Towards sustainable business models with a novel life cycle assessment method

Business model (BM) innovation for sustainability is hampered by a lack of tools for environmental assessment and guidance at the BM level. Conventional life cycle assessment (LCA) neglects the economic and socio-technical mechanisms within a BM, and tools based on the BM canvas (BMC) cannot provide recommendations sub-stantiated by environmental data. Here, a new method, BM-LCA, is applied to a case comparing the selling and renting of jackets, using profit as basis of comparison. Results identify how business parameters influence environmental performance, permitting analysis for decoupling within a business practice. This is made possible by the unique way the method links physical life cycle and the monetary flows of a BM. Usefulness of BM-LCA is discussed relative to BM innovation, business strategy and similar tools. BM-LCA provides insights into a broad range of BM elements and emerges as useful for business strategy. By measuring BM environmental performance, it helps determine what BM to compete with and support critical analysis of business against greenwashing. BM-LCA also enables identification of BM elements in greatest need of environmental innovation. BM-LCA appears as a promising tool for guiding business companies towards sustainability, filling a space between LCA and BMC. The method offers a practical way for business and LCA experts to merge their respective knowledge.

will do so in a way that contributes positively to the environment and society (Pieroni et al., 2019).
Several BMs for sustainability have been proposed; two types are circular BMs (CBMs) and product service systems (PSS) (Linder & Williander, 2017;Tukker & Tischner, 2006). Although these are recognised as promising sustainability solutions (Bocken et al., 2019;Kerdlap et al., 2021;Martin et al., 2021;Tukker, 2015), it is not guaranteed they lead to reduced environmental impacts. In their reviews of assessment studies of such BMs, Blüher et al. (2020) and van Loon et al. (2021) found that while they seem to reduce certain types of environmental impact (e.g., the use of natural resources or climate change), the overall evidence is still weak due to a lack of quantitative assessment (Nosratabadi et al., 2019). Blüher et al. (2020) also identified methodological challenges for sustainability assessment of PSS from a lack of systematic and standardised assessment approaches.
In the absence of robust quantitative methods for BM innovation for sustainability, a multitude of qualitative tools have been developed. However, few of these meet the needs and expectations of companies (Rossi et al., 2016). Prominent examples include the BM canvas (BMC) developed by Osterwalder and Pigneur (2010) and its derived tools such as the circular BMC (Nussholz, 2018) and the triple-layered BMC (Joyce & Paquin, 2016). These enable companies to represent elements of a BM visually and systemically, thereby facilitating discussion of potential innovations at the BM level (Joyce & Paquin, 2016). However, these BMC tools only provide qualitative information and base their recommendations on rules of thumb (Pieroni et al., 2019). Quantitative tools are needed to test their efficacy. In response, many call for tools that can evaluate the environmental performance of BMs (e.g., Bocken et al., 2021;de Giacomo & Bleischwitz, 2020;Schaltegger et al., 2016).
Life cycle assessment (LCA) is a well-established tool for the environmental evaluation of product or processes. However, in its current form, it is not well suited to assess BMs since it does not take into account the socio-technical mechanisms implied by BMs, such as economic interactions between the company and its value chain (Costa et al., 2019).
A novel form of LCA, BM-LCA, has been developed to address the lack of a systematic environmental assessment approach for BMs.
Its purpose is the assessment and comparison of the environmental performance of BMs. Thus, companies seeking to enhance sustainability could find BM-LCA useful for design and innovation of more sustainable BMs based on quantitative environmental results and evidence. The methodology of BM-LCA is presented in a separate article .
The aim of this paper is to present a study in which BM-LCA was applied in an environmental comparison of two different BMs of a real company. Although BM-LCA methodology is here applied to a single comparative case, the study indicates the usefulness of BM-LCA more generally. Therefore, an additional aim is to provide an analysis and discussion of the ways in which BM-LCA may contribute to sustainable BM transformation.

| METHOD
To demonstrate the application and usefulness of BM-LCA, the method was applied in a comparative case study in a real company.
The findings were analysed relative to a framework for BM innovation and further discussed to evaluate the usefulness of BM-LCA for business companies. The discussion develops understanding on BM-LCA by drawing on relevant literatures on life cycle methodologies, BM innovation and business strategy.

