Shared access or private access?
Consumer Intention to use the Pay-Per-Use model vs Product Ownership.
A case for electric vehicles
Executive Programme for Management Studies
Author: Tibo Gude
Student no.: 10886281 Thesis supervisor: Dr. H. Güngör EBEC approval no.: 20210303050348
2 Statement of Originality
This document is written by student Tibo Gude who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the
supervision of completion of the work, not for the contents.
Abstract ... 4
1.0 Introduction ... 5
2.0 Literature review ... 11
2.1 The Pay-per-Use models vs Product Ownership ... 11
2.2 Environmental concern (EC) ... 14
2.3 “Intention to use” and the Theory of Planned Behavior ... 16
2.4 Private or shared access ... 19
2.5 Product value ... 20
2.6 Consumer demographics ... 22
3.0 Research methodology ... 23
3.1 Design ... 23
3.2 Sample... 24
3.3 Measurement of the variables ... 25
3.3.1 Environmental concern (EC) ... 25
3.3.2 Intention to use ... 26
3.3.3 Access & Value ... 27
3.3.4 Control variables ... 27
3.4 Formative research (pre-test) result ... 27
3.5 Statistical procedure ... 29
4.0 Results ... 30
4.1 Operationalization of the data ... 30
4.2 Descriptive statistics ... 33
4.3 Hypothesis testing ... 34
4.3.1 Direct effects ... 34
4.3.2 Moderation effects ... 36
4.4 Between group analysis ... 38
5.0 Discussion of results ... 40
5.1 Theoretical and practical implications ... 40
5.2 Limitations ... 43
5.3 Further research ... 44
6.0 Conclusion ... 45
References ... 48
Appendices ... 53
Human lifestyle in the developed countries put immense pressure on earth ecosystems due to the linear extract-produce-use-dump material and energy flow model. A shift toward more circular business models can contribute to a reduction of this pressure, which is drastically needed. In the pay-per-use model, consumers pay for the unit of service without gaining ownership of a product, stimulating conscious use, product longevity, re-use, and recycling.
However, little knowledge exists about the relation between the intention to use these models and consumers’ environmental concern (EC). This study aims to provide more understanding regarding this relation in the case of personal electrical transportation in the form of electric bikes and cars, and the interaction effects of the type of access to the service being either private or shared, as well as by product value.
Following the established behavioral intention theory, in the Theory of Planned Behavior, intention to use is measured via its three predictors, namely attitude toward this behavior, subjective norm, and perceived behavioral control. Results from a survey under Dutch consumers (N=175) found a positive effect for EC on all three predictors, but no interaction effect by either access type or product value. This means that the current trend of increasing EC in consumerism could increase demand for the PPU model, but this relation is not affected by either access type or product value. However, results do show that a high product value increases the intention to use the PPU model and that the model is more interesting in urban areas.
Key words: Environmental concern, Pay-per-use model, Consumerism
5 1.0 Introduction
Our planet is finite. The ecological system is under a lot of pressure since it cannot regenerate resources and absorb our waste and emissions at the current rate of extraction and pollution. To take responsibility for current environmental pressure and to facilitate future generations, there is no other option than to keep our environmental footprint within earth’s regenerative planetary boundaries (Fang, Heijungs, & De Snoo, 2015). The circular economy appears to be a promising solution and is currently strongly promoted by the European Union (Korhonen, Honkasalo, & Seppälä, 2018). However, due to entropy law, recycling will always require energy, which eliminates the possibility of complete recycling (Georgescu-Roegen, 1971) and, therefore, the possibility of a fully circular economy as the comprehensive solution.
A probable solution is a sustainable “steady state economy” (Daly, 2018), in which resource use and waste are kept within the planetary regenerative and absorption boundaries.
Since, in 2020, the earth was burdened with nearly double its regenerative and absorption capacity, the urgency is extremely high. For the Netherlands, this factor is calculated to be 3.31 in 2021, meaning that on April 27th The Netherlands had used up its fair share of earth regenerative capacity (Global Footprint Network, 2020). Just like The Netherlands, most other developed countries increased their resource use per capita way above the threshold level required for a sustainable steady state economy, which has strong ecological and social consequences. Depletion of raw materials, land degradation, loss of biodiversity, climate change and other forms of pollution keep increasing while disproportionately affecting the poor. From an ethical and economic sustainability perspective, the developed countries must aim to remain within their fair share of earth’ regenerative capacity.
However, we are heading in the opposite direction. The world economy is doubling approximately every 20 years and, since ecological problems are very strongly correlated with
6 economic (GDP) growth in the current linear “extract-produce-use-dump” material and energy flow model, this is an unsustainable path (Frosch, Robert A & Gallopoulos, Nicholas E, 1989).
With neo-liberal capitalism as the current globally dominant economic system and GDP as a main indicator of welfare, most policy makers are prioritizing economic growth over sustainability. Sustainability and the circular economy are on the agenda, but this only seems a plausible ambition if it can be realized while growing economically. Proposing solutions as
“sustainable growth”, which sounds like an oxymoron, is a dangerous approach.
Like the circular economy, technology will contribute towards a sustainable human existence as part of the solution, but we cannot trust on this to be the solution by itself. The Jevons paradox from 1905 still explains this quite clearly today (Alcott, 2005) (Adua, Clark,
& York, 2020). In fact, far-reaching lifestyle changes and different economic paradigms are needed (Wiedmann, Lenzen, Keyßer, & Steinberger, 2020), of which the “degrowth”
paradigm, about downscaling overproduction and overconsumption (Schneider, Kallis, &
Martinez-Alier, 2010), seems fitting. A note must be made that the degrowth paradigm does not stand for “degrowth oriented” organizations within the capitalistic system. It is related to a radical change in the current way of life transcending capitalism altogether, which can be realized with changes simultaneously in the economic, socio-political, and cultural sphere (Fromm, 2002).
What organizations should do is investigate the degrowth parameters and see if contributions can be made to reduce resource use, inequality, and pollution. As the core of most nature and environmental problems can be traced back to (wasteful) resource use (Hanemaaijer, et al., 2021), an effective way for an organization to contribute is to produce fewer products, without reducing customer output of the service. This entails substantially increasing the useful life of products to offer longer service without replacement. Reducing production has a bigger
7 impact then efforts to produce in a more sustainable way or a focus on recycling, although these are not mutually exclusive. Besides a reduction in production, it entails less packaging, logistics, and product “end-of-life” waste.
