The Interplay Between Business Models and Entrepreneurial Capabilities in Aging Populations: Insights from Emerging Economies

Abstract

This research examines the link between business models and entrepreneurial capabilities among social assistance program participants who are aging adults in an emerging economic environment. The research targets the insufficient use of entrepreneurial abilities in seniors to advance their active aging potential while enhancing their life quality. This study collected data from selected participants by using Osterwalder and Pigneur’s business model framework as a basis for their structured questionnaire, which followed a quantitative–qualitative method. Researchers applied Spearman’s Rho statistical methods to measure relations between business elements and skills in self-confidence, creativity, initiative, perseverance, and teamwork demonstrated by entrepreneurs. The study results clearly showed that properly executed business models create substantial growth in entrepreneurial abilities among people of advanced age. This study contributes novel empirical evidence from a rural Peruvian context, confirming that structured business model training is positively associated with entrepreneurial outcomes among elderly populations. The findings (r = 0.755, p < 0.001) support the urgency of integrating capability-building into social assistance schemes. These results emphasize how targeted training programs should empower this population since this initiative supports Sustainable Development Goals like “Decent Work and Economic Growth” (SDG 8) and “Reduced Inequalities” (SDG 10). The analysis demonstrates that teaching entrepreneurial abilities to mature individuals leads to better social entrepreneurship sustainability together with superior economic involvement and social connections.

1. Introduction

The global demographic transition has resulted in a steady increase in the aging population, a trend particularly evident in Peru [1]. According to projections from the National Institute of Statistics and Informatics (INEI), the number of older adults—defined as individuals over 60 years old—is expected to rise significantly, reaching more than 4.5 million by the end of 2024 [2]. Despite this demographic shift, older adults in Peru remain one of the most vulnerable social groups, with 80% reportedly suffering from chronic health conditions, limited access to quality healthcare, and facing socioeconomic marginalization [2]. Furthermore, only a fraction benefit from food assistance programs or are affiliated with pension systems, exacerbating their exclusion and dependence. In response to these conditions, the Peruvian government established the National Program of Social Assistance “Pensión 65” in 2011. This program aims to alleviate poverty among elderly populations through bi-monthly cash transfers and the promotion of “productive knowledge” that seeks to revalue traditional wisdom and experience [3]. However, while these initiatives intend to foster inclusion and social recognition, they often overlook the entrepreneurial potential and business acumen still present among older adults [4]. Many beneficiaries of Pensión 65 exhibit key entrepreneurial capacities—such as initiative, perseverance, creativity, and self-confidence—but these are rarely nurtured or mobilized within institutional frameworks [5]. The research problem addressed is how entrepreneurial traits among older adults intersect with strategic business components to foster economic agency. This inquiry contributes to both empirical scholarship and inclusive policy design for vulnerable populations. The present study is situated in this gap. It investigates the relationship between entrepreneurial capacities and the implementation of business models among older adults enrolled in the Pensión 65 program in Llaylla, Satipo. The focus is not merely on welfare, but on exploring whether older adults can become agents of economic and social transformation through structured entrepreneurial strategies. Drawing on the Business Model Canvas framework [6], this study analyzes how key components—such as value proposition, customer segments, revenue streams, and key resources—interact with entrepreneurial dimensions [7]. The relevance of this research lies in its potential to influence policy by repositioning aging populations not as passive recipients of aid but as active economic contributors. As highlighted by national competitions like “Ancestral Producers” which recognize successful older entrepreneurs [8], there is untapped potential for scaling up these initiatives through education, technical assistance, and strategic partnerships (

Table 1. Winners of the national contest “Ancestral Producers”.

Typology	Category	Department	Venture
Crafts and Manufactures	Individual	San Martín	Clay Handicrafts
		Ancash	Handicrafts manufacturing
		Cajamarca	Straw Crafts
	Group	Madre de Dios	Elaboration of handicrafts using ancestral methods
		Piura	Silver filigree
		Ancash	Wooden Utensils
Crops	Individual	Huanuco	Ornamental plants
		Amazon	Production and sale of pitahaya
		Amazon	Vegetable cultivation with Ausangate waters
	Group	La Libertad	Sowing, harvesting, and sale of gladioli
		Apurimac	Sale of medicinal plants
		Moquegua	Production and sale of prickly pears
Animal Breeding	Individual	Ica	Guinea pig breeding
		San Martín	Cross-cultural food transfer
		Moquegua	Bee breeding and honey sales
	Group	La Libertad	Raising laying hens
		Cusco	Guinea pig breeding
		Huanuco	Guinea pig breeding
Processed and Consumer Products	Individual	La Libertad	Production and sale of quince juices, jams, and liquors
		Madre de Dios	Sale of dry cocoa beans
		Puno	Nutraceutical nectar made from Andean products in Pomata-Puno
	Group	Pasco	Production and marketing of natural essences of eucalyptus oil “San Miguel”
		Puno	Production and marketing of cheese and dairy products
		Junín	Mazamari Entrepreneurs Association

Note: Adapted from [8].

). This study also aligns with international and national sustainable development frameworks, particularly the United Nations’ Sustainable Development Goals (SDGs). It contributes directly to SDG 1 (No Poverty), SDG 8 (Decent Work and Economic Growth), and SDG 10 (Reduced Inequalities), by emphasizing entrepreneurship as a pathway to economic autonomy and social inclusion for aging populations in vulnerable settings. This study thus corresponds with broader Sustainable Development Goals by promoting social inclusion, poverty reduction, and economic empowerment among elderly populations. In a country where more than 60% of older adults remain excluded from pension systems [3], empowering them through entrepreneurship and business model training becomes not only relevant but urgent. This research contributes empirically and methodologically to understanding how entrepreneurial capabilities, when combined with strategic tools, can foster autonomy, dignity, and long-term sustainability for Peru’s aging population. The inclusion of Table 1 is intended to illustrate real-life entrepreneurial outcomes among older adults recognized by a national government initiative. The examples provided complement this study’s context and highlight existing capabilities that the research seeks to analyze further.

While the Peruvian state has taken important steps towards protecting older adults in extreme poverty through the “Pensión 65” program, critical gaps remain in its implementation—particularly in recognizing the entrepreneurial capacities of its beneficiaries. The program, launched in 2011 by the Ministry of Development and Social Inclusion (MIDIS), provides bi-monthly cash transfers to individuals aged 65 and older living in poverty or extreme poverty. It also includes the “productive knowledge” initiative, which aims to promote intergenerational transmission of traditional skills and wisdom [4]. However, the program’s current structure focuses predominantly on passive assistance rather than enabling economic autonomy or entrepreneurial activity. As emphasized by [9], the PERMA model of well-being—which includes positive emotions, engagement, relationships, meaning, and accomplishment—true quality of life for older adults cannot be achieved solely through financial aid. It requires mechanisms that empower individuals to fulfill personal goals, remain socially integrated, and contribute productively to their communities. Existing institutional strategies often ignore these aspects, instead reinforcing dependency models that diminish self-esteem and discourage innovation [10]. The failure to integrate entrepreneurial training or business model development into the Pensión 65 framework is particularly evident in the district of Llaylla, Satipo. Unlike other districts such as Mazamari—where local initiatives have been supported by strategic alliances with international institutions like Coop Business School and Producers Market—Llaylla lacks access to technical, financial, and educational support for elderly entrepreneurs [11]. Although competitions such as “Productores Ancestrales” have showcased the success of elderly-led enterprises in sectors like agriculture, crafts, and food processing, many potential entrepreneurs remain excluded due to insufficient institutional guidance and mentorship [8]. This study responds to these gaps by examining the relationship between entrepreneurial capacities and business model components among older adults participating in Pensión 65 in Llaylla. This research employs the Business Model Canvas [6] to explore how elements such as value proposition, customer segments, key resources, and revenue streams interact with entrepreneurial traits like creativity, perseverance, teamwork, and initiative [7]. The general objective of this study is to determine the relationship between business model components and entrepreneurial capacities in older adults enrolled in the Pensión 65 program in the district of Llaylla, Satipo (2023). The specific objectives include:

O1.

To analyze the relationship between entrepreneurial capacities and each of the nine components of the Business Model Canvas: market segment, value proposition, distribution channels, customer relationships, revenue streams, key resources, key activities, key partnerships, and cost structure.

O2.

To identify gaps in knowledge, training, or institutional support that may hinder the application of business models among elderly participants.

O3.

