

A number of limitations should be considered when interpreting the findings from this project. First, the desk research and survey analysis were a rapid review of the evidence to inform the framework for the qualitative research and reporting. They were not designed with the scope or depth of a standalone literature review about the barriers to business investment. Second, as the project’s core comprised a small-scale qualitative study, its findings are subject to the limitations inherent in this method.

First, the insights from the interviews should not be extrapolated to represent the shared views or experiences of other businesses in DCMS sectors. While such regularities may exist, qualitative research methods such as those used in this project are not designed to test or establish generalisability. Rather, the aim of the qualitative research was to uncover the range and diversity of views and experiences from DCMS businesses with different characteristics. Related to this, the majority of interviewees were based in London, the Southeast, and East of England, which may limit the relevance of findings to other regions.

Second, despite our sampling design, the organisations agreeing to participate in interviews may have distinct characteristics or motivations that differ systematically from those who declined or were not reached. This selection bias has potentially influenced our findings.

Last, the interviews captured respondents’ perspectives at a single point in time, which may change and evolve in the future.

Readers should therefore treat our findings as standalone insights and points of exploration, with broader generalisability best assessed through additional research designed explicitly for that purpose.

3. Findings: desk research and data analysis

Our desk research and survey analysis found that the existing evidence base about investment barriers relevant to businesses in DCMS sectors was very limited in quantity, and where it existed, also varied in quality. We specifically found that:

1. Existing surveys generally lacked specific evidence about DCMS sectors (though we note that for some surveys, such as the Bank of England the Department for Business and Trade’s Finance and Investment Decision Survey, access to the response data would allow some comparisons in this regard). Surveys we analysed usually provided results broken down by business size, and when sectoral information was included, it was often restricted to categories such as the simplified (and highly-aggregated) ISIC categories of Agriculture, Manufacturing, Construction, Retail, Hospitality, Transportation, Property/Business Services, Healthcare, and Communications.
2. We also found that, where it existed, non-survey DCMS sector-specific evidence was often focused on the creative industries. This focus seems partly driven by the Creative Industries Policy and Evidence Centre (PEC), which single-handedly generated a large volume of research related to funding within the creative sector – we did not locate analogous investment-related evidence in other DCMS sectors.
3. Finally, individual-level or behavioural barriers related to psychology and individual decisions were often overlooked in evidence outside of behavioural science, while work about business investment barriers in behavioural science often did not feature macroeconomic and organisational barriers. A striking example of this can be seen between the Finance and Investment Decision Survey, which was one of the most recent and high-quality sources of evidence about investment barriers we reviewed, and the COM-B model of behavioural change, which is a workhorse model in behavioural science across a variety of policy areas. As shown in Figure 1 below, the relevant question listing investment barriers in the former survey contains just two factors that can be considered ‘behavioural’, while COM-B is silent about barriers related to intra-, inter-organisational and macroeconomic factors affecting investment

Figure 1. Barriers in the 2023 Finance and Investment Decision Survey and the COM-B model of behaviour change

If your business invested ‘too little’ over the past three years, what were the obstacles to investing/reasons for not having invested more?

• expected returns on the investment project below target rate or time period to obtain returns too long
• higher returns available or easier to buy an existing business
• higher returns or easier to invest abroad
• inability to self-fund from cash reserves
• investment takes a long time
• lack of skilled personnel
• lack of transport infrastructure
• market conditions
• needing government support
• owner(s) preferred to invest their money in other assets outside the business
• owner(s) were reluctant to take on risk
• regulatory burden
• restrictive planning regime
• tax and business rates
• too much pressure for short-term returns
• unable to access debt finance on reasonable terms
• unable to access outside equity investment on reasonable terms
• uncertainty about the economic environment
• weak demand

Table 1: A summary of the barriers in the COM-B model of behaviour change

Capability barriers	Opportunity barriers	Motivational barriers
Do I have the physical ability to do it?	Are there opportunities in the environment to do it and does the environment make it difficult or impossible?	Do I believe I can do it?
Am I aware of the options available to me?	Does the environment encourage or discourage it?	Will it lead to a positive or negative outcome, is this outcome likely to happen and will it have a significant impact?
Do I understand it and do I know how to do it?	Do I have the resources and the time to do it?	Have I got a clear goal or target and is the goal a priority for me?
Do I have the interpersonal skills to do it?	Is it the norm in my social group to do it, will I be perceived negatively if I do it and how do my peers influence my behaviour?	Is the behaviour in line with how I see myself?
Will I remember to do it?	What role models in my environment will encourage me to do it?	How do I feel when I do it and how do I feel about doing it?
Will it capture and hold my attention or will I get bored halfway through?		Is the behaviour a habit?
Will I be able to evaluate the different options and make the right decision?		Who will hold me accountable?
		Do I do it without realising and is it an automatic response that happens outside of my conscious awareness?

1. Investment barriers were often categorised inconsistently across sources with few broader organising principles. We found that each survey provided different lists of barriers to respondents, which limits the ability to compare results across surveys and makes it difficult to judge the relative importance of factors within a given survey. This reflected the more general fact that barriers to investment were often interrogated in the narrower context of issues relating to access to finance, or in the broader context of running a business in general and all the operational activities that entails.

2. Investment was often poorly defined, with little distinction between asset classes. Evidence we reviewed tended to focus on narrower and bespoke examples of investment with asset classifications that did not usually match standard classifications such as those found in the national accounts. Despite these differences in classification though, we found evidence that the kind of assets invested in by businesses varied across business sectors.

These findings are discussed in more detail in Appendix A.

In our view, the paucity of existing evidence reinforces the value of the research conducted in this project and strengthens the motivation for it. However, the lack of relevant insights gathered throughout the desk research phase also presented a challenge in that there were few best practice pieces of research that we could use to assist our design of the qualitative research.

Our response to this was to address these evidence gaps by creating our own classification of investment barriers and asset classes that were specific to this project and which standardised the classifications found in existing evidence. The bespoke investment barriers framework is shown below in Figure 2. Both the investment barriers framework and asset classification list are discussed in further detail in Appendix A.

Figure 2: the bespoke investment barriers framework and asset classification list

Psychological/behavioural (individual level)

• Preferences that may affect the investment decision, such as:
  • objectives other than profit maximisation, e.g. market share or employment
  • attitudes toward time and risk, e.g. short termism, risk aversion
  • ambiguity aversion
• Knowledge and information gaps, such as regarding:
  • potential investment opportunities
  • the benefits and costs associated with these
  • finance and support
• Misperceptions about the benefits and costs of investment, such as those caused by measurement difficulties (among other potential reasons) in areas such as:
  • valuing intangible benefits, e.g. brand
  • underestimating depreciation due to costs not being salient
• Other behavioural biases affecting the investment decision, such as:
  • aversion to debt vs. equity or internal vs. external finance sources
  • peer effects (e.g. do what other managers do)
  • cognitive overload (running the business instead of working on it)
  • status quo bias in role

Organisational/structural (firm level)

