Digital Platforms as a Fertile Ground for the Economic Sustainability of Startups: Assaying Scenarios, Actions, Plans, and Players

Abstract

This study examines the transformative role of digital platforms in fostering sustainable entrepreneurship within emerging economies. We argue that platforms transcend mere communication channels, acting as catalysts for innovation and collaboration among startups, thereby driving economic, social, and environmental progress. Our framework emphasizes platform-enabled startups, navigating the unique challenges and opportunities presented by these dynamic markets. We adopt a dual lens, using a mixed-methods approach to analyze digital development trends through the prism of platforms in emerging economies. This reframes the discourse on technology-driven development, acknowledging the unidirectional flow of platform adoption from developed nations. The research emphasizes the need for prioritizing sustainability standards in these regions. Furthermore, we delve into the interplay between platforms and sustainable entrepreneurship with the following three objectives: (1) deciphering the drivers of platform–startup interaction for sustainability goals, (2) formulating policies to maximize platform benefits while mitigating risks, and (3) developing actionable strategies for stakeholders to cultivate a thriving ecosystem of sustainable platform-based ventures. The findings of this study reveal six key uncertainties that will shape the future trajectories of sustainable entrepreneurship within digital ecosystems, particularly in developing nations. These uncertainties encompass the following: environmental and social standards, ongoing education and development, mobile application development and utilization, global market access, and competitiveness and value creation. Several alternative future scenarios have been constructed based on these uncertainties, including advancements in digital technologies, dynamic market conditions and evolving consumer behaviors, a heightened emphasis on sustainability and corporate social responsibility, and a paradigm shift towards collaborative business models. A comprehensive framework of supportive policies and interventions has been proposed to facilitate the realization of these scenarios. Moreover, the analysis underscores the pivotal roles of digital platform providers and startups as key stakeholders in this evolving landscape.

1. Introduction

Understanding the role of digital technologies, particularly digital platforms, in fostering economic development in developing countries is a critical contemporary issue [1]. These platforms have evolved beyond mere communication tools, emerging as powerful drivers of economic growth, productivity, and sustainable development [2,3,4]. They offer opportunities for job creation, skill development, and market access, laying the groundwork for transformative economic change in communities ripe for innovation [5].

However, achieving sustainable development demands a deeper understanding of the multifaceted role digital platforms play. While they create new avenues for entrepreneurship, market access, and global knowledge sharing [4,6], a crucial gap exists in comprehensively examining their impact on economic growth and sustainable development in developing countries [7]. This knowledge gap is particularly concerning given the potential of digital platforms to integrate economic, environmental, and social dimensions, promoting sustainable practices across business operations [8]. The evolving paradigm of sustainable development, as outlined by the United Nations, necessitates a holistic approach that strategically aligns economic growth with inclusivity and environmental stewardship [8].

This research explores the potential of digital platforms to act as catalysts for transformative economic scenarios, influence policy-making, and drive actionable strategies towards sustainable development [7]. This pivotal role necessitates expanding the concept of corporate social responsibility (CSR) by intertwining it with digital innovation to foster an ecosystem where economic prosperity and sustainability coexist [8].

Digital platforms, particularly those led by startups, are instrumental in revolutionizing business models, enhancing market accessibility, and enabling sustainable value creation, thereby serving as a backbone for economic resilience and growth [9,10]. However, stakeholder pressure from customers and governments compels these nascent companies to demonstrate environmental sustainability alongside economic prosperity [11].

This study delves into how digital platforms can orchestrate economic scenarios that promote inclusive growth and sustainable practices [12]. Regarding previous studies, we contend that by fostering innovation and collaboration, these platforms can nurture a sustainable and prosperous economic environment. Digital transformation not only accelerates business digitization but also cultivates a culture of sustainability through the adoption of sustainable business models (SBMs)—crucial for driving long-term economic and environmental well-being [10].

In the milieu of developing economies, the potential of digital platforms to transform traditional economic structures is profound. They offer a scalable solution to enhance economic activities, boost innovation, and facilitate the integration of sustainability into core business strategies, thereby contributing to a more robust and sustainable economic growth [13] This research delves into various scenarios where digital platforms can empower businesses, especially startups, to leverage technological advancements for sustainable economic development [14].

Considering the global imperative for sustainable development, it becomes essential to assess how digital platforms can transfer and adapt sustainability practices across different economic landscapes, particularly from developed to developing countries [8]. In this regard and by taking into account the importance of studying digital platforms and their effects on economic sustainability in emerging economies, in this study we aim to take a futuristic approach to analyze different scenarios in which digital platforms can influence economic sustainability. Moreover, we go beyond this and detect optimal strategies for each scenario. Furthermore, to provide a more detailed overview, we analyze the role that each player plays in this domain. To the best of our knowledge, this is the first research that focuses on the study of digital platforms and economic sustainability using a futuristic approach.

The organization of the article is as follows:

This introduction sets the stage for a comprehensive analysis that aligns with the paper’s title, focusing on the dynamic interplay between digital platforms, economic growth, and sustainability within the framework of developing economies. Through this lens, we aim to offer a nuanced understanding of how digital platforms can be harnessed to drive significant economic transformations within developing economies, ensuring a balanced trajectory towards sustainable development and inclusive economic progress.

2. Literature

2.1. Digital Platforms as a Promising Tool for Sustainability Development

The growing importance of sustainability is undeniable, fueled by complex social and environmental issues like climate change and rising inequality [15,16]. Businesses are responding by prioritizing environmental concerns, which often requires reformulating policies and strategies [15,16]. However, achieving truly effective solutions hinges on strong policy coherence. This means carefully integrating economic, social, environmental, and governance (ESG) considerations at both national and international levels. International organizations like the IPBES, IPCC, and the EU are taking the lead, recognizing the interconnectedness of nature, human well-being, and economic stability [17].

While transitioning to eco-friendly practices is commendable, some studies highlight potential uncertainties for businesses [14]. Adapting to this new landscape requires novel strategies that may impact decision making [18]. Nevertheless, most of the research overwhelmingly supports adopting an environmentally conscious approach.

Digital solutions are proving to be powerful tools for tackling environmental challenges. Their transformative nature fosters innovation, improves information processing, enables product and process tracking, underpins eco-design, and promotes green IT practices [15,16]. A prime example is the shift from traditional methods to virtual ones, like e-commerce, e-banking, and online meetings. These virtual solutions require fewer resources and demonstrably generate less pollution [15].

Digital transformation is also crucial for sustainable production and consumption. It empowers companies to meet customer needs with greater efficiency, often reducing energy consumption, which gives them a competitive edge. Additionally, digital platforms like Facebook Marketplace and eBay facilitate the buying and selling of pre-owned or underutilized items, promoting a more sustainable lifestyle [9].

