https://orcid.org/0009-0007-2369-899X
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Abstract
The main purpose of this research is to empirically analyze the determinants of organizational performance using National Basketball Association (NBA) team data. Based on the resource-based theory of the firm, prior studies posit that operational efficiency encompasses the ability of professional sports teams to translate their resources into creating organizational performance. The contention is that NBA teams enhance organizational performance in the market when possessing valuable, rare, inimitable, and non-substitutable resources and capabilities. In this sense, the operational efficiencies of NBA teams align with the concept of core competence, enabling teams to achieve competitive advantages through superior performance. The exploration of the level of operating efficiency in NBA teams and its role in organizational performance is beyond essential. This study conceptualizes operating efficiency as the degree of competence exhibited by professional sports teams, drawing on comprehensive game-related statistics and financial performance data derived from human assets and team budgets. To bridge theory and empirical investigation, data spanning six seasons (2015–2016 to 2020–2021) for all 30 NBA teams were collected. The results reveal that 29 out of 180 decision-making units exhibit outstanding organizational efficiency, significantly contributing to franchise value.
Citation: Kim P, Lee SH, Moon J (2024) Evaluating the operational efficiency of NBA teams on franchise value: An assessment of data envelopment analysis. PLoS ONE 19(3): e0297797. https://doi.org/10.1371/journal.pone.0297797
Editor: Haroldo V. Ribeiro, Universidade Estadual de Maringa, BRAZIL
Received: October 22, 2023; Accepted: January 12, 2024; Published: March 8, 2024
Copyright: © 2024 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All data files are available from the NBA.com database
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Within the context of professional sports, the term "operational efficiency" holds significance, representing the output generated based on input [1]. However, in the sports domain, this term is often used interchangeably with "effectiveness." The rationale for this interchangeability lies not only in the common attributes of the terms but also in the unique aspects of professional sports franchises. Despite competing in similar environments, as exemplified by National Basketball Association (NBA) teams in the league, the pursuit of maximizing performance within the constraints of a salary cap necessitates a direct relationship between team efficiency and effectiveness [2–5].
The representation of sports franchises and type of business units are obliged to be efficient seeking not only the goal of profit maximization but also to increase its franchise value [6,7]. One of the key strategies and goals of contemporary professional sports teams is to secure a championship by accumulating regular season and postseason wins and maximize the franchise value This entails strategic investments within budget constraints to acquire quality players and optimize management efficiency. Furthermore, sports teams need to achieve financial return to have core resources to compete with other teams in the league. The presence of excellent players, their performance, and the available capital for recruiting and motivating these players have a positive impact on team wins to a certain extent [8,9].
Despite perennial questions regarding which team is the most efficient in the league [10–12], our focus is on the fundamentals of team-aggregated player performance leading to the level of organizational efficiency. The presence of talented players or financial resources does not always translate into or substitute for operational efficiency of professional sports teams that should be leveraged for franchise value [13,14]. Prior literatures have shed light on estimating the operational efficiency of sports organizations by comparing the performance of sports teams, such as athletic performance, ranking, and winning percentage [15–18]. Other studies have endeavored to assess efficiency by considering financial metrics like sales, revenue, and budget investments [19–21]. However, the context in which a sports organization is efficient should be defined in a comprehensive way to reflect its unique features, which combine both sport-specific and financial aspects of the franchise. This is because the value of a sports franchise should include dual aspects, as they are both sport-specific entities and business units.
