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Energy Policy

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Reduce, reuse, recycle: Acceptance of CO2-utilization for plastic products

Julia van Heek⁎, Katrin Arning, Martina Zieflea Human-Computer Interaction Center, RWTH Aachen University, Campus Boulevard 57, 52074 Aachen, Germany

A R T I C L E I N F O

Keywords:Carbon capture & utilization (CCU)CO2 plasticsTechnology acceptanceConjoint analysisUser diversityRisk perceptionPerceived knowledge & information aboutCCU

A B S T R A C T

Global warming is a central threat for today's society caused by greenhouse gas emissions, mostly carbondioxide emissions. Carbon dioxide capture and utilization (CCU) is a promising approach to reduce emissionsand the use of expensive and limited fossil resources. Applying CCU, carbon dioxide (CO2) can be incorporatedas raw material during the manufacture of plastic products. While most of the studies address technicalfeasibilities, hardly any systematic research on public perception and acceptance of those specific productsexists so far. This study empirically investigates the acceptance of CCU plastic products (mattress as example).First, interviews with experts and lay people revealed critical acceptance factors (CO2 proportion, saving of fossilresources, disposal conditions, perceived health complaints). Their relative importance was detailed in twoconsecutive conjoint studies. Study 1 revealed disposal conditions and saving of fossil resources as essential forproduct selection, while the products’ CO2 proportion was less important. In study 2, potential healthcomplaints were integrated as well as individual levels of domain knowledge and risk perception, whichsignificantly affected acceptance of CCU products. Recommendations concerning communication strategies forpolicy and industry were derived.

1. Introduction

Greenhouse gas emissions are primarily responsible for climatechange and are – among other sources – caused by energy generationin power plants using fossil fuels like coal, natural gas, and oil, by trafficand transportation, by agriculture, and by manufacturing and con-struction industries (Global Carbon Project (GCP), 2014). Therefore,innovative technologies are designed to save CO2 emissions by emittingno or at least significantly less CO2 (Adger et al., 2013). In this way, forexample, energy generation by renewable resources (Twidell and Weir,2015) as well as the development of electromobility (Held andBaumann, 2011) is supported, e.g., by governments, policy, andindustry, worldwide. Still, numerous technologies (in particular powerplants) eject considerable amounts of CO2 emissions.

Carbon Dioxide Capture and Storage (CCS) and Carbon Captureand Utilization (CCU) of CO2 represent options to save CO2 emissionsby capture and storage (Global Carbon Capture and Storage Institute,2015; Haszeldine, 2009) as well as to use some CO2 from industrialprocesses like fossil fuel power generation as a carbon feedstock for themanufacturing of innovative products and materials (Hunt et al., 2010;von der Assen and Bardow, 2014). In particular, a high potential ofCCU is awarded to the plastics industry due to high demands, highsales volumes, and a huge spectrum of product variants (Markewitzet al., 2012). Mattresses based on CO2 – as a plastic product example –

are currently already produced in the testing stage and will beproduced in series by 2016 (Covestro, 2015a, 2015b). As thesemattresses will soon be available for end-consumers, they are a realisticexample for the investigation of CCU plastic product acceptance. Eventhough the technical, environmental, or economic advantages of CCUtechnology are promising, the success of those innovative products andtechnologies is strongly dependent on the acceptance of consumers, adecisive factor for the success or failure of novel products on themarket (Ram and Sheth, 1989). Therefore, it is a timely topic tounderstand to which extent future users might accept products madeby innovative processes and products. This is of specific impact in CO2

products since CO2 is a negatively viewed material (Van Heek et al.,2016) with hazardous consequences for the planet (Widdicombe et al.,2013).

Previous research on CCU is mostly limited to the concept of thetechnology itself and focuses on technical aspects of manufacturedproducts (e.g., Li et al., 2014; Jones et al., 2015). Understanding theacceptance of CCU is still in an early stage, as future users‘ needs, theirperceptions, and desires are mostly examined quite generic, notconsidering the perception of specific CCU products. To the best ofour knowledge, no study has focused on the acceptance of specificplastic products manufactured by CCU yet. So far, it is ambiguous, howthose products are perceived by the public and which acceptance-related factors might impact public perception and consumers’ deci-

http://dx.doi.org/10.1016/j.enpol.2017.02.016Received 27 October 2016; Received in revised form 10 February 2017; Accepted 13 February 2017

⁎ Corresponding author.E-mail address: vanheek@comm.rwth-aachen.de (J. van Heek).

Energy Policy 105 (2017) 53–66

0301-4215/ © 2017 Elsevier Ltd. All rights reserved.

MARK

sions for or against the usage of such products. As CCU products arenot limited to tech-savvy user groups, but represent every day productsfor the diverse public, it is of importance to examine to what extent theacceptance is impacted by individual user factors. Thus, in this studythe acceptance of CO2-products is focused – taking a mattress asproduct example – and investigating acceptance-relevant factors suchas product characteristics (CO2 proportion), ecological benefits (savingof fossil resources) and potential risks (disposal conditions andperceived health risks). Only after an identification of acceptance-relevant factors it is possible to derive recommendations for commu-nication strategies focusing on aspects, which have to be carefullyconsidered by manufacturers, marketing experts, and policy-makersconcerning the “green” marketing of CCU products as part of an energypolicy strategy.

2. CCU technology and acceptance

In this section, the theoretical background of the study will bepresented. First, different approaches of CO2-utilization and especiallythe use of CO2 for plastic product manufacture are described, followedby the theoretical base of technology acceptance and the subsequentformulation of research questions and aims of the study.

2.1. Carbon dioxide capture and utilization – CCU

Since the 1980s, CCS has been discussed around the world as anoption to save CO2 emissions by capturing CO2 from power plants andsubsequent CO2-storage in order to relieve the environment andcombat climate change (e.g., Markewitz et al., 2012). Currently, thereare numerous large-scale industrial CCS systems (mostly enhanced oilrecovery, e.g., Boundary Dam in Canada) and correspondingly largeamounts of stored CO2 in the US, Canada, Asia, and partly in Europe(Global Carbon Project (GCP), 2014).

In recent years, the options of CCU were discussed and developedby research, industry, and economy as well. Within CCU, there aredifferent ways of utilization: physical and chemical utilization, as wellas the preparation of inorganic materials. Important inorganic materi-als that can be prepared from CO2 are calcite and hydrotalcite forexample, in which CO2 is not or only partially fixed (Yong et al., 2002).During physical utilization, CO2 is involved in a wide range ofapplications: it can be used as refrigerant, for fire extinguishers orcleaning processes (Markewitz et al., 2012), for the carbonation ofbeverages (Duran et al., 2008), and as inert gas for long-term storage offruit and vegetables (Nicolai et al., 2005).