To provide policy-oriented recommendations for integrating entrepreneurial training into social assistance programs aimed at older adults.

In simplified terms, this study aims to (1) identify latent entrepreneurial capacities among older adults, (2) assess how institutional and cognitive enablers support these capacities, and (3) explore how these capacities can be strategically aligned with business models to promote sustainable development. Through this analytical lens, this study not only seeks to contribute to academic understanding but also to inform sustainable development policy by demonstrating the socioeconomic potential of empowering elderly populations through business model innovation.

This article offers a structured analysis of the relationship between business model components and entrepreneurial capacities among older adults in the Pensión 65 program in Llaylla, Satipo. This study builds on a multidimensional conceptual framework grounded in the literature and national development policy. The Introduction presents demographic and socioeconomic conditions, using data from INEI and the UN Population Fund [3], and highlights the underutilization of older adults’ entrepreneurial potential. The Literature Review synthesizes theoretical and empirical work on the Business Model Canvas [6] and entrepreneurial competencies such as initiative, creativity, and teamwork [7]. The Methodology outlines a quantitative, non-experimental, cross-sectional design using a probabilistic sample of 146 elderly participants. The use of a quantitative, non-experimental, correlational, and cross-sectional design is justified by the aim to assess naturally occurring associations between variables without manipulating conditions. This design allows for hypothesis testing through inferential statistical techniques, such as Spearman’s Rho, which is appropriate for ordinal data and directional assumptions. Data collection relied on structured questionnaires based on validated scales, and the analysis employed Spearman’s Rho to assess correlations between the variables. The final sample consisted of 146 participants, of whom 91 were women (62%) and 55 were men (38%). This gender distribution provides a balanced representation for exploring patterns in entrepreneurial intention and business model engagement. Constructs were operationalized using validated instruments, with ethical procedures aligned to institutional standards [12]. The Results provide descriptive and inferential statistics, revealing significant correlations between business model elements and entrepreneurial traits (e.g., r = 0.755, p < 0.001). The Discussion examines the implications of components such as cost structure and customer relationships in relation to participant skills, drawing comparisons with prior studies [13,14]. The Conclusions highlight the importance of institutionalizing entrepreneurship training within Pensión 65 as a means to promote economic inclusion and well-being in aging populations.

2. Literature Review and Theoretical Foundations

2.1. Background

Empirical studies have explored the relationship between entrepreneurial capacities and business model development across various social and institutional contexts. These prior investigations form the conceptual and methodological foundation for the present study.

At the Peruvian level, reference [13] examined the correlation between entrepreneurial capacity and business model generation among business administration students in Apurímac, Peru. The study, based on a non-experimental, quantitative design with 60 respondents, found a moderate positive correlation (r = 0.505, p < 0.05), supporting the idea that entrepreneurial competencies are integral to effective business planning. Similarly, reference [15] investigated entrepreneurial capacities and their influence on fostering an entrepreneurial spirit among high school students in Cañete. The study concluded that core competencies such as initiative and creativity were directly linked to the students’ ability to conceptualize and act on business ideas. In another Peruvian study, reference [16] focused on the management of entrepreneurial capacity development within rural inclusive enterprises under the FONCODES project in Tarapoto. The research revealed a significant relationship between management systems and capacity development, suggesting that support structures play a vital role in enabling sustainable rural entrepreneurship. Reference [17], meanwhile, proposed a business model for a cooperative in the Andes region using the Canvas framework. The study demonstrated how tailored business models can support institutional growth and adaptation to evolving market challenges. Further, reference [18] analyzed the interplay between entrepreneurial capacity and emotional intelligence among adult entrepreneurs in Piura. Their results emphasized that affective dimensions, such as self-awareness and resilience, significantly influence entrepreneurial behavior and business success.

Internationally, reference [14] evaluated entrepreneurial capacity among Mexican university students, identifying strong awareness of entrepreneurial potential, albeit limited by weak socio-academic contextualization. Reference [19] studied strategic planning capacity among higher education students in northern Mexico, highlighting the importance of planning competencies in shaping entrepreneurial initiatives.

Reference [20] conducted a literature-based study on business model innovation and its organizational impacts. Their findings revealed that adopting innovative business frameworks enhances competitive advantage and long-term sustainability. Reference [21] examined the application of business models among artisans, identifying a lack of knowledge and training as barriers to effective implementation. In order to enhance conceptual clarity, it is important to arrange the literature thematically. While the current structure maintains a sequential presentation of relevant studies, it implicitly reflects key thematic areas such as entrepreneurship in aging populations, the adoption of business models in informal contexts, and institutional factors affecting rural development. This echoes the current study’s context in Llaylla, where institutional support for entrepreneurial development is minimal. Finally, reference [22] explored the role of learning communities in cultivating entrepreneurial capacities among high school students in Manabí, Ecuador. Their results emphasized the importance of inclusion, communication, and collaborative learning in fostering entrepreneurial mindsets. Together, these studies underscore the consistent relationship between entrepreneurial skills and the ability to conceptualize and implement business models. The literature cited throughout this section provides empirical and theoretical grounding across overlapping domains, including aging and entrepreneurship, resource-constrained innovation, and inclusive policy design in emerging economies. These intersections support the conceptual foundation of this study. However, they also highlight a pervasive gap: the need for targeted education, institutional mentorship, and structural support—especially among vulnerable populations, such as older adults. The present research contributes to this discourse by focusing on a largely overlooked group and proposing a model for empowerment through entrepreneurial frameworks and inclusive policy reform.

2.2. Theoretical and Scientific Foundations

This study is grounded in two central constructs: the business model, conceptualized through the framework from reference [6], and entrepreneurial capacities, developed primarily from a competency-based approach [7]. Both constructs are explored not only as theoretical categories but as practical tools for fostering economic inclusion among older adults in vulnerable contexts. The business model is understood as the rationale by which an organization creates, delivers, and captures value. Reference [6] propose the Business Model Canvas (BMC) as a strategic management tool that breaks down this rationale into nine interrelated components: customer segments, value proposition, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, and cost structure. These components collectively represent the operational architecture of a business and are essential for evaluating feasibility, competitiveness, and sustainability. The model is especially relevant in contexts where entrepreneurs require a clear, visual, and adaptable framework to structure their business ideas. According to reference [23], the canvas also supports the development of sustainable enterprises by aligning economic, environmental, and social goals. Moreover, reference [24] emphasized that business models serve as logical structures for value creation and delivery, enhancing decision making and innovation in dynamic markets. Reference [25] reinforces the idea that innovative business models are fundamental to organizational adaptability and client satisfaction. The BMC is particularly applicable in low-resource contexts such as Pensión 65, where older adults often possess valuable experiential knowledge but lack formal business training. By using the canvas as a learning and planning tool, participants can better articulate their entrepreneurial goals and identify areas of potential growth.

The second core construct, entrepreneurial capacities, refers to a set of personal and interpersonal competencies that enable individuals to initiate, manage, and sustain business activities. According to reference [26], these capacities include self-confidence, creativity, initiative, perseverance, and teamwork. Each dimension contributes to the entrepreneur’s ability to navigate uncertainty, identify opportunities, and mobilize resources. Reference [27] defined entrepreneurship as the act of undertaking challenging ventures, often under conditions of risk or constraint. From a psychological perspective, entrepreneurial behavior is associated with positive psychology, focusing on strengths such as resilience, agency, and intrinsic motivation [28,29]. References [30,31] both underscore the role of entrepreneurial capacities in social and economic development, particularly in fostering self-sufficiency and innovation. Older adults frequently exhibit their competencies through lived experience, yet they may lack formal mechanisms for channeling them into structured ventures [32]. This interaction suggests a dynamic relationship where conceptual models guide action, and individual capacities shape how business planning is internalized and executed among aging entrepreneurs. By linking these capacities with a business modeling framework, this study provides a theoretical and practical bridge between personal potential and institutional empowerment. The BMC offers a structural representation of entrepreneurial logic, while entrepreneurial capacities provide the behavioral and psychological drivers necessary for implementing each component effectively.

In sum, these two frameworks—business modeling and entrepreneurial competencies—are not only conceptually robust but highly complementary. Their integration supports a transformative approach to elder inclusion, allowing social programs like Pensión 65 to move beyond welfare and toward sustainable, dignity-based development.

