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Abstract

Professional sport has entered the digital economy as organisations adopt data-driven business model innovations. The purpose of this article is to highlight the potential ethical vulnerabilities sport organisations and their leaders face when adopting digital sport business models. Here, we treat data as a species of capital that can be converted into economic capital once it undergoes a computational transformation via a data-driven business model innovation. We argue for two advantages in this approach. First, it helps make transparent the mechanisms through which digital sport business models work. Second, it reveals how the extraction and application of big data exacerbates inequitable power relationships between sport organisations and supporters – the big data divide – that leads to ethical vulnerabilities for sport organisations and their consumers. We suggest that sport consumers might be particularly vulnerable to digital data risk as a consequence of their high levels of brand loyalty and involvement, which tend to encourage trust in the sport properties soliciting, analysing, and monetising their data. Platform broadcasting partnerships, e-ticketing in smart stadiums, and cryptocurrency-based fan tokens are used as examples of data-driven business model innovations based on the conversion of data to capital, demonstrating how sport organisations risk violating the trust of supporters when using digital strategies. The article concludes with directions for future research to deliver an ethically informed data-driven sports industry.

Keywords

big data internet of things digital ethics digitalisation cryptocurrency smart stadium Bourdieu

We live in an age of exponential technological change driven by ever-increasing computer processing power and machine learning accuracy. Professional sport organisations globally¹ are ‘digitalising’ by applying new technologies to traditional business models (Ritter and Pedersen, 2020), pivoting to commercial strategies that utilise new technological capabilities and fan data for product optimisation and profit (Giorgio and Westcott, 2018). This has led to both innovations in existing business models (e.g., ticket sales) and entirely new business opportunities (e.g., selling fan data) (Fruhwirth et al., 2020). For example, sport organisations readily collect demographic, behavioural and locational data points on fans for operational and sales purposes (e.g., Gravy Analytics, 2021). Likewise, sport organisations advertise through digital platforms including Facebook, TikTok, and Google, which are built on converting user behaviour into commercial insights to be analysed and on-sold (Zuboff, 2015). Some new opportunities have been augmented by radically increased digitisation capabilities that have vastly increased the ability to store behavioural information in a digit format. The result are immense – ‘big’ – data sets that enable a smorgasbord of new data-driven business model innovations (DDBMI) (Fruhwirth et al., 2020; Ritter and Pedersen, 2020). It is this transformation of data into a powerful currency of economic capital, as well as its implications for sport and its management, that motivates this article. We also suggest that sport consumers – fans – are particularly vulnerable to date exploitation.

The use of technologies capable of covertly harvesting and converting user attributes and behaviours into data have become pervasive in society and championed by the professional sports industry, packaged as beneficial to fans through new experiences, personalised advertisements, enhanced content, and innovative ways to display loyalty. Patently, new digital technologies offer previously unavailable insight into fan behaviour and used correctly can bolster the financial sustainability of organisations. Technology can help deliver an enhanced experience to dedicated fans who choose to share their data. In this sense, the sports industry is a prime example to showcase the capabilities of big data due to the diversity and volume of data points that can be extracted. Accordingly, sport management scholars have pointed out how such technologies might be commercially applied (Baker et al., 2022; Horbel et al., 2020; Naraine, 2019; Rascher et al., 2021; Stegmann et al., 2021). The sport industry’s potential as a leader in digitalisation is displayed by the partnerships formed with new digital organisations and industries, implicitly legitimating such commodities to respective fan bases. For instance, the iconic Los Angeles Staples Centre was renamed the Crypto.com Arena in 2022, signalling how the industry is embracing digital products. The capacity of sport organisations to transfer positive sentiment to products and organisations by adopting new technologies and partnering with data-driven businesses creates distinct ethical questions regarding DDBMI and the influence sport properties have over fans. In this article we address two related questions. First, in what ways are data being used as a new form of capital through ‘digital sport business models’, and second, in consequence, to what extent are sport organisations legitimating ethically controversial uses of big data?

Concerns about new technological capabilities and the ownership, collection, regulation, and trading of big data are neither new nor unique to the sport industry (see Boyd and Crawford, 2012; Richards and King, 2014; Zwitter, 2014). Systemic ethical implications that accompany data collection and utilisation in digital business models are well documented and include privacy, security, transparency, agency, autonomy, consent, and equality (see Richterich, 2018). Further, diversified technological sources capable of data collection, including but not limited to the ‘Internet-of-Things, robotics, biometrics, persuasive technology, virtual and augmented reality, and digital platforms’ (Royakkers et al., 2018, p. 127), create a constellation of potential ethical issues for sport organisations and managers to navigate when implementing innovative digital business models premised on big data computations. Critical analyses addressing the relationship between digitalisation, big data, and sport, although scarce (e.g., Hutchins, 2016; Millington and Millington, 2015; Spaaij and Thiel, 2017), have demonstrated that the datafication of the sports industry can gain from sociological examination in order to better understand the cultural impact.

One productive sociological application pertinent to our article involves conceptualising big data as a distinct, nascent form of capital (Bourdieu, 1986) that can be converted to economic capital under certain conditions (Sadowski, 2019). Big data becomes another species of capital interchangeable with economic capital (i.e., money), social capital (i.e., interpersonal networks), cultural capital (i.e., personal, objectified, and institutionalised indicators of class), and symbolic capital (i.e., reputational resources that are valued in specific settings) that structures social dynamics and power hierarchies (Bourdieu, 1986). With the concept of capital in mind, sport organisations can be viewed as collectors and utilisers of data generated by supporters, extending the degree of control sport managers have over already highly committed fans. Control is created by the influence data utilisers are given over the ‘individuality, free will, and power’ (Zwitter, 2014, p. 5) of those who provide data knowingly, or unknowingly. By extension, data-controlling organisations hold power over data-providing users because they can transform consumers’ behaviour into economic value through the application of digital business models. The power asymmetry emerges from the digital divide as the control and utilisation of data are limited, and where certain parties exercise a privileged opportunity to transform that data into economic capital (Zuboff, 2019). The digital divide extends the influence sport organisations have over supporters raising ethical questions about the degree of power and control afforded to managers.