Factors that contribute to increasing the useful life of product include durable design, easy maintainability, easy repairability, modular design for part replacement or upgrades. For an organization, this can be a difficult trade-off as financial incentives might not be in line with increased product life due to increased production cost, less maintenance income, and less product sales. This even leads to planned obsolescence where goods are specifically manufactures to shorten product lifespan for increased sales. Besides that, there apparently is demand for less quality goods, because the customer might not want to invest in a quality product since he or she is used to simply replace products when they become less useful. This means incentives are not well aligned between the producer and consumer in the product ownership model stimulating the linear “extract-produce-use-dump” material model.
A business model which tends to align incentives better regarding extended product lifetime is the pay-per-use (PPU) model. In this model, consumers pay for the unit of service without gaining ownership of a product. This business model can unburden the consumer related to product selection, ecological impact, initial investment, maintenance, and product life cycle, while promoting producers to solve these problems as much as possible in the product design, thereby increasing product lifetime (Cherry & Pidgeon, 2018). It can incentivize product longevity and reuse over the linear “extract-produce-use-dump” material model since the profit center is not the product, but rather the functional units it delivers (Tukker, 2004).
There are two versions of the PPU model. When the service is freely accessible for all consumers, which is the “shared access pay-per-use” (SPPU). In this version the product is
8 available for all consumers to use. The consumer must share the product that facilitates the service with other consumers and pays directly after using it based on the intensity of use. In the “private access pay-per-use” (PPPU) version the consumer is not sharing the product that facilitates the service, having private access at any time. Usually, the consumer must commit to a minimum use in this scenario and pays on a monthly fee based on the actual use. As perceptions of the consumer on these versions might differ, this is important to distinguish in this study.
With the Internet of Things (IoT) on the rise, the PPU model is becoming more accessible. The connected sensors allow producers or service providers to not only measure the consumers usage for billing, but also to identify and monitor metrics for maintenance, repair, and service model optimization (Heinis, Loy, & Meboldt, 2018). Besides that, consumers are increasingly ecologically aware and literate (Chitra, 2007) (Wei, Ang, & Jancenelle, 2018).
This is a key trend for organizations to consider in business model renewal, better aligning incentives between the consumer and producer or service provider regarding reduced ecological impact. The pay-per-use model can play an important part in this, especially if it is the case that there is relation between consumer environmental concern (EC) and the adoption of the PPU model.
Besides the type of access, which can be either shared or private, product value can have an influence on the intention to use the PPU model, as a key difference of the PPU model compared to product ownership is that for PPU no initial investment is required. This leaves a gap in existing literature about the effect of environmental concern (EC) on the intention to use the PPU model, and how this is different for private vs shared access, and high vs low value product.
Therefore, the research questions are:
9 1. To what extent does environmental concern (EC) influence the Intention to use PPU
vs product ownership?
2. To what extent does the “access” to the service, and “product value”, moderate the relationship between EC and intention to use PPU?
Key factors of the degrowth paradigm as “limits to growth”, “Jevons’ paradox” and the
“balance of nature” are dimensions of the “new ecological paradigm” (NEP) model used to explore levels of environmental concern in society (Albrecht, 1982). Providing not only a slight
“degrowth paradigm” touch to this study, but as the trend of increasing eco awareness is expected to continue (Chitra, 2007) (Wei, Ang, & Jancenelle, 2018), this study may provide theoretical contributions about the correlation between environmental concern and the intention to use a pay-per-use model. Besides that, managerial contribution can arise regarding key information about the expected adoption of these business models by consumers in the future and possible preference over product ownership. Eco awareness trends might differ locally and per type of consumer, therefore this study can provide direction on where to offer non-ownership business models and whether and when private access trumps shared access. It can provide additional insight in consumer type interested in pay-per-use services over product- ownership in the case of e-bikes. This can be used for marketers and perhaps even policymakers in the transition toward a more sustainable and degrowth-oriented economic system.
Regarding the structure of the thesis, in chapter 2, this research paper will discuss the existing literature regarding the variables in question and their interaction leading to the main hypothesis and the conceptual model of this study. In the chapter 3, the research methodology is described for a thorough understanding of data collection methods and measurement of variables. In the fourth chapter, the data operationalization is explained in steps, after which
10 the results are presented based on the statistical testing of the data and extracted results. Chapter 5 presents the discussion of the results as well as theoretical and practical implications, with the conclusion in chapter 6.
11 2.0 Literature review
In this chapter, the existing literature related to the research question is discussed. This includes relevant findings about the key constructs, their measurability and what is known about their interaction. This section starts with a description of the pay-per-use model and its differences compared to the product ownership model, followed by a description of “consumer environmental concern”, the “intention to use” and the interaction variables “type of access”
and “product value” including their accompanying hypotheses. The chapter ends with the graphically displayed conceptual model.
2.1 The Pay-per-Use models vs Product Ownership
The Pay-per-Use (PPU) model is part of the product service systems group that entails several versions of combining products with accompanying services (Tukker, 2004). These versions range from “product oriented”, where it is mainly about the tangible product, to “use oriented”, where product and service are combined, to “result oriented”, with a focus on the intangible service. The PPU model is in the “result oriented” category with the focus on the intangible service rather than the actual physical product. This affects the revenue model and the value proposition considerably by servitization from product to service, which can be seen as two of the three main components of a business model (Bohnsack, Pinkse, & Kolk, 2014).
The product that facilitates the service is usually a common item, however the customer does not purchase the product, only the output of the product according to the level of use (Tukker, 2004) (Bocken, Mugge, Bom, & Lemstra, 2018).
This change in the business model stimulates the transition from a linear production process and the throw-away mentality toward more circular flows of products and materials in
12 both production and consumption phases (Gullstrand Edbring, Lehner, & Mont, 2016). Shifting away from consumer product ownership and therefore also the responsibility to repair and maintain, PPU is promoted as a model with characteristics to increase product longevity (Cherry & Pidgeon, 2018) (Benton, Hazell, & Hill, 2014). These characteristics mainly entail the incentives for a producer or service provider to get the most value for the product by increasing longevity, surpassing the “take-make-dispose” economy. Therefore, promoting products and materials circulating for as long as possible before recovering them for future use (MacArther, 2013), contributing to dematerialization of the economy and reducing tangible products by focusing on the service aspect.
There are 2 versions of the PPU model. The first version is “shared access pay-per-use (SPPU). In this case the consumer shares the product so other consumers can make use of the service from the same product too. Especially this version is not a new concept. A classic example of this is the laundromat, where you visit a publicly accessible location to pay for just the output of using a washing machine in the form of clean clothing. Others are print and copy shops, where you can pay per printed sheet of paper, or car rentals that only charge for distance driven.