| The case study
The comparative case study was conducted for a Swedish apparel company with high sustainability aims. In addition to eco-design of products and incentivising product recycling and reuse, the company is also taking action at the BM level to improve their environmental performance. The study uses BM-LCA to compare the company's current sales BM for one of its staple products with a contemplated rental BM. The goal is to critically investigate the expectation that sustainable BM innovations lead to improved environmental performance.
In the apparel sector, there have been several attempts to develop innovative BMs oriented towards sustainability, including rental and sharing systems (Adam et al., 2017;Camacho-Otero et al., 2019;Day et al., 2020;Lang & Armstrong, 2018). The few LCA studies of these models indicate that they contribute to an overall reduction in environmental impacts (Bech et al., 2019;Piontek et al., 2020;Roos et al., 2015;Zamani et al., 2017). These studies provide a basis of comparison between previous LCA and the new BM-LCA findings and can be used to observe whether the latter can provide new valuable information.

| The BM-LCA method
The BM-LCA method, presented in Böckin et al. (2022), aims to assess and compare the environmental impacts of (at least) two BMs. The BMs themselves are taken as the object of analysis, and their economic performance is taken as the basis of comparison, since the purpose of a BM is to make money . In LCA terms, this means using an economic indicator as a functional unit (the unit of comparison in LCA), such as profit or rate of return, instead of product functionality as in conventional LCA .
In more detail, BM-LCA expands conventional LCA methodology by elaborating the goal and scope stage, dividing it into two phases: 'descriptive' and 'coupling'. In the 'descriptive' phase, the key features of each compared BM are described. In particular, the types of customer transactions involved in each BM are specified (e.g., whether product ownership is retained or transferred to customers) and how product stocks (if any) are maintained. Any products associated with the BMs are also defined and described in terms of their function, lifetime, weight, material composition and other relevant characteristics. In the 'coupling' phase, a functional unit is defined and quantified based on a stated level of economic performance. Subsequently, so-called coupling equations are set up. These connect the physical flows to the monetary flows related to the economic performance level defined in the functional unit. The equations are solved to find the number of customer transactions and the required production. This procedure is repeated for each BM compared.
Subsequently, mainstream LCA methodology is applied, starting with life cycle inventory (LCI) analysis. This entails the collection of data and the creation of an inventory of environmentally relevant flows scaled to the functional unit. In the subsequent life cycle impact assessment (LCIA) phase, the quantified flows are aggregated into scores indicating the potential environmental impact in different categories. All potential impacts can also be aggregated into a single score by weighting the different types of impact according to their perceived relevance (Pizzol et al., 2017). Different weighting methods emphasising different aspects of the LCI (Hauschild & Potting, 2005) can be used to filter the results and identify key indicators to be analysed in depth (Tillman et al., 1998).
Lastly, the results are analysed and interpreted in order to provide useful insights and recommendations to the company.

| Framework for BM innovation
To describe the usefulness of the BM-LCA method, the findings of the BM-LCA study are analysed using Sommer's (2012) analytical framework for BM transformation. This framework was chosen because of its comprehensive and systemic representation of the elements related to BM innovation. It can thus be used to analyse the business logic of a company seeking to manage its BM innovation for sustainability. In the present case, it is used to identify the elements of a BM to which BM-LCA provides input. The framework is a synthesis of the work of Osterwalder (2004), Osterwalder and Pigneur (2010), Johnson et al. (2008), Johnson and Lafley (2010) and Sommer (2012).
On a conceptual level, the BM can be disaggregated into five interconnected components, illustrated in Figure 1.
The first component is the value proposition, which represents the functionality of the offered products or services and their competitiveness in terms of price or value compared to existing alternatives in the market.
The second component is the target groups, that is, the company's potential customer segments, the relationships between the company and the customer, and the channels through which value is delivered.
The third component is key resources, that is, all the assets owned or controlled by the company, including properties, equipment, employees and their skills and acquired knowledge, and partnerships with external partners.
Key resources are managed via the fourth component, namely, key processes that include primary activities (e.g., inbound and outbound logistics and operations), support activities (e.g., procurement, technology development and human resource management) and steering mechanisms that represent means of influencing the business practices or the decision-making process.
The fifth and last component, financial logic, includes financial considerations such as revenue streams, pricing methods and cost structure.
The BM unit and its components are also connected with the external business environment, which affects them and is, in turn, influenced by them.

