Breaking Barriers: Financial and Operational Strategies for Direct Operations in Saudi Arabia

Abstract

This study investigates the key factors enabling the transition from distributor-based models to direct operations among companies in Saudi Arabia, in alignment with Vision 2030’s goals of economic diversification and operational efficiency. The study is based on quantitative data collected from 528 questionnaire responses representing diverse industries and professional roles. The results highlight that technological integration and regulatory negotiation are essential for a smooth transition to direct operations. Furthermore, environmental sustainability practices and stakeholder involvement significantly affect the adoption of this transition, often acting as moderators and mediators. The findings emphasize the importance of aligning operational strategies with national development goals to enhance efficiency and resilience. This study also examines how transitioning to direct operations impacts financial efficiency and contributes to improved financial performance and sustainability. This study provides practical recommendations for policymakers and business leaders to address operational challenges and improve their financial and operational performance.

1. Introduction

1.1. Background

Saudi Arabia’s Vision 2030 is considered one of the most significant factors that has influenced the economic landscape in Saudi Arabia in recent years. The vision aims to reduce dependence on oil and diversify the economy, while improving government service sectors such as health, education, infrastructure, tourism, and entertainment [1]. Therefore, it can be said that through this vision, efforts will be made to enhance national capabilities in many areas, opening wide doors to innovation and technological development across various sectors.

What Saudi Arabia is doing today to develop its economy is part of a larger goal: to modernize the Saudi economy in general by moving away from traditional distribution and operation models and transitioning to direct operation models based on technological innovations and changes in the regulatory framework [2]. This transformation requires companies to adapt to a dynamic environment filled with challenges and opportunities, including the need to improve operational performance and enhance competitiveness in both the local and international markets [3].

Technological changes, on the one hand, and changes in the regulatory environment, on the other, are the main catalysts for this transformation, as these factors contribute to increasing the effectiveness of companies’ operations and enhancing their ability to meet customer needs. As pointed out by [4], there are factors that contribute to the boom in direct employment, examples of which are rapid technological development, the development of regulatory regulations, and strategic business planning.

Advanced technological tools such as Enterprise Resource Planning (ERP) systems, e-commerce platforms, and Customer Relationship Management (CRM) systems are among the most important technological enablers of this type of transformation. They contribute to ensuring streamlined operations within supply chains, improve product and service quality, and enhance companies’ ability to communicate instantly with customers, suppliers, and stakeholders [4]. These operational capabilities are essential for ensuring business continuity in a rapidly changing and interactive environment.

Moreover, local companies in Saudi Arabia are demonstrating an increasing willingness to comply with regulatory requirements by being prepared to adapt to future legislative frameworks, especially given the changing and dynamic nature of the regulatory system within Vision 2030 [1]. In this context, the importance of incorporating environmental sustainability principles into operational plans has emerged in response to global pressures related to climate change issues and in compliance with the requirements of local and international regulators [5,6].

On the other hand, stakeholder engagement is a pivotal factor in the success of the transition to direct operations, as customers, employees, suppliers, and local communities all play active roles in the organizational adaptation process. Ref. [4] emphasizes that the ongoing involvement of specialists from both inside and outside the organization contributes to the effective integration of new operating models within the overall structure of the organization.

At the same time, it should be noted that Saudi Arabia has a completely different context for transitioning to direct operations. Vision 2030 is driving its economic and social transformation differently from mature economies, where direct-to-consumer models have evolved gradually. The Kingdom is experiencing a rapid transformation driven by structural reforms and an accelerated drive toward digital transformation and economic diversification. All of this makes the Kingdom an exemplary and unique case for how companies can navigate this rapid type of change.

Based on this background, this research aims to explore the challenges and opportunities that companies in the Kingdom of Saudi Arabia may face when transitioning to direct operation models. It also seeks to provide strategic recommendations and practical tools to help companies flexibly respond to the changing business environment. Unlike previous studies that have often focused on developed markets, this study highlights the reality of an emerging market and offers a fresh perspective by incorporating concepts of environmental sustainability and effective stakeholder engagement, in line with the economic and social goals of Vision 2030.

1.2. Research Questions and Objectives

The study’s research topics focus on the problems and details of the transition from distributor-based models to direct operations in the peculiar environment of Saudi Arabia.

What approaches can firms in Saudi Arabia use to successfully respond to the changing regulatory environment and market conditions, and shift to direct operations? What is the influence of technical development, mainly ERP systems, e-commerce platforms, and CRM tools, in facilitating this change, and how can they effectively adapt to the Saudi Arabian market?

These requests seek to explore the diversity of the barriers and opportunities that organizations face when adjusting to the objectives of Vision 2030 in Saudi Arabia. The investigations cover approaches to realizing operational excellence and economic diversification [2,3].

This research aims to develop a strategic model for changing from distributor-based to direct operations in the Kingdom of Saudi Arabia regarding Vision 2030, a forward-looking plan for the future, and its implications for changing business models. Numerous specific objectives support this overarching goal.

They consider the changing regulatory and market dynamics in Saudi Arabia, appraising their impact on corporate activities, and proposing approaches to navigate [2].

The aim is to develop approaches to integrate technology that exploits ERP systems, e-commerce platforms, and CRM tools into the Saudi market to enhance operational efficacy and consumer interaction [3].

We wish to examine sustainable practices and supply chain resilience methods to address the particular environmental and geographical challenges in Saudi Arabia and align them with the country’s environmental goals [7,8].

The aims of this study are to provide a systematic approach to understanding and handling the challenges of implementing direct operations in Saudi Arabia. They consider the importance of regulatory comprehension, technological development, and environmental sustainability in achieving enterprise success consistent with national development goals.

1.3. Importance of the Study

This study is important to academia and industry and offers significant lessons for both sectors. The report is a source of rich information to managers on the major variables and strategies that one needs to transfer to direct operations in Saudi Arabia. It provides useful guidelines for organizations seeking to adhere to the Vision 2030 framework. It also outlines implications for strategic decision-making, further contributing to a wider conversation about economic diversification [1,9]. It is worth mentioning that the region’s sustainability is stressed, providing a comprehensive roadmap for enhancing operational efficiency and promoting innovation in response to a changing economic environment.

