Analyzing the Causal Relationships Among Socioeconomic Factors Influencing Sustainable Energy Enterprises in India

Abstract

Sustainable energy entrepreneurs promote sustainable development by focusing more on energy efficiency. This study examines the interdependence and driving–dependent relationships among the socioeconomic factors (SEFs) influencing sustainable energy enterprises (SEEs). A mixed-methods approach is used, beginning with a literature review and expert consensus, followed by total interpretive structural modeling (TISM) and cross-impact matrix multiplication applied to classification (MICMAC) analysis. Seven key SEFs are finalized through interviews with 12 experts. Data are then collected from 11 SEEs. The study reveals that the regulatory and institutional framework emerges as the primary driving factor influencing other SEFs, including financial accessibility, market demand, technological innovation, and infrastructure readiness. Social and cultural acceptance is identified as the most dependent factor. The study proposes future research directions by identifying the United Nations sustainable development goals (SDGs) related to the antecedents, decisions, and outcomes with theoretical linkages through the Antecedents–Decisions–Outcomes (ADO) framework. The major SDGs identified are SDG 4 (education), SDG 7 (energy), SDG 9 (industry), SDG 11 (communities), and SDG 13 (climate). The study highlights that regulatory support, funding access, skill development, and technology transfer are required areas for strategic focus. Understanding the hierarchy of SEs supports business model innovation, investment planning, and risk management.

1. Introduction

The emphasis on sustainable energy aligns closely with the Paris Agreement’s goals and climate change mitigation [1,2,3,4]. Entrepreneurship significantly contributes through innovation, technology, and economic viability [5,6], driving emission reduction, energy access, and sustainable development [7]. Sustainable energy enterprises (SEEs) address global energy issues via the use of clean technologies and viable business models [8,9,10,11]. This shift toward SEE is fueled by climate change, fossil fuel depletion, and energy security concerns [12]. Nonetheless, energy poverty persists; as of 2022, 775 million people—primarily in sub-Saharan Africa—remain without electricity, obstructing sustainable development [13]. Addressing this requires research into inclusive, scalable energy entrepreneurship models. Energy and environmental efficiency are vital for sustainable development and climate mitigation [14]. Countries are revising regulations to meet sustainability targets and manage emissions [15]. Resource depletion, geopolitical tensions, and energy poverty accelerate sustainable energy solutions [16], differentiating sustainable energy enterprises by integrating social, economic, and environmental sustainability perspectives [17].

Energy-efficient entrepreneurs actively seek opportunities to increase energy efficiency through reduced energy consumption, thus supporting sustainable economic development [18]. Energy efficiency, defined as the ratio of useful outputs to energy inputs [19], is essential for achieving energy sustainability. Government involvement significantly promotes energy efficiency [20]. For example, China’s increased governmental investment, totaling USD 131.4 billion since 2017, marking a 32% rise, has bolstered its sustainable energy framework [21]. Conversely, Pakistan struggles due to inadequate policy support, which negatively impacts renewable energy entrepreneurship and technical, socioeconomic, and political factors [22]. India has established itself as a renewable energy leader, achieving 175 GW of installed capacity by 2022 [23]. Institutional entrepreneurship significantly contributes to the energy sector through environmental scanning, strategic planning, and tactical implementation [24]. An examination of socioeconomic factors, along with the social and economic conditions of entrepreneurship, will help establish and run their ventures effectively [25].

The literature highlights the role of entrepreneurship in renewable energy development by stressing infrastructure, policy, research, and development [9]. However, a research gap remains concerning innovation and entrepreneurial exploration [26]. Fiscal support for decentralized energy adoption is also crucial [27], along with effective market and infrastructure management [6]. Small and microenterprises struggle to survive in the competitive landscape because of disruption, uncertainties, and market demand. They are rethinking their perception of sustainability [28]. Environmental regulations significantly influence entrepreneurial outcomes, resulting in an inverted U-shaped relationship [12]. Furthermore, technological innovations, collaboration, and behavioral economics inform entrepreneurial decision-making in sustainable energy transitions [29,30,31].

This study is driven by the rising global demand for sustainable energy innovations and their critical role in advancing cleaner energy systems. Within this landscape, India emerges as a particularly compelling context, with a rapidly evolving entrepreneurial ecosystem likened metaphorically to an elephant—steady, powerful, and accelerating. India is the country which has made the greatest contribution to sustainable entrepreneurship research [32]. This research specifically examines SEEs in India, highlighting a novel contextual perspective. Government initiatives fostering entrepreneurship have created a favorable environment supported by policy measures encouraging energy-sector innovation [33]. Globally, India ranks fourth in terms of wind power capacity, generating 40% of its total energy from renewable sources [34]. Its ability to achieve 500 GW renewable capacity by 2030, as set out at COP26, further cements its role in the global energy transition, as recognized by the Renewable Energy Policy Network for the 21st Century (REN21) [35,36]. While the literature highlights the roles of market dynamics, policy support, incentives, environmental decisions, and technologies, research examining social and economic influences on SEEs is lacking. The supportive environment for entrepreneurs in India through incentives, funding, mentorship, and institutions such as the start-up mission encourages entrepreneurs [33]. Therefore, this study explores the causal relationships and interdependencies among seven socioeconomic factors identified through the literature and validated via expert interviews and quantitatively analyzes them via total interpretive structural modeling (TISM) and cross-impact matrix multiplication applied to classification (MICMAC), addressing this critical research gap. Consequently, this study proposes the following research objectives for further analysis:

1.

To identify and examine the interdependence among the socioeconomic factors influencing sustainable energy enterprises;

2.

To examine the driving power and dependence among the socioeconomic factors influencing sustainable energy enterprises.

This research distinguishes itself from existing studies by adopting a socioeconomic lens through which to examine SEEs, moving beyond the predominant focus on technological and policy dimensions. A key methodological contribution is the use of a mixed-methods approach, beginning with the qualitative identification of factors from the literature and expert validation, followed by quantitative analysis via TISM and MICMAC. This integrated design addresses the limitations of purely qualitative or quantitative methods and effectively explores factor interrelationships and hierarchical structures [37]. Additionally, the study employs the ADO (antecedents–decisions–outcomes) framework to analyze SEE dynamics, where antecedents represent drivers, decisions capture strategic choices, and outcomes reflect their consequences [38]. This structured approach enhances coherence and supports targeted decision-making for policymakers, entrepreneurs, and investors.

The study contributes to the literature by addressing a notable gap, advancing understanding through a mixed-methods design, and offering practical guidance. Identifying the hierarchical positioning of SEE factors enables practitioners to implement targeted strategies such as capacity-building programs. For policymakers, the findings inform the creation of enabling environments through incentives, subsidies, and regulatory support. Strengthening the entrepreneurship ecosystem, especially for sustainable energy startups, plays a critical role in advancing energy transitions aligned with the United Nations Sustainable Development Goals (SDGs) [39,40].