Since the maturity level of technologies for the chemical utilizationof CO2 and potential in terms of usable material volume are quitedifferent, the options of chemical utilization of CO2 are also diverse, butallow a long-term and partly permanent storage of CO2. So far, CO2 hasbeen used for the production of urea, methanol, cyclic carbonates, andsalicylic acid (e.g., Markewitz et al., 2012; International FertilizerIndustry Association, 2009). At present, a high number of technicalinnovations are on the threshold of technological implementation,currently tested and partly implemented in pilot projects (e.g.,Covestro, 2015a, 2015b). In particular, the production of (poly)carbonates from CO2 allows access to high demand and sales volumesin the plastics’ sector. Due to a virtually unlimited availability of CO2,associated economic and ecological savings of fossil resources, and avariety of applications of possible plastic products, this type of CO2-utilization is promising to exploit CO2 as a sustainable resource(Markewitz et al., 2012). By means of direct copolymerization ofepoxides with CO2, for instance, so-called aliphatic polycarbonatescan be prepared (Coates and Moore, 2004) as a starting material for avariety of plastic products. Similarly, the production of other plasticsubstances such as polyol, polypropylene, and polyurethane based onCO2 is possible. By splitting the carbon block (C1), CO2 might be a basisfor manufacturing of plastic raw materials to be processed for building

materials, insulations as well as household articles (e.g., von der Assenand Bardow, 2014). A study on life-cycle-assessment of CO2-utilizationfor polyurethane concluded, that with CO2-utilization a reduction inthe global emissions budget could not be reached, but significantamounts of fossil resources (mostly oil) and by production resultingCO2 emissions can be saved compared to the manufacture of conven-tional products (von der Assen and Bardow, 2014). Recapitulating,CCU products are useful from an ecological as well as economicperspective: on the one hand, the environment is relieved (savings ofemissions and fossil resources), on the other hand, costs (dependenceon expensive fossil resources) can be reduced.

2.2. Technology perceptions and acceptance

In addition to environmental and ecological benefits of a technol-ogy, it is important, to what extent future users accept products, whichare made of innovative – in the case of CO2 – quite negative perceivedmaterials (Shackley et al., 2004). The investigation of consumers’acceptance is necessary to potential success (of the technology as wellas thereby manufactured products) and to give product manufacturersguidelines and recommendations in the development and testing stage,even before final products enter the market (Cooper et al., 2004).

Across social science studies dealing with acceptance of renewableenergy technologies, there is a mixed usage of the terms and conceptsthat deal with “social or public acceptance” and “perception”. From apsychological perspective, “perception” refers to a predominantlycognitive mental process of the awareness and recognition of ideas oritems (Neisser, 1967) and thus, awareness is an essential condition toform a perception of an idea or item. Following this, “public percep-tion” can be defined as understanding and interpretation of technol-ogies and their elements and can be empirically captured by measur-able factors (e.g. awareness, knowledge, and attitudes of people). Incontrast, the term “acceptance” reflects an active or passive approval oradoption of technological processes or products (Schubert and Klein,2006). Consequently, “public acceptance” can be understood as the(active or passive) approval of the development or implementation of(large-scale) technologies, which is already assumed if there is no activeopposition against it (e.g., protests). Looking at Wüstenhagen's moredetailed conceptualization of acceptance – differentiating betweensocio-political, community, and market acceptance (Wüstenhagenet al., 2007) – the scenario-based acceptance analysis in this studyfocuses on the overlap between the socio-political and communityacceptance-axes.

2.3. When assessing technology acceptance

So far, the knowledge about public perceptions of CCU and itsacceptance is quite restricted, especially concerning the acceptance ofspecific products. Here, it is important to understand consumers’perception of benefits and barriers of specific CCU products as wellas to identify conditional acceptance factors, which are essential for asuccessful adoption of innovative technologies and products (Rogers,2003), but also to consider them as starting points for policy efforts.Especially in large scale technologies with a multi-year developmentalprocess, which are often quite abstract and unknown to consumers, it isessential to integrate technology acceptance knowledge as early aspossible in the developmental process in order to adapt the technicaldevelopment (Kowalewski et al., 2012), but also to shape informationand communication strategies (Zaunbrecher & Ziefle, 2016) in linewith timely and participatory policy efforts.

Referring to CCU, potential consumers are confronted with a novel,unfamiliar technology, for which no hands-on experience is present, asspecific products are not yet available on the market. In addition, thetechnology is connected to CO2, which is overall negatively connoted(Van Heek et al., 2016; Shackley et al., 2004). Using traditionalacceptance models (e.g., the technology acceptance model (TAM)

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(Davis, 1989)) to determine public perception and acceptance of CCUis not appropriate, since these models focus on existing technologiesmainly in a job-related usage context. The framework of technologyacceptance by Huijts (2012) is more useful in explaining the acceptanceof sustainable technologies. Based on psychological theories andempirically validated, it assumes, that acceptance is influenced byindividual factors (knowledge, experience), perceived costs, risks andbenefits, affective responses, (dis)trust, fairness of the implementationprocess as well as personal and social norms. Since technologyacceptance is highly context-specific (Arning et al., 2010), it is notpossible to simply transfer this framework to the field of CCU. Instead,in the comparably unexplored research area of CCU product accep-tance, the determinants of CCU-specific cost-, risk-, and benefitperceptions need to be identified in a first step (see Section 3.2;Patton, 2005).

Moreover, acceptance models such as the framework by Huijtsfocus on an evaluation of complete technology scenarios (e.g., hydrogenusage, CCS). Methodologically, these models are based on a structuralequation modeling approach, whose constructs are operationalized ona high level of abstractness, with multiple item responses summarizedin one construct score. Hence, this type of acceptance modeling doesprovide insights into the perception of single acceptance-relevantcriteria of a technical scenario or product (e.g., CO2-proportion ofproducts, waste management of CCU products). Moreover, they do notdeliver practical guidelines or decision criteria for policy approaches.Further, acceptance models do not allow to holistically portray complexdecision scenarios, in which several decision criteria are weightedagainst each other. More specifically, it is not possible to drawconclusions about relationships and interactions of factors concerningCCU product acceptance, e.g., CCU product characteristics or condi-tions of production.

2.4. Public perception and acceptance of CCU

Worldwide numerous acceptance studies have been conductedfocusing on CCS. The results show that the acceptance of CCSdiversified greatly depending on respective countries or regions andespecially the CO2-storage was considered critically (van Alphen et al.,2007; Reiner et al., 2006; Itaoka et al., 2005; Fischedick et al., 2008;Huijts et al., 2007; Krause et al., 2014). From a social acceptanceperspective, it is crucial to find out, how and to what extent the publicperception changes, if CO2 – which has been stored in the case of CCS –is used for the manufacture of plastic products (CCU). Recently, it hasbeen argued that CCU and CCS technologies are confounded in thepublic discussion even though both technologies address differenttechnological issues, but also have different roles regarding environ-mental policy (Bruhn et al., 2016).

To date, some CCU acceptance studies focus on perceived benefitsand risks of the CCU technology itself, e.g., in terms of conceptual,technological, and societal issues (Jones at al, 2015). Further, anotherstudy on the acceptance of CCU included diverse CCU options andenabled an evaluation of these options as “means of tackling CO2

emissions from industry” (Jones et al., 2014): the results show thatmethanol production was ranked as best option of CCU, followed byconcrete manufacture, plastics manufacture, fuel production, enhancedoil recovery (EOR), and using CCS without CCU. Hence, this studyallowed first insights into the evaluation of CCU with regard to a ratherrough product level. As plastics manufacture was evaluated positivelyand represents the option of CCU where end-consumers get most likelyin contact with the respective products (compared to methanol orconcrete), it is important to analyze the acceptance of individual CCUplastic products in detail.