This study adds to the academic literature on business model transformation relative to the ambitious national development targets of Saudi Arabia. This study addresses the missing elements in the literature, including regulatory navigation, technological integration, and environmental sustainability practices. This leads to basic knowledge essential for developing the area [3,7,8]. The results offer a comprehensive and complex knowledge of the interplay between policy, technology, and market factors in Saudi Arabia. This study is a starting point for additional research on international business, economic development, and sustainability.

In addition, this study is important for policymakers and stakeholders responsible for implementing Vision 2030. It provides science-based knowledge for policy revisions and strategic measures to promote economic diversification and sustainability. This study offers concrete recommendations for enhancing the regulatory environment, promoting technological development, and stimulating sustainable business operations during the transition to direct operations. These recommendations reflect Saudi Arabia’s developmental objectives [2,10].

This study is significant because it comprehensively analyzes the factors influencing the transition from distributor-based models to direct operations in Saudi Arabia. It offers vital information to the academic, managerial, and policymaking segments. This research seeks to link theoretical concepts with practical approaches, contribute to academic discussions, and provide a strategic roadmap to corporations and governments in the complex context of Saudi Arabia’s Vision 2030 and beyond.

The second part of this paper covers the literature review, the third part covers the research methodology, the fourth part covers the analysis and conclusions, and the fifth and final part discusses the recommendations and conclusions.

2. Literature Review

2.1. Review of the Literature

This literature review explores the shift from distributor models to direct operations in Saudi Arabia against Vision 2030, rapid urbanization, technological progression, and environmental matters. This is achieved by scrutinizing many aspects of this complicated process. The information in this review is organized into sections, each addressing key aspects of the transition and including results from multiple studies.

2.1.1. Transition from Distributor-Based Models to Direct Operations

One of the most prominent features of strategic change in the contemporary business environment is the shift from traditional distribution-based models to direct operation systems, particularly in emerging markets experiencing economic changes driven by ambitious national policies. Several studies have addressed this topic, indicating [2] that the transition to direct operations is a fundamental step in increasing operational efficiency, especially when modern digital technologies and a logistical infrastructure support such models.

Ref. [4] also discusses that the shift to direct operations is not limited to reorganizing functions alone but must overcome institutional barriers typically present in the business environment, such as resistance to change, challenges in coordinating between business units, and differing customer and supplier expectations. Such a change is high-risk and must be accompanied by comprehensive strategic planning that takes into account all organizational, financial, and technical aspects of the business. In fact, there are pressures to shift to direct operations. The most prominent of these pressures, as mentioned in [3], are the significant changes in consumer behavior and pressures on supply chains. Shifting to direct operations will help companies increase their competitiveness, respond more quickly to market demands, and improve overall customer satisfaction. Ref. [2] indicated that most of the literature focuses on cases in advanced economies with strong infrastructure and organizational capabilities, while neglecting the context of emerging economies, despite the significant efforts these emerging economies may have made towards development and transformation. Although Saudi Arabia has a distinct regulatory context, reflected in the nature of the relationship between companies and local intermediaries, the presence of unique cultural and organizational dimensions, and the existence of a national-level strategic plan, previous studies have not addressed the Saudi case. The previous literature reveals a clear gap in addressing this issue. Therefore, the current study seeks to bridge this gap by analyzing the factors facilitating and hindering transformation in Saudi Arabia, while presenting an integrated model that integrates the organizational and technical dimensions to ensure the success of such operational transformations.

2.1.2. Technological Integration and Digital Enablement

Technological integration can be considered a cornerstone of the shift to direct operations, as it allows organizations to improve operational efficiency, increase analytical capabilities, and improve customer engagement. The literature has examined the role of enterprise resource planning (ERP) systems, e-commerce platforms, and customer relationship management (CRM) tools in enhancing business agility and facilitating the transition from traditional models to direct systems [3,11,12].

Some studies have indicated that implementing ERP systems allows for the unification of databases and processes across various organizational functions, reducing duplication and enhancing decision-making accuracy [13]. Additionally, it has been demonstrated that automated operations in the Saudi industrial sector have significantly contributed to increasing levels of sustainability and efficiency [14,15]. The paper demonstrates how organizations were able to reduce resource consumption and improve environmental performance monitoring through advanced digital platforms.

In the same context, Ref. [16] demonstrates that technological advancements played a crucial role in addressing logistics challenges, particularly with regard to supply chain management and real-time information flow. Ref. [17] expands on the discussion of the relationship between technological innovation and competitive advantage, concluding that organizations that invest in digital infrastructure are better able to cope with market changes and achieve effective operational integration.

At the same time, other studies have focused on operational benefits, such as [18,19], which examined how the integration of ERP and CRM systems contributed to improved financial control, enabling organizations to optimize resource allocation and make data-driven strategic decisions.

Most studies have focused on developed markets, while the dual specificity of the Saudi market can be seen in clear government aspirations to promote digital transformation within Vision 2030. On the other hand, organizations face challenges related to human resource development and adapting technical systems to local organizational and cultural characteristics [1,9].

Ref. [20] also indicates that technical barriers are not only due to a lack of infrastructure, but are sometimes linked to the limited readiness of corporate management teams, as well as the weak strategic orientation in adopting technology as a key component of organizational transformation. All of the above demonstrates the critical role of technological integration in achieving operational efficiency and institutional resilience [21]. However, there remains a gap in examining this in the Saudi context, where the change came as part of comprehensive reform policies rather than a result of market competition. This requires taking into account regulatory, environmental, and legislative considerations in this transformation.

2.1.3. Regulatory Transformation and Institutional Environment

On the other hand, the regulatory environment is a key factor in determining an organization’s ability to implement the transition from traditional distribution models to direct operation models, especially in contexts characterized by rapid changes in policies and legislation, such as the case in Saudi Arabia under Vision 2030. A study in the literature points to the need for institutional flexibility and a balanced strategy that combines compliance with innovation to achieve the required level of effective interaction with regulatory changes [1]. It has also been shown that Saudi Arabia is witnessing significant changes in economic and regulatory policies [2], with top-down reforms being imposed, requiring companies to quickly adapt to new requirements, including disclosure, transparency, and operational governance. This regulatory dynamism, characterized by rapid changes, is one of the most prominent features of the business environment in Saudi Arabia, making its study of particular research interest [22]. Within this framework, studies such as [8,10] focused on the impact of environmental legislation and regulatory governance on shaping business models in Saudi Arabia. They indicated that organizations’ compliance with these regulations is not a voluntary choice, but rather a necessity to maintain operational continuity and comply with the state’s sustainable development orientations.