2. Literature Review

The urgency of transitioning toward integrated renewable energy systems is driven by climate action, technological advancements, and business model innovation [16]. Decentralized renewable technologies have emerged, supported by political frameworks and incentives [27], with entrepreneurship vital to technology adoption [9]. Social enterprises significantly influence inclusive energy transitions across geopolitical contexts; Solar Sister and wPOWER initiatives exemplify the empowerment of women entrepreneurs to scale renewable energy access [10]. Current research emphasizes stakeholder collaboration, business innovation, consumer behaviors, and policies as key enablers of sustainable energy entrepreneurship (SEE), aligning renewable energy with financial viability and environmental goals [41,42,43]. Technological innovation in China further demonstrates how entrepreneurial factors—such as market readiness, infrastructure, and government support—significantly shape sustainable energy transitions globally [5,6,44].

The dependence on fossil fuels impedes climate mitigation targets [45]. Unlike hydroelectric and nuclear facilities, which are typically governed by the state, renewable energy initiatives often involve multinational corporations and small-to-medium enterprises, diversifying market competition [18]. Strengthening domestic manufacturing capabilities, particularly in the wind and solar sectors, could further reduce monopolistic tendencies and bolster long-term sustainability in energy entrepreneurship [23]. Educational initiatives such as the BOTSA program, developed by Eindhoven University in partnership with Dutch energy enterprises, foster sustainable entrepreneurship among students, thus promoting energy innovation and business skill development [11].

The systematic literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for document selection to identify the most relevant research works from the Scopus and Web of Science databases, following a filtering process in terms of inclusion and exclusion criteria. The 38 selected studies were identified in the context of sustainable energy enterprises and from a socioeconomic perspective. The initial identification of the factors was performed by examining these studies and identifying the SEFs from the studies. After the literature review, expert validation through preliminary interviews with 12 domain experts, including energy consultants, auditors, entrepreneurs, and academicians with experience ranging from one to thirty-six years, was conducted. After incorporating a contextual understanding and the refinement of the different factors from identification through a literature review, which was checked for practical relevance and again checked with the literature for confirmation, we obtained seven SEFs, listed below Section 2.1, Section 2.1, Section 2.2, Section 2.3, Section 2.4,Section 2.5,Section 2.6 and Section 2.7. We have identified the following socioeconomic factors influencing innovation in sustainable energy entrepreneurship:

2.1. Regulatory Policies and Institutional Support (RP&IS)

The effectiveness of SEEs is influenced by the supportive policy framework and supportive measures such as incentives, subsidies, tax deductions, and government-sponsored programs [20,22,46]. Strong institutional support ensures that sustainable energy enterprises operate in a positive regulatory framework with less financial risk and a favorable investment climate [47]. The supportive policy climate for sustainable energy transitions and innovations ensures the long-term sustainability of ventures and attracts investors to play a significant socioeconomic role [43].

2.2. Financial Accessibility and Investment Climate (FA&IC)

Financial accessibility and investment are essential for the success and stability of SEEs [22,43,47]. Investment in these ventures requires financial support and venture capital assistance, as well as government incentives and grants [25]. Investment in sustainable energy solutions is highly risky [42]. The accessibility of financing determines the viability of clean energy entrepreneurship and has become an important socioeconomic factor [46].

2.3. Market Demand, Consumer Awareness, and Adoption (MDCA&A)

The awareness and readiness of customers influence the growth of SEEs [42,46]. The market demand, perception, and behavioral indicators determine the adoption of sustainable energy innovation. Therefore, market-based policies, awareness programs, etc., increase market demand and change customer perceptions [43]. The market demand also impacts the scalability of SEEs. Dependence on sustainable energy solutions is influenced by prosocial consumer behavior and depends on stakeholder opinions for adoption [48]. This is one of the socioeconomic factors influencing the adoption and development of sustainable innovation in SEEs.

2.4. Technological Advancements and Innovation Ecosystem (TA&IE)

Sustainable energy entrepreneurs encourage research and development, innovations, and technology commercialization [42,43,47]. Technological advancements have focused on energy storage, distribution, smart grid technology, integration mechanisms, etc., which are used to increase sustainable energy innovations and the reliability of solutions [42]. The innovation ecosystem is the collectiveness of different actors and dimensions, which involves strategies and decision-making [49]. Hence, collaboration and partnerships among academia, industry, institutions, etc., will advance sustainable energy innovations [46].

2.5. Resource Availability and Infrastructure Readiness (RA&IR)

The availability of raw materials, energy sources, distribution platforms, efficient transportation facilities, storage facilities, and supply chains is essential for sustainable energy enterprises [22,42]. In particular, challenges in infrastructure create issues such as grid capacity and transmission disruptions, increased costs, and inadequate strategies, which hinder the scalability of clean energy technology startups and innovation [43]. Proper resource viability, accessibility, and strong infrastructure support are essential socioeconomic factors for the efficient operation of SEEs.

2.6. Sociocultural Attitudes and Acceptance (SCA&A)

The increase in market demand reflects the acceptance of energy solutions by sustainable energy enterprises. Social acceptance and community engagement are essential for the implementation of energy solutions [43]. Cultural preferences and positive attitudes determine the preference for renewable energy technologies and increase their rate of adoption [47]. Community-driven energy projects usually have high success rates [46]. Hence, sustainable energy entrepreneurs should prioritize community-based solutions, which will lead to acceptance and, in turn, ensure long-term sustainability.

2.7. Human Capital, Skills, and Entrepreneurial Capacity (HCS&EC)

Entrepreneurial skills are essential for entrepreneurial success in the competitive world. A skilled workforce, specialists, and entrepreneurial capacity determine success. Skill enhancement training programs, the development of capacity initiatives, etc., are the major determinants of innovative solutions [46,47]. The educational institutions and the institutions that provide vocational training facilities are major players in enhancing the capacity and skills of the evolving, dynamic, sustainable energy landscape [43]. It enhances the innovations and complexity of SEEs [42].

3. Methods

3.1. Research Design

The study follows mixed-methods research comprising both quantitative and qualitative exploration to understand the interconnectedness, driving, and dependence of socioeconomic factors influencing sustainable energy enterprises. The flow of the methodological approaches is presented in Figure 1. The initial approach involved a systematic literature review of the literature to identify the SEFs influencing SEEs. For this purpose, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework was followed to identify suitable papers on SEEs. From those papers, we identified the seven major SEFs, followed by interviews with experts in this SEE field to confirm the identified factors. We then checked the literature and provided a working definition of each factor by combining the literature and expert insights. The actual data collection was then conducted with 11 entrepreneurs who met the inclusion and exclusion criteria through a structured questionnaire confirmed with expert opinions. The collected data were analyzed via quantitative methods, such as TISM and MICMAC. The following subsections discuss the framework adopted in each stage.

3.2. Identification of Factors

A systematic literature review was conducted to identify the SEFs influencing SSEs, guided by the PRISMA framework. The review followed five sequential stages: formulation of research questions, development of a search strategy, identification of relevant literature, screening and filtration, and final synthesis [50,51]. Adhering to the structure proposed by Moher et al. [52] enhances the credibility and rigor of the review process [53]. This systematic approach ensures transparency, consistency, and replicability, supporting best practices in literature synthesis [54,55]. Figure 2 illustrates the overall review process. Details of the identification, screening, and inclusion of documents are presented below in the figure.

3.2.1. Identification

The Scopus and Web of Science (WoS) databases were used for the data search. Comprehensive coverage, interdisciplinary research, and a reduction in the likelihood of missing core and high-quality publications are the major reasons for combining these two databases [56]. The use of more than one database ensures coverage as well as the comprehensive identification of the literature.