The other version is private access pay-per-use (PPPU). Here the user has private access to the service and does not have to share the product. In B2B, this concept is not new either as in 1962, Rolls-Royce implemented its 'Power-by-the-Hour' business model, where only running hours of the engine are charged to the customer (Rolls Royce, 2012). However, in B2C setting, it is relatively new. Still an example can be found where a consumer has private access to the product. HOMIE offers several household appliances via the private PPU model where was found that the PPPU model stimulated sustainable consumption (Bocken, Mugge, Bom, &
13 Lemstra, 2018). An interesting difference is here that in return for private access the consumer is committed to a minimum use of the product.
The transfer of ownership from the consumer to the producer or a service provider affects the consumer’s experience. Worry about maintenance, upgrades, repair, and disposal are shifted away from the consumer (Cherry & Pidgeon, 2018) and an initial purchase amount is no longer required. On the other hand, with B2C PPU, the consumer usually has fewer models to choose from, can have less flexibility and could have some responsibilities that come with entering into contract-based service agreements. Furthermore, the consumer has less autonomy over the product, higher cost per use, and can be burdened with a minimal usage amount to pay, even when the product is not used at all. For the producer or service provider, this entails a responsibility to keep the service available for the customer. This implies maintenance and repairs, but also the logistics, re-use and redistribution of products, as well as refurbishment and remanufacturing schemes to be able to get the most running hours as possible from the product to maximize resource value (Benton, Hazell, & Hill, 2014).
Different trends regarding product ownership can be observed. Advocating the ethics of minimalism has seen an upsurge in the post-2008 financial crisis era (Meissner, 2019), possibly promoting consumer perception on PPU models. However, “desire to own” was classified as one of the main attributes of consumption culture in 1988 (Wallendorf & Arnould, 1988) and, in a more recent study of 612 participants, over 40% indicated that “desire to own”
was a reason against access-based consumption (Gullstrand Edbring, Lehner, & Mont, 2016).
Another recent study found a lack of interest for the PPU model specifically compared to other circular business models (Elzinga, Reike, Negro, & Boon, 2020). But as this study was strictly focused on “pay per print”, did not incorporate consumer demographics as a variable and made no distinction between shared and private access, there is still ground to cover.
14 Different product categories can lead to significant different results. Consumer attitudes on alternative modes of consumption in general diverge greatly between product groups (Gullstrand Edbring, Lehner, & Mont, 2016). Therefore, to make the results more beneficial in both a scholarly as a business setting, product categories should be selected for this study. A product currently strongly on the rise, becoming mainstream is the electric bicycle, or e-bike (Fishman & Cherry, 2016). As e-bikes are easily equipped with IoT sensors to track distance driven, the category resonates with both the private and shared PPU models. To be able to gain more understanding about the impact of economic value, a comparison will be made to a high value electronically propelled mode of transport, the electric car. This product is on the rise worldwide as well with some cities planning to deny access to fossil fuel driven cars as soon as 2030 (City of Amsterdam, 2019) and countries banning sales of fossil fueled cars that same year (Netherlands Enterprise Agency (RVO.nl), 2019). As new cars tend to be equipped with IoT this is an interesting item for the PPU models and therefore to be used as the “high value”
item compared to the lower valued e-bike regarding “intention to use PPU”.
2.2 Environmental concern (EC)
Humanity is not living in balance with earth ecosystems natural limits (Global Footprint Network, 2020). In fact, we are crossing the boundaries further and further with serious consequences in the future. As environmental concern (EC) is on the rise (Chitra, 2007) and the PPU models are considered more sustainable this study aims to validate if EC is an explainer for the “intention to use” of a PPU model. EC is a quite broad concept and greatly studied. Therefore, it is suggested to specify which parts of EC will be measured (Pellow, Dunlap, & Michelson, 2003). For this study EC is defined as the degree to which a person
15 perceives the seriousness of environmental problems based on his or her ecological worldview, and beliefs regarding the human-nature relationship.
This was similarly defined when assessing EC in other literature (Ester & Van Der Meer, 1982), (Dunlap, Van Liere, Mertig, & Jones, 2000) (Liu, Vedlitz, & Shi, 2014) and fits the New Ecological Paradigm (NEP) scale which was developed in the late seventies (Dunlap
& van Liere, 1978) and early eighties (Dunlap & van Liere, 1984) and revisited in 2000 (Dunlap, Van Liere, Mertig, & Jones, 2000). The NEP scale tests the ecological world view and fundamental beliefs of a person and represents an environmental worldview via subcomponents as the balance of nature, human interaction with nature, and limits to growth.
A pro-ecological score on the NEP scale is considered to be related to high environmental concern (EC) (Stern, Kalof, Dietz, & Guagnano, 1995).
As product service systems in general, and PPU business models specifically, are considered a more environmentally alternative compared to product ownership (Tukker, 2004), it can be assumed that consumer environmental concern is related to consumer intention to use the PPU model. However, in a more general study regarding environmental attitude and adoption of different kinds of circular business models, it seemed that take-back management was the only version where EC significantly contributed to the consumers’ intention to participate (Elzinga, Reike, Negro, & Boon, 2020). The case for pay-per -use in this study was an exceptionally low value with relatively low ecological impact of a single print, which therefore might not be representative regarding the effect of EC and, in turn, impacts generalizability. So, the effect of EC might have gotten clouded by other reasons to use pay- per-print as convenience or cost. Therefore, in this study, the effect of EC will be directly tested regarding the intention to use a PPU model instead of buying the product.
16 Since consumer environmental concern is on the rise worldwide (Chitra, 2007) (Dilkes- Hoffman, Pratt, Laycock, Ashworth, & Lant, 2019) and environmentally considerate consumer behavior is growing (Mainieri, Barnett, Valdero, Unipan, & Oskamp, 1997) this is an important piece of additional information as it explains more about the consumer category that is interested in the PPU models and how this interest can evolve in the future.
2.3 “Intention to use” and the Theory of Planned Behavior
Consumers tend not to be very rational in decision making. What seem good determinants of consumer intention is the combination of behavioral beliefs, normative beliefs, and control beliefs. Generally, a more favorable attitude toward the behavior (ATB), positive subjective norm (SN), and greater perceived behavioral control (PBC), lead to a stronger intention for a person to perform the behavior in question. With a strong intention it is expected that people carry out the actual behavior when the opportunity arises, if there is sufficient actual behavioral control (Ajzen, 1991).
