Determining the Factors to Improve Sustainable Performance in a Medium-Sized Organization

Abstract

Small- and medium-sized organizations rely heavily on their internal configuration to achieve sustainable performance. However, their internal structure often represents an obstacle to achieving that goal. To help organizations achieve sustainable performance, we develop a research framework using the viable system model (VSM) to evaluate the relationship between organizational factors. We adopt a systems perspective: (1) The VSM serves as a theoretical foundation to define factors to be evaluated through a conceptual model; (2) social network analysis to obtain information for the conceptual model; (3) partial least squares path modeling to test the proposed model with 150 employees; and (4) VSM to suggest changes. The nine hypotheses are supported, suggesting that improving sustainable performance is related to adopting a network structure and focusing on relational factors to reduce inconsistencies between operations and coordination systems. This article differs from previous studies, as it proposes a methodological coupling to assist decision-makers in improving organizational balance and performance. Additionally, it can encourage academics to reconsider structural factors, enabling them to allocate resources more precisely and enhance effectiveness.

1. Introduction

Tourism is vital to Mexico’s economy, contributing around 9.5% of GDP. Small- and medium-sized enterprises (SMEs) that offer lodging services are crucial to the economy, constituting 65% of active organizations [1]. However, the economic recovery of Mexican tourism SMEs has yet to be achieved, and around two and a half million jobs are at risk [2]. These SMEs face challenges jeopardizing their equilibrium, sustainable performance (hereinafter SUP), and capacity for continuous environmental adaptation [3]. Improving their organizational structures is critical for their viability and adaptation to a changing environment.

SUP refers to the organizational state achieved by improving operating units’ capabilities while maintaining autonomy and using appropriate management and control mechanisms to serve the purpose of the system [4]. SUP is an important study area because of the current operating context’s complexity [5], the crisis of organizational models, and their limited responsiveness [6]. SMEs must integrate organizational components to foster continuous improvement [7]. SUP is also hampered by poor planning, which results in inconsistencies between strategies and metrics, and a limited ability to explore the environment and formulate actions based on data analysis to adapt continuously [8]. However, addressing SUP offers opportunities for SME managers to operate more efficiently. Ref. [9] established that some “day-to-day” aspects that hinder SUP are defects, unnecessary movements, inefficient use of employee knowledge, and overprocessing services.

Despite the relevance of SUP, it has not received the same level of attention as strategic planning or decision-making [8,10]. Limited research hinders companies from developing adaptive capabilities and leveraging resources for value. As a result, the SMEs’ success factors remain a black box for managers. In this sense, SUP requires reconsidering the perspective that reduces it to a univariate problem [11].

This article advocates for managers to take a holistic approach to achieving sustainable operations and bridging the SUP gap [12]. This method considers the interaction of various factors, such as organizational structure, functions, and environment [13]. The theoretical foundation of this article is the viable system model (VSM) [14], specifically the operations or S1 function, which is the essence of any company. Thus, the VSM framework enables addressing SUP due to the operating units’ harmonious integration and regulation, with sufficient autonomy to use structural, relational, and environmental components to maintain viability [9]. Considering this, the theoretical foundation allows us to establish relationships between variables to propose a conceptual model.

Our article takes the following form. First, a literature review is presented, emphasizing the need for a systematic study approach to SUP problems. Second, in the methodology section, we use social network analysis (SNA) and partial least squares path modeling (PLS-PM) to design a conceptual model and validate the construct [8]. We want to clarify that we are not presenting a traditional PLS-PM work; the hypotheses are not stated immediately after the literature review or in the methodology section. Instead, PLS-PM is incorporated into the systems thinking cycle. Finally, we propose a brief conclusion, highlight theoretical implications, and suggest future academic research.

2. Literature Review

In line with [8], SUP is defined as an emergent property within an organization that results from the harmonious integration of operational units with control and coordination mechanisms, and it should promote organizational learning and autonomy [15]. Understanding various factors, such as organizational design, processes, internal collaboration networks, and external information analysis, should result in SUP. These factors encourage learning at all levels, provide feedback to control tools, and allow adjustments to influence adaptation and continuous improvement. The first approaches to the SUP problem were developed by [16,17]. They primarily focused on the relationship between internal organizational factors.

SUP has been approached through diverse perspectives, including economics [18], organizational theory [19], social and relational framework [20], engineering [21] and ecology [22]. These various perspectives agree that SUP involves the interrelationship of various organizational factors to meet the needs of both internal and external customers and achieve business transcendence and adaptation [15,23]. However, there are still barriers to overcome regarding its adoption and implementation, particularly in the context of SMEs [6,9]. One of the challenges is the reductionist management viewpoint, in which problem solvers tend to reduce complex problems to single-factor situations, and systems are designed to measure indicators that are far from an integral approach [17]. This approach results in several management efforts that fall into a loop that focuses only on measuring specific factors or systems without connecting the information. Measuring only the process effectiveness [18], financial performance [24], variations in personnel management processes [25], and organizational climate [26] are some examples. SUP is expected to be linked to environmental and political issues. This notion of SUP has resulted in interventions focused on changing organizational culture by centralizing management teams and their interaction with external actors to develop and use sustainable resources [27]. However, due to the addition of complicated concepts to daily procedures, Ref. [12] contended that this approach creates gaps between the strategy design and the key processes of any organization. Ref. [25] argued that many companies lack an organizational model that allows them to understand the systemic nature of the organization. As a result, they frequently measure simple elements without a clear action plan for continuous improvement. Ref. [28] proposed the systems thinking approach as a framework for addressing the SUP problem holistically. They used the Vanguard method to rethink an organization’s processes by simplifying them and combining them with precise control mechanisms and consistent alignment with organizational objectives at all levels. Agreeing with [21], Ref. [27] specified that implementing the systems engineering framework enables organizations to reduce operations-related waste. However, Ref. [29] also noted that more work is required to adopt and deploy SUP due to the integration of critical components of an organization. According to [30], SUP is often treated simplistically as a metric to monitor results on corporate social engagement, creating a gap between strategy and implementation. To address this, Ref. [31] stressed the importance of clarifying the concept of SUP and supplementing company management style with factors such as attention to environmental degradation, workspace and condition improvement, and employee accountability. Given that any company’s resources and capabilities are limited, Refs. [6,32] suggested using multicriteria analysis tools to consider the greatest number of employees and guide consensus construction. This will allow organizations to devote resources to long-term operations and continuous adaptation while remaining socially responsible. Refs. [6,33] proposed a pragmatic approach to increasing organizational SUP. Their recommendations include concentrating solely on process efficiency and effectiveness, ensuring proper implementation of operational regulations, strengthening decision-making processes, and motivating personnel participation through a reward system. However, Refs. [4,34] argued that tying sustainability achievement solely to a reward system can create problems at different levels that could compromise the integrity of an organization. In line with [31], Ref. [35] proposed adopting a constructivist framework with multicriteria decision analysis methods to address problematic situations that hinder SUP adoption and help employees in developing a shared vision that can guide organizational capabilities toward strengthening organizational capabilities to face a complex environment.