• Search period: No limit. The search was performed on 18 August 2024.
• Keywords: “sustainable energy enterprise*”; “sustainable energy entrepreneur*”; “sustainable energy enterprise*”; “sustainable energy business model*”; “sustainable energy startup*”; “sustainable energy innovation”.

The initial search revealed 54 documents from Scopus and 16 from Web of Science on the basis of the above search parameters.

3.2.2. Screening

The following inclusion and exclusion criteria were applied in this phase:

• Language: All these papers were published in the English language. Hence, no other criteria were followed.
• Document Types: The 54 publications from Scopus included articles (35), conference papers (8), notes (3), reviews (3), and book chapters (1). Likewise, in WoS, articles (11), review articles (3), and proceeding papers (2) were identified. To maintain high quality, only the articles and review papers were considered and included. Hence, 38 from Scopus and 14 from WoS were selected.
• Duplications: Six duplicate studies were found.

The final selected documents in this phase consisted of 46 papers.

3.2.3. Eligibility

The full-text papers that were accessed and the studies that met the scope of the eligibility criteria were included. A total of 38 full-text papers and studies were included.

3.2.4. Included

After applying all the inclusion and exclusion criteria, 38 papers were ultimately selected.

3.3. Preliminary Interview

After the factors were identified, we interviewed sustainable energy entrepreneurs, academicians, and energy auditors, who focused on energy efficiency and promoted sustainable practices, to validate and confirm the identified factors from expert opinions. This qualitative approach ensures reliability guides for further quantitative research. This method was adopted by Kharb et al. [37] to analyze the barriers to green financing in the economy to achieve environmental sustainability. In addition, this method was successfully adopted by Agarwal et al. [57], Sushil [58], and Agarwal et al. [59]. We identified 12 experts in this field and interviewed them. Their expertise in energy varies across different fields. The experts are mainly engaged in the areas of energy consultancy (energy efficiency is their major focus), including the general secretary of engineering associations related to energy, entrepreneurs who are founders, cofounders, and managing directors of ventures in sustainable energy, CEOs, academicians, senior research scientists, and senior energy associates. The details are presented in

Table 1. Details of the experts.

Sl. No	Designation	Total Years of Experience
E1	Senior Project Research Scientist–Energy	1 year, 1 month
E2	Senior Energy Consultant	8 years, 3 months
E3	General Secretary–Society of Energy Engineers and Managers	1 year, 2 months
E4	Principal Energy Consultant, Co-founder & Professor	3 years
E5	Accredited Energy Auditor	5 years, 5 months
E6	Accredited Energy Auditor	36 years, 4 months
E7	Founder	4 years, 2 months
E8	Senior Associate in Energy	7 years
E9	Engineer in Energy Systems	1 year, 10 months
E10	Founder & Professor	I year, 8 months
E11	CEO	12 years
E12	Certified Energy Auditor & Professor	5 years

.

This expert consensus helped to confirm the factors that are relevant and correct in the actual scenario. In terms of expert consensus, we limited our analysis to seven factors without duplication and renamed four of the factors. The preliminary interviews also helped to provide a working definition of the factors, with support from the literature.

3.4. Structured Interviews

After confirming the factors, a closed-ended questionnaire with 42 questions rated on a Likert scale (0–4, where “0” denotes very low and “4” very high influence) was developed. To assess the interdependence of factors, 11 energy entrepreneurs with expertise in socioeconomic factors influencing SEEs were identified through purposive sampling, followed by snowball sampling. The initial respondents identified via purposive sampling suggested further experts during the brainstorming sessions. Snowball sampling, which is commonly used for identifying eligible participants [60,61], was adopted to ensure that the respondents met specific inclusion and exclusion criteria (Figure 3). The interviews were conducted between September and December 2024, with respondents having expertise ranging from 1 to 36 years. Each session, conducted in person or online via Google Meet, lasted 45–60 min. The participants provided ratings and justifications of each factor’s influence. The sample size was limited to 11 respondents because of the repetition of the responses and the lack of possibilities for the identification of any further set of factor relationships after completing the interviews with 11 experts. This indicated that data saturation was achieved.

The study followed the analysis through TISM and MICMAC. These are multicriteria decision-making (MCDM) methods. MCDM is widely applied in energy research. For example, Brodny et al. [62] assessed energy security in terms of energy, economic, environmental, and social factors. Compared with other methods, this method requires a comparatively smaller sample size in quantitative research. There are already studies that have been conducted with a smaller sample size. Kaur et al. [63] conducted a study with seven experts to understand a team’s emotional intelligence. Dalvi-Esfahani et al. [64] examined barriers to green computing with 15 experts. Kharb et al. [37] relied on eight experts to explore barriers to obtaining green financing for attaining environmental sustainability. The respondents in this research have expertise in this phenomenon of interest, which also became the reason for this low sample size.

3.5. TISM Approach

TISM is applied to identify the relationships among the SEFs in the SEEs. TISM is widely used by different researchers in the energy sector [65,66,67]. Interpretive structural modeling (ISM) is a well-accepted method for identifying the connections between variables related to an issue through the lens of what, why, and how the components are related to clear expert opinions. TISM is an advancement of the ISM used to obtain a comprehensive understanding with a detailed interpretation of how the variables are related, which is helpful for model development [33]. What and how ISM covers model development is extended by the TISM through what, why, and how the relationship exists [58,68]. Another advantage of depending on TISM is the full interpretive structural modeling with consideration of the direct as well as transitive links. It helps in the interpretation of relationships in all path analyses [37]. A TISM-based hierarchical model is better for addressing the identified problem [69]. Figure 4 presents the whole process of TISM. The steps in the TISM are discussed below:

• Identification of the factors: The SEFs are identified through a systematic literature review and further validated based on experts’ views through preliminary interviews before the data collection is discussed in the literature review.
• Interconnectedness among the identified factors: The contextual relationships among the seven factors are established to obtain the initial reachability matrix (IRM). Eleven experts’ opinions are collected on the SEFs in the SEEs. The IRM is illustrated in

  Table 2. IRM for socioeconomic factors influencing energy entrepreneurship.

  	RP&IS	FA&IC	MDCA&A	TA&IE	RA&IR	SCA&A	HCS&EC
  RP&IS	1	1	1	1	1	1	1
  FA&IC	0	1	0	1	1	0	1
  MDCA&A	0	0	1	1	1	0	0
  TA&IE	0	0	0	1	0	1	0
  RA&IR	0	0	1	0	1	0	1
  SCA&A	0	0	0	0	0	1	0
  HCS&EC	0	0	0	1	0	0	1

  on the basis of the pair-based assessment by entering “1” (influencing) and “0” (not influencing).
• Interpretation of the relationships among factors: The answers to the question of how the factors are related are identified and presented through comprehensive interpretations. This is the phase where the major difference between the ISM and TISM is revealed. The interpretation of the influence of one factor on another promotes the understanding and basis for creating a conceptual model [37], e.g., how RP&IS influences FA&IC.
• Final reachability matrix (FRM) development after checking transitivity: The FRM is a matrix developed after the direct and transitivity links are considered. The transitivity check is the indirect relationship among the factors [70].

  Table 3. FRM for socioeconomic factors influencing energy entrepreneurship.