The notion of resource-based theory (RBT) provides a clear logic on organizations being capable of seeking sustainable competitive advantage to perform better based on their level of core competencies [22,23]. Sports franchises, accordingly, must possess core competencies characterized as valuable, rare, inimitable, and difficult to substitute. In line with this argument, [24] defined the operating efficiency of a professional sports team as the ability to transfer its resources into winning. Such organizational resources include the budget spent to maintain human capitals and the aggregated capabilities of players into the professional sports franchise. It is critical for a sports franchise to not only possess superior level of human assets that should perform well for the winning of the game, but also to retain capabilities to transfer such resources into operational efficiencies that should maximize franchise value. The value of a sports franchise depends not only on the team’s rank in the league, but also on its financial status [12]. This means that sports teams’ performance should be evaluated based on both on-field performance and financial performance. Thus, the efficiency of a sports franchise can be comprehensively estimated by considering the budget invested, human assets, and both game and financial performance. Despite this, studies considering on-field and financial performance as output variables, with budgets invested and human assets as input variables, are scarce in the sports domain.
Accordingly, this research aims to estimate the operational efficiency of professional sports organizations using the budget invested in team-aggregated player capabilities as input factors, with game performance and financial gain as output factors. Team operating efficiency is defined as the ability of a professional sports team to effectively utilize its inherent organizational resources to achieve organizational performance. It stands as a key determinant of team value, as teams with high operating efficiency can construct more attractive teams in the market, even under identical conditions. Given that most NBA teams compete under relatively similar circumstances, operating efficiency may play a crucial role in determining organizational performance, even when resources are comparable [25,26]. Consequently, we argue that team operating efficiency is an inherent and unique determinant of organizational performance, serving as an essential organizational resource that enables teams to gain a comparative competitive advantage in the NBA.
In this regard, the objective of this research is to provide a theoretical framework for the comprehensive evaluation of professional sports franchise operational efficiency using NBA team data. This study employs data envelopment analysis (DEA), a widely utilized method in the field of professional sports to compare the efficiency of players or teams relative to their inputs [27–29]. The data used in this study was collected from 6 seasons (2015~2016 to 2020~2021) of NBA game records. Through the application of DEA, we aim to estimate which team is more efficient than others and further examine the impact of team operational efficiency on the increased Forbes franchise value. We believe this study can contribute to the domains of sports analytics by analyzing NBA team operating efficiency. The idea of considering the quality of human resources of a sports team alongside financial investment as input factors and both on-field and financial performance as output factors can provide insight to sports stakeholders on how to assess the resources sports teams possess and utilize them effectively.
Theoretical background
Resource-based theory and operating efficiency
This research theoretically applies and extends the resource-based theory to elucidate the impact of operational efficiency on the value of professional sports franchises. Originating in the field of strategic management, RBT identifies organizational characteristics that confer advantages in competitive environments [22,30,31]. Empirically supported over the years, RBT has become integral in sports management literature, explaining determinants of organizational performance for professional sports teams [9,32–37].
RBT posits that organizations with resources possessing intrinsic value, rarity, difficulty of imitation, and non-substitutable attributes can achieve sustainable performance advantages—collectively termed as core competencies. Such organizations can effectively execute strategies, attain objectives, and maintain a competitive advantage in the market [22,30,31]. When applied to professional sports teams, RBT suggests that possessing core competencies not found in other organizations leads to differentiated performance compared to competing teams in the same league [9,35,38]. Building on RBT, two types of core competencies for sports franchises are identified [38–40].
The first resource is human assets, specifically the players, who are crucial as the core products of sports organizations are game performances. Yet, assessing individual player proficiency at the organization level requires considering the aggregated game performance of a team. Another vital resource is the budgets invested in players, i.e., team salaries. Salaries play a fundamental role in attracting, retaining, and motivating valuable human assets. In this context, the total salaries of a team are considered as organizational resources.
RBT posits that organizational resources encompass both tangible and intangible aspects [38,40]. Operational efficiency is viewed as an intangible core competence of sports franchises, providing the ability to gain competitive advantages through superior performance. Efficiency is typically measured as the ratio of inputs to outputs. An efficiency study in the sports domain defined operating efficiency as the ability to transfer sports team resources into winning [24]. Extending this definition, we define operating efficiency as the ability to transfer organizational core competencies into organizational performance.