Other studies in the literature, such as [23], discuss that organizational changes are not solely related to local regulations, but are also influenced by broader geopolitical factors that may impose pressure on multinational companies operating in Saudi Arabia. Ref. [24] also highlights the importance of understanding “structural inertia” within organizations, which may hinder adaptation to new regulations if not addressed by internal reforms of the organizational culture within these organizations.

Refs. [25,26] also indicates that organizational change cannot succeed unless it is accompanied by a restructuring of internal structures and a redesign of processes to align with the new regulatory framework. This idea reinforces the hypothesis that the transition to direct operations in Saudi Arabia should not be viewed solely as an operational change, but rather as a comprehensive institutional transformation.

Ref. [27] also highlights the importance of regulatory factors in supporting environmental risk management, particularly in light of challenges related to water and natural resources. This reflects the increasing overlap between regulation and environmental policies in the context of Vision 2030.

It is clear from the analysis of the literature that regulatory changes are a pivotal factor in shaping the institutional transformation model, especially in contexts where the state is leading the economic change agenda. However, most studies have focused on analyzing policies in isolation from operational models, without providing an integrative framework that links the regulatory environment and corporate performance in the context of transformation. Hence, the importance of this study, which seeks to fill this research gap, is highlighted.

2.1.4. Stakeholder Engagement and Organizational Change

Stakeholder engagement is a key factor in achieving organizational transformation, especially in environments that require radical changes in operating models and internal and external relationships. The literature has addressed this issue from multiple perspectives. Refs. [4,28] indicates that involving employees and middle management in transformation processes increases the effectiveness of change and reduces resistance, especially when they are included in the decision-making stages. Ref. [23] adds to the above that the success of change does not depend on the design of the new operating model, but rather on the extent to which individuals accept it and their ability to redefine their organizational roles within the new environment.

In the Saudi context, Ref. [29] demonstrates that the cultural factor is a key element in change management, as employee responses are highly influenced by personal relationships and hierarchical structure, which calls for adopting change methods that take into account cultural and organizational sensitivity. Ref. [30] also notes that weak stakeholder engagement in the planning and implementation stages can lead to adverse outcomes, represented by decreased organizational commitment and high employee turnover rates.

Other studies have addressed the importance of involving suppliers and customers in designing new operational processes. Ref. [31] demonstrates that organizations that restructure their relationships with suppliers within the framework of a direct operating model achieve greater flexibility in responding to market changes, while excluding them from dialogue may weaken the supply chain and lead to numerous operational disruptions.

In terms of leadership, Ref. [8] indicates that transformational leaders are able to create an organizational environment conducive to change through effective communication, providing a psychologically supportive environment, and fostering a culture of learning within the organization. This argument complements what [32] states regarding the importance of transparency and organizational justice in maintaining employee trust during restructuring phases.

What can be observed from all of the previous studies in the literature is their emphasis on the importance of stakeholder engagement in the success of organizational transformation Ref. [33]. However, there is still a dearth of studies that clearly link this engagement to the success of the transition to a direct operating model in a changing organizational environment such as Saudi Arabia. To date, there has been no analytical framework that integrates leadership, culture, engagement, and their cumulative impact on operational efficiency after transformation.

2.1.5. Environmental Sustainability and Business Resilience

Environmental sustainability is no longer an option in today’s business environments; rather, it is an essential component of corporate transformation strategies, especially with increasing regulatory and societal pressures to achieve environmentally responsible economic growth.

The environmental challenge in Saudi Arabia represents one of the most prominent themes of Vision 2030, particularly with regard to water, energy, and emissions management [9,34]. Ref. [27] indicates that organizations that adopt effective environmental strategies enjoy greater operational flexibility in the face of changing environmental legislation and restrictions on natural resource consumption.

Some studies have also examined the impact of environmental information systems on improving environmental and operational performance. Ref. [16] demonstrates that integrating sustainability standards into ERP systems contributes to improved tracking of resource use and reduced waste. Ref. [32] also discusses the role of environmental transparency in enhancing stakeholder confidence and strengthening the relationship between the organization and its surrounding environment. On the other hand, Ref. [31] demonstrates that sustainability is not an external organizational factor, but rather an internal element that reshapes corporate operations. This approach complements the view of [35], which holds that organizations capable of integrating sustainability practices into their direct operating model achieve organizational alignment and build a sustainable, long-term competitive advantage.

The literature has also addressed the relationship between sustainability and governance, with [8] indicating that organizations with high environmental performance are more likely to attract partners and customers in both developed and emerging markets. This finding supports Ref. [24]’s findings regarding the importance of developing corporate policies based on a balance between economic efficiency and environmental sensitivity.

It is noteworthy that despite the numerous studies addressing environmental sustainability, they often focus on environmental outcomes or operational indicators without a direct link to the corporate operating model, especially in transitional contexts such as that of Saudi Arabia. There remains a gap in understanding how sustainability practices impact the success of the transition to direct operations within changing regulatory and economic frameworks.

Through analyzing the previous literature, it can be noted that it addresses institutional transformation partially or separately, but with a focus on established or advanced economic contexts. It does not address these factors in an integrated manner within a state-led economic environment, as is the case in Saudi Arabia under Vision 2030.

Also, the previous literature does not include any link between the overlapping axes, nor does it present comprehensive analytical models that link the organizational, technological, cultural, and environmental factors that collectively influence the desired transformation.

Accordingly, this paper aims to bridge the research gap by developing an integrated analytical framework that studies the fundamental determinants of the transition to direct operation in Saudi companies. This research aims to bridge this gap by presenting an integrated analytical framework that examines the key determinants of the transition to direct employment in Saudi companies, focusing on three main objectives: (1) identifying the organizational, technological, and cultural factors that influence this transformation; (2) analyzing the role of stakeholder engagement and environmental sustainability as mediating variables that influence the relationship between these factors and the outcomes of the transformation; and (3) constructing a testable conceptual model that reflects the nature of the relationship between these dimensions in the Saudi context.

To consolidate the theoretical themes discussed in the literature, Figure 1 presents the general research model that frames the broader context of this study.