  	RP&IS	FA&IC	MDCA&A	TA&IE	RA&IR	SCA&A	HCS&EC
  RP&IS	1	1	1	1	1	1	1
  FA&IC	0	1	1 *	1	1	1 *	1
  MDCA&A	0	0	1	1	1	1 *	1 *
  TA&IE	0	0	0	1	0	1	0
  RA&IR	0	0	1	1 *	1	1 **	1
  SCA&A	0	0	0	0	0	1	0
  HCS&EC	0	0	0	1	0	1 *	1

  * represent transitive links; ** represents significant transitive links.

  contains the FRM. The transitivity is denoted with an asterisk [37]. For example, 1*. This means that if “X” influences “Y,” “Y” influences “Z,” then “X” also influences “Z.” Likewise, if the transitivity is 1**, “W” influences “X,” “X” influences “Y,” “Y” influences “Z,” and “W” influences “Z.”
• Partitioning of the factors from the FRM into levels: The partition reachability matrix (PRM) was developed from the FRM [71].
• Designing the interaction matrix: The interaction matrix is prepared after the direct and transitivity links are considered [37].

  Table 4. Interaction matrix.

  	RP&IS	FA&IC	MDCA&A	TA&IE	RA&IR	SCA&A	HCS&EC
  RP&IS	1	1	1	1	1	1	1
  FA&IC	0	1	1 *	1	1	1 *	1
  MDCA&A	0	0	1	1	1	1 *	1 *
  TA&IE	0	0	0	1	0	1	0
  RA&IR	0	0	1	1 *	1	1 **	1
  SCA&A	0	0	0	0	0	1	0
  HCS&EC	0	0	0	1	0	1 *	1

  * represents transitive links; ** represents significant transitive links.

  presents the interaction matrix.
• Creating the digraph and the TISM model: All the relationships are portrayed in the directed graph or digraph (Figure 5) designed from the PRM and the interaction matrix [72]. The relationships among the factors are presented in the diagram at different levels. The top of the model is the first-level factor, and then the remaining levels are ranked in ascending order. The digraph nodes and links present the relationships. The arrows connecting the factors represent the relationship directions among the factors.

3.6. MICMAC Analysis

MICMAC is used to find the driving and dependent SEFs influencing SEEs. Along with TISM, MICMAC helps to understand the independent and dependent factors suitable for decision-making [73]. The interconnectedness can be understood from TISM. However, to understand this linkage, MICMAC is essential. The three major steps involved in this method are the identification of relevant factors, the identification of causal relationships among the factors, and the identification of essential factors. The reachability matrix is used to create the diagram, which shows the driving power–dependence diagram, revealing the classification of factors into zones [37].

Table 5. MICMAC ranks of the socioeconomic factors influencing energy entrepreneurship.

Factor	Driving Power	Dependence	Driving Power/Dependence	MICMAC Rank
RP&IS	7	1	7.000	1
FA&IC	6	2	3.000	2
MDCA&A	5	4	1.250	3
TA&IE	2	6	0.333	5
RA&IR	5	4	1.250	3
SCA&A	1	7	0.143	6
HCS&EC	3	5	0.600	4

and Figure 6 show the driving power and dependence of the factors. The division of factors on the basis of the driving power/dependence in the system offers managerial implications and strategy development [73]. The x-axis represents the driving, and the y-axis represents the dependence. MICMAC is used because of its significant advantage over other methods, such as ISM, in terms of a lower chance of error in the classification of factors in quadrants, versatility, and the ability to be applied in the case of problems related to decision-making [73]. The classification of the factors into zones/quadrants is as follows:

• Zone/Quadrant I: Autonomous factor: This factor falls within the zone containing weak dependence and driving power [74,75].
• Zone/Quadrant II: Dependent factors: This zone represents factors that have high dependence and less driving power [74]. In simple terms, the factors that are non-independent and depend on others but do not create change or influence the rest of the factors are called dependent factors. The ideal characteristics of the factors that fall in this zone are factors that depend on others and do not create changes in the other factors.
• Zone/Quadrant III: Linkage factors: Factors with high driving power and dependence fall in this zone [76]. They are focused mainly on developing links with driving and dependent factors.
• Zone/Quadrant IV: Driving or independent factors: This is the opposite of Zone 1. The factors that highlight driving but are less dependent on other factors are associated with this zone [77].

4. Results

The results of TISM are presented in Table 2, Table 3 and Table 4.

4.1. Interpretation of the TISM Digraph

Figure 5 represents the graphical representation of the TISM analysis of the socioeconomic factors influencing SEEs through six paths or levels.

Level VI: Level six has one factor, which is factor 1.

• RP&IS influencing FA&IC: Regulatory policies and institutional frameworks influence financial accessibility and investment in SEEs because the government and institutions provide financial support, subsidies, and benefits in the form of taxes and incentives and attract investors to invest in ventures. These policies primarily help reduce investment risk and fund accessibility to early SSEs and establish existing SSEs for their scalability. The current focus on the increasing support of the government for renewable energy ventures also encourages banks and financial institutions to support or provide seed and angel funds to SEEs. This phenomenon was examined by Musah et al. [78] in the case where feed-in tariffs help increase investment. The Indian government introduced the following schemes for supporting sustainable energy entrepreneurs: the Production Linked Incentive Scheme, the Solar Park Scheme, the Viability Gap Funding Scheme, and the National Hydrogen Mission.
• RP&IS influencing MDCA&A: Well-structured, clear policies on energy transition, reporting, and green and sustainable energy are mandated, and Renewable Portfolio Standards (RPS) increase the demand for clean energy in the market. The next important element is increasing the awareness of customers, especially the net-zero energy rates for sustainability. The subsidies offered by the government for the installation of solar panels and support for energy auditors enhance consumers’ adoption of sustainable energy solutions. Supportive policy frameworks encourage the adoption of sustainable energy solutions by the public, increasing market demand [79].
• RP&IS influencing TA&IE: Supportive policies for research and development, innovation encouragement, and technology development increase sustainable energy transitions. The government supports R&D grants and collaboration among universities and industries for energy technology advancements, patents, and other intellectual property-supportive actions to increase the development of innovations. The “Ministry of New and Renewable Energy” introduced the “Research and Technology Development Program” to support R&D in the new and renewable energy sector with the aim of sustainable energy transition. The nations that have innovation support will develop new and sustainable energy technologies. Germany’s Energiewende policy is an example of this [11].
• RP&IS influencing RA&IR: Energy storage is one of the major issues faced in the sustainable energy sector. The availability of infrastructure and resources is dependent on the supportive policy environment. Energy policies that cover restrictions on land usage, grid accessibility, etc., influence the operations of SEEs. The feasibility is determined on the basis of energy policies. The proper regulation of land consumption encourages the development of wind and solar farms by enterprises. Grid integration aimed at energy strength leads to better infrastructure development, and investment in the grid increases energy efficiency. Investment in smart grids encourages the development of SEEs.
• RP&IS influencing SCA&A: Policy plays a major role in the development of social attitudes. Decentralized energy solutions through community solar initiatives increase community engagement. This also opens the door for SEEs. Policy assistance in community-based energy investment through subsidies and national policies encourages the acceptance of sustainable energy. Germany’s strong pro-renewable stance vs. that of fossil-fuel-reliant economies is the best example of this. This creates the demand for SEEs to focus on communities and develop sustainable energy solutions across communities to increase acceptance.
• RP&IS influencing HCS&EC: Educational institution initiatives, training, and development programs encourage awareness of and demand for sustainable energy solutions. The policy support for incubation through institutions, including educational institutions and pitching and startup assistance, has encouraged more entrepreneurs to join sustainable energy initiatives. The establishment and scalability of the product support an important driver for sustainable energy change. The development of training programs and workshops by the government and institutions creates responsible and developing skills, identifying and increasing the capacity of entrepreneurs.

