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Journal of Cleaner Production 418 (2023) 137992
Available online 10 July 2023
0959-6526/© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Designing a digital platform to foster data-enhanced circular practices in
the European solar industry
¨
Assia Boukhatmi
a
,
b
, Roger Nyffenegger
a
,
c
, Stefan N. Gr¨
osser
a
,
*
a
Management Science, Innovation, Sustainability and Entrepreneurship (MISE), School of Engineering and Computer Science, Department Industrial Engineering, Bern
University of Applied Sciences, Quellgasse 12, CH-2502, Biel/Bienne, Switzerland
b
Faculty III Process Sciences, Chair of Circular Economy, Technical University Berlin, Building Z, Straße des 17. Juni 135, 10623, Berlin, Germany
c
Maastricht Sustainability Institute, School of Business and Economics, Maastricht University, Tapijn 11 Building D, P.O. Box 616, 6200 MD, Maastricht, the
Netherlands
ARTICLE INFO
Handling Editor: Cecilia Maria Villas Bˆ
oas de
Almeida
Keywords:
Circular economy
Solar industry
Design science research
Digital platform
Digital product passport
Relational database
ABSTRACT
Enhanced data exchange among different actors and stages of the value chain (VC) is key to mastering the
transition toward a circular solar industry. Data on in-use products and assets enable early assessments of the
adequate circular strategy at the end of the rst life cycle, which includes the reuse of photovoltaic (PV) modules
in a second life cycle. In this context, digital platforms represent a proven technology to facilitate information
exchange between different actors along the VC. However, digital platforms that are targeted specically at
fostering the circular economy (CE) the solar industry are under-researched. We apply Design Science Research
to build and evaluate an artefact for a digital platform that enables collecting comprehensive PV data at different
life cycle stages by involving different solar value chain stakeholders. Data enrichment is incentivized by two
platform use cases that represent the outcome of our study: (i) an assessment schema (devised in collaboration
with a third-party certier) designed to gather information relevant to creating a digital product passport; and
(ii) a photovoltaic reuse online marketplace designed to match the supply and demand for second life panels
(supported by a standardized testing and repurposing infrastructure). Initial insights from Switzerland (our pilot
area) pave the way for implementing the proposed concept. Future studies should investigate scalability to the
European context.
1. Introduction
The need to expand the use of solar energy and other renewable
energy sources to counteract the climate crisis is undisputed. Forecasts
expect a global growth of photovoltaic (PV) installations to a capacity of
840 GW by 2030 and up to 8519 GW by 2050 (IRENA, 2019). However,
the increasing number of new PV systems is posing major challenges in
terms of managing the growing volumes of discarded modules entering
the waste stream at the End-of-Life (EoL) stage (Tao et al., 2020). Thus,
PV waste in Europe is likely to grow from 50,000 tons in 2020 to around
1.5 million tons in 2030 (Graulich et al., 2021).
To offset this increasing amount of waste in the solar industry, the
Circular Economy (CE) paradigm provides a framework for creating a
regenerative system in which resource inputs and waste outputs are
minimized by slowing, narrowing, and closing material and energy
loops (Geissdoerfer et al., 2017). A part of the discarded PV modules is
suitable for a second life, but the increased application of circular
practices in the solar industry still lacks guidelines on preparing PV
modules for reuse (van der Heide et al., 2022), consumer awareness of
second life products, and supporting policies (Harms and Linton, 2016).
In several European countries, moreover, the collection rate of
dismantled PV modules equals only a fraction of previous projections,
which is due to increasing exports to non-European countries (Wade
et al., 2017).
One underlying problem of those market imperfections is insufcient
information exchange between different actors across the solar industry
value chain (VC) (Rabaia et al., 2022). Generally, decient data sharing
leads to a poor understanding of measuring CE and to not using enough
data to formulate circularity indicators (Serna-Guerrero et al., 2022). To
remedy these developments, the EU’s Circular Economy Action Plan
focuses on innovative models. Powered by digital technologies (DTs),
these models provide product information, for example, by means of
* Corresponding author.
E-mail addresses: aessia.boukhatmi@bfh.ch (¨
A. Boukhatmi), roger.nyffenegger@bfh.ch (R. Nyffenegger), stefan.groesser@bfh.ch (S.N. Gr¨
osser).
Contents lists available at ScienceDirect
Journal of Cleaner Production
journal homepage: www.elsevier.com/locate/jclepro
https://doi.org/10.1016/j.jclepro.2023.137992
Received 10 March 2023; Received in revised form 27 June 2023; Accepted 3 July 2023
Journal of Cleaner Production 418 (2023) 137992
2
digital product passports (DPPs) (Walden et al., 2021).
It is plainly evident that digitalization is pivotal to advancing the CE
transition through information sharing (J¨
ager-Roschko and Petersen,
2022a). In recent years, digital platforms have been acknowledged as CE
enablers as they mediate transactions between networks aimed at
minimizing resource inputs and waste outputs (Ciulli et al., 2020a;
Konietzko et al., 2019). Current research discusses the importance of
digital platforms for the CE in various VC stages and industry sectors
(Gerrard and Kandlikar, 2007; Honic et al., 2021; Mossali et al., 2020).
However, a platform capable of accelerating the CE in the solar industry
is still missing.