The Theory of Planned Behavior (TPB), developed by Icek Ajzen in the late 1980’s, is a framework using this logic to measure human intention, which together with actual behavioral control, is a strong indicator for actual behavior. Besides TPB allowing to indicate the likelihood that people intend to carry out a specific behavior, it provides an understanding of the factors that lead to the behavioral intention. This can help in overcoming barriers toward a behavior. As mentioned, this framework entails three main determinants of “intention” which are described individually based on (Fishbein & Ajzen, 2010).
The first one is “attitude toward the behavior” or ATB, as the Theory of planned behavior is based on an expected value formulation of an attitude toward the behavior. ATB is
17 seen as a function of readily accessible beliefs toward the behavior's likely consequences, which are the behavioral beliefs. And a behavioral belief is the subjective probability of a person that the behavior will lead to a set outcome or experience. For example, the belief that choosing the PPU model over product ownership (the behavior) has positive environmental effects (the outcome) or is inconvenient (the experience). According to the theory, the combination of the scores of all behavioral beliefs, will result in a positive or negative attitude toward the behavior (ATB).
The second determinant of intention is Subjective Norm (SN). It consists of two types of believes: injunctive and descriptive. Injunctive represents the expectation that other persons or groups (family, friends, coworkers, peers), important to the person in question, would approve the behavior or not. Descriptive beliefs represents if these important others (intent to) perform the behavior. This combination between whether important others approve, and if they (would) perform the behavior is the overall subjective norm.
The third determinant is Perceived Behavioral Control (PBC). PBC is based on the beliefs regarding behavioral control and the factors that can either support or obstruct the behavior in question. These control beliefs or factors can range from skills and abilities to time or economic resources or any other factor impacting PBC. Each of these control beliefs contributes to the perceived behavioral control (PBC) by multiplying the factors strength and power and subsequently compute the overall PBC score. Please view figure 1 for a schematic overview of the theory of planned behavior on the next page.
Figure 1; (Ajzen, The Theory of Planned Behavior, 1991)
TPB is most commonly used in health-related behavioral research, and to some extent criticized in that field (Sniehotta, Presseau, & Araújo-Soares, 2014), and widely and successfully used to explain and predict behavior in other fields. Positive assessments and meta-analysis studies were conducted on TPB in dietary behavior (Riebl, et al., 2015) (Armitage & Conner, 1999), physical behavior (Hagger, Chatzisarantis, & Biddle, 2002) (Hirschey, et al., 2020), seeking social support (Albarracin, Fishbein, & Goldestein de Muchinik, 1997), choice of travel mode (Yuzhanin & Fisher, 2016), safer sex (Tyson, Covey,
& Rosenthal, 2014), and technology adoption (Weigel, Hazen, Cegielski, & Hall, 2014), to recycling (Cheung, Chan, & Wong, 1999) and consumer behavior (Nardi, Jardim, Wagner, &
Santini, 2019). A meta study from 2016 confirms the effectiveness if this theory (Steinmetz, Knappstein, Ajzen, Schmidt, & Kabst, 2016). Therefore, the theory of planned behavior can be used to provide a good indication for consumer intention to use PPU models instead of buying the product, while providing insight on which factors matter regarding the intention to use.
Therefore, the first hypotheses are:
19 H1a: Environmental concern (EC) has a positive effect on the Attitude Toward Behavior (ATB) for using PPU instead of product ownership.
H1b: EC has a positive effect on the Subjective norm (SN) for using PPU instead of product ownership.
H1c: EC has a positive effect on the Perceived behavioral control (PBC) for using PPU instead of product ownership.
2.4 Private or shared access
In existing literature, the pay-per-use model is generally seen as a service provided by shared use of a product, not private access (Tukker, 2004) (Boons & Lüdeke-Freund, 2013) despite the possibility of a large impact on consumer intention to use a PPU model. Having either shared or private access changes the service offering to the consumer as availability is lower when the service is shared, but a minimum usage fee is more suitable with the private access version of the pay-per-use model. Please find main characteristics in figure 2 (Bocken, Mugge, Bom, & Lemstra, 2018) (Tukker, 2004) (Elzinga, Reike, Negro, & Boon, 2020).
Figure 2; pay per use characteristics
Due to the differences in characteristics between the different types of the PPU, this might affect the relation between environmental concern and the intention to use the PPU model. Existing literature does not cover this, leaving a gap regarding the comparison in consumer intention to either use the “shared” or “private” PPU model. Therefore, the third hypothesis is:
H2: Shared access to the service positively effects the relationship between Environmental Concern and intention to use the PPU model instead the product ownership model.
2.5 Product value
As the pay-per-use model seems to have a different appeal to consumers for different reasons and products with economic reasons among the main drivers for using the PPU model instead of product ownership (Botsman & Rogers, 2010) (Gullstrand Edbring, Lehner, & Mont, 2016), the product value can provide key insights on the intention to use. As mentioned in
21 chapter 2.2 regarding environmental concern, in existing literature no link was found regarding a very low value and low impact service as pay-per-print (Elzinga, Reike, Negro, & Boon, 2020) which might therefore might not be suitable to link to the user’s environmental concern.
On the other hand, regarding higher value products that express social status such as cars, consumers do generally higher desire to own (Mont & Plepys, 2003).
Usually more expensive products have a bigger environmental footprint regarding resource use for production and maintenance, CO2 and other emissions for transportation to the end consumer and more waste and the product end of life. Meaning that when compared to the linear extract produce use dump system, a more circular model like pay per use can bring more benefits per product. However, as the cheaper products are generally more abundant, the product longevity stimulation regarding this category can be seen as a key contribution to the current environmental situation as a whole. Therefore, it might be the effect of a consumer’s environmental concern on the intention to use a PPU model is affected by the value of the product.
Therefore, in this study the product value, with an e-bike representing a relatively low value, and an electric car representing the relatively high value product, is considered for interaction effects between environmental concern and the intention to use a PPU model. This brings us to hypothesis 3:
H3: High product value positively affects the relationship between Environmental Concern and intention to use the PPU model instead of the product ownership model.
See figure 3 for the schematic conceptual model on the next page.
Figure 3; the conceptual model
2.6 Consumer demographics
Consumer demographics are measured in general to obtain more specific population information. For this study is chosen to measure gender, age and area type of inhabitance being either urban or rural. Regarding We are not expecting to find any interaction regarding these effects on the main effect of EC on the intention to use the PPU model, but it is interesting to look for correlations in general as there might be some effect of age and area type on the intention to use the PPU model, but we do not expect to find a correlation for gender.
Furthermore, the area type is interesting to consider regarding managerial implications of the intention to use the PPU model. Since one of the predictors of intention to use is
“perceived behavioral control”, it can be that a certain type of the PPU models seem less likely to be an option in less densely populated areas. Especially when the access type shared instead of private, consumers might struggle to use this model, and for service providers there is no business case when the area is only mildly populated.