Level V: Level five has one factor, which is factor 2.

• FA&IC influencing MDCA&A: Access to finance and a favorable investment climate help sustainable energy entrepreneurs innovate new solutions that meet customer requirements and cover triple-bottom-line lenses. Innovative solutions with novelty increase demand in the market, and increasing customer awareness and adoption leads to customer satisfaction. Affordable financing options also increase accessibility, and marketing can be enhanced to reach a wider market with strong economic backing. SSEs provide microfinancing options, subsidized loans for energy-efficient appliances, and solar panels that make sustainable energy affordable for customers. Investment in green bonds also reduces the high costs. The feed-in tariffs in Europe and renewable energy credits increase the rate of adoption of solar and wind energy.
• FA&IC influences TA&IE: Finance and investment also promote research and development (R&D), technological development, and development in the overall ecosystem. Well-equipped financial infrastructure is a pathway to sustainable energy research and innovations. Investors such as venture capitalists and angel investors support sustainable energy startups, and government R&D funds for battery storage advancement, solar, wind, and additional financial assistance for scaling activities in the growth stage address how financing in the form of capital and investment creates cutting-edge innovations. Germany and the U.S. have increased their innovations, which are technology-oriented in terms of smart grid advancements, storage facilities, and hydrogen energy [11].
• FA&IC influencing RA&IR: Infrastructure development and the accessibility of resources depend on finance and investment. Capital investment is required for SEEs in innovation in terms of grid technologies and integration, the development of energy storage systems, and large-scale installations. Government support for smart grids, electric vehicle charging points, and decentralized systems of energy is influenced by the financial and investment climate. The increase in financial investment leads to the accessibility of resources and the development of innovations. Investment with financial incentives in energy infrastructure creates portions of the total energy mix, which can be seen in the context of Chinese infrastructure initiatives [11].
• FA&IC influences HCS&EC: The development of human capacity, skills, and entrepreneurial skills is based on the element of finances. The dynamic energy sector needs skilled, sustainable energy entrepreneurs to develop innovations. Finance and investment encourage training, the development of the workforce, and the enhancement of the overall capacity of entry entrepreneurs, attracting institutions and investors for scalable investments. Adequate financing and investment in SEEs promote development initiatives and research and development activities, which increase innovative solutions and demand in the market. Denmark and the Netherlands are the countries that are investing more in developing the workforce and enhancing the entrepreneurship capacity in renewable sources of energy and loans for innovations [79].

Level IV: Level four has two factors: factor 3 and factor 5.

• MDCA&A influences TA&IE: The demand for sustainable energy increases SEE investment in R&D to improve existing products, promote innovation, and increase energy efficiency in energy technologies. The increase in customers’ awareness of climate change issues, the need to depend on renewable energy sources, and the importance of energy efficiency increase SEE innovations to enable enterprises to survive in competitive markets. The innovation ecosystem consists of major players such as investors’ and entrepreneurs’ partnerships, and research on new solutions has focused mainly on capturing the demand in the market. The demand for solar panels has increased, and technology development and cost-efficient, innovative battery technologies are the result of this increasing demand. It also requires infrastructure, such as storage systems, to store energy to meet demand during nonpeak times.
• MDCA&A influences RA&IR: Market demand and consumer preference toward sustainable energy sources lead to the need for resources in the form of humans, machines, finance, entrepreneurial skills, and infrastructure support to develop innovative, consumer-demanded, cost-effective energy solutions. Energy efficiency distribution systems and the availability of customer services, such as charging stations and battery technologies, should be developed on the basis of market demand. The demand for solar energy increases grid system development, and energy storage and distribution networks are enhanced through the high demand for green energy. The demand for more decentralized energy systems also increases infrastructure readiness and resource requirements. The best example is the modernization of infrastructure and investment in infrastructure enhancement in Germany and China due to the large-scale addition of wind and solar energy [79].
• MDCA&A influences HCS&EC: Demand in the market develops skills, entrepreneurial capacity through training, a well-trained and skilled workforce, and the development of human skills in a full-fledged manner to develop innovations. The market expansion for SEEs also opens the door to creating employment opportunities and, at the same time, increasing the skills of the existing workforce. These skills are related primarily to technology development, expansion, maintenance, installation, etc. Training programs and educational programs to increase innovations in renewable or sustainable energy technologies can be used to enrich the skilled workforce and increase the current capacity.
• RA&IR influencing MDCA&A: SEEs with good infrastructure and resources that are capable of innovation and optimizing at maximum efficiency increase positive customer perceptions of their solutions. EV charging stations and smart grids facilitate adoption, and proper energy storage systems lead to the wider adoption of solutions by customers and increasing demand in the market. Accessibility and expanded charging networks increase electric vehicle adoption. The best example is electric vehicle charging in Norway, revealing that infrastructure development leads to increased market demand [11].
• RA&IR influencing TA&IE: Technological development and R&D activities rely on supportive infrastructure and available resources. The infrastructure includes storage system platforms for pilot projects, test beds, and simulated experiences with real-world application of sustainable energy technologies, called test marketing before market entry, to check the feasibility of sustainable energy technologies. Smart grid systems and storage solutions help in the testing of renewable energy solutions such as wind, solar, and bioenergy in technology development. The infrastructure also reduces costs, which helps early-stage startups reduce their costs for technology development and the overall costs in the innovation ecosystem. The developed infrastructure support in California enhances innovations in batteries and grids [78].
• RA&IR influencing HCS&EC: The infrastructure and resources are ready, and SEEs can focus on developing human skills, capacity, and development through training and development initiatives for the workforce in sustainable energy innovations. Skill development programs with existing infrastructure for offering training to the workforce in grid management, enhancing battery storage systems, and innovations for capturing the market from competitors are needed. The testing of solutions at a large scale is only possible for startups with supportive infrastructure and the availability of resources. A well-trained workforce with entrepreneurial capacity and the resources and infrastructure developed by startups and enterprises attract investors and lead to game changers in the market through innovations in sustainable energy solutions.

Level III: Level three has one factor, which is factor 7.

• HCS&EC influences TA&IE: The required skilled workforce and entrepreneurship with high-level capacity can lead to the development of existing energy technologies and the development of innovative new technologies. The entrepreneurship ecosystem consists of different actors. Human capital and a skilled and trained workforce, driven by sustainable innovation in energy, ensure the long-term sustainability of SEEs. This will contribute to the innovation, adoption, and development of technopoles. Human capital, skills, and entrepreneurship capacity are essential for ventures in the energy sector because of the continuous innovation and adaptation in terms of technical expertise, leading innovation hubs, and perpetual R&D culture. A skilled workforce and the capacity of entrepreneurs create pathways for development. Germany and the USA have innovations in technology in the energy sector. Similarly, Silicon Valley Cleantech is another example of a startup ecosystem-driven pool of talent and entrepreneurial capacity [78].

