Digital transformation has gained great relevance in the last decade and can be conceptually defined, among other possibilities, as an important improvement in a company through the combination of computing, communication and connectivity (Vial, 2019). Small companies have been also adhering to this digital transformation seeking to develop their business models to obtain greater sales and better services to their consumers (Sudarnice et al., 2024).

The adoption of digital transformation has become more imperative with the advent of the COVID-19 pandemic. The pandemic has affected small companies hardly, and those that have managed to adapt using digital technology have outperformed their peers (Robertson et al., 2022). Digital transformation in small companies in developed countries has been accelerated by the COVID-19 pandemic (Kádárová, et al., 2023). On the other hand, in developing countries, the impact of COVID-19 has reached more the small companies, among other reasons due to structural limitations on the use of digital technology (Bai et al., 2021).

In this context, one of the most relevant strategies for companies that want to transform themselves digitally is the adoption of businesses based on digital platforms. Digital platforms have assumed an ever-growing role in the business ecosystem, and even those companies that do not develop their own platforms must identify the opportunities arising from this new economic practice (Gatautis, 2017).

Digital platforms are an innovation directly related to digital transformation, using technologies to connect people and organizations, forming a collaborative ecosystem in which significant volumes of value are added through exchanges between the parties (Parker et al., 2016). The European Commission (2016) defined a platform as an enterprise based on internet connectivity, which allows bilateral or multilateral transactions, generating value for the parties involved. Some important characteristics of platform-based models are the operation in a bilateral market, the presence of network effects, and the participation in an ecosystem (Kim, 2015).

When we evaluate this digital transformation scenario focusing on small and medium companies, a segment that represents more than 90% of the country's enterprises and accounts for approximately 30% of the gross domestic product and more than 50% of formal jobs, according to data from the Brazilian Industrial Development Agency in partnership with Getulio Vargas Foundation, we find references that indicate that the adoption of platforms and ecosystems can be an alternative for generating value for this segment (Cenamor et al., 2019).

Studies suggest that platforms offer new opportunities for small and medium companies in terms of new value propositions, new markets, and new access to resources (Jin & Hurd, 2018; Nambisan et al., 2018; Subramaniam et al., 2018). Digital platforms have shifted the focus of value creation to the network, which implies a drastic change for an organization (Li, Zheng, et al., 2017; Parker et al., 2017). Technologies such as e-commerce and social media have been widely and rapidly adopted, and the transformation resulting from these technologies goes beyond the usual internal improvements (Bai et al., 2021). The application of digital technology has made it possible to implement new processes throughout the value chain, especially in the sale and service links to consumers (Kádárová, et al., 2023).

However, many small and medium companies lack resources and capabilities, which can make it difficult to adopt a new and complex business model (Gupta & Bose, 2018; Karimi & Walter, 2016). Many entrepreneurs lack the appropriate technology expertise and, limited by their own past experience, are not easily convinced of the value of digital transformation (Santarelli & D'Altri, 2003). This cognitive inertia (Messner & Vosgerau, 2010) can be an obstacle when these entrepreneurs are forced to compete online (Li, Su et al., 2017). Therefore, the platform approach represents a paradigm that can enable entrepreneurial small and medium companies to benefit from digital platforms if adoption barriers are overcome (Cenamor, et al., 2017). This technology-driven transformation is not only desirable, but necessary for the maintenance of small businesses in the contemporary world (Sudarnice et al., 2024).

To understand the profile of small and medium companies that have adopted platform-based models in Brazil, we conducted an online survey of those responsible for 126 small businesses between March 2 and 15, 2021. In the sample, 90% of the companies have revenues below US$ 5 million per year and 92% have fewer than 100 employees.

Based on this information, we sought to find some common characteristics that may be necessary conditions for small companies looking to adopt a platform-based business model.

Small and medium companies have simple structures, and they are highly centralized in chief executive officers (CEOs). In most cases, the owner of the company and the CEO are the same person (Ghobakhloo et al., 2011). The owner is central to the company, since his decision influences all the organizational activities, both in the present and in the future (Chau, 1995; Lybaert, 1998; Fuller-Love, 2006; Smith, 2007).