To expand the review on the scope of this article, we summarize in

Table 1. Articles addressing SUP.

Study	Factors	Analytical Approach	Findings
[36]	Discovering system, innovating system, selecting system, executing system, transferring system, reflecting system, acquiring knowledge from environment system, contributing knowledge to environment system, building organizational memory system.	Criticist conceptualmodel	Management practices should jointly address the structure, precise processes, policy and culture of an organization to enable continuous learning and adaptation, the policy and culture of an organization to allow continuous learning and adaptation.
[37]	Commitment to learning, shared vision, openmindedness, learning orientation, performance orientation, leadership quality, performance.	Interactive learning	A positive influence of the leadership role, the shared vision and the principle of operational management to generate a strategic learning pathway and influence performance.
[38]	Motivation, need for satisfaction, performance management, performance appraisal, distributive justice, work strategies, performance improvement.	Dialogic method	High level of distributive justice and precise performance management leads to improved performance.
[39]	Best HRM practices, knowledge management, organizational learning capability, organizational capabilities, organizational performance.	Systematic analysis	Best HRM practices and knowledge do not significantly influence the organization’s overall learning and, thus, the company’s positive performance as a whole.
[40]	Degree performance, professionalism of process management, impact of process managers, usage of methodology and standards.	Principal component analysis, Multiple linear regression	Essential processes and operations are highly influential factors in designing the basis of an organizational sustainable performance strategy.
[41]	Ecological dimension, teleological dimension, psychosociological, technological, retilogical, public policies.	Mixed logit method, Structural Equation Modeling	Large companies are more prone to Competitive intelligence. SMEs face difficulties, especially structural ones. Therefore, SMEs should focus on the technological and teleological dimensions and the generation of internal collaboration networks.
[20]	Business ties, government ties, institutional framework, methodological framework, economic performance, and operational performance.	Meta-Analysis	SME managers should invest in internal linkages. The authors suggest promoting guanxi in SMEs as it increases organizational ownership and sustainable performance.
[42]	Infrastructure and technology, lack of financial resources, culture, customer base, government policy and support.	Factor analysis, ANOVA	Innovation-focused or innovation-oriented SMEs have higher organizational performance compared to those that are not focused compared to those that pursue fewer types of innovations.
[43]	Strategic resources, network resources, strategic alliances, network structure, organizational flexibility, management complexity.	Criticist conceptual model	The increase in management complexity positively impacts achieving objectives, reducing process variability and adaptive capacity.
[44]	Organizational process, organizational structure, communication channels, resource management, performance	Statistical process control	Monitoring and control of variability positively influences sustainable performance.
[45]	Organizational structure, organization channels, feedback mechanisms, coordination mechanisms, management complexity, maintenance planning.	Statistical process control	An organization’s core processes or activities should be considered critical because their correct integration with other organizational factors affect the balance and capacity to adapt to the environment.
[46]	Staff job satisfaction, cash funds, good processing, customer satisfaction, carbon emissions.	System Dynamics	Sustainable performance has focused on its external relationships or impacts. Factors such as staff job satisfaction and sound processing positively influence SUP.
[47]	Skills, operational governance, data handling, resilience, coordination, productivity, sales change.	Mixed methods	Data handling, Coordination and skills positively influence organizational dynamism and resilience.
[48]	Network capability, strategic flexibility, organizational ambidexterity, strategic performance.	Structural Equation Modeling	Network capability and Strategic flexibility directly and positively affect strategic performance.
[10,49]	Production, efficiency change, technological change, sustainable performance.	Data Envelopment Analysis	Efficiency change and Technological change are positively related to the increased organizational capacity to foster sustainable performance.
[50]	Intellectual capital, integrative mechanisms, performance.	Partial Least Squares, Ordinary Least Squares	Organizations should strive for intellectual capital as it positively influences performance (integrative mechanisms act as a mediating factor).
[51,52]	Environmental management control systems, environmental strategies, organizational capabilities sustainable performance.	Partial Least Squares Path Modeling	Environmental management control systems do not influence organizational capabilities and have a medium influence on environmental strategies. Sustainable performance must combine factors related to operations and process control.
[53]	Knowledge-based HRM practices, social capital, knowledge sharing, innovative performance.	Structural Equation Modeling	Promoting strategic training and identifying and disseminating knowledge among employees fosters innovation and impacts sustained performance. Improving human resources management practices is critical to generating the conditions for employees to pursue the company’s integrity.
[30,54]	Reflective capacity, self-reflection, reflection, cognitive complexity, cognitive flexibility, holistic thinking, behavioral complexity, dialectical thinking, strategic decision-making, absorptive capacity, learning goal orientation, sense-making, sustainable performance.	Multivariate linear regression, Structural Equation Modeling	Managers and directors should rethink the idea of resilience and consider the idea of sustainable performance. Reflective capacity, cognitive complexity, holistic thinking, decision-making, and  absorptive capacity enable managers and directors to foster sustainable performance.
[29]	Strategic flexibility, structural flexibility, communication, decision-making, formalization.	Exploratory and Confirmatory Factor Analysis, Clustering and Decision Tree Analysis	Managers and directors should rethink the idea of resilience and consider the idea of sustainable performance. Reflective capacity, cognitive complexity, holistic thinking, decision-making, and absorptive capacity enable managers and directors to foster sustainable performance.
[52]	Hotel environmental management initiative, environmental strategies, employees eco-friendly behaviour, hotel’s sustainable performance.	Partial Least Squares Path Modeling	Hotel environmental management initiative is positively associated with sustainable performance. Sustainable performance is generated by focusing on the industry analysis of a given organization.
[55,56]	Acquiring talented employees, development of talented employees, talent leadership, development of strategic talent management, designing talent teams, development of strategic agile management, competitiveness, support agile management culture of the organization, agile leadership.	Structural Equation Modeling	Factors related to strategic talent management positively influence agile strategic management. Agile strategic management is a predecessor of sustainable performance.
[17,57]	Technological capabilities, big data analytics capabilities, strategic flexibility, resilience capabilities.	Structural Equation Modeling	Technological capabilities positively influence resilience capabilities.
[58,59]	Perceived benefits, technological complexity, infrastructure capabilities, organization resources, organization management support, government legislation, big data adoption, sustainable marketing, sustainable operations.	Partial Least Squares Path Modeling, Neural networks	The influence of adopting big data in SMEs enables sound business decisions by improving the analysis of the environment and translating that information into data that can be used to improve management.

the studies that identified factors and used various analytical tools to suggest alternatives for understanding and operationalizing SUP in the organizational context.