| THE BM-LCA STUDY
This section describes the BM-LCA study assessing the environmental impacts of two BMs, renting and selling.

| Goal and scope: Descriptive phase
The objective of the assessment was to compare the company's sales BM with a rental BM for polyester jackets by answering the following specific questions: The sales model assumes that every garment produced is sold to a customer at an established price. Consequently, the number of transactions during a certain period equals the number of garments that need to be produced. The company also offers customers a free repair service.
In the rental model, the company retains ownership of the garments while customers pay a price to access them 1 day at a time.
The company maintains the garments, including laundering them between customers and repairs. When garments are deemed too worn after repeated rentals, they are sold second-hand at a reduced price.
In both BMs, the company accepts old jackets returned by customers for recycling.

| The product system
The jacket investigated is made of polyester and has the same design in both BMs. It is composed of (i) an outer face fabric (with a fluorocarbon-free water repellent), (ii) an interior backing fabric, and   were divided into input-based revenues, generated when customers take ownership of a product, and usage-based revenues, generated when customers access or use a product. The main technical processes in the system are briefly described in Table 2.

| Data collection methods and sources
Regarding data quality for the product specifications, the use phase and the BM set-ups, the goal was to represent the real situation of the case company as closely as possible. Hence, specific data were gathered from the company via personal communication. These data were based either on empirical observations or on estimations, both for the economic and environmental modelling. LCA databases and relevant sources from literature were used for the rest of the life cycle. These data were complemented by using online tools (e.g., Google Maps and marine cargo rates) and personal communication with experts (including a researcher on chemical polyester recycling and a specialist employee at a repair shop). Table 3 summarises the data sources used for each process of the system. For details on all processes and sources for all data, see the full LCI in Appendix S1.

| Impact categories for the environmental assessment
The impact categories recommended by the International Reference Life Cycle Data System (ILCD) (Hauschild & Huijbregts, 2015) were used to assess the environmental performance of the sales and rental BMs. In order to identify the most important type of impact, a filtering process was applied based on two separate weighting methods that emphasise different aspects of the LCI. The most important types of impact were identified and used for dominance analysis.
One of the weighting methods used was the endpoint ReCiPe  (Frischknecht & Büsser Knöpfel, 2013), where the weighting is based on the distance to politically or scientifically defined environmental targets (Hauschild et al., 2018).