2.2. Digitalization and Circular Economy as Propellant of Sustainability

Stakeholders are increasingly concerned with environmental issues like resource depletion, climate change, and waste. This pushes them to transform production and consumption practices for long-term sustainability and economic well-being [11]. Manufacturers face additional challenges due to recent events like COVID-19, further highlighting the need for sustainable solutions [19]. In response, companies are embracing digitalization to achieve a more sustainable supply chain and transition to a circular economy (CE) [19]. The CE is a framework that companies use to address the imbalance between economic growth and environmental sustainability. It promotes reusing products and materials instead of a linear “take, make, consume, discard” approach [20,21].

Digitalization is another crucial concept for manufacturers seeking long-term success [19]. Together, digitalization and the CE offer a powerful combination to improve productivity, efficiency, and environmental sustainability [22]. Digitalization acts as an enabler for the CE, minimizing resource use and maximizing the value of materials. Its impact on the environment, society, and economy is primarily indirect, influencing how products are designed, marketed, and used [23]. Studies have shown numerous benefits of digitalization for sustainability, including improved production processes, reduced energy consumption, eco-friendly product design, increased efficiency, lower transportation costs, and waste reduction [23].

While some studies highlight challenges like the need for rare materials to manufacture technology and energy consumption for blockchain applications, these seem outweighed by the advantages [23]. The implementation of digitalization varies by company size, with larger firms adopting it more readily [22]. However, for small- and medium-sized enterprises (SMEs) facing resource constraints, digital technologies are even more critical. They can help SMEs identify opportunities and achieve significant gains in efficiency and sustainability.

2.3. Startups as Agents of Sustainability Development

Environmental sustainability has become a top global priority due to the alarming effects of climate change and environmental disasters on economies and development [24]. Governments are enacting environmental regulations to push businesses towards mitigating their negative impact, with non-compliance leading to penalties and reputational damage [24,25,26].

However, for companies, environmental sustainability offers more than just regulatory compliance. It fosters a positive reputation and strengthens stakeholder trust, leading to moral capital [24,25,26]. The financial benefits are also significant. Environmentally conscious companies attract investors who perceive them as less risky [16,25]. Additionally, these companies gain a competitive edge through improved marketing and customer loyalty [27], ultimately driving financial growth and market expansion.

While developed nations currently lead in sustainability efforts, this trend is poised to reach developing countries as well, driven by global economic expansion [24]. Given the inherent innovation of environmentally conscious companies [28,29], startups are likely to be the key drivers of this shift. This is because startups are known for diffusing innovation and contributing significantly to sustainability transitions in developing economies [30].

3. Materials and Methods

This study delves into the complex world of sustainable startups, aiming to identify key drivers and develop actionable strategies for their success. Employing a mixed-methods approach, it combines qualitative and quantitative techniques to gain a comprehensive understanding of the landscape. To address the research questions below, the steps that follow are deemed necessary to undertake.

• What are the driving forces behind sustainable entrepreneurship within digital ecosystems in developing countries?
• What are the uncertainties shaping future scenarios for sustainable entrepreneurship in digital ecosystems in developing countries?
• What are the potential scenarios, policies, actions, and a comprehensive set of criteria for sustainable entrepreneurship within digital ecosystems in developing countries?
• What is the relationship between actions, policies, and policies and scenarios?
• How do stakeholders interact and align with strategic objectives?

• Step 1: Identifying the Drivers

The analysis begins with a thorough literature review, leveraging existing research on sustainability drivers in startups (e.g., [12,31]). This foundation is then solidified through the fuzzy Delphi method, a recognized tool for expert consensus, factor validation, uncertainty reduction, and resource efficiency [32,33,34,35,36]. Excel software 2013 facilitates the data analysis in this step, ensuring accuracy and efficiency [37].

• Step 2: Mapping the Uncertainties

With confirmed drivers in hand, the focus shifts to key uncertainties that shape future scenarios. In this regard, the Cross Impact analysis method is utilized [38]. Utilizing Mic-Mac_5.3.0 software, we analyze the impact and susceptibility relationships between drivers, revealing potential challenges and opportunities.

• Step 3: Envisioning the Future through Focus Groups

Moving into the qualitative realm, the research employs focus groups to delve deeper into the identified uncertainties and generate creative solutions [39,40,41]. Led by research experts, these sessions facilitated the brainstorming of scenarios, policies, actions, and evaluation criteria, paving the way for strategic development.

• Step 4: Connecting Actions and Policies through Multipol

The Multipol method, a multi-criteria futures study tool, takes center stage in the final step. This technique, supported by Multipol_5.3.0 software, allows us to evaluate the effectiveness of actions under different policies, and vice versa, within the context of the envisioned scenarios. This network analysis provides valuable insights for decision making by offering a range of potential solutions.

• Step 5: Implementing the Mactor Method

In this phase, we utilize the Mactor method to systematically analyze the interactions and influence between strategic actors identified in our study. Developed by [42], the Mactor method is instrumental in examining the power dynamics and mutual influences between actors and the objectives of the system. This approach does not only facilitate the identification of various actor roles and positions but also enables the effective forecasting of potential conflicts and collaboration opportunities. Thus, the Mactor method serves as a critical tool in crafting optimal strategies and enhancing strategic decision making, vital for management, policy-making, and development planning in the realm of sustainable startups. This comprehensive analysis aids in aligning strategic actions with the overarching goals of sustainability, ensuring that coherent and actionable strategies are developed.

Throughout these five steps, from the literature review to the Multipol and Mactor analyses, we engage with a carefully selected group of experts. This theoretical community, comprising members of the scientific board, entrepreneurship academics, and startup managers, brings diverse perspectives and deep knowledge to the research [19,43,44]. Their expertise in startups, sustainable entrepreneurship, and digital platforms ensures the relevance and validity of the findings.

A purposive sampling technique was employed to select a panel of experts to complete the research survey. Twenty-five experts were specifically chosen to complete Questionnaire 1, while an additional fifteen experts were selected for other research components. All selected experts possessed a minimum of five years of professional experience, held at least a master’s degree, demonstrated familiarity with the research methodologies, and expressed a strong commitment to participating in all stages of the research. These selection criteria were designed to ensure that the experts possessed the requisite knowledge and expertise to contribute meaningfully to the study. The expert panel was drawn from a population of academic faculty, entrepreneurship scholars, and startup executives.

By meticulously selecting experts based on their subject mastery, motivation, and professional experience, we ensure a robust and collaborative research process.