We therefore aim to develop a digital platform prototype (designated
as “PV asset database”). Our prototype seeks to facilitate circular prac-
tices in the solar industry based on exchanging the data collected across
the PV VC. The prototype is based on two main use cases, which frame
subsequent artefact development. The rst use case involves sustainable
product certication. PV manufacturers can initiate third-party assess-
ment schemes for PV products via a Graphical User Interface (GUI). In
exchange for the data provided, manufacturers receive certication that
distinguishes them from other PV producers. The data thus obtained
help to create a DPP for PV modules. This in turn enables implementing
circular strategies along the VC (e.g., recycling PV modules at the EoL
stage). The second use case involves reusing PV modules in an additional
life cycle. The envisaged PV reuse online marketplace for second life
modules enables (1) PV industry actors to search for single replacement
modules or low-cost modules and (2) collection schemes and recyclers to
access new revenue streams through reselling. The marketplace involves
data based on a reliable testing and repurposing infrastructure. In both
use cases, the information exchanged by actors across the VC is collected
and stored in a relational database schema (RDS), whose structure is an
additional result of our study. We therefore ask:
RQ1: What features of a digital platform foster the application of
circular strategies for PVs?
RQ2: What data do different PV value chain stakeholders require to
implement these strategies?
To address these questions, the paper is structured as follows: First,
the study’s theoretical background is introduced in Section 2, which
represents the relevance cycle according to Hevner’s (2007) design sci-
ence research (DSR) methodology. Section 3 outlines the DSR method-
ology that features our research design. The rigor cycle substantiates our
design knowledge in Section 4, where the design principles and re-
quirements are developed. Section 5builds the core of our project by
developing and evaluating the artefact against the predened re-
quirements, which is dened as design cycle by Hevner (2007). Section 6
discusses the theoretical and practical implications as well as limitations
of our study. Finally, Section 7 concludes our study.
2. Theoretical background
2.1. Circular economy and the role of digital technologies
In recent years, the application of DTs to boost the CE transition has
gained increasing importance among academics, industry, and policy
makers (Okorie et al., 2018; Kristoffersen et al., 2019; Bressanelli et al.,
2022). One important reason for the shift towards digitalization for the
CE is that it potentially accelerates meeting the UN’s Sustainable
Development Goals (Dantas et al., 2021). Pagoropoulos et al. (2017a)
categorized DTs according to three layers: data collection, data inte-
gration, and data analysis. Data collection means obtaining data from
heterogeneous sources (e.g., Internet of Things sensors or physical tags),
while data integration enables contextualizing these data sources in a
specied data architecture (e.g., relational database management sys-
tems; Pagoropoulos et al., 2017b; Sherman, 2014; Kristoffersen et al.,
2020b). In turn, data analysis aims at understanding the contextualized
data to support decision making (Lieder and Rashid, 2016), which can
be enabled by techniques such as machine learning or Big Data analytics
(Weichhart et al., 2015; Moreno et al., 2019). Kristoffersen et al. (2020a)
extended this approach to the “smart CE framework” by two additional
elements: Data transformation levels illustrate the required processes to
transform raw data into insights (Rowley, 2007; Siow et al., 2018), and
resource optimization capabilities describe the different levels of ana-
lytics to substantiate circular-oriented innovation and CE resource
management. Together, these three elements are organized in a struc-
ture to represent the increasing maturity of implementing DTs in busi-
nesses to enable value creation in the context of resource optimization
(Kristoffersen et al., 2020b; Ranta et al., 2021). It becomes evident that
DTs and data management systems are essential to improve the trace-
ability of products, components, and materials information (Lew-
andowski, 2016), in order to enable improved decision making in
remanufacturing (Charnley et al., 2019), waste handling (Scott, 2017),
and closed-loop resource ows (Scheepens et al., 2016). However,
unleashing the full potential of data as a CE driver requires better un-
derstanding how VC stakeholders share information (Despeisse et al.,
2017; J¨
ager-Roschko and Petersen, 2022b; Farooque et al., 2019).
2.2. Digital platforms for the circular economy
Digital platforms represent a promising technology to foster infor-
mation ows between different business areas (Zutshi and Grilo, 2019;
Halstenberg et al., 2017; Demestichas and Daskalakis, 2020) and can
thus enhance sustainable multi-actor interactions enabled by resource
sharing, cooperation, and networking (Grunwald, 2017). While the
growing body of literature on digital platforms uses a broad range of
denitions, Gawer (2009a) and Koskinen et al. (2019) distinguish three
types of platforms. First, transaction platforms are contextualized as in-
terfaces designed to mediate the transactions of goods and services be-
tween different actors in a multi-sided market (Bonina et al., 2021;
McIntyre and Srinivasan, 2017). Second, innovation platforms serve as a
basis for businesses to develop complementary products, services, or
technologies (Gawer, 2009b); they also provide diverse features and
interfaces for different types of innovation. And third, integration plat-
forms combine transaction and innovation platforms (Koskinen et al.,
2019).
From a transaction platform perspective, digital platforms for the CE
are recognized as market places where discarded products and materials
can be exchanged between VC businesses to enhance circular strategies,
such as reuse, remanufacturing, recycling, or EoL management (Berg
and Wilts, 2019). Digital platforms also enable online data storage to
provide and obtain extensive product information for CE purposes, also
referred to as DPP or Material Passports (MPs) (Honic et al., 2021; Çetin
et al., 2021). The emergence of digital platforms across all industry
sectors is perceived as a “platform revolution” (Parker et al., 2016). The
belief that every product and service can potentially be turned into a
platform (Thomas et al., 2014) underpins the increasing growth of CE
platform businesses in the last few years (Ciulli et al., 2020b).
Accordingly, research on digital platforms for the CE is still in its
infancy. Ciulli et al. (2020b) investigated the impact of CE platforms on
food supply chains and identied six brokerage roles that utilize plat-
forms for transferring and recovering resources discarded between
supply chain actors. Schwanholz and Leipold (2020) examined 73
sharing economy platforms by identifying their goals and business
models, while T¨
auscher and Laudien (2018) analyzed 100 randomly
selected online marketplaces to develop a taxonomy for six types of
marketplace business models.