The choice of input-output variables in efficiency equations depends on the study’s purpose. However, previous sports domain studies often overlooked human assets, a critical core competency of sports franchises, by only using financial investment as input variables [27,41–45]. Recognizing human assets and financial resources as critical tangible resources in sports management, we argue that both human capital and total team salaries should be included as input variables when estimating operating efficiency.
According to a recent RBT review paper in the sports domain [38], human assets and financial resources are considered critical tangible resources in sports management. [46] also argue that capital and human assets are the main categories of input variables when estimating the efficiency of organizations. As argued earlier, human capital and budgets invested in sports teams are critical resources, and both need to be considered as input variables when estimating operating efficiency. Therefore, we argue that the quality of human capital and total team salaries should be included as input variables when estimating the operating efficiency of sports franchises.
Output variables align with the goals of sports franchises, which vary based on the team, sport, and country. Despite these diverse goals, most efficiency studies in the sports domain do not consider both financial and performance aspects [8,28,29,41,47,48]. This research aims to contribute to the efficiency literature in the sports domain by estimating efficiency with more comprehensive input and output variables reflective of sports franchise characteristics. Specifically, we adopt game performance and financial performance as output variables, advancing efficiency studies in the sports domain.
The role of operating efficiency on franchise value
Based on RBT, we contend that the resources of a sports franchise include the amount of financial investment in the team, the quality of human assets, and operating efficiency. The level of capital invested in a sports team and the human assets of the team are clear core competencies of sports teams. Higher pay levels are one of the strongest determinants of attracting valuable human assets, and preeminent players can contribute to the success of sports teams [49–52]. Furthermore, star players’ better game performance can lead to better win probability, attract more fans and media, and sponsors, which can lead to better financial returns [8,9,53–55].
Whether operating efficiency is another core competency of sports franchises, in addition to total salaries and human assets, is a question that remains to be answered. Despite operating efficiency being estimated through variables representing capital, human assets, game, and financial performance, we posit that it is conceptually and empirically distinct from other core competencies. This distinction arises from our approach, where we move beyond a simple calculation of ratios and consider the team’s ability to transfer resources into performance, aligning with previous operating efficiency studies [24].
Not only conceptually, the source of operating efficiency is also distinct from other core competencies. The sources of capital and human assets are relatively clear, as they are tangible resources and generally determined by the organization’s decision-makers [38,56–58]. However, the source of operating efficiency is more ambiguous. It can come from the system of organization, mentality of the members, organizational culture that is developed over time or transferred by coaching staffs, or even outside of the organizations. In this sense, operating efficiency is an organization’s unique resource that is valuable, rare, inimitable, and non-substitutable and even the members of the teams do not know where it is from [24,33,59–61]. Therefore, there should be no misunderstanding that operating efficiency and other core competencies are overlapping concepts simply because capital and human assets are used to estimate operating efficiency. This is because operating efficiency is a more complex concept that goes beyond the simple calculation of ratios. It measures the organization’s ability to use its resources effectively and efficiently to achieve its goals.
Aligned with the core premise of RBT, organizational resources contribute to better organizational performance. Operating efficiency, therefore, plays a critical role in the key performance of sports franchises, as evidenced by the use of team efficiency in explaining the performance of professional sports teams in various studies [24,27,28,62–64]. However, to establish whether operating efficiency constitutes a distinguishable and critical core competence for sports franchises, a statistical test is imperative. If operating efficiency is a core competence and can be distinguished from other core competencies, its effects on organizational performance should remain statistically significant even after controlling for other core competencies.
Determining the most comprehensive measure of organizational performance for sports franchises is essential for a rigorous assessment. As the goals of sports franchises extend beyond game performance or financial return, a holistic measure reflecting both dimensions is necessary. We propose that franchise value serves as an excellent indicator of a sports franchise’s comprehensive goals, encompassing both game performance and financial return [13,14]. Therefore, we define franchise value as the performance of a sports organization.