Existing deep trust in a sport organisation might encourage fans to abandon the same caution applied to other contexts and products, and even abrogate their responsibility for due diligence. As a result, the ethical questions concerning power and influence over supporters raised by digitalisation and the commercial use of big data could pose a significant problem for sport organisations that enjoy a higher level of trust from fans but fail to reciprocate with higher levels of data vigilance by endorsing controversial, untested, or risky products or partners. Sport organisations therefore serve as a source of symbolic capital (Bourdieu, 1986) for the data-driven organisations and products they co-opt in DDBMI, a relationship often exemplified by the brand image exchange underpinning commercial sponsorships. Sport organisations and managers might face deeper scrutiny and perhaps should assume higher levels of social responsibility concerning their data ethics as a consequence of the high levels of engagement, identification, and trust that sport fans hold in their favoured properties (Smith et al., 2017). The potent combination of diverse commercial technologies, positive image transfer, and fan loyalty means that sport organisations are particularly exposed to the negative repercussions of data-related incidents.

Motivating this article is a paucity of discussion concerning business model digitalisation, ethics, and sport fans; a surprising gap considering the technological escalation in sport business (Spaaij and Thiel, 2017; Watanabe et al., 2021). Given the severe reputational damage suffered by other industries found failing to protect data or using it improperly (Makridis, 2021), this article begins with the premise that sport organisations and managers need to be equipped to make informed decisions concerning the data ethics implications emanating from business model digitalisation. Further, these decisions demand an empirical and critical platform in order to: (1) ensure fans are aware of data practices conducted by sport organisations, (2) hold sport organisations accountable for digital practices towards fans, and (3) ensure that sport practitioners are informed about how data-driven innovation transforms data into economic capital at the expense of symbolic capital. In addition to pragmatic questions about data ownership and privacy, there is also a greater question about whether sport organisations should be at the forefront of the data-driven economy (King, 2020).

In furthering the above platform, this article aims to explore how data are converted into economic capital through DDBMI models in order to help sport organisations and their managers to better understand the ways in which data can be converted to economic capital, provide exemplars of how sport organisation’s digital innovations instantiate fan data ethics issues and legitimate digital partners, raise awareness of the power issues that should be considered when using data to innovate business models (Sadowski, 2019), and outline a short series of high priorities for future research to promote an ethically informed data-driven sports industry that safeguards fans’ rights.

Data-driven business model innovation and capital

Even more than a decade and a half ago, 2006 German FIFA World Cup organisers had integrated digital channels, data analytics, and branding into a powerful symbolic capital form that became known as the ‘FanZone’. In these specially designed areas, fans unable to get match tickets could still share an emotive experience in a physical space. Presently, virtual FanZones have become commonplace and far more valuable than the physical kind as fans engage with teams, players, and sponsors from a smart device anywhere in the connected world, in the process surrendering their data to the organisers and sponsors for later on-sale and targeted promotions. As Andrejevic (2008) presciently noted, consumers in the digital world are captured within a ‘digital enclosure’, where their every piece of personal information is subject to acquisition and commercial exploitation. It is this digital enclosure that sport fans exist within that provides the setting for our arguments and analysis.

We begin by proposing that, in seeking to reveal the tensions between sport organisations, DDBMI, and sport supporters and fans, it is productive to conceptualise big data as a form of capital that can be translated into economic capital via digital commercial strategies that facilitate asymmetric power concentrations, inevitably in the favour of those with the existing capital stocks (Bourdieu, 1986) to acquire and analyse data (Andrejevic, 2014; Boyd and Crawford, 2012; Sadowski, 2019). Towards that end, we begin in the next section by defining big data, explaining how it came to be viewed as a commercial business model opportunity, and then highlighting the ethical problems of power and control accompanying the commodification of data, the data divide, and digitisation.

Defining big data

Defining what constitutes ‘big data’ is a complex question with most interest to date focused on data qualities (Emmanuel and Stanier, 2016) such as the so-called seven V’s (validity, volume, velocity, veracity, variety, volatility, value; Khan et al., 2014). These qualities of big data enable analysts to study large populations at granular levels using advanced analytical methods (Szymanski, 2020; Watanabe et al., 2021). Alternative attempts at defining big data have avoided focusing on the size and characteristics of a data set, and instead have considered the insights enabled by a data set and the commercial value it can create (Boyd and Crawford, 2012; Mikalef et al., 2018). A data set produced from online behavioural data capable of swaying which product to buy or which political candidate to vote for in an election would constitute big data (Tufekci, 2014). The key point is that big data are not just voluminous but influential. As a result, the term refers to more than just the nature of the data itself, also encompassing the type of analytical process and potential insights that it derives. However, exactly how big data is defined might be less important than how it is used when considered in the context of business models and the conversion of data into capital. We therefore introduce data-as-capital first.

Big data as capital

With the growth of data-driven economies and a transition to DDBMI, sociological, political, and critical economic scholars have raised ethical queries about the use of data and the monopolisation of industries permitted by digitalisation (e.g., Nuccio and Guerzoni, 2019; Stucke, 2017). Critical data studies (Iliadis and Russo, 2016) reject the notion of data as an objective artifact to be mined like other physical resources and instead forefront how big data are an expression of social structure and power (Trittin-Ulbrich et al., 2021; West, 2019). In this sense, data are not just ‘available’. Digital behaviours require purposeful collection, manipulation, and storage to create viable information usable for sale or application. Hence, relatively simple human activity, such as what a person ‘likes’ on Facebook, can be converted and used to create accurate models capable of predicting sensitive insights about an individual (Kosinski et al., 2013). For organisations with the capability, the creation of big data from digital behaviours traced across multiple sites confers them with power over the individuals whose behaviour has been assessed and commodified.