A recent interview study with lay people and technical expertsfocused on perceived benefits, perceived barriers, and the acceptance ofspecific CCU plastics (van Heek et al., 2016). Argumentations from theparticipants revealed that an environmental relief was perceived as the

most important benefit of CCU by both groups. However, expertsconsidered savings of fossil resources and lay people focused on a“global” reduction of CO2 emissions. Whereas, perceived risks forhuman health and the environment (i.e., disposal conditions) weremainly discussed as barriers of CCU by lay people thinking that CO2

can leak out of the products during use and disposal of the products.As the preceding study revealed acceptance-relevant factors accord-

ing to specific CCU plastics, an evaluation and weighting of thesefactors would deliver valuable insights for policy and industry. Hence, aconjoint analysis combined with a traditional questionnaire wasapplied in this study aiming for an examination of the influence of aproduct characteristic (CO2 porportion), ecological benefits (savingfossil resources), potential ecological risks (disposal conditions), andpotential health risks (subjectively perceived health complaints) on theacceptance of CCU products. Further, this approach was used to enablean analysis of relationships and interrelations of the mentionedattributes as well as their levels and to define user profiles and theirinfluence on CCU product acceptance.

3. Method and materials

This section presents the study's empirical approach. After out-lining the objectives of a conjoint analysis, the selection of rationalattributes for the conjoint analysis is detailed as well as the experi-mental design and the questionnaire instrument. Finally, statisticaldata analysis and the sample of the study will be described.

3.1. Conjoint analysis

For the analysis of CCU acceptance the conjoint measurementapproach was applied, an empirical quantitative research method forstudying individual preferences, determining trade-offs, segmentinggroups with similar values, and simulating preferences for novelproducts or scenarios. In the 1960s Luce and Tukey developed theconjoint analysis (CA) approach, which combines a measurementmodel with a statistical estimation algorithm. CA were predominatelyused in economic science and market research to evaluate newproducts or product configurations and to fix price levels (Luce andTukey, 1964, Green and Srinivasan 1990). Today, CA are becomingmore common in a broader range of applied acceptance research, e.g.information systems (e.g., Kowalewski et al., 2012), in environmentalresearch (e.g., Salm et al., 2016), healthcare and medicine (e.g., Ryanand Farrar, 2000), and pharmaceutics (e.g., Aristides et al., 2002). Incomparison to surveys, which are still the dominating quantitativeresearch paradigms in acceptance research, CA enables a holisticexamination of decision scenarios, in which product attributes areweighed against each other. An advantage of CA is the possibility toinvestigate how future or imaginary products and scenarios areperceived by respondents. In CA, respondents assess specific productconfigurations, which consist of multiple attributes and differ fromeach other in the attribute levels. By this, it is possible to simulatehuman decision processes and to decompose the preferences intoseparate part-worth utilities of the attributes and their levels (Chrzanand Orme, 2000; Orme, 2010). Thus, CA yield information about whichattribute influences the respondents’ choice the most and which level ofan attribute is valued highest. Accordingly, preference judgments andresulting preference shares are interpreted as prediction of likelihoodor indicator of acceptance. In this study, a choice-based-conjointanalysis approach (CBC) was chosen, because it mimics complexdecision and product selection processes, in which more than oneattribute influences the final decision (Sawtooth Software, 2009;Sawtooth Software, 2013). In CBC respondents are asked to choosebetween complete scenario concepts. Based on the assessed statedchoices a model about the probability of choice is developed, which isbased on multinomial logit or the probit model (Rao, 2014).

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3.2. Selection of relevant attributes

The most important step in planning, preparation, and implemen-tation of a conjoint analysis is the identification and selection ofrelevant attributes and levels in order to limit the complexity of theresearch design, because it affects the significance as well as thegeneralizability of findings (Rao, 2014). Also, decision-relevant attri-butes have to be selected carefully, which may not only affectrespondents’ preference, but are also relevant for policy, industrialproducers, and associated marketing. In order to identify relevantinfluencing factors on users’ preferences referred to mattresses as CCUproduct example, we analyzed relevant literature and used the resultsof a preceding qualitative interview study (Section 2.2) in whichacceptance-relevant motives and barriers of CCU products wereidentified.

We choose the following attributes in order to investigate theirimpact on the acceptance of CCU for the manufacturing of specificplastic products: different degrees of CO2 proportion in the plasticproduct, different degrees of saving fossil resources, different disposalconditions, and subjectively perceived health complaints.

As mentioned before, the mattress was selected as CCU plasticproduct example, because it is one of the most marketable productsand will soon be produced in series (Covestro, 2015b). Subsequently,for Conjoint Analysis selected attributes and attribute levels areexplained below and shown in Table 1.

CO2 proportion was integrated as attribute in the conjoint analysis.This attribute was relevant from the laypersons perspective -as thepreceding study showed-, because younger and older participantsevaluated the CO2 proportion differently: older participants preferreda low percentage of CO2, as they assumed negative effects on theirhealth and the environment. In contrast, younger participants pre-ferred a high percentage of CO2 in order to relieve the environment asefficiently as possible (van Heek et al., 2016). The CO2 proportion wasimportant from the expert's perspective as well, arguing that theenvironmental benefits were greater, the more CO2 could be incorpo-rated in the products. The levels of the attribute CO2 proportion wereestablished to 10%, 20%, and 30% based on a feasibility study and life-cycle assessment of CCU for plastics manufacture (von der Assen andBardow, 2014). Additionally, a level of 3% CO2 was added in order toexamine to which extent a very low CO2 proportion would impact theacceptance of a CCU mattress. Other product characteristics were notyet considered in this study to ensure an economic research design. Tocontrol for potential effects of further characteristics like comfort,participants were instructed that the product characteristics of the CCUmattress were identical to conventional mattresses.

Similar to existing studies on the general acceptance of CCU (Jones

et al., 2015), both laypeople and experts perceived the environmentalrelief as most important and hence, the efficiency of CO2-utilization forplastics as crucial. In contrast to the experts, lay participants focusedon global savings of CO2 emissions as high as possible, but also arguedabout how many plastic products have to be produced in order toachieve measurable global savings of CO2 emissions (van Heek et al.,2016). Since global savings of CO2 emissions were unrealistic from thetechnical expert perspective, savings of fossil resources (i.e., economic-ally recoverable oil) are used as a measure of CO2-utilization'sefficiency – as suggested by the experts. "Fossil resource depletion"designates the relied characteristic (von der Assen and Bardow, 2014),which was taken as a basis for the definition of attribute levels. Basedon these recent results, levels for saving fossil resources of “5%”, “15%”,and “25%” were selected. In addition, the level “0% saving of fossilresources” was chosen to serve as a baseline.