| Goal and scope: Coupling phase
In the coupling phase, the relationships between monetary and material flows were modelled and expressed through a number of coupling equations. These, together with the functional unit, are used to derive achieving a certain level of profitability for each BM. The first step was to define a profit-based functional unit, defined as 'a certain amount of profit, π, over a business period of 30 days, from transactions involving the studied jackets'. To achieve this, the money flows and other economic parameters were defined and calculated or estimated. The adopted cost structure for both BMs is presented in Table 4.
The numerical economic data are summarised in Table 5. Notable parameters include the 'rental efficiency' (E r ), which describes the share of garments in the rental stock rented by customers at any given time. It depends on the time required for maintenance activities and the overcapacity of the stock needed to meet fluctuating demand.
Another key parameter is the rental lifetime (RL), which is how many use days a jacket can provide before being worn out and removed from the rental stock. The removed jackets are sold second-hand at The socio-technical product system for jackets, representing a sales business model (left) and a rental business model (right). Arrows represent material flows and colours represent different actors. Costs and revenues for the case company are indicated by red and green text, respectively. Some costs or revenues are associated with running a process like the warehouse, others stem from the exchange of material to/from another actor. In the latter case, they are indicated next to the corresponding material flows [Colour figure can be viewed at wileyonlinelibrary.com] 60% of the original price, and the rental stock is replenished by adding a newly produced jacket.
In the study, the functional unit was defined as the monthly profit from the jackets. The functional unit was quantified based on the collected economic data for the sales model, together with the monthly sales volume, estimated at 200 transactions per month (t s = 200 transactions). As shown in Table 6, the monthly profit, π s , amounts to 319,391 SEK. This translates to a physical flow of 200 jackets per month, since, in the linear model, the number of sold jackets equals the required production (q s = 200 jackets).
Stipulating the same profit for the rental BM allows calculation of the required number of rental transactions (t r ) and thus the number of jackets produced (q r ) in the rental model. Considering that revenues minus costs should add up to the profit, π r , the following equation can be set up: Some costs and revenues depend directly on the transactions, t r , while the rest depends on the number of jackets produced (q r ), or the number of stores (N r ). However, each revenue and cost can be expressed in terms of the rental transactions, t r , by expressing the relations between t r , q r and N r by means of a coupling factor (f ) for each cost or revenue. These are derived in Appendix S2 and are summarised in Table 7. The coupling factors enable us to rewrite Equation 1 as the following: Solving Equation 2 for t r gives the number of transactions required to reach the profit defined as the functional unit. The corresponding number of new jackets produced, q r , needed to replace those sold second-hand can be derived via the following relation between t r and q r (detailed in Appendix S2): The results of the coupling phase are summarised in Table 8. The number of transactions and amount of production for each BM are the parameters fed into the subsequent phase, the LCI.

| LCI and impact assessment
The number of transactions and the required amount of production in each BM were used to build the LCI, perform the LCIA and interpret the results. Conventional LCA methodology was applied using OpenLCA software.
For the LCI, data were collected as described in Section 2.2. A life cycle model was built by considering all environmentally relevant flows, scaled according to the defined functional unit. Detailed LCI and the related data sources and modelling choices are presented in Appendix S1.
T A B L E 2 Description of the processes included in the technical system of the jacket represented in Figure 2 Processes Description

Face fabric production
The polyester face fabric is produced by chemical recycling of used garments. First, collected garments are sorted, washed and shredded; then, the shreds are chemically depolymerised to dimethyl terephthalate (DMT) through a compounding and methanolysis process. A distillation process separates out the DMT, which is then polymerised back to polyester (PET). PET granules are melted, spun into a yarn and woven into a fabric. Finally, the fabric is dyed and finished with a durable water repellent.

Backing production
The knitted jersey backing is made of polyester based on crude oil. Oil is extracted, refined and processed to DMT, which is polymerised to PET granules. Melt spinning and yarn spinning transform the granules into a yarn that is knitted into a fabric and then dyed and dried.

Membrane production
The membrane is made of polyester based on crude oil. Oil is extracted, refined and processed to DMT, which is polymerised to PET granules. Plastic film extrusion produces the membrane.

Other components
The zipper is assumed to be made from polyester, modelled as an amount of virgin polyester granulate input.

Garment production
The face fabric and membrane are laminated together and then, together with the backing, cut and sewn before adding tape and zipper.

Distribution
External distribution includes transport of textile from the producer in Japan to the garment manufacturer in Estonia by freight cargo ship and truck. From there, finished jackets are transported to Sweden by truck and ferry. Internal distribution includes truck transport between warehouse and stores.

Customer transport
For every transaction in the sales model, customers make a round trip to the store by car, bike, walking or public transportation. Two round trips are made in the rental business model, to pick up and return rented jackets.

Laundry
In the sales business model, users launder the jackets in residential washing machines. In the rental business model, the company launders the jackets after every rental transaction, using residential washing machines.