By utilizing a combination of qualitative and quantitative methods, we gain a comprehensive understanding of the drivers, uncertainties, and potential strategies for sustainable startups (

Table 1. The relationship between the methodology, questionnaire, and experts’ profiles.

Methodology	Questionnaire	Experts’ Profiles
		Members of the Scientific Board		Entrepreneurship Academics		Startup Managers
		Degree	Nember	Degree	Nember	Degree	Nember
Fuzzy Delphi	Expert Survey Questionnaire	Ph.D.	10	Ph.D.	3	Ph.D.	4
		Master’s	0	Master’s	5	Master’s	3
Cross-Impact Analysis	Paired Comparison Questionnaire	Ph.D.	5	Ph.D.	3	Ph.D.
Focal Group		Master’s					2
Multipol and Mactor	Evaluation Questionnaires		0	Master’s	2	Master’s

).

In the second step of the research, an expert survey questionnaire was used to identify the assessment factors that influence the level of impact. These assessment factors were derived from the drivers identified in the literature review of the existing literature.

In the third step, a standard paired comparison questionnaire was used to assess the level of influence that each of the influencing variables has on each other. The influencing variables were selected from the drivers identified in the previous step and screened by the experts. The level of influence was determined on a scale of 0 (no effect) to 3 (strong impact).

In the fifth step of the research, three standard questionnaires, designed as a matrix, were used to evaluate intervention options, policy alternatives, and future state projections with respect to the identified assessment factors. The scoring in the first survey instrument ranged from 0 to 20, with the columns representing the assessment factors and the rows representing the intervention options. The scoring in the second survey instrument was such that the sum of the scores given in each row must always be equal to 100, with the columns representing the assessment factors and the rows representing the policy alternatives. The scoring in the third survey instrument was also such that the sum of the scores given in each row must always be equal to 100, with the columns representing the assessment factors and the rows representing the future state projections.

It is important to note that the assessment factors, intervention options, policy alternatives, and future state projections used in these three questionnaires were derived from the fourth step, which employed a qualitative group discussion. However, in order to give the participants more control over their responses and to facilitate the presentation of their ideas, critical unknowns were identified through a separate process and then presented to the participants. This is because understanding these uncertainties is essential for scenario development.

The initial phase of this study involved the identification of 12 drivers through a thorough review of the relevant literature. Subsequently, these drivers were examined for screening and validation by a panel of experts using the fuzzy Delphi method [37]. This methodology, introduced by Kaufman and Gupta in 1988, effectively addresses the limitations of the traditional Delphi approach [45]. By consolidating expert opinions within a single round, the fuzzy Delphi method offers significant time and cost savings. The panel of experts comprised 25 individuals, a number recommended for generating highly coherent expert opinions within the fuzzy Delphi framework [11]. In this regard, an expert survey questionnaire was crafted, including the drivers extracted from the literature. This questionnaire was then distributed to the experts, who were asked to express their opinions using verbal terms ranging from “very low importance” to “very high importance,” in accordance with Table 2. The employment of Triangular Fuzzy Numbers (TFNs) served to enhance decision-making capabilities in the context of complex problem solving [36].

Subsequent to the data collection, the drivers were examined by employing the following criteria:

(1) Average Distance Values (d): These values represent the deviation between the “average of expert opinions about a driver” and “each expert’s opinion about each of the drivers”. These values should not exceed 0.2 [23,46].

$$d\left(\tilde{m},\tilde{n}\right)=\sqrt{{\displaystyle \frac{1}{3}}\left[{\left(m_1-n_1\right)}^2+{(m_2-n_2)}^2+{\left(m_3-n_3\right)}^2\right]}$$

(2) Consensus Percentage for Experts: The percentage of this agreement among experts for each of the drivers should surpass 75% [11,23].

$$\mathrm{P}\mathrm{e}\mathrm{r}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{a}\mathrm{g}\mathrm{e} \mathrm{o}\mathrm{f} \mathrm{e}\mathrm{x}\mathrm{p}\mathrm{e}\mathrm{r}\mathrm{t} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{e}\mathrm{n}\mathrm{s}\mathrm{u}\mathrm{s}=100\times {\displaystyle \frac{\sum _{i=1}^j\left(c_i\right)\left\{\begin{array}{c}{c}_i=1, if d\le 0.2\\ 0 otherwise \end{array}\right.}{j}}$$

(3) Threshold: In the context of this study, the threshold for screening drivers is established at a minimum of 0.7. Consequently, the defuzzification values of each of the drivers must exceed this threshold [11,47]

$$\mathrm{D}\mathrm{e}\mathrm{f}\mathrm{u}\mathrm{z}\mathrm{z}\mathrm{i}\mathrm{f}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}={\displaystyle \frac{a_1+{2a}_2+a_3}{4}}$$

The expert panel’s confirmation of all drivers, as demonstrated in

Table 3. Fuzzy Delphi results for the expert consensus.

Result	Defuzzification	Fuzzy Numbers			$\mathbf{E}\mathbf{x}\mathbf{p}\mathbf{e}\mathbf{r}\mathbf{t} \mathbf{C}\mathbf{o}\mathbf{n}\mathbf{s}\mathbf{e}\mathbf{n}\mathbf{s}\mathbf{u}\mathbf{s}(\%)\ge 75\%$	$\left(\mathit{d}\right)\le 0.2$		Drivers	Reference
		a1	a2	a3
Approved	0.785	0.560	0.810	0.960	84%	0.131473	Environmental and social standards	A1	[48]
Approved	0.758	0.530	0.780	0.940	80%	0.145169	Sustainable ecosystems	A2	[49]
Approved	0.775	0.540	0.790	0.980	92%	0.086519	Internationalization of technology	A3	[50]
Approved	0.753	0.520	0.770	0.950	80%	0.120219	Sustainable supply chain management	A4	[51]
Approved	0.758	0.530	0.780	0.940	76%	0.143686	Transparency in reporting	A5	[52]
Approved	0.795	0.580	0.830	0.940	84%	0.167082	Legislation and institutional facilitation	A6	[10]
Approved	0.840	0.630	0.880	0.970	88%	0.129722	Continuous education and development	A7	[53]
Approved	0.808	0.580	0.830	0.990	96%	0.101477	Augmented reality (AR) and virtual reality (VR)	A8	[8]
Approved	0.778	0.550	0.800	0.960	84%	0.125617	Mobile app development and use	A9	[7]
Approved	0.803	0.570	0.820	1.000	100%	0.082303	Access to global markets	A10	[54]
Approved	0.773	0.550	0.800	0.940	76%	0.154997	Competitiveness	A11	[13]
Approved	0.833	0.610	0.860	1.000	100%	0.100592	Value creation	A12	[48]

, indicates the high accuracy with which the literature review identified these factors in addressing the research questions.