The information technology adoption process in small and medium companies is also directly affected by senior management, which makes all decisions (Bruque & Moyano, 2007; Nguyen, 2009; Fuller & Lewis, 2002). These decisions are based on a combination of abilities, personal experience, judgment, and communication skills (Carson & Gilmore, 2000). Reinforcing this perspective, when discussing the entrepreneurs’ digital transformation capabilities, Li, Su et al. (2017) indicated that, in small and medium companies, digital transformations were initiated and driven by owners. The success of this transformation is the result of several factors, including management's perception and attitude towards information technology, which directly impacts the process of adopting technology-based businesses (Drew, 2003; Lybaert, 1998; Qureshi & York, 2008; Thong et al.,1993; Thong & Yap, 1995).

Buxton and Walton (2014) demonstrated that the age of small and medium companies’ owners or CEOs impacted the adoption of technology-based and e-commerce strategies, since the older generation of executives sees technology more as a threat than an opportunity.

The analysis of these studies leads to the perception that the decisions made by small and medium companies depend directly on their chief executive. Then, investigating whether older companies or older managers have greater resistance to adopting digital platforms and whether companies that have been operating for less time and managers that have been in business for less time have less resistance makes sense. The first hypothesis to be investigated here comes from this reasoning:

H1: The demographic characteristics of small and medium companies and their owners interfere directly with the development of digital platform-based businesses, with companies with a shorter period of activity and entrepreneurs with a shorter time in management having a greater propensity to develop businesses based on these platforms.

In 2021, the Brazilian Industrial Development Agency, along with Getulio Vargas Foundation, launched a survey of 2,572 small and medium companies and identified that the objective of “‘establishing new bases for competition’”, through digital transformation, obtained the lowest average of the entire survey. The practice of “participating in business platforms (marketplaces)” is not implemented to any degree by more than 80% of the companies surveyed, while more than 80% of the companies do not know how to develop forms of competition using multichannel strategies to access audiences with different profiles. In addition to identifying the low capacity of small and medium companies to transform themselves through digital means, this data leads us to understand that it may be more feasible for companies in the early stages of development to venture into platform-based businesses.

Vial (2019) pointed out that business inertia can prevent companies from successfully performing their digital transformation journey. Existing resources and skills can act as barriers to disruption and innovation through digital technologies (Islam et al., 2017; Svahn et al., 2017; Srivastava & Shainesh, 2015; Wenzel et al., 2015).

When we look at the benefits of digital platforms, we notice that they allow startups to reach a massive scale and gain value in a very short period, which can be confirmed by observing the large number of unicorns (startups valued at over US$1 billion) based on digital platforms (Acs et al., 2017). It would be expected, therefore, that many of the new businesses still in the early stage of development have been thinking of in terms of digital platforms by their executives. Thus, we arrive at the elaboration of the second hypothesis to be tested in this work.:

H2: Companies in early life cycle stage are more likely to develop businesses based on digital platforms.

Studies by Kim et al. (2018) and Madrid-Guijarro et al. (2009) indicate that the fact that small and medium companies have limited resources for their survival makes them more likely to innovations that put them in a more comfortable situation in the market. FinTechs are an example of market innovation that is accessible to small and medium companies. Schueffel (2016) defines FinTechs as companies that combine finance and technology and produce digital solutions that meet the needs of payment methods, credit and financing, and investments. By taking these characteristics into consideration, we understand they can affect the dynamics of small and medium companies’ operations (Lee & Shin, 2018).

Abassi et al. (2021), Baber (2020) and Odinet (2018) found that FinTechs increase the likelihood of small and medium companies obtaining credit at more attractive rates. In addition, the speed of obtaining credit is also greater with FinTechs (Rosavina et al., 2019; Sangwan et al., 2020). Gomber et al. (2018) and Lee e Shin (2018), pointed out FinTechs support small business owners with investment management advice at a lower cost. In short, there is a positive association between FinTechs and small and medium companies’ efficiency (Abassi et al., 2021). We have therefore our third hypothesis to be tested:

H3: Companies that team up with digital financial institutions known as FinTechs are more likely to develop digital platform-based businesses.