2.3. Conceptual Framework

The conceptual framework of this study is built upon two primary variables: the business model and entrepreneurial capacities, each comprising multiple dimensions that reflect their operational and theoretical components. The integration of these variables enables a structured analysis of the potential link between strategic business structuring and personal competencies among older adults in the Pensión 65 program. The concept of a business model (variable 1), as defined by [6], refers to how an organization creates, delivers, and captures value. The model is broken down into nine key dimensions, each representing a core function of the enterprise:

• Customer Segments: Identifying and targeting groups of customers based on shared characteristics, behaviors, or needs. Segmentation enables tailored value delivery and more efficient resource allocation.
• Value Proposition: The central offering that solves a problem or fulfills a need. It is what differentiates a business from competitors and drives customer loyalty.
• Channels: The pathways through which products or services reach customers. This includes communication, distribution, and sales infrastructures.
• Customer Relationships: Strategies to attract, retain, and enhance customer engagement, including personalized service, loyalty programs, and after-sales support.
• Revenue Streams: The sources through which income is generated, whether through transactional or recurring models.
• Key Resources: Assets critical to the delivery of the value proposition, which may be physical, human, intellectual, or financial in nature.
• Key Activities: Operational tasks essential to business functioning, such as production, marketing, or customer service.
• Key Partnerships: Strategic alliances with suppliers, collaborators, or institutions that enhance business efficiency and scalability.
• Cost Structure: The financial architecture of the business, including fixed and variable costs associated with operations and growth.

This framework offers a comprehensive lens for analyzing microenterprises and entrepreneurial ventures, which is particularly useful in low-income and informal economies.

Entrepreneurial capacities (variable 2) are defined here as individual competencies that enable a person to identify opportunities, mobilize resources, and sustain a business venture [7,33]. These are particularly relevant in contexts of economic vulnerability, where formal education may be limited but practical knowledge is abundant. The five dimensions considered are as follows:

• Self-confidence: The belief in one’s ability to succeed, make decisions, and take initiative in uncertain environments.
• Creativity: The ability to generate innovative ideas and adapt to changing circumstances through problem-solving and original thinking.
• Initiative: A proactive attitude towards identifying and acting upon opportunities without external prompting.
• Perseverance: The capacity to remain committed to goals despite obstacles or setbacks, often linked to discipline and resilience.
• Teamwork: The skill to collaborate effectively, delegate responsibilities, and contribute to collective outcomes through empathy and communication.

For instance, initiative enhances value proposition development, perseverance supports the sustainability of revenue streams, and teamwork is essential for effective key partnerships and customer relationships. Together, these dimensions align with the broader concept of entrepreneurial self-efficacy and are seen as foundational for sustainable business development, particularly among older adults who often operate within informal or resource-constrained environments [34,35]. This perspective also aligns with recent contributions highlighting the importance of green innovation in entrepreneurial leadership [36] and the evolving psychological dimensions of organizational commitment in emerging contexts [37].

By articulating these variables and dimensions, the conceptual framework provides the basis for exploring how strategic business design interacts with personal entrepreneurial traits in the context of social assistance and rural entrepreneurship.

3. Methods

3.1. Research Methodology

This study employed a quantitative, non-experimental, cross-sectional, and correlational research design, aligned with the methodological guidelines proposed by [12]. This approach was selected to examine the relationship between two core variables—business model components and entrepreneurial capacities—among older adults participating in the Pensión 65 program in the district of Llaylla, Satipo, Peru. Quantitative methodology was used to obtain measurable, objective data on the variables of interest. The non-experimental nature of the research indicates that no manipulation of variables occurred; instead, this study observed existing conditions among the participants. The cross-sectional design allowed data collection at a single point in time during 2023, providing a snapshot of the relationship between entrepreneurial competencies and business model structures among elderly program beneficiaries. The correlational scope of this study focused on assessing the strength and direction of associations between the dimensions of both variables without implying causality. The study population consisted of all older adults enrolled in the Pensión 65 program in Llaylla. A probabilistic sampling method was applied, ensuring equal selection probability and enabling statistical generalization. Based on a total population of 236 program beneficiaries, the final sample size was 146 participants, calculated using a 95% confidence level and a 5% margin of error. Data collection was conducted using two structured questionnaires, each validated by experts in social sciences and entrepreneurship. The first instrument evaluated the nine components of the Business Model Canvas, while the second assessed entrepreneurial capacities as explained in the previous sections. Both instruments used Likert-type scales to measure agreement or frequency, depending on the item (

Table 2. Operationalization matrix of the instrument.

Variables	Operational Definition	Dimensions	Indicators	Measuring Scale
Variable 1 Business Model	The business model variable will be measured by a questionnaire with Likert-type scale alternatives.	Market segment	Groups of people	(1) Never (2) Almost never (3) Sometimes (4) Almost always (5) Always
			Satisfaction
		Value proposition	Troubleshooting
			Needs
		Service channels	Providing information
			Value proposition
			After sales
		Customer relations	Customer training
			Customer loyalty
			Customer experience
		Revenue sources	Cash flow
		Key resources	Physical Resources
			Financial resources
			Human or intellectual resources
		Key Activities	Value proposition
			Customer relations
			Contact platform
		Key partnerships	Key partners
			Key suppliers
		Cost structures	Fixed costs
			Variable costs
Variable 2 Entrepreneurial skills	The entrepreneurial capabilities variable will be measured by a questionnaire with Likert-type scale alternatives.	Self-confidence	Skills	(1) Never (2) Almost never (3) Sometimes (4) Almost always (5) Always
			Preparation
			Decision making
			Difficulties
		Creativity	Imagination
			Troubleshooting
			Adaptability to change
		Initiative	Independent
			Challenges
		Perseverance	Effort
			Motivation
			Failure
		Teamwork	Delegate
			Empathy

Note: Own elaboration.

). To streamline the narrative flow, the operationalization matrix has been presented in summary form. Detailed items remain available for review but are condensed in the main body for readability.

The validity of the instruments was established through expert judgment, ensuring content relevance, clarity, and coherence. Reliability was measured using Cronbach’s Alpha, with coefficients exceeding 0.85 for both instruments, indicating a high level of internal consistency. The analysis of data was conducted using SPSS (Statistical Package for the Social Sciences), version 25. Descriptive statistics (mean, standard deviation, frequency, and percentage) were employed to characterize the population and the distribution of responses. Inferential statistics were applied to test the hypotheses, specifically using Spearman’s Rho coefficient, appropriate for ordinal variables and non-parametric data. This allowed for determining the direction and strength of correlation between the business model dimensions and the entrepreneurial capacities. Ethical considerations were strictly observed. Participation was voluntary, and informed consent was obtained from all respondents. Anonymity and confidentiality were guaranteed, and this study followed the ethical guidelines for research with human subjects as stipulated by the Peruvian Ministry of Education. By employing this methodological structure, the research ensured the rigor, validity, and reliability needed to generate meaningful conclusions about the entrepreneurial potential and strategic business understanding of elderly individuals supported by state welfare programs.

3.2. Type, Level, and Research Design

This study adopts a quantitative, non-experimental, correlational, and cross-sectional research design, following the methodological principles established by [12]. These choices are aligned with the research aim: to determine the relationship between business model components and entrepreneurial capacities among elderly beneficiaries of the Pensión 65 program in Llaylla, Satipo. The research is quantitative in nature, focusing on the collection and statistical analysis of numerical data to evaluate defined variables. Quantitative methods enable the measurement of perceptions, capacities, and behavioral patterns in a standardized and replicable manner, suitable for testing hypotheses and determining correlations between structured constructs [12]. In this context, the variables—business model and entrepreneurial capacities—were operationalized through measurable dimensions drawn from validated theoretical frameworks [6,7]. This study is conducted at a correlational–descriptive level. As a descriptive study, it aims to characterize the degree to which entrepreneurial capacities and business model components are present among participants. Descriptive statistics provide insights into patterns, frequencies, and average levels of performance across the variables’ dimensions.