23 3.0 Research methodology
With this chapter the empirical part of this study commences. After a brief overview of the design of the study, the key steps, and properties of the data (collection) are described. Then the variables and constructs in the questionnaire are explained as well as the questionnaire validity and reliability. Followed by a summary of steps taken in the statistical testing of the hypothesis and its outcome. The full questionnaire can be found as appendix.
This study aims to find relationships between consumer environmental concern (EC) and their intention to use the pay-per-use model instead of buying the product. The reason for this is to broaden knowledge about the adoption of PPU models for organizations to better understand consumer decision-making regarding the use of PPU models, understand the effect of consumer environmental concern on the intention to choose for the PPU model, and to some extent which factors matter most in their decision-making. This study will focus on PPU models for personal transportation in the form of a low-value E-bike and a high value E-car.
The understanding of the relationships in this study will be explained by quantitative data and therefore involves statistical testing. Prior to the analysis and hypothesis testing, primary data in the form survey is collected. In the participants Environmental Concern is measured via the NEP scale. Consumer Intention via the Theory of planned behavior for 4 different scenarios depending on “product value” and “access” as displayed in figure 4. The participant received the same questions in a slightly different scenario based on the product value and access type. The participants were randomly assigned to a scenario.
Figure 4; Randomly assigned scenarios for participants
The population for this study is Dutch consumers. The sample data is collected via a non-probability sampling method, using convenience sampling in the authors personal network and via Prolific to increase valid responses. The data was collected in March 2021 by distributing a link to the online questionnaire created in Qualtrics. In total, 199 participants started the questionnaire of which 177 (89%) completed it. One response was removed due to the participants current country of residence being South Korea, and another was removed due to bot warning by Qualtrics. The remaining 175 valid responses are included in this study. The remaining respondents all indicated to live in the Netherlands, of these 175 responses 68 (40%) is female, aged between 18 and 64 with 40% between 25 and 34. 138 (80%) living in an urban area and all participants finished high school with most participants (41%) complete a bachelor program.
25 3.3 Measurement of the variables
The main constructs of this study are “environmental concern” and “intention”. These are measured in the questionnaire via either an established scale or an established theory. Below the measurement of each of the variables will be explained.
3.3.1 Environmental concern (EC)
The New Ecological Paradigm scale (NEP) is the most widely used scale to capture people’s environmental concern (EC) (Hawcroft & Milfont, 2010) while capturing some key aspects of the degrowth paradigm (Hickel, 2020). This is used to identify a relation between a person’s EC and the intention to use the PPU model. Despite being developed originally with 15 questions (Dunlap, Van Liere, Mertig, & Jones, 2000), an abbreviated version is widely used to keep surveys more user friendly and reduce mortality risk, while it remains valid for assessing the fundamental ecological worldview by providing a balanced measure of the key three key constructs of the original NEP scale. (Hawcroft & Milfont, 2010). These three constructs are “balance of nature”, “limits to growth” and human’s “right to rule”. As this study is linked to the degrowth paradigm, the “limits to growth” is particularly interesting although this will not be looked into separately, but only to the NEP scale as a whole. The scale generally scores a reliability of Cronbach’s α > .76 (Alibeli & White, 2011) (Hawcroft & Milfont, 2010).
Most commonly a 5-points scale is used for NEP studies. However, a meta-analysis found using either a 5-point scale or 7-point scale did not have any effect on the NEP score (Hawcroft & Milfont, 2010), therefore is chosen for a 7-point bipolar scale corresponding with the scale used in the Theory of Planned behavior with answers from 1 = strongly disagree, to 7 = strongly agree. Two example questions from the NEP scale are “The balance of nature is very delicate and easily upset by human activities” and “There are no limits to growth for
26 nations like the United States and The Netherlands” (reverse coded). The mean of the outcome to the 7 questions determined to create the construct of environmental concern (EC).
3.3.2 Intention to use
Consumer intention will be measured via three main determinative factors according to the Theory of Planned behavior. These determinants are attitude toward the behavior (ATB), subjective norm (SN) and perceived behavioral control (PBC). To measure these determinants, formative research, or a pre-test, is carried out for eliciting salient beliefs among the sample.
Pilot respondents (N=36) were asked what they associate with the pay-per-use models in the case of e-bikes and electric cars and for both PPU models individually, in open questions. For example, one of the answers was that most participants perception is that the pay-er-use model will reduce worry about ownership responsibilities as repair and maintenance. Other examples are that the PPU model can reduce impact on the environment, peers are important regarding the subjective norm and a long-term contract might discourage the use of the PPU model instead of product ownership. The answers were sorted to from high to low frequency of mention to understand the actual beliefs about PPU models among the sample. Combined with direct measures, items are formulated for the top salient beliefs to assess in the main quantitative questionnaire for this study. The results of the formative research overlapped strongly with previous qualitative research on similar access-based models for furniture (Gullstrand Edbring, Lehner, & Mont, 2016). The formative research results can be found in the appendix.
In line with the Theory of Planned Behavior (Ajzen, 1991), 17 items are created from the direct measures and formative research resulting in 34 questions as the items consist of a question about the participants belief and the subjective evaluation of this belief (also know as believe strength). These are 6 items for ATB, 6 for SN, and 5 items for PBC. Previous research
27 has shown that a seven-point bipolar adjective scale is most suitable in TPB-related research (Ajzen, 2015) therefore this scale is used for each of the questions. To calculate the score of each item based on the question of the participants belief (b) and the subjective evaluation of the belief (e), the outcomes are multiplied, i.e., ATB α Σbi ei. The belief score is a score from 1 to 7 and the strength score from -3 to 3, therefore resulting in a score for the item between - 21 and 21.
As some items were specifically created for this study based on the formative research there is no previous reliability measure for this construct. So, despite reliability and validity has proven sufficient in previous research using the Theory of Planned Behavior as described in the literature review, this is tested on the actual data for this specific scale.
3.3.3 Access & Value
Value and access are both measured as dichotomous moderators in the dataset, meaning all recorded scores either have a label for access with either “private” or “shared”, as well as a label for Value which can be either “low” or “high”. Based on these variables the 4 groups can be created to analyze differences between them.
3.3.4 Control variables
As control variables for this study some consumer demographics are measured. These are gender as a nominal value, age as an ordinal value, country as nominal value, urban or rural citizen as a binary value and education and income as ordinal values.