• Resource constraints, such as:
  • insufficient cash/internal funds for investment
  • lack of access to external finance
  • poor credit history
  • a lack of relevant skills, e.g. financial modelling (also includes factors affecting this such as leadership turnover)
• Operational and process barriers, such as:
  • lack of internal processes to identify and assess investments
  • high switching costs and technological lock-in (e.g. reliance on an outdated IT system)
  • information diffusion issues between teams, e.g. between those responsible for investment decisions and colleagues (including those resulting from biases in group decision-making)
  • contrasting goals within teams
  • cultural norms and firm-level policy and process inertia

Macro/systemic (industry and economy-level)

• Macroeconomic barriers, such as:
  • high interest rates; supply of external capital
  • customer demand levels and uncertainty (including those caused by confidence and ‘animal spirits’-type effects)
  • supply chain disruptions
  • shortage of relevant skills in the labour market (e.g. investment analysts
  • cost of available technology affecting the investment decision
• Policy and regulatory barriers, such as:
  • tax/subsidy structures and rates (including eligibility)
  • political uncertainty

Asset clarification list

Tangible assets

• land
• buildings
• machinery, equipment, and vehicles
• transport infrastructure

Intangible assets

• R&D
• software and databases
• design and branding
• staff training
• organisational capital (e.g. process and management practices)
• entertainment, literary and artistic originals

Creating these frameworks was a critical input in informing the structure of our qualitative research and drew upon our knowledge of evidence gaps uncovered in the desk research and survey analysis: to our knowledge, both are new to the evidence base about investment barriers, with the barriers taxonomy being the only barriers classification scheme that includes factors at a macroeconomic, inter-firm, intra-firm, the intra-individual level. As these taxonomies extend beyond psychological or behavioural barriers and are not specific to any given sector, we expect both frameworks will add value to continued government work in this area (for example, through being used to collect data on behavioural barriers in future surveys of businesses in DCMS sectors).

4. Findings: qualitative research

This section presents our findings from our qualitative research, structured along the journey of making an investment. We present findings in relation to each of the following five steps of making an investment:

While a real investment journey might be much more complex than the steps we present, this simplified approach helps lay out barriers in a clear manner. See Table 2 for a conceptual map of the investment journey and associated key barriers for each step. Table 1 summarises how the barriers vary across business size and sector. In contrast to business size and sector, regional differences were largely absent across those we interviewed.^{[footnote 3]} We focus on individual-level barriers, such as barriers related to beliefs, attitudes, knowledge, and skills, following our research questions and the paucity of evidence in this area (as identified in our preliminary desk research). However, we also include evidence related to organisational and macro-level barriers against each step of the investment journey.

Table 2: Investment journey from the intention to invest to implementing an investment decision

1. Intention to invest – perception of investment and investment goals	2. Identification of investment opportunities	3. Evaluating investment options	4. Making the investment decision	5. Implementation
Barriers: limited understanding of investment and its value; preference for maintaining the status quo; reactive (as opposed to proactive) mindset towards investment.	Barriers: lack of knowledge on how and/or what to invest in; lack of time and cognitive capacity from daily operations to seek out and plan investments.	Barriers: lack of formal evaluations of investment options; difficulty conducting evaluations even when it is a core part of business procedures.	Barriers: risk aversion; overconfidence; perceived economic uncertainty; financial challenges; internal organisational dynamics, processes and competing prioirites.	Barriers: insufficient digital/technical skills to make use of technological investments; administrative burden and bureaucracy.

Table 3: Variations in barriers to investment by size and sector

Step 1: Intention to invest

Barriers	Differences across sizes	Differences across sectors (including for-profit vs. not-for-profit organisations)
Limited understanding of what investment involves	Most prominent among micro businesses	No differences found across sectors
Limited understanding of the value of investment	Barrier relevant to micro and small businesses only	Not-for-profit organisations viewed some types of investments as being at odds with fulfilling charitable purposes
Preferences for maintaining status quo	Most evident in sole traders and family businesses who were satisfied with current size and preferred to maintain established working methods	We conjecture that businesses in DCMS sectors may be more likely to prioritise personal fulfilment over profit compared to other sectors of economy. This is because some leaders we interviewed viewed their business as a passion project related to personal interests, which may be less frequent in other sectors.
Reactive (as opposed to proactive) mindset towards investment	No differences found across sizes	No differences found across sectors

Step 2: Identification of investment opportunities

Barriers	Differences across sizes	Differences across sectors (including for-profit vs. not-for-profit organisations)
Lack of knowledge on how and/or what to invest in	Micro businesses particularly lacked awareness of external funding options, relying on personal savings and profits	Civil society organisations tended to focus on a single source of funding (government grants or fundraising)
Lack of time and cognitive capacity from daily operations to seek out and plan investments	Micro businesses bogged down by daily operational responsibilities. Small to medium-sized businesses distracted by other, competing priorities	No differences found across sectors

Step 3: Evaluating investment options

Barriers	Differences across sizes	Differences across sectors (including for-profit vs. not-for-profit organisations)
Lack of/difficulty conducting formal evaluations of investment options	Micro and small businesses typically did not perform formal/quantitative evaluations. Medium-sized businesses found it challenging to conduct formal/quantitative evaluations	No differences found across sectors

Step 4: Making the investment decision

Barriers	Differences across sizes	Differences across sectors (including for-profit vs. not-for-profit organisations)
Risk aversion (including debt aversion)	Particularly high among micro businesses	No differences found across sectors
Overconfidence	No differences found across sizes	No differences found across sectors
Perceived economic uncertainty	No differences found across sizes	No differences found across sectors
Financial challenges	No differences found across sizes	For-profit businesses experienced cash flow issues due to volatility in demand. Not-for-profit organisations cited lack of long-term government grants
Internal organisational dynamics, processes, and competing priorities	More prevalent in larger organisations with formal decision-making processes	Civil society organisations were constrained by pre-determined charitable purpose in their investment activities

Step 5: Implementation

Barriers	Differences across sizes	Differences across sectors (including for-profit vs. not-for-profit organisations)
Insufficient digital/technical skills to make use of technological investments	Only evident in micro businesses	No differences found across sectors
Administrative burden and bureaucracy	Micro businesses either struggled with applying for loans from banks or found the process cumbersomeIssues with red tape were more prominent for small and medium-sized businesses	Particularly impactful for civil society organisations that need to meet regulatory requirementsParticularly impactful for those needing planning approval to build physical infrastructure

4.1 Step 1: Intention to invest – perception of investment and business goals

Participants, particularly micro businesses, had a narrow understanding of what investments might be. When asked to elaborate on what they understood by the term ‘investment’, leaders of micro businesses struggled with providing a comprehensive definition or overview. Responses were often limited to one or a few particular types of investment, such as investing revenues in securities that pay dividends. Even when subsequently provided with a shortened form of our asset classification list (Figure 2), some participants did not associate activities such as branding or software purchases with investing. This implies that some business leaders may have spent money on investment assets without viewing them as investment.

Participants also felt uncertain about the potential benefits of investing. This negative perception manifested in three ways. First, there was scepticism about the value of specific types of investments – for example, the value of investing in staff who might leave the company later. Secondly, there was scepticism about the role of investments in the success of a business compared to the day-to-day direct contributions of the business leader.

The success of my business is down to me […]. There’s no real investment that I’m aware that I can make to encourage my business.