Disposal conditions were integrated as third attribute in theconjoint analysis. Laypeople perceived disposal conditions as majorbarrier of the CCU technology (van Heek et al., 2016): it wasconsidered to be disadvantageous and not acceptable, if the disposalcaused higher emissions compared to the disposal of conventionalproducts. Likewise, alternatives were devised to capture CO2 emissionsresulting from the disposal again and to store or recycle them as a rawmaterial for new products. From the technical experts’ perspective, thisaspect was not relevant, arguing that the base substance of CO2-products and conventional products would be the same and thus,emissions during disposal should be identical. Since it was a key barrierof CCU perception for laypeople, disposal conditions were integrated asattribute in the study, because we aimed for an evaluation of theacceptance of future users, which cannot rely on profound domainknowledge. When confronted with the lay perceptions, experts statedthat a further carbon dioxide capture and storage as well as a reuse of –during disposal emitted – CO2 is hypothetically possible (van Heeket al., 2016). Based on the perceptions and ideas of laypeople, thefollowing attribute levels were designed compared with disposal ofconventional products: “more CO2 emissions”, “identical CO2 emis-sions”, “less CO2 emissions & storage of CO2“, and “less CO2

emissions & reuse of CO2 for new products”.In the context of CO2, people frequently assume concerns about

health risks (Vendrig, 2003; Wallquist et al., 2010). Concerns abouthealth hazards caused by novel large scale technologies are a well-known consumer fear (even if irrational), reported according todifferent types of technologies, such as mobile communication networkscenarios (Arning et al., 2014), electricity pylons (Zaunbrecher et al.,2015), or overhead transmission lines (Cotton et al., 2013). Equally,interviewed lay participants in the preceding study were concernedabout health risks due to possibly leaking CO2 and assumed effects on

Table 1Attributes and their levels in study 1 & 2.

Attributes - study 1 Description Levels

CO2 proportion Proportion of CO2 in the foam mattress in relation to the other “components” • 3%

• 10%

• 20%

• 30%Saving fossil resources Proportion of fossil resources that can be saved within the manufacturing of a CCU plastic product

compared to the manufacturing of conventional plastic products• 0%

• 5%

• 15%

• 25%Disposal conditions Way of disposal of CCU products if they reach the end of their lifecycle (based on laypeople's

perception)• more emissions

• identical emissions

• fewer emissions by storage of CO2

• fewer emissions & reuse of CO2

Added Attribute - study 2 Description LevelsPerceived health complaints

(PHC)Subjective perceived health complaints that could possibly be noticed due to too high levels of CO2

concentration (based on laypeople's perception)• no PHC

• changes in ambient air

• effects on skin

• effects on cardiovascular system

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ambient air, allergic reactions, effects on the circulatory system up tosuffocation. The interviewed experts, in contrast, perceived health risksas irrelevant, arguing that only the carbon molecule is incorporatedinto the raw material of mattresses and thus, no gaseous CO2 wouldpossibly be able to leak. As the acceptance of “normal” future users hadto be examined, perceived health complaints (PHC) had to beinvestigated. Knowledge on the frequency of health complaints affectedby leaking of CO2 from products is only rarely available (Gale andDavison, 2004). In order to learn about perceptions about health risksin combination with the other attributes, we integrated subjectiveperceived health complaints according to their type into the conjointanalysis. Based on a study about health complaints due to CO2

concentration (Vendrig, 2003), the attribute levels “no PHC”, “changesin ambient air”, “superficial effects on skin”, and “effects on thecardiovascular system” were designed in order to examine differentdegrees of PHC. In order to experimentally separate the effect of healthrisks on other product attributes of the mattress, we presented a firstconjoint study without the attribute of health risks (Study 1) and asecond conjoint study in which health risks were integrated (Study 2).

3.3. Experimental design

Four attributes and each four attribute levels were chosen for theCBC (choice-based conjoint) studies (Table 1). In the CBC tasks, foursets of product configurations were presented and a forced-choiceresponse format was chosen (no “none-option”). All attribute levelswere presented in verbal and pictorial form to improve comprehensi-bility. Prior to the start of the study, the complete questionnaire andvisualization of attributes and levels were checked concerning compre-hensibility and clearness. In study 1, the CBC tasks consisted of thethree attributes disposal conditions, saving of fossil resources and CO2proportion. In study 2, perceived health complaints were added inorder to evaluate the effects of this attribute on preference judgmentsseparately. Respondents took part in both studies (repeated measuresdesign), thereby enabling to interpret the effect of perceived healthcomplaints as decision-criteria immediately. Because a combination ofall corresponding levels would have led to 64 (4×4×4) possiblecombinations for study 1 and 256 (4×4×4×4) combinations for study2, the number of stimuli was reduced. Respondents completed sixrandom choice tasks in each study. Due to this reduction some levels ofattributes might not appear together in one set and participants mostprobably do not evaluate the same scenario configurations. A test ofdesign efficiency was applied to examine whether the design wascomparable to the hypothetical orthogonal design (SawtoothSoftware, 2016). Design efficiency was confirmed with a medianefficiency of 99% relative to a hypothetical orthogonal design.Additionally, the design's standard error served as a characteristicvalue and confirmed the design efficiency as it was below the maximalvalid limit of 0.05 for both studies.

3.4. Questionnaire design

The questionnaire consisted of six parts. First, demographicinformation (age, gender, health status) were collected. In a secondpart, participants’ self-reported technology expertise (four items)(Beier, 1999), their environmental consciousness (nine items)(Schahn et al., 2000) as well as risk perceptions towards CO2-utiliza-tion (eight items) (Fischhoff et al., 1978; Renn, 1989) were assessedeach on a six-point Likert scale (min=1 “I strongly disagree”; 6=max “Istrongly agree”). In the third part, attributes and levels of study 1 (nohealth risks) were introduced in detail. In the choice tasks, participantswere to imagine that they would like to buy a new mattress, which waspartly produced from CO2. Then they were asked to choose the product,they would be most comfortable with (Fig. 1).

The fourth part of the questionnaire (Study 2) started with anintroduction, in which the attribute perceived health complaints was

presented. It was explained that PHC (perceived health complaints)means subjectively perceived and extremely rarely reported healthcomplaints (in order to differentiate PHC from real risks). Again,respondents were asked to choose the product which they would bemost comfortable with (Fig. 2).

In a fifth section, participants evaluated perceived barriers andbenefits of CO2-utilization as well as the willingness to buy and use aCCU mattress (all items are presented in Fig. 9 in Section 4.5) on a six-point Likert scale. In the last part, the self-reported expertise with CCS/CCU (“Are you professionally involved with CCS/CCU?”; responseoptions: yes/no) and the perceived knowledge about CCU (e.g., “Howwell do you feel informed about CCU?”, response options 1=min “not atall”; 6=max “very well”) were determined as well as the factualknowledge about CO2. This matter was assessed by using a quiz (sixquestions which were formulated by CCU experts, e.g., “CO2 is heavierthan air.”; response options: true/false).

3.5. Data analysis

The calculation of relative important scores, estimation of part-worth utilities, and preference simulations were conducted usingSawtooth Software (SSI Web, 2015). First, relative importance scoresof attributes were calculated, which deliver information about howimportant this attribute is relative to all other attributes for the productselection. Second, part-worth utilities were computed and part-worthutilities scores were deduced (Sawtooth Software, 2013). As part-worthutility scores do not allow a comparison of utility scores betweendifferent attributes (Orme, 2010), we used zero-centered differentialspart-worth utilities for which differences between attribute levels canbe compared. Third, preference simulations were carried out whichshow consumer preferences if certain attribute levels changed or werekept constant within a specific scenario (Rao, 2014). As such, specific“what-if”-examinations, e.g., the influence of perceived health risks onrespondents’ preferences, can be analyzed in detail within a predefinedscenario. Finally, different user profiles were defined using Latent classsegmentation analysis (LCA) (Sawtooth Software, 2004).