Current research focuses mainly on business models for CE plat-
forms. Therefore, CE platform deployment needs to be examined from a
technological perspective (and is the subject of ongoing research by the
authors). Nevertheless, to bridge the gap between research and practice
regarding DSR (Kuechler and Vaishnavi, 2011), we chose three CE
platform organizations to emphasize the relevance of our study. We
¨
A. Boukhatmi et al.
Journal of Cleaner Production 418 (2023) 137992
3
selected the platforms based on the following criteria: (i) time of exis-
tence; (ii) potential impact on CE transition in the respective industry
sector; (iii) contribution to an academic journal.
The International Dismantling Information System (IDIS) and the Inter-
national Material Data System (IMDS) were created already in the early
2000s in response to the updated EU EoL Vehicle (ELV) Directive, which
requires vehicle manufacturers to use material coding standards that
enable identication during dismantling procedures (Gerrard and
Kandlikar, 2007). To nd information about reusable parts, manufac-
turers grant access to their repair and maintenance websites via IDIS.
Both initiatives appeared to enhance data collection and dissemination
in reverse supply chain operations (IDIS, 2022).
To counteract the adverse impacts of the construction sector as the
world’s largest consumer of raw materials (World Economic Forum,
2016), the Madaster platform was originally developed as part of a
2017–2019 Horizon 2020 project aimed at eliminating waste by
implementing MPs for buildings. In the case of Madaster, the MP delivers
information about the total masses installed and is used to evaluate the
recycling potential and environmental impact of materials (Honic et al.,
2021). Additionally, Madaster incorporates laws and regulations for
sustainable and circular construction to ensure that registered properties
comply with current regulations (Madaster Plattform, 2022).
Finally, the DigiPrime project was funded by a four-year Horizon
2020 program. The project aims to develop a digital platform that
provides data-enhanced circular business models and services to pro-
mote information sharing between stakeholders, not only within their
own VC but also across different industries. Services are classied into
two different categories: VC-oriented services and operational services.
VC-oriented services aim to connect stakeholders from different sectors
through a demand-supply matching tool for suppliers of post-usage
products and (re)manufacturers, life-cycle analysis (LCA), or material
ow monitoring. Operational services include a materials testing and
certication tool to support testing procedures for remanufactured or
recovered goods based on their digital twins. Services will be demon-
strated in six pilots in different industries (Mossali et al., 2020).
Both, the present state of research on digital platforms for the CE, as
well as insights into the current use of CE platforms in practice highlight
the relevance of our study as follows: To the best of our knowledge,
current literature on CE-related platforms lacks studies that examine
how digital platforms connect different VC stakeholders on a common
intermediary to enable data-enhanced circular practices and which
technological setup is required for developing such platforms. Secondly,
no platforms are currently able to enhance the CE transition specically
in the solar industry. Nor is any digital solution in place that would
enable VC stakeholders to access PV information in order to facilitate
circular practices (e.g., reuse or recycling). We argue that the CE tran-
sition in the solar industry has likely escaped policymakers’ attention in
recent years due to prioritizing more energy- and resource-intensive
industries (e.g., construction; EU action plan for the Circular Econ-
omy, 2015). This shortcoming (and research gap) accentuates the need
for a viable solution to implement circular practices in the solar industry
supported by the potentials of digitalization. This intention for the solar
sector requires developing a platform that is capable of accommodating
all relevant stakeholders and of collecting and managing PV data to
foster information ows. Thus, we propose designing a two-component
“PV asset database” artefact: (1) a prototype for a digital platform that
presents two main use cases to incentivize stakeholder interaction for
circular practices; (2) a relational database schema that lays the foun-
dation of the proposed platform by collecting and storing PV data across
the VC.
3. Research approach: design science research
Our qualitative approach follows the Design Science Research (DSR)
methodology. DSR applies a participant-observer perspective, where
outcomes of interventions in a specic context are analyzed and put into
practice (van Aken and Romme, 2012). Thus, DSR in information sys-
tems (IS) represents a research paradigm that encompasses the explan-
atory development and testing of artefacts to solve problems within an
application domain (Hevner et al., 2004) and that enables improving
conditions as desired (March and Storey, 2008; March and Smith,
1995a; Dresch et al., 2015). In recent years, DSR is being increasingly
adopted in studies developing IS for sustainability projects (Diniz et al.,
2021; Gimpel et al., 2021; Matinmikko et al., 2022; Peltokorpi et al.,
2019). Therefore, and following from these studies, DSR is particularly
suitable for producing a conceptual design of a digital platform artefact
for promoting circular practices in the PV industry that incorporates
data from different VC stages.
Our study is structured following the research process proposed by
Hevner (2007) who dened three inherent cycles of DSR (see Fig. 1).
First, the relevance cycle ensures project relevance by identifying and
representing the research problems through contextualizing the appli-
cation environment (Hevner and Chatterjee, 2010). In Section 2, we
demonstrate the relevance cycle of our study by drawing on insights
from theory and practice on the current state of research on CE-related
digital platforms. Second, the rigor cycle provides grounding theories
along with domain experience and adds new, research-based insights to
the knowledge base. We use insights from theory and practice for
elaborating design principles and requirements that guide the artefact
development in Section 4. Finally, the design cycle ensures a tighter
research loop aimed at developing and evaluating a proposed solution
via multiple feedback iterations (Hevner, 2007b; March and Smith,
1995a), on which the results of our study build in Section 5.
4. Research methods
Following on from the DSR, this section leads through the various
steps and corresponding methods for data collection and analysis
(Fig. 2). First, Section 4.1 explains the research methods used in the rigor
cycle, based on practical and theoretical insights. As a result from the
rigor cycle, design principles and requirements are formulated, which
then serve as a foundation for developing and evaluating the “PV asset
database” artefact in the design cycle. The research methods used in the
three iterations during the design cycle are outlined in chapter 4.2.
4.1. Development of design knowledge
The development of design knowledge, materialized in the design
principles and requirements, is based on ndings from theory and
practice, with the practical insights being summarized initially.