In Table 1 we present the relationship between the hypotheses and the tested constructs.

Table 1 Table 1 Relationship between hypotheses, constructs, and researched studies Table 1 Relationship between hypotheses, constructs, and researched studies

Table 1
Relationship between hypotheses, constructs, and researched studies
Hypothesis	Definition of constructs	Theoretical reference (in order of appearance in the text)
H1: DE (DE1, DE2) à PP (PP1, PP2)	DE: Company Demographics.	Bruque and Moyano (2007), Nguyen (2009), Ghobakhloo et al. (2011), Chau (1995), Lybaert (1998), Fuller-Love (2006), Smith (2007), Fuller and Lewis (2002), Carson and Gilmore (2000), Drew (2003), Qureshi and York (2008), Thong et al. (1993), Thong and Yap (1995), Li, Su et al. (2017), Buxton and Walton (2014).
The demographic characteristics of small and medium companies interfere directly with the development of digital platforms-based businesses. Companies with a shorter period of activity and entrepreneurs with a shorter time in management have a greater propensity to develop businesses based on these platforms.	DE1: Company operating time.
	DE2: Senior manager's working time in the company.
	PP: Platform Propensity.
	PP1: Current type of digital platform-based business model (marketplace; hidden advertising; subscription).
	PP2: Plans to adopt a platform-based business model in the future (marketplace; hidden advertising; subscription).
H2: ECV (ECV1, ECV1) à PP (PP1, PP2)	ECV: Life Cycle Stage.	Vial (2019), Islam et al. (2017), Svahn et al. (2017), Srivastava and Shainesh (2015), Wenzel et al. (2015), Acs et al. (2017).
Companies in early life cycle stages are more likely to develop digital platforms-based businesses.	ECV1: Company life cycle stage before COVID-19 pandemic.
	ECV2: Current company life cycle stage, after the peak of the COVID-19 pandemic.
H3: IF (IF1, IF2) à PP (PP1, PP2)	IF: FinTech Interaction.	Abassi et al. (2021), Schueffel (2016), Rosavina et al. (2019), Odinet (2018), Sangwan et al. (2020), Lee and shin (2018), Baber (2020), Gomber et al. (2018), Kim et. al. (2018), Madrid-Guijarro et al. (2009).
Companies that team up with digital financial institutions, known as FinTech, are more likely to develop digital platforms-based businesses.	IF1: Consider FinTech to meet the company's potential financial needs.
	IF2: Receive financial services from FinTech for the company's needs.
Note: Elaborated by the authors.

Note: Elaborated by the authors.

We used methodologies that, combined, helped to analyze whether there are direct relationships between:

the demographic characteristics of a small company and its propensity to adopt digital platform-based business models;

We collected data through an online primary survey of 126 companies between March 2 and 15, 2021. The distribution of the sample across the different sectors of the economy and by company size, defined by the number of employees, is in line with expectations. Table 2 presents the distribution of the sample surveyed by sector of activity and size.

Table 2 Table 2 Distribution of the sample surveyed by sector of activity and size Table 2 Distribution of the sample surveyed by sector of activity and size

Table 2
Distribution of the sample surveyed by sector of activity and size
Size (number of employees)	Basic, energy, and infrastructure industry	Consumer goods, retail, and healthcare	Technology, media and telecommunication	Professional and financial services	Total
10-19	4	10	12	13	39
20-49	7	20	12	19	58
50-99	0	5	5	3	13
100-149	3	1	7	3	14
150 -249	0	1	1	0	2
Total	14	37	37	38	126
Note: Elaborated by the authors.

Note: Elaborated by the authors.

For the purposes of this study, we considered three types of business based on digital platforms. These choices were based on the literature that discusses digital transformation in small companies. Bai et al. (2021) indicated that one objective of applying digital technology in small and medium companies is to increase non-traditional revenues through e-commerce and social media by marketing and advertising. Da Rocha et al. (2024) pointed out three types of platforms that small companies adhere to: sales platforms (marketplace), which facilitate transactions; interaction platforms, which facilitate promotion; and support platforms, which facilitate operations. These three types are directly associated with the types analyzed here:

Marketplace: a company that provides a website that brings together suppliers and buyers. In this model, the marketplace owner makes his profit by charging a processing fee;

We selected eight research questions that were associated with the dependent and independent variables of the model and that are related to the formulated hypotheses, as presented in Table 3.