Table 2. Verbal terms and fuzzy numbers in the fuzzy Delphi method [19,46,48].

Fuzzy Numbers	Verbal Terms
(0,0,0.25)	Very Low Importance
(0,0.25,0.5)	Unimportant
(0.25,0.5,0.75)	Medium Importance
(0.5,0.75,1)	High Importance
(0.75,1,1)	Very High Importance

Table 2. Verbal terms and fuzzy numbers in the fuzzy Delphi method [19,46,48].

Fuzzy Numbers	Verbal Terms
(0,0,0.25)	Very Low Importance
(0,0.25,0.5)	Unimportant
(0.25,0.5,0.75)	Medium Importance
(0.5,0.75,1)	High Importance
(0.75,1,1)	Very High Importance

The third step involved administering a standardized questionnaire to the designated experts to collect data for cross-effects analysis so as to reach key uncertainties. This methodology, which entails examining the reciprocal relationships between variables, serves to identify the critical system variables [55]. The extent of this influence is measured on a scale ranging from zero to three. The matrix dimensions are 12 × 12. Within this matrix, the sum of the rows represents the amount of influence exerted by a driver on other drivers, while the sum of the columns represents the amount of influence received by a driver from other drivers. Factors with high influence and high dependence are identified as key uncertainties. The results obtained in

Table 4. Matrix characteristics.

Indicator	Value
Matrix size	12
Number of iterations	2
Number of zeros	25
Number of ones	28
Number of twos	63
Number of threes	28
Number of P	0
Total	119
Fill rate	82/63,889%

indicate that the matrix dispersion degree is 82.64 percent. This makes the matrix optimal based on the statistical index with two desirability and optimization rotations. This finding attests to the high validity of the matrix and the responses provided.

The direct relations diagram (Figure 1) elucidates the position of each variable within the system. Variables A2, A3, A6, and A8 fall under the category of influential variables, while A4 and A5 belong to the category of dependent variables. Additionally, variables A12, A7, A9, A10, A11, and A1 are classified as linkage variables, showcasing both influential and dependent characteristics. The MICMAC analysis identified these variables (A12, A7, A9, A10, A11, and A1) as key uncertainties.

In the fourth step, a focal group was convened to address the identified uncertainties and generate suggestions for scenarios, policies, actions, and a set of criteria. Subsequently, the Multipol method was employed to analyze the data gathered from the distribution of evaluation questionnaires. Multipol is a multi-criteria decision-making tool that evaluates various actions based on policies through expert participation. This participation is also utilized in this method to assess different policies based on scenarios. This methodology empowers decision-makers by providing a comprehensive network of potential solutions [39,52,54]. The Multipol method’s structure includes four distinct components [36,56].

(1) Determining Evaluation Criteria that Align with the Study Objective: Evaluation criteria are the essential measurable aspects that assess the effectiveness of a judgment. Therefore, these criteria form the foundation for determining the processes used to evaluate the performance of scenarios, strategies, and actions. According to

Table 5. Criteria for sustainable entrepreneurship on digital platforms in developing countries.

Evaluation Criteria	Symbol	Dimension	Weight	Description
Social Impact of Digital Entrepreneurship	C1	Social	5	Evaluate the social impact of entrepreneurship based on digital platforms, including increased employment, online social interactions, and enhanced community awareness.
Social Balance	C2	Social	5	Assess whether digital entrepreneurship contributes to social balance or may lead to unfair disparities in access to opportunities.
Utilization of Innovative Technologies in Entrepreneurship	C3	Technological	5	Investigate how modern technologies are utilized in the process of digital entrepreneurship and their impact on innovation and technological performance.
Societal Acceptance of Technology	C4	Technological	4	Evaluate to what extent digital entrepreneurship leads to societal acceptance of technology.
Impact on Employment and Economic Growth	C5	Economy	4	Evaluate the impact of digital entrepreneurship on job creation and local and overall economic growth.
Effect on Regional Development	C6	Economy	5	Examine how digital entrepreneurship contributes to the development of various regions and its impact on regional balance.
Environmental Impact	C7	Environment	4	Investigate the environmental impact of digital entrepreneurship, considering energy consumption, greenhouse gas emissions, and other ecological effects.
Use of Natural Resources	C8	Environment	5	Examine how natural resources are utilized in processes and productions related to digital entrepreneurship, with a focus on optimizing consumption.

, experts in the focal group proposed eight criteria in the social, technological, economic, and environmental domains.

(2) Determining Scenarios: Scenarios are visualizations of the prospective futures that depict the attainment of the desired objectives. As illustrated in

Table 6. Scenarios for sustainable entrepreneurship on digital platforms in developing countries.

Scenario	Symbol	Weight	Description
Advancement in Digital Technology	S1	5	The growth of innovative technologies such as artificial intelligence, the Internet of Things, and blockchain that can support digital entrepreneurs in creating new models and processes, enhancing efficiency, and fostering innovation in the business domain.
Market Dynamism and Changes in Consumption Patterns	S2	5	Accelerated changes in customer needs and preferences, urging digital entrepreneurs to predict and quickly adapt to these changes.
Emphasis on Sustainability and Social Responsibility	S3	5	Increased attention to environmental and social issues, necessitating sustainable measures in digital businesses, including heightened corporate social responsibility (CSR) and consideration for environmental impacts.
Shift in Business Models and Promotion of Collaboration	S4	5	New ways of collaboration between companies and startups to create dynamic ecosystems that enable smaller businesses to leverage the technologies and resources of larger corporations.

, experts in the focal group identified four alternative scenarios, including advancement in digital technology, market dynamism and changes in consumption patterns, emphasis on sustainability and social responsibility, shifts in business models, and the promotion of collaboration for evaluation.

(3) Determining Policies: Policies form a range of strategies devised to accomplish objectives while taking into account environmental conditions such as political, social, economic, and physical contexts. The policies considered in this study by the focal group are listed as below (

Table 7. Policies for sustainable entrepreneurship on digital platforms in developing countries.

Policy	Symbol	Weight	Description
Policy to Support Research and Development in Technology	P1	5	Elevating investment in research and development in digital technology to facilitate progress and innovation in digital businesses. This policy focuses on securing financial resources and supporting technological projects for the improvement of technologies and the development of new products.
Promotion of Sustainability and Social Responsibility Policy	P2	4	Establishing standards and encouraging sustainable business practices, including environmental protection and the development of socially responsible activities. This policy aims to create positive connections with the community and customers, enhancing commitment to social responsibility.
Facilitation of Startup Processes Policy	P3	3	Simplifying and supporting the establishment of new companies in the digital domain, including providing financial facilities, removing legal barriers, and offering platforms for knowledge exchange and collaboration. This policy addresses creating a suitable governance environment for startup growth.
Encouragement of Collaboration and Data Sharing Policy	P4	4	Formulating policies and facilities that incentivize digital entrepreneurs to collaborate and share data. This policy focuses on creating collaborative ecosystems among companies and sharing information to enhance innovation and improve business processes.