The starting point for gaining insights from practitioners and eld
experts was provided by four interviews in spring 2021 with ve
stakeholders of the European solar VC, including two representatives of
the upstream (PV manufacturer, CTO and project manager, both
participated in the rst interview), one expert from the midstream
(Service Provider, CEO), and two experts from the downstream (PV
collection scheme, CEO, and PV refurbishment/reuse company, CEO)
VC. We used interviews as a data collection method as it allows re-
searchers to explore people’s perceptions more in-depth (Kvale, 1996)
and because we believe it lends itself to the exploratory nature of DSR.
Furthermore, our ambition was to cover each VC stage by at least one
representative to gain insight into the current state of the European solar
industry. The interviewees were contacted as part of the Horizon 2020
project Circusol, which allowed us to ensure that all participants were
representatives of the VC and had previous experience with imple-
menting circular practices in the European solar industry. The online
meetings lasted up to 1 h, were conducted in English and followed a
semi-structured interview approach according to Kallio et al. (2016),
whose guidelines include main question themes and follow-up ques-
tions. The interviews were recorded, verbatim transcribed and analyzed
using mind maps. We chose this approach for interview analyses as mind
maps represent a simple method of organizing, visualizing, and
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A. Boukhatmi et al.
Journal of Cleaner Production 418 (2023) 137992
4
connecting complex data in an illustrative manner (Crowe and Shep-
pard, 2012).
First, the interviews served to better understand what processes and
resulting information ows are currently occurring in the VC, from
material procurement to reuse or recycling of EoL PV modules. Second,
we aimed at gathering insights into how stakeholder processes and in-
teractions promote circular practices along the PV VC. Finally, we
explored the requirements of each stakeholder on data needs, features,
and user interactions on a common platform that can facilitate the
application of circular practices through enhanced data management.
The interviews demonstrated the relevance of data from all stages of
the PV VC for several circularity purposes. Some examples include: One
manufacturer outlined the importance of graphical locations and the
installation date to estimate the EoL of their PV modules, but also
pointed out the sensitivity of certain information, such as material
composition. The interviewed service provider emphasized how proper
track records of returned defect PV modules could facilitate handling
decisions. One downstream VC actor pointed out the relevance of ma-
terial compositions to efcient recycling processes (corresponding
quotes are attached in Table 1).
This empirical setting helped us to formulate nine hypotheses (see
Appendix) for evaluating potential incentives of different stakeholder
groups to retrieve and deliver data from other VC actors on a neutral
platform (e.g., H7“Recyclers are interested in product data to align recycling
activities with panel designs and materials used”). The evaluation of these
hypotheses was subject of a survey answered in November 2021 by
eleven participants of the Circusol consortium, including two repre-
sentatives of the upstream (PV manufacturer), four respondents of the
midstream (service provider) and four representatives of the down-
stream (PV collection scheme, PV recyclers) VC. The surveys varied
slightly depending on the stakeholder group and included a total of 19
questions that contained both qualitative and quantitative as well as
open-ended and closed-ended question types. Four of these questions
were used to test the respective hypothesis. For the creation and analysis
of the surveys we used the online tool SurveyMonkey, mainly for its user-
friendly interface and integrated data analysis features. To analyze the
survey responses, we used an interpretive sensemaking approach that
aims at understanding the ndings through the subjective experiences of
the actor (Johnson and Duberley, 2000). Examining the responses
revealed that the majority of all participants were interested in
Fig. 1. Hevner’s (2007) Three cycle view of design science research.
Fig. 2. Steps conducted for developing design principles and requirements based on practice and theory (rigor cycle). Design principles and requirements served as
the basis for developing and evaluating the “PV asset database” artefact in three iterations (design cycle).
¨
A. Boukhatmi et al.
Journal of Cleaner Production 418 (2023) 137992
5
retrieving PV data, be it in the own or in other VC stages. In turn,
manufacturers showed the lowest willingness to share sensitive data
about their PV products, even though their curiosity in obtaining this
information from other manufacturers, mainly for benchmarking pur-
poses, was comparatively high (corresponding quotes in Table 1).
After the outline of the practical part, the theoretical part, which
serves as second basis for developing the design knowledge, is briey
described. Thereby, we point to Watson (2008) who discusses key re-
quirements that companies need to address when exploiting the trans-
formative potential of IS for developing sustainable practices, also
referred to as “Green IS” (Seidel et al., 2010, 2013; Butler, 2011). Hilpert
et al. (2013) built on these requirements and developed six design
principles for “Green IS” which encompass (1) accurate, rich, and timely
data collection, (2) transparency and reliability, (3) performant and
persistant data structure, (4) interfaces for data integration, (5) analysis,
monitoring and reporting features, and (6) information diffusion and
interaction features. These theoretical prerequisites guided the formu-
lation of our design principles from a theoretical viewpoint. Moreover,
the elaboration of subordinate design requirements is aligned with
selected non-functional software engineering requirements (Chung
et al., 2012) that include accuracy, security, and performance attributes.
The outlined practitioners insights, as well as the six design princi-
ples for “Green IS” guided the development of three design objectives for
designing the proposed “PV asset database”. First, the artefact should
facilitate access to product and life cycle information for different
stakeholder groups along the PV VC. Second, it should enable
downstream VC stakeholders (e.g., collection schemes and recyclers) to
gather information about PV products based on a DPP aimed at efcient
reuse and recycling. Third, the artefact should support standardized
demand-and-supply matching of second life PV modules. We achieved
these objectives by adhering to three overarching design principles
(DP1–DP3; see Table 1). Furthermore, interview and survey responses
from practitioners served to develop subordinate design requirements
(DR1–DR11; see Table 1).
