953 American Journal of Economic and Management Business e-ISSN: 2835-5199 Vol. 4 No. 7 July 2025 Implementation of Partnership Scheme Strategy on Cost Efficiency and Drivers' Performance at PT X Jakarta Luthfi Khairawan Putra, Bobby Wiryawan Sekolah Tinggi Ilmu Ekonomi Harapan Bangsa, Indonesia E-mail: luthfi.khairawan@gmail.com, bobby@ithb.ac.id Abstract Market behavior shifts and digital disruptions in the transportation industry over the past decades have prompted PT X Jakarta to undertake structural adjustments through the implementation of a civil-law-based partnership scheme. This strategy aims not only to reduce the rigidity of fixed labor costs but also to enhance operational flexibility in responding to fluctuating service demands. However, the effectiveness of this strategy requires empirical validation, particularly concerning its impact on cost efficiency and driver performance, two critical elements for sustaining competitive advantage and long-term business viability. This study investigates the influence of the partnership scheme implementation on cost efficiency and driver performance. The research framework is grounded in Transaction Cost Economics, Workforce Flexibility Theory, Self-Determination Theory, and Agency Theory, which collectively explain structural efficiency rationale, the importance of numerical and financial flexibility, and the role of autonomous motivation and incentive systems in non-hierarchical work arrangements. Employing a quantitative approach with an explanatory-causal design, data were collected from 200 active partner drivers using a Likert-scale questionnaire and analyzed using both simple and multiple linear regression. The results indicate that the partnership scheme significantly affects cost efficiency (β = 0.656; R² = 47.4%) and driver performance (β = 0.327; R² = 34.9%). These findings affirm that a well-structured partnership model can serve as an effective cost-efficiency strategy without compromising performance, provided it is supported by a fair compensation system and adequate operational support. The study offers practical implications for transportation organizations seeking to build adaptive, efficient, and sustainable workforce systems. Keywords: partnership scheme, cost efficiency, driver performance, workforce flexibility, human resource strategy INTRODUCTION The transportation industry landscape is experiencing significant disruption alongside the rapid development of digital technology. The transformation process in the transportation industry was accelerated by the emergence of global transportation technology companies such as Uber and Lyft, which implemented a platform-based business model with a gig economy scheme (Cramer & Krueger, 2016). One of the main manifestations of this transformation phenomenon is the shift in consumer preferences from private vehicle ownership towards the concept of Mobility as a American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 954 Service (MaaS), which is a digital platform-based mobility service that offers flexible, on-demand, and multimodal access for its users (Jittrapirom et al., 2017). This growth, which has led to a change in consumer preferences, has increased the urgency for transportation companies to reconstruct their traditional business models to respond to market dynamics that increasingly demand efficiency, flexibility, and ease of service (Shaheen & Cohen, 2019). Platform-based business models are not only changing the way consumers access transportation services, but also transforming the employment structure within the industry (Zhang et al., 2020). The rise of app-based services such as Uber, Grab, and Gojek has shifted the focus towards a more demand-driven and user-centered mobility approach (Li et al., 2021). This transformation is driven by digitalization, which enables real-time matching of demand and supply, thus improving operational efficiency (Narayanan et al., 2020). However, the transition has also raised concerns about labor rights and job precarity, as platform workers often face uncertain income and lack of social protection (Rosenblat & Stark, 2016). Additionally, this model allows transportation providers to scale rapidly without proportional increases in fixed assets, fundamentally altering cost structures (Heinrichs, 2016). Consequently, understanding the dual impact on service delivery and labor market dynamics is essential for policymakers and businesses alike (Frenken & Schor, 2017). A study conducted by Wallsten (2015) revealed that the penetration of application-based transportation services has reduced the number of conventional taxi trips by 10% in major cities in the United States, demonstrating a significant disruptive impact on traditional transportation business models. This development has led to the emergence of a gig economy model that emphasizes flexibility and autonomy in employment relationships (Wood et al., 2019), in line with the global transformation of the future of work, which increasingly prioritizes flexible work models. The phenomenon of global transformation in the transportation industry also had a significant impact on the industrial landscape in Indonesia in the same period (Dіachuk et al., 2023). In the Business-to-Customer (B2C) segment, this shift in consumer behavior is supported by an increase in the number of internet users and high smartphone penetration in Indonesia, which—according to data from the Central Statistics Agency (2023)—has reached 73.7% of the total population in 2023, in line with the growth graph of smartphone use in Indonesia below. This digital penetration is also marked by the emergence of ride-sharing services such as Gojek and Grab, which have significantly disrupted customer consumption patterns and transportation business models (Wirtz & Zeithaml, 2018). The prospect of ride-hailing services in Indonesia is predicted to have a market size of $4.78 billion with a CAGR of 8.80% as visualized in Figure 1.3. The growth of ride-hailing services such as Grab and GoCar has caused many taxi companies and base motorcycle taxi operators to have difficulty competing, leading some to close their businesses. Gojek and Grab as the two dominant platforms in the ride-hailing and gig economy ecosystem in Indonesia have created structural changes in transportation consumption patterns and employment relations in this sector. Data estimates show that the number of Gojek Luthfi Khairawan Putra, Bobby Wiryawan 955 users has increased from around five million in 2016 to more than 75 million by 2025. Grab also experienced similar growth, from around three million to more than 60 million users in the same period. As the data presented by Databoks below shows regarding the highest number of online transportation applications in the Republic of Indonesia in 2023, in general there has been an increase in