At the correlational level, the research investigates the degree of association between the two primary constructs. It does not seek to establish causal relationships but rather to determine whether and how strongly the variables are statistically related. This approach is appropriate given the nature of the constructs—personal competencies and strategic planning elements—which are expected to co-occur in entrepreneurial behavior but are influenced by various external and contextual factors. This study follows a non-experimental, cross-sectional design. It is non-experimental because the researchers did not manipulate or control any variables; instead, they observed and measured phenomena as they naturally occurred among the population. This is particularly relevant when working with vulnerable or protected groups, such as older adults receiving state assistance, where ethical considerations preclude experimental manipulation. The cross-sectional design refers to the collection of data at a single point in time during the 2023 calendar year. This allows for a timely assessment of the participants’ conditions and perspectives without requiring longitudinal follow-up. The design enables the researcher to compare and correlate multiple variables within the same timeframe, optimizing efficiency while maintaining analytical rigor. This methodological configuration provides a solid framework for understanding the interplay between personal entrepreneurial competencies and structured business planning, especially in under-researched populations such as rural older adults in Peru. It facilitates evidence-based policy recommendations for programs like Pensión 65, offering a pathway to integrate capacity-building and business development into existing social protection models. By choosing a correlational, quantitative, and cross-sectional approach, this study remains both ethically responsible and analytically robust, providing valuable insights into how elder entrepreneurship can be supported through structured institutional frameworks and validated pedagogical tools.

3.3. Population and Sample Description

The target population for this study comprised all older adults registered in the Pensión 65 program in the district of Llaylla, located in the province of Satipo, Junín region, Peru. This rural population is characterized by limited access to education, healthcare, and formal employment opportunities, often relying on subsistence agriculture or informal economic activities. As part of the Peruvian government’s effort to reduce extreme poverty among the elderly, Pensión 65 provides bi-monthly financial support to individuals aged 65 or older who are classified as extremely poor based on socioeconomic assessments [4]. According to official data provided by the program’s local administrative unit, the total number of active beneficiaries in Llaylla during 2023 was 236 individuals. These beneficiaries represent a vulnerable segment of the population whose entrepreneurial potential remains largely unexplored, despite their extensive life experience and productive knowledge. To ensure representation and analytical validity, this study employed a probabilistic sampling method, using a simple random sampling strategy. This approach allowed each member of the population an equal chance of selection, thereby minimizing bias and enhancing the generalizability of results to the broader Pensión 65 beneficiary population in Llaylla. The sample size was determined to be 146 participants, based on statistical parameters commonly used in social research: a confidence level of 95%, a margin of error of 5%, and a response distribution of 50%, which is the most conservative estimate when no prior information is available on population variability. The formula for sample size determination followed established quantitative methods [12], ensuring a robust foundation for inferential analysis as follows:

$$n={\displaystyle \frac{Z^{2}pq·N}{E^2\left(N-1\right)+Z^2·pq}}$$

(1)

where

n = sample size

p = 0.5

q = 0.5

N = population size

E = error level (5% for 95% confidence) = 5%

Z = Z-value for 95% confidence interval = 1.96

Replacing:

$$n={\displaystyle \frac{{1.96}^2\left(0.5\right)\left(0.5\right)·236}{{\left(0.05\right)}^2\left(236-1\right)+{\left(1.96\right)}^2·\left(0.5\right)\left(0.5\right)}}$$

$$n=146.4\approx 146$$

Participants were selected from various sectors of Llaylla to reflect the geographic and cultural diversity of the district. Inclusion criteria were as follows: being an active recipient of Pensión 65, residing permanently in the district, and having cognitive and physical capacity to respond to survey items independently. Participants with temporary residency, severe cognitive impairments, or unwillingness to consent were excluded from this study. Data collection was conducted through structured, face-to-face interviews to accommodate potential literacy limitations among participants. Interviewers received prior training to ensure respectful engagement and adherence to ethical standards, including the protection of participant confidentiality and informed consent procedures. The final sample reflects a balanced representation of the elderly population in Llaylla, encompassing both male and female participants across varying levels of education and occupational backgrounds. This diversity provided a rich empirical basis for analyzing the relationship between business model knowledge and entrepreneurial competencies in a socially and economically marginalized context. By capturing this segment of the population, this study offers valuable insights into the capacity of older adults to engage in entrepreneurial activity when supported by inclusive, well-structured social programs. It also underscores the importance of tailoring development interventions to the specific characteristics of rural elderly populations in Peru.

3.4. Data Collection Techniques and Instruments

The data collection process in this study was designed to ensure validity, reliability, and ethical integrity while being adapted to the sociocultural context of older adults in the rural district of Llaylla. Two primary data collection techniques were employed: structured surveys and direct interviews, both implemented with instruments tailored to measure this study’s two core variables—business model components and entrepreneurial capacities. Given the target population’s characteristics—primarily low levels of formal education, limited technological access, and possible literacy challenges—the researchers opted for in-person interviews using structured questionnaires. This technique allowed participants to respond verbally while ensuring standardized administration of each item, thereby maintaining the objectivity of the quantitative research [12]. Trained field researchers conducted the interviews in participants’ homes or community centers, ensuring accessibility and comfort. This approach minimized the risk of non-response or misinterpretation, particularly in a population where written self-administered surveys may have been impractical. It also allowed for the immediate clarification of questions when needed, thus improving response accuracy and data quality. Two validated instruments were developed and applied (

Table 3. Instrument construction matrix.

Variables	Dimensions	Indicators	Items
Variable 1 Business Model	Market segment	Groups of people	1. You believe that by segmenting the market, you identify your customers as the most important in your venture.
		Satisfaction	2. You believe that by segmenting the market, you will increase customer satisfaction by segmenting your customers according to their needs, behaviors, and attributes.
	Value proposition	Troubleshooting	3. Believe you with the value proposition, you will help provide a solution to our customers’ problems.
		Needs	4. Create the value proposition that will help you meet your customers’ needs.
	Service channels	Providing information	5. Do you believe that the service channels make your customers aware of your products or services?
		Value proposition	6. Do you believe that the service channels provide an opportunity for customers to evaluate the value proposition of your company?
		After sales	7. Do you believe that your customer service channels provide your customers with personalized after-sales service?
	Customer relations	Customer training	8. You believe that customer relationships are based on customer acquisition strategies.
		Customer loyalty	9. You believe that customer relationships are based on loyalty strategies.
		Customer experience	10. You believe that customer relationships are based on global experiences.
	Revenue sources	Cash flow	11. Are you familiar with the concept of benefits?
			12. Are you familiar with the concept of expenses?
			13. Are you familiar with the concept of income?
	Key resources	Physical Resources	14. Knows the concept of physical assets such as “manufacturing facilities, buildings, vehicles, machines, systems, points of sale and distribution networks”.
		Financial resources	15. You believe that one of the key resources are economic guarantees, such as cash, lines of credit.
		Human or intellectual resources	16. You believe that a key resource is creative people, with a high level of knowledge vital to a company.
	Key Activities	Value proposition	17. You believe the value proposition will help improve production.
		Customer relations	18. Create relationships with customers will help improve production.
		Contact platform	19. You believe that the platform of contacts, networking, software, and branding will help increase revenue.
			20. You believe that the platform of contacts, networks, software, and brands will help improve the efficiency of distribution channels.
	Key partnerships	Key partners	21. Do you believe that having key partners helps to optimize the resources of the company or venture?
			22. Do you believe that having key partners helps to optimize the activities of the company or venture?
		Key suppliers	23. Do you believe that having key suppliers contributes to optimizing the resources of the company or enterprise?
			24. Do you believe that having key suppliers contributes to optimize the activities of the company or enterprise?
	Cost structures	Fixed costs	25. Are you familiar with the concept of fixed costs?
		Variable costs	26. Are you familiar with the concept of variable costs?
Variable 2 Entrepreneurial skills	Self-confidence	Skills	1. I am aware of my abilities and I demonstrate them.
		Preparation	2. He considers that his knowledge requires constant development and preparation.
		Decision making	3. You make decisions without delay when necessary (you do not leave for tomorrow what has to be solved at the moment).
		Difficulties	4. Frequently faces problems without being intimidated by possible difficulties.
	Creativity	Imagination	5. He usually takes advantage of his imagination to invent alternatives to solve a problem.
		Troubleshooting	6. He frequently visualizes problems that seem to be unidentified or overlooked by others.
		Adaptability to change	7. You are the person who is not afraid of change.
			8. You are the person looking for several options to solve a problem.
	Initiative	Independent	9. He considers himself an independent person to make his own decisions.
			10. You reject suggestions, opinions of other people.
			11. You find that you get discouraged easily.
		Challenges	12. You are a person who usually takes on challenges and strives to achieve your goals.
			13. You are a person who evaluates several alternatives before making a decision.
	Perseverance	Effort	14. You set your goals and don’t stop until you achieve them.
			15. You strive to persevere and maintain what you have achieved.
		Motivation	16. You are often motivated and enjoy what you do or perform.
		Failure	17. In general, you believe that the word failure is the end.
	Teamwork	Delegate	18. You feel that you can do things alone and independently without asking others for help.
			19. Usually, you delegate important activities to your team members.
			20. You usually delegate important activities to your team members and collaborate on these tasks.
		Empathy	21. I am a person who treats people well and considers them an important part of your business.
			22. I am a person who knows how to listen to suggestions and other people’s opinions.