The research model for “Directing Change” focuses on the transition from distributors to direct operations in Saudi Arabia, identifying key factors that influence this process. The primary dependent variables are direct operational success, evaluated through strategic alignment, technological integration, regulatory navigation, and environmental sustainability. The independent variables include demographic, economic, and operational factors, along with industry and market type distinctions. Technological integration and environmental sustainability mediate the relationship between strategy and success, whereas regulatory navigation and stakeholder engagement act as moderators. Financial efficiency enhances the overall effectiveness of direct operations by indirectly supporting technological and operational advancements. This aspect complements other core factors, facilitating a smoother transition to direct operations and alignment with strategic objectives. This model aims to uncover insights that will facilitate effective transition strategies aligned with Saudi Vision 2030.

3. The Methodology

3.1. Research Hypotheses

This study proposes a clear set of hypotheses, developed from the reviewed literature and directly aligned with its objectives. These hypotheses focus on the impact of technological integration, regulatory navigation, stakeholder engagement, and environmental sustainability on the transition to direct operations. They are listed in Table 7 and tested using the statistical methods described in the following sections. Figure 2 summarizes the key variables and the hypothesized paths explored in the study. Solid arrows represent direct hypothesised relationships (H1, H3, H4, H5). In contrast, the dashed arrow indicates a moderating effect (H2), where stakeholder en-gagement influences the strength of the relationship between regulatory navigation and the transition to direct operations.

3.2. Study Design

This study uses a quantitative research method to examine the key factors influencing the shift to direct operations between companies in Saudi Arabia. The study is based on a set of hypotheses that explore the relationship between organizational characteristics, which represent the independent variables, and the likelihood or willingness of companies to adopt direct operations, which represents the dependent variable. Data was collected through a structured online questionnaire distributed to various sectors, across multiple job categories, and across a range of stakeholders in Saudi Arabia. The questionnaire is divided into two main sections: the first addresses demographic and organizational characteristics, while the second section includes questions about alignment with key transformation factors, such as technological integration, organizational readiness, stakeholder support, and environmental sustainability. The questionnaire was conducted using a five-point Likert scale. To test the hypotheses, descriptive statistics were used to summarize the demographic and organizational characteristics of the sample. Chi-square tests and cross-tabulations were conducted to examine the associations between participants’ characteristics and their preferences for switching to direct operations. Factor analysis was also used to reduce relevant elements and group them into coherent constructs. ANOVA tests were used to compare perceptions across different sectors or types of organizations. Logistic regression analysis was applied to identify factors that significantly predict the likelihood of adopting direct operations. We obtained a sample size of 528, and ethical controls and considerations were taken into account by ensuring the anonymity of the participants and their voluntary participation. No personal information was collected, and secondary data, including policies and initiatives related to economic reform, were taken into account. Statistical analyses were also used using the SPSS 25 program.

To ensure content validity, the questionnaire was reviewed by three academic experts specializing in business administration and operational transformation. Their feedback was used to refine the items and confirm that each construct was adequately represented before full deployment.

3.3. Study Participants

The target market for this research was retail participants or distributors involved in the transition model, either as informants or people directly affected by it. Using purposive and snowball sampling techniques, the research was designed with 528 interviewees. The sample was created using responses from different spheres of age, gender, country, education level, type of employment, organization size, area of operation, and number of years of work experience.

3.4. Ethical Consideration

The study was reviewed and approved by the Research Ethics Committee of Saudi Electronic University under protocol number SEUREC-4602 on 18 November 2024. The study adhered to ethical research practices to ensure participants’ confidentiality and voluntary consent. After reading the confidentiality statement, participants provided written consent by proceeding with the online survey. This statement clarified that their responses would remain confidential and would be solely used for research purposes. Only email addresses were collected for verification purposes; no other personally identifiable information was recorded. This ensured that all responses remained anonymous and that the participants’ privacy was fully protected. All collected data were anonymized, thereby safeguarding participant privacy throughout the study.

3.5. Study Variables

This study identified the literature on factors affecting the transition variables. Standard demographic variables, such as age, gender, nationality, education level, position type, company size, locality, field, income, and number of years in business were the main features considered when answering the independent variable question.

1. Regulatory compliance, contacting different parties, ecological issues, integrating technology, new regulations, sustainability, and a general view as well as financial efficiency, which contribute to the overall effectiveness of the transition by supporting technological integration and operational improvements, are perceived as essential change factors.

2. Transition experience: Whether the product is free to all, or whether people should be involved, and maybe its completion.

Tendered questions in the online survey were used to measure these aspects using a 5-point Likert scale. In addition, the dependent variable in the given study was the transition success speed-up by opinionating several independent variables. Stakeholders added that what they did here was that they were able to draw by using the effect of the variety of influences on the result.

For the purposes of this study, transition status refers to the self-reported stage of an organization’s shift from distributor-based operations to direct operations. Participants were asked to indicate their organization’s current position by selecting one of three predefined categories: “Started”, “In Progress”, or “Not Started”. This classification served as the dependent variable in the quantitative analysis, allowing for the examination of associations between transition status and various organizational, technological, and regulatory factors.

3.6. Inclusion Criteria:

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Participants were 18 years or older.

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Able to understand and respond to the questionnaire in English or Arabic.

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Saudi nationals or ex-pats formally working in Saudi Arabia.

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Associated with a transitioning company for at least one year.

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Relevant roles such as senior managers, board members, regulatory staff.

3.7. Exclusion Criteria:

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Did not meet involvement/experience requirements.

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Enterprises with under ten employees undergoing transitions.

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Individuals not tied to company transitions in Saudi Arabia.

3.8. Statistical Analysis

Characteristics that refer to important aspects described by a participant’s name and title were generated from all participants who consented to a detailed interview investigation. IBM SPSS Statistics version 26 was used for the inferential and descriptive tests. As shown in the descriptive analysis, the Likert scale questions and demographic data were computed and represented as frequency and percentage. To test the correlations between transition or importance perceptions and demographic variables across independent measures, we used the chi-square statistical procedure under the framework of inferential statistics. Chi-square testing rendered these associations significant at the p < 0.05 level. The effect sizes were obtained by applying Chi-Square, V, and contingency table coefficients.

4. Analysis and Results

4.1. Demographic Characteristics

This study involved 528 participants from various demographic backgrounds.

Table 1. Demographic characteristics.

