Trade-in marketing strategies in gaming industry: The effect of digital transformation

Abstract

The gaming industry is undergoing a significant digital transformation. Gaming firms are thus incentivized to reassess the key areas in their business operations, such as the trade-in marketing offerings. We investigate two primary trade-in marketing strategies adopted by gaming firms, namely, trading physical copies of old games for physical copies of new games (TON) and trading physical copies of old games for digital copies of games (TOD). We employ multi-objective mathematical optimization models incorporating consumer preferences, government interventions, and impacts of digital transformation. Key findings include (1) when the publisher cannot observe digital-preferred consumers in the game market, enhancing the acceptance of digital copies and increasing service efforts for ordinary consumers are beneficial for boosting demand; (2) government-subsidized trade-in options can drive both gaming firms and consumers toward TOD; (3) when facing a high proportion of digital-preferred consumers, if government subsidies are low or require additional service efforts, the publisher may consider abandoning the TON or TOD strategies; and (4) when government identified a large proportion of digital-preferred consumers, providing a certain amount of government subsidies aimed at nudging the digital transformation can both increase consumer surplus and publishers’ profit. Our study enriches the literature by shedding light on the interplay between digital transformation, consumer preferences, and regulatory frameworks and offers valuable insights for policymakers and managers seeking to promote sustainability on the digital economy.

Introduction

The gaming industry is not only the largest but also the fastest-growing sector in the global entertainment industries (Nan et al., 2022; Parshakov et al., 2020; Ward, 2022). The fast-growing gaming industry in recent years is also a direct outcome of the COVID-19 pandemic, which has significantly shaped the lifestyle of people around the world (Piñeiro-Chousa et al., 2023). For instance, during the periods of lockdown and “work from home,” playing games has become a popular choice for home entertainment, and many people have (re)developed a hobby in gaming. This has led to an increase in gaming consumption in the global market. Such changes in culture and society are considered definitive factors that have contributed to the growth of the gaming industry and helped strengthen its market dominance in the foreseeable future (Ruohonen & Hyrynsalmi, 2017; Skwarczek, 2021). Based on a report by PwC (2022), the revenue of the gaming industry typically stems from the following segments: casual games, PC games, console games, and integrated video game advertising. Among these segments, casual games (e.g., mobile phone and web-based games), PC games, and integrated in-game advertising are either already or nearly fully digitalized (i.e., games are sold digitally). Thus, our study focuses on the segment of the console gaming market, where games are distributed through two distinctive channels: traditional retailers (selling physical copies) and digital online shops (selling digital copies) (Rietveld et al., 2019).

Console gaming publishers have adopted both traditional retailing and digital distribution. In retailing, games are sold via storage media such as CDs (used by most publishers) and cartridges (used by Nintendo only), which are termed physical games. Physical copies can attract consumers as they provide long-term access for games, which can contribute to publishers’ reputation (Rietveld & Eggers, 2018). However, they also bring additional costs including the expenses for manufacturing, logistics, and retailer margin and can cause environmental burden as a form of e-wastes (Islam & Huda, 2020). There is an incentive for publishers to promote demand for digital copies and achieve sustainability mainly for two reasons. First, publishers can increase their profit margin given games are often priced the same for both retail and digital copies but with different costs. For example, a newly released console game is currently priced at $70 in the US (i.e., the “full price” of a console game in the current console generation: PS5 and Xbox Series X/S). In the case of digital sales, the revenue for first-party and third-party publishers can increase to about $70 and $49, respectively; whereas in the case of physical sales, the revenues for first-party and third-party publishers are set to decrease to about $45.5 and $35, respectively (Toto, 2020). Second, digital copies can help the publisher cope with digital transformation and provide environmentally friendly products (Brassell, 2022). While publishers might prefer digital sales as evident in the continuous rise of digital sales, many consumers still prefer the ownership of physical copies (Plant, 2021). Coupled with other factors such as infrastructure development (e.g., high speed internet is often required for the ease of using digital games), publishers may still not give up on traditional retailing, and hence, they seek to promote sales for both CDs and digital copies. Therefore, as one of the key sustainable operations in the video game industry, publishers may investigate the trade-in marketing strategies in two ways: trade old CDs for new CDs (TON) (e.g., trade in old physical games for new physical games) and trade old CDs for digital copies (TOD) (e.g., trade in physical games for digital vouchers, which consumers can use to purchase new digital games).

Apart from the sustainable operations on the publishers’ side, under the calls for better sustainability and environmental protection (e.g., low-emissions circular economy), many governments have devoted efforts to stimulate and incentivize both corporations and consumers to move toward a greener and more sustainable market environment, including using regulations and subsidies for the reduction and recycling of e-waste goods (e.g., Morton, 2020). Such efforts could also affect the video games industry given that physical games are traded via CDs and cartridges packaged in plastic boxes. Subsequently, publishers may be required to promote digital games and/or limit the sales of physical games. Consumers may be incentivized to choose digital games in the future and possibly reduce their possession of physical games on hand (Brassell, 2022; Zhang et al., 2024).

However, despite the market trend that seems to be pointing at a “digital future” for the console gaming market, digital games in their current state are not yet perfected to replace traditional physical games. For example, from the consumers’ perspective, many people simply still prefer to buy physical copies. Some consumers are collectors who purchase physical games as they enjoy having a gaming collection that “can be seen and touched.” This gives them a sense of de facto owning a game, which digital copies cannot provide (Hall, 2020). This is also one of the biggest advantages that physical games have over digital games. Physical media can be permanent if they are properly maintained. Digital copies, on the other hand, are essentially an access or license which grants the consumer the right to download and play the game. Consumers cannot own a digital game—as they may lose their access in situations such as when the platform or servers are made unavailable. A recent controversy involving Ubisoft, a France-based multinational gaming publisher which decided to shut down the servers for several old games and their paid downloadable content, is a case in point—a major public outcry from the fanbase eventually made Ubisoft postpone the closure of the game servers (Wales, 2024). However, major damage has already been caused to the company’s reputation. As such, “the biggest problem with digital distribution [is that] you can’t buy games… you can only rent them for a nebulous period of time” (Rowe, 2022). This is the reason why many consumers still favor physical games and traditional game retailing.

In summary, the two distinct market segments in console gaming highlight the potential for publishers to invest more resources in the digital transformation of game sales and explore further opportunities for value creation. However, it has proven challenging for digital publishers to attract the demographic of gamers who still prefer buying games physically. Therefore, our study will explore possible solutions to this issue by evaluating strategies for publishers to better promote the digitalization of the gaming market and potentially attract more traditional consumers to the digital segment. In other words, our study examines potential trade-in marketing strategies that console game publishers can adopt in their pursuit of digitalizing game distribution and sales (i.e., replacing traditional retailing with digital sales, influenced by higher profit margins as well as the calls for environmental sustainability). In doing so, we will address the following two research questions:

• RQ1: What is the motivation for gaming publishers to implement the TOD strategy (allowing consumers to trade old physical games for new digital games) over the TON strategy (allowing consumers to trade old physical games for new physical games)?

• RQ2: How do consumers preference in digital/physical games and government subsidies affect publishers’ selection of the above two trade-in marketing strategies?