Level II: Level two has one factor, which is factor 4.

• TA&IE influences SCA&A: Social and cultural acceptance is influenced by the wide adoption of sustainable energy technologies. Accessible, affordable, efficient, and cost-friendly energy technologies help with community and social acceptance. Innovative technologies such as smart grids, solar solutions, and electric vehicles are desirable and accepted sustainable energy solutions. The customer’s awareness of advanced technologies and the innovation ecosystem for demand-based solutions encourage the customer’s trust and confidence. The development of grid technology reduces renewable intermittency, increases recognition, and promotes a positive societal attitude. Sustainable energy has become the norm rather than just an alternative to nonrenewable sources. The best example of this is the adoption of solar panels in rural India to increase social acceptance of cost-effective energy solutions [79].

Level I: Level one has one factor, which is factor 6.

Social and cultural acceptance (SCA&A) is related to the objective of this study. The most dependent SEFs are social and cultural attitudes and community engagement. The failure of most sustainable energy entrepreneurs is the lack of adequate demand-based, community-oriented innovations and development, creating hurdles to large-scale adoption. Positive social attitudes and preferences are determinants. The demand for sustainable energy entrepreneurs is increased through campaigns for sustainable energy by the government and nongovernmental organizations (NGOs). The focus on sustainability also creates a positive perception of sustainable energy solutions, and the efforts of SEEs in community wind farms and the participatory approach increase demand and society’s decision-making toward sustainable energy adoption. The Scandinavian countries focus on renewable energy and social norms on the basis of their impact on the community [11]. All other socioeconomic factors lead to positive social attitudes, cultural acceptance, and engagement in sustainable energy solutions, which are essential for the success of SEEs.

4.2. Interpretation Based on MICMAC

MICMAC analysis helps classify factors into four quadrants: driving, autonomous, dependent, and linkage factors. Table 5 and Figure 6 show the results of the classification of factors.

1.

Autonomous factors (Quadrant I): Here, no factors fall into this zone. This means that there is no factor with low dependence and low driving power.

2.

Dependent factors (Quadrant II): The factors with low driving power and high dependence on the other factors are HCS&EC, TA&IE, and SCA&A.

3.

Linkage factors (Quadrant III): This quadrant shows the factors that can drive other factors and are highly dependent on other factors. The results show that MDCA&A and RA&IR are linkage factors.

4.

Driving or independent factors (Quadrant IV): Factors that have high independent or driving power and less dependence or weaker levels depending on other SEFs belong to this quadrant. The results indicate that the two most independent factors are RP&IS and FA&IC. Hence, these two factors are the major driving factors.

In the MICMAC analysis, the SEFs influencing sustainable energy entrepreneurship are ranked, and the results are presented in the following table and figure.

The results show that RP&IS is ranked first. Socio-Cultural Attitudes and Acceptance (SCA&A) is ranked sixth in the MICMAC analysis ranking. This study provides insights for sustainable energy entrepreneurs, practitioners, and policymakers to increase the importance of flexible and supportive policies and institutional frameworks for enhancing SEE innovations and entrepreneurial activities that influence other factors. Likewise, social and cultural attitudes and acceptance are the result, and the pathway analysis discussed in this research shows that this is the outcome and depends on the remaining factors.

5. Discussion

The independence and hierarchical level of the relationships among the socioeconomic factors influencing SEEs through TISM and MICMAC analysis provide a more contextual understanding. From the six hierarchical levels of influence, the study identified the importance of regulatory policies and institutional support, and financial accessibility and investment are the critical influencing factors. This finding aligns with observations of the importance of policy frameworks in sustainable energy transitions [12]. This further builds on this finding from the enterprise perspective, which is accelerating sustainable energy innovation. The role of support from policymakers through incentives, subsidies, regulation, etc., is decisive in increasing sustainable entrepreneurial performance. This also confirms our findings from the expert’s perspective. However, the inverted U-shaped relationship between regulatory incentives and sustainable entrepreneurial outcomes identified by Peng and Pan [12] highlights the negative impact of regulations that may disrupt innovations. This research does not support this finding and adds to the existing findings on the importance of incentives for boosting entrepreneurship performance.

Financial development plays an important role in renewable energy technologies [6]. This finding also supports another important examination that identified the influence of financial accessibility as a socioeconomic enabler of other factors in SEEs. Political will and technological factors influence the effective energy system [27]. The market demands, infrastructure, and linkage factors contribute to the literature through the bidirectional influence of market demand, infrastructure, and resources as important socioeconomic factors for sustainable innovation in SEEs. Wang et al. [5] identified the importance of skills for successful green entrepreneurial and business model innovations. This research reveals that entrepreneurial skills, capacity, and technological advancement are dependent and not driving factors. This highlights the fact that technological and entrepreneurial innovations and progress depend on the regulations and policy frameworks of the financial state, and if there is a need to enhance these innovations, then only success will occur.

The key hurdle identified by Lu et al. [80] in the energy sector is the importance of corporate social responsibility (CSR). The present study emphasizes that the major linkage factor for the success of entrepreneurial innovation in the provision of sustainable energy solutions by enterprises is social and cultural acceptance. This also highlights the need for further research on incorporating the importance of parameters of governance and the institutional mechanisms for sustainable energy innovation. Low-carbon innovation technology positively impacts SEEs through political and market legitimacy. This study reveals that technological advancement is the dependent factor [44]. Renewable energy entrepreneurs’ development is influenced by regulatory and policy consistency and investment [9]. The results also highlight the importance of these two factors, which have high driving power, and indicate their importance in the success of SEEs. Public perception and workforce readiness are major factors for increasing the adoption rates of sustainable energy technologies and are relevant in the energy transition [29]. The identification of the importance of the indirect influence of skills, entrepreneurial capacity, and the dependent factors of social and cultural acceptance becomes a determinant of the long-term sustainability of SEEs and is significant in the energy transition.

This study has several limitations. The small sample size and the use of TISM and MICMAC may not fully capture all SEFs or account for nonlinear relationships. The TISM and MICMAC methods are qualitative–structural–expert interpretation methods used to understand the structural relationships among factors and are helpful for theory-building and decision-making [81]. Reliance on expert opinions may lead to personal bias, perception variability, and interpretive subjectivity, which may influence the hierarchy and causal relationships identified. Future research possibilities include incorporating statistical techniques such as structural equation modeling (SEM) or regression analysis using quantitative survey data to empirically validate the conceptual model and test hypotheses through quantitative validation, eliminating biases to enhance the in-depth model and analysis and generalizability. Respondents’ perceptions may change over time, suggesting the need for longitudinal studies. The study focuses solely on the Indian context, limiting its geographical generalizability. It also excludes cognitive and psychological factors relevant to SEE risk assessment. Hence, in future research, studies with larger sample sizes and incorporating data triangulation, such as the integration of survey data, case studies, or secondary data sources, could be conducted to increase the breadth and validation of the findings. In addition, future research with a comparative study lens involving other developing economies (e.g., Brazil, South Africa, or Indonesia) is good and will reveal cross-cultural and policy views. This will improve geographical generalizability and help understand how socioeconomic factors might differ across different contexts in light of the regulatory environment, entrepreneurial ecosystem, and cultural attitudes toward sustainable energy, which can vary widely across countries.