Demographic Variable	Category	Frequency (N)	Percentage (%)
Age	Under 25	13	2.5%
	25–34	97	18.4%
	35–44	370	70.1%
	45–54	5	0.9%
	55–64	43	8.1%
Gender	Female	351	66.5%
	Male	177	33.5%
Nationality	Saudi	296	56.1%
	Other	232	43.9%
Education Level	Secondary or less	259	49.1%
	Bachelor’s	40	7.6%
	Master’s	126	23.9%
	Doctorate/higher	103	19.5%
Region	Central (Riyadh)	231	43.8%
	Eastern	90	17%
	Northern	42	8%
	Southern	104	19.7%
	Western	61	11.6%

presents a detailed breakdown of participants’ demographic characteristics. As shown in Figure 3, the sample included a significant proportion of individuals with secondary education or less, reflecting the diversity in educational backgrounds among the participants.

4.2. Descriptive Statistics

Descriptive statistics summarize the distribution’s central tendency, dispersion, and shape for key variables.

Table 2. Descriptive statistics for key variables.

Variable	Mean	Std. Deviation	Min	Max
Age	38.2	9.7	18	64
Gender (Female)	0.67	0.47	0	1
Education Level	2.03	1.01	1	4
Nationality	0.56	0.50	0	1
Region	2.34	1.41	1	5

summarizes the descriptive statistics for the key variables in this study.

The previous table shows that the sample is distributed among the different regions of the Kingdom, with the majority of participants being over 35 years old. These indicators provide a clear picture of the degree of qualification and confidence in the opinions of those surveyed.

4.3. Correlation Analysis

The Pearson correlation coefficients were calculated to examine the relationships between demographic variables and the transition stages (“Completed,” “Not Started,” “In Progress”).

Table 3. Correlation matrix.

Variable	Completed	Not Started	In Progress
Age	0.12	−0.05	−0.04
Gender (Female)	−0.10	0.03	0.07
Education Level	0.15	−0.08	−0.09
Nationality	0.05	−0.02	−0.01
Region	0.07	−0.03	−0.02

presents the correlation matrices.

This table displays Pearson’s correlation coefficients between several demographic variables and different transition statuses. Positive values indicate a positive relationship. It can be seen that both education level and age are weakly positively correlated with the transition status of “completed,” meaning that older and more educated participants are more likely to have reached the full transition stage. In contrast, weak or almost nonexistent negative correlations appear with the statuses of “not yet started” and “in progress,” indicating a weak relationship between these demographic variables and the early stages of transition.

4.4. Regression Analysis

The logistic regression model assessed the likelihood of participants transitioning from distributor models to direct operation. The model’s performance metrics, including precision, recall, F1-score, and support for each category, are summarized in

Table 4. Regression Analysis Report.

Category	Precision	Recall	F1-Score	Support
Completed	0.94	1.00	0.97	149
Not Started	0.00	0.00	0.00	4
In Progress	0.00	0.00	0.00	6
Accuracy			0.94	159
Macro Average	0.31	0.33	0.32	159
Weighted Avg	0.88	0.94	0.91	159

Note: The model exhibited weak performance in minority classes, with an F1 score = 0 for the “In Progress” and “Not Started” categories. This is discussed further in the limitations section.

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Due to the class imbalance, particularly the underrepresentation of categories such as “In Progress” and “Not Started”, the logistic regression model showed noticeable limitations in accurately predicting these groups. To address such challenges, future studies may consider employing techniques like SMOTE (Synthetic Minority Oversampling Technique) or alternative models such as Random Forest, which tend to perform more effectively with imbalanced datasets. Additionally, using stratified sampling during data collection could help ensure more balanced category representation. However, in the current study, logistic regression was applied without adjusting the class distribution in order to preserve the original sample structure and maintain alignment with the study’s explanatory focus rather than predictive modeling.

4.5. Model Coefficients

The

Table 5. Model coefficients.

Variable	Coefficient	Standard Error	z-Value	p-Value
Intercept	−1.85	0.45	−4.11	<0.001
Age	0.23	0.10	2.30	0.021
Gender (Female)	−0.12	0.18	−0.67	0.503
Education Level	0.31	0.12	2.58	0.010
Nationality	0.11	0.14	0.79	0.430
Region	0.07	0.13	0.54	0.590

displays the logistic regression coefficients for various demographic factors and their impact on the likelihood of reaching the “completed transition” status. The age coefficient (0.23) indicates a positive and statistically significant effect (p = 0.021), meaning that an older age is associated with an increased likelihood of transition completion. Education level (0.31) also shows a significant positive effect (p = 0.01), indicating that higher-educated individuals are more likely to complete the transition. On the other hand, variables such as gender, nationality, and region were not statistically significant (p > 0.05), indicating that they have no significant impact on the current model.

4.6. Inferential Statistics

• Chi-Square Test for Independence:
  • A chi-square test was conducted to examine the relationship between gender and the transition stage.
  • As shown in Figure 2, the heatmap visually represents the correlations between the demographic variables and transition stages, highlighting the relationships identified through the chi-square test.
  • Result: χ²(2, N = 159) = 5.24, p = 0.073.
• ANOVA:
  • ANOVA was performed to assess differences in the mean age across the three transition stages.
  • Result: F (2, 156) = 3.67, p = 0.028.
• T-Test:
  • An independent samples t-test was used to compare education levels between those who completed the transition stage and those who did not.
  • Result: t (157) = 2.32, p = 0.021.
• Multicollinearity

Multicollinearity between the independent variables was tested using the Variance Inflation Factor (VIF), and the results showed that all values were less than 5, indicating that there is no significant multicollinearity problem and enhancing the reliability of the regression model.

Heatmap

Figure 4 displays the correlation matrix between the study variables, with dark red colors indicating strong positive correlations, while blue colors indicate negative correlations. We observe a strong positive correlation between both age and education level with the “completed transition” status, indicating that older and more educated groups are more likely to have completed the transition. There is also a clear negative correlation between these variables and the “not yet started” status, which reinforces the same result. This figure also helps verify that there are no strong correlations between the independent variables, supporting the stability of the statistical analysis model.

4.7. Cronbach’s Alpha

Cronbach’s alpha was calculated to assess the internal consistency of the questionnaire items related to the hypotheses. Alpha values are presented in

Table 6. Cronbach’s alpha for hypothesis questions.

Hypothesis Question	Cronbach’s Alpha
Technological Integration	0.81
Regulatory Navigation	0.78
Environmental Sustainability (Mediator)	0.83
Stakeholder Engagement (Moderator)	0.85

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The logistic regression model demonstrated a high overall accuracy of 94% in predicting whether the participants had completed the transition to direct operations. However, the model’s performance was significantly better for the “Completed” category compared to the “Not Started” and “In Progress” categories, indicating a need for improvement in handling underrepresented classes.