):

• Business Model Questionnaire: This instrument operationalized the nine components of the model: customer segments, value proposition, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, and cost structure. The questionnaire was structured with closed-ended items using a five-point Likert scale, ranging from “strongly disagree” to “strongly agree”, allowing respondents to express the degree of relevance or understanding they attributed to each dimension.
• Entrepreneurial Capacities Questionnaire: This instrument conceptualizes five core entrepreneurial competencies: self-confidence, creativity, initiative, perseverance, and teamwork. The items were likewise presented in a Likert scale format to measure frequency or intensity of behavior, enabling a quantitative assessment of each dimension.

Both instruments underwent expert validation prior to field application. Specialists in education, entrepreneurship, and social sciences evaluated content relevance, item clarity, and cultural appropriateness. Modifications were made accordingly to improve coherence and ensure the instruments’ suitability for elderly respondents in rural Peru. To evaluate reliability, internal consistency was measured using Cronbach’s Alpha, yielding coefficients above 0.85 for both instruments. These values indicate high reliability and confirm that the items within each scale consistently reflect the underlying constructs [12]. Ethical safeguards were incorporated throughout the data collection process. Participants were informed about the purpose of this study, their right to confidentiality, and their freedom to withdraw at any time. Informed consent was obtained verbally, considering the population’s potential limitations in reading or writing.

In sum, the combination of structured interviews and rigorously validated instruments enabled the collection of high-quality data suited to the specific context of the study population. This methodology ensured that the insights gathered were both statistically reliable and culturally grounded.

3.5. Data Processing and Analysis

The data collected through structured interviews and questionnaires were subjected to a systematic process of organization, coding, and statistical analysis. This stage was essential to ensuring the reliability and validity of the findings and followed the methodological guidelines established by [12]. After collection, the survey responses were manually reviewed for completeness and accuracy. Any ambiguous or incomplete responses were clarified or excluded following predefined criteria to preserve data integrity. Subsequently, the responses were coded numerically in accordance with the Likert scale used in the instruments—ranging from 1 (“strongly disagree” or “never”) to 5 (“strongly agree” or “always”). The dataset was then entered into the Statistical Package for the Social Sciences (SPSS), version 25, which facilitated both descriptive and inferential statistical procedures. Data cleaning procedures were applied to identify outliers, missing values, or inconsistencies. Frequencies, cross-tabulations, and graphical inspections ensured data consistency before formal analysis. The analytical strategy was divided into two main phases:

• Descriptive Statistics: The first phase involved summarizing the key characteristics of the sample and the distribution of responses across all questionnaire items. Measures of central tendency (mean, median, mode) and dispersion (standard deviation, range) were calculated for each dimension of the business model and entrepreneurial capacities. Additionally, frequency distributions and percentage values were used to profile the demographic characteristics of participants and their perceptions in each variable domain.
• Inferential Statistics: The second phase aimed to test this study’s central hypothesis: whether a statistically significant relationship exists between business model components and entrepreneurial capacities in older adults. Given that the data were ordinal and did not assume a normal distribution, Spearman’s rank-order correlation coefficient (Rho) was used as the primary inferential test.

Spearman’s Rho is a non-parametric statistic ideal for assessing monotonic relationships between ranked variables. The test allowed the researchers to determine the strength and direction of association between each of the nine business model components (e.g., value proposition, revenue streams, customer segments) and the five entrepreneurial dimensions (e.g., creativity, initiative, perseverance). A significance threshold of p < 0.05 was adopted to evaluate the results, ensuring a 95% confidence level in the interpretations. To confirm the internal consistency of the instruments, Cronbach’s Alpha was computed for both scales. The business model instrument yielded a coefficient of 0.872, and the entrepreneurial capacities instrument reported 0.885, both indicating strong reliability and homogeneity within the respective item sets. Overall, the statistical methods employed were rigorously selected to match this study’s correlational design and the nature of the data. These procedures enabled a robust analysis of how entrepreneurial potential among older adults is associated with their understanding and application of business model components, offering actionable insights for programmatic and policy interventions.

3.6. Ethical Considerations

As already introduced in the previous sections, the ethical integrity of the research was prioritized throughout the design, data collection, and analysis stages, particularly given this study’s focus on a vulnerable population: older adults in extreme poverty. All procedures adhered to national and international ethical guidelines for research involving human participants, in line with the standards set forth by the Peruvian Ministry of Education and the methodological recommendations of [12]. One of the primary ethical considerations was the principle of informed consent. Prior to participation, each individual was provided with a clear and accessible explanation of this study’s purpose, scope, procedures, potential risks, and benefits. Given the possibility of illiteracy among participants, consent was obtained verbally, ensuring comprehension through direct communication in a respectful and culturally sensitive manner. This approach guaranteed that participation was voluntary, and no individual was coerced or misled. The research also upheld the principle of anonymity and confidentiality. Personal identifiers were not collected, and all data were coded numerically to protect participant identity. The information gathered was used solely for academic purposes and securely stored in password-protected databases accessible only to the research team. During data presentation, results were aggregated to prevent the identification of any individual respondent. Additionally, this study ensured non-maleficence, avoiding any physical, emotional, or psychological harm to participants. The interviews were conducted in familiar and safe environments—typically in participants’ homes or local community centers—to foster trust and reduce anxiety. Interviewers received prior training in ethical conduct and effective communication with older populations, especially regarding patience, empathy, and respect for the participants’ pace and cognitive abilities. The research also adhered to the principle of justice, ensuring equal opportunity for participation across the entire district of Llaylla. The probabilistic sampling method guaranteed that selection was impartial and inclusive, without discrimination based on gender, ethnicity, or health status. Furthermore, the findings aim to benefit the same community studied, through policy recommendations and practical proposals that promote the inclusion and empowerment of older adults in social programs such as Pensión 65. In cases where participants expressed discomfort or declined to continue, their decision was respected without consequences, in line with the right to withdraw at any time without justification. No form of compensation or incentive was provided, to avoid undue influence over the decision to participate. Lastly, this study was developed within an academic framework under institutional supervision, incorporating peer and expert reviews at various stages to ensure methodological soundness and ethical compliance. Any potential conflicts of interest were disclosed and addressed in advance. By incorporating these ethical principles—autonomy, confidentiality, non-maleficence, beneficence, and justice—this study maintained a human-centered and respectful approach, ensuring that participants’ dignity and rights were fully protected throughout the research process.

4. Results

This study’s results revealed significant patterns regarding the relationship between business model components and entrepreneurial capacities among elderly beneficiaries of the Pensión 65 program in the district of Llaylla, Satipo. The analysis included descriptive and inferential statistics derived from a sample of 146 older adults.

4.1. Descriptive Results on Quality of Service (Variable 1)

The analysis of the data presented in

Table 4. Variable 1: Quality of service.

Levels	Scale	Frequency	Percentage
Bad	26 to 60	36	24.66%
Regular	61 to 95	90	61.64%
Good	96 to 130	20	13.70%
Total		146	100%

Note: SPSS results.

,

Table 5. Dimension 1 Variable 1: Quality in services.

Levels	Scale	Frequency	Percentage
Bad	2 to 4	51	34.93%
Regular	5 to 7	63	43.15%
Good	8 to 10	32	21.92%
Total		146	100%

Note: SPSS results.

,

Table 6. Dimension 2 Variable 1: Value proposition.

Levels	Scale	Frequency	Percentage
Bad	2 to 4	55	37.67%
Regular	5 to 7	57	39.04%
Good	8 to 10	34	23.29%
Total		146	100%

Note: SPSS results.

,

Table 7. Dimension 3 Variable 1: Service channels.

Levels	Scale	Frequency	Percentage
Bad	3 to 6	56	38.36%
Regular	7 to 10	69	47.26%
Good	11 to 12	21	14.38%
Total		146	100%

Note: SPSS results.

,

Table 8. Dimension 4 Variable 1: Relationships with customers.

Levels	Scale	Frequency	Percentage
Bad	3 to 7	55	37.67%
Regular	7 to 12	75	51.37%
Good	13 to 15	16	10.96%
Total		146	100%

Note: SPSS results.