Our study aims to make several significant contributions. Firstly, we consider the impact of consumer preferences and government intervention when studying companies’ market strategies for value creation (i.e., pricing and trade-in marketing strategies to promote the digitalization of game sales). Secondly, in the context of digital transformation, we further dissect the concept of “trade-in for new products” into TON and TOD and examine the antecedents of a company’s strategic choices between these two sub-trade-in strategies. Thirdly, we conceptualize and develop a new model to outline the interactions between consumer behaviors (motivated by government subsidies) and a company’s adoption of trade-in strategies.

The paper is organized as follows: “Literature review” section reviews the related literature, and the “Model setup” section introduces the model set. The “Equilibrium analysis” section provides an equilibrium analysis and comparison without considering consumers’ digital preferences, and the “Numerical studies considering digital-preferred consumers” section compares two strategies with consideration of consumers’ digital preferences. The “Limitations and directions for further research” section offers managerial insights and future research directions.

Literature review

Digital transformation and consumers’ digital preference in video game industry

The rapid changes and evolution in the video game industry have attracted much attention in the literature on innovation and strategy (Handrich et al., 2022; Kim & Gruca, 2024; Majumder et al., 2022). Game publishers tend to produce innovative products and influential cultural icons that bolster the growth and development of the entertainment and internet-related sectors (Burger-Helmchen & Cohendet, 2011; Ciriello et al., 2023; Kim & Gruca, 2024). A significant part of the value creation process in the video game industry is the cognitive resources obtained from consumers. Existing research on the video game industry often emphasizes the core of the publishers’ organization being the specialists and user communities (Lantano et al., 2022). Due to the increasing demand from user communities for faster communication channels and enhanced visual effects, firms are rapidly transforming and have begun to incorporate digital tools for platform upgrading and product offerings.

Previous studies indicate that consumers in virtual communities seek strong communication platforms due to their geographically dispersed locations and the need for social networking during gaming. Publishers in the video game industry are incentivized to develop a broad range of software systems that enable consumers to communicate, interact, and share data with group members or other users. Some studies suggest that the development of digital platforms can facilitate the mechanics of conversation and relationship building before, during, and after games (Cameron, 2022; Mele & Russo-Spena, 2022). Internally, due to the high demand for innovative features and virtual effects experiences, managers of gaming companies are seeking diverse talents and expertise with high artistic values that can promote the development of digital tools (Cohendet et al., 2018). Externally, like in other industries, the rapid globalization and competitive pressures for global integration require firms to develop digital capabilities that allow them to integrate online gaming activities on a global scale (Deng et al., 2022; Feliciano-Cestero et al., 2023).

Considering the advantages of digital transformation, gaming publishers have introduced new business models for digital gaming, namely, subscription services similar to Netflix and Amazon Prime, where consumers can stream or rent a library of digital games by maintaining an active membership (e.g., PlayStation Plus, Xbox Game Pass, EA Play) (Koch & Bierbamer, 2016; Skwarczek, 2021). Over the past decade, digitalized gaming distribution has been accepted by both publishers and consumers, as evidenced by the continuous rise in digital sales (Lantano et al., 2022). For instance, in the fiscal year of 2021, Sony reported that at least 60% of their first-party game sales were accounted for by digital sales, and Nintendo also reported a 40% digital contribution to its annual sales, which was a 12.3% increase compared to 2020 (Plant, 2021). The digital transformation of gaming publishers enhances their ability to attract more attention from virtual communities and improve the user experience in gaming.

Trade-in strategy in video game industry

Trade-in practices have been increasingly adopted by firms in markets of durable products over the last decade (Heidenreich et al., 2023; Rao et al., 2009). Research shows that the exchange-old-for-new program in electronics, household electrical appliances, and automobile sectors has helped firms reduce production costs and facilitate the recovery of used products (Quan et al., 2021). In literature, the trade-in mechanism has been widely recognized as an important channel for green or sustainable supply chain operations (Li & Tian, 2024; Miao et al., 2017). Researchers examine how firms can offer a trade-in rebate to reduce the deterioration rate of used products and lower recovery costs (Xiao et al., 2017). Gift cards or cash coupons, for instance, are used to facilitate trade-in marketing strategies (e.g., Cao et al., 2020), especially for those firms operating in B2 C platforms. Some studies explore the potential conflicts between the coexistence of trade-in programs and used products in a secondary market (Feng et al., 2020; Quan et al., 2021), highlighting the need to reconsider whether firms should offer trade-in services in different situations (Bian et al., 2019).

Due to increased environmental pressure and climate risk, gaming publishers and consumers are encouraged to participate in trade-in programs. On one hand, publishers can utilize trade-in marketing strategies to offer different price schemes and change their pricing decisions considering market segmentations and the costs of recovering a used product (e.g., Ray et al., 2005; Wu et al., 2023). For instance, Sony, Microsoft, and Nintendo charge royalties for trade-ins when releasing games on their consoles and upgrading gaming programs (e.g., Sheu & Choi, 2019). On the other hand, consumers are offered opportunities to acquire new products at a lower price by returning their used ones, which allows cost savings and incentivizes consumers to accept the trade-in service (Quan et al., 2021). In retailing, games are sold via storage media such as CDs (used by most publishers) and cartridges (used only by Nintendo), which are termed as physical games. Physical copies can attract consumers as they provide long-term access to games. However, it has been shown that incorporating trade-in programs can encourage consumers’ repeat purchasing (Liu et al., 2019). The remanufacturing process also brings about additional costs for the publishers, such as expenses for manufacturing, logistics, and retailer margin (game retailing is normally done by dedicated retailers such as Gamestop and Bestbuy in the North American market.

Government intervention

Given that operations in the video game industry are rapidly shifting toward online content in the digitalization era (Burger-Helmchen & Cohendet, 2011; Marchand & Hennig-Thurau, 2013), managing the interaction between large communities of users and the development of trade-in programs is becoming increasingly complex. More and more studies identify the need for government intervention in the process of publishers’ trade-in services. A series of recent studies highlight how government incentives affect consumers’ willingness to engage in trade-ins for remanufactured products or new products (Guo et al., 2022; Quan et al., 2021). Because consumers tend to perceive a loss in quality if they trade in old products for remanufactured ones (Ma et al., 2020), there is a need for publishers to offer consumers a rebate to encourage participation in trade-in programs. Therefore, governments subsidizing remanufactured products of gaming publishers can help alleviate their financial burden and provide them an incentive to offer remanufactured products at a lower retail price (e.g., Guo et al., 2022).

Viewing government intervention as an important channel to affect resource distribution, researchers also investigate that effective governance rules enable the creation of a pool of innovation resources (Cohendet et al., 2018; Lu et al., 2022; Wan & Yang, 2024). In addition, under the institutional perspective, the regulative intervention brought about by governments’ policymaking and regulatory control can directly shape companies’ decision-making and strategies for market competition (Hafezalkotob et al., 2023; Scott, 2014). The governments’ intervention actions, such as implementing take-back policies in the remanufacturing process, introducing state-operated systems, or proposing new legislation on recycling (e.g., Atasu et al., 2009; Cohendet et al., 2018; Ma et al., 2020), may change the virtual communities’ consumption behavior as well as the gaming publishers’ intention to make an effort in trade-in programs. Considering that the value of video game products relies heavily on the interaction between users (Burger-Helmchen & Cohendet, 2011), government intervention in the industry’s business model creates an external force that affects the remanufacturing rates and therefore the effectiveness of trade-ins.