).

(4) Actions: Actions are series of potential interventions that serve as supporting measures in the implementation of policies. As demonstrated in

Table 8. Actions for sustainable entrepreneurship on digital platforms in developing countries.

Actions	Symbol	Description
Increase in Research and Development Budget	AC1	Boosting investment in projects and activities related to digital research and development to facilitate innovation and technological advancement.
Establishment of Specialized Research Centers	AC2	Creating and establishing specialized research centers in key areas of digital technology to facilitate research initiatives.
Development of Environmental Standards	AC3	Formulating and presenting environmental standards for digital businesses to promote environmentally responsible behaviors and practices.
Enhancement of Collaboration with Universities and Industry	AC4	Developing effective collaborations with universities and industry to increase technology transfer and leverage specialized knowledge in research and development projects.
Encouragement of Ecosystems of Collaboration	AC5	Formulating policies and measures to incentivize companies and startups to establish collaborative ecosystems. This includes providing facilities and resources for the exchange of knowledge, resources, and shared information.
Promotion of Data-Sharing Culture	AC6	Organizing programs and training sessions to increase understanding and foster the acceptance of a data-sharing culture within organizations and digital businesses. This policy aims to enhance collaborative interactions and promote knowledge sharing within the organizational framework.
Establishment of Supportive Platforms	AC7	Creating online platforms aimed at providing support services to startups, including the provision of financial facilities, specialized consultation, and connection with investors.
Encouragement of Renewable Energy Use	AC8	Implementing policies and measures to incentivize the use of renewable energy sources and reduce negative environmental impacts.
Conducting Educational Programs on Social Responsibility	AC9	Organizing programs and diverse training sessions to increase awareness and develop social responsibility skills among employees and managers of the company.
Simplification of Company Registration Processes	AC10	Facilitating and streamlining the steps for company registration for startups through the provision of online processes and forms, with the goal of enhancing accessibility and speed in launching digital businesses.

, experts proposed 12 policy actions aligned with the research objectives.

4. Results from the Multiple Analysis

Employing a multiple-methods approach, three questionnaires were developed to evaluate criteria, actions, policies, and scenarios. These questionnaires were distributed to a panel of experts who were instructed to complete them collaboratively and reach a consensus on their responses. The first questionnaire assessed actions against the evaluation criteria, employing a scoring system ranging from 1 to 20. The second questionnaire evaluated policies based on the same criteria, ensuring that the sum of each row totaled 100. Similarly, the third questionnaire assessed scenarios, utilizing the same scoring methodology as the second questionnaire. The findings derived from these three questionnaires, encompassing actions aligned with policies and policies aligned with scenarios, were presented in a tabular and graphical format.

4.1. Study of Actions Based on Policies

Table 9. Evaluation of actions with respect to policies.

Action/Policies	P1	P2	P3	P4	Average	Rank
AC1	12/4	12/2	12/3	12/2	12/3	6
AC2	13/1	12/8	12/9	12/8	12/9	10
AC3	12/6	12/6	12/5	12/5	12/5	8
AC4	12/2	12/2	12/2	12/1	12/2	5
AC5	11/1	11/3	11/3	11/3	11/2	2
AC6	12/4	12/4	12/4	12/4	12/4	7
AC7	12	11/6	11/8	11/7	11/8	3
AC8	12/8	12/9	12/8	12/8	12/8	9
AC9	12	12/2	12/1	12/2	12/1	4
AC10	10/1	10	10/1	10/1	10/1	1

presents the score of actions regarding policies, with AC2, AC8, AC3, AC6, and AC1 emerging as the top five highest-ranked actions. These actions achieved a highest average value and lower standard deviation compared to their counterparts.

Next, the profile map, derived from the action–policy analysis, depicts the relative performance of each action in relation to the policies. This map provides insights into the behavioral patterns of actions and their respective policy affinities. As per the chart, AC2 exhibits the highest score related to policy, while AC10 holds the lowest. Additionally, a nuanced examination of the chart reveals that AC2, for instance, possesses a stronger association with policy P1 compared to P2, indicating a closer relationship with policy P1.

The below chart (Figure 2) reveals significant variations in policy association scores across the ten AC units. AC2 emerges as the unit with the highest overall policy score, while AC10 demonstrates the lowest.

Further nuanced analysis highlights specific trends within individual policy associations. AC2 exhibits a stronger connection with policy P1 compared to P2, indicating a closer alignment with the former. Similarly, AC1 maintains a stronger relationship with P1, while AC3 demonstrates a more balanced association with both P1 and P2. This trend continues, with the subsequent units displaying an increasing breadth of policy engagement: AC4 encompasses P1, P2, and P3; AC5 focuses on P2, P3, and P4; AC6 demonstrates a strong connection across all four policies. Notably, AC7 and AC8 each show a distinct preference for individual policies, P1 and P2, respectively. AC9 maintains a stronger association with P2 and P4, while AC10 exhibits a balanced engagement with P1, P3, and P4.

An analysis of the classification sensitivity map outputs generated by multiple_5.3.0 software packages revealed a correlation between the action importance (average score) and standard deviation, suggesting that actions with a higher importance and lower standard deviation possess a higher likelihood of success. As per the Figure 3, AC1, AC3, AC4, AC6, AC8, and AC9 emerged as actions with a higher probability of success, with AC8 demonstrating the highest efficacy. While AC8 stands out as the most effective action, it is noteworthy that strategic consideration and proper management of AC2 could further enhance the overall success rate.

Figure 4 highlights the optimal actions for each policy. Actions AC3, AC8, and AC9 emerge as the most suitable choices for policy P2, while actions AC2, AC1, and AC4 demonstrate the highest suitability for policy P1. Additionally, actions AC7 and AC10 are identified as the most effective options for policy P3, and AC6 and AC5 demonstrate the highest suitability for policy P4.

4.2. Study of Policies Based on Scenarios

The second phase of the data analysis, utilizing multiple software, focused on evaluating policies based on scenarios. As per

Table 10. Evaluation of polices with respect to scenarios.

	S1	S2	S3	S4	Average	Rank
P1	12/1	13/4	12/7	13/4	12/9	4
P2	12/6	11/9	12/5	12/3	12/3	1
P3	12/6	12/9	12/3	12/9	12/6	3
P4	12/7	12/6	12/2	12/4	12/5	2

, policy P1 emerges as the most effective policy in this study, followed by policies P3, P4, and P2, respectively.