the number of people downloading online transportation applications. This impact is also felt by the vehicle and vehicle driver service rental industry, especially in the business-to-business (B2B) segment, which has been the main segment of rental companies in Indonesia. Initially, online transportation was an indirect competitor, but slowly, along with changes in consumer behavior, online transportation became a direct competitor for rental companies. Corporate clients are starting to reduce their reliance on long-term rental contracts— from being used to renting vehicles on a long-term basis (3–5 years), now they are starting to switch to on-demand rental schemes with more dynamic and economical pay-per-use schemes. The shift in this segment is also driven by the emergence of various digital platforms such as GoCar and GrabCar that create special corporate products offering application-based vehicle rental services with transparent prices, high flexibility, and a convenient booking process. This model allows companies to avoid fixed cost structures and only pay for services when needed, thus better adapting to daily operational dynamics and fluctuations in demand (Cramer & Krueger, 2016). This research was conducted at PT X's Jakarta branch, an outsourcing company that specializes in providing professional driver services. PT X has been supporting the needs of rental and logistics company drivers for more than twenty years, making it one of the most competent and trusted service providers in the industry. PT X operates throughout Indonesia with 32 provincial cities and 25 sites, managing 6,000 drivers mainly in the corporate segment. This change in demand structure puts real pressure on PT X, which has been focusing on serving the B2B market with a work model based on Fixed Time Work Agreements (PKWT). Over the past decade, as shown in Figure 1.6, PT X has experienced a drastic decline in the number of drivers managed, from more than 9,000 in 2012 to around 3,400 in 2022 (PT X Annual Report, 2023). The decline in performance experienced by PT X reflects a disruption that is not just a temporary challenge, but a fundamental change in the market's preference with regard to implementing a PKWT work model. This scheme is suitable for long-term contracts with fixed volumes, but has become less efficient and less flexible in the face of changes in market behavior. After conducting a comprehensive analysis of industry trends and changing consumer preferences, PT X realized the need for a fundamental transformation in the company's business model, and so began to formulate a new business model strategy by implementing the Partnership scheme as a service product development in 2022. The growth in the number of partners since implementation has been significant—from 40 partners in 2022 to 300 partners at PT X Jakarta branch and a total of 1,712 national partners by the end of 2024. The exponential growth in the number of partners shows that the formulation of the strategy carried out by PT X provides the opportunity to align its business model with the American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 956 demands of the contemporary market (Contractor & Lorange, 2002). PT X aims to remain competitive in the market and execute a long-term strategy, restoring its competitive advantage in the B2B segment as well as penetrating the B2C market segment, which is increasingly influenced by application-based services and on-demand preferences. The successful implementation of this partnership, based on PT X's internal study (2022), shows that the cost of managing one driver under a partnership is able to provide efficiency of 30– 40% lower than the PKWT scheme. Fixed cost components such as basic salary, fixed benefits, and social security, which must be paid regardless of driver productivity, become a significant financial burden, especially when market demand is declining (Cappelli & Keller, 2013). In addition, PT X will face serious challenges in the form of idle costs and decreased labor utilization, which have a direct impact on profitability. From a theoretical perspective, the implementation of the employment model in the transportation industry can be understood through the framework of Transaction Cost Economics (TCE) developed by Williamson (1981). This theory explains that companies tend to adopt systems that reduce transaction costs and minimize market uncertainty. In the context of the transportation industry, partnership schemes allow companies to reduce fixed costs related to human resource management while increasing flexibility in the face of fluctuations in market demand (Kalleberg, 2003). Product development toward this partnership model is designed and executed with clear strategic goals. First, PT X seeks to change the cost structure from fixed cost to variable cost that is more adaptive to market demand fluctuations. In the PKWT model, companies have to bear significant fixed costs regardless of the driver's productivity level, while in the partnership model, drivers' compensation is more aligned with their actual contributions. Second, the development of partner products aims to reduce idle time costs, which are a significant financial burden in the PKWT model. Third, the partnership scheme is expected to increase operational cost flexibility. In this scheme, drivers are positioned as independent partners with flexibility to choose working hours, while companies can adapt their cost structure to actual demand, increasing flexibility in workforce management to respond to changes in demand more efficiently. Thus, it can create a more competitive pricing structure to attract clients who have switched to online transportation services (Martínez-Sánchez et al., 2011). However, the cost efficiency obtained through this partnership scheme is not free from challenges. Driver performance remains a key factor in the success of the service, including productivity, customer satisfaction, and partner retention rates. If the partnership scheme is not designed in a balanced way between the interests of the company and the welfare of the partners, the potential for a performance decline can pose a serious risk that actually hinders business sustainability (Wallsten, 2015). Amid the company's push to cut fixed costs and increase operational flexibility, the aspect of driver performance is a critical point that should not be ignored. Driver performance not only reflects work productivity but also has a direct impact on customer experience, service image, and the sustainability of business relationships. When partnership schemes are designed with a Luthfi Khairawan Putra, Bobby Wiryawan 957 dominant orientation on efficiency, without considering the sustainability of income and the stability of the partner's work, the risk of performance decline becomes inevitable. This is in line