In all, the distinctive market segments and complex involvement of virtual communities, publishers, and governments require a more holistic approach to examine the efficiency of trade-in practices in the video game industry. Although the literature has acknowledged the importance of consumer involvement in the business operations of gaming publishers (Marchand & Hennig-Thurau, 2013), limited attention has been paid to consumer participation in trade-in programs to purchase used physical console games. In addition, despite the numerous works on trade-in services and rebate rates (Quan et al., 2021; Sheu & Choi, 2019), our understanding of how digital publishers engage in the digital transformation of game sales to influence users’ purchasing decisions and participation in trade-in programs remains limited. Existing research highlights the challenges for digital publishers to estimate the dynamic demand for used video games considering potential physical depreciation (e.g., Ishihara & Ching, 2019), yet one significant gap in the literature is the lack of consideration of the interaction between consumers, publishers, and governments. Therefore, this study aims to address the literature gaps by exploring potential solutions for publishers to leverage the digital transformation of the gaming market and government legislation to affect consumers’ intentions to participate in trade-in programs and join the digital segment.

Based on the literature review, we summarize the hypotheses proposed in existing research, which also serve as the foundation for our study:

1. Digital transformation positively influences consumers’ digital preferences in the video game industry;

2. Trade-in strategies enhance consumers’ repeat purchasing behavior and help reduce production costs for publishers;

3. Government intervention can moderate the relationship between trade-in strategies and remanufacturing effectiveness.

Figure 1 presents the framework of our research, visually illustrating the relationships between the key variables we investigate: digital transformation, trade-in strategies, government intervention, and their effects on consumer behavior and publisher outcomes.

[See PDF for image]

Fig. 1

Research framework

Model setup

To develop a robust, systematic framework for understanding complex phenomena, particularly when analyzing large-scale trends and interactions among multiple variables, and to explore underlying dynamics that may not be easily observed through empirical methods alone, this section presents optimization models. These models investigate pricing and trade-in marketing strategies while considering the effects of digital transformation, sustainability on consumers, and government subsidies.

Problem description

We consider a system consisting of a single direct sales publisher and two consumer groups, namely digital-preferred and physical-preferred consumers, with heterogeneous preferences for digital and physical copies. Consumers own the old copies and can choose different trade-in marketing strategies: trade-in for a new physical copy (TON strategy), trade-in for a digital copy (TOD strategy), and retain the old copy (no trade-in strategy). According to the segmentation of consumer market, this paper investigates the influence of consumers’ behavior and government subsidies on the publisher’s optimal trade-in strategy, environment, consumer surplus, and social welfare. Table 1 provides a symbol summary of parameters and variables used in the research.

Table 1. Notation

Symbol	Definition
Model parameters
$v$	Consumer value to the new physical copies, and $v\sim U[0,1]$
$\delta$	The value discount rate of digital copies to the physical copies,$0<\delta <1$
$P_t$	The subside provided by the government to a trade-in copy
$\beta$	Proportion of digital-preferred consumers in the market, and $0\le \beta <1$
$\gamma$	The value discount rate of the old copy to the new copy,$0<\gamma <\delta$
$C_i$	Unit production cost of copy i, and $c_d<c_n$ ($c_d$ and $c_n$ denote the cost of digital and physical copy i, respectively)
$e_i^m$	Unit environmental impact of physical copy i in the production stage
$e_i^u$	Unit environmental impact of physical copy i in the disposal stages
Decision variables
$P_I$	The retail price of physical copy i
s	The degree of service effort of the publisher under the TOD strategy
Functions
$U_{\mathit{ij}}$	The utility of consumer j to retain old physical copy i
$D_i^k$	Demand for physical copy i under strategy k
${\pi }^k$	The profit of the publisher under strategy k
$E^k$	Environmental impact under strategy k
${\mathit{CS}}_j^k$	Consumer surplus of consumer j under strategy k
Wk	Social welfare under strategy k
Subscript	$i\in \mathrm{n},\mathrm{d},\mathrm{u}$ represents physical, digital, and old copies;$j\in \{G,P\}$ represents digital-preferred and physical-preferred consumers
Superscript	$k\in \{N,TON,TOD\}$ represents no trade-in, TON, and TOD strategy

Assumptions

Assumption 1. This paper normalizes the scale of consumers to one, among which the proportion of digital-preferred consumers is β, and $0\le \beta <1$.

Fast development of digital technologies provides an alternative for consumers in video game purchase. Digital-preferred consumers assume digital copies are homogenization as physical copies (Vernik et al., 2011). While primary consumers consider the value of the digital copies is less than the value of physical copies with a ratio of δ, and $0<\delta <1$, given that physical copies can provide long-term access for games. To ensure that the demand is positive, the price of digital copies should not be too high, i.e., $p_d<\delta p_n<p_n$.

Assumption 2. Under the “no trade-in” scenario, the utility perception of the consumers is assumed low, and the retention utility is trivial. Under the TON/TOD strategy, we define the utility of retaining old physical copies as $U_u=\gamma v$, and $0<\gamma <\delta$.

For the sake of tractability, we assume the retention utility is trivial and can be neglected under the “no trade-in” scenario mainly because the consumers cannot achieve extra benefits even though publishers provide different trade-in plans. We further apply a discounted value rate $\gamma$ for keeping the old physical copies under the TON/TOD plans aiming to describe the phenomenon that the utility of holding old physical copies is lower than buying new copies (both for physical and digital copies). This assumption can be justified practically and academically (Ma et al., 2017; Zhang & Zhang, 2018).

Assumption 3. Under the TON strategy, we assume that consumers can obtain subsidies $p_t$ from the government, which are exogenous (Ma et al., 2017). Under the TOD strategy, consumers also obtain $p_t$, but publishers need to pay extra service efforts s, with its cost as $\eta s^2/2$ (Feng et al., 2018).

We assume there exists extra service efforts under the TOD strategy. This assumption can be justified practically as applying digital copies normally needs help service and after-sale service to deal with issues such as installation package and identification. Further, to ensure and stimulate the publisher participating in the TON/TOD, we assume $p_t<p_n-p_d<p_t+s$; otherwise, the demand will be negative.

Assumption 4. The publisher determines the trade-in marketing strategies by optimizing the profit.

Similar to Xiao (2017) and Zhang and Zhang (2018), we assume the publisher can decide which trade-in strategy he would apply during a specific selling period. Assumption 4 confirms the leadership of the publisher which can be observed in practice as publishers usually conduct promotional activities including trade-in programs on special holidays to expand demand and establish brand reputation.

Assumption 5. In the production stage, the negative environmental impact of the physical copies is worse than the digital copies (i.e., $e_n^m>e_d^m$), whereas in the usage stage, the environmental impact of the physical and digital copies is the same (i.e., $e_n^u=e_d^u$).

Assumption 5 addresses the distinct environmental impact of the physical and digital copies in the production stage as physical games are normally traded via CDs consuming plastic and metal materials.