Repair
Repair activities include sewing or replacing faulty components (e.g., the zipper).
End of life End-of-life jackets are either returned to the company or shipped by freight cargo ship to Japan for recycling, or customers dispose of them through incineration. All collected jackets are assumed to be chemically recycled into new face fabric. Since not all jackets are collected, the recycling has to be complemented by virgin polyester production.
The LCIA results were generated for all ILCD 2018 midpoint impact categories (Hauschild & Huijbregts, 2015) and are presented in Figure 3. Compared to the sales model, the rental model resulted in lower scores in most impact categories, although some were considerably higher. Among the higher scores were those for the ozone layer depletion impact category, owing to customer transport by car and related petroleum production. Laundry and public transportation in the rental case also resulted in comparatively higher uses of electricity, which in Sweden is largely based on hydropower and nuclear power production, causing a deterioration in the scores for freshwater use and ionising radiation. In addition, scores for resource use in terms of metals and minerals and land use were higher in the rental model, mostly due to the amount of road construction required.
However, it was difficult to determine what impacts were most significant for the overall environmental performance from such detailed results. Moreover, the results did not permit a straightforward ranking of the BMs. Weighting was thus employed. Application of the ReCiPe (H,A) and the ecological scarcity endpoint methods showed that renting reduces overall impacts by 33% and 22% respectively and that the dominant impact category was climate change (for details, see Appendix S3). Figure 4 shows the impact scores for climate change across different life cycle stages for each BM. When comparing the sales and rental models, major impacts shifted from production to the use phase. Particularly potential impact from energy intense production processes like 'spinning and weaving' and 'dyeing and drying' was reduced in the rental model since fewer new jackets were needed. In contrast, the rental model gave an eightfold increase in potential impacts related to the use phase, mostly due to increased customer transport. Overall, however, the total score for climate change was 43% lower in the rental model, meaning that it represents a more decoupled business.

| Sensitivity analysis
A sensitivity analysis was performed to investigate the effects of changing selected business parameters, uncertain parameters and The results for the baseline scenario, presented in the previous section, are shown at the top of Figure 5, while the sensitivity to selected parameters is shown beneath. Figure 5 shows that results are highly sensitive to the rental price.
With a 50% lower rental price, more rental transactions are needed to generate the same profit as the sales BM, reversing the ranking order of the BMs. Conversely, a 50% higher rental price makes the rental BM even more preferable than the sales model compared to the base case.
Also evident from Figure 5 T A B L E 5 Values of costs, prices and parameters to calculate total costs and revenues and related physical flows

Symbol Description
Values/parameters Sources k prod a Unit cost of production per jacket 2,500 SEK/jacket Derived from the sales and an estimated mark-up margin of 50% (Locsin, 2021) k distr a Unit cost of distribution per jacket 0.14 SEK/jacket Estimated by referring to Maibach et al. (2006)  Supplier choice can make a large difference in the sales model. If textile production is moved from Japan to Sweden, with a lower share of fossil fuels in the electricity mix, production impacts are reduced. If, conversely, textile production uses a high fossil electricity mix, in this case exemplified by production in China, the environmental impacts from production are increased. This is turn has a negative effect on both BMs, but to a larger extent on the sales model.
Another business-related aspect is the number of employees per store. Increasing the number from 1 to 1.5 employees per store has a moderately negative effect on the results for the rental model. Conversely, a decrease only slightly reduces impacts.
In addition to BM choices, the company can alter the product design, for example, by altering the quality of the textile. A fabric with a higher fibre density (75 dtex instead of 150 dtex) increases the environmental scores for the sales model, since more energy is required to achieve the higher density fabric. The rental model is only slightly affected because of the lower production volume. Using less energyefficient laundry in the rental BM (washing twice as often, at 60 C with electricity with a high share of fossil fuels) has a moderately negative effect.
In summary, several internal aspects that the company can directly control significantly affect the results. Some of these were related to the BM set-up, such as rental price or supplier choice, while others related to product design and maintenance.
In addition to factors that the company can directly control, there are relevant external aspects that can only be indirectly influenced.