with the findings of Abdul Jamil (2025) in a study on operational partnership strategies in the courier sector. The study revealed that although companies gain significant benefits in terms of cost efficiency and service expansion, partners are often faced with fluctuating incomes, lack of social protection, and reliance on work systems that they do not fully control. When partners have to chase the number of services to maintain income, work pressure increases, while job security and ownership decrease. In the long run, this situation has an impact on the quality of service and the loyalty of partners to the company. Furthermore, a study from Joewono, T.B. et al. (2021) emphasizes the importance of creating a positive work environment as a key to the success of partnership schemes in the digital transportation ecosystem. In the context of the controversy over the determination of online motorcycle taxi fares, the research shows that when drivers feel that they are not involved in policies related to their income, tensions arise, directly impacting work morale and service quality. Communication transparency, fairness in incentive schemes, and clarity of roles between companies and partners are important factors in creating healthy and mutually beneficial working relationships. The implications of these findings are very relevant for PT X, which is implementing a partnership scheme. If these partnerships are not built on the principle of balance—between the efficiency of the company and the sustainability of the well-being of the partners—then the company risks losing the key foundation of reliable services, which is the resource of motivated and high-performing drivers. Therefore, a humanist and long-term oriented partnership design is key, through an approach that includes clarity of compensation systems, operational support, and basic protection that partners deserve. Thus, this implementation not only encourages increased operational efficiency, but also contributes to the creation of a performance-based work ecosystem for partner drivers (Lee et al., 2023). The implementation of this partner driver scheme raises several fundamental questions that are at the core of this research in understanding whether the development of this partnership product can function as a strategy that is not only effective in terms of cost efficiency, but also able to drive optimal driver performance and support long-term operational sustainability. This research offers a comprehensive analytical framework to understand the dynamics of employment transformation in industries that are experiencing technological disruption. By integrating the theoretical perspectives of Transaction Cost Economics, Workforce Flexibility Theory, and Self-Determination Theory, the findings of this research are expected to support the development of adaptive HR management strategies as well as provide a reference for the vehicle rental industry in responding to digital disruption strategically. Based on the background description, this study aims to fill the gap in the existing study by analyzing the impact of the implementation of the partnership scheme at PT X, especially from the perspective of cost efficiency and driver performance. The main focus of this study is to evaluate the extent to which the development of this partnership product can be a strategy that is American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 958 not only financially efficient, but still encourages optimal driver performance and supports long- term business sustainability. This study aims to: Evaluate the effect of partnership scheme implementation on operational cost efficiency in PT X Jakarta. Evaluate the influence of the implementation of the partnership scheme on driver performance at PT X Jakarta. This research will enrich the theory and academic literature in management science, especially in the following aspects: Offering a conceptual understanding of partnership schemes as a cost efficiency strategy in workforce management in the service industry. Integrating various theoretical approaches, Transaction Cost Economics (TCE), Workforce Flexibility Theory (WFT), Self-Determination Theory (SDT), Agency Theory. To enrich the literature on the relationship between strategic variables: flexible work schemes, operational efficiency, and human resource performance. Provide a new perspective in the study of service-based organizations with adaptive and non-conventional work models. In addition to enriching the theoretical understanding of the causal relationships between individual variables, this approach contributes to filling in the gaps in the literature regarding the synergy between structural efficiency strategies (TCE, WFT) and their influence on performance output through the perspective of service-based organizations. The findings of this study can be used as a practical reference for interested parties, for the management of PT X: Develop a partnership policy that is efficient, adaptive, and still maintains the productivity and welfare of driver-partners. For rental or other transportation companies: Design a flexible work system that responds to market demand dynamics with a competitive cost structure. For HR and operational practitioners: Design a system of compensation, performance control, and training of partners that correspond to the characteristics of non-employee relationships. For policymakers or regulators: Provide an empirical reference for regulators in drafting flexible employment relations policies based on civil agreements in the transportation sector. RESEARCH METHODS This study examines the implementation of partnership schemes at PT X, a Jakarta-based driver labor service provider, focusing on drivers' perceptions and the impact on cost efficiency and performance from April to June 2025. Using an explanatory quantitative approach with an associative-causal design, the research analyzes the relationships between variables through questionnaire surveys and statistical analysis. The study aims to understand how the shift from conventional employment (PKWT) to partnership models affects operational outcomes in the competitive vehicle rental industry, which faces digital disruption and requires flexible cost structures, with PT X serving as a representative case of workforce transformation in transportation services. Following Creswell's (2018) and Sekaran & Bougie's (2019) methodologies, the study employs simple linear regression to test causal relationships between partnership schemes (independent variable), cost efficiency (Y1), and driver performance (Y2), providing quantifiable insights into how flexible work arrangements influence both operational metrics and individual productivity in non-hierarchical work systems. By analyzing data from drivers with a Luthfi Khairawan Putra, Bobby Wiryawan 959 minimum of