Table 3 Table 3 Variables, research questions, and study hypotheses Table 3 Variables, research questions, and study hypotheses

Table 3
Variables, research questions, and study hypotheses
Question (construct)	Question description	Answer scale	Hypotheses
S4b (DE1: Company operating time)	How long has your business been operating?	6 – Less than three years	H1
		5 - Three years to less than six years
		4 - Six years to less than 11 years
		3 - 11 years to less than 16 years
		2 - 16 years to less than 21 years
		1 - 21 years or more
S11b (DE2: Senior manager's working time in the company)	How long have you been working for the business?	6 – Less than three years	H1
		5 - Three years to less than six years
		4 - Six years to less than 11 years
		3 - 11 years to less than 16 years
		2 - 16 years to less than 21 years
		1 - 21 years or more
Q1b (ECV1: Company life cycle stage before COVID-19 pandemic)	Which of the following options best describes the stage of your business life cycle prior to the COVID-19 outbreak in January 2020?	6 - Conception	H2
		5 - Inicialization
		4 - Growth
		3 - Maturity
		2 - Decline
		1 - Exit
Q2b (ECV2: Current company life cycle stage after the peak of COVID-19 pandemic)	Which of the following options best describes the current stage of your business life cycle?	6 - Conception	H2
		5 - Inicialization
		4 - Growth
		3 - Maturity
		2 - Decline
		1 - Exit
Q21r5 (IF1: FinTechs are considered to meet the company's potential financial needs)	If you needed to access cash for your business, which of the following sources would you consider?	1 – FinTech	H3
Q24r5 (IF2: Financial services from FinTechs for the needs of the company are received)	Which of the following options does your company receive financial services from?	1 – FinTech	H3
Q10br7r9r11 (PP1: Current type of digital platform-based business model (marketplace; hidden advertising; subscription)	Which of the following options best describes your current business model(s)?	Sum (Marketplace (1); Hidden Advertising (1); Subscription (1))	Dependent variable (DV)
Q12b r7r9r11 (PP2: Plans to adopt a platform-based business model in the future (marketplace; hidden advertising; subscription)	Which of the following options best describes the business model(s) you plan to change to in the future?	Sum (Marketplace (1); Hidden Advertising (1); Subscription (1))	Dependent variable (DV)
Note: Elaborated by the authors.

Note: Elaborated by the authors.

The descriptive results for each variable are in Table 4.

Table 4 Table 4 Descriptive Results of the Selected Variables Table 4 Descriptive Results of the Selected Variables

Table 4
Descriptive Results of the Selected Variables
Question	Average	Median	Minimum	Maximum	Standard seviation	Kurtosis Excess	Skewness	Hypothesis
S4b (How long has your company been operating?)	3.889	4	1	6	1.364	-0.187	-0.632	H1
S11b (How long have you been working for the business?)	4.302	5	1	6	1.197	0.648	-0.856	H1
Q1b (Which of the following options best describes your business lifecycle stage prior to the COVID-19 outbreak in January 2020?)	3.516	3	1	6	0.852	1.260	0.262	H2
Q2b (Which of the following options best describes your current business life cycle stage?)	3.222	3	1	6	1.007	0.610	0.719	H2
Q21r5 (If you needed to access cash for your business, which of the following sources would you consider using?)	0.214	0	0	1	0.410	-0.014	1.409	H3
Q24r5 (Which of the following options does your company receive financial services from?)	0.254	0	0	1	0.435	-0.702	1.144	H3
Q10br7r9r11 (Which of the following options best describes your current business model(s)?)	0.206	0	0	2	0.460	4.168	2.182	DV
Q12br7r9r11 (Which of the following options best describes the business model(s) you plan to change to in the future?)	0.278	0	0	3	0.544	5.322	2.158	DV
Note: Elaborated by the authors.

Note: Elaborated by the authors.