3.6. Data collection and participants

Data was collected online in Germany in 2015. Participants werereached via e-mail and a link to the questionnaire, disseminated intopically appropriate online forums (e.g., energy technology forum).The completion of the questionnaire took approximately 25 min.Overall, 145 complete data sets were analyzed. Participants’ meanage was 34.9 years (Min=16; Max=80; SD=13.7) with 53.8% males and46.2% females. Regarding participants’ general technology expertise,risk perception, environmental awareness, and knowledge about CO2,CCS, and CCU respective items (see Section 3.4) were summed up andchecked for item reliability. On average, technology expertise wascomparatively high (M=19.52; SD=3.87; min=4; max=24), while CCUrisk perception was on an average level (M=23.86; SD=6.41; min=8;max=48). In contrast, environmental consciousness was high(M=42.56; SD=6.23; min=9; max=54). Based on the results of thequiz about CO2, respondents showed an average (factual) knowledgeabout CO2 (M=3.53; SD=1.26; min=0; max=6). One third (34%) of thesample indicated to have previously dealt with CCS (17% with CCU),while 8.5% had professional experience with CCS and CCU. Themajority of the participants reported to feel “not at all” (26.2%,n=37) or very bad (27.0%, n=38) informed about CCU, while 26.2%(n=37) indicated to feel “rather bad” informed about CCU. In contrast,only 12.8% of the participants felt to be “rather well” informed aboutCCU (n=18). A small minority indicated to feel “well” (5.7%, n=8) and“very well” (2.1%, n=3) informed about CCU.

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Fig. 1. Example of a choice task in study 1.

Fig. 2. Visualization of the additional attribute “PHC” in study 2.

5.9

16.1

28.6

49.3

10.5

37.3

52.2

0 10 20 30 40 50 60

CO2 proportion

saving resources

disposal conditions

perceived health complaints

relative importance (%)

study 1

study 2

Fig. 3. Relative importance scores of the attributes concerning study 1 and study 2.

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4. Results

The root likelihood (RLH) is the geometric mean of estimatedprobabilities associated with the alternatives actually chosen byrespondents, i.e., the nth root of the likelihood. The RLH indicatesthe goodness of a hierarchical Bayes model (varying between 1.0 as(best possible value) and the probability of the different choices in theaverage task as minimal score). For both studies the RLH showed amoderate, but still sufficient goodness of fit (study 1: 0.45; study 2:0.49). First, the relative importance scores of all attributes arepresented for both studies, followed by part-worth utility estimationresults. Then results of user group segmentation are reported, followedby preference simulations depending on specific user profiles.

4.1. Relative importance scores

Disposal conditions (52.17%; SD=10.65) were the main factorinfluencing acceptance (Fig. 3). Saving resources (37.29%;SD=10.58) was the second important criteria and CO2 proportion(10.54%; SD=9.14) was the attribute with the lowest impact on CCUmattress’ acceptance.

After adding perceived health complaints as fourth attribute instudy 2 (Fig. 3), perceived health complaints (49.28%; SD=15.37) weremost crucial, while all other attributes were of minor importancethough the ranking of the other attributes’ importance remained thesame to the first study. Disposal conditions (28.64%; SD=9.30) andsaving resources (16.14%; SD=6.93) were second and third important.Again, CO2 proportion had the lowest important score (5.94%;SD=4.23) with only minimal impact on CCU acceptance.

4.2. Part-worth utilities: meaning of attribute levels

In Fig. 4, the average zero-centered diff part-worth utilities areshown for all attribute levels in both studies. Based on the part-worthutilities, attribute levels with the highest positive and negative evalua-tion and accordingly, product configurations with the highest andlowest potential of acceptance were identified. Within study 1 (no

health complaints), the best product configuration was: disposal with“fewer emissions & reuse of CO2”, resource savings of “25%” and aCO2 proportion of “10%”.

Corresponding to the relative importance of the attribute, disposalconditions had the largest span of part-worth-utilities in study 1 (whichexplains the high importance score of this attribute): disposal with“fewer emissions & reuse of CO2” received the highest utility score,followed by “fewer emissions by storage of CO2”, whereas identicalemissions were slightly rejected and “more emissions” resulted in thelowest utility scores. Regarding the attribute saving resources, savingsof “25%” had the highest score, followed by “15% savings”. Savings of“5%” received a negative utility value, while savings of “0%” obtainedcomplete rejection.

Looking at CO2 proportion. “10%” CO2 proportion receivedslightly positive values, while all other levels obtained slightly negativeor neutral values.

In study 2, the attribute perceived health complaints had thelargest span of values by far: “no” perceived health complaints revealedthe only positive utility value, while “changes in ambient air” and“superficial effects on skin” were perceived negative and “effects on thecardiovascular system” sustained the highest negative value.

4.3. Segmentation of user groups

As we assumed that the decisions and especially the susceptibility toperceived health complaints might not be the same for all respondents,user profiles based on scenario decisions in study 2 were formed (usingLatent Class Analysis (LCA) (Sawtooth Software, 2004)). Using LCA,the sample is post-hoc divided into groups or segments based onsimilar preferences (Green and Krieger, 1991). Thereby, the utilities foreach segment are estimated, along with the probability to belong to thissegment for each respondent. In a next step, the identified segmentsare linked to demographic data and user profiles can be derived, whichenable user-group-specific interventions (Arning, 2017).

A two-group segmentation showed the best data fit (taken fromcriteria percentage certainty, consistent Akaike information criterion(CAIC), and relative Chi square). The characteristics of both segmented

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Fig. 4. Part-worth utilities of the attribute levels of study 1 and 2.

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groups are shown in Table 2.The segmented groups did not differ with regard to age or gender,

but in their reported CCS expertise (as well as CCU, but not significanton a 5% level) and perceived knowledge about CCU.

Group 1 had mainly no expertise with CCS (+ CCU) and lowerperceived knowledge about CCU (in the following denominated as “lessinformed”). Group 2 had more expertise with CCS (+CCU) and a higherperceived knowledge about CCU (in the following denominated as“more informed”). Group comparisons revealed different importancepatterns for both groups of study 2 (Fig. 5). By far, perceived healthcomplaints (PHC) was the most important attribute for the “lessinformed” group (58.4%), followed by disposal conditions (25.9%)and saving resources (13.8%). CO2 proportion was completely unim-portant for this group (1.9%). However, for the “more informed”persons, disposal conditions (47%) was the most important criterion,followed by saving resources (24.7%) and PHC (21.7%) in third place.Again, CO2 proportion was rather unimportant (6.7%).

In Fig. 6, average zero-centered diff part-worth utilities of allattribute levels in study 2 are depicted. Apparently, both groups didnot differ in their optimal product configuration: both groups preferred“no” perceived health complaints, disposal with “fewer emissions &reuse of CO2”, saving resources of “25%”, and “20%” CO2 proportion.However, group-related differences were most prominent within theirsusceptibility to perceived health complaints. “No” PHC were nearlyfour times more important for the “less informed” group than for the“more informed” group and it was the only level that was acceptable forthe “less informed” group. “Changes in ambient air” were accepted bythe “more informed”, but rejected by the “less informed” group whilesuperficial effects on the skin” and “effects on the cardio-vascularsystem” were seen negative by both groups.