A scenario–policy profile map was generated, similar to the previous section, to showcase the performance of each policy across various scenarios. This map elucidates the behavioral patterns of policies in relation to scenarios and their respective scenario affinities. As per the Figure 5, P1 exhibits the highest scenario-related score, while P2 holds the lowest. Additionally, a closer examination of the chart reveals that P1, for instance, possesses a stronger association with scenarios S2 and S4 compared to S3 and S1, indicating a closer alignment with scenarios S2 and S4. Furthermore, it can be conferred that P2 has a stronger connection with S1 and S3 scenarios, while P3 has a more robust connection with scenarios S2 and S4. Also, P4 has established a stronger connection with scenarios S1 and S2.

Similar to the previous section, a classification sensitivity map analysis was conducted utilizing multiple software. This chart also depicts the standard deviation and importance (average score) of each policy. As per the chart, policies with higher importance and lower standard deviation demonstrate a higher likelihood of success. According to the Figure 6, P4 exhibits the highest probability of success, while P1 maintains the highest average score (importance).

The final output of the multiple software in this section is the policy–scenario closeness map, as depicted in Figure 7. The distance between each of the policies and the scenarios represents the effectiveness of that policy in supporting the desired scenario.

Consequently, based on the analysis of Figure 8, it can be concluded that policies P2 and P4 emerge as the most effective policies for scenario S1. Policies P1 and P3 constitute the most effective policies for scenario S2. Policies P1 and P2 stand out as the most effective policies for scenario S3, while policies P1 and P3 demonstrate the highest effectiveness for scenario S4. Therefore, by integrating the findings from the study of actions based on policies and the study of policies based on scenarios, a future-oriented framework of actions and policies to achieve alternative scenarios can be established, as illustrated in Figure 8.

This study unveils the transformative influence of startups on digital platforms in fostering sustainable entrepreneurship through the following four pivotal scenarios: (1) Advancement in Digital Technology, (2) Market Dynamism and Evolving Consumption Patterns, (3) Emphasis on Sustainability and Social Responsibility, and (4) Shift in Business Models and Promotion of Collaboration.

5. Advancement in Digital Technology

The rapid advancement of digital technology has profoundly impacted the sustainability of entrepreneurship, particularly when intertwined with the active presence of startups on digital platforms [2,57]. This synergistic interplay empowers entrepreneurs to embark on new business ventures that foster sustainability, innovation, and positive social impacts [4,58]. Firstly, the progress in digital technology has equipped startups with an arsenal of tools to enhance their products and services in an innovative manner [58,59]. From artificial intelligence to the Internet of Things (IoT), these tools empower entrepreneurs to introduce groundbreaking improvements in processes and products. Simultaneously, startups on digital platforms contribute to heightened market dynamics [4,58]. Their agility in responding to market shifts and introducing novel products steers the market towards innovation and altered consumption patterns [8]. Furthermore, startups on digital platforms, with an emphasis on sustainability and social responsibility, harness technology to address social and environmental challenges [8]. By employing technology to solve societal problems, companies not only tackle social vulnerabilities but also generate economic advancements while maintaining a balance in natural resources.

Sustainable entrepreneurship, anchored by the presence of startups on digital platforms, necessitates a paradigm shift in business models and the promotion of collaboration. Leveraging technologies such as artificial intelligence, blockchain, and other tools allows entrepreneurs to reap the benefits of industrial collaboration and create novel business models [4,58,60]. The intricate interconnectedness between digital technology advancements and the presence of startups on digital platforms not only transforms business markets but also facilitates the emergence of an entrepreneurial, innovative, and sustainable ecosystem.

6. Market Dynamism and Changes in Consumption Patterns

The confluence of market dynamism and the presence of startups on digital platforms has far-reaching implications for sustainable entrepreneurship [61]. The rapid evolution of markets and shifts in consumption patterns, spurred by the active involvement of startups, usher in a paradigm shift in how entrepreneurs approach sustainability. Primarily, the dynamic nature of markets, amplified by startups on digital platforms, catalyzes agility and responsiveness among entrepreneurs [62,63,64]. Startups, armed with innovative solutions, swiftly adapt to market shifts, fostering an environment conducive to continuous innovation and evolution.

Furthermore, changes in consumption patterns, influenced by startups on digital platforms, contribute to the emergence of sustainable business models [8,58]. Entrepreneurs, cognizant of evolving consumer preferences, harness digital technologies to tailor products and services that align with sustainable practices, thereby establishing a symbiotic relationship between market dynamism and sustainability [13]. In essence, the interplay between market dynamism and the presence of startups on digital platforms propels entrepreneurs towards a sustainability-driven approach. This synergy not only enhances the adaptability of businesses but also fosters a culture of innovation that is inextricably linked to the evolving dynamics of consumer behavior in the digital age.

7. Emphasis on Sustainability and Social Responsibility

The heightened emphasis on sustainability and social responsibility within the entrepreneurial landscape is inextricably linked to the active presence of startups on digital platforms [10,64]. This synergistic interplay not only redefines the paradigm of business practices but also underscores the pivotal role of startups in driving sustainable entrepreneurship. At the forefront of this transformation, startups on digital platforms manifest their commitment to sustainability through innovative solutions that address environmental and societal challenges [8,58]. By harnessing the power of digital technologies, these startups meticulously design products and services that prioritize environmental impact reduction, promote responsible resource management, and contribute positively to societal well-being [15,16]. Furthermore, the inherent transparency facilitated by digital platforms empowers startups to directly communicate their commitment to sustainability and social responsibility to consumers. This fosters a sense of trust and loyalty, as consumers increasingly gravitate towards businesses that prioritize ethical and responsible practices [9].

Additionally, the collaborative nature of digital platforms enables startups to forge alliances and partnerships that amplify the impact of their sustainability initiatives [65,66,67]. Through the exchange of shared resources and knowledge, these collaborations contribute to the development of a robust ecosystem where sustainability is not merely a goal but a collective endeavor. In essence, the convergence of sustainability and social responsibility with the active engagement of startups on digital platforms heralds a transformative era in the entrepreneurial landscape. It showcases how startups, leveraging the digital realm, are at the vanguard of instigating positive change, influencing consumer behavior, and collectively steering the entrepreneurial landscape towards a more sustainable and socially responsible future.