(size: micro, sector: other, region: London, East or South-East)

Thirdly, leaders of civil society organisations did not always consider how investments could be valuable to their beneficiaries, and focused instead on their immediate costs. They shared the sentiment that most civil society organisations should concentrate on providing the best day-to-day service to those they support, leaving limited funds for investing. Therefore, they viewed certain types of investments that do not directly impact their services, such as buying office space, as being at odds with fulfilling their charitable purposes.

This narrower understanding of what investments and their potential benefits are might have prevented businesses considering the full range of available investment options and might have reduced the scope of investments made.

Business leaders exhibited status quo bias^{[footnote 4]}: a preference for maintaining their existing strategies, product ranges, and ways of working, rather than investing to grow. Sole traders and family businesses were satisfied with their current business size and the profits their business generated. They saw a trade-off between growing the business further and having a good work-life balance: participants were afraid that running a larger business would be both too complex and time-consuming. Businesses not looking to grow or make larger profits lacked an important incentive to invest in improving business practices – even if there would have been wider benefits to investing. We conjecture that this barrier might be more prominent in DCMS sectors than in the wider UK economy: participants who turned their passion for travel or culture into a business often deprioritised profit-making and growth, which might be a less common phenomenon in other sectors of the economy. Case illustration 1 provides a real-life example of why a business owner did not want to pursue growth.

Case illustration 1: The Lifestyle Entrepreneur

Jake^{[footnote 5]} has spent much of his career in management roles in South East Asia. When he returned to his city in the South West of England, he did not find a suitable role for himself, so decided to set up his own company. Relying on his knowledge about South East Asia, he started a travel agency organising luxury trips to the region.

Jake sees his current work as a passion project: he wants to keep himself busy, do something he enjoys, and be a useful member of his community.

I do it more out of passion […]. I still feel that there’s a lot that I can give. It helps to keep me mentally well.

(size: micro, sector: tourism, region: South West England)

Making a profit is not a priority, as Jake is nearing retirement and does not want to sacrifice valuable family time for short-term monetary benefits. Therefore, he does not want to grow the business any further. For example, he is conscious that he could seek external financing to set up an office, hire employees and offer trips to customers living elsewhere in the UK, but prefers not to.

Profit isn’t the primary motive. The primary motive is to build something, and it’s to give great customer satisfaction. As long as I’m covering my costs and it’s a good use of my time, then I’m very happy to do it. Also, I see it as an opportunity for me to go back to Asia, which I love going to, and picking up with people that I know there.[…] It’s more about giving people a chance to experience Asia in the way that I share what I’ve loved about it

(size: micro, sector: tourism, region: South West England)

Reluctance to change was a barrier to investment even when businesses were open to growth. Those who established businesses related to personal interests did not want to sell products or services they were not familiar with. This led to a conscious avoidance of certain investment opportunities, for example, those related to an expansion of their product range. Similarly, sole traders often had well-established working methods, for example, trading on a single e-commerce platform or drawing architectural plans by hand. While they were conscious of potential ways to improve these practices and thereby boost revenues, their aversion to change prevented them from doing so. Lastly, businesses also recognised that changing how their business operated was needed, but saw this as a daunting task that they kept delaying.

One day, [the business will be well-organised], but it’s so far away from it that it’s – I don’t even approach it. I just carry on digging the hole, really.

(size: micro, sector: cultural, region: London, East or South East)

However, there were also factors beyond profit maximisation that motivated participants to invest in their business’ future. Participants were keen to provide high-quality products and services to their customers and thereby build a good reputation. Owners of micro businesses were also keen for their children to take over the business one day, making them motivated to leave a successful business behind. Others had a general desire to be competitive and to not fall behind competitors. These businesses tended to see investing as intrinsically valuable and as a core part of their business culture. These desires and attitudes all made participants more open to the idea of investing.

Further, businesses saw investing as a way to react to problems, rather than as a way to plan their future. This might have led businesses to stick to suboptimal practices until they faced a challenge, and then to focus on solving short-term issues rather than regularly thinking about investing for the future.

It was obvious we couldn’t carry on working like that, so we just needed [an office] that was up quickly with a good internet connection, and that’s what we did.

(size: micro, sector: sector: cultural, location: London, East or South East)

However, some were critical of this mindset and were trying to prevent their own business from falling into the same pitfall as their competitors did:

There’s obviously that old adage of: if something’s not broken, you don’t fix it or whatever. That seems to be also a bit of a mindset with lots of companies.

(size: small, sector: cultural, location: London, East or South East)^

4.2 Step 2: Identification of investment opportunities

Even when business leaders understood investing and its value, there were still challenges in finding investment opportunities due to limited knowledge or information about how and what to effectively invest in. Specifically, businesses revealed knowledge and information gaps in four domains.

Internal needs

Businesses struggled to identify the most urgent internal needs, such as gaps in staff skills, which needed to be addressed.

Experience with markets

Businesses did not know where to start when considering expansion due to a lack of relevant experience in a particular market or with providing a certain type of service. Businesses also linked this problem to a lack of high-quality, market-specific insights provided by other organisations.

Tech options

Businesses were unsure what new technologies they should invest in due to the abundance of options, such as available AI tools. Businesses highlighted that they would like more trustworthy information on what worked well for other businesses similar to theirs.

Sources of finance

Businesses did not know how to find external investors, or had a lack of awareness of alternative sources of finance. This may have impeded their ability to plan large-scale investments. For example, micro businesses tended to use personal savings and recent profits to finance investments, and never sought external funding. Civil society organisations also focused on a single source of funding – in some cases, government grants, in others, fundraising. In Step 4, we describe how this lack of knowledge about alternative funding sources led to cash flow problems.

Businesses mitigated these barriers to some extent, using a range of approaches:

Internal culture

Businesses highlighted that their organisations had an open culture that promoted the voicing of ideas and opinions. This may have helped businesses identify investment opportunities via their employees.

Competition

Businesses felt like market competition encouraged them to stay open to new ideas and opportunities to invest in, and to look to others for inspiration.

We would have our antennae up’ is the way I talk to the staff about it. Make sure we are aware of what people are doing, what they’re not doing. Where is the opportunity? Be a first-mover somewhere.

(size: small, sector: civil society, region: London, East or South-East)

External advice

Businesses sought out advice from people with relevant experience. This included family members with an entrepreneurial background, leaders of similar businesses, as well as specialists, such as accountants or employees with technical expertise.

However, some were sceptical about seeking external advice, thinking that they knew best about what was good for their business. This scepticism was either based on previous negative experiences with business support services or a general notion that others do not have enough insight into their business. This suggests that overconfidence might have played a role in preventing these businesses from making use of available insights and potential partnerships.^{[footnote 6]}

Focus on the day-to-day operational requirements limited the time and cognitive capacity available to seek out and plan investments. For instance, senior employees of small to medium sized companies said they were often distracted by competing priorities:

^My role is supposed to be more strategic, more high-level, and taking a view of things. At the moment, I’m always putting out fires and just sort of go round.

(size: medium, sector: tourism, region: London, East or South East)

Similarly, those running micro businesses complained about being bogged down by daily operational responsibilities for extended periods or struggling to build in time for investment activities due to the unpredictability of workload. This meant that investment decisions were postponed or made on an ad-hoc basis.