Concerning disposal conditions, “more emissions” were stronglymore rejected by the “more informed” than by the “less informed”group. In contrast, “fewer emissions & reuse of CO2” is strongly moreaccepted by the “more informed” group in contrast to the “lessinformed”. The criterion saving resources was generally more impor-

tant for the “more informed” than the “less informed” group: the “moreinformed” respondents revealed higher positive (for “25%” and “15%”

savings) and higher negative utilities (for 5% and 0% savings)compared to the “less informed”. The attribute CO2 proportion wasoverall not decisive, still slightly more important for the “moreinformed” persons. Both groups preferred a CO2 proportion of“20%”, however, the “less informed” showed lowest utilities for a CO2

proportion of “30%”, while the “more informed” persons revealedlowest utilities for a CO2 proportion of “10%”. Perceived knowledgeabout CCU as well as expertise with CCS (and CCU) obviouslyinfluenced acceptance and scenario decisions.

4.4. Sensitivity simulations for segmented groups

In a next step, sensitivity simulations were run to explicitlydetermine the magnitude of the attributes effect and its dependenceon perceived knowledge and CCU expertise (SMRT Software, 2015). Inthe simulation, we examined to which extent the relative preferences ofrespondents for a scenario vary when single levels of an attributechange while other attribute levels are kept constant. Based on thefindings in previously reported part-worth utilities, the levels of theattribute PHC were kept constant and the preference simulation wasrun for the “less informed” (Fig. 7) and the “more informed” (Fig. 8). Ascan be seen, preference values differed extremely across both groups.

For the “less informed” participants, it was particularly striking thathighest and only slightly varying preferences (97.4% to 100.0%)showed up only if “no PHC” were to be expected independently ofother attributes and levels. Any type of impact on health possessedpreference values of 0.0% regarding the attributes CO2 proportion andsaving resources and thus, they were completely rejected. Slightlyfavorable preference values (maximum of 16.3%) only existed withinthe attribute disposal conditions for a disposal with “fewer emissionsand reuse of CO2” and PHC in terms of “changes in ambient air”. Here,health effects for “skin” or “cardiovascular system” received the lowestpreference values with a maximum of 6.1%, also at a preferably low-emission disposal. In summary, health complaints are a “Knockout(KO) criterion” (i.e. an attribute functions as exclusive decision-makerand represents the point where acceptance turns into rejection) for the“less informed” group. Whenever potential health complaints areamong the attributes, nearly no differentiation between other attributestook place. The extent of health complaints acted solely as a decision-maker for a product alternative for the “less informed” groups’ decisionmaking.

Conversely, the preference ratings in the “more informed” group aredifferent (Fig. 8). Although highest preference ratings were alsoachieved if no PHC were to be expected, other product configurationsstill received comparatively high favorable preference values. In con-trast to the “uninformed” group, assumed PHC did not serve as “KOcriterion”. Within the attributes CO2 proportion (at “20%”: −75.6%)and saving resources (at “25%” saving of fossil resources: 70.6%), thelevel “no PHC” reached the highest preference values each, followed by“changes in ambient air” and “superficial effects on the skin” withconsiderable distances. PHC with respect to the “cardiovascularsystem” received minimum values (max. 4%) in combination withthese two attributes and, thus, were totally rejected.

Table 2Description of segmented user groups of study 2.

Group 1 “lessinformed”(n=101)

Group 2 “moreinformed” (n=44)

P

age 34.8 (13.4) 35.2 (14.5) n.s.M (SD)

gender 55.4%; 44,6% 50.0%; 50.0% n.s.(male, female in %)

expertise CCS 26.7%; 72.4% 48.8%; 51.2% < 0.05(yes, no)

expertise CCU 13.3%; 86.7% 25.6%; 74.4% n.s. ( <0.1)(yes, no)

Perceivedknowledge CCU

57.4%; 42.6% 38.6%; 61.4% < 0.05

(low, middle)

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Fig. 5. Relative importance scores of attributes of study 2 for the “less informed“ and the “more informed“ group.

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Within the attribute CO2 proportion, “changes in ambient air”(with up to a maximum of 25.6%) and “superficial effects on the skin”(with up to a maximum of 15.6%) were accepted (each at 20% CO2proportion). In relation to the attribute saving resources, highestpreference values were reached at the highest level of savings of fossilresources (25%): at this point, “no PHC” were also preferred (70.2%),but “changes in ambient air” (15.6%) and “superficial effects on theskin” still received favorable preference values.

The differences between the “less informed” and “more informed”group were especially visible on a closer examination of the attributedisposal conditions. All levels of PHC received higher preference values(were regarded as less negative) by improving of the disposal condi-tions. Thus, highest values were achieved at a disposal with “feweremissions and re-use of CO2”: “no PHC” 95.5%, “changes in ambientair” 95.5%, “effects on the cardiovascular system” 81.0%, and “super-ficial effects on the skin” 70.4%. The high preferences showed that

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Fig. 6. Part-worth-utilities of attribute levels of study 2 for the “less informed“ and the “more informed“ group.

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Fig. 7. Sensitivity analysis with constant PHC levels (“less informed” group).

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disposal conditions acted as primary decision-maker in the “moreinformed” group. Preferences for all other disposal options were alsoremarkably high, whereas “no PHC” and “changes in the ambient air”showed a tendency to be preferred. “No PHC” (70.2%) were favoredwith greatest difference over “change of ambient air” (15.6%), “super-ficial effects on the skin” (12.8%), and “effects on the cardiovascularsystem” (1.4%) only for the disposal with “more emissions.” Overall,the “more informed” respondents assigned high and considerablepreference values to the scenarios in spite of involving different typesof PHC into the study.

4.5. Acceptance of a CO2-mattress

Since the results of the conjoint analysis were strongly influencedby (perceived) knowledge about CCU, we assumed that this also appliesto participants‘ CCU risk perception and in turn affects the acceptanceof CO2-mattresses. Perceived knowledge about CCU (r=−0.391;p <0.01) as well as real knowledge (about CO2) (r=−0.273; p < 0.01)correlated with risk perception significantly: the higher respondents’perceived and real knowledge, the lower is the CCU risk perception. Inturn, all items concerning the acceptance of a CO2-mattress werestrongly affected by risk perception: “beneficial” (r=−0.527;p < 0.01),“useful” (r=−0.537; p < 0.01), “risky” (r=0.670; p < 0.01), “intention tobuy and use” (r=−0.681; p < 0.01). By median split, two risk perceptiongroups were constituted. As shown in Fig. 9, participants with a highrisk perception evaluated CO2-mattresses as significantly less beneficial(M=2.8; SD=1.1) and less useful (M=2.9; SD=1.1) than participantswith a low risk perception (M=3.9; SD=1.1 and M=4.1; SD=1.1). Also,participants with a low risk perception (M=2.3; SD=1.1) concerningCCU assessed CO2-mattresses to be less risky than participants with ahigh risk perception (M=3.9; SD=1.1). Finally, persons with high riskperceptions (M=3.0; SD=1.2) indicated a significantly lower intentionto buy and use a CO2-mattress than participants with low CCU riskperceptions (M=4.6; SD=1.0).