4.2. Intermediate stages of artefact development
Having outlined the rigor cycle, this chapter discusses the research
methods of the design cycle (see Fig. 2). While the rigor cycle built up the
design knowledge that is essential for the development of the “PV asset
database” artefact, the design cycle serves to iteratively develop that
artefact. This artefact development was conducted in three iterations,
which led to the conceptual design of a digital platform GUI (Section
5.1) and a RDS for capturing data throughout different stages of the PV
life cycle (Section 5.2). The rst and second iteration were presented
during two feedback discussions in spring 2022, followed by a nal
evaluation in February 2023. These evaluations were formative and
articial as (1) the demonstration was conducted by the researcher
rather than real users, (2) the artefact used was the design rather than
the implemented application, and (3) the application was based on hy-
pothetical use cases (Walls et al., 1992; Wiliam and Black, 2006).
The participants of all evaluations provided no specic knowledge
Table 1
Design principles (DPs) and design requirements (DRs) based on practical insights from interviews and surveys. Attribute designations guiding the denition of
DR1–11 align with a subset of non-functional requirements based on Chung et al. (2012, p. 160).
Design principles (DP) Quote
DP1 Collect and update data from existing data sources and all
stages of the PV VC
•“(…) At the end of the day, you miss a software program that gives you the full VC (…).“(Interview (INT),
collection scheme (CS))
•“Very simple if you look into data sheets from PV panel manufacturers, which you nd online, so this already
helps.” (INT, CS)
DP2 Develop assessment schemes based on extended PV product
data through platform to create DPP
•“Product data can be used for building a material database in sustainability assessment schemes.” (Survey
(SUR), recycler (REC))
•“Suppliers should differentiate from competitors by showing data on the circularity of their product.” (SUR,
Manufacturer (MAN))
DP3 Develop PV online marketplace that involves a reliable
testing and repurposing infrastructure
•“Your database would be a great asset that leads to a standard database, which displays the copies of all the
panels which are available for secondhand sales (…)” (INT, CS)
•“We need to know upfront which modules are candidates for reuse. And we know that there are parameters
which can ensure that.” (INT, PV refurbishment company (REF))
Design requirements (DR)
DR1 Accessibility: Enable full platform access only for selected
parties through login
•“One way is that recycling companies can only access information about material content and to see these
information they would need to login, so you will need a prole that are made only for certain companies.”
(INT, MAN)
DR2 Completeness: Enrich data of technical data sheets with
additional information
•“Most of the data sheets we see from the manufacturers are not complete because they talk about (…) a lot of
technical aspects (…), you never see data sheets which are telling us ‘we use 18 kg of glass, and there is 1.2 kg of
aluminum (…).’” (INT, CS)
DR3 Consistency: Promote consistent data sharing among VC
stakeholders
•“If we disclose information, but other companies are not obliged to, it doesn’t make sense for us to share
information (…). And that would be information related with material content.” (INT, MAN)
DR4 Efciency: Facilitate operation processes to gather product
information
•“(…) It would make it easier for us if clients are asking for details about specic products, we wouldn’t need to
use our own maybe slow processes.” (INT, MAN)
DR5 Inter-operability: Allow different stakeholders to add
information on installations
•“Or maybe even for installers, you have to read the tag to add additional information.” (INT, MAN)
DR6 Security: Ensure platform hosting through an external,
neutral authority
•“The platform should be managed by a third party, with high security levels (…).” (INT, CS)
DR7 Sensitivity: Delimit condential information such as the
materials supplier
•“Material passports can include condential information. None of the companies would like to make public
such information as for example the name of the suppliers of materials used for PV module production.” (INT,
MAN)
DR8 Traceability: Provide PV life cycle history through data
tracking
•“So, often when modules come back, we don’t have a track record. We don’t know where it was used, in which
application? Also, when it goes to a collection scheme, they know it’s a module, but they don’t know the
history.” (INT, service provider, (SP))
DR9 Transparency: Create transparency through data sharing •“Recovery data is relevant to create transparency. Contributing to circularity as PV sector.” (SUR, SP)
DR10 Time performance: Save time expenditure of stakeholders
to gather information about PVs
•“(…) But if clients ask for information about PV panel technical characteristics, this is where we see a lot of time
consumption (…) and changing of the manufacturing system to allow better management of some
information.” (INT, MAN)
DR11 Visibility: Establish different information visibilities
based on respective stakeholder group
•“(…) If we talk only about database, then the information which could be stored in it, some parts should only be
visible to manufacturer, some parts only visible to clients.” (INT, MAN)
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A. Boukhatmi et al.
Journal of Cleaner Production 418 (2023) 137992
6
about the technical development of the artefact and hence were
considered secondary evaluation participants according to Prat et al.
(2015). Therefore, the meetings served to understand which of the
proposed features and information are most essential for VC stake-
holders prior to discussing the technological aspects (e.g., IS infra-
structure) of the concept. However, an external software expert was
consulted frequently in parallel to evaluate the technical feasibility of
the artefact and to conceptualize its technological implementation,
including the required steps and technologies.
To demonstrate the rst and second iteration of the prototype, two 1-
h discussions were conducted with representatives of the Circusol con-
sortium, consisting of an online meeting with ten participants in March
and a presence meeting with fteen participants in April 2022. We
selected this audience because all participants were representatives from
different stages of the European PV VC and thus embody potential users
of the platform. The demonstration covered a presentation of the pro-
totype, including the envisioned use cases and the data to be provided
and accessed by each stakeholder group through the GUI. During the
meeting, participants were able to use the Padlet online software to enter
feedback, ideas, and questions, which were subsequently discussed in
the group.
Based on the participants feedback, both meetings yielded three
major insights that provided relevant impetus for further developing the
artefact. First, attendees doubted the time required for data input and
participation on the platform, especially because covering all stages of
the PV VC demands an extensive data scope. Second, there was uncer-
tainty about the registration of individual PV modules to the database,
which again would require an increased time expenditure. Third, and
based on the rst two insights, it became clear that an implementation of
the artefact at the European level would generate major challenges.