The Kruskal-Wallis’ test obtained χ2 = 810.81, with GL = 7 and p = 2.20e-16, indicating that there are significant differences between the answers collected. The Mardia’s test, for multivariate normality of the constructs, indicated that the data set of the final sample of 126 companies is non-normal, with Mardia's skewness = 492.74 (p = 1.21e-46) and Mardia's kurtosis = 8.45 (p = 0.00).

Based on the characteristics of this sample, we proceeded to the sufficiency analysis by applying Partial Least Squares Structural Equation Modeling (PLS-SEM). Some factors present in this study indicate modeling by PLS-SEM:

the study seeks to better understand the established theory about the small company’s characteristics that make it more likely to adopt digital platform-based business models, in an exploratory analysis;

The structural models were evaluated according to the methodology proposed by Hair et al. (2019). This evaluation considers the following steps, which will be used in the presentation of the results of the PLS-SEM models, ahead: (a) preliminary considerations; (b) measurement model evaluation; (c) structural model evaluation. All the analyzed models were the reflexive-reflexive type (type I), in which the measurements were all independent, but correlated, forming a hierarchical model of common factors (Becker et al., 2012).

Since the sufficiency analysis did not obtain all the statistically significant results, we complemented the study using the Necessary Condition Analysis (NCA). NCA complements, rather than replaces, traditional approaches to analyzing causal relationships. NCA provides new evidence that is not typically discovered in sufficiency analyses, particularly by the application of PLS-SEM. Before applying the NCA, it is essential that the necessary conditions identified are theoretically justified (Dul, 2016).

The approach used is based on the methodology proposed by Richter et al. (2020) for the combined use of PLS-SEM and NCA. The guidelines for combining PLS-SEM and NCA followed the steps:

to specify the research objective and theoretical basis;

NCA identifies factors that are indispensable for a result, in our case the propensity to develop platform-based businesses, according to the necessity.

The analysis of the results showed that it is not possible to obtain a significant sufficiency relationship between company demographics (H1), life cycle stage (H2), and FinTech interaction (H3) with the platform propensity variable. In addition to the sufficiency analysis, we continue with the emerging analysis of necessary conditions (Dul, 2016). The results obtained indicated that the life cycle stage before COVID-19 and the current life cycle stage are the only dependent variables for which the necessary condition is confirmed for planning the adoption of a platform-based business model (Marketplace; Hidden Advertising; Subscription) in the future. That is, for small companies to adopt platform models, they need to be in the conception or startup stages.

When we look at the distribution of answers regarding plans to adopt a platform-based model in the future at the stage of the company life cycle after the peak of the COVID-19 pandemic, we found that 50% of companies in the conception stage and 36% of companies in the startup stage intend to adopt the platform model. Regarding the economic sector of small companies, 41% of companies in the technology sector, and 29% of companies in the industrial sector intend to adopt the platform model. Table 13 presents the distribution of the percentage of companies that intend to adopt the platform model by life cycle stage after the peak of COVID-19 and by economic sector.

Table 13 Table 13 Distribution of the percentage of companies that intend to adopt the platform model by life cycle stage after the peak of COVID-19 and by economic sector Table 13 Distribution of the percentage of companies that intend to adopt the platform model by life cycle stage after the peak of COVID-19 and by economic sector

Table 13
Distribution of the percentage of companies that intend to adopt the platform model by life cycle stage after the peak of COVID-19 and by economic sector
Post-COVID-19 life cycle stage	Basic, energy and infrastructure industry (%)	Consumer goods, retail and healthcare (%)	Technology, media and telecommunications (%)	Professional and financial services (%)	Total (%)
1 - Exit	0	0			0
2 - Decline	0	29	40	0	17
3 - Maturity	38	24	41	10	25
4 - Growth	0	0	40	0	18
5 - Initialization		50	33	25	36
6 - Conceptualization	100	0	50		50
Total	29	22	41	8	24
Note: Elaborated by the authors. The table is a heatmap. Each cell ranges from 0-1, and is calculated by dividing the number of companies that have adopted the platform model by the total number of companies in that category. For example, for the “conception” row, 1/1 basic company adopted the platform model (100%), 0/1 retail company (0%), 1/2 technology company (50%) and there was no professional services company. In total, 2/4 companies in the conception stage adopted the platform model (50%).