In light of this, it is prudent to explore the relationship between operating efficiency and franchise value. However, it is crucial to acknowledge the temporal dynamics inherent in the evaluation. The efficiency of sports franchises in this study will be assessed over a specific period, with the unit of analysis being a team in a given year. In contrast, franchise value accumulates over time, with a specific year’s franchise value reflecting the culmination of organizational performance over the years. Consequently, while the operating efficiency of one year may not directly impact the total franchise value, it may exert influence on the annual change in franchise value.
Building on this rationale, we hypothesize the following.
Hypothesis: There is a positive relationship between the operating efficiency of a sports franchise and the incremental value of the franchise, controlling for the level of capital invested and the quality of human assets
Methodology
In this study, NBA teams serve as sample of sports organizations due to their prominence in the sports industry, offering substantial on- and off-field data. NBA teams operate under various league regulations, including the draft and salary cap [49,65,66]. The input and output factors for NBA teams, used to estimate operating efficiency, exhibit minimal variation, making Constant Returns to Scale (CRS) an appropriate measure for assessing teams’ operating efficiency.
The evaluation of organizations’ operating efficiency in sports commonly employs data envelopment analysis (DEA), an excellent method for estimating as it does not require statistical assumptions. It compares each decision-making unit (DMU)’s efficiency by comparing the input-to-output ratio among the DMUs. If a DMU has the highest efficiency among the DMUs, the DMU’s efficiency is 1. If a DMU’s efficiency is extremely low, the efficiency is 0. In this case, a DMU refers to each sports organization. Two types of DEA are prominent: Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS). Given the relatively consistent resources invested in and outputs of sports teams, CRS is typically utilized to assess their efficiency [27,65,66].
Efficiency, as determined by DEA, is influenced by factors such as aggregated player skill levels, total pay-to-game ratio, and financial performance indicators. It is evident that operating efficiency, as estimated through DEA, can impact both game performance and financial outcomes. However, sports organizations may have diverse objectives. Some teams prioritize winning championships, while others, often sponsored by business firms, focus on leveraging sports organizations as marketing tools, placing less emphasis on financial returns. Conversely, certain organizations prioritize financial gains, seeking to boost ticket sales and advertising revenue. Most sports organizations likely fall somewhere between these extremes [50,67,68].
Data for this study were sourced from various websites that provide information freely accessible to the public. Specifically, game-related data for 30 NBA teams (n = 180) over six seasons (2015~2016 to the 2020~2021 season) were collected from the NBA official website and Basketball-Reference.com. Financial data, including total revenue, ticket revenue, and operating income, were gathered from runrepeat.com, and total compensation was collected from hoopshype.com. Franchise values were obtained from forbes.com. We employed R software to conduct DEA and statistical computing such as regression analysis. The study adopts CRS efficiency as the measure of operating efficiency for NBA teams. Table 1 outlines the variables used in DEA, while Table 2 provides a more detailed overview of these variables.
The study also takes advantage of tracking stats instead of traditional stats for a comprehensive overview of the collective quality of NBA players Tracking statistics go beyond individual player capabilities, representing the combined skills that coaches aim to showcase during games. These statistics encompass drive and pass percentages, secondary assists, potential assists, passes made, points from catch-and-shoot plays, points from screen assists, deflections, loose balls recovered, and contested shots. The financial investment in NBA teams is operationalized as total compensation, while game-related output variables for operating efficiency include winning percentage, final appearances, and winning championships. Financial-related output variables comprise total revenue, ticket revenue, and operating income. Subsequent to the Constant Returns to Scale (CRS) estimation, a regression analysis was conducted to elucidate the impact of operating efficiency on organizational value.
The Forbes organizational brand value is operationalized as the measure of NBA teams’ organizational values in this study. Specifically, we utilize the incremental value of organizations’ brands as the dependent variable, recognizing that a single-year resource allocation does not singularly determine total organizational value but contributes to incremental value. In this equation, the input variables employed in DEA serve as control variables.