| Recommendations for the case company
In answer to the questions posed in Section 3.1, the results of the BM-LCA show that the rental BM can lead to an overall better environmental performance compared to the sales BM while maintaining the company's profit level.
The environmental hotspot in the sales BM is the production phase, due to energy-intensive processes related to the large production volume, particularly regarding the face fabric. In the rental BM, the environmental impact is instead dominated by the use phase, mainly caused by the increase in customers' transport to pick up and return jackets.
The sensitivity analysis showed that the rental model does not unambiguously perform better, since some parameters strongly affect the environmental performance of the rental BM. While some of these are outside the company's control, they can still be managed.
An example includes efforts to influence customer transportation habits towards sustainable transport modes. For the same reason, store location is an important factor within the company's control.
Stores could, for example, be located close to public transportation.
Other business factors within company control include the option to offer hybrid forms of rental services (selling rented jackets). This option should be avoided since it leads to loss of potential revenues from repeated jacket rentals. The company should also set the rental price as high as possible, finding a balance between market considerations (e.g., demand and customers' willingness to pay) and sustainability ambitions. Similarly, the rental efficiency should be maximised.

| ANALYSIS
The results from the BM-LCA study are analysed and matched against the BM elements in Sommer's (2012) framework (see Figure 1) in T A B L E 7 Revenues and costs in the rental model (according to the cost structure presented in Section 3.4), connected to the number of transactions (t s ) by using the coupling factors derived in Appendix S2

Revenue or cost category
Revenue or cost expressed in terms of t r Coupling factor

Revenues from rental transactions
RE r = f 1 * t r f 1 = P r Revenues from secondhand sales RE r, 2nd = f 2 * t r f 2 = P 2nd * U r /RL

Production costs
C prod = f 3 * t r f 3 = k prod * U r /RL

Distribution costs
C distr = f 4 * t r f 4 = k distr * U r /RL

Laundry costs
C laundry = f 7 * t r f 7 = k laundry Repair costs C repair = f 8 * t r f 8 = k repair

End-of-life costs
C EoL = f 9 * t r f 9 = k EoL * CR * U r /RL Alternatively, the company may need to develop channels and delivery systems that can prevent or indirectly reduce customer environmental impacts by influencing customer's transportation habits.

T A B L E 8 Basis of comparison (profit level), number of customer transactions and jackets produced in each business model
The BM-LCA study also provided information to the key More than addressing individual elements in Sommer's (2012) framework, the BM-LCA study enabled an investigation of inter- From an understanding of interconnectedness between BM elements through a BM-LCA study, the method may guide innovation on the steering mechanisms element, that is, on the business logic so it can be adjusted for better environmental performance.
To summarise, BM-LCA applied in a comparative case of renting versus selling provided insights into individual BM elements, as well as their interconnectedness. Also, business parameters like price level and rental efficiency were shown to have direct consequences for the environmental performance of the BMs.

| DISCUSSION
The BM-LCA method was able to provide guidance on many BM elements (Sommer, 2012)  What is different with the present study is that it identified business factors as key for environmental performance. While our findings agree that customer behaviour is an important factor, alongside product design choices and efficient processes, we found that factors relating to business parameters, such as rental price and rental efficiency, had greater significance. The greatest impact reduction

| Comparing guidance to BM innovation from LCA, BMC and BM-LCA
In Section 4, the findings from the BM-LCA study were related to the framework of Sommer (2012). Here, using the same framework, we compare BM-LCA with conventional LCA and the BMC. Figure 6 shows the type of contribution from the three methods to different BM elements. The range of elements on which LCA provides guidance is limited. This is because, as discussed in Section 5.1, conventional LCA attempting to analyse BMs still focuses on the technical system. Consequently, LCA can only provide guidance for BM elements relating to product design choices and related technical processes (e.g., production, distribution, transport and use), which only affect the key resources and the key processes components of the framework. In summary, as indicated by Figure  5.4 | BM-LCA supporting BM innovation and business strategy BM and business strategy are inextricably linked, and simultaneous attention to both is needed for the long-term success of a company (Braun et al., 2019;Shafer et al., 2005). A discussion about the usefulness of BM-LCA for BM innovation has thus bearings on business strategy.
The BM captured by BM-LCA is, in the words of Timmers (1998), the 'architecture' of how a company makes money, while business strategy is about how the company stays competitive on the market (Magretta, 2002). Business strategy adapts to market trends and societal changes, and the BM 'structures' the value process so that it provides value to customers and collects a portion of this in revenues to the company. A company's BM is thus never finished (Teece, 2010  In the current study, the company had a strong sustainability profile. At the outset, there was a notion that a rental BM was environmentally preferable to their linear sales model. However, this notion got called into question since the sensitivity analysis showed results to be highly sensitive to how customers transported themselves to the stores (see Figure 5).  Shafer et al. (2005), the probability for a company's long-term success with the greening of its business strategy likely increases when it systematically analyses the environmental impacts of its strategic and tactical choices through its BMs. BM-LCA provides a means for such systematic analysis. The method can direct BM innovation by identifying the parts of a BM in greatest environmental need of innovation and the options within the company's control, but determining which options have best strategically fit is outside the scope of the method.
Even so, the method can assist with an environmental evaluation of choices and validate the environmental performance of a preferred BM configuration.