A focus on day-to-day operations might also indicate short termism, where too much weight is placed on securing short-term benefits, impeding long-term growth. For example, a participant who successfully identified an investment opportunity spent a long time trying to convince other leaders in the business to commit to it. The decision to invest was only made when directors were convinced that the costs would be covered by increased revenues within 2-3 years, indicating that longer-term benefits were seen as less important.

4.3 Step 3: Evaluating investment options

Businesses across size and industry struggled with evaluating potential investment opportunities.

Micro and small businesses did not do quantitative evaluations and forecasting that would have helped them evaluate investment options. In some cases, businesses did not mention any formal evaluations when describing their decision-making process. This suggests that they either did not do such evaluations or did not see them as an important part of their decision-making process. In one case, a participant said that they had the skills to do formal evaluations, but the organisation’s CEO discouraged spending time on it. Others were explicit about their lack of quantitative skills or experience with formal evaluations.

If there’s […] an investment that we need to make, I will research it as much as I possibly can – perhaps discuss it with my accountant, as well. I’m not a figures guy.

(size: micro, sector: creative industries, region: North West England)

These difficulties evaluating their options prevented participants from making investments. For example, a participant considered investing in marketing activities on Facebook, but did not know whether these advertisements would translate into sales, holding them back from making the investment. In other cases, however, businesses had the confidence to make decisions based on instincts, rather than formal evaluation, as outlined in Step 4 below.

Medium-sized businesses saw forecasting and doing quantitative evaluations as a core part of running their business. However, they also highlighted how difficult this can be, for example due to frequent changes in the variables involved in modelling.

People can change their minds, defer things, cancel things, and suddenly, you’re trying to put together a cash flow forecast and a forecast for your business based on X number of events in this month. It’s really difficult.

(size: medium, sector: tourism, region: London, East or South East)

4.4 Step 4: Making the investment decision

Internal organisational dynamics, processes, and priorities slowed down decision-making. Apart from sole traders and family businesses, participants reported internal disagreements with regards to what and how much to invest, which slowed down decision-making. For instance, while some team members saw investments in staff training as an essential part of keeping the business functioning well and contributing to its long-term financial performance, others were not convinced of its necessity. Sub-teams or departments focused on their own needs and the benefits an investment could bring them within their own silo, leading to slower decision-making.

[Some conversations go] on and on and you go round and round in circles that actually an investment decision that could have been made way easier has become a bigger thing.

(size: small, sector: tourism, region: London, East or South East)

Furthermore, larger organisations also had formal approval processes for investment decisions – often involving a board – that took longer than participants wished.

In addition, those in the civil society sector explained that their investment activities were constrained by their pre-determined charitable purpose. Leaders of these organisations agreed that they always needed to think about how their investment plans impacted their beneficiaries, often coming to the conclusion that spending on short-term solutions was preferable.

Business leaders exhibited a range of confidence levels in making investment decisions, particularly in terms of taking on risk. Micro businesses exhibited high levels of risk aversion: they were worried about making the ‘wrong’ investment decision or not being able to pay for the investments they made, potentially leading to an outsized negative effect on their private life. Risk aversion might also have been linked to the perception of uncertainty detailed later in this section: thinking that the future is ambiguous or unpredictable might have exacerbated existing negative feelings about making investments that are not guaranteed to pay off. Leaders took some proactive steps to mitigate perceived risks, such as keeping a risk register.

Businesses also had concerns around taking on debt, seeing it as an unnecessary source of risk that was best avoided. As a result, they decided to invest only when they could pay for it without external financing.

In the past, I’ve used my own savings – brought them to the company. Other than that, I never really get finance. What I’ll generally do is wait until we’ve got a new client that will basically pay for something.

(size: micro, sector: creative industries, region: North West England)

Businesses also said they would be more likely to commit to an investment if it had guaranteed returns or if there was a safety net preventing negative outcomes.

[I want] something where there was a bit of a safety net so you’d have a 100 per cent guarantee that investment would work.

(size: micro, sector: sport & gambling, region: London, East or South East)

Case illustration 2 portrays a participant’s negative attitudes towards taking risks.

Case illustration 2: The Guardrail Seeker

Margaret set up her graphic design company a decade ago. She bought office equipment and software in the past, seeing them as essential to run the business. But she describes herself as extremely risk averse, making her reluctant to spend money on anything that is not essential to keep the business running or does not lead to immediate benefits.

I don’t think I’ve made many investments where I’ve not known that it’s going to pay off.

(size: micro, sector: creative industries, region: North West England)

She recently paid to get access to a professional network. Before doing so, she sought the advice of similar businesses online and was reassured that the fee was often covered within a year or two by new commissions secured through networking.

While she is open to the idea of making further investments, she would only do this if they secured a big project that would pay for it. Taking out a business loan is not something Margaret has ever considered, because she cannot be sure that future revenues would cover repayments.

In contrast, other participants exhibited more confidence – particularly in their ability to do enough research to make the right investment decision. However, it is unclear how and when these businesses decided that they had done enough research or had all the pertinent facts and information to make a decision. Such high confidence might also be at odds with our finding outlined in Step 3 that businesses did not evaluate business options formally. Participants acknowledged this, stating that ultimately, after all their research, they made decisions based on their instincts.

We just went with gut on that one, just thought it would probably work

(size: medium, sector: cultural, region: London, East or South East)

In summary, while some businesses did not invest to avoid risks, others were highly confident that their instincts could guide them well enough – even if they might have potentially led to sub-optimal investment decisions.

Financial challenges also prevented investments. For-profit businesses experienced cash flow issues, in some cases due to volatility in demand. There was some disagreement about how much the cost of living crisis contributed to this issue: for example, businesses operating in the tourism and the sports and gambling sectors mentioned that their potential customers might have reduced their spending on these forms of entertainment. However, other businesses from the same sectors disagreed, saying that demand for their products and services had been steady. Businesses also said that recent changes in National Insurance contributions and taxation had had a negative impact on their budgets allocated to investments.

That’s basically our whole surplus gone on extra National Insurance contributions.

(size: medium, sector: cultural, region: London, East or South East)

Not-for-profit organisations and businesses with social purpose projects felt like there were not enough government grants which would have allowed them to make long-term investments. For example, one participant talked about how the lack of long-term grants for social-oriented programmes had led to a cycle of stop and start with their projects.

Financing issues may have been compounded by general perceptions of uncertainty in the economy. Some businesses were worried about a potential recession in the economy or disruptions due to policy changes after the 2024 UK general elections. Perceptions of uncertainty impacted participants’ confidence in investing – possibly leading to cancelled or postponed plans, or more conservative approaches to investments in general. A feeling of uncertainty might also have led to further increases in risk aversion, as discussed earlier in Step 4.

4.5 Step 5: Implementation

Micro business leaders lacked the necessary digital or technological skills to effectively implement investments or to reap their benefits. This barrier was also relevant for businesses that were otherwise able to identify investment opportunities. For example, businesses described how they had invested in new technologies and equipment, but then failed to make use of them.