Table 1 presents various approaches to addressing problems with understanding and implementing SUP. For example, some studies on SUP have taken a purely conceptual approach, focusing on organizational culture, adaptation, and continuous learning [36], whereas others have considered soft factors such as motivation and human resource management [38,39]. Network analysis and social structures are also suggested as perspectives for linking group measures, allowing managers to increase capabilities and remain competitive [20,43]. Statistical analysis techniques, such as multiple regression models [40], clustering, and decision tree analysis [29], and structural equation models [48,52], are also reported from a statistical analysis standpoint. These models explore various relationships between organizational factors, such as the positive impact of flexibility in strategy design and implementation, the importance of investing in social capital to promote strategies that provide an organization with autonomy, and the ability to respond adequately to environmental changes.

Additionally, Table 1 lists articles that assessed the impact of various factors on SUP using system dynamics and network analysis. Infrastructure capabilities, organizational management support, and coordination mechanisms are among these factors [26,46,58,60]. However, these studies have limited their scope to only the analysis of individual factors and have sought to adopt an organizational framework that facilitates implementation at all recursive levels. The works presented in Table 1 analyzed the relationship between factors that facilitate SUP, but none considered functional- or systemic-based factors that would enable any organization in any context to move toward the adoption and deployment of SUP at all levels. Refs. [61,62] emphasized the importance of adopting an integral perspective that enables understanding of SUP and its components to overcome implementation barriers in SMEs in the tourism sector. They reframed the gap between SUP and basic operations deployment to achieve SUP. Based on this last point, we must address the gap that prevents tourism SMEs from developing their structure to achieve survival while not losing sight of the primary goal of continuity.

3. Methodology

Our research is supported by the systemic method, which promotes methodological complementarity to understand better a problem [63]. To understand the relationship that fosters SUP in tourism organizations, we suggest combining SNA, PLS-PM, and VSM. This helped us to provide recommendations based on the VSM [8]. Following the approach of [64,65], we employ the tools as follows: (a) SNA is used to identify factors that hampered SUP; (b) the information obtained from SNA is employed as input to propose a conceptual model that can trigger organizational change; and (c) PLS-PM is adopted to estimate the statistical validity of the relationships proposed in the model. In summary, the following phases are developed:

• Phase 1: Identifying issues. We identify potential issues with SUP implementation in organizations. To accomplish this, we review the structural models reported in the literature and gathered information on S1 using network questions. The information is represented through networks, and the questions are based on VSM concepts.
• Phase 2: Component selection. We choose the minimum but most important components to configure a conceptual model that can be modified to incorporate the SUP [8]. We calculate the correlation between the network constructed in Phase 1 (Equations (1) and (2)). We review the literature, particularly the structural models proposed by [41,48,56], to ensure the coherence of integrated factors:

  $$cor(G,H)={\displaystyle \frac{cov(G,H)}{\sqrt{cov(G,G)cov(H,H)}}}$$

  (1)

  where:
• $\mathrm{cov}(G,H)$ is the covariance between graphs G and H.
• $\mathrm{cov}(G,G)$ is the graph G’s covariance with itself, equivalent to the variance of the elements of the graph G’s adjacency matrix.
• $\mathrm{cov}(H,H)$ the graph H’s ccovariance with itself, equivalent to the variance of the elements of the graph H’s adjacency matrix.
  where the graph’s covariance is defined as:

  $$cov(G,H)={\displaystyle \frac{1}{\left(\genfrac{}{}{0pt}{}{\left|V\right|}{2}\right)}}\sum _{\{i,j\}}(A_{ij}^G-\mu G)(A_{i,j}^H-\mu H)$$

  (2)

  where:
• $\left|V\right|$ is the number of nodes in the graphs.
• $\left({\displaystyle \genfrac{}{}{0pt}{}{\left|V\right|}{2}}\right)$ is the number of unique pairs of nodes, equal to ${\displaystyle \frac{\left|V\right|\left(\right|V|-1)}{2}}$.
• ${\sum }_{i,j}$ denotes the sum over all pairs of nodes $(i,j)$ .
• $A_{ij}^G$ and $A_{ij}^H$ are the elements of the adjacency matrices of the graphs G and H, respectively.
• G is the mean of the elements of the adjacency matrix $A^G$ of the graph G, calculated as:

  $$\mu G={\displaystyle \frac{1}{\left(\genfrac{}{}{0pt}{}{\left|V\right|}{2}\right)}}\sum _{\{i,j\}}{A}_{ij}^G$$

  (3)
• $A^H$ is the mean of the elements of the adjacency matrix $A^H$ of the graph H, calculated similarly.
• Phase 3: Expression of the conceptual model. This step integrates the identified factors to develop a conceptual model and express working hypotheses that can be validated to help decision-makers. The goal is to facilitate organizational change and to operate from a SUP standpoint.
• Phase 4. Validation. We use PLS-PM [66] to assess the congruence of the proposed conceptual model with the context and assess its relevance for organizational implementation.
• Phase 5. Propose changes. Based on the VSM [14], we propose recommendations to promote SUP.

4. Information Collection and Analysis

Ref. [14] suggested that operations (S1) are the core of any organization. We focus on S1 and use SNA to identify patterns that could hinder the SUP, as SNA is an analytical tool that allows us to evaluate relationships at the micro and macrolevels of almost any system [19]. In Phases 1 and 2 of the described methodology, we apply the SNA from the top down. The managers’ support is required to encourage employee participation while maintaining anonymity [8]. We gather data from a tourism SME comprising 200 employees, but only 150 of them fully participate.