three months' experience, this approach offers empirically validated conclusions about the strategic implications of partnership models in responding to industry dynamics, while maintaining academic rigor through its structured examination of cause-effect relationships without researcher intervention in natural organizational settings. RESULT AND DISCUSSION Validity and Reliability Tests Before further analysis is carried out, it is necessary to test the quality of the instruments used in this study. The validity and reliability test aims to ensure that the statement items in the questionnaire are able to measure the variables in question accurately and consistently. Validity indicates the extent to which the question items are able to accurately measure the construct in question, while reliability reflects the consistency of respondents' answers to the items measured in a single variable. The test was conducted using the help of SPSS software version 26. Validity Test Validity tests are used to measure the extent to which each item in the questionnaire is able to accurately represent the intended variable. In this study, the analysis technique used was the correlation of Pearson Product Moment with a significance level of 5% (α = 0.05). The number of respondents was 200 people, so the value of the table at the degree of freedom (df) 198 was 0.139. Table 1. Summary of Validity Test Results of Question Items Variable Number of Items Calculated Range Conclusion Partnership Scheme (X) 17 items 0.390–0.604 All items valid Cost Efficiency (Y1) 13 items 0.500–0.691 All items valid Driver Performance (Y2) 8 items 0.541–0.730 All items valid Source : Data processed (2025) The test results showed that all statement items on the Partnership Scheme (X), Cost Efficiency (Y1), and Driver Performance (Y2) variables had a calculated r value greater than the table r (> calculation r 0.139), as well as a significance value < 0.05. Thus, all items in this research instrument can be declared statistically valid. Conceptually, this validity indicates that the item of the statement has been developed based on relevant indicators and supported by a strong theory. For example, the indicators of flexibility and responsibility in the Partnership Scheme variables are compiled by referring to the theory of Workforce Flexibility and Self-Determination Theory (Kalleberg, 2003; Deci & Ryan, 2000), while the indicators on Cost Efficiency are based on the principles of Transaction Cost Economics (Williamson, 1981). For the Driver Performance variable, items are compiled based on task-based performance and customer satisfaction indicators that are internalized in a flexible work system. The validity of the construct achieved is an important basis that the instrument is able to accurately capture the perception of driver-partners towards each dimension of the variable being studied, making it suitable for use in reliability tests and analysis of relationships between variables at a later stage. American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 960 Reliability Test Once all items have been declared valid, the next step is to test the reliability or internal consistency of the instrument used. Reliability tests aim to assess the extent to which items in a single construct provide stable and consistent results when used to measure the same variables in similar times and conditions. A reliable instrument will generate reliable data for further analysis purposes. In this study, the reliability test was carried out using Cronbach's Alpha coefficient, where the reliability value of ≥ 0.70 was considered to meet good reliability standards (Hair et al., 2022). The closer you are to number 1, the higher the level of consistency. Data processing was carried out using SPSS version 26, and the test results are summarized in Table 2 below: Table 2. Reliability Test Results Variable Cronbach's Alpha Description Partnership Scheme (X) 0.819 Reliable (good) Cost Efficiency (Y1) 0.86 Very reliable Driver Performance (Y2) 0.798 Reliable (good) Source : Data processed (2025) All three research variables showed Cronbach's Alpha values above 0.70, which means that each item in the construct is correlated with each other and is able to measure the same concept consistently. These values indicate that the research instrument has adequate internal stability and can be used for further testing such as regression and analysis of relationships between variables. Conceptually, the high reliability of the Partnership Scheme variables shows that the dimensions of flexibility, output-based compensation, and operational responsibility are closely related in describing the form of an effective partnership relationship. Meanwhile, the high reliability values on Cost Efficiency and Driver Performance reflect that respondents' perceptions of efficiency and performance have been well recorded by theoretically and contextually structured statement items. Thus, it can be concluded that all instruments in this study are suitable for use in inferential analysis so that they can be used as a valid basis for measuring the relationship between constructs in regression tests and subsequent inferential analysis. Classic Assumption Test Before performing a linear regression analysis, it is important to ensure that the data used meet the basic assumptions of the classical regression model. The fulfillment of this assumption is necessary so that the results of regression estimation are unbiased, efficient, and consistent. In this study, a classical assumption test was carried out for three regression models: (1) the effect of the Partnership Scheme on Cost Efficiency, (2) the effect of the Partnership Scheme on Driver Performance. Luthfi Khairawan Putra, Bobby Wiryawan 961 Normality Test The normality test is one of the fundamental assumptions in classical linear regression that must be met in order for the model to have the property of BLUE (Best Linear Unbiased Estimator). This assumption is important to ensure that the residual regression model is distributed normally, so that the results of the regression parameter estimation are statistically valid. In this study, the normality test was carried out using the Kolmogorov-Smirnov (K-S) method through the Test of Normality feature in SPSS software version 26. Interpretation was carried out based on probability value (asymptotic significance) with a significance level of 5% (α = 0.05), in accordance with the guidelines from Ghozali (2016). The decision-making criteria are as follows:' a) If the significance value (Sig.) > 0.05 then the residual is normally distributed. b) If the significance value (Sig.) < 0.05 then the residual is not normally distributed. Residual distributions that deviate significantly from normality can impair the accuracy of inferential tests such as t-tests and F-tests, as cautioned