I bought what was meant to be a magnificent iMac that was about £3,000 about five years ago and it sat in a box for about six months. Then somebody set it up, but they didn’t set it up to my email address and it’s never really got going properly.

(size: micro, sector: cultural, region: London, East or South East)

In other cases, lack of digital skills meant that business leaders had to rely on external support frequently, for example, to make changes to their website. These difficulties not only reduced the benefits of past investments, but potentially discouraged future ones too.

Administrative burden and delays in government approvals forced businesses to postpone investments. Participants thought that heavy bureaucracy impacted their abilities to invest in two ways. First, they spent resources, including time and money, on filing taxes and making sure they met regulatory requirements, especially in the civil society sector. This meant that they had less time and a smaller budget left to spend on investments. Second, delays in planning approvals meant that investments in buildings had to be postponed. Case illustration 3 demonstrates how delays in planning approvals impacted a business.

Businesses open to the idea of getting a loan (see Step 4 for details on debt aversion) disliked the application process. Micro businesses struggled especially: they thought the application process was cumbersome and that proving the value of their business to banks was difficult, for example, if they had a large inventory that banks were not aware of. One business, therefore, often preferred getting informal loans, for example from family members.

With the borrowing from friends and family, you don’t have to give out any personal guarantee, often it’s just a handshake. […] That process can take a day or two or a week maximum, where with banks it could take longer and that could delay decision-making for setting up your major projects.

(size: micro, sector: creative industries, region: London, East or South East)

Case illustration 3: The Red Tape Wrestler

James is the CEO of a large tourist attraction in the South East of England. The organisation relies both on government funding and their own revenues to make investments. In the past few years, the organisation invested in preserving a historic site, but also in supplementing the visitor experience with other attractions and services.

However, James recently had a negative experience with getting a planning application approved. He had planned to build accommodation for overnight visitors – something that even the local council described as uncontroversial. Even so, there was a three-month delay in getting the approval and starting building. This meant that they could not open when the tourist season started, leading to an estimated loss of £200,000 in revenues. James expressed his frustration that even simple planning applications take much longer to get approved than expected:

I don’t need information or support from the government; I just need them to do their job. So if I put in a planning application, I expect it to go through and not get held up. But to an extent, I just need the government to get out of the way, honestly.

(size: medium, sector: cultural, region: London, East or South East)

5. Conclusions and recommendations

In this project, we set out to explore the behavioural barriers that businesses in DCMS sectors face when investing in assets that may help to improve business productivity and growth. We wanted both to understand what barriers businesses face, but also how perceptions of these barriers may vary based on sector, size, and region.

On the one hand, our desk research and analysis found that behavioural barriers to investment were under-explored in prominent surveys of and reports on businesses’ investment decisions, and that specific research on how investment decisions and barriers vary for DCMS sectors was limited. On the other hand, our qualitative research suggested that behavioural barriers likely influenced every step of investment decision-making for our interviewees – from intentions to invest to implementation. This suggests that for firms like the ones involved in our qualitative research, building a better understanding of behavioural barriers to investment and addressing them as part of growth policy and programmes may be an important addition to the UK government’s mission to Kickstart Economic Growth.

Our research found that, while some barriers were shared across businesses of varying types, some barriers emerged as affecting certain types of businesses more than others. For example, we found that micro businesses had a less clear understanding of the value of investments and more limited skills to effectively implement investments. They also tended to exhibit risk aversion and a preference for maintaining the status quo rather than being motivated to grow. Our findings suggest that incorporating an understanding of how behavioural barriers differ across businesses of different sizes will likely be an important consideration when designing policy and programmes aimed at encouraging investment. In contrast, we found no evidence for regional differences in barriers to investment.

We also found differences in how barriers presented across for-profit and not-for-profit businesses. For example, some charities perceived that financing investments was at odds with their charitable purpose, which required them to focus on providing services to their beneficiaries. Given that not-for-profit businesses make up the majority not only of civil society organisations, but also a significant share of organisations in the cultural, sport, and tourism sectors, understanding how behavioural barriers differ across for-profit and not-for-profit organisations will be an important consideration for DCMS.

This research contributes to the emerging evidence base that behavioural barriers may significantly impact investment decisions, and thereby the effectiveness of policies and programmes aimed at boosting investment. Overcoming these barriers likely requires a better understanding and segmentation of businesses based on characteristics such as size and profit orientation.

5.1 Recommendations

In this section, we discuss the potential policy implications emerging from our research and present seven recommendations based on our project’s findings.

5.1.1 The value of policy recommendations from secondary and qualitative research

The research methods used in the project consisted of desk research and survey analysis (also known as secondary research) and qualitative research. The secondary research aimed to explore existing evidence on the prevalence and prominence of barriers to investment in DCMS sectors compared to the economy as a whole. Interestingly, we found the existing evidence base about investment barriers relevant to businesses in DCMS sectors was limited in quantity, and where it existed, also varied in quality. National surveys of businesses often did not publish data that allows researchers to examine results at the sector level, and most surveys overlooked individual-level behavioural barriers when asking businesses about barriers to investment.

The second research method used in this project – a qualitative study involving semistructured interviews – was not designed to produce findings that would be generalisable to all businesses within DCMS’ sectors across the UK (see Section 2.3 (Limitations). The primary purpose of this research was exploratory, aiming to uncover the presence and nature of behavioural barriers rather than quantify their prevalence or importance relative to other factors affecting investment.

Despite these boundaries, our findings nonetheless hold significant policy value. Despite the paucity of existing evidence on behavioural barriers to investment among UK businesses and in DCMS’ sectors, our work demonstrates that behavioural barriers are not merely speculative ideas; they tangibly affect real businesses across DCMS sectors. Although we cannot claim that the findings from our interviews generalise more widely to businesses of certain sizes or sectors, by documenting these barriers’ existence, our findings confirm that these barriers are relevant and impactful enough to warrant further consideration from policymakers. Moreover, as well as being complementary, in the small number of cases where they overlap, our findings are usually consistent with the existing evidence we examined about barriers to investment facing businesses in DCMS sectors. For example, barriers identified by some of our interviewees, such as a reluctance to take on external financing, risk aversion, and uncertainty about the economic environment are factors that have also been documented in previous research.

Our recommendations are split into two sections. The first section focuses on recommendations for future research. The second section focuses on potential directions for policy. We do not present this second set of recommendations as prescriptive policy recommendations, as that would require broader quantitative validation through separate research (for example, through a representative survey of businesses in DCMS sectors across the UK). However, we nonetheless believe it is valuable to discuss the potential policy implications from the experiences of the businesses in our qualitative research. There are several reasons why doing this is worthwhile. For one, it is possible that other businesses similar to those we studied may face comparable challenges. Second, the recommendations we provide can serve as informed hypotheses for future research to explore. Finally, as found in the desk research and analysis phase of the project, applying a behavioural lens is itself innovative in the context of barriers to investment, and thus it is useful to outline how policy may be improved if behavioural barriers prove widespread among UK businesses more generally.