Table 2. Questions to gain insight about S1.

S1 Factor	Question
Tasks	On whom do you depend to accomplish your tasks?
Communication between operators	Whom do you consult for professional advice or support to improve your work?
Resource allocation	Who do you get the resources from that you need to perform your tasks?
Relationship between employees and managers	To whom do you report your task progress?
Collaboration	Name the collaborators you assist in their work due to your friendship with them?
Coordination	Who is responsible for establishing clear rules to coordinate your work and ensure that you meet your weekly goals?

Source: Based on [67].

shows the questions we asked about S1.

We aim to understand the correlation between the networks and their relationship to the S1 concept. This information is then used as input to develop the conceptual model. It is worth noting that a correlation of at least 0.30 is required to connect two graphs [68]. Clarifying the previous idea, we define each network as $G_i=\left(V,E_i\right)$, where V is the set of nodes, and $v\in V$ denotes each participant. At the same time, $E_i$ is the set of connections. Then, a connection exists between $v_j$ and $v_k$ in $G_i$ if the employees agree on the perceived importance of a particular organizational factor. Such co-occurrence is defined by the participants’ responses, where $r_j^i$ and $r_k^i$ are the responses of the individuals corresponding to nodes $v_j$ and $v_k$ in factor i, respectively.

Based on the above, if we consider $G_1,G_2\dots ,G_n$, where $G_i$ corresponds to a factor expressed in Table 2, each network can be represented by an adjacency matrix ${\mathbf{A}}_{ij}$, where $A_i(j,k)=1$ if a connection exists, or 0 otherwise. As mentioned earlier, a match exists between two people if they rate a particular factor of importance in the same rank (e.g., four or five). Adjacency matrices allow calculating the covariance by comparing the adjacency matrices, i.e., first, it is necessary to obtain the differences between each value in the matrices and the mean of all the values in their respective matrices. Then, we multiply the corresponding differences of the two graphs for each pair of nodes and average these products. The final average is the covariance indicating how much the structure in one graph resembles another. After obtaining the covariance, we calculate the standard deviations of each adjacency matrix to normalize it. Then, we divide the covariance by the product of the standard deviations of the two adjacency matrices. We use the Igraph package [69] in R software to examine the relational data and determine the degree of correlation between the networks.

The conceptual model survey is based on the proposals of [41,48,52,56]. The evaluation scale used is a Likert scale, with one indicating complete disagreement and five indicating complete agreement. Ref. [66] suggested using at least 100 observations with PLS-PM to ensure reliable results. Given that our application context is limited to one company, we follow the recommendation of [70] and distribute the surveys to 200 company employees by email. We receive complete responses from 150 collaborators, including 145 employees and 5 managers.

5. Results

We present the results in the order of the phases described in Section 3. In Phases 1 and 2, using SNA helps us gain insight into how participants viewed the factors that could impact SUP adoption in SMEs. Figure 1 depicts six networks that display the connections between managers (yellow nodes) and staff (gray nodes) based on the organizational factor evaluated. Subsequently, we examine the network correlation to determine whether the organizational factors are relevant and the degree of relationship between them.

Table 3. Correlations among networks.

	Tasks	Communication between Operators	Resource Allocation	Employee-Manager Relationship	Collaboration	Coordination
Tasks
Communication between operators	0.450
Resource allocation	0.575	0.455
Employee-manager relationship	0.450	0.550	0.458
Collaboration	0.520	0.532	0.389	0.457
Coordination	0.515	0.557	0.512	0.568	0.563

shows the level of correlation between the networks formed, which confirms the importance of organizational factors in expressing a conceptual model. The results in Table 3 indicate that the participants consider that the resource allocation (RA), collaboration, coordination, and relationship between managers and employees need improvement to create an appropriate framework for SUP.

Accordingly,

Table 4. Variables definitions and items.

Variable	Definition	Item	Id
Resources allocation	The resources needed to achieve organizational objectives are delivered fully under a control scheme that enables accountability and streamlines operations [61].	Management provides me with the resources I need to do my job.	RA1
		The organization has policies in place to account for the management of resources.	RA2
		The organization has clear values and policies that guide allocating resources.	RA3
Communication between operators	Deploy communication actions to simplify operations, regulate efforts, and collect information that provides appropriate feedback [14].	Instructions for performing my assignments are clear and precise.	CBO1
		Accurate information that allows me to improve or adjust my operational efforts.	CBO2
		Feedback mechanisms that promote continuous improvement.	CBO3
Primary tasks	Core activities focused on producing and delivering goods or services to customers, avoiding efforts duplication. Likewise, these activities seek to positively contribute to achieving the organizational objective [14].	The tasks I need to perform foster my development and achievement in my work.	PT1
		Primary tasks respond to a specific service or organization area without overloading.	PT2
		Primary tasks are efficiently autonomous and flexible to achieve objectives.	PT3
Support employees–managers	Set of organizational capabilities that enable achieving objectives without neglecting employees’ professional and personal development [15].	The organization continuously implements coordination mechanisms to reduce errors and friction among employees.	SEM1
		Supervisors optimize the organization of tasks and work teams.	SEM2
		The organization offers support based on data analysis.	SEM3
Collaboration	Strategies and actions based on internal and external data analysis seek to generate adaptation-oriented actions [61].	Employees are more focused on the organization than on promoting themselves individually.	COL1
		Employees avoid engaging in political activities rather than performance.	COL2
		All employees know what to do and how their involvement contributes to the organizational purpose.	COL3
Coordination	Cooperation between operators and managers encourages cohesion, anti-oscillation, and continuous task regulation [14].	The implementation of effective coordination mechanisms reduces waste and overlapping of primary activities.	CRD1
		Quantitative metrics to measure the performance of primary tasks are conducive to implementing coordinated actions.	CRD2
		The organization’s policies and value systems are sufficiently clear to guide employees in performing their work.	CRD3
Workload	Implementing control and coordination mechanisms allows for leveling production lines or work areas, reducing waste related to unnecessary movements or reprocessing [61].	Each work group has well-established responsibilities that are manageable.	WLD1
		My workload is congruent with my level of responsibility.	WLD2
Sustainable performance	Organizational state resulting from coherently integrating and regulating the operating units, considering the support among stakeholders, policies, and long-term vision to efficiently use organizational resources to continuously improve and adapt to the environment specifications [15].	Task forces can operate autonomously and respond quickly to environmental disturbances without compromising sustainable performance.	SUP1
		The organization’s operations implement feasible actions to minimize the negative impact on the environment.	SUP2

illustrates the factors that make up the conceptual model.