8. Shift in Business Models and Promotion of Collaboration

The transformative shift in business models and the emphasis on collaboration, facilitated by startups on digital platforms, are profoundly impacting the landscape of sustainable entrepreneurship [10]. This synergistic interplay underscores the pivotal role of innovative business approaches and collaborative endeavors in catalyzing sustainable practices [5]. At the forefront of this transformation, startups on digital platforms are driving the evolution of business models, characterized by innovation and adaptability. Empowered by technological advancements, these startups are redefining traditional business structures, embracing agile methodologies and customer-centric approaches [6,8]. As a result, sustainable business practices emerge that not only address evolving market demands but also contribute positively to environmental and societal concerns [8,68,69]. Furthermore, the promotion of collaboration on digital platforms is reshaping the competitive landscape. Recognizing the advantages of shared resources and expertise, startups are actively engaging in collaborative efforts. Technologies such as artificial intelligence and blockchain are facilitating seamless collaboration, enabling startups to collectively address complex sustainability challenges and fostering an environment where knowledge exchange becomes a driving force for positive change [8,51].

Moreover, collaborative initiatives lead by startups on digital platforms are contributing to the formation of interconnected business ecosystems. These ecosystems promote a culture of collective responsibility, where startups collaborate not only for competitive advantage but also to achieve shared sustainability goals [56,70,71]. This collaborative ethos extends beyond individual businesses, creating a network effect that strengthens the overall resilience and sustainability of the entrepreneurial landscape. In essence, the interplay between the shift in business models and the promotion of collaboration, driven by startups on digital platforms, is instrumental in advancing sustainable entrepreneurship. This dynamic relationship not only revolutionizes how businesses operate but also establishes a collaborative foundation upon which the principles of sustainability can flourish, paving the way for a more responsible and resilient entrepreneurial future.

In conclusion, the endeavors of startups on digital platforms in addressing these four scenarios not only revolutionize the business landscape but also steer us towards a more sustainable and innovative future of entrepreneurship. This study unequivocally establishes that the prevalence of startups on digital platforms serves as a pivotal catalyst in shaping sustainable entrepreneurship in the contemporary world.

• Step 5: Implementing the Mactor Method

The Mactor method effectively analyzes interactions within complex systems by focusing on the following two main aspects: interactions among actors and their alignment with strategic objectives. This analysis categorizes actors based on influence and dependency, helping to understand power dynamics and develop tailored strategies.

In this study, scenarios generated from the Multipol method are used as objectives in the Mactor phase, allowing for a comprehensive evaluation of how these scenarios influence actors’ interactions and strategic alignments. This integration is crucial for identifying potential collaborations and conflicts, thus enhancing decision making and the efficiency of the system. The Mactor method provides detailed insights into the dynamics of the system, facilitating the development of effective strategies based on the interplay of power relationships and strategic objectives.

This Mactor analysis diagram, Figure 9, illustrates the varying levels of influence and dependence among key actors in the digital platform ecosystem. Actors like Digital Platform Providers and Startups are both highly influential and dependent, central to driving innovation yet reliant on each other. In contrast, Policy Makers and Government Agencies wield significant influence with minimal dependence, reflecting their regulatory roles. Technology Developers show moderate influence and dependence, essential yet not dominant. Finally, stakeholders such as Investors, Research Institutions, and NGOs, while supportive and dependent, exert minimal influence over the ecosystem’s direction. This visualization highlights strategic leverage points and potential vulnerabilities within the ecosystem, guiding stakeholders in prioritizing efforts to enhance engagement and influence distribution.

This histogram, Figure 10, visualizes the competitiveness of various actors within the digital platform ecosystem, indicating how each actor stands in terms of market competitiveness on a scale from 0 to 1.1. Startups, Digital Platform Providers, Government Agencies, Investors and Financial Institutions, and Policy Makers exhibit the highest level of competitiveness, each scoring 1.1, suggesting that these groups are highly dynamic and effective in maintaining competitive edges in their respective domains. Research Institutions also show strong competitiveness at 1.0, reflecting their capability in driving innovation and maintaining relevance. In contrast, Local Communities, Non-Governmental Organizations (NGOs), and Customers and Users score slightly lower at 0.9, indicating a slightly less competitive position, which may reflect lesser influence or resources to assert dominance in the marketplace compared to other more central actors. Technology Developers score 1.0, aligning them closely with Research Institutions in terms of their contribution to competitive innovation in the ecosystem. This distribution highlights the varying degrees of influence and capability among the actors, essential for understanding power dynamics and potential areas for strategic enhancements in the ecosystem.

The two diagrams presented, Figure 11 and Figure 12, are outputs from a Mactor analysis, providing visual representations of distances, one for objectives (S1 to S4) and the other for actors within a digital platform ecosystem. The first diagram shows net distances between four distinct objectives (S1–S4), where S1 and S4 are closely positioned, suggesting they are more aligned or similar in their outcomes or requirements, while S2 is notably distanced, indicating it is quite different or potentially conflicting with the others. The second diagram maps net distances between various actors, from startups to policy makers. This visual suggests a dense cluster around startups, policy makers, technology developers, and digital platform providers, indicating these actors are closely related in terms of goals or impacts within the ecosystem. In contrast, actors like local communities and investors appear more isolated, implying less direct interaction or influence with the central cluster of actors. Together, these diagrams help stakeholders understand alignments and tensions both between goals and actors, facilitating more informed strategic planning and management decisions in the ecosystem.

9. Conclusions and Discussion

Developing economies are undergoing significant transformations due to the rise of digital platforms, which have proven to be powerful catalysts for innovation and growth. These platforms have transitioned traditional markets into dynamic, digitally enabled ecosystems, facilitating inclusive economic development that benefits both local entrepreneurs and global investors [2,8]. The adoption of advanced digital technologies, such as artificial intelligence and blockchain, enables these economies to become more agile, transparent, and resilient, positioning them to capitalize on the digital era’s potential for sustainable development [51].

In the following paragraphs, we answer the research questions.

• What are the driving forces behind sustainable entrepreneurship within digital ecosystems in developing countries?

This study identified twelve critical determinants of sustainable entrepreneurship within digital platforms in developing country contexts. These drivers encompass environmental and social standards, sustainable ecosystems, international technology transfer, sustainable supply chain management, transparent reporting, enabling legislation and institutions, continuous capacity building, the integration of augmented reality (AR) and virtual reality (VR), mobile application development and utilization, access to global markets, and the pursuit of competitiveness and value creation.

2.

What are the uncertainties shaping future scenarios for sustainable entrepreneurship in digital ecosystems in developing countries?

Among these drivers, six uncertainties were identified as having a profound impact on the future trajectory of sustainable entrepreneurship in digital platforms within developing countries. These uncertainties pertain to environmental and social standards, continuous capacity building, mobile application development and utilization, access to global markets, competitiveness, and value creation.

3.