Amongst competing concepts and terms that reflect a critical political-economic approach to big data (e.g., Srnicek, 2017; West, 2019; Zuboff, 2019), a common theme is treating data-as-capital (Sadowski, 2019). Treating data as a form of capital makes it akin to a form of power (Iliadis and Russo, 2016) as it can be converted to economic capital but also other forms (Bourdieu, 1986). Bourdieu argued that social hierarchies are determined by the amount of economic, social, cultural, and symbolic capital groups possess and the value afforded to different types of capital in a field. From this perspective ‘the different types and subtypes of capital at a given moment in time represents the immanent structure of the social world’ (Bourdieu, 1986, p. 15), while the control of highly valued forms of capital dictates hegemonic relationships between actors in a shared field. Under this lens, big data become another type of capital to be accumulated in order to enable commercial growth whilst reinforcing social structures between sport organisations and fans through asymmetries in data capital collation and exploitation. Therefore, all aspects of society become open to datafication and extraction enabled by the ‘Internet of Things’ and embedded online connectivity in social practices. As Sadowski (2019) summarises, ‘When data is treated as a form of capital, the imperative to collect as much data, from as many sources, by any means possible intensifies existing practices of accumulation and leads to the creation of new ones’ (p. 8). Once big data are conceptualised as a unique species of capital (Bourdieu, 1986), it is possible to examine the power inequalities that digital business models manifest through capital disparities (West, 2019) while exploding the ethical issues such imbalances create.

Referred to as the ‘big data divide’, the localised skills required to collect and analyse data encourages disparities between those with the economic and cultural capital (e.g., computer science skills and resources) and those without the knowledge to do so (Andrejevic, 2014). Power emanates from the ability of those who control data to categorise and attribute value to an individual’s personal information without their consent (Lyon, 2014). To use a sporting example, most athletes are subordinate to a digital divide as they are subject to performance monitoring (e.g., biometric and biomechanical data collection) by their team, which is used to assess their economic worth; in most cases without athletes’ full access to the granular data and algorithms upon which they are being assessed (Baerg, 2017). Thus, athletes have a valid argument that they have a right to know and access what is being collected about them, how this is used, and how far into their personal life data collection extends.

The big data divide enables private organisations to determine emergent social practices as the controllers of information exposure and technological design. As private controllers of digital spaces, organisations can implement new requirements (e.g., data consent) and features where users have the choice of accepting or leaving the platform. The latter is less likely given the lock-in and network effects of digital platforms meaning organisations further acquire data capital, cultural capital, and ultimately, economic capital.

Digital business models create ethical issues concerning power and autonomy because there is an imperative to extract as much data as possible positioning matters of consent and transparency in opposition to profit (Sadowski, 2019). Consequently, digital business models rely upon the big data divide, clandestine practices, and user apathy towards data protection to ensure that ‘the depth and the scale of the accumulated data remains opaque and inaccessible to the ordinary person’ (Tufekci, 2014, p. 1). Sport organisations are increasingly adopting data-driven innovations as the industry digitises. Therefore, ethical debates related to capital disparities that were previously limited to the technology sector are relevant in the sports ecosystem. But first it is instructive to review how data can be translated into economic capital via digital commercial strategies.

Data-driven business models

Big data, understood as information sets capable of influencing behaviour and revealing hitherto unavailable insights once analysed, have contributed to the emergence of data-driven business models. At its broadest, by ‘business model’, we mean the way that firms or sport enterprises in this case go about doing business and particularly how they generate value, or more crudely how they make money (Johnson and Lafley, 2010). Despite a proliferation of definitions and constructs, one useful and common point of consensus is that business models reveal not just how firms capture value but also how they create it (Zott et al., 2011). Nor is business model ‘innovation’ just about how technology is employed (Chesbrough, 2007) but rather incremental or radical shifts in one element or numerous within a firm (Ramdani et al., 2019). While Chesbrough (2007) notes that business model innovation goes beyond the application of a new technology, inescapably ‘digital’ business model innovations revolve around digital tools and opportunities, including the collection, analysis, and monetisation of data (Zott and Amit, 2017).

Expanding data availability across various digitised touchpoints has also combined with cumulative computer-based algorithmic prediction capabilities (e.g., deep learning). With the addition of minimal regulatory oversight, market players have recognised the value of collecting, storing, analysing, and applying previously inconsequential data for commercial advantage (Aho and Duffield, 2020; Ciuriak, 2021). Big data analytical methods, such as machine learning, enable the detection of correlations and relationships that were previously unidentifiable using traditional methods and information, leading to predictive algorithmic models that can be used with great effect to shape product marketing, or to inform interventions designed to influence behaviour. Consequently, data-driven business models generate income through the sale of data to other companies, via the collection of freely available data, or by on-selling dedicated analysis that converts the data into actionable insights (Hartmann et al., 2016). The result has been the emergence of high-profile data-driven businesses that hold strong influencing capabilities across society precisely because they have determined how data can be converted into economic capital.

In concert with the rise of big data availability and analytics capabilities, organisations have adopted DDBMI as they integrate aspects of big data into their own business models. DDBMI is defined as ‘when an organization adopts a novel approach to commercialize data as its new underlying asset to deliver value to existing or new customers’ (Fruhwirth et al., 2020, p. 10). Data and technology are used to provide an enhanced value proposition to customers (B2C and/or B2B) through the supply of raw data, knowledge, or a non-virtual product for economic capital (Hartmann et al., 2016). Accordingly, big data are treated as an asset to improve an existing internal product or process (i.e., refinement), or to generate new external revenue opportunities (i.e. creation) through data collection, data analytics, or the digitalisation of technology (Fruhwirth et al., 2020).

With respect to new revenue opportunities, first, data collection refers to unrefined information that can provide value to customers (in the case of sport organisations, we treat fans as the customer) through process and product refinement, where, for example, a sports team can collect usage data from their fan app in order to improve user functionality (B2C). Alternatively, sport companies can share or sell collected data to external third parties to raise revenue (B2B). For example, gambling and fantasy sports companies may purchase fan data or work with sport organisations to better design games that appeal to supporters.