5. Discussion

Previous research on acceptance of CCS and CCU were mostlydirected to process-chain related factors (Li et al., 2014; Jones et al.,2015; Reiner et al., 2006; Itaoka et al., 2005). Hardly any studyinvestigated the acceptance of specific CCU end-products so far.Therefore, the present study evaluated preferences for different pro-duct configurations of a CO2-mattress. The acceptance-relevant attri-butes -CO2 proportion, saving fossil resources, disposal conditions, andperceived health complaints- were derived from literature analysis anda preceding qualitative study. Different product configurations wereformed out of these attributes(-variations) and within the conjointprocedure, respondents were to choose the product configuration theywould be most comfortable with. This procedure delivers informationabout how CO2-mattresses are assessed by potential users and to whatextent they are desired at all. More so, results show which factorsshould be complied by a CO2-mattress and which aspects manufac-turers should especially consider regarding communication and mar-keting strategies in order to meet future users’ demands and require-ments.

5.1. Acceptance of CO2-utilization for mattresses

Overall, the perception of CCU was quite positive showing thatrespondents basically acknowledged the potential of CCU technology asa novel technology.

Additionally, insights into future users’ CCU product acceptancewere won with a detailed evaluation of the importance of single productcharacteristics. The attribute disposal conditions was the key factor forproduct acceptance, followed by the attribute saving resources. Merelythe attribute CO2 proportion did not play a decisive role for CCUproduct acceptance. The results of the attribute levels give informationabout the importance of specific product characteristics and can beused for subsequent studies in the comparatively unexplored field ofCCU product acceptance. Concerning disposal conditions, more emis-sions and a corresponding worse disposal compared to the disposal ofconventional products were completely rejected. In the precedinginterviews, the majority of participants emphasized the outstandingimportance of a sustainable utilization of CO2: if CO2 is used tomanufacture products, people expect a long-term fixation and usageof those products. Reaching identical emissions of the novel productrepresents the turning point in acceptance between rejection andagreement. Disposal conditions have to be at least as good as thedisposal conditions of conventional products to enable acceptance or atleast tolerance of these products at all. Fewer emissions during disposalwere desired and accepted, while reuse of CO2 was clearly favored over

70.2 69.575.6

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Fig. 9. Acceptance of CO2-mattresses depending on participant's risk perception.

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storage, corroborating that respondents are able to differ between CCUand CCS technology. Regarding saving of fossil resources, a linearpattern showed up: the more fossil resources can be saved, the higher isthe acceptance. Savings of 0% and only 5% fossil resources wererejected and reduced acceptance of products, while 15% and especially25% saving of resources were rated positively. Thus, noticeable savingsare necessary to reach CCU product acceptance. In contrast, the CO2

proportion in the mattress had the lowest influence on CCU productacceptance and seem to be a negligible acceptance driver.

Perceived health hazards play a specific role in the evaluationpattern of CCU products. In the preceding interviews lay peopleemphasized perceived health risks as a prominent acceptance factor.When quantifying the perception of health risks in combination withother attributes, we assumed that alleged health effects might over-shadow any other attributes of the CCU mattress. Therefore, weexperimentally separated alleged perceived health complaints as anCCU product attribute by presenting a first conjoint study without theattribute of health complaints and a second study in which healthcomplaints were integrated. Whenever perceived health complaintswere presented as a product characteristic in addition to the otherattributes (Study 2), health complaints evolved to the most decisivefactor in the acceptance decision process. Only scenarios with no PHCreached positive utility and acceptance values, while all other types ofPHC received (partly very high) negative utility values. It is noteworthythat the role of perceived health complaints for CCU acceptance is notequally decisive for acceptance decision in all participants, but isrestricted to lay persons which have no or limited domain knowledge,have lower self-reported technical knowledge in general and high riskperceptions (Rowe and Wright, 2001; Kasperson et al., 1988). Personswith high domain knowledge in CCU and in technology in general, incontrast, do not respond to the extent of perceived health complaints inthe decision simulation. The separation of perceived health risks instudy 1 and 2 allowed to directly assess the weight of perceived healthrisks on acceptance. Still, however, one could critically argue that theeffect of perceived health complaints has been artificially provoked:Following this argumentation, the design of the presented decisionscenarios could have animated risk-susceptible and uninformed per-sons to explicitly consider health risks in their decision and thus,overestimate the drawbacks of this characteristics on acceptance.However, this objection can be ruled out: lay persons did not onlystress potential health hazards in the interviews (without being urgedto) showing that this argumentation pattern is quite frequently in linewith a novel technology. More so, from other technology domains(electricity pylons (Zaunbrecher & Ziefle, 2016), overhead transmis-sion lines (Cotton et al., 2013), mobile communication networks(Arning et al., 2014), invasive medical technology (Ziefle & Schaar,2011), alleged health risks and perceived health complaints revealed tobe a decisive key determinant for acceptance and public perception ofthe respective technologies, independently of the presence of factualrisks. Apparently, lay persons are not able to differ between factual(and proved) health risks and alleged health risks connected to atechnology. Grounding on this undifferentiated perceptions of lay-people, technology experts could argue that it might be effective toignore such unjustified public concerns as no evidence of factual healthrisks is given and to simply hope that the media do not push publicconcerns in this regard. Even though this strategy might be compre-hensible on a first sight there are considerable doubts that this iseffective in the long term. Studies about human risk perception(Fischhoff et al., 1978; Wildavsky and Dake, 1990) show that feelingsof risks in novel technology are archival human reactions, which havebeen nurtured by daily experience for a considerably long time:

“Citizens of modern industrial societies are presently learning aharsh and discomforting lesson – that the benefits from technologymust be paid not only with money but with lives. Whether it be ozonedepletion and consequent skin cancer from the use of spray cans, birthdefects induced by tranquilizing drugs, or radiation damage from

nuclear energy, every technological advance carries some risks ofadverse side effects” (Fischhoff et al., 1978, p. 128).

The public experience with failure and negative consequences in thecontext of novel technologies is rich, and the public might be over-sensitive to suspect health hazards even if there is no evidence for it.This emphasizes the urgent need of a sensible and credible publicinformation and communication strategy which does not ignore thoseprevailing (hidden) public concerns, but to openly and transparentlyinform about novel technologies, the underlying procedures, and thedevelopment in an understandable way. In this context, Leiserowitz(2006) points out that it is essential to not only provide more detailedtechnical information but to consider specifically emotional andaffective responses in public communication in order to strengthenthe public trust in an honest and credible information and commu-nication strategy.

5.2. Impact of user factors: to feel well informed helps!

Our results showed that perceived CCU knowledge and the techni-cal expertise with CCS and CCU strongly affect product preferences.Confirming previous research results (e.g., Li et al., 2014; Jones et al.,2015; Reiner et al., 2006; Curry et al., 2005), the perceived and realknowledge was quite low in our study and hence, the portion ofinformed persons was considerably smaller than the uninformedgroup. It is a common feature with other acceptance studies relatedto energy technologies like CCS (e.g., Itaoka et al., 2005; Huijts et al.,2007), but a new result in the context of CCU, that perceived knowl-edge and risk perception of CCU are strongly connected. This isparticularly important, because risk perception of CCU significantlyimpacts acceptance and intention to use of CCU products. Care shouldbe taken to draw no premature conclusions: information does notcorrespond to knowledge. It is not sufficient to deliver information tofuture users, because future users may not trust and believe thisinformation or sources of information (policy, manufacturers, market-ing). Therefore, communication and information strategies have to bederived from our findings in order to afford and support future users tofeel well informed. Thus, criticism with regard to “green washing” ofcompanies (also remarked as feedback of participants in our study)could be debilitated.