by Gujarati (2012). The results of the normality test for the three regression models are presented in Table 3 below: Table 3. Normality Test Results Research Model Nilai Sig. (2-tailed) Results X → Y1 0.200 Usual X → Y2 0.200 Usual Source: Data processed (2025) All regression models showed significance values above 0.05, which means that the residual data from all three models were normally distributed. Thus, the assumption of normality has been met, and the regression model is feasible to use for further analysis. The fulfillment of this assumption also has important methodological implications. The normal residual distribution reinforces the validity of the regression analysis results which will be discussed in the next chapter. In addition, these results show that PT X's driver-partner perception data is reasonably dispersed and does not contain systematic outliers or deviations that can negatively affect the model's estimation. Thus, it can be concluded that the regression model used has met the prerequisites for the residual normal distribution, making it feasible to use in hypothesis testing and interpretation of regression results. Linearity Test The linearity test is carried out to evaluate whether there is a linear relationship between independent variables and dependent variables. This test is one of the important assumptions in linear regression analysis, because the regression model will only produce accurate estimates if the relationships between variables are indeed linear. Non-linear relationships can cause deviations in the estimation results and reduce the validity of research findings (Ghozali, 2016). In this study, the test was carried out using the Test of Linearity approach available in SPSS version 26. The interpretation of the results was carried out by paying attention to the significance value in the Deviation from Linearity component. The decision-making criteria refer to: American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 962 a) If the significance value of Deviation from Linearity > 0.05, then the relationship between variables is declared linear. b) If the significance value < 0.05, then the relationship is considered nonlinear and violates the basic assumption of linear regression. The test results for the two main models in this study are presented in the following Table 4: Table 4. Results of Intervariable Linearity Test Research Model Nilai Sig. Deviation from Linearity Results Partnership Scheme (X) → Cost Efficiency (Y1) 0.406 Relationships are linear Partnership Scheme (X) → Driver Performance (Y2) 0.708 Relationships are linear Source: Data processed (2025) Based on the test results, all models showed a significance value of Deviation from Linearity above 0.05, which means that there were no significant deviations from the linear relationship pattern. Thus, the assumption of linearity in the regression models used has been fulfilled. The fulfillment of this linearity assumption has important implications methodologically and practically. Statistically, this strengthens the validity of the regression model that will be used in hypothesis testing in the later stages. Meanwhile, in terms of the research context, these findings show that partner drivers' perceptions of partnership schemes and cost efficiency have a stable and proportional relationship to their performance. This means that an increase or decrease in the perception of partnership schemes and cost efficiency tends to be followed by a uniform change in the perception of performance, without an extreme deviant pattern of relationships. Thus, the regression model used in this study has fulfilled all the basic assumptions of classical linear regression and is statistically feasible for use in hypothesis testing at a later stage. Heteroscedasticity Test The heteroscedasticity test aims to evaluate whether the residual variance in the regression model is fixed (homoscedastic) or variable (heteroscedastic) at various levels of predictor values. The assumption of homoskedasticity is one of the important conditions in classical linear regression. Although violations of this assumption do not cause the estimated coefficient to be biased, it can reduce the efficiency of the estimation and result in errors in significance testing, both through the t-test and the F-test (Gujarati, 2012). In this study, the test was carried out with two approaches, namely visual through scatterplot and statistics using the Glejser test. This approach aims to obtain a more thorough validation of the stability of residual variance across the regression models used. Initial testing was carried out through a scatterplot between residual (ZRESID) and predictive value (ZPRED) for each model. If the dots in the scatterplot are randomly spread above and below the horizontal line (the zero line), without forming a specific pattern, then it can be concluded that there is no symptom of heteroscedasticity. Luthfi Khairawan Putra, Bobby Wiryawan 963 In the first regression model between Partnership Schemes to Cost Efficiency, the scatterplot point spread (Figure 4.8) appears random and does not form a specific pattern, indicating that the residual variance is homogeneous. Figure 1. Results of the Heteroscedasticity Test of the Partnership Scheme Relationship Model to Cost Efficiency Source: SPSS Processed Output (2025) For the second model that tested the relationship between the Partnership Scheme and Driver Performance, the scatterplot results (Figure 2) also showed a randomly spread distribution without a systematic pattern, so it can be concluded that the homogeneity assumption is met. Figure 2. Results of the Heteroscedasticity Test of the Partnership Scheme Relationship Model to Driver Performance Source : SPSS Processed Output (2025) To reinforce the results of visual observations, statistical testing was performed using the Glejser test, which regresses the residual absolute value to each independent variable. The decision-making criteria in this test are: a) If the significance value > 0.05 → there is no heteroscedasticity. b) If the significance value is < 0.05 → there is an indication of heteroscedasticity. The results of the Glejser test on the main model showed a significance value of 0.975 for the Partnership Scheme variable (X) and 0.067 for the Cost Efficiency variable (Y1). Both values American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 964 were above the 0.05 threshold, which means that there was no statistical indication of heteroscedasticity. Table 5. Glejser Test Results Independent Variables Nilai Sig. (Glejser) Results Partnership Scheme (X) 0.975 No heteroscedasticity Cost Efficiency (Y1) 0.067 No heteroscedasticity Based on the results of the visual scatterplot and statistical testing through the Glejser test, it can be concluded that all regression models in this study do not