In term of the problem description and assumptions, the utilities of digital-preferred consumers for digital copies and new physical copies under “no trade-in” strategy are $U_{\mathit{nG}}=v-p_n$ and $U_{\mathit{dG}}=v-p_d$, respectively. According to $p_d<p_n$, we have $U_{\mathit{nG}}<U_{\mathit{dG}}$ which indicates that digital-preferred consumers do not intent to buy physical copies but consider to buy digital copies given the trade-offs between $U_{\mathit{dG}}$ and 0. The utilities of primary consumer for digital copies and new physical copies are $U_{\mathit{nP}}=v-p_n$ and $U_{\mathit{dP}}=\delta v-p_d$, respectively. By discussing the trade-offs between $U_{\mathit{nP}},U_{\mathit{dP}}$ and 0, demands of two products can be obtained. Similarly, utility and demand under TON and TOD strategies are shown in Table 2.

Table 2. Utility and demand under different strategies

Trade-in marking strategy	Utility and demand—physical copy	Utility and demand- digital copy
No trade-in	$U_{\mathit{nG}}=U_{\mathit{nP}}=v-p_n$; $D_n^N=(1-\beta )(1-\frac{p_n-p_d}{1-\delta })$	$U_{\mathit{dG}}=v-p_d,U_{\mathit{dP}}=\delta v-p_d$,; $D_d^N=\beta (1-p_d)+(1-\beta )\frac{\delta p_n-p_d}{\delta (1-\delta )}$
TON	$U_{\mathit{nG}}=U_{\mathit{nP}}=v-p_n+p_t$; $D_n^{\mathit{TON}}=\beta (1-\frac{p_n-p_t}{1-\gamma })+(1-\beta )(1-\frac{p_n-p_t-p_d}{1-\delta })$	$U_{\mathit{dG}}=v-p_d,U_{\mathit{dP}}=\delta v-p_d$ $D_d^{\mathit{TON}}=\beta (\frac{p_n-p_t-p_d}{1-\gamma })+(1-\beta )(\frac{p_n-p_t-p_d}{1-\delta }-\frac{p_d}{\delta -\gamma })$
TOD	$U_{\mathit{nG}}=U_{\mathit{nP}}=v-p_n$;	$U_{\mathit{rG}}=v-p_r+p_t+s,U_{\mathit{rP}}=\delta v-p_r+p_t+s$
	$D_n^{\mathit{TOD}}=(1-\beta )(1-\frac{p_n-p_d+p_t+s}{1-\delta })$	$D_d^{\mathit{TOD}}=\beta (1-\frac{p_d-p_t-s}{1-\gamma })+(1-\beta )(\frac{p_n-p_d+p_t+s}{1-\delta }-\frac{p_d-p_t-s}{\delta -\gamma })$

Note that the utility of keep using the old copies under trade-in marketing strategies is $U_u=\gamma v$

Based on the assumptions above, the profit function of publishers under “no trade-in,” TON and TOD strategies are as follows.

The publisher’s profit under the “no trade-in” strategy is

1

$${\pi }^N=(p_n-c_n)D_n^N+(p_d-c_d)D_d^N$$

In order to describe the role of the government by providing subsidies, we further introduce the consumer surplus (CS) and social welfare (SW) under the TON and TOD strategies. The publisher’s profit under the TON strategy is

2

$${\pi }^{\mathit{TON}}=(p_n-c_n)D_n^{\mathit{TON}}+(p_d-c_d)D_d^{\mathit{TON}}$$

Consumer surplus and social welfare are

3

$$C{S}_P^{\mathit{TON}}={\int }_{1-D_{\mathit{nP}}^{\mathit{TON}}-D_{\mathit{dP}}^{\mathit{TON}}}^{1-D_{\mathit{nP}}^{\mathit{TON}}}(\delta v-p_d)\mathrm{d}v+{\int }_{1-D_{\mathit{nP}}^{\mathit{TON}}}^1(v-p_n+p_t)\mathrm{d}v$$

4

$$C{S}_G^{\mathit{TON}}={\int }_{1-D_{\mathit{nG}}^{\mathit{TON}}-D_{\mathit{dG}}^{\mathit{TON}}}^{1-D_{\mathit{nG}}^{\mathit{TON}}}(v-p_d)\mathrm{d}v+{\int }_{1-D_{\mathit{nG}}^{\mathit{TON}}}^1(v-p_n+p_t)\mathrm{d}v$$

5

$$W^{\mathit{TON}}={\pi }^{\mathit{TON}}+(1-\beta )·C{S}_P^{\mathit{TON}}+\beta ·C{S}_G^{\mathit{TON}}-p_t·D_n^{\mathit{TON}}$$where $C{S}_P^{\mathit{TON}}$ and $C{S}_G^{\mathit{TON}}$ are consumer surplus of primary and digital-preferred consumers, respectively, and $p_t·D_n^{\mathit{TON}}$ is the subsidy provided by the government for consumers to participate in TON.

The publisher’s profit under the TOD strategy is

6

$${\pi }^{\mathit{TOD}}=(p_n-c_n)D_n^{\mathit{TOD}}+(p_d-c_d)D_d^{\mathit{TOD}}-\eta s^2/2$$where $\eta s^2/2$ is the cost of extra sales effort input by the publisher to stimulate consumers accepting TOD strategy in the presence of government subsidy $p_t$.

Therefore, the consumer surplus and social welfare under TOD scenario are

7

$$C{S}_P^{\mathit{TOD}}={\int }_{1-D_{\mathit{nP}}^{\mathit{TOD}}-D_{\mathit{dP}}^{\mathit{TOD}}}^{1-D_{\mathit{nP}}^{\mathit{TOD}}}(\delta v-p_d+p_t+s)\mathrm{d}v+{\int }_{1-D_{\mathit{nP}}^{\mathit{TOD}}}^1(v-p_n)\mathrm{d}v$$

8

$$C{S}_G^{\mathit{TOD}}={\int }_{1-D_{\mathit{dG}}^{\mathit{TOD}}}^1(v-p_d+p_t+s)\mathrm{d}v$$

9

$$W^{\mathit{TOD}}={\pi }^{\mathit{TOD}}+(1-\beta )·C{S}_P^{\mathit{TOD}}+\beta ·C{S}_G^{\mathit{TOD}}-p_t·D_d^{\mathit{TOD}}$$where $C{S}_P^{\mathit{TOD}}$ and $C{S}_G^{\mathit{TOD}}$ are consumer surplus of primary and digital-preferred consumers, respectively, and $p_t·D_d^{\mathit{TON}}$ is the subsidy provided by the government for consumers who participate in TOD.

To facilitate an understanding on the environmental impact of physical and digital copies in different operations, and by referring to Raz et al. (2013) and Zou et al. (2016), we assume the environmental impact is

10

$$E^k=D_n^k(e_n^m+e_n^u)+D_d^k(e_d^m+e_d^u),k\in \mathrm{N},\mathrm{TON},\mathrm{TOD}$$

Equilibrium analysis

In this section, we firstly discuss the equilibrium decisions of the publisher under three trade-in marketing strategies without the consideration of digital-preferred consumers (i.e., $\beta =0$), then the characteristic of the digital-preferred consumers (i.e., $0<\beta <1$) is addressed in the numerical studies. Finally, we investigate selection mechanisms of the publisher regarding three trade-in marketing strategies.