These include a high variety of different actors, data sources, and leg-
islations that could not have been fully addressed given the time horizon
of the study. These three insights encouraged us to change our approach
and explore ways of incorporating data from already existing and pub-
licly available data sources into the artefact development in a more
regional context. This was done to ensure feasibility in time and an
improved user-friendliness. Thus, we exploited publicly available data
sources in the geographic region of Switzerland (see Section 5.2), mainly
to populate the database with sample data and to identify potential data
gaps.
As a result of these changes in our approach, the nal evaluation of
the artefact was subject of an in-person focus group in Switzerland. This
focus group took place in February 2023 with ten representatives
exclusively of the Swiss solar and building industry to discuss the pro-
totypical instantiation with local stakeholders. During this session, we
demonstrated the GUI prototype, including its use cases, features, and
data elds while participants provided their feedback on sticky notes
that were then collected on a white board. Discussion and evaluation
illumined which data are most relevant to build trust in circular prac-
tices along the PV life cycle and provided important impetus for the
future implementation of the artefact.
5. Proposing the “PV asset database” artefact
This section summarizes the design cycle of our study, which in-
cludes developing a conceptual design of a GUI digital platform proto-
type and a RDS. Fig. 3 shows the aspired system architecture of the “PV
asset database” artefact. It consists of the application back-end, which
includes a le system, a SQL database (see Section 5.2), and a server. We
used relevant data from existing data sources (e.g., public registers
containing information about current installations or product charac-
teristics of different PV module types) to generate database records.
Constituting the presentation layer of the system, the front-end enables
user-friendly data access via the GUI. The user groups “member” and
“guest” are assigned different access and role permissions for the ac-
tivities and information displayed on the platform (see below). Watch
this video for a demonstration.
5.1. Digital platform GUI prototype
The requirements set in Section 4.1 provide the starting point for
developing a GUI web-based platform prototype utilizing the interface
design software Figma. The artefact includes a set of use cases. The
corresponding diagram in Fig. 4 presents the interactions between sys-
tems and external entities in a simplied manner (i.e., excluding details
on the system’s internal behavior or the arrangement of the external
Fig. 3. “PV Asset database” artefact system architecture.
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Journal of Cleaner Production 418 (2023) 137992
7
environment). The use case diagram encompasses the three principal
stakeholder groups (“manufacturer,” “service provider,” “recycler”) and
“guest” users (who do not represent solar VC actors). VC actors are
authorized to sign up as platform members, which requires additional
service authentication. Thus, they gain full access to the information
displayed in the database, while guests receive only limited access to
sensitive data (e.g., material contents, which are displayed in the DPP).
All user groups receive full access to the PV reuse online marketplace to
view and purchase inspected PV modules.
5.1.1. Use Case 1: PV assessment schema
Within the scope of the rigor cycle, Section 4.1 revealed the reluc-
tance of manufacturers to release sensitive information about their
products, which mainly concerns the material contents and their origin.
Thus, incentives to obtain this information are based on complementary
services, which can be created through a circular product assessment
schema devised in collaboration with an independent third-party certi-
er. In the given use case, the assessment schema combines LCA-related
information (Sumper et al., 2011), such as materials contents, and
statements corresponding to the Product Circularity Datasheet (PCDS).
The PCDS is based on the Circularity Dataset initiative of Luxembourg’s
Fig. 4. Use case diagram of the “PV asset database” artefact including the different user groups and their access and role permissions.
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Journal of Cleaner Production 418 (2023) 137992
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Ministry of Economy and represents an open-source data template
containing standardized and trustworthy statements on product circu-
larity and a third-party verication process to validate the provided
information (Mulhall et al., 2022). Using the “Add product” view,
manufacturers can rst select the product to be certied from the
existing product inventory. Second, all relevant information on material
contents and PCDS statements (e.g., pre- and post-consumer recycled
contents, chemical composition, or circular pathways) can be added to
the product. Once the manufacturer has completed and stored the data,
the certication process is initiated. The third-party certier is now
requested via email to view and evaluate the information. Once the
manufacturer receives the approval notication, the obtained certi-
cation is released as part of the product information. The information
resulting from the assessment schema forms the basis of the DPP, which
is displayed within the product installation register.
5.1.2. Use Case 2: PV reuse online marketplace
The second use case arising from the proposed life cycle database is
an online marketplace for matching the supply and demand for second
life PV modules. Therefore, PV inspectors can add information about the
reuse potential of assets to the database that corresponds to the infor-
mation stated in the test protocols (see Section 5.2). This enables parties
interested in second life PV modules to search for PV assets via the
interface (“Reuse PV panels”) and to subsequently add assets to the
shopping cart. Implementing this use case may require additional
stakeholders, such as a logistics company (to ship assets) or a service
provider (to install the PV modules at the customer’s site).
5.2. PV life cycle database
The core of the platform is a MySQL relational database schema.
Depending on the stakeholder group signing up to the platform, different
access and role permissions are assigned for adding or changing infor-
mation about products, installations, and assets. Fig. 5 shows the relations
between these three hierarchical levels using an entity-relationship
model, which represents the system components and user groups as
entities. Products correspond to various PV panel types, whose physical
characteristics differ and thus are assigned the producer’s retail desig-
nation. Manufacturers are assigned to select a PV panel type from the
database and to add information in order to initiate product certica-
tion. In turn, a PV asset corresponds to one instance of a certain product
that is brought into circulation. Thus, an installation represents the
accumulation of multiple assets of one or several products at a specic
location. Service provider and plant owner are assigned to add and
update information about existing installations in the database. This
allows downstream VC stakeholders to retrieve information about
existing installations already before decommissioning, thus enabling a
preliminary assessment of further handling. At the end of the rst life
cycle, recycling companies or collection schemes test products for sec-
ond life qualication and can add inspection protocols. PV modules that
fail inspection or lose their functionality already at an earlier stage of the
life cycle (e.g., during usage or transport) can be timestamped (to
indicate the effective EoL date) and thus are released for recycling.