,

Table 9. Dimension 5 Variable 1: Sources of income.

Levels	Scale	Frequency	Percentage
Bad	3 to 7	58	39.73%
Regular	7 to 12	68	46.58%
Good	13 to 15	20	13.70%
Total		146	100%

Note: SPSS results.

,

Table 10. Dimension 6 Variable 1: Key resources.

Levels	Scale	Frequency	Percentage
Bad	3 to 7	55	37.67%
Regular	7 to 12	70	47.95%
Good	13 to 15	21	14.38%
Total		146	100%

Note: SPSS results.

,

Table 11. Dimension 7 Variable 1: Key activities.

Levels	Scale	Frequency	Percentage
Bad	4 to 9	45	30.82%
Regular	10 to 15	81	55.48%
Good	16 to 20	20	13.70%
Total		146	100%

Note: SPSS results.

,

Table 12. Dimension 8 Variable 1: Key partnership.

Levels	Scale	Frequency	Percentage
Bad	4 to 9	46	31.51%
Regular	10 to 15	80	54.79%
Good	16 to 20	20	13.70%
Total		146	100%

Note: SPSS results.

and

Table 13. Dimension 9 Variable 1: Cost structure.

Levels	Scale	Frequency	Percentage
Bad	2 to 4	56	38.36%
Regular	5 to 7	60	41.10%
Good	8 to 10	30	20.55%
Total		146	100%

Note: SPSS results.

reveals a worrisome trend in terms of the level of capacity development among older adults in the “Pension 65” program in the District of Llaylla, Satipo in terms of the Quality of Service and its different dimensions. In general, a significant percentage of this population is at low or regular levels in various dimensions evaluated. For example, in several tables, more than 30% of the participants are classified in the “poor” level, and in some cases, this percentage is close to 40%. In addition, the majority of older adults are placed at a “fair” level, indicating that, although they are not at the lowest level, they do not reach an optimal level of skill development either. Only a small percentage achieved a “good” level, suggesting that current interventions may not be sufficient to foster meaningful development in this population. These results underscore the need to review and improve training and support strategies within the program to ensure that older adults can reach their full potential and improve their quality of life. While the number of tables may appear extensive, they have been preserved in individual form to provide a disaggregated view of each business model dimension, enabling a clearer understanding of the specific areas where participants scored low or moderate.

4.2. Descriptive Results on Entrepreneurial Capacity (Variable 2)

The analysis of the results on the entrepreneurial capacity of older adults in the “Pension 65” program in the District of Llaylla, Satipo, reveals a worrisome distribution in the levels of development of this variable. In the tables analyzed (

Table 14. Variable 2: Entrepreneurial capacity.

Levels	Scale	Frequency	Percentage
Bad	22 to 51	37	25.34%
Regular	52 to 81	89	60.96%
Good	82 to 110	20	13.70%
Total		146	100%

Note: SPSS results.

,

Table 15. Dimension 1 of Variable 2: Self-confidence.

Levels	Scale	Frequency	Percentage
Bad	4 to 9	52	35.62%
Regular	10 to 15	71	48.63%
Good	16 to 20	23	15.75%
Total		146	100%

Note: SPSS results.

,

Table 16. Dimension 2 of Variable 2: Creativity.

Levels	Scale	Frequency	Percentage
Bad	4 to 9	46	31.51%
Regular	10 to 15	73	50.00%
Good	16 to 20	27	18.49%
Total		146	100%

Note: SPSS results.

,

Table 17. Dimension 3 of Variable 2: Initiative.

Levels	Scale	Frequency	Percentage
Bad	5 to 11	42	28.77%
Regular	12 to 18	80	54.79%
Good	19 to 25	24	16.44%
Total		146	100%

Note: SPSS results.

and

Table 18. Dimension 4 of Variable 2: Perseverance.

Levels	Scale	Frequency	Percentage
Bad	4 to 9	45	30.82%
Regular	10 to 15	76	52.05%
Good	16 to 20	25	17.12%
Total		146	100%

Note: SPSS results.

), it is observed that a considerable percentage of the participants are at a “poor” level, with figures ranging from 25.34% to 35.62%. Most of the older adults are at a “fair” level, with percentages ranging from 48.63% to 60.98%, which indicates that, although they are not at the lowest level, they do not reach an optimal level of entrepreneurial capacity either. Only a small percentage achieved a “good” level, with figures ranging from 13.70% to 18.49%, suggesting that current interventions may not be sufficient to foster significant development in this population. These results highlight the need to implement more effective strategies to improve the entrepreneurial skills of older adults, which is crucial for their economic and social integration. In line with the approach used in the previous section, tables for each entrepreneurial capacity dimension are presented separately to highlight distinct patterns of performance, which are relevant for interpreting the diagnostic value of each trait. The findings presented in Table 4, Table 5, Table 6, Table 7, Table 8, Table 9, Table 10, Table 11, Table 12, Table 13, Table 14, Table 15, Table 16, Table 17, Table 18 and

Table 19. Dimension 5 of Variable 2: Teamwork.

Levels	Scale	Frequency	Percentage
Bad	5 to 11	42	28.77%
Regular	12 to 18	77	52.74%
Good	19 to 25	27	18.49%
Total		146	100%

Note: SPSS results.

consistently show that the majority of participants are positioned at “regular” levels across nearly all dimensions, while only a minority reached “good” levels. These trends, particularly the concentration of over 60% of respondents in the “fair” category, support the argument that current training efforts may be insufficient to develop high-level entrepreneurial or business model competencies. The majority of participants scored in the “regular” range for most variables. Notably, dimensions such as value proposition and cost structure exhibited high percentages of “poor” scores, indicating critical gaps in strategic understanding.

4.3. Normality Test—Inferential Statistics

The analysis of the normality test, presented in

Table 20. Normality Test—Inferential statistics.

	Kolmogorov–Smirnov a			Shapiro–Wilk
	Statistic	df	Sig.	Statistic	df	Sig.
Entrepreneurial skills	0.162	146	0.000	0.899	146	0.000
Business Model	0.168	146	0.000	0.882	146	0.000

^(a) significance correction. Note: SPSS results.

, focuses on testing hypotheses to determine the distribution of the data for the variables “business model” and “entrepreneurship”. The null hypothesis states that the data follow a normal distribution, while the alternate hypothesis suggests the opposite. Using the Kolmogorov–Smirnov test, it is concluded that the alternate hypothesis is accepted and the null hypothesis is rejected, indicating that the data do not follow a normal distribution (p-value < 0.05). Because of this, it was decided that a non-parametric test be employed. In this context, Spearman’s Rho statistic was used, suitable for correlational level studies with an ordinal measurement scale, as detailed in

Table 21. Correlation coefficient.

Relationship Type (r)	Range	Relation	Significance
	(+0.10 to +0.24)	Very weak positive correlation
r is 1 direct (positive)	(+0.25 to +0.49)	Weak positive correlation
	(+0.50 to +0.74)	Average positive correlation	Significant (p-value < 0.0) Highly significant (p-value < 0.01) Not significant (p-value > 0.05)
	(+0.75 to +0.89)	Strong positive correlation
	(+0.90 to +0.99)	Very strong positive correlation
	(+1)	Perfect positive correlation
	(−0.10 to −0.24)	Very weak negative correlation
r is 1 inverse (negative)	(−0.25 to −0.49)	Weak negative correlation
	(−0.50 to −0.74)	Average negative correlation
	(−0.75 to −0.89)	Strong negative correlation
	(−0.90 to −0.99)	Very strong negative correlation
	(−1)	Perfect negative correlation

Note: The table shows the correlation indexes and the significance level of the results. Source: [12].

.

4.4. Testing the General Hypothesis

The analysis of the testing of the general hypothesis, presented in

Table 22. Correlation between business model and entrepreneurial capabilities.

			Entrepreneurial Capabilities	Business Model
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.755 **
		Sig. (bilateral)		0.000
		N	146	146
	Business model	Correlation coefficient	0.755 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, focuses on evaluating the relationship between the “Business Model” and the “Entrepreneurial Capacities” of older adults in the “Pension 65” program in the District of Llaylla, Satipo.

The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test, and with a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 22, Spearman’s Rho correlation index is 0.755 with a p-value of 0.000, indicating a strong positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between the business model and entrepreneurial capabilities.

4.5. Specific Hypothesis Testing

The analysis of the testing of Specific Hypothesis 01, presented in

Table 23. Correlation between entrepreneurial capabilities and market segment.