5.1.2 Recommendations for future research

1. Obtain data access to existing high-quality investment barriers research that allows analysis of businesses in DCMS sectors

Our desk research and survey analysis identified several recent surveys about barriers to investment – most notably the 2023 Finance and Investment Decisions Survey run by the Bank of England and the the Department for Business and Trade – with response data that, while not available in full publicly, would in principle allow for a subgroup analysis of DCMS sectors. Accessing these data in a future point in time may be a low-cost way to obtain additional quantitative insights about barriers to investment for DCMS-sector businesses in a way that was precluded in this project due to time constraints. Reaching out to other commissioners of national business investment surveys to work with or encourage them to collect and publish data that would allow for sectoral analysis could also be an opportunity to build a broader understanding of investment barriers at the sectoral level.

2. Incorporate conceptual frameworks for individual-level behavioural barriers and asset subcategories into future DCMS research related to investment

We believe that future DCMS research about investment may benefit from incorporating the taxonomy of individual-level behavioural investment barriers (Figure 2), the asset classification list (Figure 2), and the conceptual investment journey (Table 2) developed in this project. Our qualitative findings can be seen as initial positive evidence of the importance of these frameworks, which as found in the desk research were minimally represented in existing research about investment barriers. Thus, we believe that consideration of the frameworks may ultimately enhance the design, targeting, and effectiveness of future research and policy in a way that mitigates potential blind spots. Examples of how these might be used in future research are as follows:

• the taxonomy of behavioural barriers to investment (Figure 2) could be used to design survey questions to collect data on a wider range of barriers than is currently practiced or in helping policy teams and programme designers to think through policy or programme components and how they might address different barriers
• the asset classification list (Figure 2) could be used to clarify or standardise definitions of investment across survey research, as well as in communications to be clearer about what is meant by investment, as the term itself is likely to be interpreted more narrowly than intended by at least some business leaders
• the conceptual investment journey (Table 2) could be used in helping policy teams and programme designers to think through what parts of the investment journey their policy or programme is targeting, and what barriers are likely to be present at that stage which may prevent businesses from taking action

5.1.3 Recommended directions for policy

3. Ensure communications do not assume growth and profit are primary motivators and use messengers trusted by the target population

Among the businesses we interviewed, growth and profitmaking were not always key motivators for investing. Communication and advice may benefit from appealing to other motivations and values. For example, some micro businesses might see investing as a way to improve work-life balance or as an opportunity to pursue personal passions. In addition, messages should be cautious on using the term ‘investment’, as target groups’ understanding of this term might not align with policymakers’. Instead, they could test alternative wording or framings, such as referring to specific activities and assets instead of the more generic ‘investment.’

Additionally, credible messengers should be identified for targeted subgroups (see Recommendation 5 below for an example of a potential messenger). We add that previous policy research has also noted the importance of the ‘messenger’ in productivity interventions (BEIS 2019) and investing in innovation (BIT and BEIS, 2018).

4. Make existing programmes and services more visible, easier to access, and less ‘shrouded’

Several participants asked for more information about investment advice and resources to be made available despite many programmes already existing. Thus, for businesses like the ones interviewed, improving the visibility of available resources and making them easier to access – for example, through reducing administrative burdens and unnecessary red tape in the form of ‘sludge’ (Sunstein 2021) – may be worthwhile. Furthermore, this ease-of-access may also be facilitated in helping business owners in DCMS sectors discern provider quality that is usually ‘shrouded’, potentially reducing scepticism and guiding businesses toward higher-quality and sector-specific advice about the investment process (Halpern et al. 2024).

5. Promote investment for charities by sharing good practice

Findings from our qualitative research suggested that charities and civil society organisations might see investing as incompatible with their duties as charitable organisations. DCMS could actively promote approaches to investing that align with the ethos of charities, for example, impact investing, which can help provide high-quality services to beneficiaries in the long term. To achieve this, DCMS could partner with credible messengers such as the Charity Commission to develop guidance and share successful case studies related to identifying and implementing investments that support rather than contradict an organisation’s charitable purpose. These resources could also introduce charities to a wider range of financing options, as participants from civil society interviewed in our qualitative research often narrowly focused on fundraising and government grants, and did not consider alternatives such as borrowing.

6. Improve quantitative skills for evaluating investment options

Throughout our interviews, we found a gap in understanding among business leaders, particularly within micro enterprises and not-for-profit organisations, in how to quantitatively evaluate investment options and forecast investment outcomes. This limited investment literacy may constrain these businesses’ ability to pursue opportunities effectively. To address this, policy initiatives could focus on educational programmes or tailored training aimed at building skills for evaluating and forecasting investment in these sectors.

7. Contribute to initiatives aiming to understand what works to improve management practices

Business leaders in DCMS reflected that day-to-day operational priorities often took precedence over longer term strategic investment; investments were often reactive to immediate needs in the business rather than the product of proactive planning for the future. This phenomenon is not unique to DCMS sectors, and getting businesses to invest more strategically through better management practices has been a key focus of UK policy in the productivity sphere (see, for example, Business Basics and Help to Grow: Management). More research is needed to build on the findings of these programmes to address the particular challenges of inertia, status quo bias and present bias that business leaders face in taking up and implementing these approaches. One potentially promising area is to consider how management skills building could be condensed into smaller, bite-sized courses that can more easily fit around daily operations, and can help to build a habit of strategic thinking. BIT have been working with Be the Business on one such gamified intervention for small business leaders, together with The Productivity Institute (publication forthcoming).

Appendices

A. Detailed findings from desk research and survey analysis

Introduction

This document details our findings from the desk research and survey analysis, which reviewed surveys, reports, past BIT work, and other existing evidence relevant to investment barriers for businesses in DCMS sectors. We aimed to identify patterns, barriers, and classifications related to investment with a particular emphasis on DCMS sectors. These insights informed interview materials for DCMS businesses in the qualitative research phase of this project.

What we did

Approach

Our desk research involved a review of surveys, reports, and relevant national statistical datasets. We paid particular attention to content about barriers to investment, whether the evidence source enabled a sector-based analysis, how investment was defined and classified, and other questions we could adapt for the qualitative research phase of the project.

What we found

Key findings

In the evidence we examined,

1. surveys generally lacked specific evidence about DCMS sectors

2. where it existed, DCMS sector-specific evidence was often focused on the creative industries

3. within research about investment barriers, Individual-level behavioural barriers were often overlooked; these barriers most frequently appeared in the general literature about behavioural science (where they may not be business or investment-specific)

4. investment barriers were often categorised inconsistently across sources with few broader organising principles

5. investment itself was sometimes poorly defined, with little distinction between asset classes

6. the kind of assets invested in by businesses varied greatly across business sectors

Each of these findings is further detailed and discussed below.

Surveys generally lacked specific evidence about DCMS sectors

Across the surveys we reviewed, we did not find enough sector breakdowns that applied to DCMS business areas. Surveys usually provided results broken down by business size, and when sectoral information was included, it was often restricted to categories such as the simplified ISIC categories of Agriculture, Manufacturing, Construction, Retail, Hospitality, Transportation, Property/Business Services, Healthcare, and Communications (for example, see the BVA BDRC & UK Finance’s SME Finance Monitor). Other surveys featured even less detailed classifications, such as grouping sectors into Production, Construction, Distribution, Business Services, and Other Services, as seen in the SME Finance Survey by the British Business Bank, Federation of Small Businesses and Ipsos.