Following CRS estimation, a regression analysis will be employed to test the hypotheses. If CRS demonstrates a significant effect in increasing the marginal value of a sports franchise, while controlling for other variables, we can infer that operating efficiency constitutes a core competency for sports franchises, distinguishable from other competencies.
Results
Descriptive statistics and intercorrelations among the focal variables are described in Table 3. Focal variables generally show the correlations with what we expected. Specifically, incremental value is strongly related to operational efficiency (r = .39, p < .001), total revenue (r = .68, p < .001), ticket revenue (r = .56, p < .001), final appearance (r = .26, p < .001), championship won (r = .28, p < .001), and operating income (r = .56, p < .001). Operational efficiency also has positive relationships with winning percentage (r = .55, p < .001), total revenue (r = .51, p < .001), ticket revenue (r = .60, p < .001), final appearance (r = .38, p < .001), championship won (r = .27, p < .001), and operating incomes (r = .44, p < .001).
Fig 1 shows the positions of the teams analyzed in this study based on winning percentage, total revenue, and operating efficiency. The size of the circles indicates the level of operating efficiency, with larger circles representing higher operating efficiency. The teams with perfect operating efficiency tend to have better winning percentages and total revenues, but this is not always the case. For example, the Toronto Raptors in 2016 had a relatively good game performance but their financial return was not impressive. The Los Angeles Lakers in 2016 were the opposite. Their total revenue was relatively good among the sample, but their winning percentage was almost disastrous. This implies that operating efficiency is fundamentally related to game performance and financial return, but it is a different concept.
Among the 180 DMUs, 29 DMUs’ CRS were 1. This means 29 out of 180 NBA teams had perfect operational efficiency compared to the samples. The list of the NBA teams is descripted on Table 4.
To explore the further meaning of operating efficiency, we conducted a regression analysis to test our hypothesis.
Prior to conducting the regression analysis, Variable Inflation Factor (VIF) tests were performed, leading to the exclusion of three variables—contested shots, loose balls recovered, and deflections—due to their elevated VIF scores (33.37, 19.19, and 11.859, respectively). The remaining variables exhibited acceptable VIF levels ranging from 1.22 to 4.61. The dependent variable in the regression analysis is the annual increase in team value, as determined by Forbes’ annual franchise valuations. The results of the regression analysis are presented in Table 5. In Model 1, various control variables, such as human assets, the budget of the year, and the population increase of the year, were included. This was undertaken because the dependent variable represents the annual increase in the team’s value, and changes in city conditions, such as population change, may influence the franchise value change in the city. Model 2 elucidates the role of operating efficiency in predicting incremental organizational value (B = 462.21, p < .001), even after controlling for human assets and budget. Moreover, the model fit was significantly improved (delta R-square = 0.15, p < .001; delta BIC = 34.29, p < .001). The results underscore that NBA teams’ operating efficiency embodies unique features not mirrored by other organizational resources, offering an incremental explanation for changes in organizational value, emphasizing the distinctive contribution of operating efficiency in influencing the annual increase in team value.
Fig 2 visually represents the intricate relationships among revenue, operating efficiency, and team value increment. Red collars signify the highest value increments, while blue collars denote the lowest value increments. Notably, a discernible pattern emerges wherein a larger area of red collars corresponds to higher CRS efficiency, and conversely, a larger area of blue collars aligns with lower CRS efficiency. This visually compelling evidence solidifies the clear relationship between operating efficiency and team value increment.
Discussion and conclusion
This study provides an empirical exploration of the operating efficiency of professional sports teams, considering both game-related and financial factors. The Data Envelopment Analysis (DEA) results, based on data from 30 NBA teams over six seasons (n = 180), reveal that only 29 out of 180 teams (16%) attained perfect operating efficiency within the sample. Notably, this finding underscores the significant observation that, within the NBA’s postseason structure featuring 16 competing teams annually, only three teams can theoretically achieve perfect efficiency each season. This arithmetical constraint emphasizes the formidable challenge of attaining 100% efficiency when considering both game performance and financial outcomes. Additional detailed information on the operationally efficient teams in the NBA league can be found in Table 6.