Scenario 1: No trade-in (N) marketing strategy

Under the “no trade-in” strategy, consumers have three options: buy a physical copy, buy a digital copy, or keep using the old copy. The equilibrium decisions under “no trade-in” strategy can be obtained as follows.

Proposition 1. Assume $\delta -(1-c_n)<c_d<\delta c_n$. The equilibrium decisions are$p_n^{N\ast }=(1+c_n)/2$and $p_d^{N\ast }=(c_d+\delta )/2$. On this basis, equilibrium demands and profits are $D_n^{N\ast },D_d^{N\ast }$, and $\pi _{}^{N\ast }$.

The proof is provided in Online Supplementary Material.

Note that the assumption of $\delta -(1-c_n)<c_d<\delta c_n$ ensures the non-negativity the existence and uniqueness of the optimal decisions. As the proportion of digital copies’ value relative to physical copies’ value increases, the publisher intents to increase the price of digital copies (i.e., $\partial p_d^{N\ast }/\partial \delta >0$). This result confirms the observation in practice that when identifying consumers’ higher acceptance of the digital copies, the main publisher would increase the selling price of digital copies to seek higher profits. Intriguingly, Proposition 1 also shows a counterintuitive result that when the proportion of digital copies’ value relative to new physical copies’ value reaches up to a certain threshold (i.e., $c_d/c_n<\delta <1$), the increase in digital copies’ price do not negatively affect the continually increase in publisher’s profit (i.e., $\partial \pi _{}^{N\ast }/\partial \delta >0$). A possible reason for this finding is that the positive effect brought by the general consumers’ acceptance of digital copies outweighs the negative effects of price increases, or the potential acceptance of the digital copies effectively promotes the demand, surpassing the decrease in demand caused by the price increase of digital copies.

Scenario 2: Trade-old-for-physical copy (TON) marketing strategy

Similar to Proposition 1, the equilibrium decisions under TON strategy can be obtained as follows.

Proposition 2. Assume $p_t+(1-\delta )/2<c_n<p_t+(1-\gamma )/2$ and $c_r<\min \{{\widehat{c}}_{r1},{\widehat{c}}_{r2}\}$. The equilibrium decisions are $p_n^{TON\ast }=(1-\gamma +c_n+p_t)/2$ and $p_r^{TON\ast }=(c_r+\delta -\gamma )/2$. On this basis, equilibrium demands and profits are $D_n^{TON\ast },D_r^{TON\ast },$ and $\pi _{}^{TON\ast }$.

Propositions 1 and 2 indicate that comparing with “no trade-in” strategy, the sales of physical copies and digital copies under the “trade-in” strategy have both increased (i.e., $D_n^{TON\ast }>D_n^{N\ast }$ and $D_r^{TON\ast }>D_r^{N\ast }$). This result explains the effect of the subsidy on demand. “Trade-in” strategies with subsidies can be attractive to consumers and thereby stimulate demand for physical copies which is obvious and can be easily observed in practice. However, counterintuitively, the “trade-in” strategy can also increase consumers’ demand for digital copies. Generally, there exists a certain degree of competition between physical and digital copies when there is no digital-preference, and subsidies for trade-in programs may intensify the competition between these two types of products. This means that while trade-in strategy promotes the demand for the physical copies, they should also suppress demand for digital copies owing to the characteristic of substitutability. The simultaneous increase may be because the increasing demand for physical copies promotes the volume of trade-in copies, indirectly stimulating the production of digital copies.

Scenario 3: Trade-old-for-digital copy (TOD) marketing strategy

Like Propositions 1 and 2, the equilibrium decisions under the TOD strategy can be obtained as follows.

Proposition 3. Assume ${\widehat{c}}_{d3}<c_d<\min \{\frac{(\delta -\gamma )c_n}{1-\gamma }+p_t,{\widehat{c}}_{d4}\}$ and $\widehat{\eta }<\eta <2\widehat{\eta }$. The equilibrium decisions are $p_n^{TOD\ast }=(1+c_n-\gamma )/2,s_{}^{TOD\ast }=\frac{(1-\gamma )(c_d-p_t)-(\delta -\gamma )c_n}{1-\gamma -2(\delta -\gamma )(1-\delta )\eta }$, and $p_d^{TOD\ast }=(s_{}^{TOD\ast }+c_d+p_t+\delta -\gamma )/2$. On the basis, equilibrium demands and profits are $D_n^{TOD\ast },D_d^{TOD\ast },$ and $\pi _{}^{TOD\ast }$.

Proposition 3 addresses that when there is no unit subsidy for all trade-in copies (i.e., $p_t=0$), publishers’ profit under the TOD strategy is lower than that under the TON strategy (i.e., $\pi _{}^{TOD\ast }<\pi _{}^{TON\ast }$). When offering unit subsidy for all trade-in copies (i.e., $p_t>0$), the profit of the publishers under different trade-in marketing strategies highly depends on the unit subsidy for different types of copies. Also, there might be one or two thresholds of the unit subsidy that can result in the TOD being the optimal strategy. The specific impact mechanism will be investigated and analyzed applying numerical examples in the next section.

Counterintuitively, Propositions 1 and 3 suggest that when the unit subsidy for trade-in copies is low (i.e., $p_t<{\widehat{p}}_t$), the sales of digital copies under the TOD strategy are increased (i.e., $D_d^{TOD\ast }>D_d^{N\ast }$). This is completely opposite to the effect of the unit subsidy on the sales of physical copies under the TON strategy. This result is possibly because the unit subsidy, together with the service efforts made by the publisher under the TOD strategy, jointly promotes the utility of consumers buying digital copies, stimulates consumer preferences, and ultimately incentivizes the growth of demand for digital copies. Numerical studies are needed to in-depth understand the changes in profit and strategy selection.

Similar to Propositions 1 to 3, Proposition 4 shows the equilibrium decisions under “no trade-in” strategy in the presence of digital-preferred consumers. Table 3 shows the equilibrium decisions with consideration of digital-preferred consumers.