Second, data analytics can also be used to improve the value proposition of organisational processes such as using search history information to promote relevant content to fans (B2C). A final example is the use of analytics to create new value propositions like when customer analysis enables sport organisations to distinguish fan segments that can be offered or on-sold to specific sponsors or licensees (B2B).

Third, digitalisation technology refers to new services that embed technology and internet-connectivity in aspects of the material world and human behaviour (Parviainen et al., 2017). Sport organisations can therefore create new digital products and digitise previously difficult to measure behaviours creating opportunities for product refinement and revenue generation. The availability of enhanced data ‘scraping’ capabilities means that every aspect of the material world that is integrated with technology and internet-connectivity becomes an opportunity for data collection (Royakkers et al., 2018). The transformational yield inherent in data might be captured by the term the ‘Internet of Things’, which broadly refers to ‘scenarios where network connectivity and computing capability extends to objects, sensors and everyday items not normally considered computers, allowing these devices to generate, exchange and consume data with minimal human intervention’ (Rose et al., 2015, p. 1).

Smart watches exemplify how a traditionally analog device has been augmented with digital abilities to increase the value proposition to customers whilst also providing data to companies, such as geo-location tracking (e.g., navigation functions), biometric data (e.g., heart rate), and user behaviour (e.g., messaging services) that can be used to refine products. New digital technologies and environments that replace material experiences, such as NFT collectibles (i.e., uniquely identifiable digital versions of sports memorabilia) and virtual goods located in meta-environments, further create new revenue opportunities as organisations can enter previously unreachable international markets.

A key issue we are seeking to address in this article is that the inflection point where a DDBMI transforms data to capital also exposes sport consumers to a significant series of vulnerabilities. More importantly, by endorsing partnerships with data-controlling organisations and utilising big data products, sport organisations implicitly legitimate such partnerships affording symbolic capital through positive image transfer. In recognising how big data is converted to commercial opportunities and the positive image transfer to sponsors, sport organisations wielding DDBMI must safeguard their users through data ethics protocols. Next, we consider why we think that sport organisations are worthy of specific concern with respect to data ethics vulnerabilities stemming from the transition and bestowal of data, economic, and symbolic capital between fans, sport organisations, and digital properties. By way of illustration, we then provide three examples exposing the power inequities associated with DDBMI in the sport industry.

Data ethics vulnerabilities in sport: the fan factor

Fans strongly identifying with a sport property perceive it in intimate terms, like a trusted friend. Fellow identifying fans are also seen as in-group members sharing a common cultural literacy bolstering collective belonging. Sponsorship can render the in-group boundary permeable by including the sponsor within the intimate, trusted circle. Fans are therefore more likely to accept sponsored communications, especially if the sponsored messages appeal to the collective cultural lexicon of the sport and property (Bauer et al., 2008). A sponsorship that achieves a bond between the fan, the sponsored property, and the sponsor, is more likely to encourage product loyalty for the sponsored product while reducing the probability of defection. High involvement of fans in the sport itself leads to a more positive image of the companies sponsoring ‘their’ sport and leading to more favourable intentions to purchase sponsor products (Ko et al., 2008).

The sport industry has long grappled with partnerships from ethically controversial industries including alcohol, tobacco, junk food, and gambling. The association between sport organisations and these industries has been subject to scrutiny due to sport ‘lending’ its positive image to these contentious industries. Questions have been raised about sport sponsorship involving the promotion of ‘risky’, or potentially unhealthy products. For instance, the concerns begin with alcohol, which can lead to personal illness and anti-social behaviours, and moves on to fast foods, which have been seen as precursors to obesity, diabetes, and heart disease. Digital innovations are now creating connections between sport organisations and digital technologies, and industries. These connections afford symbolic capital (Bourdieu, 1986) to the sponsor or partner through association with the positive image of sport held by fans whilst simultaneously generating power inequalities through conversion of data to capital.

Sport properties might lend credibility and trustworthy associations to brands, organisations, or products without appropriate data management safeguards. Sports properties and authorities have an obligation to protect their stakeholders’ data rights. From a data ethics viewpoint, the issue is not just whether certain brands or products are necessarily too unsafe or risky, but also whether an endorsement or sponsorship of some form will infer data security as well. While it is evidently possible to run successful (for the investor) sports sponsorship programmes for both ‘unhealthy’ products (tobacco, fast foods) and health-neutral products (electronic consumables, credit cards, etc.), it is generally agreed among theorists of team sponsorship that the greater the congruence between sponsor and sponsored product (sport in this case), the more likely that the observer (potential consumer) will see the sponsor as altruistic and therefore perceive the product favourably (Rifon et al., 2004). Bennett (1999), for example, suggested that a state of ‘false consensus’ is created through sponsorship, whereby individuals assume that their own judgements are appropriate and that alternative judgements are incorrect.

Successful sponsorship campaigns remove or minimise any scepticism about the product resulting in sports fans, supporters, or even casual observers of the sponsored product (a sporting event or team) simply attributing the positive qualities of the sport, team, or event to the product. A form of sponsorship-altruism is created whereby such products come to be seen as integral to sport (e.g., the sport property’s NFT or cryptocurrency), but the same effect does not occur with other products. In a seminal critical commentary, Slack (2004) referred to how the symbolism and imagery of sport becomes associated with an individual’s need for the sports-associated product and how a consumer’s personal identities are associated with consumption of the sponsor’s product.