The data in Table 3 and Table 4 are used to develop Phase 3. The systemic method is applied to develop a conceptual model that explains how specific components can be configured to promote positive change. We develop a proposed conceptual model for driving SUP as illustrated in Figure 2, based on the findings of our literature review and the degree of correlation between the networks. This model introduces the relationship between the following factors in this context: coordination (CRD), workload (WLD), collaboration (COL), communication between operators (CBO), RA, manager’s support to employees (SEM), primary tasks (PT), and SUP.

Based on the conceptual model, the following hypotheses are proposed:

$H_1:$

CRD has a positive effect on COL.

$H_2:$

CRD positively affects WLD.

$H_3:$

Adequate WLD positively influences COL.

$H_4:$

RA positively affects COL.

$H_5:$

RA positively affects SEM.

$H_6:$

COL has a positive effect on PT.

$H_7:$

SEM has a positive impact on PT.

$H_8:$

CBO has a positive effect on PT.

$H_9:$

PT has a positive effect on SUP.

Before discussing the results obtained, we report the estimations for common-method bias to identify any discrepancies between the measurements of different traits [66]. Models developed from the systemic thinking perspective typically include the perspectives of those involved in a particular problem, making them prone to bias. As a result, we run a full collinearity test using variance inflation factors (VIFs). Note that, according to [70], a VIF score higher than 3.33 indicates a collinearity problem, implying that the construct is not a suitable approximation for the situation under consideration. The proposed construct is considered reliable because the maximum VIF obtained is 2.171 (

Table 5. Full collinearity VIF.

Variable	Resources Allocation	Communication between Operators	Primary Tasks	Support Employees-Managers	Collaboration	Coordination	Workload	Sustainable Performance
VIF	1.537	1.701	2.035	1.545	1.465	1.604	1.488	2.171

).

In Phase 4, the conceptual model is validated. According to [64], a conceptual model developed using the systemic approach should include the participants’ vision or perspective and information from the literature. This method combines constructs by focusing on estimating multiple regressions and the complexities of unstructured situations while still reaching systemic conclusions. Ref. [71] suggested that PLS-PM is an appropriate tool for validating models built under this perspective.

Table 6. Results for the model.

Latent Variable	Item id	Convergent Validity			Internal Consistency
		Loadings ($\mathit{\lambda }$)	Indicator Commonality	AVE	${\mathit{\rho }}_{\mathit{c}}$	$\mathbf{\alpha }$
Resources allocation	$R{A}_1$	0.900	0.810	0.693	0.897	0.724
	$R{A}_2$	0.876	0.768
	$R{A}_3$	0.710	0.504
Communication between operators	$CB{O}_1$	0.866	0.750	0.708	0.879	0.794
	$CB{O}_2$	0.873	0.763
	$CB{O}_3$	0.781	0.611
Primary tasks	$P{T}_1$	0.915	0.838	0.727	0.898	0.818
	$P{T}_2$	0.907	0.823
	$P{T}_3$	0.722	0.521
Support employees- managers	$SE{M}_1$	0.884	0.781	0.702	0.883	0.768
	$SE{M}_2$	0.853	0.728
	$SE{M}_3$	0.773	0.597
Collaboration	$CO{L}_1$	0.754	0.568	0.622	0.831	0.723
	$CO{L}_2$	0.733	0.538
	$CO{L}_3$	0.872	0.761
Coordination	$CR{D}_1$	0.852	0.726	0.708	0.869	0.761
	$CR{D}_2$	0.908	0.825
	$CR{D}_3$	0.756	0.418
Workload	$WL{D}_1$	0.877	0.769	0.786	0.880	0.728
	$WL{D}_2$	0.896	0.803
Sustainable performance	$SU{P}_1$	0.910	0.828	0.864	0.898	0.845
	$SU{P}_2$	0.938	0.879

Source: Following [66].

presents the results for the model’s convergent validity and internal consistency. Convergence validity levels are found to be acceptable since all items had a $\lambda >0.70$, indicating commonality and that each item explains at least 50% of the variance of each variable. The variable average variance extracted (AVE) exceeds 0.5, providing adequate validity to the indicator. Furthermore, adequate internal consistency is obtained since all estimated $\left({\rho }_c\right)$ and $\alpha$ values are between the suggested range of 0.70 and 0.90 [66]. This supports the idea that indicators are appropriate proxies for their respective variables.

After analyzing the model, we evaluate the discriminant validity to determine the extent to which each model component empirically differs from the others, and the heterotrait–monotrait (HTMT) evaluation is a commonly used method for this purpose. A value of 0.90 or higher indicates the possibility of discriminant validity issues, implying that the model components are conceptually similar [66]. We use a conservative threshold of 0.85 as suggested by [70]. According to the HTMT results, all the variables in the model report values below the conservative threshold, indicating no discriminant validity issues (

Table 7. Heterotrait–monotrait (HTMT) discriminant validity assessment.

	CRD	WLD	RA	COL	SEM	CBO	PT	SUP
CRD
WLD	0.802
RA	0.709	0.622
COL	0.457	0.394	0.578
SEM	0.542	0.421	0.596	0.722
CBO	0.818	0.633	0.720	0.482	0.595
PT	0.780	0.710	0.764	0.711	0.789	0.395
SUP	0.843	0.829	0.665	0.278	0.252	0.687	0.626

).

The structural model’s coefficient of determination $\left(R^2\right)$ measures the level of variance that each variable can explain. This means that it indicates each variable’s explanatory power and predictive power in sample [66]. Generally, $R^2$ values of 0.25, 0.50, and 0.75 can be considered weak, moderate, and substantial, respectively. Accordingly, the $R^2$ value for the SUP variable is considered high, whereas for the variables WLD, COL, SEM, and PT, the value is moderate (

Table 8. Type of variable, $R^2$, and $f^2$ results.