Table 3. Equilibrium decisions under TON and TOD strategies with consideration of digital-preferred consumers

Trade-in strategy	The prices of new physical and digital copies/the level of service effort
TON	$p_{\mathit{ng}}^{TON\ast }=\frac{(2{\mathrm{X}}_1+2{\mathrm{X}}_2+{\mathrm{X}}_3){\mathrm{c}}_{\mathrm{n}}-(\mathrm{\beta }{\mathrm{X}}_1+{\mathrm{X}}_2){\mathrm{c}}_{\mathrm{d}}+(2{\mathrm{X}}_1+{\mathrm{X}}_2-{\mathrm{X}}_3){\mathrm{p}}_{\mathrm{t}}-2(1-\mathrm{\gamma })({\mathrm{X}}_1+{\mathrm{X}}_2/\mathrm{\beta })}{4{\mathrm{X}}_1+3{\mathrm{X}}_2},$ $p_{\mathit{dg}}^{TON\ast }=\frac{\left({2X}_1,+,X_2,-,X_3\right)C_d+X_4\left(\delta ,-,\gamma \right)\beta \left(p_t,-,c_n\right)+\left(\delta ,-,\gamma \right)\left[\left(1,-,\gamma \right),X_4\right]}{{4X}_1+{3X}_2}$
TOD	$p_{\mathit{ng}}^{TOD\ast }=\frac{Y_3{c}_n+{(1-\gamma )}^2-\beta {(1-\delta )}^2}{2Y_3},$ $p_{\mathit{dg}}^{TOD\ast }=\frac{2(Y_1+Y_2)Y_3{c}_d+(1-\gamma )(\delta -\gamma )\left\{[(1-\beta )c_n+2(1-\delta )\eta p_t],Y_3,+,[Y_1+2Y_2+\beta (1-\delta )Y_3]\right\}}{2Y_3(Y_1+2Y_2)},$ $s_g^{TOD\ast }=\frac{Y_1(c_d-p_t)+(1-\gamma )(\delta -\gamma )[(1-\beta )c_n+\beta (1-\delta )]}{Y_1+2Y_2}.$

Proposition 4. Assume $\delta -(1-c_n)<c_r<\frac{[(1-\beta )c_n+(1-\delta )\beta ]\delta }{1-\beta (1-\delta +{\delta }^2)}$. The equilibrium decisions are $p_{\mathit{ng}}^{N\ast }=\frac{1+[1-\beta (1-\delta )]c_n-\beta {(1-\delta )}^2}{2[1-\beta (1-\delta )]}$ and $p_{\mathit{dg}}^{N\ast }=\frac{[1-\beta (1-\delta )]c_d+\delta }{2[1-\beta (1-\delta )]}$. On the basis, equilibrium demands and profits are $D_{\mathit{ng}}^{N\ast },D_{\mathit{dg}}^{N\ast },$ and $\pi _g^{N\ast }$.

Based on Propositions 1 and 4, the comparison of publisher’s decisions and profits under “no trade-in” strategy is obtained, as shown in Lemmas 1 and 2.

Lemma 1. Under the no trade-in strategy, we have $p_{\mathit{ng}}^{N\ast }>p_n^{N\ast },p_{\mathit{dg}}^{N\ast }>p_n^{N\ast },\partial p_{\mathit{ng}}^{N\ast }/\partial \beta >0,$ and $\partial p_{\mathit{dg}}^{N\ast }/\partial \beta >0$.

Lemma 1 shows that under the “no trade-in” strategy, when there are digital-preferred consumers in the console game market, both the prices of the physical and digital copies will increase (i.e., $p_{\mathit{ng}}^{N\ast }>p_n^{N\ast }$ and $p_{\mathit{dg}}^{N\ast }>p_n^{N\ast }$), which is a counterintuitive finding. Usually, when the publisher identifies that the digital-preferred consumers can obtain higher utility from digital copies than physical copies, to meet the needs of all consumers and promote demand, the publisher typically increases the price of physical copies and decreases the price of digital copies. However, Lemma 1 suggests that the publisher can also achieve his objective by simultaneously raising the prices of both physical and digital copies (i.e., $\partial D_{\mathit{ng}}^{N\ast }/\partial \beta <0$ and $\partial D_{\mathit{rg}}^{N\ast }/\partial \beta >0$). Additionally, with an increase in the proportion of digital-preferred consumers, prices for physical and digital copies also increase accordingly (i.e., $\partial p_{\mathit{ng}}^{N\ast }/\partial \beta >0$ and $\partial p_{\mathit{dg}}^{N\ast }/\partial \beta >0$), indicating a significant influence of digital-preferred consumers on product prices.

where $X_1=\left(1,-,\beta \right){\left(1,-,\gamma \right)}^2,X_2={\beta }^2\left(1,-,\delta \right)\left(\delta ,-,\gamma \right),X_3=\beta \left(1,-,\beta \right)\left(1,-,\gamma \right)\left(\delta ,-,\gamma \right),$ and $X_4=\beta (\delta -\gamma )-(1-\gamma );Y_1=\beta \left[1,+,{\gamma }^2,-,\delta ,\left(1,-,\delta \right),-,\gamma ,\left(1,+,\delta \right)\right]-{\left(1,-,\gamma \right)}^2,Y_2=\left(1,-,\gamma \right)\left(1,-,\delta \right)\left(\delta ,-,\gamma \right)\eta ,$ and $Y_3=1-\gamma -\beta (1-\delta )$

According to the analysis above, we identify that when there are no trade-in marketing strategies, publishers need to thoroughly investigate the number or proportion of digital-preferred consumers in the market which can be supportive information to reasonably increase the prices.

Lemma 2. Under the no trade-in strategy, if $c_n\le {\widehat{c}}_{n1}$, or$c_n\ge {\widehat{c}}_{n2}$with $c_d<\delta$, the publisher obtain the highest profit when $\beta =0$; if ${\widehat{c}}_{n1}<c_n\le {\widehat{c}}_{n3}$ or ${\widehat{c}}_{n4}\le c_n<{\widehat{c}}_{n2}$, there exists a threshold $\widehat{\beta }$ to minimize the publisher’s profit and the highest profit is $max\left\{\pi _g^{N\ast },\left|_{\beta =0}^{},,,\pi _g^{N\ast }\right|,_{\beta =1}^{}\right\}$; otherwise, $\pi _g^{N\ast }\left|_{\beta =1}^{}\right)$ is the highest profit.

Under the “no trade-in” strategy, the publisher’s strategic choices primarily depend on the production cost of physical copies (i.e., $c_n$). However, regardless of how the production cost of physical copies changes, the maximum profit for the publisher can only be $\pi _g^{N\ast }\left|_{\beta =0}^{}\right)$ or $\pi _g^{N\ast }\left|_{\beta =1}^{}\right)$. Particularly, only when the production cost of physical copies falls within a certain range (i.e., ${\widehat{c}}_{n3}<c_n<{\widehat{c}}_{n4}$), do more digital-preferred consumers contribute to a greater profit for the publisher. In this scenario, the publisher neither partially abandons the profit from physical copies due to excessively high production costs, nor chooses not to produce digital copies due to excessively low production costs, thus avoiding loss of profit from digital copies.

Numerical studies considering digital-preferred consumers

We conduct several numerical studies to complement the aforementioned analysis which did not consider the effect of digital-preferred consumers (i.e., $\beta =0$) and to illustrate how the digital preference (i.e., $0<\beta <1$) affect the publishers’ optimal strategy.

Further, to improve the robustness and reliability of numerical studies, we conduct several experiments in multiple trials according to our assumptions and select the best default value of parameters to show the trade-offs under different trade-in marketing strategies. The default values are $p_t=0.14,c_n=0.32,c_d=0.26,$$\eta =1.2,\gamma =0.45,\delta =0.55,e_n^m=0.4,$$e_d^m=0.2,e_n^u=e_d^u=0.1,\beta \in [0,0.7]$. Figures 2, 3, 4, 5, and 6 show the impact of the proportion of digital-preferred consumers on the publisher’s trade-in strategy selection, environment, consumer surplus, and social welfare.