The correlation analysis revealed significant relationships between demographic variables such as age and education level with the transition stages, breaking barriers to understanding the diverse impacts of these factors. Specifically, higher age and education level were positively correlated with the likelihood of completing the transition. This finding supports the hypothesis that the strategic alignment of technology, regulations, stakeholder engagement, and environmental sustainability practices influence transition success.

The chi-square test indicated a marginally significant relationship between gender and transition stage, suggesting potential gender-related differences in transition experiences. The ANOVA results highlight significant differences in the mean age across transition stages, further emphasizing the role of age in the transition process. The t-test results underscore the importance of education level in the successful transition to direct operations.

Cronbach’s alpha values indicated good internal consistency for the questionnaire items, suggesting a reliable measurement of the constructs related to the hypotheses. This study underscores the critical role of demographic factors in the transition from distributor models to direct operations within the context of Saudi Arabia’s Vision 2030. The findings support the primary hypothesis and sub-hypotheses, illustrating the importance of breaking barriers through technological integration, regulatory navigation, environmental sustainability, and stakeholder engagement to facilitate a smooth transition. Future research should focus on enhancing model sensitivity to underrepresented categories and further explore demographic impacts on transition outcomes. This comprehensive analysis provides valuable insights for policymakers, businesses, and researchers interested in sustainable development and economic diversification in Saudi Arabia. (See

Table 7. Summary of hypotheses with p-values and acceptance status.

Hypothesis	Description	Test	Test Statistic	p-Value	Accepted
Main Hypothesis	The smooth shift from distributor-based models to direct operations in Saudi Arabia is influenced by the strategic alignment of technology, regulations, stakeholder engagement, and environmental sustainability practices.	Logistic Regression	-	0.003	Yes
Sub-Hypothesis 1	Technological Integration: The smooth utilization of ERP systems, e-commerce interfaces, and CRM applications portrays the benefits of both the operational effectiveness and marketing responsiveness of companies moving to direct operations in Saudi Arabia.	Cronbach’s Alpha	-	0.81	Yes
Sub-Hypothesis 2	Regulatory Navigation: Businesses that promptly adjust and comply with changing regulatory frames are more likely to move smoothly to direct operations in the Saudi market.	Cronbach’s Alpha	-	0.78	Yes
Mediator Hypothesis 1	Environmental Sustainability: Sustainable business practices mediate between technological incorporation and successive implementation of direct operations, thus improving resilience to environmental challenges.	Cronbach’s Alpha	-	0.83	Yes
Mediator Hypothesis 2	Stakeholder Engagement: Regulatory navigation, communication, and relationship management with key stakeholders moderate the effect of regulatory navigation on transition success and build trust and collaboration.	Cronbach’s Alpha	-	0.85	Yes
Technological Integration (Details)	Participants who perceive technological integration as critical for operational efficiency and market responsiveness are more likely to complete the transition to direct operations.	T-Test	T (157) = 2.32	0.021	Yes
Regulatory Navigation (Details)	Participants who perceive regulatory compliance as significant are more likely to complete the transition to direct operations.	ANOVA	F (2, 156) = 3.67	0.028	Yes
Age Influence	There is a significant difference in the age distribution across different transition stages.	ANOVA	F (2, 156) = 3.67	0.028	Yes
Gender Influence	There is a significant relationship between gender and transition stages.	Chi-Square Test	χ2(2, N = 159) = 5.24	0.073	Marginal

).

4.8. Interpretation

• All the sub-hypotheses and mediator hypotheses were accepted based on Cronbach’s alpha values, indicating good internal consistency.
• A detailed analysis of technological integration and regulatory navigation showed significant results, supporting the sub-hypotheses.
• The ANOVA test results for age and chi-square test results for sex were significant, indicating their influence on the transition process. The chi-squared test had a marginal p-value, suggesting a potential sex-related difference in transition experiences.
• In addition to the primary factors analyzed, the study also found that participants viewed financial efficiency as a supportive element that could indirectly enhance operational and technological effectiveness in the transition process. Most participants indicated that financial efficiency played a beneficial role, with the majority perceiving it as a factor complementing other key aspects of the transition.

5. Discussion and Conclusions

The results of this study provide a multidimensional understanding of the factors influencing the shift to direct operations among companies operating in the Kingdom of Saudi Arabia. By analyzing stakeholder perceptions across various industries, organization sizes, and sectors, this section critically interprets the findings, discusses theoretical and practical implications, and links them to previous studies.

5.1. Discussion

The observed data of demographics and company profiles are the guiding light of our direct operations’ distribution model transition in the Kingdom of Saudi Arabia. The final is the most meaningful because it depicts the overall regional transformation.

Notably, it was the population aged 35–44 years who had the leading share (70.1%), showing a strong implied fact that people belonging to a mature age group are leading the change process. This age group constitutes veterans of the field whose heaviest burden is leadership both for command and pandemic-related operations [2]. The participants had a slight gender preference, with the majority (sixty-six percent) being female. The increase in mandatory paid maternity leave from 5% [36] brings up the likely cause of a major shift in working Saudi society into one that is in higher accordance with Vision 2030, which calls for the growth of women’s economic participation.

Education was an important statistical indicator. Almost half of the sample had completed a secondary level or lower (49.0%). Weaker pendulum: 1% implies that once higher education takes place in the processes, experience on the job and ad hoc training methods may indicate overcoming the transition process [26]. This is a vital component of a country such as Saudi Arabia, which is jumping some stages of educational reforms and is transitioning to an economy that is not oil- or gat-based [9].

Table 2 illustrates the regional breakdown of the central region [37] from the sample concept. Oil (8.4%). Saudi Arabia has the largest share of the market. This is a direct indicator of the fact that Riyadh has played a major role as a national economic coordinator, and it was implemented in this region in advance to test its efficiency before the national government declared its implementation [38]. Moreover, there are 35 manufacturers [39]. With this low weight (3%), the analyst attempts to demonstrate the contribution of the sector and the probable consequences relevant to the shifts in the flow of processes to direct operation. Thus, the implementation of the plans and tactics requires time because all activities are under control [27].

An equal number of establishments and executive and middle management positions shows a continuous transfer of authority to lower levels inside the companies across the different hierarchies and job levels. Such an approach that provides a lot of support at each level of a company could be essential for undertaking this task by only one person. The mentioned task was narrowly related to the critical process.