Id	Type	${\mathit{R}}^2$
WLD	Endogenous	0.468
COL	Endogenous	0.280
SEM	Endogenous	0.260
PT	Endogenous	0.753
SUP	Endogenous	0.385
$f^2$
CRD → WLD		0.881
CRD → COL		0.153
WLD → COL		0.130
RA → COL		0.225
RA → SEM		0.355
COL → PT		0.055
SEM → PT		0.358
CBO → PT		1.373
PT → SUP		0.498

). Table 8 also shows the effect size $f^2$ that allows evaluating the impact of omitting a specific construct on the model if systems thinking is used as the framework for proposing the conceptual model [70]. According to [72], effect sizes of 0.02 (small), 0.15 (moderate), and ≥0.35 (large) are considered guide values. The following relationships have a small effect: WLD with COL, and COL with PT. The following relations have a moderate effect: CRD with COL. A large or significant effect is present with the following: CRD with WLD, RA with SEM, SEM with PT, CBO with PT, and PT with SUP.

The path diagram presented in Figure 3 shows the coefficients of the relationships proposed in our model. Note that CRD, WLD, COL, RA, SEM, and CBO do not have a direct influence on SUP. However, according to the VSM, the relationships between these variables positively impact fundamental factors, such as the PT of any organizational system. Therefore, the interaction of the model variables can enhance SUP. According to the path diagram results, SUP is a reasonable and attainable goal for an SME. Additionally, the path coefficients show that the conceptual model’s factors and their relationships explain 53% of the variance in the SUP construct. However, adopting an organizational design that allows for the coherence of personnel, management, control, and regulation mechanisms to promote continuous improvement and adaptation and implement SUP is crucial.

A bootstrapping procedure with 10,000 iterations is conducted to determine the significance of the relationships expressed in the conceptual model (

Table 9. Bootstrap analysis by factors. Confidence interval at 95% and their significance levels: *** 0.001.

Path	Original	Bootstrap Mean	Bootstrap SD	T Stat	Perc.025	Perc.975	Signf
CRD → WLD	0.684	0.684	0.059	11.570	0.555	0.786	***
CRD → COL	0.202	0.209	0.115	1.756	0.120	0.340	***
WLD → COL	0.332	0.334	0.112	2.964	0.185	0.256	***
RA → COL	0.451	0.454	0.085	5.290	0.277	0.609	***
RA → SEM	0.510	0.516	0.063	8.108	0.388	0.632	***
COL → PT	0.361	0.359	0.061	2.634	0.035	0.274	***
SEM → PT	0.139	0.140	0.070	1.977	0.002	0.280	***
CBO → PT	0.700	0.701	0.043	16.161	0.614	0.784	***
PT → SUP	0.533	0.537	0.054	9.929	0.428	0.636	***

). The findings show that SUP is not a result of a single organizational factor. In the context of systems thinking, SUP can be viewed as a nonreducible property that emerges from the interrelationship between the components of an organizational system and their environment. The bootstrap also allows us to check the confidence intervals to see how stable the sample statistics are as a population estimator [66]. Therefore, if the intervals (0.025–0.975) do not include the value 0, the relationship is significant at 95%. Table 9 shows that all nine hypotheses are supported because no interval contains 0. This suggests that adopting our model can increase the SMEs’ likelihood of favoring SUP.

According to [63], designing a conceptual model aims to propose changes that other users can easily implement with minimal adjustments. Ref. [70] suggested that this ability can be evaluated by examining whether the model can work with new or out-of-sample data. To determine this, we compare the PLS model errors for each indicator. According to [66], if the PLS errors are less than the linear model (LM) for all indicators, the model has high predictive power.

Table 10. Model errors.

		PLS		LM		PLS - LM
Latent Variable	Item id	RMSE	MAE	RMSE	MAE	RMSE	MAE
Workload	$wl{d}_1$	0.608	0.619	0.794	0.830	0.222	0.211
	$wl{d}_2$	0.709	0.667	0.902	0.854	0.145	0.187
Collaboration	$co{l}_1$	0.601	0.693	0.792	0.876	0.275	0.183
	$co{l}_2$	0.639	0.696	0.848	0.889	0.250	0.193
	$co{l}_3$	0.492	0.569	0.634	0.715	0.223	0.146
Support employees- managers	$se{m}_1$	0.507	0.680	0.672	0.838	0.331	0.158
	$se{m}_2$	0.540	0.622	0.702	0.735	0.195	0.113
	$se{m}_3$	0.633	0.746	0.874	0.937	0.304	0.191
Primary tasks	$p{t}_1$	0.487	0.520	0.607	0.680	0.193	0.160
	$p{t}_2$	0.507	0.517	0.646	0.682	0.175	0.165
	$p{t}_3$	0.576	0.613	0.764	0.768	0.192	0.155
Sustainable peformance	$su{p}_1$	0.569	0.767	0.751	0.986	0.417	0.219
	$su{p}_2$	0.634	0.766	0.810	1.017	0.383	0.251

shows that the PLS errors are lower when comparing with LM, implying that the model can be used in other organizations with minor adjustments.

In Phase 5, the systemic method emphasizes the need to suggest changes to initiate or implement improvements after proposing and evaluating new relationships to improve a situation [9]. The present study uses the VSM to translate the conceptual model’s results into specific recommendations for changes in organizational functions. These suggestions guide the efforts of managers and other actors who can effect change. It is important to note that the VSM integrates five functions at all organizational system recursive levels. The interrelationship of these functions seeks to strengthen control and reduce oscillation or variation in an organization’s essential operations. Thus, the VSM helps redesign relationships between different levels of an organization [73]. The following is a brief description of the functions of the VSM (for more detailed information, refer to [14,67] and [8]):

• S1 (operations): It refers to all the primary activities and components involved in producing and delivering its goods or services. It can be considered concrete actions taken at the operational level to implement the organization’s purpose.
• S2 (coordination): Processes in any organization are inherently subject to variation due to their nature. The coordination function focuses on implementing processes that coordinate S1’s actions to minimize process overlapping and reduce variability or oscillation of their results. For example, using graphs like $\overline{X}-R$ or $\overline{X}-S$ can function as effective coordination mechanisms.
• S3 (control management): Assists S1 by managing resources, establishing norms, rights, and responsibilities, putting controls in place, and seeking integration and synergies. This allows S1 to focus on the “here and now” without neglecting organizational goals and values. The Andon dashboards are excellent examples of how to operationalize this systemic function. Furthermore, S3 converts strategic information into operational information and gathers data from S1 for reporting to S4 and S5.
• S3*: This is a specialized function that assists S3 by retrieving information that might otherwise escape S3.
• S4: This function involves studying the environment, collecting and analyzing data, detecting patterns, identifying opportunities, and devising action plans to preserve S1 while adjusting S2 and S3.
• S5: This function represents high-level decision-making and defines organizational principles, identity, and purpose. Using the information from S4, it attempts to make long-term changes to policies, standards, and principles.