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Fig. 2

The impact of digital-preferred consumers’ proportion and value discount rate of digital copies

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Fig. 3

The impact of the proportion of digital-preferred consumers and the discount rate for retained physical copies

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Fig. 4

The impact of value discount rates of digital copies and retained old copies on trade-in strategy under different proportions of digital-preferred consumers

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Fig. 5

The impact of digital-preferred consumers’ proportion and the value discount rate of retained old copies on the environment

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Fig. 6

The impact of the proportion of green consumers and the value discount rate of retained old products on consumer surplus and social welfare

Figure 2 shows that when the proportion of digital-preferred consumers and the value discount rate of digital copies are both relatively low (i.e., Region C), publisher chooses the TOD strategy, which is counterintuitive. Generally, considering that digital-preferred consumers only purchase digital copies, a smaller proportion of digital-preferred consumers indicates less popularity for digital copies. Meanwhile, the value discount rate of digital copies reflects the consumer acceptance of them, the lower the discount rate; the lower the relative value of digital copies to consumers. In this scenario, to cater to consumer purchasing preferences, publishers should introduce the “no trade-in” or TON strategies instead of adopting the TOD strategy.

The possible underlying economic driver for the above result is that, in the context of consumer preferences for physical copies, even if the publisher adopts the TOD strategy, the main profits come from physical copies. On one hand, trade-in subsidies play a significant role as consumers prefer the trade-in strategy due to government subsidies, rather than preferring “no trade-in.” On the other hand, considering that primary consumers prefer physical copies, and the adoption of the TON strategy by publisher does not significantly increase the demand for physical copies, choosing the TOD strategy still allows publishers to obtain partial profits from digital copies. Therefore, choosing the TOD strategy ensures that the demand for physical copies is not significantly affected while also obtaining more profits from digital copies.

However, when there is a significant inconsistency between the proportion of digital-preferred consumers and the value discount rate of digital copies (i.e., Region A), consumers exhibit significant preference differences for distinct products. In this scenario, although trade-in marketing strategies may vary in promoting demand for certain products, there is not much change in overall profit, and publishers will choose the “no trade-in” strategy. The boundary lines between Region A and Region B also confirm the above findings, indicating that as the proportion of digital-preferred consumers decreases and the value discount rate of digital copies increases, publishers prefer the “no trade-in” strategy over the TON/TOD strategies. In reality, when the characteristics of digital-preferred consumer behavior are not obviously observed, the “no trade-in” strategy is more attractive to publishers than the TON/TOD strategies. In this case, instead of focusing on trade-in marketing strategies, it might be better for the publishers to concentrate on technological inputs to pursue cost savings in production.

Figure 3 shows that when the proportion of digital-preferred consumers exceeds a certain threshold (i.e., $\beta >0.3$), publishers choose the “no trade-in” strategy (i.e., Region A). Generally, the more digital-preferred consumers there are in the market, the more beneficial it is for the publisher. However, the counterintuitive conclusion here potentially indicates that in the current scenario where government trade-in subsidies are provided to consumers, the presence of more digital consumers disadvantages publishers in choosing trade-in marketing strategies. Once they opt for trade-in marketing strategies, publishers either lose a significant amount of profit from digital copies or incur additional costs to obtain profits from digital copies through trade-in efforts. However, when the proportion of digital-preferred consumers is low (i.e., Regions B and C), publishers’ choice of TON/TOD strategy is mainly influenced by the value discount rate of retaining old copies. Specifically, when the value discount rate of retaining old copies is low, the difference between the value of retaining old copies and purchasing new copies is significant. In addition, when observing that consumers are sensitive to the TON strategy, publishers will choose this strategy to meet consumer demand and obtain sufficient profit from physical copies, which is also in line with practical considerations.

Considering that it is not meaningful to discuss the choice of the “no trade-in” strategy when the proportion of digital-preferred consumers exceeds a certain threshold in Fig. 3 (i.e., $\beta >0.3$), we only discuss the scenarios that $\beta =0$ and $\beta =0.2$. Figure 4a, b reveals that the impact of the value discount rate of digital copies and the value discount rate of retaining old physical copies on trade-in marketing strategies depends on the difference between these two value discount rates. When this difference is large (i.e., Region B), publishers choose the TON strategy; conversely, they choose the TOD strategy. This is because when the value discount rate of digital copies is much higher than the value discount rate of retaining old physical copies, more consumers tend to make trade-offs between purchasing new physical copies and digital copies rather than keeping old copies. Therefore, both TON and TOD strategies effectively attract consumers to purchase copies.

The superiority of these two trade-in marketing strategies mainly depends on the cost of trade-in and the marginal profit of different copies. With this concern, when the value discount rate of digital copies is high, theoretically, publishers should prefer the TOD strategy to cater to consumer preferences and promote demand. However, counterintuitively, they still choose the TON strategy. As mentioned in the analysis of Fig. 2, when consumers prefer digital copies, choosing the TOD strategy does not significantly increase the demand for digital copies. On the other hand, opting for the TON strategy not only saves the cost of trade-in efforts but also does not lead to a significant decrease in the demand for digital copies. Moreover, it allows publishers to obtain more profit from new copies, achieving a “win–win” situation where both types of copies are profitable.

As stated in introduction section and justified in our model description, the environmental impact of producing physical copies outweighs that of digital copies, and the environmental impact of the production stage is greater than that of the usage stage (i.e., $e_n^m>e_d^m>e_n^u=e_d^u$). Therefore, when the demand for digital copies increases, the environmental impact decreases. This explains why there is no scenario of TOD strategy in Fig. 5. Conversely, when the demand for physical copies increases, the environmental impact in increases. Specifically, when the value discount rate of retaining old physical copies is lower (i.e., Region B1 in Fig. 5), consumers retain fewer old copies and opt for trading them in for new physical copies more frequently; thus, the TON strategy has a greater negative environmental impact in this situation. When the proportion of digital-preferred consumers and the value discount rate of retaining old physical copies are both high (i.e., Region B2 in Fig. 5), digital-preferred consumers refrain from purchasing new copies, and the willingness of ordinary consumers to trade in for new copies is also low. At this point, the environmental impact mainly stems from digital copies. Other than above scenarios, the “no trade-in” strategy has a greater negative environmental impact.

Figure 6a shows that when the proportion of digital-preferred consumers is relatively high and the value discount rate of retaining old physical copies is large or small (i.e., Regions B1 and B2 in Fig. 6a), the consumer surplus under the TON strategy is greater than that under the TOD strategy; otherwise, the consumer surplus under the TOD strategy is greater (i.e., Region C in Fig. 6a). This is because when the value discount rate of retaining old physical copies is smaller, more consumers are willing to exchange their old copies for new ones, leading to an increase in demand for new physical copies. Although this also increases the subsidies paid by the government, the increase in consumer surplus is more significant. Thus, in this scenario, the TON strategy leads to higher social welfare (i.e., Region B in Fig. 6b). However, when the value discount rate of retaining old physical copies is large (i.e., Region B2 in Fig. 6a), although the consumers’ utility for trading in new physical copies is high, the demand for new copies decreases, resulting in publishers being unable to obtain higher profits, and ultimately choosing the TOD strategy. Unlike consumer surplus, social welfare is more influenced by publishers’ profits and subsidies provided by the government. Generally, consumer surplus depends on the proportion of digital-preferred consumers, consumer utility, and demand under different trade-in marketing strategies. As for social welfare, it is only significant under conditions where the consumer surplus is large, and a certain level of demand can be ensured.