			Entrepreneurial Capabilities	Market Segment
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.728 **
		Sig. (bilateral)		0.000
		N	146	146
	Market segment	Correlation coefficient	0.728 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between the “Entrepreneurial Capacities” and the “Market Segment” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis suggests that there is no direct relationship between these variables, while the alternative hypothesis proposes the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 23, Spearman’s Rho correlation index is 0.728 with a p-value of 0.000, indicating an average positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial capabilities and market segment.

The analysis of the testing of Specific Hypothesis 02, presented in

Table 24. Correlation between entrepreneurial capabilities and value proposition.

			Entrepreneurial Capabilities	Value Proposition
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.729 **
		Sig. (bilateral)		0.000
		N	146	146
	Value proposition	Correlation coefficient	0.729 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between the “Entrepreneurial Capacities” and the “Value Proposition” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 24, Spearman’s Rho correlation index is 0.729 with a p-value of 0.000, indicating an average positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial capabilities and value proposition.

The analysis of the testing of Specific Hypothesis 03, presented in

Table 25. Correlation between entrepreneurial capacities and service channels.

			Entrepreneurial Capabilities	Service Channels
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.762 **
		Sig. (bilateral)		0.000
		N	146	146
	Service channels	Correlation coefficient	0.762 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between the “Entrepreneurial Capacities” and the “Channels of Care” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 25, Spearman’s Rho correlation index is 0.762 with a p-value of 0.000, indicating a strong positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial capabilities and attention channels.

The analysis of the testing of Specific Hypothesis 04, presented in

Table 26. Correlation between entrepreneurial capabilities and client relationship.

			Entrepreneurial Capabilities	Client Relationship
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.733 **
		Sig. (bilateral)		0.000
		N	146	146
	Client relationship	Correlation coefficient	0.733 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between “Entrepreneurial Skills” and “Relationship with clients” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 26, Spearman’s Rho correlation index is 0.733 with a p-value of 0.000, indicating an average positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial skills and customer relationships.

The analysis of the testing of Specific Hypothesis 05, presented in

Table 27. Correlation between entrepreneurial capabilities and income sources.

			Entrepreneurial Capabilities	Income Sources
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.721 **
		Sig. (bilateral)		0.000
		N	146	146
	Income sources	Correlation coefficient	0.721 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between the “Entrepreneurial Capacities” and the “Sources of Income” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 27, Spearman’s Rho correlation index is 0.721 with a p-value of 0.000, indicating an average positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial skills and sources of income.

The analysis of the testing of Specific Hypothesis 06, presented in

Table 28. Correlation between entrepreneurial capabilities and key resources.

			Entrepreneurial Capabilities	Key Resources
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.701 **
		Sig. (bilateral)		0.000
		N	146	146
	Key resources	Correlation coefficient	0.701 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between the “Entrepreneurial Capacities” and the “Key Resources” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 28, Spearman’s Rho correlation index is 0.701 with a p-value of 0.000, indicating an average positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial capabilities and key resources.

The analysis of the testing of Specific Hypothesis 07, presented in

Table 29. Correlation between entrepreneurial capabilities and key activities.

			Entrepreneurial Capabilities	Key Activities
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.770 **
		Sig. (bilateral)		0.000
		N	146	146
	Key activities	Correlation coefficient	0.770 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between the “Entrepreneurial Capacities” and the “Key Activities” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 29, Spearman’s Rho correlation index is 0.770 with a p-value of 0.000, indicating an average positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial capabilities and key activities.

The analysis of the testing of Specific Hypothesis 08, presented in

Table 30. Correlation between entrepreneurial capabilities and key partnership.

			Entrepreneurial Capabilities	Key Partnerships
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.705 **
		Sig. (bilateral)		0.000
		N	146	146
	Key partnerships	Correlation coefficient	0.705 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between “Entrepreneurial Capacities” and “Key partnership” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 30, Spearman’s Rho correlation index is 0.705 with a p-value of 0.000, indicating an average positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial capabilities and key partnership.

The analysis of the testing of Specific Hypothesis 09, presented in

Table 31. Correlation between entrepreneurial capabilities and cost structure.

			Entrepreneurial Capabilities	Cost Structure
Spearman’s Rho	Entrepreneurial capabilities	Correlation coefficient	1.000	0.740 **
		Sig. (bilateral)		0.000
		N	146	146
	Cost structure	Correlation coefficient	0.740 **	1.000
		Sig. (bilateral)	0.000
		N	146	146

** Correlation is significant at the 0.01 level (bilateral). Note: From software—SPSS 26.

, examines the relationship between the “Entrepreneurial Capacities” and the “Cost Structure” of older adults in the “Pension 65” program in the District of Llaylla, Satipo. The null hypothesis states that there is no direct relationship between these variables, while the alternative hypothesis suggests the opposite. Using Spearman’s Rho statistical test and a significance level of α = 0.05, the decision rule is established: if p > α, the null hypothesis is accepted; if p ≤ α, it is rejected. According to the results shown in Table 31, Spearman’s Rho correlation index is 0.740 with a p-value of 0.000, indicating an average positive correlation. Therefore, the null hypothesis is rejected and the alternative hypothesis is accepted, confirming the existence of a direct relationship between entrepreneurial capabilities and cost structure. These results support each specific hypothesis, particularly highlighting strong associations such as initiative with value proposition and teamwork with key activities, confirming the theoretical model’s internal consistency.

Basically, no negative correlations were identified, and all results were statistically significant at the 0.01 level. These findings are consistent with prior studies [13,16] that found positive associations between entrepreneurial attributes and business model construction, particularly in educational or rural economic development contexts. The statistical evidence from this study thus reinforces the viability of incorporating entrepreneurial and business training into social assistance programs such as Pensión 65. Doing so could transform these programs from passive support mechanisms into proactive development platforms, aligning with broader policy goals for economic inclusion and productive aging.

5. Discussion

5.1. Analysis and Discussion of Results

The findings of this study strongly align with its general and specific objectives, which sought to determine the relationship between business model components and entrepreneurial capacities among older adults enrolled in the Pensión 65 program in Llaylla, Satipo. The results provide compelling evidence that elderly individuals in vulnerable contexts possess latent entrepreneurial potential that, when paired with structured business tools, can significantly enhance their economic and social participation. The general objective—to examine the relationship between business model development and entrepreneurial capacities—was achieved through robust correlation analyses. The statistically significant and strong positive association (r = 0.755, p < 0.001) suggests that older adults with higher levels of creativity, perseverance, initiative, teamwork, and self-confidence are better positioned to understand and engage with the strategic components of a business model. This supports the view that entrepreneurship is not limited by age but rather by access to knowledge and institutional support [26,33].

Regarding the first specific objective, which aimed to analyze the relationship between entrepreneurial traits and each of the nine business model components, the results confirmed positive and statistically significant correlations across all dimensions. For instance, initiative showed a strong correlation with the value proposition component (r = 0.721), indicating that older adults who actively pursue opportunities are more capable of identifying and communicating what makes their product or service valuable. This finding echoes previous research in both educational and rural settings [13,16]. Moreover, the link between perseverance and revenue streams (r = 0.683) highlights the importance of sustained effort in achieving economic outcomes, especially in resource-limited environments. These results align with the insights of reference [22], who emphasized perseverance as a defining quality of entrepreneurial success in adverse conditions.

The second specific objective—to identify gaps in knowledge or institutional support—was indirectly addressed through the descriptive findings. While participants demonstrated strong entrepreneurial dispositions, their understanding of business model components such as cost structure and key partnerships remained limited. This gap underscores the need for targeted training and access to formal networks, which are essential to scale up microenterprises and improve sustainability [4,20]. Based on these findings, it is recommended that Pensión 65 integrate structured training modules in business model development, including key components such as cost structures and value propositions. This would allow older adults to more effectively translate their entrepreneurial traits into viable economic initiatives. Lower performance in dimensions like cost structure and partnerships may be due to their abstract nature and participants’ limited access to formal financial or institutional training.

Finally, in relation to the third specific objective, the results support the development of policy recommendations to incorporate entrepreneurial training into Pensión 65. As shown in national programs like “Productores Ancestrales” [8], older adults can succeed as micro-entrepreneurs when supported through technical assistance, education, and strategic alliances.