6. Implications

6.1. Implications for Energy Entrepreneurship Theory

This study contributes to energy entrepreneurship theory by highlighting the importance of external, systemic SEFs in sustainable energy entrepreneurial activities. The literature has focused largely on firm-based, resource-based, and opportunity recognition-related examinations. Our findings show that socioeconomic structures comprising regulatory frameworks, financial accessibility, and infrastructure readiness play a foundational role. Total Interpretive Structural Modeling (TISM) and MICMAC provide a systems-theoretic perspective linked with institutional theory, which covers the influence of formal and informal institutions on entrepreneurial behavior.

By applying the ADO (antecedents–decisions–outcomes) framework, the study further links structural drivers to entrepreneurial choices and their outcomes, contributing to process-based views of entrepreneurship. The identification of social and cultural acceptance as a highly dependent factor, revealing the relevance of legitimacy theory, suggests that successful SEE also depends on societal alignment and acceptance. Thus, this research offers a holistic view of energy entrepreneurship, integrating structural, institutional, and behavioral dimensions.

This study contributes to the sustainable energy entrepreneurship literature by employing TISM and MICMAC analyses to examine socioeconomic factors. Its first major contribution lies in its innovative mixed-methodology approach, which integrates qualitative and quantitative techniques within the ADO framework. This research fills a critical literature gap by systematically analyzing the interdependencies among the socioeconomic factors influencing SEEs. By highlighting how policy frameworks and institutional support affect market demand, financial accessibility, and infrastructure, this study reveals hierarchical relationships among these factors. The categorization of socioeconomic elements into dependent, linkage, and driving quadrants provides a foundation for deeper theoretical discourse on their significance and roles within the sustainable energy entrepreneurship context.

6.2. Implications for Policymakers, Practitioners, and Entrepreneurs

The findings offer actionable insights and recommendations for policymakers, practitioners, and entrepreneurs in sustainable energy. Recognizing regulatory policies and institutional support as influential driving factors underscores the need for transparent regulatory frameworks and incentivized funding environments conducive to entrepreneurial innovation. Policymakers should prioritize infrastructure development, financial accessibility, and targeted programs that specifically encourage sustainable energy ventures. The study also emphasizes the importance of strengthening financial institutions, governmental collaboration, and venture capital support to enhance investment capacity and financial solutions. Furthermore, capacity-building training emerges as a critical dependent factor, suggesting the need for collaboration among institutions to provide specialized entrepreneurial training and workforce skill development. The promotion of technology transfer, research, and knowledge-sharing platforms by governments further supports technological advancement. Ultimately, these insights guide strategic decision-making, enabling sustainable energy entrepreneurs to effectively prioritize socioeconomic factors, innovate business models, scale operations, and manage risks within the dynamic sustainable energy sector.

7. Future Directions Using the ADO Framework

The ADO framework proposed by Paul and Benito [82] offers a structured and organized way to summarize existing findings while also addressing forward-looking questions in the assembly of relationships [38]. In this model, antecedents refer to the key drivers of behavior, decisions capture the type or structure of constructs, and outcomes represent the consequences of those decisions [38,83,84]. These elements are interconnected, where antecedents shape decisions and decisions influence outcomes. This interlinkage is particularly important for understanding hierarchical factor relationships and influencing pathways. The framework has been widely applied in energy-related research. For example, Aggarwal et al. [85] used it to examine environmental, social, and governance investment patterns. In the current study, the results from TISM serve to identify the antecedents, whereas MICMAC analysis categorizes the decisions on the basis of their driving and dependence (

Table 6. The ADO framework as applied to sustainable energy enterprises.

Component	Key Elements	Related SDGs
Antecedents (A)	Regulatory policies and institutional support Financial accessibility and investment Market demand Infrastructure readiness Technological advancements Skill development and human capital Social and cultural acceptance
Decisions (D)	Policy and investment strategies Infrastructure and technology planning Skills and education alignment Community engagement and awareness initiatives
Outcomes (O)	Improved investment climate Technological innovation and efficiency Expanded energy access and equity Social acceptance and sustainability adoption

). Integrating the ADO model into this analysis not only strengthens the theoretical foundation but also aligns the findings with sustainable development pathways, particularly those contributing to United Nations SDGs such as SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), and SDG 13 (Climate Action) [86,87].

7.1. Antecedents (Drivers)

Regulatory policies and institutional support are identified as core drivers that influence a wide range of socioeconomic factors, including financial accessibility and investment climate (F2), market demand (F3), technological advancements (F4), infrastructure readiness (F5), social and cultural acceptance (F6), and skill development (F7). Prior research underscores the foundational role of public policy in shaping the renewable energy landscape. Studies by Aldieri et al. [88], Hájek and Stejskal [89], and Kassouri et al. [46] emphasize that the absence of adequate research infrastructure, technology support, and investor incentives can significantly hinder innovation in clean energy. As Musah et al. [78] noted, public investment in sustainable technologies and funding mechanisms is vital not only for accelerating adoption but also for contributing to broader environmental goals, particularly those aligned with SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action).

Financial accessibility and investment also serve as critical enablers for downstream factors such as market demand, technology development, infrastructure expansion, and human capital formation. The availability of financial resources directly affects the scale, speed, and sustainability of renewable energy deployment [42,79]. Badi and Pryke [90] highlighted that financial partnerships and funding models often determine the success of energy ventures, whereas Smink et al. [91] noted that institutional barriers to financing remain a key obstacle. Addressing these challenges through public and private sector collaboration can support innovation ecosystems, thereby advancing SDG 9 (Industry, Innovation, and Infrastructure).

Market demand exerts a cascading influence on infrastructure development, technology adoption, and skill formation. As Reijonen et al. [92] argue, innovation driven by market needs has the potential to accelerate the integration of emerging technologies. Similarly, resource accessibility and infrastructure readiness are critical to sustainable energy innovation. [27] and Lu et al. [80] highlight infrastructure as a foundational pillar in supporting both the deployment and operational efficiency of energy systems—key concerns addressed by SDG 11 (Sustainable Cities and Communities).

Skill development and entrepreneurial capacity are equally important drivers. As Wijnker et al. [11] suggested, workforce expertise and entrepreneurial insight are crucial to driving innovation in renewable energy enterprises. This aligns with SDG 4 (Quality Education) and SDG 8 (Decent Work and Economic Growth), as investments in education and vocational training strengthen the human capital necessary for a green transition. In turn, sustained technological advancement is expected to enhance societal acceptance and adoption of clean energy solutions. These innovations collectively support long-term energy efficiency, resilience, and climate sustainability [43,44], reinforcing the global agenda for inclusive, just, and climate-resilient energy systems.

Research questions:

• How do regulatory policies and institutional frameworks influence the formation and evolution of sustainable energy enterprises in emerging economies?
• In what ways do financial accessibility and investment mechanisms drive technological advancement and infrastructure development in the context of sustainable energy transitions?

7.2. Decisions (Strategic Choices)

The driving influence of government policy and institutional support shapes strategic decisions in sustainable energy enterprises. The state’s role in the energy transition involves setting renewable energy targets, implementing carbon taxation policies, and offering economic assistance to stimulate clean energy adoption [80,93]. These policy decisions are operationalized through various financial instruments, such as grants, loans, subsidies, and tax incentives, encouraging both public and private sector investment in clean energy solutions [91].