3.4 Formative research (pre-test) result
As explained in chapter 3.3.2 Intention to use, the formative research, or pretest, is a key part of the Theory of Planned behavior. It not only provides the foundation of the indirect measures in the qualitative questionnaire to measure the intention of the participant, it also
28 provides insight in which beliefs about the topic is questions live among the sample and therefore, to some extent within the population. Figure 5 displays the results of the formative research.
Figure 5 - Salient beliefs result
From this result it is clear that ownership responsibilities as “worries about repair and maintenance” and the expectation of overall cost being high, are the main associations with the PPU models when compared to product ownership. When looking at the subjective norm, so which groups of people or individuals are associated in either a positive or negative way and would approve the use of the PPU models compared to product ownership, age seems to be quite important. In the perceived behavioral control topics as pricing and user experience matter most.
For the quantitative questionnaire, the indirect measures are developed based on these results but asking the participant if he or she considers the belief realistic and how important this is for the participant in questions. The calculated score represents the score for that specific belief which contribute to the computed score of the predictor it belongs to.
29 3.5 Statistical procedure
The data is collected in Qualtrics for easy access, easy participation, and direct feedback of the result. Qualtrics randomly assigned the questionnaires with the different scenarios to the participants regarding access to the product (private/shared) and value (low/high). The data was downloaded as a file suitable for analysis in the IBM statistical program for social sciences (SPSS). Several operationalization steps had to be taken prior to the actual analysis of the data and hypothesis testing including deleting incorrect responses, calculating computed scores, reliability and validity testing and checking robustness. After this the hypotheses are tested with regression, and via MANOVA additional findings are investigated.
30 4.0 Results
In this chapter the operationalization of the data will be described followed by
preliminary tests regarding reliability, validity, and robustness. Then the descriptive statistics after which the hypotheses will be tested. Lastly the results of any additional finds that can be extracted for the data.
4.1 Operationalization of the data
First 22 incomplete responses were deleted, 1 respondent not living in The Netherlands was eliminated together with a response that triggered a bot warning in Qualtrics, leaving 175 valid responses. Secondly, following the procedure of the Theory of Planned Behavior (Ajzen, 2020), the questions regarding belief and belief strength per indirect measure are combined into one score for each measure, resulting in 6 components for Attitude toward behavior (ATB), 6 measures for subjective norm (SN) and 5 measures for perceived behavioral control (PBC) as described in chapter 3.3.2 Intention to use. Each measure has a computed score of between -21 and 21 to be computed into one score for each predictor according to the Theory of Planned Behavior; ATB, SN and PBC.
Third, 2 items from EC and 2 items from TPB were reverse coded since they were counter indicative. For the EC items on the 7-point scale were recalculated by subtracting the score from 8. As the TBP items are a computed score between -27 and 27, the results are multiplied by negative one (-1). Fourth, additional variables were created based on the questionnaire type for “type of access”, “product value” and “Group”. The group variable has 4 categories based on access and value.
The fifth step was to check the validity for NEP and each determinant of TPB. The abbreviated version of the NEP scale has proven valid in previous research (Hawcroft &
31 Milfont, 2010) (Liu, Vedlitz, & Shi, 2014) meaning that results represent what they are supposed to measure. Despite TPB has proven to be a valid construct, most questions in the questionnaire for this study are created based on the formative research (pre-test). Therefore, there is no existing research to confirm validity, and must be checked with statistical testing.
Each of the determinants (ATB, SN and PBC) were tested individually via principal component analysis. The scree plots levelled of strongly after the first component for each predictor (figure 6) with only the first components Eigenvalue substantially >1, and with KMO scores of .700 for ATB, 0.734 for SN and .732 for PBC with a significant result in Bartlett's Test of Sphericity for all three, meaning the items are correlated and suitable within the determinants.
Figure 6 – PCA results
This, including the high extraction values of at least .6 but generally > .8 makes the data suitable for factor analysis (results can be found in the appendix). With the scree plots for each predictor leveling off after the after the first factor, is it can be stated that the individual questions do represent the one determinant.
Figure 7 - PCA result Scree Plots
Sixth, to check the internal consistency, reliability tests were conducted and found to be acceptable. The NEP has a Cronbach’s alpha of .715 over the 7 items. For the measure of intention, the reliability is measured for its determinants; ATB, SN and PBC individually and per group. Only for PBC, for group 1 (α = .663) and 3 (α = .681) the Cronbach’s Alpha was only slightly below 7 despite the low number of only 5 items in PBC. For all other combinations of determinants and group the value was α > .700, view figure 8 for an overview of all CA’s.
Figure 8 - Internal validity scores Theory of planned behavior predictors
As reliability and validity is established, in the 7th step the computed scales are created for EC, ATB, SN and PBC. For each scale, the mean is calculated into a new variable named EC_mean, ATB_factor_mean, SN_factor_mean and PBC_factor_mean respectively.
33 Step 8; to be able to determine the moderating effect of Access and Value, interaction variables are created based on calculation of EC and Access, and EC and Value. EC is mean centered and named EC_centered_mean. From this, the interaction variables SharedAccess_X_EC and HighValue_X_EC are calculated.
4.2 Descriptive statistics
In figure 9 the minimum and maximum score, mean, standard deviation and Pearson correlation can be found for all variables, of which the last 3 are the control variables.
Interestingly the mean for environmental concern (EC) is quite high with 5.6 on a scale of 7 with a minimum of only 3.57, meaning EC is quite high in the sample and no participants can be said to have low EC. From the determinants of the Theory of Planned Behavior, which are measured on the same scale, PBC has the highest mean (6.02) so the perceived control over the decision to choose for the PPU model instead of buying the product seems not to be an objection. The attitude toward the behavior is quite positive in general with a mean of 4.38, however the score for subjective norm (if others approve of the behavior and whether this is important) is just above the middle score of 0, and therefore does not seem to have much effect.
As expected, the determinants of intention (ATB, SN and PBC) are correlated among each other. When a person is positive about the PPU model, it is likely that it effects their view on the subjective norm and perceived behavioral control. There also is a correlation or effect between EC and all determinants of intention (TPB), which already gives a sneak peek regarding H1a, H1b and H1c. However, age group is correlated to EC as well and must be controlled for. At first glance it seems more likely to expect a direct effect from moderation variable “Product Value” then from “Access Type”. The frequencies and descriptive statistics for all demographics can be found in the appendix section.