Yet sport fans are not necessarily passive recipient of brand messages and brand-initiated interactions. In many cases, they take an active role in shaping brand relationships for their own advantages, whether for access to fellow fans in geographically distant locations, savings on desired merchandise, or access to novel experiences. A fan’s interactions with a sporting brand can yield a co-created experience, stimulating engagement and delivering experiential value, satisfying their insatiable demand for higher levels of personalisation and value. Symbolic value also resides beyond the fan/team connection, extending to a broader group of stakeholders that form the sport value network (Woratschek et al., 2014). Sport therefore operates within an ecosystem where stakeholders collaborate to achieve mutually beneficial outcomes through interactions that result in data sharing. Furthermore, since value is based on fans’ consumption experiences, sport brands might reasonably argue that their data acquisition and utilisation is a necessary feature to deliver the social bonds to allow each party to achieve their goals (Neghina et al., 2015).

When explored through the lens of how sponsorship may successfully engender product loyalty, the data ethics issue revolves around how the associated technologies and companies gain symbolic capital and legitimacy from sporting sponsorships, endorsements, and partnerships. Instead of putting the onus on partners, such as digital broadcasting platforms, to prove the values of their products with respect to sport, the relationship implies that sports authorities (administers, teams, and sport event organisers) have a responsibility to re-examine whether they are satisfied that such relationships are data safe.

Companies leveraging sport brand partnerships not only aim to build their product profiles, but also reignite their brand image and strengthen their legitimacy as suppliers of products that deliver fan benefits. Equally, sport organisations employing digital innovations, such as fantasy gambling games or fan tokens, in their own business models confer positive sentiment to the product. Both of these approaches constitute digital sport business models, however, favourable attitudes towards affiliated companies and their products risks camouflaging a lack of clarity surrounding their products’ data efficacy and safety. The digital ethics of a business model innovation through a digital partnership or sponsorship with a sport property rest on the legitimacy conveyed to these products by sport brands, and the implicit trust it creates when users are asked to hand over their personal information, or even when their consumption is tracked without notice. Not only then does the power inequality between sport organisations and fans increase through data collection, sport properties might also be conveying credibility on a new and largely unknown class of companies and products that collect, manipulate, and monetise fan data without oversight.

Sports properties are facing vulnerabilities as their endorsement of new technologies and digital partners implicitly legitimates these affiliates with the ethical issues associated with conversion of data to economic capital central to their appeal. Where once, tobacco, alcohol and gambling were vilified, we may come to view the willingness of sport organisations to embrace economic capital generated through big data applications and a transfer of symbolic capital to partners as equally morally contentious.

Data, capital, and ethics in the sport industry

As we noted, digital sport business models involving DDBMI, has included a proliferation of online, indigenous platforms, add-on devices, and streaming web services that interchanges data, symbolic, and economic capital. We begin here with a detailed example of DDBMI focusing on how broadcasting partnerships between sport organisations and online platforms, leading to an exposition of the power inequalities the transformation is instantiating. Second, we describe how a combination of coercion into e-ticketing paired with smart stadiums normalises technology that relies on data collection with fans. Last, we examine how digital fan tokens encourage sports fans to purchase digital products without due diligence.

Example 1. Sport broadcasting

In the absence of live broadcasting rights, some broadcasters have sought to generate economic capital by repackaging recorded sport with commentaries, highlights, and new content. Meanwhile, others relying on subscription revenues license the sport content for a series of events, matches or seasons, or like Netflix and their competitors, tinker with a modest amount of new content production often as documentaries. Inexorably, the rise of digital platform businesses in society (Nieborg et al., 2022) has stimulated a commensurate rise in the value of digital consumption data. Platforms are ‘digital infrastructures that facilitate and shape personalised interactions among end-users and complementors, organised through the systematic collection, algorithmic processing, monetisation, and circulation of data’ (Nieborg et al., 2022, p. 32). Platform-based businesses, such as Alphabet, Amazon, and Tencent, control data circulation by operating intermediary services such as social networking, payment services, and crucially streaming (Van Dijck, 2021). The platformisation of society further skews power imbalances as DDBMI are reliant upon the small number of organisations operating platform services. Sport organisations wishing to broadcast content via social media (e.g., YouTube) or streaming services (e.g., Amazon Prime) therefore become ‘complementors’ in multi-sided markets governed by the logics of platform businesses who control access to data, how content can be monetised, and what is ‘appropriate’ online behaviour (Petersen-Wagner and Lee Ludvigsen, 2022a) reinforcing the oligopolistic status of major platform businesses (Van Dijck, 2021).

These platform giants have ventured into sports broadcasting offering digital and mobile viewing options ostensibly motivated by the economic capital derived from online advertising and subscription revenue (Hutchins et al., 2019). However, their business models are geared towards accumulating consumer data too, poised for exploitation via other services and products, or for various forms of sale or fee-based access. For example, Amazon has purchased broadcasting rights to drive new consumers to its ecommerce platform (Hutchins et al., 2019). At present, the model principally revolves around electronic sell-through or video on-demand where sport consumers subscribe, purchase, or rent pre-packaged recorded shows, movies, or events.

Despite the juggernaut market presence of players like Amazon and Apple, their model fits poorly with live sport given the need to acquire event, match, or game rights that are largely controlled by television broadcasters and pay-per-view providers. Similarly, advertising-driven user-generated content providers like YouTube provide for some sport recordings but also censor others, collecting consumer data along the way. Despite the inherent challenges, the interest in sport broadcasting shown by platform giants places them in direct competition with international media conglomerates that have historically controlled fan access (Lawrence and Crawford, 2022).

The question that arises is whether sport content owners extend their data ethics responsibilities to those fans and consumers who access sport via on-sold platforms. If current expectations hold, we might expect that technology partners purchasing content from sport owners would not be quick to yield to imposed data ethics restrictions. It is also unclear how third-party vendors can protect the content uploaded by sport properties, or of the data associated with its consumption given the secrecy of platform businesses pertaining to their algorithms and infrastructure (Van Dijck, 2021).

Sport consumers might even be their own worst enemies when it comes to safeguarding their data from covert commercial exploitation. With a growing sense of impatience, sport fans have drifted towards on-demand, mobile, customised, and digital sport viewing, in the process trading the convenient removal of irrelevant clutter for personal information. YouTube, for instance has become a central feature of modern sports fandom allowing consumers to express dissatisfaction and find solidarity with other fans (Petersen-Wagner and Lee Ludvigsen, 2022b).