| Future research
BM-LCA is a new, yet promising method, and the current study is the first of its kind. There is thus considerable scope for more research.
To begin, BM-LCA need to be further applied and tested on different types of BMs and in different industry sectors. This could be combined with studies of how the method contributes in practice to different business processes and comparisons with related methods.
More methodological research is also wanted. Better understanding of how the method behaves, for example, in relation to longer timeframes or different forms of decoupling could help develop simpler tools appropriate for business practice. Also, how social sustainability is reflected in BM-LCA is welcome since sustainable BMs are expected to create value not only for customers and business but also for society at large.
BM-LCA represents a complex multidisciplinary synthesis, and business and LCA scholars could merge their expertise through it. We hope the method will attract collaborative efforts and inspire new research on the environmental sustainability of business and economy.

| CONCLUSIONS
This article presents the first application of a new business-oriented LCA method, BM-LCA, and discusses benefits and usefulness of the method for BM innovation for sustainability. We contend that BM-LCA is a response to frequent calls for methods that can measure and validate the environmental performance of BMs.
BM-LCA was applied to a case comparing rental and sales BMs.
The assessment showed that a rental model can lead to decoupling of environmental impacts from profit compared to a sales BM. This is the first time, to our knowledge, that decoupling has been shown at business level. Application of BM-LCA provided relevant and important insights for BM innovation for the company since the method was able to identify both key business and technical parameters affecting the environmental performance of BMs. Particularly rental price level and rental efficiency together with customer transport behaviour proved to be critical for ensuring an environmentally sustainable BM and should be managed carefully in the innovation process. This represents an important contribution since previous similar LCA studies have emphasised technical factors.
BM-LCA is a methodological innovation on LCA. The essential innovation is a coupling of the product system to the business system around the product, thereby switching the perspective taken in an LCA, from a product and user perspective to a business and company perspective. This methodological innovation has relevant implications for business strategy and BM innovation.
Using BM-LCA, a company can assess a BM to identify whether or not it effectively improves the environmental performance without losing profitability and determine if it selects that BM to compete with. In an economic environment where many companies compete with green intents, BM-LCA can be used to validate the sustainability of a particular BM for a specific company, thereby help avoiding greenwashing and strengthening the credibility of its environmental claims.
With increasing societal demands for environmental sustainability and for decoupling, all BMs are called into question. The method enables a company to identify the parts of a BM in greatest need of environmental innovation and evaluate the environmental effectiveness of the options within the company's control. This means that a company can test its strategical and tactical options through the BM and innovate it for environmental sustainability.
Analysis showed that BM-LCA produced insights on both individual and interconnected BM elements. This makes BM-LCA a useful tool for companies pursuing BM innovation for sustainability. Its capacity to provide quantitative information on a wide range of BM elements places it between conventional LCA and BMC. In comparison with other company-oriented LCA tools, only BM-LCA provides environmental evidence on BMs.
Although BM-LCA shows promise as a missing link for win-win solutions, more research is wanted. Especially, application and test of BM-LCA on different BMs is needed. We envision the practical application of BM-LCA through joint efforts of business and LCA analysts, who could merge their expertise through it. Hopefully, the method will inspire new research that supports the environmental transformation of business and economy.