Figure 9 – correlation matrix
4.3 Hypothesis testing
Prior to running the main regression analyses, the robustness through analyses on assumptions of linear regressions was confirmed. This means that the data is suitable for regression analysis. The data was tested for normality, homoscedasticity and multicolinearity, and the results were all in line with positive results that should be obtained. In the P-P plot, normality was confirmed as the residuals of the regression follow a normal distribution. In addition, the data is homoscedastic as there is no pattern in the scatterplot and the residuals are equally distributed and there is absence of multicollinearity as the VIF values are <1.62. Now the data is validated and prepared to run regression analysis.
As the data is prepared for correlation analysis regarding the direct effects corresponding with hypothesis 1a, 1b and 1c, and the interaction effects or moderation analysis, this will be looked into first.
4.3.1 Direct effects
The results of the measuring direct effects using regression analysis can be found in in figure 7. The first model in this figure shows the effects of the covariates on the three determinants of Intention to use. The only significant effect of a control variable is the area
35 type (being urban or rural) which is negatively related to Perceived behavioral control, meaning the that the perception of consumers to be able to use the PPU model instead of product ownership is significantly lower than in urban areas.
When adding Environmental Concern (EC) to the model (see figure 7, model 2) we can see the effect of EC on the three determinants of intention to use according to the Theory of Planned behavior. First, we look at the effect of EC on ATB corresponding with Hypothesis 1a. The effect of EC on ATB is significant (p = .018) with a standardized beta of β = .198.
Thus, given these results we can conclude that hypothesis 1a, which stated that EC has a positive effect on the Attitude Toward Behavior (ATB) for using PPU, is supported.
Secondly, we look at the effect of EC on the subjective norm regarding PPU in line with H1b. The effect of EC on SN is significant (p = .014) with a standardized beta of β = .195.
Thus, given these results we can conclude that hypothesis 1b, which stated that EC has a positive effect on the subjective norm (SN) regarding the use of PPU, is supported as well.
Lastly, we look at the effect of EC on the perceived behavioral control (PBC) regarding PPU in line with H1c. The effect of EC on PBC is significant (p = .009) with a standardized beta of β = .210. Thus, given these results we can conclude that hypothesis 1b, which stated that EC has a positive effect on the attitude toward using PPU, is supported as too.
As the effects are all significant and quite similar regarding the standardized beta coefficient, we can say that the effect of EC seems quite similar on ATB, SN and PBC, contributing to an increased intention to use the PPU model, instead of buying the product when the opportunity arises. The proportion of the variance explained by EC for ATB R2=.115, SN R2=.044, PBC R2=.078, indicating that the variance of ATB is best explained by the variance of EC.
36 In the third model of figure 10 it can be seen that, from the moderation variables, only product value has a direct effect on some determinants of the TPB, namely on the attitude toward the behavior and subjective norm. However, this does not provide information regarding hypothesis 2 & 3 as we are looking for the moderation effect.
Figure 10 – Regression analysis
4.3.2 Moderation effects
To measure the interaction or moderation effects of Value and Access type, statistical analysis is done according to figure 11. In this figure X=EC. The model is run for each determinant of intention (ATB, SN and PBC) behavior individually as Y, and both moderators individually as W. Meaning the analysis was run 6 times to measure if the regression coefficient of the moderation is significantly different from zero in any of the cases.
Figure 11 – moderation model
For type of access which can either be “shared” or “private”, unfortunately, no significant interaction effects were found on either ATB, SN or PBC. This means we did not find the effect and therefore cannot reject the null hypothesis for H2 and cannot claim a moderating effect. In fact, there seems not to be any effect for Access type on the intention to use a PPU model vs product ownership as a direct cannot be found either.
Unfortunately, product value, being low in case of an e-bike to high in case of an e-car, does not provide any significant interaction effect either. Therefore, we cannot reject the null hypothesis for H3 either. However, for Product Value there does seem to be an effect on the intention to use, more specifically on the attitude toward the behavior and subjective norm. The results of the moderation analysis for both Access Type and Product Value can be found in figure 12.
Figure 12 – Regression for moderation analysis
4.4 Between group analysis
For Access type, no moderation or direct effect, on either ATB, SN or PBC was found.
Therefore, a multivariate analysis of variance (MANOVA) was done to check if some effect of Access type can be found. The results of the multivariate test for Pillai's Trace, Wilks' Lambda, Hotelling's Trace and Roy's Largest Root resulted all as not significant, meaning that the different Access types had no effect on either of the DV’s in the model. This concludes that no significant effect was found and therefore, that when the opportunity arises to choose between the PPU model and product ownership for an e-bike or e-car, the type of access does not seem to influence this decision.
The MANOVA with Product Value as fixed factor did proof to be significant for Pillai's Trace, Wilks' Lambda, Hotelling's Trace and Roy's Largest Root all with p<001. Levene's Test of Equality of Error Variances is not significant so we can assume homogeneity of variance which strengthens the case to assume the multivariate test statistics are robust (Field, 2018).
The between-subjects test resulted (view figure10) in a significant effect of Value on ATB and on SN, but not for PBC, however the effect size is quite small with a Partial Eta squared of
39 .053 for ATB and 0.26 for SN. This means that with a higher product value, it is more likely that a consumer (in the Netherlands) will choose to use the pay-per-use model over the product ownership model when the opportunity arises.
Figure 13 – between subjects testing
40 5.0 Discussion of results
In this chapter the most evident findings are discussed with their implications regarding current literature and practical implications followed by the limitations of this study. Finally, suggestions for further research are given.
5.1 Theoretical and practical implications
This study aimed to empirically test assumptions about the direct effect of environmental concern and the moderation effects of product value and PPU access type, on the intention to use the pay-per-use model vs the product ownership model. As described in the introduction, the PPU models as part of the product service systems are considered as a more circular business model. However, the relation between the consumers’ environmental concern and their intentions to use the PPU system for e bikes or electric cars, especially regarding the type of access to the service, being either private or shared, is largely unexplored. Therefore, the mean research question is about the main effect of environmental concern on Intention to use and the moderation effects of product value and access type.
When stepping into the research gap and initially for the direct effect of environmental concern on the intention to use the PPU system, this can be answered decisively. For a reliable prediction of actual behavior, its immediate antecedent, which is the intention to perform the behavior, is measured. The stronger the behavioral intention, the more likely it is that the behavior will follow when the opportunity arises (Ajzen & Kruglanski, 2019). This is measured via the attitude toward the behavior, the subjective norm, and the perceived behavioral control.
There is a significant positive effect of environmental concern on each of these determinants, meaning that a consumer’s increased environmental concern does lead to a higher intention to
41 use the PPU models instead of buying the product. This means that H1a, H1b and H1c are all accepted.