Sport consumers have started to ‘cut the cord’, electing to experiment with digital platforms instead of conventional free, cable, pay-per-view, or satellite delivery. Such platforms provide ‘over the top’ (OTT) content, requiring little more than some hardware like a smart TV or a box and fast online data streaming. The new data capital-based business models will therefore capitalise on multi-platform viewing expectations from a new generation of data-loose mobile audiences who prioritise fluid on-demand options via digital environments (Hutchins et al., 2019). If the trend continues, we will see the exclusive licensing model embedded in sport fall to a more fragmented assortment of consumer on-demand platforms, all of which will inevitably require a minimum of personal data to participate increasing the digital divide situating control of data capital with platform owners. For the sport consumer, the on-demand model offers bespoke customisation in exchange for their data. Of course, the combination of consumer choices, analytics, and predictive AI will provide the digital licensees with a rich vein of commercial data to exploit further entrenching the power dynamic between fans, clubs, and broadcasters.

Rather than selling rights to platform businesses or uploading content to digital media platforms, some sport organisations, like the NBA and NFL, have already ventured seriously into their own broadcasting platforms, although so far it remains unclear to what extent they have collected or monetised the data of their consumers. As a digital sport business model, direct-to-fan content converts sporting properties into media companies, which as we noted in our exposition of DDBMI, might be more accurately described in the near future as ‘data’ companies. The transformation to generating economic capital from data places new ethical responsibilities on sport properties, which would be poised to shunt consumer data through a vertically integrated product pipeline. In addition, content owners can sell advertising, attract more lucrative sponsorship contracts, and yield subscription fees placing them in competition with existing platform business giants.

Inevitable digital platform growth will be accompanied by a commensurate risk in data ethics breaches. Partly, exposure will be relevant, as DDBMI is the most fluid, flexible, and modular, incorporating advertising, subscription, or customised OTT content, all connected to users’ profiles and consumption histories. As broadcasters select the most lucrative games for conventional free or pay-per-view broadcasting, the remainder of simultaneously played games can be made available via alternative digital channels (live or recorded), in mobile-friendly formats, or even held over for streaming by the sport content owners for repackaging via their own channels. If online streaming were to become the dominant paid programming vehicle for sport content and products through a concoction of connected devices, then not only will the volume of data available to sport organisations increase but sport consumers’ data will reside at the centre of a prodigious new form of unrealised capital.

Allied with the platformisation of sport content is the legitimation of online platforms that collect user data with opaque personal data policies that enable third-party tracking. For example, multiple sports leagues have signed contracts to broadcast events and highlights for free via YouTube including the Indian Premier League, International Olympic Committee, and the National Football League (McCaskill, 2021). A study by Klais (2022) however, showed that YouTube contacts 14 other domains to enable user tracking. Likewise, TikTok has become a platform for sports content and highlights for many organisations and has agreed sponsorship deals with notable properties including English Premier League sides, Ultimate Fighting Club, and Extreme E. The same Klais (2022) study demonstrated that the app was allowing 13 third-party domains to track data. If users are concerned about their privacy online, the willingness of sport organisations and teams to promote content through these platforms gives credibility, and symbolic capital that encourages supporters to reveal personal information online (i.e., the privacy paradox; Kokolakis, 2017). For sport organisations, there is the added benefit of data collection and feedback on content strategies enabled by digital platforms, even if organisations must follow rules set out by platforms (Petersen-Wagner and Lee Ludvigsen, 2022a). Similar arguments can be made about the symbolic capital bestowed by the sale of broadcasting rights to platform businesses, such as Amazon and Tencent, that collect and share behavioural data to third parties for financial gain. The traditional consumption of sport via attendance, television, and print media are being replaced by internet-connected processes capable of data collection. This represents new trends in the transfer of data, symbolic, and economic capital between sport organisations and digital platforms even if organisations cannot guarantee privacy or safety to supporters who are required to use these digital platforms to engage with their sport.

Example 2. E-ticketing and smart stadiums

The second example to demonstrate the power inequalities issues associated with digital sport business models reliant on data capital is the increase in ‘forced technology adoption’ of e-tickets (i.e., digital rather than physical tickets) typically offered by team or stadium apps (Popp et al., 2021) in combination with ‘smart stadiums’ (Yang and Cole, 2022). The benefits of e-tickets are notable including control over resales, automated transactions, reduced waste, and crucially, data collection on fans. Popp et al. (2021) provide a relevant study of attitudes towards forced adoption of e-tickets indicating that most fans surveyed preferred digital tickets (48%) over physical tickets or had no preference, but 73% of participants who preferred a physical ticket were 45 years or older. Further, ticket preference had no impact on future likelihood to attend, potentially explained by the lack of alternatives for fans who want to attend sport (Popp et al., 2021).

The forced used of e-tickets in conjunction with smart stadiums raises concerns over the autonomy supporters are afforded in transferring their data capital to sport organisations. Questions have been raised about whether individuals should be compensated for their data given that it is typically monetised (i.e., converted to economic capital) once collected (Sadowski, 2019). In can be argued that use of the desired service (e.g., an app or search platform) in exchange for user data is compensation, but in the case of e-ticketing sport fans have no alternative. In synergy, smart stadiums have emerged as a tool for teams to enhance fan experience, increase sales, and collect user data (Melander, 2016). Through a combination of stadium apps and internet-connected sensors within a stadium, sport organisations can track and collect fan pictures, location, movement, purchases, interactions, and even loyalty (Ferguson, 2020; Watkins and Lewis, 2014; Yang and Cole, 2022). The potential coercion of fans onto stadium applications via e-ticketing that are capable of tracking user and behavioural data undermines the privacy of supporters who are forced to use applications capable of collecting personal information for commercial purposes that may also be distributed to undisclosed third parties. Forced adoption feeds into autonomy as user data can be applied to influence fan behaviour through targeted advertisements that increase commerce sales for the organisation with little consideration of what is best for the supporter (Watkins and Lewis, 2014; Yang and Cole, 2022).