We include the path coefficients in the VSM to demonstrate the organizational relationships an SME should consider to promote SUP. Following [67], Figure 4 shows the level at which the organizational system of interest is located. The figure represents the following levels: $R_0$, the context in which Mexican SMEs operate; $R_1$, the critical sectors for the Mexican economy; and $R_2$, the critical areas where SMEs are concentrated. At this level, the organizations of interest (tourism SMEs) are located, and SUP is sought.

We incorporate the path coefficients into the VSM design after analyzing them. This assists us in determining which organizational functions and connections require more attention from managers to effect change in SMEs. Management must address various factors, including implementing proper coordination mechanisms (CRD), to modulate WLD. Moreover, the local and global coordination mechanisms must be distinguished to encourage local collaboration (COL) while promoting collaboration with the higher and lower recursive levels. According to [73], PTs are the heart of an organizational system. As a result, we can improve CBO and align factors such as RA and SEM to promote SUP at various levels of tourism SMEs. Figure 4 shows the standard structure and functions found in any tourism SME (recursion level 2), with the VSM design used to increase internal control, provide autonomy, and handle internal and external disruptions.

Figure 5 indicates that SUP depends on the seamless integration of organizational coordination and support mechanisms for basic operations. Therefore, managers must exercise caution when allocating resources through operational management channels. The results also suggest that adequate coordination and resource allocation are crucial to fostering collaboration. The VSM design (Figure 5) suggests that the coordination factor (CRD) should be understood as more than just a set of tools for regulating processes. Managers should instead integrate the workload from a broader perspective to ensure that the organization’s purpose is not overlooked. Based on the preceding, empowering those involved in PT becomes critical for promoting and strengthening the organizational capacity to respond to environmental demands.

6. Discussion

The motivation of this article is to support the understanding of SUP in the context of SME organizations. Therefore, a proposed framework considers organizational mechanisms and components to promote SUP.

The effectiveness and efficiency of operations play a crucial role in achieving SUP [73]. However, to direct an SME toward SUP, the enterprise must have an organizational design that allows efficient internal connections or relationships at various recursive levels while still keeping the system’s philosophy clear. The model’s result supports $H_1$, which suggests that CRD positively impacts COL. The coefficient of this relationship is 0.202, indicating the importance of local and global coordination mechanisms in regulating operations without overstepping their role and ignoring collaboration [39]. The CRD factor (S2 in VSM) is critical not only for reducing oscillations in the operational framework and achieving objectives more efficiently but also for allowing SMEs to effectively use their internal resources and provide a scaffolding for each operational unit to perform its primary functions adequately [36]. $H_2$ assumes a relationship between CRD and WLD and obtains a coefficient of 0.684 , thereby supporting the relation [20]. This emphasizes the need for SMEs to take a systemic or holistic approach to task and workday planning because, according to [43], task planning and assignment in SMEs are usually conducted on a quota basis and do not usually consider workload regulation and its impact on the degree and quality of collaboration that can be generated [59]. $H_3$ proposed this last idea, linking WLD to COL; the result obtained for this hypothesis (0.332) supports the proposed relationship. However, this relationship is often underestimated in SMEs because the workload is associated with productivity and goal achievement but not with collaboration in SMEs [17,74]. Therefore, the scope of coordination mechanisms must be adapted and amplified; that is, managers at different levels should adequately define local coordination instruments without disconnecting from global instruments, which, according to our model, could significantly improve the achievement of objectives for the TPs without neglecting the organizational ethos. These findings and ideas contrast with the findings of [47,50,52], who all agreed that this relationship is of little relevance to SUP.

The coefficients for $H_4$ (0.451) and $H_5$ (0.510) support the respective relationships and allow us to posit the relevance of RA’s influence on an organization’s PTs. On the one hand, from a systemic standpoint, RA functions as an anti-oscillatory mechanism between personnel and their tasks because it focuses on ensuring the provision of sufficient and necessary resources to operate and evaluating resource uses not only in terms of operational performance but also under organizational principles and policies, which is conducive to aligning collaboration at various levels [40,42]. The results also highlight the importance of the relationship between strategic resource planning and operations management in employee support. In this sense, the coefficients for $H_6$ (0.361) , $H_7$ (0.139), and $H_8$ (0.700) allow us to say that collaboration extends beyond the organizational climate or even the scope of the human resources department’s leadership style or influence [55]. Thus, PT must be supported by meshing multiple organizational factors as input. However, these same factors and their interactions may operate in different departments at different levels. These results are consistent with the central postulates of the systemic approach, particularly from the VSM perspective [8], that is, operations provide the identity of an organizational system, allowing the emergence of SUP to be generated through the coherent rearrangement of specific functions present in any system [29,41,45]. Based on the above, we consider that the conceptual model in this article proposes to address relationships between minimum and sufficient factors by articulating the coordination mechanisms and clear communication channels, strategic planning, organizational philosophy, and operational management to mitigate environmental disruptions and strengthen operational units’ ability to adapt to challenges [48]. Based on these assumptions, the result for $H_9$ (0.553) shows that the relationships between the proposed factors can assist a medium-sized organization in achieving SUP.

Our work proposes a methodology that has generated some results. Based on these results, we can indicate some implications for decision-makers and change-implementing actors in the context of SMEs who wish to operate under a SUP scheme. To accomplish this, one must reconsider the internal interactions between core operating units, which are responsible for providing the company’s identity, and the coordination and management mechanisms that can promote faster responses in order to adapt efficiently to the needs of the contexts they serve [49]. Regarding the CRD, managers should divide these mechanisms (information channels, technical resources, programming functions, shared resources, organizational culture, policies, and operating rules) into two basic levels, namely, local and general coordination mechanisms. This would reduce overlapping mechanisms and provide indicators to specific operational departments or actors [20,43]. Identifying the levels at which CRD should perform would be conducive to operational units’ coherent and orderly work (PT) based on regulating WLD and COL [44,47]. This necessitates reviewing and strengthening internal communication channels and models to simplify aspects such as resource management and accountability for these resources.