Where it existed, DCMS sector-specific evidence was often focused on the creative industries and took the form of reports

This focus was partly driven by the Creative Industries Policy and Evidence Centre (PEC), which single-handedly generated a large volume of research related to funding within the creative sector. These efforts included a survey conducted by the Creative Industries Council in 2017 and a more recent survey about access to finance in the creative industries carried out by the PEC in 2024. Throughout our search we did not locate analogous investment-related evidence in other DCMS sectors.

Individual-level behavioural barriers were often overlooked in areas outside of behavioural science

Lists of barriers to investment specified in the evidence we reviewed – particularly in surveys – tended to focus mostly on economic and firm-level factors including but not limited to macroeconomic objects, like interest rates, relative rates of return, skills availability, and access to finance. For example, even in the 2023 Finance and Investment Decision Survey by the Bank of England and the Department for Business and Trade, which contained perhaps the most comprehensive investment barriers list we reviewed, provided businesses that reported an underinvestment in the previous year with the following set of potential reasons for this lack of investment:

If your business invested ‘too little’ over the past three years, what were the obstacles to investing/reasons for not having invested more?

• expected returns on the investment project below target rate or time period to obtain returns too long
• higher returns available or easier to buy an existing business
• higher returns or easier to invest abroad
• inability to self-fund from cash reserves
• investment takes a long time
• lack of skilled personnel
• lack of transport infrastructure
• market conditions
• needing government support
• owner(s) preferred to invest their money in other assets outside the business
• owner(s) were reluctant to take on risk
• regulatory burden
• restrictive planning regime
• tax and business rates
• too much pressure for short-term returns
• unable to access debt finance on reasonable terms
• unable to access outside equity investment on reasonable terms
• uncertainty about the economic environment
• weak demand

All but two of these (owner(s) preferred to invest their money in other assets outside the business; owner(s) were reluctant to take on risk) relate to non-individual investment barriers. This leaves psychological and decision-making factors, such as risk aversion, cognitive biases, or lack of confidence underrepresented despite their influence on investment decisions. The evidence we reviewed did not always exclude individual factors, however. For example, according to the Enterprise Research Centre (2024) and Golubova (2024), one of the main factors shaping investment decisions is business leaders’ attitudes and perceptions regarding the perceived ease and benefits of these investments.

Interestingly, the barrier frameworks and classifications we reviewed from the field of behavioural science (none of which specifically applied solely to business investment) tended to feature a complementary problem: in these cases, the focus of barriers in these frameworks tended to skew heavily toward factors relating to an individual and their psychology. A prime example of this is the influential COM-B model developed in 2011 by Susan Michie, Lou Atkins and Robert West. This model is a workhorse framework in behavioural science that classifies barriers to behaviour change in the categories of Capability, Opportunity, and Motivation; as is clear by the name of these categories alone, firm, industry, and economy-wide barriers to investment are not easily contained within such frameworks.

Capability barriers	Opportunity barriers	Motivational barriers
Do I have the physical ability to do it?	Are there opportunities in the environment to do it and does the environment make it difficult or impossible?	Do I believe I can do it?
Am I aware of the options available to me?	Does the environment encourage or discourage it?	Will it lead to a positive or negative outcome, is this outcome likely to happen and will it have a significant impact?
Do I understand it and do I know how to do it?	Do I have the resources and the time to do it?	Have I got a clear goal or target and is the goal a priority for me?
Do I have the interpersonal skills to do it?	Is it the norm in my social group to do it, will I be perceived negatively if I do it and how do my peers influence my behaviour?	Is the behaviour in line with how I see myself?
Will I remember to do it?	What role models in my environment will encourage me to do it?	How do I feel when I do it and how do I feel about doing it?
Will it capture and hold my attention or will I get bored halfway through?		Is the behaviour a habit?
Will I be able to evaluate the different options and make the right decision?		Who will hold me accountable?
		Do I do it without realising and is it an automatic response that happens outside of my conscious awareness?

A summary of the COM-B framework often used within BIT projects (see table above).

These complementary problems were important factors in us choosing to develop our own barriers list presented in Figure 2.

Investment barriers were often categorised inconsistently across sources with few broader organising principles

We found that each survey provided different lists of barriers to respondents, which limits the ability to compare results across surveys and makes it difficult to judge the relative importance of factors within a survey (as other barriers could be missing). This reflected the more general fact that barriers to investment were often interrogated in the narrower context of issues relating to access to finance (for example as in the British Business Bank’s Small Business Finance Market Report), or in the broader context of running a business in general and all the activities that entails (for example as in the aforementioned SME Finance Monitor).

Investment types were poorly defined in both surveys, reports, and other evidence we reviewed

Consider the categories presented to respondents in the two highest-quality surveys featuring the topic which we reviewed: the 2023 SME Finance Monitor and the 2023 Finance and Investment Decision Survey (noting that the former is not even an investment-specific question).

2023 SME Finance Monitor	2023 Finance and Investment Decision Survey
Are you planning any activities traditionally associated with growth? Significantly improve aspect of business; take on more staff; invest in plant, machinery or premises; develop a new product or service; take steps to reduce carbon footprint; start to sell/sell more overseas; other major expenditure; innovation (any).	Can you tell me in which of the following areas you made your investment? Acquisition of land and buildings; acquisition of plant, machinery and vehicles; investment in new processes; IT investment; market development; new product or service development/R&D; staff training; other.

Examples of how two of the surveys we reviewed asked about investment types (note also the difference in framing: one question is forwards-looking whereas another is backwards-looking). See table above.

Neither category covers the totality of what may be considered investment in a business, let alone one in a DCMS sector. We were in particular disappointed at the lack of a link to standard asset type and investment classifications (for example, the distinction between tangible and intangible assets and investments in these). Partly as a result of this issue we decided to create a provisional asset taxonomy ourselves for use in the qualitative research phase of the project, presented in Figure 2.

Where it existed, the evidence we reviewed suggested that the composition of investment varies greatly across business sectors.

Some of the PEC reports we reviewed found that investment in the creative industries was more focused on intangible assets, e.g. “Firms are more likely to identify investment opportunities for R&D, particularly for new products, and less likely to identify potential capital investments in plant, facilities, and property” (Siepel, Rathi & Cowling, 2024). This particular report found that types of investments prioritized by businesses in the creative industries significantly influenced their ability to secure financing or persuade stakeholders to support these initiatives.

This finding appears consistent with asset-level investment statistics published by the Office for National Statistics (ONS). For example, consider the differences in the asset make-up of intangible investments between the ‘Arts, recreation and other services (RST)’ industry section to ‘Information and communication’ in 2022:

Intangible investment by industry section and asset, current prices, £ million, UK, 2022

Arts, recreation and other services (RST)

Industry sector and asset	Current price (£ million)
Artistic originals	411
Branding- own account	338
Branding- purchased	1,315
Design- own account	124
Design-purchased	340
Financial product innovation	0
Firm specific training	2,210
Mineral exploration	0
Organisational capital- own account	1,005
Organisational capital- purchased	293
R&D	687
Software- own account	1,139
Software-purchased	414

Intangible investment by industry section and asset, current prices, £ million, UK, 2022

Information and communication

Industry sector and asset	Current price (£ million)
Artistic originals	6,563
Branding- own account	753
Branding- purchased	5,062
Design- own account	548
Design-purchased	116
Financial product innovation	0
Firm specific training	2,151
Mineral exploration	0
Organisational capital- own account	1,891
Organisational capital- purchased	1,682
R&D	3,563
Software- own account	4,984
Software-purchased	3,493

Two project-specific classification schemes: investment barriers and asset hierarchies

In light of our findings in the previous section, and particularly those about the inadequacy of investment schemes and asset classes in existing work, we developed our own list of investment barriers and asset hierarchies.