contain symptoms of heteroscedasticity. Residual variance tends to be stable and does not show a systematic pattern of deviation from the predictor value. In the operational context of PT X, the fulfillment of this assumption strengthens the validity of the model in describing the dynamics of causal relationships between variables, so that the regression results obtained can be used as a basis for more accurate and credible strategic decision-making. Methodologically, these results strengthen the validity of the regression model used, as the fulfillment of homoskedasticity assumptions ensures that the estimated coefficients in the model have optimal efficiency. It can also be used for hypothesis testing at the next stage. Regression Analysis Effect of Partnership Scheme (X) on Cost Efficiency (Y1) a. Regression Test and t-Test Testing of the influence of the Partnership Scheme variable (X) on Cost Efficiency (Y1) was carried out through simple linear regression analysis. Based on the results of data processing using SPSS version 26, information was obtained as shown in Table 6 below: Table 6. Results of Partnership Scheme Calculation on Cost Efficiency Coefficientsa Type Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 4.882 2.552 1.913 .057 Partnership Scheme .656 .049 .689 13.360 .000 a. Dependent Variable: Cost Efficiency Source: SPSS Output Data processed (2025) Based on these results, the following simple linear regression equation is obtained: y=4.882+0.656x The interpretation of this equation is that each one unit increase in the perception score against the partnership scheme will increase the cost efficiency score by 0.656 points, assuming the other variables are fixed. This coefficient value also indicates the direction of the positive relationship between the two variables. The partial significance test through the t-test yielded a t-count of 13,360, while the t-table at a significance level of 5% (α = 0.05) and a degree of freedom of 198 was 1,972. Since the t- calculation > the t-table (13,360 > 1,972) and the significance value (p-value) = 0.000 < 0.05, it Luthfi Khairawan Putra, Bobby Wiryawan 965 can be concluded that the effect of the Partnership Scheme on Cost Efficiency is statistically significant. Thus, the first hypothesis (H1) is accepted. Substantively, these findings suggest that improvements in aspects of the Partnership Scheme such as work flexibility, clarity of compensation systems, and the arrangement of operational responsibilities contribute directly to increased efficiency in the use of operational resources. When drivers experience a flexible and fair work structure, companies benefit from reduced fixed costs, time efficiency, and workload optimization. These results are consistent with the principles of Transaction Cost Economics (Williamson, 1981) which states that the structure of employment contracts designed to minimize uncertainty and clarify coordination mechanisms can significantly reduce transaction costs, including the costs of supervision, re-coordination, and contractual negotiations. In the context of PT X, the partnership scheme acts as an instrument of transformation from a fixed cost model to a variable cost model. This allows companies to be more responsive to fluctuations in demand, without being burdened by the rigidity of fixed cost structures that are generally inherent in PKWT's work system. The efficiency achieved is not only in terms of finance, but also in terms of workforce flexibility and the reduction of potential idle capacity in the dynamic vehicle rental sector. b. Correlation Coefficient and Determination Test Furthermore, to explore the strength of the relationship between the variables of the Partnership Scheme (X) and Cost Efficiency (Y1), the correlation coefficient and determination coefficient were analyzed. This test aims to measure how closely the two variables are linked, as well as how much the Partnership Scheme contributes in explaining the changes that occur in Cost Efficiency. The results of the data processing are shown in the following Table 7: Table 7. Calculation of the Correlation Coefficient of Partnership Schemes to Cost Efficiency Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate 1 .689a .474 .471 8.574 a. Predictors: (Constant), Partnership Scheme b. Dependent Variable: Cost Efficiency Source: SPSS output, data processed (2025) The value of the correlation coefficient (R) of 0.689 indicates a strong and positive relationship between the Partnership Scheme and Cost Efficiency. According to Guilford's (1978) classification, correlation values in the range of 0.60–0.79 belong to the strong category. This positive correlation means that an increase in perception scores towards partnership schemes is associated with increased cost efficiencies achieved by companies. These findings reinforce the argument that the implementation of a good partnership scheme including work flexibility, compensation transparency, and clarity of operational responsibilities plays a role in creating significant cost efficiencies. This positive correlation also American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 966 reflects the synergistic linkage between non-conventional work structures and the effectiveness of resource management. Meanwhile, a determination coefficient (R²) value of 0.474 indicates that approximately 47.4% of the variation in Cost Efficiency can be explained by the Partnership Scheme variable. The rest, at 52.6%, is likely to be influenced by other factors outside this model, such as fuel tariff policies, incentive systems, the use of operational technology, and the dynamics of service demand. In the context of social research and organizational behavior, an R² value of 0.474 can be considered substantial, given the complexity of the factors that affect cost efficiency in the rental sector. This shows that the Partnership Scheme has a strategic role in efforts to transform the company's cost efficiency. Thus, these correlation and determination results not only confirm the existence of a strong statistical relationship, but also provide an empirical basis that the transformation of workforce management through a partnership approach can be an important foundation in PT X's overall cost efficiency strategy. The Effect of Partnership Schemes (X) on Driver Performance (Y2) a. Regression Test and t-Test Testing on the influence of the Partnership Scheme variable (X) on Driver Performance (Y2) was carried out using simple linear regression analysis. The purpose of this analysis is to test the extent to which the implementation of the partnership scheme contributes to improving driver performance in the operational environment of PT X. The results of the data processing are presented in the following Table 8: Table 8. Results of Partnership Scheme Calculation on Driver