The combination of forced adoption and the employment of technologies that rely on data collection demonstrate how sport organisations normalise and bestow symbolic capital on digital products reliant on capturing user information. The conversion of data as a form of capital into economic capital inadvertently provides symbolic capital to the organisations, partnerships, and products that allow this transaction. Research has begun to explore how fans can reject technology in sporting spaces (Hutchins, 2016; Uhrich, 2022), but there is a lack of inquiry reporting on to what extent fans understand how their behaviours are being tracked, how this data are used, and if they are willing to trade privacy and autonomy for an enhanced digital experience.

E-ticketing exemplifies a convergence impact as hardware technology, software development and application, digital channels, and social media entangle to create new opportunities for symbolically amplified fan data. Although nascent, wearable media technologies and associated applications are increasingly combining with smart watches. Added to smart watches is the rise of microchipped ‘attachables’ integrated into phone software providing everything from heart rate monitors to predictive software capable of anticipating the needs of the user, in the process generating masses of personalised data. In a smart stadium setting, this convergence of different data sources provides sport managers a potentially unbridled view into fans thoughts and feelings to be utilised for commercial purposes.

E-ticketing and smart stadiums expose the power inequities emerging from the relationship between data, symbolic, and economic capital exchange in sport DDBMI. Primarily, data capital is being taken from the producers (i.e., fans) without consent for sport organisations and their partners to monetise. This transaction then undermines fan privacy and autonomy. Forced adoption also leverages the value of symbolic capital as sport organisations promote e-ticketing agencies to supporters and embed the use of digital platforms as part of the game day experience.

Example 3. Fan tokens

The final example is provided by the adoption of digital fan tokens supplied by Socios.com, part of blockchain provider Chiliz. Recently, cryptocurrency platforms have entered into significant financial relationships with major sports properties including naming rights, broadcast advertising, and shirt sponsorship deals affording symbolic capital to these platforms. As noted by the Advertising Standards Authority (2021), cryptocurrencies are an investment that are often poorly understood and high-risk. As sport regulators determine whether it is appropriate to partner with other industries given the harm they may cause, perceptions of cryptocurrencies and sport should also be scrutinised. A further issue arises in the form of due diligence as sport organisations adopt official cryptocurrency partners without full assurances of the companies propriety (Guardian Sport, 2021).

The power inequity problem is not specifically or exclusively linked with any one new digital product, whether cryptocurrency or NFT. Any brand or product associated with a sport property might have the opportunity to collect data from sport consumers; indeed, the solicitation, collection, and monetisation of such data capital are primary motivations for endorsements in exchange for paid access. However, implicit associations in the form of sponsorships or other endorsements can lead to the transfer of symbolic capital and trust.

Professional clubs from a variety of sports including European soccer, US basketball, and motorsport have established partnerships with Socios.com, encouraging supporters to buy club-specific fan tokens that promise buyers the chance to influence club decisions (Socios, 2022). Fans can only purchase Socios’ tokens using the cryptocurrency Chiliz. In theory, the ability for dedicated fans to influence decisions is a promising opportunity to promote engagement and integrate supporters into governance. In practice, fan tokens have received criticism for offering few meaningful engagement opportunities and the reality that cryptocurrency traders with no interest in the club can profit from legitimate supporters whose tokens may lose value (Football Supporters Europe, 2022). In this sense, the symbolic capital afforded by sport clubs to cryptocurrency required to purchase fan tokens facilitates economic capital transfer from fans to digital platforms. Further, the British Advertising Standards Agency upheld complaints against Arsenal Football club’s fan token advertisements for trivialising cryptocurrency investments, taking advantage of low consumer experience, and not highlighting the full financial nature of the transaction (Advertising Standards Authority, 2021).

Most concerningly, fans of different English Premier League soccer clubs have protested the monetisation of their fandom via tokens, arguing that they should not have to pay to be involved in club decisions (MacInnes, 2022). West Ham United eventually cancelled their fan token launch with Socios following the backlash from supporters unwilling to pay for a voice in the club. The case of fan tokens exemplifies (1) the potential injustice of fan exploitation given their committed status via unequal power relationships enabled by digital strategies, and (2) the level of trust and involvement expected from supporters that were violated.

The symbolic capital inherent in sport, and its exploitable potential through risky digital products, highlights the rise of the ‘prosumer’ fan (Santomier and Hogan, 2013), the emerging group of informed, empowered, and networked consumers who simultaneously produce, distribute, and consume content. Detailed information about huge numbers of fans is converted into customised offerings, in some cases offered directly to those fans whose recorded behaviour matches or predicts a favourable profile including the propensity to make large purchases with alacrity, and high levels of risk tolerance. Added to this, prosumer fans themselves create and contribute valuable niche content into the data pool describing their own experiences and stimulating others to engage around new products like cryptocurrencies. The cycle catapults data to unparallelled levels of transformative capital.

The 2022 cryptocurrency crash is the starkest demonstration of the risks to sport organisations that accept financial injections from digital platforms in return for the symbolic capital associated with being an official partner of a prestigious sports property. The burst of the cryptocurrency bubble has led to most ‘coins’ losing significant value (Hern, 2022). As fan tokens were tied to a coin, supporters who believed they were purchasing fan tokens have lost fiat money as the cryptocurrency underpinning the purchase have devalued (D’Urso, 2022). Despite the dramatic fall in cryptocurrency value, sport organisations continue to endorse sponsorship deals from the industry undermining claims about protecting fans (Orchard, 2022).