Barriers to investment

Our investment barriers list is included in Figure 2 in 3. Findings: desk research and data analysis. Our aim in creating this list was to address the shortcomings in the existing evidence that largely separated individual and psychological barriers from more ‘traditional’ economic barriers at the firm or economy level. To do this, our framework segments investment barriers by whether they primarily apply at the individual, organisational, or macro (industry/economy) level and adopts two defining levels.

As with any classification scheme, there are likely to be many critiques that apply to it. For our list for example, there may be many links between some barriers in the macro/firm level and the micro/behavioural ones that may describe a common phenomenon. For example, a lack of skills within the organisation may result in misperceptions among those responsible for capital expenditure. But this is not always the case: for example, psychology is completely irrelevant to planning regimes. Nonetheless, we believe the present list provides a solid foundation for clarifying the project’s approach to defining and analysing investment barriers, particularly those at the individual/behavioural level that past evidence has so far failed to do.

Asset categories

To better define what ‘investment’ entails for a business we decided to create a table of asset hierarchies, included in Figure 2 in 3. Findings: desk research and data analysis. We prepared this list by starting from standard means of reporting investment by asset class from the UK national accounts (for capitalised assets) and the ONS (for both capitalised and un-capitalised assets, e.g. several categories of intangible investment in the latter case). We caution that our breakdown is not an exhaustive combination of these official sources and is rather a purposive framework that was used for the project’s qualitative research. However, it would not be difficult to create such a classification if one were sought.

Relatedly, the table itself is clearly not on its own fit for purpose to use in qualitative work: in many cases even these categories may be too technical for a typical interviewee (e.g. consider categories like ‘organisational capital’ and ‘artistic originals’).

B. Standard Industrial Classification (SIC) codes used in recruitment screening

The below list includes the SIC codes shared with the recruitment agency to aid in the recruitment, screening, and selection of businesses for the qualitative research.

Creative industries

• 3212: manufacture of jewellery and related articles
• 5811: book publishing
• 5812: publishing of directories and mailing lists
• 5813: publishing of newspapers
• 5814: publishing of journals and periodicals
• 5819: other publishing activities
• 5821: publishing of computer games
• 5829: other software publishing
• 5911: motion picture, video and television programme production activities
• 5912: motion picture, video and television programme post-production activities
• 5913: motion picture, video and television programme distribution activities
• 5914: motion picture projection activities
• 5920: sound recording and music publishing activities
• 6010: radio broadcasting
• 6020: television programming and broadcasting activities
• 6201: computer programming activities
• 6202: computer consultancy activities
• 7021: public relations and communication activities
• 7111: architectural activities
• 7311: advertising agencies
• 7312: media representation
• 7410: specialised design activities
• 7420: photographic activities
• 7430: translation and interpretation activities
• 8552: cultural education
• 9001: performing arts
• 9002: support activities to performing arts
• 9003: artistic creation
• 9004: operation of arts facilities
• 9101: library and archive activities
• 9102: museum activities

Cultural sector

• 1820: reproduction of recorded media
• 3212: manufacture of jewellery and related articles
• 3220: manufacture of musical instruments
• 4763: retail sale of music and video recordings in specialised stores
• 5911-5914: motion picture activities (as listed above)
• 5920: sound recording and music publishing activities
• 6010: radio broadcasting
• 6020: television programming and broadcasting activities
• 7420: photographic activities
• 8552: cultural education
• 9001-9004: arts facilities and activities (as listed above)
• 9101: library and archive activities
• 9102: museum activities
• 9103: operation of historical sites and buildings and similar visitor attractions

Gambling and sport

• 9200: gambling and betting activities
• 3012: building of pleasure and sporting boats
• 3230: manufacture of sports goods
• 4764: retail sale of sporting equipment in specialised stores
• 7721: renting and leasing of recreational and sports goods
• 8551: sports and recreation education
• 9311: operation of sports facilities
• 9312: activities of sport clubs
• 9313: fitness facilities
• 9319: other sports activities

Tourism

• 55100: hotels and similar accommodation
• 55201-55209: holiday and other short-stay accommodation
• 55300: camping grounds, recreational vehicle parks and trailer parks
• 55900: other accommodation
• 56101-56103: restaurants and mobile food service activities
• 56210: event catering activities
• 56290: other food service activities
• 56301-56302: beverage serving activities
• 49100: passenger rail transport, interurban
• 49320: taxi operation
• 49390: other passenger land transport n.e.c.
• 50100: sea and coastal passenger water transport
• 50300: inland passenger water transport
• 51101-51102: passenger air transport
• 77110: renting and leasing of cars and light motor vehicles
• 77341: renting and leasing of passenger water transport equipment
• 77351: renting and leasing of passenger air transport equipment
• 79110: travel agency activities
• 79120: tour operator activities
• 79901: activities of tourist guides
• 79909: other reservation service activities
• 82301: activities of exhibition and fair organizers
• 82302: activities of conference organizers
• 68202: letting and operating of conference and exhibition centres
• plus various cultural and recreational activities (90010-93290) as listed in previous sectors

Civil society

• N/A (not defined purely via SIC code)

References

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Bakhshi, H., Breckon, J. and Puttick, R (2021) Business R&D in the arts, humanities and social sciences. London: Creative Industries Policy and Evidence Centre and Nesta.

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Prowle, M., Lucas, M., Barnes, S., & Lowth, G. (2017). Improving productivity in UK Small-medium sized enterprises: A research study. University of Gloucestershire, Gloucestershire Business School.

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1. This downward trend was primarily driven by the tourism sector, which was particularly affected by the pandemic. ↩

2. The assessment process has been designed to meet the criteria set out by the UK government’s Social Research Unit. ↩

3. This finding could be due to limitations in our sample. It is worth noting that the findings in our desk research and survey analysis found mixed evidence on regional differences in investment barriers. For example, the 2023 Finance and Investment Decisions Survey found little evidence of regional heterogeneity not explained by the existing distribution of firm productivity across the UK. However, some other surveys – such as the 2023 SME Finance Monitor – found regional differences in growth perceptions and perceived difficulty of accessing finance. ↩

4. Status quo bias describes the tendency to prefer the current state of affairs, leading to resistance to change. For more details, see: Samuelson, W., & Zeckhauser, R. J. (1988). Status quo bias in decision-making. Journal of Risk and Uncertainty, 1(1), 7–59. ↩

5. The personal details of participants described in case illustrations have been altered to preserve anonymity. ↩

6. Note, however, that we cannot conclusively state whether a business was overconfident or not, as we do not know how their performance or productivity compared to the industry average. ↩