5.3. Limitations and future research desiderata

The applied conjoint analysis approach was useful for assessingpreferences for different CCU product configurations. However, it hassome limitations regarding methodology and content, which have to beconsidered in future studies.

Following the old debate in social science about the gap betweenhuman attitudes and actual behavior, one could criticize that estimatedpreference ratings do not necessarily mirror or predict actual behavior.Thus findings have to be taken with some caution as confirmation orrejection might be lower or higher in real situations (Ajzen andFishbein, 1980).

A second methodical limitation belongs to the restricted number ofattributes, which could be used in a conjoint analysis. A compromisehad to be made between an economic research design with a limitednumber of attributes and the complexity of the comparably newresearch issue. In future studies we will include further aspects (e.g.,product price as potential influencing variable) by using adaptiveconjoint approaches (e.g., ACBC) allowing for a larger number ofattributes and to get a more holistic picture on CCU product accep-tance.

So far, we concentrate on acceptance for CCU products in order tounderstand the active or passive approval or adoption of technologicalprocesses or products. Still, it could be insightful to directly study riskperceptions of respondents. This way, it would be possible to examine ifthe risks are directed to health impacts per se that have the biggest

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impact on people's opinions of the technology or if the risks aredirected to the fact that you are making the technology more personallyrelevant by discussing the health impacts? Here, previous work onaffect heuristics (Kasperson et al., 1988; Sjöberg, 2000) could valuablyinstruct further research.

Further, the sample size of this study was quite small (even thoughwell-balanced regarding age and gender). The low level of perceivedknowledge regarding CCU in our sample confirms previous researchresults of CCS and CCU acceptance studies, in which also low levels ofknowledge (perceived and real) and high information needs weredetermined (Jones et al., 2015; Reiner et al., 2006; Itaoka et al.,2005; Curry et al., 2005).

In addition, the sample was selective (high educational level, ratherhigh environmental awareness, and awareness of climate change) andhence, the underlying methodological approach was a benchmarktesting procedure that probably underestimated the findings. Thus,we aim for a replication of this study, on the one hand, trying to reach alarger and more balanced sample (e.g., education, environmentalawareness). On the other hand, it would also be useful trying to reachmore persons with a higher domain knowledge and persons withhands-on experience with CCU products. This way a more detailedinvestigation and comparison of laypersons (and their “irrationalbeliefs”) with experienced persons would be possible (Slovic et al.,2002; Renn, 1988).

Additionally, it should be recognized that Germany is a special caseinasmuch as the implementation of CCS plants was prevented by publicprotests and thus, the commercial implementation of CCS failed inGermany (Fischer, 2015). It is necessary to consider, whether this alsoresulted in a more critical attitude towards CCU in Germany. Futureusers of other countries and cultures probably show different attitudesand acceptance patterns. Hence, as this study only reflects a Germanperspective, our approach and findings should be replicated in othercountries to compare CCU product acceptance and desires of futureusers depending on different countries, established societal values, andcultures.

6. Conclusion and policy implications

The present study delivered insights into acceptance drivers andbarriers connected to CCU technology and provided a holistic andvalidated methodology to implement technology acceptance in theearly stages of the CCU technology development process.

Considering the potential of CO2-utilization for reduction of CO2

emissions and fossil resource use, it will be vitally important to consultfuture users in CCU product development processes and to informthem about CCU in order to reach broader acceptance of CCU products.It should be considered that purely delivering information about CCUis not sufficient, because future users have to feel well informed andhave to be able to rely on sources of information. Specific user-tailoredinformation and communication strategies can be derived from ourresults concerning CCU product preferences and impacting userfactors. For CCU product acceptance, disposal conditions was the mostimportant attribute, succeeded by saving fossil resources and CO2proportion. Integrating perceived health complaints into the studyeffected significant changes of preferences for the most accepted CCUproduct scenario, in particular for participants who felt to be badlyinformed about CCU. This indicates the necessity of precise informa-tion and communication of potential as well as real risks and barriersconcerning CCU. Although the results cannot be simply generalizeddue to the small and selective sample, the study delivered firstquantitative insights into CCU product acceptance and influencinguser factors.

In the case of CCU and CCU products, public perceptions may beinfluenced not only by risks associated with the products or thetechnology itself but by several other factors such as a lack offamiliarity with the technology, a lack of knowledge and a feeling to

be insufficiently informed as well as contextual and institutionalfactors.

The results of attributes’ relative importance can be used for furtherstudies and should be considered by policy and industry, if CCUproducts shall be large-scale commercialized as “green” products -maybe as part of a energy policy strategy to combat climate change, asit was also suggested by technical experts (mechanical and chemicalengineers) (e.g., van Heek et al., 2016): in detail, the results of ourstudy showed that the communication of the CO2 proportion ofproducts is comparably unimportant and could be disregarded infurther research; however, benefits and barriers of CCU are muchmore important and crucial for acceptance. Environmental relief isconsidered as main benefit of CCU by saving of fossil resources andemissions (both during production and disposal). On the one hand,political and industrial communication strategies should focus on clear,easily comprehensible, and realistic presentations and informationabout potential benefits of CCU and CCU products especially in termsof environmental relief by saving fossil resources and CO2 emissions.For instance, the presentation of fossil resource and carbon dioxideemissions savings could be implemented by using energy efficiencysymbols or established environmental labels or seals (Wiel andMcMahon, 2005) such as it was suggested as feedback of theparticipants of our current and previous studies (van Heek et al.,2016). This implementation could help to increase the probability thatfuture customers (and especially people who felt to be badly informedabout the technology) are able to rely on the information about CCUproducts. However, the use of such symbols and labels has to be legallyand politically regulated. As perceived health complaints represent themain barrier of CCU, users’ concerns about potential complaints haveto be considered by policy and product manufacturers as well even ifactually no health complaints exist or are rather not expected to exist.Hence, on the other hand, political and industrial communicationstrategies should keep in mind these concerns and maybe counteractthem with presenting equally clear, easily comprehensible, and truthfulinformation about results of health and environmental inspectionsconducted by reputable institutions which also have to be legally andpolitically regulated.

Further, our findings allow to develop professional training pro-grams promoting CCU production for the next generation of scienceand industry and represent an effective information base for thedevelopment of effective and transparent public communication stra-tegies.

Heeding these recommendations can possibly contribute to in-crease future users’ or customers’ felt knowledge and informationabout CCU products and the CCU technology and finally, to increasethe probability of accepting CCU products and the CCU technology aspart of a holistic energy policy strategy.

Acknowledgments

The authors owe gratitude to participants for their openness toshare opinions on a novel technology. In particular, we like to thank theChair of Technical Thermodynamics (RWTH Aachen University) underthe lead of Prof. André Bardow for valuable technical input andexchange. Further thanks go to Saskia Ziegler for research assistance.This work has been funded by the European Institute of Technology &Innovation (EIT) within the EnCO2re flagship program Climate-KIC..

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