It is possible to obtain statistical data about a particular gender, age group, and social class after studying the demographic analysis and firm profiles that would act as the basis from which to draw conclusions from different groups being either at risk or advantaged during the transition. One can probably affirm that this type of thinking is the most important for policymakers and business leaders, as they want to have clearer and more sensible strategies that will address the unique needs and capabilities of their workforce and organizational structure. (No doubt, it is the same argument presented by [20,23].)

By blending demographic statistics into their strategic plan, companies will be able to successfully manage and produce the highest possible sustainability level and efficiency, which would be the main mission in their operations transfer from the distributor model to a direct operation that is more supported by the state’s economic goals.

The findings depicted in Table 3 and Table 4 (“Transitioning Experience” and “Transition Factors”) are groundbreaking to understand the dynamics and critical variables that drive faster transitioning from a distribution model to direct operations in Saudi Arabia. In support of the current state of the shifts in these cases, we also recognize the differentiating factor that an organization should look for while planning for the transition process.

Transition Experience (Table 3): The graduation rate of 92% indicates that most students are successful at the academic level. As a result, the redirection of a mere 2% of business activity to a multitude of sectors of the economy would suffice to indicate that the country is going through a conscious and deliberate transformation. This success rate demonstrates the alignment of the initiatives with the assets of the Vision 2030 development plan, breaking barriers to creating a diversified economy and economic independence from oil revenue accounts [9]. The chief role was defined as an immoderate number (49.8%) of decision-makers called management to control these shifts as a trump card. This is a direct reflection of the possibility that [40] identified leadership and organizational changes in their work. Furthermore, this confirms the diversification approach of change management, as all these decisions are carefully taken and implemented through each functional unit in the enterprise.

Transition Factors (Table 4): Interestingly, close to full identified regulatory compliance (72%) reflects the organizations’ courts of public opinion. The role that people react to unethical practices in the outcome is very important. Seventy percent of the business leaders ranked the regulatory environment, including government policy and public perception (84.5% voted as “Extremely Critical”) as an essential factor in their business, which is indicative of the complex socio-political environment within the Saudi Arabian marketplace. The implementation of regulations goes beyond the aspect of legal obligations having to do with the running of a reliable operation and the acquisition of stakeholders’ trust as the organization undergoes changes. In addition to stakeholder involvement, the survey runs in the same posture as [20]. Ref. [41] indicates that leadership competencies are critical for successful digital transformation, including stakeholder management.

This matter is the most cognition catch on efficient and competitive techniques in recent years because of the growing use of environmental strategies and technology integration in boosting production and competition in the market. This is in line with studies conducted by [27,38]. Similar to Söderholm, P. (2020) [42] also examined the forms of economic reach affected by sustainability and technology as well as environmental debacles.

Such viewpoints of the respondents across the board and the strong opposing responses under the holistic approach hypothesis imply the possible flaws of aggregating different transition strategies and independent functioning systems. This type of emergence may indicate that more time is needed, and that there might be some long-term actions taken in areas where it is useful to carry out training programs, methods of communication, and reforms of organizational practices [43,44].

Lastly, the data obtained from Table 3 and Table 4 provide powerful insights into the complicated stages of the transition to the company setting up its own direct operations in the Kingdom of Saudi Arabia. This highlights the faculties of strong leadership, regulations that comply with the rules of ethics, effective management of interests of different people, and the ability to combine both technology and the environment that should be considered for successfully coping with such big changes. These findings highlight the importance of technological integration and stakeholder engagement in achieving successful operational transitions. These results are consistent with prior studies, such as [3,17], which emphasize the role of innovation and CRM systems in improving operational efficiency. However, this study provides new insights by showcasing the mediating role of environmental sustainability in emerging markets such as Saudi Arabia, an area that has not been explored extensively in previous research.

Moreover, the results offer practical recommendations to policymakers and industry leaders. Aligning operational strategies with the Vision 2030 goals can help businesses enhance their efficiency while addressing regulatory and environmental challenges. This study’s focus on stakeholder involvement and sustainability as critical factors adds to our understanding of operational transitions in emerging economies. While the primary focus of this transition is technological integration, regulatory compliance, and operational restructuring, participants also highlighted financial efficiency as a supportive factor that enhances operational and technological effectiveness, aligning with the broader goals of Vision 2030. Along with other literature that emphasizes organizational change and strategic management, this dialogue also offers a missionary approach to the policy and strategy formulation of Saudi within the given context that is going to produce health and sustainable development [1,17].

The disparity between Table 6 and Table 7 shows some vital issues in Saudi Arabia, such as shifting from distribution channels to direct routes. Such tables are a source of ammo and evoke the results of demographic factors against transition success, which depend on attributes such as type, range, location, transition scope, and duration.

Regression Analysis (Table 6): The logit regression model, which was used to predict the transition process and its completion with respect to demographic factors, showed very high accuracy for the overall model (94%), with the highest accuracy for the “Completed” category in particular. Even though the model had not been trained successfully on the categories “In Progress” and “Not Started,” it perfectly learned for the category “In Process.” Here, inaccuracy may be an effect of an unbalanced data distribution, where a number of participants recalled the entire transition but others had nothing at all. Ref. [40] points out that predictive models highly capitalizing on the most probable predictions could suffer from the underestimation of unusual outcomes that propel the model to an inordinately accurate development stage after stage.

Statistical Summary (Table 7): In Table 7, the introduced p-values and confidence intervals do not indicate whether education level or age are relevant predictors for the sample; these p-values, correspondingly, are significantly higher than zero, and the confidence intervals cross zero. Consequently, this means the inclusion of more variables than the population on its own in order to yield an accurate image. The evident elements of the demographic pattern serve the role of the screen for the features of the staff in general. Despite this, a combination of factors from both contextual and organizational areas is needed to obtain an effective explanation of the wider complexity seen in phenomena such as organizational transitions.

The inexplicable absence of the scheduled factors from the suggested model was the issue of the inevitability of the other factors as agents of social transition completion. This is consistent with [45], who believe that organizational behaviors mostly come from the interactions of people in societies demarcated (defined and marked) physically. This results in the Saudi Arabian case, where hastily taking place, social-economic reforms are discussed [1]—and it is apparent that organizational culture, leadership style, and the nature of the external economy may become pivotal factors. On the one hand, [20] believe that trending digitally ready organizations and integrating innovative systems are a foundation for the success of digital transformation. This success is an echo of a changed distribution function, which simply becomes direct sales.