Note: Elaborated by the authors. The table is a heatmap. Each cell ranges from 0-1, and is calculated by dividing the number of companies that have adopted the platform model by the total number of companies in that category. For example, for the “conception” row, 1/1 basic company adopted the platform model (100%), 0/1 retail company (0%), 1/2 technology company (50%) and there was no professional services company. In total, 2/4 companies in the conception stage adopted the platform model (50%).

The results obtained are in line with Vial (2019), who identified 35 studies that indicate business inertia as a factor that makes it difficult the adoption of business models that require digital transformation capabilities. Established and mature companies have greater difficulty in establishing business models that are highly dependent on digital technologies, such as the platform model. Similar results were presented by Islam et al. (2017), Svahn et al. (2017), Srivastava and Shainesh (2015), and Wenzel et al. (2015).

The number of publications on digital transformation in small companies has been growing significantly, indicating the importance of the topic for the academy and the management practice (Sarango-Lalangui et al., 2023). The digitalization movement among small and medium companies is characterized by the adoption of new technologies that allow small companies to adopt new transactional business models and interact with consumers through marketplaces and social networks (Da Rocha et al., 2024; Sarango-Lalangui et al., 2023; Bai et al., 2021). This work contributes to understand the dynamics of adoption of digital platforms-based business models by small companies, through an empirical approach based on Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA) and supported by a survey with 126 small Brazilian companies.

The universe of small companies is extremely important for the economic development of society in general. Small companies play a very large role in the countries’ economy and need to adapt to the new business models that are emerging, which are mostly based on digital technologies and platform models and ecosystems, in order to survive in the long term, overcoming the impacts caused by the COVID-19 pandemic and expanding the reach of services of these companies to less developed regions (Sudarnice et al., 2024; Kádárová, et al., 2023; Robertson et al., 2022; Bai et al., 2021).

The fact that most of unicorns (emerging companies valued at more than US$ 1 billion) are digital platform-based models, which allow early-stage companies to reach massive scale and gain value in a very short period, may be a factor that directs entrepreneurs with nascent businesses to consider digital platforms-based business models for their enterprises (Acs et al., 2017).

On the other hand, small companies in more mature stages are not embracing this technological transformation nor appropriating the value created within digital platforms and need to overcome the business inertia and barriers imposed by existing capabilities through incremental innovation strategies and with initiatives to retrain leadership and employees (Vial, 2019; Islam et al., 2017; Svahn et al., 2017; Srivastava & Shainesh, 2015; Wenzel et al., 2015).

It is important to notice that this study has limitations related to self-response bias, which is mitigated by the significant number of companies of the sample and by the quantitative nature, which did not allow us to delve deeper into the reasons for the non-adoption of the platform model by the companies analyzed.

As a suggestion for new studies regarding the object of analysis of this work, we believe new investigations with small-sized companies could be of great value, with a greater number of interviewees. Longitudinal investigations that demonstrate the progress of platform adoption by small companies will also contribute to a better understanding of the topic. Moreover, a qualitative approach focused on a deeper understanding of the profile of the digital entrepreneur should be considered to identify the critical success factors for digital technologies-based small companies and evaluate how to overcome business inertia through government or private initiatives.

The authors declare that there is no conflict of interest.

Authors’ statement of individual contributions
Roles	Contributions
	Schur R. D.	Sabiá R.	Trabasso R.
Conceptualization	∎
Methodology	∎
Software	∎
Validation	∎	∎
Formal analysis	∎	∎
Investigation	∎	∎
Resources	∎	∎	∎
Data Curation	∎
Writing - Original Draf	∎	∎
Writing - Review & Editing	∎	∎	∎
Visualization	∎	∎	∎
Supervision	∎
Project administration	∎
Funding acquisition	N.A.
Note: Acc. CRediT (Contributor Roles Taxonomy): https://credit.niso.org/

Note: Acc. CRediT (Contributor Roles Taxonomy): https://credit.niso.org/

The dataset supporting the results of this study is not publicly available.

The dataset supporting the results of this study is not publicly available.