After formulating the design requirements, we established what data
needs to be collected during the life cycle. To this end, we developed a
relational database schema. This is an interrelated set of tables and
associated items. To devise the RDS, we used the database management
system MySQL, mainly for its open-source access, easy handling via the
MySQL workbench server, and its wide range of data types and character
sets. Each row of values in a table has a primary key (ID) and is auto-
matically assigned a unique numerical value. As the logical data in the
model contains several many-to-many (n:n) relations, we transformed
these into two one-to-many-relationships by adding additional bridge
tables, so-called assignments. The nal model (Fig. 6) consists of 38 tables
and 166 elds. To simplify matters, we have omitted the designations of
the respective data types from the tables. Although the PV value chain
consists of various steps and stages, and may vary depending on the PV
panel type (Franco and Groesser, 2021), we classied the entities of the
model and the associated data elds into four categories (see below).
5.2.1. Product-related data
Starting at the end of the production stage of a PV module, several
characteristics and features are assigned to the product, which in the
relational database represents the parent entity. In Fig. 6, the yellowed
tables capture all information about the PV manufacturer, the materials
and components used, PV product’s physical and electrical properties, as
well as additional resources (e.g., product data sheet or certicates).
Together with the PCDS-based information, these entities provide the
basis for the DPP. For instantiation purposes, we used a data set of an
existing module database, provided by the German website Photo-
voltaikforum.com, which collects information from over 100,000 existing
PV product datasheets to populate the provided data elds.
5.2.2. Installation-related data
All entities framed green contain data elds referring to an installa-
tion at a certain location. The system location is encoded in two separate
values, for latitude and longitude, respectively. The installation date is
timestamped and relevant for estimating the provisional PV module’s
Fig. 5. Entity-relationship model showing the relationships between products, installations, and assets.
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Journal of Cleaner Production 418 (2023) 137992
9
EoL based on the given product or performance warranty. The practical
instantiation of the installation data was carried out using an open-
source dataset from the online register of the Swiss Proof of Origin,
which supplies the required information on every PV system registered
in Switzerland. Survey results indicated that the interest in performance
data for CE purposes, especially among downstream VC stakeholders,
was moderate. Moreover, performance data from different inverter
systems require an additional interface to a time-series database and an
aggregation of these data. As this involves signicant implementation
effort, performance data were deliberately excluded from the artefact at
the current stage of development.
5.2.3. Reuse-related data
The blue-framed table test_reuse_potential in Fig. 6 includes all infor-
mation about the inspections required to qualify the reusability of PV
assets after rst usage. For the proposed artefact, reuse potential is
evaluated based on a multi-stage test procedure. This begins with a vi-
sual check to identify physical damages because some defects (e.g.,
fractured front glass, burned front cells, or a bloated junction box) justify
directly recycling the module. If the module passes the visual inspection,
an I–V-measurement can be conducted to determine the remaining
power, which should be at least 80% of the original power. Finally, an
insulation test is required to measure insulation resistance as required
for any electrical device (van der Heide, 2022). After test completion,
assets can be labelled for reuse on the platform.
The fourth data category (grey-framed tables) includes all informa-
tion that is relevant across the entire PV life cycle, (e.g., the utilized
product identier and specic time stamps, which are assigned to assets,
including the production date or the actual EoL).
Fig. 6. RDS including product-related (yellow-framed tables), installation-related (green-framed), reuse-related (blue-framed), and life cycle-related (grey-framed)
data. (For interpretation of the references to colour in this gure legend, the reader is referred to the Web version of this article.)
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Journal of Cleaner Production 418 (2023) 137992
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5.3. Artefact evaluation
We developed an artefact that according to Gregor and Hevner
(2013) is classied under the Level 2 DSR contribution type, thus rep-
resenting the design knowledge as operational principles or architec-
ture. This design knowledge is evaluated based on Prat et al. (2015),
who hierarchized evaluation criteria in the following descending order:
efcacy, usefulness, technical feasibility, accuracy, and performance.
Efcacy (criterion 1) means the extent to which the artefact achieves its
goal in a narrow sense (i.e., excluding situational concerns). We assess
how far each design objective is achieved based on the dened DP1–3
(Section 4.1) as follows:
•The artefact provides a relational database schema that enables
collecting and updating data from existing data sources and at
various stages of the PV value chain.
•The platform prototype conceptualizes an assessment schema to
enable the collection of extended product data that creates the DPP.
•The platform prototype conceptualizes a PV online marketplace that
involves data on the reuse potential of PV modules to support a
reliable testing and repurposing infrastructure.
Usefulness (criterion 2) means the extent to which the artefact’s
structure includes all the necessary elements and their interrelations.
The artefact can be considered useful as it provides a database infra-
structure that interconnects products, installations, and assets, thus
covering the different stages of the PV life cycle. Second, it conceptu-
alizes a digital platform GUI that logically builds on this infrastructure.
Although this concept is currently demonstrated by an illustrative sce-
nario, it is useful because it clearly visualizes the use cases and user
groups, and thereby facilitates future technological implementation.
The same applies to technical feasibility (criterion 3), which involves
evaluating, from a technical viewpoint, how readily a proposed artefact
can be built and operated. The technical feasibility of the artefact was
validated by the aforementioned expert (Section 4.2), who had already
devised a technical approach for artefact implementation (including a
detailed technological infrastructure).
Accuracy (criterion 4) describes how far artefact output and the
expected output correspond. We justify output accuracy by the fact that
existing data sources for prototype instantiation are also exhausted
during later implementation in order to cover as many stages of the
value chain as possible. Nevertheless, this might mean that the extent of
data can be further limited, as some information strongly depends on
stakeholders’ willingness to release it.