Conclusion and future directions

This article is motivated by the first premise that professional sport’s entry into the digital economy has brought with it the increasingly widespread adoption of DDBMI, which have allowed big data to be converted into capital. A corollary of the capacity to transform data into capital is a suite of ethical vulnerabilities accompanying the power over fans facilitated by acquisition and application of data. The purpose of this article was therefore to highlight the potential ethical vulnerabilities sport organisations and their leaders face when adopting digital sport business models. Our argument proposed two advantages accompanying the treatment of data as a species of capital that can be converted into economic capital once it undergoes a transformation via DDBMI.

First, it helps make transparent the mechanisms through which digital sport business models work. Second, it reveals how the extraction and application of big data for economic capital at the expense of symbolic endorsements of partners intensifies inequitable power relationships between sport organisations and supporters – the big data divide – that leads to ethical vulnerabilities to sport organisations and their consumers. Finally, we proposed that sport consumers might be particularly vulnerable to digital data risk as a consequence of their high levels of brand loyalty and involvement, which tend to encourage trust in the sport properties soliciting, analysing, and monetising their data. We exemplified the vulnerabilities associated with DDBMI in potentially violating the trust of supporters when using digital strategies via three examples: platform broadcasting partnerships; e-ticketing in smart stadiums; and cryptocurrency-based fan tokens.

The examples demonstrate how increasingly common digitalisation strategies applied by sport organisations can generate ethical vulnerabilities when analysed using a political-economic approach to data. The vulnerability emerges as the well-recognised ethical concerns associated with technology and business models that harness big data are being symbolically legitimated through association with the positive image of sport organisations and the profound trust fans accord them. We now finish with propositions for future research that can further understanding of data ethics vulnerabilities in sport, and thereby help guide practitioners.

Firstly, it is prudent to examine how different stakeholders may view the ethical issues created by the sport industry’s digitalisation. Understanding fan views concerning how data are collected and analysed by sport organisations is most pressing given that they are the source of behavioural data being commodified and used in predictive algorithms. Exploration of how much data fans believe organisations are collecting can help reveal the level of awareness and trust among supporters. Equally, studies comparing expectations of sport organisations against other industries can establish whether clubs are held to a higher standard than other businesses. Several studies have examined how the technology was received by supporters with mixed findings (Hutchins, 2016; Uhrich, 2022) and understanding the source of these beliefs is imperative to making ethically informed decisions and promoting technology uptake. Further, the willingness to trade-off data for enhanced experiences should also be considered, as it is perfectly reasonable for fans to wish to benefit from the sharing of their data. At a minimum, fans should be informed and educated on how their data will be used and any implications. Alternatively, structures that provide fans with greater power within sport organisations to determine how data are used may be championed such as meaningful fan votes on data ownership and sales, board representation, fan ownership, or policy intervention from central government or funding bodies. Similarly, greater fan involvement in organisational structures might lead to vetoing new digital partners considered problematic.

Secondly, researching managerial views of digitalisation to understand how ethical issues are currently treated by sport organisations, and the extent to which they are considered, provides another promising line of investigation. It is also worth exploring how developments in other industries influence digitalisation in sport. For instance, how have emergent digital marketing practices such as social media advertising translated into sport. Likewise, how has data collection and insight changed the relationship between gambling companies, sport organisations, and fan? Scoping analysis of sporting organisations to ascertain organisational level of preparedness for data violation issues (e.g., a data leak) can also shed light on attitudes towards data management and opportunities to provide support to organisations. Content analysis of usage and privacy terms and conditions for sport organisations can reveal the extent to which sport organisations track users and whether there is any notable difference in how organisations handle data in comparison to other industries. Given that many sport organisations are partly or wholly funded by governmental departments, such as national federations, data collection and ownership also tread a thin line between private and public possession.

Lastly, sponsors and broadcasters represent another stakeholder group that merit attention. Sponsors are keen to align their brands with the image and values of sport to drive positive association and commercial outcomes. Digitalisation is a double-edged sword as sport organisations can provide detailed, granular insights into fans and sponsorship impact metrics to attract larger fees, but simultaneously risk damaging their highly prized image through data breaches. Inevitably, sport sponsorship and marketing research will have to address the ethical vulnerabilities presented by big data. Similarly, the broadcasting industry is at the forefront of digitalisation as consumers switch to OTT platforms and demand customisable viewing experiences. Augmented and virtual reality technology as well as internet-connected devices have been propositioned as the solution to tackling dwindling in-person attendances. How sport organisations implement network-connected technology in the pursuit of viewers will have telling consequences for the privacy of fans, especially when fans are more vulnerable to accept sport enterprise and sponsorship messaging without critical evaluation.

In this article, we have advocated for a critical review of the digitalisation of the sport industry and the subsequent impact on fans. Although digitalisation is nascent in the industry, sport organisations are only likely to further integrate digital technology in physical and material supporter practices. Sport management scholars need to be acutely aware of the ethical problems that big data sets created through the Internet of Things may present in an industry distinguished by high fan loyalty. Failure to do so could lead to data incidents that generate fan backlash or even drive supporters away from the club. Treating data-as-capital (Sadowski, 2019) is one conceptual lens that enables ethical interrogation of digital sport management practices. The critical analysis of sport’s digitalisation raises broader questions about the function of competitions. In the short term, digitalisation provides new levers to clubs and sponsors through which to monetise fandom. The insights gained from such analysis might also transfer into other areas of society that look to capitalise on big data placing sport management in a position to contribute to critical data studies more broadly. For example, it is likely that monitoring technology applied in smart stadiums will increasingly pervade other social spaces. In the long term, it is feasible that business model of professional sport will explicitly include collecting and selling data on individuals turning sport organisations into ‘data companies’.

In closing, the intersection of sport, fandom, and technology surfaces deeper philosophical questions for sport managers that need to be answered. As digital technology changes how sport is played, consumed, and monetised, there is the uncomfortable problem for organisations and leagues of determining what is the purpose of sport? For sport management scholars, there is the question to whom do allegiances lie, and whose priorities in the sport industry should be promoted?

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Daniel Read

Note

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