Some governments have implemented subsidy policies to promote the selling of digital copies and for TON programs. However, once these policies end, demand for digital copies and TON trades sharply declines. Therefore, as a government, on one hand, it is necessary to encourage companies to participate in digital transformation and consumers to participate in trade-in programs by providing subsidies. On the other hand, it is essential to establish an evaluation and supervision mechanism to prevent subsidy fraud, which can weaken the effectiveness of subsidy policies and maximize social welfare.

Figure 7 demonstrates the impact of value discount rates of digital copies and retained old physical copies on social welfare under varying proportions of digital-preferred consumers. Figure 7 indicates that when the value discount rate of retained old copies is low or value discount rates of digital copies is high, the TON strategy (TONB regions) leads to higher social welfare, as consumers are more willing to trade in old copies for new ones, increasing demand for new physical copies and boosting consumer surplus. Conversely, when the value discount rate of retained old copies is high or value discount rates of digital copies is high, the TOD strategy (TODC regions) becomes more favorable, as consumers derive greater utility from keeping their old copies, reducing demand for new physical copies. As the proportion of digital-preferred consumers increases from 0.7 to 0.9, the TODC regions narrow, indicating that the TON strategy becomes more dominant in achieving higher social welfare. Social welfare is influenced by a combination of consumer surplus, publishers’ profits, and government subsidies, with the TON strategy excelling when consumer surplus and demand for new physical copies are strong, and the TOD strategy being more effective when digital preferences dominate and the value of retaining old copies is high.

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Fig. 7

The impact of value discount rates of digital copies and retained old copies on social welfare under different proportions of digital-preferred consumers

Conclusions

This study examines the dynamics of a console game supply chain involving a dominant direct-selling publisher and two consumer segments, with a focus on the impact of digital transformation and trade-in strategies. By analyzing pricing decisions and profits under the “no trade-in” (NT), trade-in for new physical copies (TON), and trade-in for digital copies (TOD) strategies, we provide valuable insights for publishers, consumers, and policymakers. The main findings and contributions of this research are as follows.

1. Publisher strategies and profitability

When digital-preferred consumers are not observable, publishers can enhance profitability by increasing the acceptance of digital copies and investing in after-sale services for ordinary consumers. Under the TOD strategy, after-sale service efforts have a more significant impact on demand promotion than trade-in subsidies. However, when facing a high proportion of digital-preferred consumers, if government subsidies are low or require additional service efforts, counterintuitively, the publisher may consider abandoning the TON or TOD strategies. Counterintuitively, in the absence of subsidies, the TOD strategy always yields lower profits than the TON strategy, and the publisher’s preference is always for TON in digitally inclined markets. To effectively implement the TOD strategy, publishers should collaborate with the government to secure higher subsidies while simultaneously investing in advertising and high-quality after-sale services. Conversely, publishers focused on physical copies may not need to prioritize government subsidies.

1. Digital transformation and consumer preferences

The emergence of digital-preferred consumers necessitates strategic caution. When the proportion of digital-preferred consumers is high and government subsidies are insufficient, publishers may opt for the NT strategy. Conversely, when digital-preferred consumers are fewer, publishers should adopt trade-in strategies that contrast with consumer preferences. For instance, if consumers prefer digital copies, the TON strategy is optimal, as it ensures profitability for both digital and physical copies. This approach leverages the resolute purchasing behavior of digital-preferred consumers, minimizing the impact of the value discount rate of digital copies.

1. Environmental and social implications

The TOD strategy has the least environmental impact, while the NT and TON strategies’ environmental effects depend on the quantity of physical copies sold. From a societal perspective, the TOD strategy enhances consumer surplus and social welfare when the proportion of digital-preferred consumers is high and the value discount rate of retaining old physical copies is either extremely large or small. For governments, providing subsidies to encourage digital transformation can simultaneously boost consumer surplus and publisher profits, fostering a win–win scenario.

This study contributes to the literature by providing a comprehensive framework for understanding the interplay between digital transformation, trade-in strategies, and government intervention in the console game industry. The findings offer actionable insights for publishers to optimize their strategies, for consumers to benefit from improved services and pricing, and for governments to design effective subsidy policies that promote sustainability and digital transformation.

By addressing these critical aspects, this research not only advances academic understanding but also provides practical guidance for industry stakeholders navigating the evolving landscape of digital gaming.

Limitations and directions for further research

This study has several limitations that provide valuable opportunities for future research to extend and refine our findings. First, while we examine the impact of two consumer segments on gaming publishers’ pricing decisions and strategies, future studies could incorporate a broader range of consumer characteristics that may influence these outcomes. Factors such as gender, age, religious beliefs, educational background, and work experience (e.g., Kolyesnikova et al., 2009; Mathras et al., 2016) could significantly alter the dynamics of consumer behavior and, consequently, publishers’ strategic decisions. For example, do male consumers show different preferences in purchasing digital games than female consumers, and will this change the publisher’s decision-making on their trade-in marketing strategies? Will brand awareness of consumers or different levels of consumer characteristics change the publishers’ pricing decisions under different strategy scenarios? We suggest future studies investigate the complexity of the consumer segments to further advance our understanding of publishers’ decisions.

Moreover, in our modeling, we viewed the publishers in the video game industry as a whole without considering the heterogeneity among the publishers. This oversight may limit the generalizability of our findings, as previous studies suggest that micro, small, and medium-sized firms tend to show different propensities for strategic change and innovation compared to large firms (Radicic & Petković, 2023). The different positions of firms in global value chains can also influence the impact of digitalization on their strategies (Huang & Zhang, 2023). Additionally, publishers with internal R&D centers may experience a different influence from digitalization on their strategic decisions. Thus, we suggest that future studies examine the trade-in practices of different types of publishers. For example, what is the impact of heterogeneous resources and capabilities of publishers on their decision to implement trade-in strategies? Will larger publishers, or those with stronger innovation capacities, pay more attention to recycling? How does the governance structure of gaming publishers affect their pricing decisions in trade-in programs?

Finally, even though we considered how government subsidies foster the digital transformation of gaming publishers and consumers’ incentives to participate in trade-in, it is important for future research to consider other forms of government intervention, such as changes in policies (Zaremba et al., 2020), shareholding by government agencies (Bradshaw et al., 2019), or resource provision and technical partnerships (Broto & Bulkeley, 2013). Additionally, broader policy tools, such as regulatory incentives or tax breaks, could further enrich the analysis. Some future research questions could be: how can government agencies implement new policies on digitalization to foster the gaming publishers improving their trade-in services? Can gaming publishers cooperate with institutions at different levels to reshape consumers’ intentions to recycle? Will shareholding by government agencies change the effectiveness of gaming publishers’ trade-in programs? Future studies on this topic can use multiple research methods to quantify the influence of government intervention on consumer surplus and publishers’ profits.

Acknowledgements

This research was supported in part by the National Natural Science Foundation of China (No. 72202110) and the National Social Science Key Project (No. 24AGL006).

Data Availability

No data was used for the research described in this article.

Markus Bick

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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