In sum, this study confirms that entrepreneurial capacity and business modeling are synergistic, even among older adults in poverty. Recognizing and cultivating these capacities within social programs can shift the paradigm from welfare dependency to productive inclusion, fostering dignity, autonomy, and sustainable development.

5.2. Comparison with Previous Studies

The results of this study are consistent with a growing body of national and international research that highlights the interdependence between entrepreneurial capacities and the development of business models, particularly in vulnerable or under-resourced populations. This alignment with the existing literature reinforces the relevance and applicability of this study’s findings. Nationally, the results resonate closely with the findings of reference [13], who investigated the correlation between entrepreneurial capacity and business model generation among business administration students in Apurímac. Reference [13] identified a moderate positive correlation (r = 0.505), similar in direction though somewhat lower in magnitude than the strong correlation (r = 0.755) observed in the present study. Both studies affirm that entrepreneurial traits—especially initiative and creativity—are critical for shaping viable business strategies. Likewise, reference [16], in her research on inclusive rural enterprises supported by the FONCODES project in Tarapoto, emphasized the importance of structured managerial support in fostering entrepreneurial capacity. Her findings align with the current study’s conclusion that older adults possess substantial entrepreneurial potential that can be harnessed through proper guidance, particularly in the formulation of business models using frameworks such as the Business Model Canvas [6]. In a similar vein, reference |7] demonstrated that business model design contributed to the growth and resilience of Andean cooperatives. This mirrors the present study’s observation that components such as value proposition, revenue streams, and key partnerships are essential but are often underdeveloped areas for older adult entrepreneurs. Both studies suggest the need for technical training and strategic planning to strengthen local ventures. These results are consistent with previous national studies that reported similar moderate-to-strong correlations between entrepreneurial traits and business planning, particularly in rural and educational contexts [13,16]. Such alignment reinforces the validity of the findings and highlights the broader relevance of strengthening entrepreneurial training within social protection frameworks.

International comparisons further support these conclusions. In reference [14], entrepreneurial intention in Mexican university students is primarily determined by entrepreneurial capacity and the teaching–learning process, and not teacher training. This is comparable to the case in Llaylla, where elderly participants show high entrepreneurial dispositions but lack systematic instruction in business modeling. Similarly, reference [21], examining artisans, concluded that limited knowledge and training were significant barriers to effective business model implementation. The parallels with the older adults in Llaylla are clear: despite their productive potential, gaps in formal knowledge about cost structure, partnerships, and customer segmentation hinder scalability and long-term sustainability. Moreover, reference [18] found a link between emotional intelligence and entrepreneurial capacity among adult entrepreneurs in Piura, reinforcing the idea that psychological attributes like perseverance and self-confidence—dimensions also measured in this study—are key predictors of entrepreneurial behavior and strategic planning.

In sum, the results of this research are in strong agreement with prior studies. They confirm that entrepreneurial capacities are not only prevalent in diverse populations—including the elderly—but also function as enablers of strategic business thinking. The findings contribute to a broader evidence base advocating for the integration of business model training into social assistance programs, thus transforming them into vehicles for economic empowerment and inclusion.

5.3. Recommendations for Future Research

Based on the findings and limitations of this study, several recommendations emerge for future research aimed at deepening the understanding of the relationship between entrepreneurial capacities and business model development among older adults, particularly in vulnerable or rural populations.

• Future research could build upon these findings by evaluating whether targeted training in specific business model components—such as revenue streams or customer segmentation—significantly enhances entrepreneurial outcomes among older adults. This would allow for a more precise understanding of how the competencies identified in this study translate into practical business success.
• Expand the Geographical Scope: This study was limited to the district of Llaylla, Satipo, which, while representative of rural Andean–Amazonian populations, does not capture the diversity of socioeconomic and cultural realities across Peru. Future research should include comparative studies across multiple districts or regions, such as coastal and highland zones, to identify geographical patterns and regional disparities in entrepreneurial engagement among Pensión 65 beneficiaries. Such work could also explore differences in access to training, markets, or institutional support.
• Adopt Longitudinal Designs: Given that this study employed a cross-sectional design, it was not possible to assess how entrepreneurial capacities or business model understanding evolve over time. Among the various lines of future inquiry, longitudinal studies are especially crucial to understanding the long-term impact of business training interventions on entrepreneurial behavior. Future research should consider longitudinal approaches to evaluate the impact of specific interventions, such as training programs, technical assistance, or institutional partnerships, on the entrepreneurial trajectories of older adults. This would provide more robust evidence on causality and long-term outcomes, aligning with findings from references [16,17].
• Incorporate Mixed Methods: While the quantitative approach provided measurable correlations, it did not capture the rich, subjective experiences of participants. Future studies could adopt mixed methods designs, combining statistical analysis with in-depth interviews or case studies. This would allow researchers to explore motivations, perceptions, barriers, and enabling factors in more nuanced ways, as recommended in studies focused on emotional intelligence and entrepreneurship [18].
• Explore Institutional and Policy Dimensions: There is a need for research that critically examines the institutional frameworks surrounding programs like Pensión 65, particularly in terms of their capacity to integrate entrepreneurial training. Future studies should assess the role of public–private partnerships, local governments, and civil society organizations in supporting productive aging. Such research could build on international case studies and models that have successfully linked social assistance with inclusive entrepreneurship [13,14].
• Investigate Technology and Innovation in Older Adult Enterprises: Future research could examine the role of digital tools, e-commerce platforms, and agroecological innovation in supporting older adult entrepreneurs. Given that many rural elderly lack digital literacy, exploring how adapted technologies or intermediaries could bridge this gap may open new avenues for market access and productivity [11].
• Evaluate Gender-Specific Dynamics: Future research should also explore gender differences in entrepreneurial capacity and business development among elderly populations. Understanding how gendered experiences shape access to resources, social networks, and institutional recognition can inform more inclusive program design and support frameworks.

In sum, future research should aim to broaden, deepen, and contextualize the analysis of elderly entrepreneurship, contributing to a more holistic and policy-relevant understanding of aging, productivity, and economic inclusion in Latin America. Additionally, potential endogeneity or omitted variable bias may limit causal interpretations, as unobserved factors could influence both entrepreneurial dispositions and business model awareness.

6. Conclusions

This study set out to explore the relationship between business model components and entrepreneurial capacities among older adults participating in the Pensión 65 program in Llaylla, Satipo. The results yield both general and specific conclusions that reinforce this study’s theoretical foundations and provide valuable insights into policy and practice. The research confirms a statistically significant and strong positive relationship between entrepreneurial capacities and business model components among older adults living in conditions of poverty. Participants who scored higher in traits such as initiative, creativity, perseverance, self-confidence, and teamwork were more likely to understand and engage with the strategic dimensions of a business model. This finding suggests that the elderly population possesses not only the disposition but also the cognitive and experiential resources necessary to develop entrepreneurial ventures when given the proper tools and support. This research challenges the prevailing perception of older adults in welfare programs as passive beneficiaries. Instead, it positions them as potential agents of economic development, capable of contributing meaningfully to their communities if empowered through capacity-building and structured business education.

This study identified strong correlations between specific entrepreneurial traits and key business model components. For example, initiative was closely linked to value proposition (r = 0.721), and perseverance correlated strongly with revenue streams (r = 0.683). These associations highlight that individual traits directly influence how older adults conceptualize, structure, and sustain economic activities. These findings are consistent with prior studies depicted in this document, which also found positive relationships between entrepreneurial ability and business planning. Despite the presence of entrepreneurial traits, participants demonstrated limited understanding of the more technical business model components, such as cost structure and key partnerships. Only a minority reported high familiarity or application of these elements. This indicates a clear gap between personal entrepreneurial capacity and strategic business execution, reinforcing the need for educational interventions tailored to older adult populations. The results support a rethinking of Pensión 65 from a strictly welfare-oriented initiative to one that includes entrepreneurial empowerment. Programs such as “Productores Ancestrales” already demonstrate the feasibility of integrating productive activities among older adults. Expanding this approach through training in business model design and strategic planning could significantly enhance the autonomy, dignity, and economic resilience of elderly participants.

In conclusion, this study provides empirical evidence that supports a paradigm shift from viewing older adults as dependents to recognizing them as productive actors with valuable experience and capacity for innovation. Strengthening this potential through targeted support would contribute not only to the well-being of elderly citizens but also to the broader goals of social inclusion and sustainable rural development. Ultimately, elderly entrepreneurship should be seen as a key instrument for advancing inclusive rural development, especially when integrated into public social assistance frameworks.