Performance Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Itself. B Std. Error Beta 1 (Constant) 7.098 1.651 4.300 .000 Partnership Scheme .327 .032 .590 10.295 .000 a. Dependent Variable: Driver Performance Source: SPSS output, data processed (2025) Based on the results of a simple linear regression analysis for the relationship model between the Partnership Scheme (X) and Driver Performance (Y2), the equation was obtained: y=7.098+0.327x The above equation means that every one unit increase in perception of the quality of the implementation of the Partnership Scheme will increase the Driver Performance score by 0.346 points on average. A positive regression coefficient value indicates the direction of the relationship between the two variables. To test the significance of these influences, a t-test was performed. The results show a t- count value of 7.662, while the t-table at the degree of freedom (df = 198) and the significance level of α = 0.05 is about 1.972. Since the t-calculation > the t-table (7.662 > 1.972) and the Luthfi Khairawan Putra, Bobby Wiryawan 967 significance value (Sig.) = 0.000 < 0.05, it can be concluded that the Partnership Scheme has a significant effect on Driver Performance, so the second hypothesis (H2) is accepted. These findings reflect that partnership schemes not only contribute to the cost efficiency aspect, but also have a real influence on the quality of driver performance. In the context of PT X, drivers' perceptions of role clarity, freedom in managing working hours, and fairness in the incentive system affect motivation, discipline, and punctuality in carrying out daily operational tasks. This is in line with the Self-Determination Theory (Deci & Ryan, 2000), which emphasizes the importance of autonomy, competence, and connectedness as key factors in driving intrinsic motivation. Partnership schemes designed with this aspect in mind have been proven to increase individual involvement and responsibility for the results of their work. Thus, the company not only succeeds in creating structural efficiencies, but also establishes a more productive and results- oriented work culture. Correlation Coefficient and Determination Test To understand the extent of the strength of the relationship between the Partnership Scheme (X) and Driver Performance (Y2), a correlation and determination analysis was conducted. The purpose of this analysis was to measure the degree of association between the two variables as well as the relative contribution of the Partnership Scheme in explaining the variation in Driver Performance. The results of data processing are presented in Table 9 below: Table 9. Calculation of the Correlation Coefficient of the Partnership Scheme to Driver Performance Model Summaryb Type R R Square Adjusted R Square Std. Error of the Estimate 1 .590a .349 .345 5.547 a. Predictors: (Constant), Partnership Scheme Source: SPSS output, Data processed (2025) The value of the correlation coefficient (R) of 0.590 indicates a strong and positive relationship between the Partnership Scheme and Driver Performance. Based on Guilford's (1978) classification, correlation values in the range of 0.40–0.59 are included in the moderate to quite strong category. The positive direction of the relationship indicates that an increase in the perception score of the implementation of the Partnership Scheme tends to be accompanied by an increase in the Driver Performance score. This correlation implies that components in the partnership scheme such as clarity of rights and obligations, work flexibility, and compensation system are closely related to the quality of individual performance, including in the aspects of responsibility, discipline, and the fulfillment of work targets. Meanwhile, a determination coefficient value (R²) of 0.349 shows that 34.9% variation in the Driver Performance variable can be explained by the Partnership Scheme. That is, the contribution of the model is quite substantial in the context of social research, where human behavior is influenced by many external variables. The remaining 65.1% variation was influenced American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 968 by other factors not covered by this model, such as training quality, organizational culture, managerial support, or field working conditions. In the context of PT X, this figure reflects that partnership schemes have become one of the important components in directly influencing driver performance. Nonetheless, the success of performance improvement is also highly dependent on other management strategies, including ongoing coaching and operational feedback mechanisms. Thus, the results of this correlation and determination provide statistical justification that the implementation of partnership schemes plays a significant role in encouraging driver performance improvements, as well as opening up opportunities to integrate partnership strategies with other aspects of human resource development. Thus, it can be concluded that this regression model not only has adequate statistical validity, but also strong practical and theoretical relevance in supporting the formulation of partnership-based workforce management strategies in the vehicle rental industry. This chapter presents an in-depth discussion of the empirical findings outlined in Chapter 4.5, with a focus on conceptual interpretation, theoretical significance extraction, and mapping practical implications in managerial and strategic contexts. The main purpose of this discussion is to integrate the results of statistical analysis with the theoretical foundations that have been previously described, compare them with the findings in previous research, and reflect on the meaning of the findings for decision-making in the vehicle rental industry. Each subchapter in this section will systematically discuss the influence between the main variables in the research model, namely Partnership Scheme (X), Cost Efficiency (Y1), and Driver Performance (Y2). The discussion will be carried out in an interpretive manner, reflecting how the quantitative results can be explained through theoretical perspectives such as Transaction Cost Economics (TCE), Self-Determination Theory (SDT), Workforce Flexibility, and Resource-Based View (RBV), while considering the empirical characteristics of the field at PT X as a case study. Through this approach, it is hoped that readers will not only understand what is found in statistical analysis, but also why the results appear, what they mean for the development of management theory, and how these findings can be applied strategically to improve effectiveness and efficiency in workforce management in the transportation and logistics industry. The Effect of Partnership Schemes on Cost Efficiency The regression analysis reveals that the Partnership Scheme (X) significantly enhances Cost Efficiency (Y1) (coefficient=0.656, p<0.001, correlation=0.689), demonstrating that positive partner perceptions directly improve cost optimization by transforming fixed costs into variable expenses. Aligning with Williamson's (1981) Transaction Cost Economics, this shift from PKWT to partnership models reduces rigid costs (fixed salaries, allowances) through productivity-based payments, minimizing idle costs during demand fluctuations while achieving dynamic efficiency. The findings also support Atkinson's (1984) Workforce Flexibility Model, as the scheme enables adaptive labor capacity adjustments to seasonal demand and market trends without long-term cost commitments. Operationally, performance-based incentives reduce supervision needs and administrative costs while maintaining productivity, though successful implementation requires Luthfi Khairawan Putra, Bobby Wiryawan 969 transparent compensation, effective work management systems, and digital integration for contract administration. These results position partnership schemes not merely as cost-saving tools but as strategic platforms for building adaptive, output-oriented work systems in the competitive vehicle rental industry, provided they incorporate fair governance principles, technology support, and consistent monitoring to ensure sustainable business competitiveness. The Effect of Partnership Schemes on Driver Performance The analysis confirms that the Partnership Scheme (X) significantly improves Driver Performance (Y2) (regression coefficient=0.327, p<0.001), demonstrating that well-implemented partnerships enhance work effectiveness, punctuality, and service compliance. These findings align with Self-Determination Theory (Deci & Ryan, 1985), as drivers gain autonomy in work scheduling, competence through transparent incentives, and connectedness via operational support while maintaining independence. The scheme also reflects Workforce Flexibility Theory's functional flexibility, enabling adaptive decision-making and problem-solving without hierarchical constraints. Practically, PT X's partnership model fosters mutual trust and outcome- based relationships, shifting motivation from external compliance to intrinsic performance-driven rewards, with drivers particularly valuing flexible hours (1), transparent trip-based payments (2), and accessible communication channels (3). However, concerns about income variability suggest the need for balanced flexibility-stability measures, highlighting opportunities for future research on job satisfaction mediators or experience moderators. These results emphasize that successful partnership systems must combine contractual flexibility with robust support mechanisms - including mentoring, training, and recognition frameworks - to sustain both operational efficiency and human capital development, transforming partnerships from mere cost-saving tools into platforms for professional growth and service excellence in the transportation sector. Theoretical Synthesis and Strategic Implications This study conclusively demonstrates that partnership schemes significantly enhance both cost efficiency and driver performance, validating Transaction Cost Economics (Williamson, 1981) through reduced hierarchical controls and flexible work structures, while substantiating Workforce Flexibility Theory (Atkinson, 1984) via adaptable labor capacity management. The findings equally support Self-Determination Theory (Deci & Ryan, 2000), showing how autonomy, clear incentives, and outcome-based systems boost intrinsic motivation. For PT X, these results necessitate moving beyond contractual flexibility to develop a comprehensive managerial ecosystem encompassing digital infrastructure, productivity-focused training, transparent incentive mechanisms, and enhanced communication channels. The research further reveals opportunities for data-driven policy innovations, suggesting targeted interventions like productivity-based partner segmentation to optimize coaching programs, thereby transforming partnership systems into strategic tools for operational excellence that align financial efficiency with human capital development in the evolving transportation sector. American Journal of Economic and Management Business Vol. 4 No. 7 July 2025 970 From the academic side, this research contributes to the development of studies on workforce flexibility and gig economy in the context of the Indonesian transportation industry, a theme that has been minimally explored empirically. Follow-up research can deepen the psychological and social dimensions of partnership-based work relationships, including exploring the mediating role of job satisfaction, or moderation by contextual factors such as work location, order density, and technological support. In closing, this synthesis emphasizes that the transformation of work schemes is not just an administrative issue, but part of a business strategy that directly touches the core of organizational efficiency and productivity. The successful implementation of the partnership at PT X is proof that with the right design, alternative work systems can generate sustainable added value for the company, driver-partners, and the service ecosystem as a whole. CONCLUSION This study aims to examine the effect of the implementation of partnership schemes on cost efficiency and driver performance as part of the workforce management transformation strategy at PT X Jakarta Branch. Based on the data collected from 200 driver-partners and the regression analysis that has been carried out, several key findings can be concluded as follows: Partnership schemes contribute positively to operational cost efficiency. The switch from a PKWT system to a partnership relationship allows companies to manage labor costs more flexibly. The fixed cost component, which was previously a burden, is now converted to a variable cost that is more adaptive to fluctuations in demand. These findings support the Transaction Cost Economics (TCE) framework, which emphasizes the importance of contractual efficiency in response to market dynamics and uncertainty. The partnership scheme also has a positive impact on improving driver performance. A more flexible work system, performance-based incentives, and clarity of roles have been shown to increase drivers' sense of responsibility and work motivation. These results are consistent with Self-Determination Theory, which states that autonomy, competence, and connectedness are the main drivers of productive work behavior. 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Journal of Transport Geography, 82, 102601. https://doi.org/10.1016/j.jtrangeo.2019.102601 Copyright holders: - Luthfi Khairawan Putra, Bobby Wiryawan (2025) First publication right: AJEMB – American Journal of Economic and Management Business https://doi.org/10.1080/01441647.2018.1497728 https://doi.org/10.1016/j.jtrangeo.2019.102601