Subsequently, the study delves into the analysis of the role of operating efficiency in influencing organizational value—a more comprehensive variable that encompasses both game and financial performance, aligning with the overarching goals of most sports organizations. The results underscore that the operating efficiency of NBA teams significantly impacts their value. This implies a critical strategic implication for sports organizations, suggesting that a focus on operating efficiency is paramount for achieving their fundamental goals.
This study holds several theoretical implications. First, it introduces a comprehensive approach by incorporating both game and financial aspects of sports organizations conducting data envelopment analysis. Conceptualizing professional sports organizations as not only athletic groups but also as business units with sports content, this study recognizes the critical importance of both game and financial performance as essential goals. Furthermore, the inclusion of players’ aggregated skill level as input variables, in addition to the budget invested, distinguishes this study from most DEA studies in the sports domain [20,69]. By conceptualizing players as human assets, the study contributes to advancing DEA studies in the sports domain, offering a more holistic estimation of operating efficiency.
Second, we adopted tracking stats instead of traditional measures of the NBA for estimating operating efficiency. While traditional measures persist in many studies, this research argues their inadequacy in capturing the collective qualities of human assets within teams. To the best of our knowledge, this is the first study that uses tracking stats to conduct DEA providing a more dynamic and nuanced perspective.
Third, we analyzed how operating efficiency works in sports organizations when various goals are considered. Achieving a better position with outstanding game and financial performance have common but different aspects. However, the value of organizations in sports can include both aspects. If efficiency can increase organizational value even after controlling for other significant factors, the organizations must pursue increasing operating efficiency regardless of their different goals. In this sense, the results of this study show why operating efficiency of sports organizations is important.
This study holds valuable practical implications for sports organizations, emphasizing the imperative to enhance operational efficiency. The argument posits that sports organizations, contingent upon their specific situations, may prioritize diverse goals, ranging from game-related performance to financial success. Notably, organizations sponsored by external businesses with a primary focus on game-related performance operate differently from those pursuing financial objectives. In the former case, the organization seeks to bolster its organizational value for sponsorship purposes. Conversely, organizations prioritizing financial performance aim to increase revenue through enhanced ticket sales, advertising, and improved organizational value through fan engagement [70]. The call for increased operational efficiency resonates across these varied goals. Even organizations with differing objectives ultimately share the common need to augment their value. Operational efficiency, derived from various sources such as coaching staff, organizational systems, and external factors, plays a crucial role. Noteworthy is the finding that sports organizations facing distinct situations can achieve high levels of operational efficiency through different means. Thus, general managers must discern the specific conditions of their organizations and emulate strategies conducive to enhancing operational efficiency.
The study significantly contributes to the sports research domain by estimating the operating efficiency of sports organizations, considering various factors, and elucidating the pivotal role of operating efficiency in influencing organizational value. However, several limitations warrant consideration. Firstly, given the inclusion of financial aspects in this study, operating efficiency may be susceptible to external factors such as economic cycles. The six-season sample period may lead to operating efficiency estimations influenced by these external factors. Future studies could address this limitation by employing alternative methodologies, such as DEA-Window, which accommodates different time frames [51]. Moreover, advancing this study could involve the consideration of more diverse factors beyond players’ collective game performance. In the current analysis, human assets were solely represented by players. However, the impact of coaching staff or front-office personnel on operating efficiency in sports games necessitates future studies to broaden the scope and incorporate other human assets within organizations [71,72]. Lastly, the study acknowledges the potential variation in the effects of operating efficiency on organizational value based on organizational goals. [73] contends that organizational strategy may moderate the relationship between organizational systems and organizational performance. Future research may explore the role of sports organizations’ goals as moderators, providing valuable insights into the nuanced dynamics of operating efficiency in sports organizations.
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