As we hypothesized for a moderation effect, disappointingly no interaction effect was found for either “access type” or “product value” meaning that the effect of environmental concern was not significantly different when the value was either high or low, or the access was either shared or private. Based on this both H2 and H3 must be rejected. Although it could be due to sample size, the non-significant results did not provide a clear indication regarding this effect.
Despite no interaction effect, there does seem to be a direct effect for product value on the attitude and subjective norm toward the PPU model vs product ownership. When looking into this, it is clear that the attitude toward the behavior and the subjective norm increase when the product value is higher, or in this case if an e-bike is compared to an e-car. Due to the setup of the study, it is possible to take a between groups look into the data. For this data is split into a group for either of the moderation variables to see its individual effect which resulted in a significant difference between groups for low value (e-bike) and high value (e-car) for ATB and SN. Not for PBC. So, it seems that when the product value is higher, the attitude towards the behavior is more positive, and that the opinion or actions of others (subjective norm) matter more.
Regarding theoretical implications, it is interesting to see that in previous research (Elzinga, Reike, Negro, & Boon, 2020) no link was found between environmental concern and the intention to use the PPU model in de the case of pay-per-print. This could be due to the low value and ecological impact of a single print as in this research about electrical transportation devices, a significant effect is found, and the intention to choose the PPU model over product ownership does increase with increased environmental concern. The result that product value
42 and therefore cost concern has a direct effect on the intention to use the PPU model is in line with theory (Gullstrand Edbring, Lehner, & Mont, 2016).
Practically, this presents an opportunity in business model renewal as environmental concern is rising among consumers in general (Chitra, 2007). Despite that the effect size is not extraordinarily strong with an R2 of around 0.1 (ATB=.115, SN=.044, PBC=.078), the intention to use PPU models instead of buying the product will increase along with this trend. Besides this, the Theory of Planned Behavior has proven to be a strong predictor of actual behavior when the opportunity arises (Steinmetz, Knappstein, Ajzen, Schmidt, & Kabst, 2016), and as the behavior in question is not just about the intention to use the PPU, but to choose it over product ownership, this result should be taken into account. Organizations can start experimenting with this model, offering it next to their current model of product ownership to get more familiar with it, preparing for the possible increase in demand, especially regarding higher priced products. This matters because organisations need to reinvent their business to remain competitive (Nunes & Breene, 2011). Anticipating effects of market trends is a key part and therefore, adopting, getting familiar with, and offering the PPU model can contribute to improving the organization’s competitive position. For example, Volkswagen is considering a pay per use model for their autonomously driven vehicles (Steitz, 2021) to be ready to better service their customers in the future.
The theory of planned behavior provides some understanding of the factors that lead to the behavioral intention. From the indirect measures resulting from the TPB formative research in combination with their quantitative result, we find that the top reason to choose for the PPU model instead of buying the product is not to reduce pressure on the environment. The “reduced ownership responsibilities” with a mean computed score of 11,51 is nearly 30% higher than the computed mean score of “reduced environmental concern” of 8.96. The other factor in the
43 top 3 regarding consumer attitude toward the behavior is increased flexibility. View figure 14 for more details.
Figure 14 – Top 3 contributors to intention to use PPU
And finally, which makes sense, the area type affected the perceived behavioral control of consumer regarding the intention to use the PPU model instead of product ownership. As when living in a rural area the shared access pay-per-use type is not realistic, either for the consumer or for an organisation.
The findings of this study are subject to some limitations. First, the data was not randomly sampled. The data was partially collected via the author’s personal network and partially via Prolific. This convenience sampling technique limits generalizability of this study among Dutch consumers. The nature and size of the sample are adequate for the study and relatively diverse regarding gender, age, and income, it is relatively small to generalize to all Dutch consumers. The participants are relatively highly educated, not corresponding with the Dutch population. Furthermore, for example, there seems to be a difference between rural and urban participants, which can make sense regarding the PPU model, specifically the shared access.
When talking about the intention to use the PPU model compared to product ownership, the study is focused on private electrical transportation. So, when in a similar situation, whether
44 the participant would rather purchase the vehicle or use a PPU model. This is beneficial as it generally eliminates issues with the consumer to require the vehicle in the first place, but it only specifically provides insight about the use of pay-per-use for e-bikes and e-cars, reducing generalizability.
Another is that in this scenario the difference between an e-bike and an e-car represents the difference is low vs high value. It can be that other characteristics influence the participants’
perception when indicating a preference between an e-bike and an e-car then the value of the product. Lastly, when measuring intention as a proxy for behavior, there is always uncertainty about whether the intention will actually translate into behavior when an opportunity arises.
Despite the Theory of Planned behavior being an established theory specifically developed to reduce this gap, the gap cannot be eliminated.
5.3 Further research
To be more beneficial, further research should confirm the results on a better and greater sample to be able to generalize these results about the intention to use the PPU model for e-bikes and e-cars to Dutch consumers or a more specific population. This study does provide some preliminary views on the topic and interestingly pointed out that the type of access did not proof to be significant. With a better sample a relation will probably be found between access type and intention to use the PPU model, but it is unlikely to be very profound in general, especially when controlled for rural and urban living area. With a large enough sample, the interaction effect of access on the relation between environmental concern and intention to use the PPU model, as in hypothesis 2 of this study could be reassessed too, as the environmental benefits of sharing equipment can outweigh private use.
45 The claim regarding high and low value products must be validated for other product categories as this is currently related to electric bikes and electric cars. If this claim could be generalized it holds value for organizations when rethinking their business- or revenue model while extrapolating environmental concern among consumers. Other practical implications should be investigated for better utility of the pay-per-use model like a possible threshold for population density after which the model becomes economical interesting, specifically for the shared access version of the PPU model. It should be validated whether the findings are similar in other countries and if the results are different, what the reason is how this can is best approached strategically. And as this research has shown, product value and type does matter in the adoption of the pay per use model, future research could look into this more specifically to find which product types fit the model best.
A more theoretical research direction would be to investigate why there is a link between environmental concern and the intention to use the PPU model. This could be due to a more progressive nature of the person in question, or perhaps a more worrisome person tends to worry about the environment and about ownership responsibilities. This could strongly affect the practical implication from study.
This study aimed to investigate the relation between consumers’ environmental concern (EC) and their intention to participate in the circular economy by choosing a more circular business model. The specific model reviewed in this study is the pay-per-use model which can contribute to the transition from the linear “extract-produce-use-dump” material model to a more circular re-use, reduce and recycle model (Gullstrand Edbring, Lehner, & Mont, 2016). The central question is to what extent will the increasing consumer awareness trend (Chitra, 2007) affect