Infrastructure-related decisions include the expansion of energy grids, deployment of smart meters, and modernization of energy distribution systems in alignment with broader infrastructure development plans [27]. Technological development, supported by robust research and development (R&D) investments, must prioritize energy storage, improved energy efficiency, and the integration of smart grid solutions on a scalable basis [43]. These decisions are pivotal for advancing SDG 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities), ensuring more resilient and adaptable energy systems. Another strategic choice lies in strengthening human capital. Educational institutions and vocational training programs should partner with industry and government stakeholders to enhance workforce capabilities and entrepreneurial readiness [11]. This aligns with SDG 4 (Quality Education) and SDG 8 (Decent Work and Economic Growth), as it fosters skill development tailored to the evolving energy sector.

A further decision point is tied to the factor of social and cultural acceptance, which is identified as highly dependent. Promoting sustainable energy adoption requires targeted awareness programs, behavioral campaigns, and incentive-driven participation. Community-based energy initiatives, in particular, have proven effective in enhancing public engagement and increasing the rate of technology adoption [94,95]. These efforts contribute to inclusive and participatory models of energy governance, reinforcing long-term sustainability and just transitions. Together, these decisions serve as crucial links between systemic drivers and measurable outcomes, forming the strategic core of enterprise-level actions that enable progress toward sustainable energy futures.

Research questions:

• How do government-led investments and policy incentives shape the strategic decisions of sustainable energy enterprises in adopting advanced technologies and infrastructure?
• In what ways do collaboration between educational institutions and energy enterprises influence workforce development and entrepreneurial capacity in the renewable energy sector?

7.3. Outcomes (Effects of Decisions)

The outcomes of strategic decisions made by sustainable energy enterprises reflect the direct influence of driving factors such as regulatory policies, institutional support, financial access, and technological innovation. A key outcome highlighted in the study is the improvement of the investment climate, which is essential for fostering innovation and ensuring the long-term success of SEEs. To meet future energy and sustainability targets, investments in renewable energy must increase significantly [42,43]. These investments contribute to achieving SDG 7 (Affordable and Clean Energy) by enabling the wider adoption of clean energy technologies and supporting enterprise sustainability. The energy sub-target in SDG 7.1, which focuses on universal access to affordable, clean, reliable energy services for all, the sharing of renewable energy in the total energy mix enhancement in SDG sub-target 7.2, and the energy efficiency doubling mentioned in sub-target 7.3, are achieved directly by means of sustainable energy entrepreneurship [10].

Technological advancement emerges as another crucial outcome. Innovations such as AI-driven energy forecasting systems and the deployment of smart grid technologies enhance operational efficiency and optimize energy distribution [43]. These outcomes demonstrate the tangible benefits of integrating advanced digital tools into energy infrastructure planning, contributing to SDG 9 (Industry, Innovation, and Infrastructure) and SDG 13 (Climate Action).

Furthermore, the expansion and modernization of infrastructure, particularly in energy distribution networks, have a direct effect on improving access to sustainable energy [27]. This infrastructure development not only supports energy security but also plays a critical role in reducing inequalities in energy access, advancing SDG 10 (Reduced Inequality) and SDG 11 (Sustainable Cities and Communities).

Research questions:

• What are the measurable impacts of strategic investments in technology and infrastructure on the scalability and performance of sustainable energy enterprises?
• How do innovation-driven decisions contribute to improved energy access, social acceptance, and the achievement of long-term sustainability goals such as SDG 7 and SDG 13?

By structuring the analysis through the lens of antecedents, decisions, and outcomes, the study provides a clear and coherent understanding of how systemic enablers influence enterprise-level actions and their subsequent impact. The antecedents—regulatory support, financing mechanisms, and technological readiness—lead to decisions involving targeted investment, skill development, and innovation strategies. These decisions, in turn, result in measurable outcomes that inform practical actions for entrepreneurs, investors, and policymakers. Validating the study’s findings through this conceptual framework strengthens the internal consistency of the analysis and provides actionable insights for stakeholders aiming to build sustainable energy futures. This alignment ensures that enterprise-level strategies are not only locally relevant but also globally responsive to sustainability goals.

Despite growing attention being paid to sustainable energy, gender disparities persist in energy access, decision-making, and the adoption of clean technologies [96], particularly in rural Africa [13]. Initiatives such as Solar Sister address this gap by training women entrepreneurs to distribute solar products via a “business in a bag” model that combines technical, marketing, and financial support. Similarly, ENERGIA has supported over 4000 women in countries such as Kenya, Nigeria, and Nepal in establishing clean energy ventures in marginalized communities [97]. In the Pacific region, the Sustainable Energy Entrepreneurship Facility (PSEEF) provides seed funding and mentorship to small enterprises and NGOs to promote gender-inclusive energy access [98]. However, limited scholarly attention has been given to systematically analyzing how such gender-focused energy initiatives contribute to long-term empowerment and sustainable development outcomes across diverse regional contexts. This presents a critical research gap.

8. Conclusions

This research aims to identify the interdependence and driving power and dependence of the seven identified SEFs influencing SEEs through a structured mixed-methodological exploration that integrates literature-oriented, qualitative data collection. Quantitative analysis and, again, qualitative approach-based future research directions highlight the theoretical line of the findings through the ADO framework to guide further research by proposing research questions. This is the first study that has applied this integrated approach. The first research question on identifying the interdependence of factors is identified through TISM. The major influencing SEFs are regulatory policies and institutional support, which are the independent factors that influence the rest of the SEFs. Government and policy support, market demand, and financial accessibility are identified as important linkages in driving behavior, and the results also contribute to strategic decision-making. This interdependence emphasizes that SEEs are driven by broader socioeconomic factors and not only by innovation for long-term sustainability. Government policy, institutional support, and financial accessibility are the identified driving factors, and social and cultural attitudes and acceptance are the factors with high dependent power (RQ2). This also highlights the importance of a supportive policy environment and that social and cultural acceptance is the result of the interplay of the remaining SEFs influencing SEEs.

The ADO framework was applied to understand the enablers, decisions, and effects to guide further research. The antecedents highlighted the role of regulatory policies, technological advancements, etc., in strategies for sustainable energy investment, planning infrastructure, and developing skill decisions for improving energy and technological efficiency outcomes. The study further contributes to the goals of global sustainability by covering the multiple SDGs covered by sustainable energy enterprises. Access to renewable energy technologies through clean energy expansion, which links the SDG 7 target, infrastructure, and technology development, aligns with SDG 9 through the development of resilient energy systems, community-driven operations, and ensuring equitable energy access, contributing to SDGs 10 and 11. The energy transition requires the expertise of professionals in the workforce by providing skill development and training programs related to SDGs 4 and 8, along with the overall sustainability focus through reducing carbon emissions, which also meets the targets of SDG 13. The integration of the ADO provides a theoretical basis for sustainable energy entrepreneurship research by showing the importance of policy intervention and technological innovations that can enhance the contribution to sustainability goals, along with promoting social inclusion and economic development. Hence, further research is needed to explore these dimensions and strengthen the understanding of sustainable energy entrepreneurship as a key driver of sustainable development.