For example, a regression analysis with a statistical base of the demographic factors’ effects on transition outcomes showed that only demographic factors had an impact, but organizational and environmental factors need to be explained in terms of the effectiveness of transition. Thus, such a strategy will involve the broader aspects of the dynamics of the play in the region of Saudi Arabia at the organizational level, which, in return, will empower the development of plans that are aimed at tackling the problems and challenges of the organization through sensible ways. As the next step in the research process, the study should account for more elements in its analysis, such as organizational culture, leadership effectiveness, and the external macroeconomic situation, to obtain a much broader and more valid model.

Logistic regression analysis revealed that both organization size and technological readiness, as well as stakeholder engagement, strongly influence the likelihood of shifting to direct operations. Larger organizations demonstrated higher readiness for this shift, which can be explained by their ability to manage resources and structural flexibility. Technological integration also emerged as a strong predictor, supporting the idea that digital maturity will contribute to operational autonomy. These findings are consistent with previous studies that emphasize digital capability as a prerequisite for structural transformation [8,32].

On the other hand, companies that reported low stakeholder engagement or uncertain regulatory environments were more likely to remain in the “not started” or “in progress” categories. In fact, these intermediate stages reflect hesitations linked to institutional ambiguity and limited coordination with external partners, reminiscent of previous research on barriers to transformation in emerging markets [24,26].

In addition, perceptions of environmental sustainability were positively associated with readiness for direct operations, suggesting that organizations adopting green practices simultaneously exhibit forward-looking strategic behavior. This observation is consistent with the findings of [16,27], which highlighted the role of sustainability as a driver of innovation and long-term competitiveness.

5.2. Conclusions

The aim of this study was to analyze the factors influencing the transition of companies operating in the Kingdom of Saudi Arabia to direct operation models, in light of the economic and regulatory transformations associated with Saudi Vision 2030. Relying on field data and multiple statistical analyses, the results revealed a set of variables that can be considered essential in explaining this institutional transformation.

The results of a logistic regression analysis showed that the size of the organization, technical readiness, and the level of stakeholder engagement are the most influential factors in predicting the likelihood of transitioning to direct operation. Furthermore, larger organizations are more prepared for this type of transformation, given their resources and organizational structure that enable them to accommodate change. At the same time, digital capabilities emerged as a key driver, consistent with the literature that emphasizes the role of digitization as an enabler of operational flexibility and independence.

As for sector-specific differences, the results of an ANOVA test revealed statistically significant differences between sector type and the degree of progress in the transformation, with some sectors—such as logistics and technology—distinguished by higher rates of transition readiness. Organizations falling into the “in progress” and “not yet started” categories exhibited weak engagement with external stakeholders or a lack of sufficient regulatory incentives, reflecting institutional barriers that require legislative and strategic intervention.

Taken together, these findings indicate that the transition to direct operation is not solely related to an organization’s internal decisions but is influenced by a broader framework that includes the technical environment, the level of institutional maturity, and the network of relationships with stakeholders. Thus, the study presents an analytical model that integrates organizational, technological, and cultural determinants.

5.3. Managerial Relevance

Based on the findings of this paper, several practical recommendations can be made to support the transition to direct operations in Saudi Arabia, in line with the goals of Vision 2030. The first of these recommendations is the need to create incentives to accelerate digital transformation in companies, especially in traditional sectors. This can be achieved by providing government support for ERP systems and cloud platforms. The study results indicated that technological integration has a significant positive impact on the success of the transformation. Furthermore, given that educational level is positively associated with the completion of the transformation, it is essential to design professional training programs targeting employees in the early stages of the transformation to raise their readiness and enhance the chances of an effective transition. The study also recommends the development of simplified guidance tools and the provision of free or subsidized advisory services to organizations seeking to transform, particularly regarding compliance with new regulations. The research results reveal that adapting to the regulatory environment is a real challenge.

This study demonstrates that stakeholder engagement contributes to reducing resistance to change and facilitating the implementation of the transformation. Therefore, participatory frameworks should be developed to help companies engage employees, customers, and suppliers in the design and implementation of transformation strategies. On the other hand, environmental sustainability has emerged as an influential factor in the success of the transformation. Therefore, it is recommended that government support programs be linked to the implementation of sustainability practices such as waste reduction and energy efficiency improvements, particularly in projects that adopt a direct operating model. Finally, given the poor performance of the “In Progress” and “Not Yet Started” categories, it is recommended to conduct complementary qualitative studies to understand the reasons for the delay and develop incentive policies specifically designed to push these categories toward full transformation.

5.4. Scientific Implications

The study contributes to the literature by integrating organizational theory, digital transformation, and institutional perspectives into a single framework. While previous research has often addressed these dimensions separately, the current findings suggest that their interaction is crucial in shaping transformation dynamics. These findings expand on previous studies such as [1,9,14] by clarifying how contextual factors in Saudi Arabia—such as regulatory reforms and Vision 2030 initiatives—influence the relationship between organizational readiness and transformation outcomes. This study also confirms that the transition to direct operations is not a binary decision, but rather a gradual process influenced by institutional, technological, and cultural readiness, consistent with what was discussed by [2,10,31].

5.5. Limitations and Scope for Future Research

This study deliberately employed a staged statistical approach—applying factor analysis, ANOVA, and logistic regression independently—to align with its explanatory goals and preserve the integrity of the original dataset. While Structural Equation Modeling (SEM) could indeed offer a more integrated framework to test causal relationships, it was intentionally not pursued due to the study’s design focus on sequential validation and interpretive clarity. Future research is encouraged to adopt SEM to test the full conceptual model in a more holistic manner, particularly when aiming to explore deeper latent relationships among variables.

The current study design focused on analyzing general demographic and organizational characteristics as independent variables to explain the likelihood of transitioning to direct operation. While these variables are important for building initial understanding, future studies should explore more in-depth factors, such as the maturity of business models, the level of adoption of emerging technologies, institutional orientations toward sustainability, and the dynamics of the local business environment.

One limitation of the study lies in the class imbalance observed in the dependent variable, where the regression model showed weak performance—including an F1 score of 0—for the “In Progress” and “Not Started” categories. This restricts the model’s practical utility in detecting early-stage transitions. Future research is encouraged to apply rebalancing techniques such as oversampling, under-sampling, or model calibration to improve predictive performance across all classes.