What are the potential scenarios, policies, actions, and a comprehensive set of criteria for sustainable entrepreneurship within digital ecosystems in developing countries?

To assess the potential outcomes, the following eight evaluation criteria were established: the social impact of digital entrepreneurship, social equity, the innovative application of technologies, societal technology acceptance, contributions to employment and economic growth, regional development impact, environmental performance, and natural resource utilization. Subsequently, the following four potential future scenarios were constructed: advancements in digital technology, evolving market dynamics and consumer preferences, a heightened emphasis on sustainability and social responsibility, and a transformation of business models towards collaboration.

Based on these scenarios, policies aimed at stimulating sustainable entrepreneurship were formulated, considering political, social, economic, and environmental factors. These policies encompass research and development support, promoting sustainability and social responsibility, facilitating the startup process, and fostering collaboration and data sharing. To operationalize these policies, twelve supportive actions were proposed, including increased research and development investment, the establishment of specialized research centers, the development of environmental standards, enhanced university–industry partnerships, the cultivation of collaborative ecosystems, the promotion of data sharing, the creation of supportive platforms, the encouragement of renewable energy utilization, the implementation of social responsibility educational programs, the simplification of company registration processes, and the establishment of interactions between stakeholders.

4.

What is the relationship between actions, policies, and policies and scenarios?

The analysis revealed specific relationships between policies, actions, and scenarios. For instance, policies P3 and P4, in conjunction with supportive actions AC5, AC6, AC7, and AC10, could contribute to the “Advancement in Digital Technology” scenario. Similar relationships were identified for the other scenarios.

5.

How do stakeholders interact and align with strategic objectives?

Our Mactor analysis has highlighted the pivotal role of startups in this transformative process. As primary agents of change, startups are not just adopting digital tools, but are at the forefront of creating innovative, sustainable economic models. By utilizing platforms that support extensive collaboration and interconnectedness, these startups are steering away from traditional competitive practices towards systems that emphasize economic resilience and sustainability [6,72].

The Mactor analysis underscores that startups are strategically positioned at the nexus of influence among key ecosystem actors—government agencies, policy makers, and technology developers—playing a critical role in shaping the digital landscape. This positioning facilitates startups to leverage their innovative capabilities while aligning with broader economic goals that promote long-term societal and environmental well-being [8].

From the MultiPolar analysis, we extracted actionable insights that demonstrate how the alignment of strategic objectives among different actors fosters a conducive environment for policy development and strategic investment. Particularly, the close alignment of startups with technology developers and policy makers highlights a synergy that can be tapped into for accelerating sustainable economic practices. Additionally, potential conflicts identified between strategic objectives—such as those between environmental sustainability and immediate economic returns—point to areas requiring careful policy intervention to ensure that economic growth does not come at the expense of environmental health.

Our research provides a clear view of how digital platforms can serve as engines of economic growth, driving sustainable development in emerging markets. By exploring future-oriented scenarios, we have illuminated pathways for these platforms to orchestrate economic, social, and environmental prosperity effectively. The immense potential for startups to instigate significant changes underscores the necessity of nurturing an ecosystem where innovation is deeply integrated with sustainability principles.

In summary, the synergy between digital platforms and startups in developing economies is not only reshaping traditional economic paradigms but also setting the stage for a sustainable future. The strategic use of the Mactor and MultiPolar analyses in our study has provided a detailed blueprint for stakeholders to navigate and optimize these transformations. This approach ensures that digital innovations are strategically harnessed to support comprehensive economic transformation and sustainability, making a significant impact on the global economic landscape.

The findings of this study align with the work of [48] in exploring the role of digital technologies in sustainable business models. Both studies underscore the potential of digital tools to reshape business model components and facilitate collaborative value creation. Furthermore, the research resonates with [73] in emphasizing the pivotal role of digital platforms in sustainable entrepreneurship, particularly in terms of leveraging capabilities and digital innovations.

While the contributions of [74] to the field are acknowledged, these studies predominantly adopt either quantitative or qualitative methodologies. A comprehensive understanding of the multifaceted relationship between digital technologies and sustainable entrepreneurship necessitates a mixed-methods approach. Moreover, these studies often overlook the dynamic nature of the phenomenon by failing to incorporate future-oriented perspectives and a comprehensive analysis of influential factors. Additionally, while existing research highlights the importance of actor relationships, it falls short of exploring the intricacies of these interactions and their implications for value creation.

10. Theoretical Implications

This study offers a novel framework for understanding how digital platforms can serve as catalysts for sustainable entrepreneurship in developing countries. By identifying key drivers, uncertainties, and potential pathways, the research contributes to the theoretical discourse on sustainable business models and digital innovation. The analysis of key actors highlights the multidimensional nature of sustainability and underscores the importance of collaborative efforts. This study posits that digital platforms can be a cornerstone of sustainable development strategies in developing economies.

11. Practical Implications

The findings of this research provide valuable insights for policy makers and practitioners seeking to foster sustainable entrepreneurship through digital platforms. By delineating potential actions and policies, the study offers a roadmap for creating supportive ecosystems that nurture startups and drive environmental sustainability. The emphasis on collaboration among digital platform providers, startups, and other stakeholders is crucial for maximizing the impact of these initiatives. This research underscores the need for targeted investments in platform-based startups and the development of robust evaluation frameworks to assess the effectiveness of sustainability-oriented policies and actions.

By bridging the gap between digital platforms and sustainable development, this study offers a blueprint for harnessing the power of technology to address pressing global challenges.

12. Limitations and Future Studies

Our research encountered several limitations that warrant consideration. Firstly, access to comprehensive and up-to-date data was limited. Secondly, sampling was constrained, particularly within specific countries or industries. Thirdly, ongoing political and economic changes impacted the adoption and use of digital platforms within the study period. Finally, the chosen research methods also presented methodological limitations. These limitations combined may affect the generalizability of our findings to all developing economies and restrict our interpretations of the role of digital platforms in economic development and sustainability.

Building on these insights, several avenues for future research present themselves. Expanding the scope of investigation to encompass a broader range of developing economies and diverse industries would enhance the generalizability of the findings. Longitudinal studies could provide deeper insights into the evolving impact of digital platforms on economic development and sustainability. Further exploration into the socio-cultural nuances and their influence on digital platform adoption can shed light on the underlying mechanisms driving this phenomenon. Additionally, integrating quantitative data with qualitative insights would enrich our understanding of the multifaceted relationship between digital platforms and sustainable economic growth. This approach would offer a more comprehensive view of how these platforms can be leveraged for transformative impacts in developing economies. These future studies, building upon our current research, should aim to address the identified gaps and explore the long-term effects and scalability of digital platforms’ contributions to sustainable development.