Addressing the organizational aspects related to the variables WLD, COL, and CBO also implies providing work cells with greater autonomy so that through appropriate coordination mechanisms, each work cell or operational unit can regulate workload and modulate collaboration, thus avoiding overloads or overlaps. As a result, the units in charge of the PT strive to meet their objectives while focusing on operating within a SUP framework [48]. Strategic planning, in turn, should include the study and analysis of both internal and environmental data to generate appropriate courses of action and provide support to employees through management (SEM); that is, decisions and support to employees must be based on data and information from the environment. In other words, decisions and employee support should be data-driven, and RA should be based on continuous monitoring of the environment to reduce waste and anticipate potential changes [10]. From the perspective of organizational cybernetics and because the results obtained support the notion that the PT variable is important in determining the SUP, the relevance of SME managers in promoting changes or strengthening the capacity for collaboration between CRD, WLD, RA, COL, and CBO is highlighted [8,50] under a perspective that allows implementing the same changes at all resource levels of the organization [51], an alternative available in the VSM [14]. The active participation of business owners, human resource managers, and key stakeholders at each level is critical to driving changes and enabling SUP to be an emerging property without ignoring the requirements of internal and final customers [53]. However, from the VSM framework, the variables and relationships of our model should be pursued at all SME levels to ensure consistency in cascading change [30].

Although our conceptual model considers the perspective of the members of the SME under study, we intend to reduce the model’s subjectivity in two ways: the first is by grounding its components and their relationships in the theoretical framework of organizational cybernetics, specifically through the VSM. This framework is appropriate for the model because it incorporates three aspects of any system: control, self-regulation, and the necessary variety management [54]. Accordingly, SMEs can consider it as a common language to unify or standardize communication at different levels and focus on working on enabling SUP, that is, creating nonexistent relationships, improving or increasing the capacity of the basic units, and seeking to increase both responsiveness and adaptability [29]. The structural equation model is used in the second approach to try to reduce subjectivity by estimating its statistical validity. Concerning the last point, the model’s path coefficients can be used to identify areas of opportunity for learning or organizational development for tourism SMEs. According to [57,74], the inability of tourism SMEs to operate under a SUP framework is due to their structural design, a lack of institutional support, and a lack of organizational learning capacity. Ref. [26] suggested that SMEs can reduce learning problems by strengthening organizational culture and policies, and increasing productivity-oriented economic incentives while adhering to sustainability requirements.

Meanwhile, the framework proposed by our model assumes that organizational learning can be generated to the extent that organizational management addresses critical factors and relationships, such as coordination, support for essential operations at each level, and strategic planning. Implementing courses of action aimed at SUP should result from learning work cells and strengthening adaptive capacities [29,58]. In this regard, it is pertinent to mention that the VSM makes it possible to support which structural conditions are necessary and sufficient to procure learning under a systemic approach [8,73].

To be more comprehensive, our framework emphasizes the importance of having or developing critical functions and processes that enable management and decision-makers to lead to a SUP. In addition, it highlights the capabilities required to deal with potential complications that may arise during the practical implementation of SUP. Regardless of how much an organizational system adheres to its standards in its structural design, its SUP performance is determined by its interaction with the environment or context in which it operates. The current economic climate for most SMEs presents dilemmas, as SUP objectives often conflict with market dynamics. Refs. [17,59] raised paradoxes of strategy deployment that could complement our framework by providing tools to strengthen decision-making at different levels of tourism SMEs. The framework generated by the VSM could help decision-makers influence change to clarify the dilemmas of SUP practice.

7. Conclusions

Despite the continued relevance of SUP [68,75], our literature review suggests that the most common analytical tools used to address performance-related problems are statistical process control, structural equation modeling, data envelopment analysis, and general linear models. These tools focus on specific areas, such as verifying relationships between variables that influence or trigger performance, predicting personnel performance, comparing the performance level of operating units with other operating units or organizations, and implementing environmental or social practices to achieve eco-efficiency. However, using these tools is consistent with a reductionist view of performance, treating it only as a process measure, a financial indicator, or sometimes as a measure of the degree of business innovation. To promote SUP, we must still identify and understand the systemic functions that should be present in any organization to aid in decision-making and organizational changes. Although various models include factors such as environment, information processing capacity, human factors, or management models that could be interpreted as systemic functions, the systemic or integrative nature is frequently overlooked. The emerging character of SUP is also frequently overlooked. As a result, particularly in the SME environment, adopting a perspective that brings together critical relationships that affect operations, structure, and context is critical to operate sustainably. This article introduces a framework for investigating organizational factors and their relationships conducive to SUP. The systemic approach, which combines analytical tools, can help managers understand complex organizational problems. Using SNA, we incorporate the participants’ perspectives and identify key factors essential for operating under the SUP scheme. This integration of methodologies can foster a culture of continuous learning at all organizational levels, allowing for better management of information and knowledge derived from interactions between system functions. We advocate for statistical and mathematical validation to increase decision-making certainty. By applying SNA, we achieve our second objective: identify the correlation between networks to recognize the organizational factors that should be addressed to configure the conceptual model. This leads to a process of continuous change and improvement aimed at promoting relationships that results in SUP. The structural education path modeling model is used to validate the relationships proposed in the conceptual model, which is our third goal. Although our model agrees with existing research on factors, we propose new paths, and the results support our conceptual model as aligned with the issues faced by organizational systems. Furthermore, we believe that the model variables, which are based on systemic concepts, are correct, making them easy to understand by personnel from other areas. As a result, we believe the proposed framework should be extended to organizations in other industries. After validating our conceptual model with PLS-PM, we incorporate the VSM to suggest ways for managers to rethink their efforts and RA to promote SUP at every level of the organization. The VSM recommends incorporating generic functions into any system while keeping regulations in mind. Therefore, the managers’ use of the VSM involves rethinking departmental relations, adopting concurrent control and feedback, and seeking autonomy in operating units. Furthermore, the VSM can help SMEs understand their internal problems and serve as a source of information to supplement the proposed model and continue the improvement process. We acknowledge the limitations of our proposal. The application context is a medium-sized company; although the sample size is sufficient for statistically significant results, more work is required to replicate the study in various other companies. Furthermore, we suggest two alternatives to broaden the scope of our work. First, the network analysis must be deepened to predict the creation or breakdown of links to maintain SUP. Second, the network analysis and data envelopment analysis must be integrated to measure SUP operationally.