Lastly, performance (criterion 5) describes the degree to which the
artefact performs its functions within the given temporal or spatial
constraints. We argue that the artefact does not pose any performance-
relevant problems given the implementation of the current concept.
We do, however, acknowledge that as the database grows larger, certain
precautions (e.g., monitoring of SQL user queries) need to be taken to
counteract performance limitations. In sum, the developed design
knowledge can be considered practically viable as it meets the pre-
dened requirements of our study and thus provides the potential to
digitally assist circular activities for PV modules across different life
cycle stages.
6. Discussion
This paper presents design knowledge for a “PV asset database”
artefact to digitally enable circular strategies for the solar industry.
Using DSR methodology, we developed a concept for a digital platform
and an associated relational database schema which both facilitate in-
formation exchange between different VC stages and stakeholders. This
approach was guided by three design principles and eleven subordinate
design requirements, which were informed by practical insights and the
six design principles for “Green IS” (Hilpert et al., 2013). Following
three iterations with different representatives of the European solar in-
dustry, we adjusted our concept and nally evaluated our design artefact
on a set of evaluation criteria comprising efcacy, usefulness, technical
feasibility, accuracy, and performance (Prat et al., 2015).
6.1. Research implications
This paper provides the following implications for research: First,
although digital platforms have been already explored as CE enablers
(Ciulli et al., 2020a; Konietzko et al., 2019), current research still lacks
insight into the potentials platforms provide to accelerate CE adoption in
the solar industry. We therefore propose a concept for a digital platform
to enhance information exchange across different stages and stake-
holders of the PV value chain. Additionally, our selected use case ex-
tends existing studies on data-driven practices for the CE transition
(Pagoropoulos et al., 2017b; Kristoffersen et al., 2020b; Ranta et al.,
2021) by elaborating which datasets support the implementation of
various circular strategies throughout the product life cycle, such as
reuse and recycling.
Second, our artefact describes two use cases for promoting circular
PV practices based on improved data collection. Starting at the begin-
ning of the value chain, we propose a circular PV assessment schema to
gather extended information on PV products that are relevant for
creating a digital product passport. We thus complement previous work
on DPPs (e.g., Honic et al., 2021; Çetin et al., 2021), not only by pro-
posing the rst-ever approach to a PV product passport, but also by
incorporating additional circularity statements, which consider other
pathways (e.g., reuse; Mulhall et al., 2022) besides recycling. We also
extend theoretical research on the role of CE transaction platforms (Berg
and Wilts, 2019) by providing a second use case, which utilizes the
proposed artefact to match demand and supply for second life PV assets.
Moreover, we exploited existing data sources in our pilot area
(Switzerland) to support the elaboration of a RDS, thus ensuring that PV
data are properly collected and made accessible to VC actors. As such,
our research extends existing approaches, such as the IDIS platform,
which enables performing EoL activities based solely on product data
(Gerrard and Kandlikar, 2007), by adding information about installed
PV systems and individual assets to better forecast and execute an
appropriate circular strategy at the EoL stage.
6.2. Practical implications
We developed our design principles and requirements, as well as
adjusted and evaluated our nal concept, in collaboration with practi-
tioners from the European solar industry. This approach aligns our
concept with the dynamics of the PV sector and enriches our results with
the practical insights of the involved stakeholders. In turn, our proposed
design knowledge can support industry in adopting data-driven circular
practices at the rm and at the VC level.
Our artefact has several practical implications: The rst use case
includes an assessment schema capable of assisting third-party certiers
and PV manufacturers in automatizing certication processes. The
artefact saves time and costs as requires neither manual data entry (e.g.,
in a Word le) nor the involvement of intermediate bodies. Additionally,
we argue that manufacturers can be incentivized to disclose extended
product information as the received certication serves differentiation
from other producers. Clearly assigned data visibility ensures that only
selected users can access sensitive information.
Our second use case supports an extensive testing infrastructure by
facilitating access to repurposed PV panels via the reuse online
marketplace. The enhanced traceability of the tested assets means that
this use case contributes to a more controlled second life PV market in
Europe. In the long-term, it will counteract challenges related to illegal
exports to developing countries (Okoroigwe et al., 2020). Additionally,
collection schemes and recyclers can create new revenue streams by
reselling second life PV modules that would otherwise be recycled.
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Journal of Cleaner Production 418 (2023) 137992
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Moreover, as the proposed concept follows an approach that can be
generalized product-independently, our framework provides the basis
for future extensions to other industry sectors.
Additionally, we have incorporated practical data (from
Switzerland) to investigate the potentials of existing and publicly
available data sources. We argue that our approach can be transferred to
other countries with similar data sources, such as Germany, where PV
installations are digitally recorded in the Market Master Data Register.
However, every instantiation, whether in another product segment or
geographic region, demands further adjusting data collection and the
sources from which the required information is obtained.
6.3. Limitations
Besides the described opportunities, various barriers impede the
future adoption of the proposed artefact. Tu et al. (2017) and Rabaia
et al. (2022) mentioned the low quality and shortage of practical data in
the PV value chain (including data gaps, unrepresentative data, and data
inaccuracy). Thus, it cannot yet be guaranteed that all stages of the PV
VC can be illustrated with data. Furthermore, no comprehensive infra-
structure currently exists for testing and recertifying second-life mod-
ules, which means that hardly any data from downstream VC processes
can be transferred to the database at present. Rauer and Kaufmann
(2015) noted the lack of supply chain transparency, which we attribute
to a low willingness to share information, especially in the upstream VC.
Hence, it is uncertain whether realizing the presented use cases will
effectively enhance information exchange and thus transparency among
PV industry stakeholders.
In addition, challenges potentially arising when implementing the
artefact should be considered: They include obstacles to practicality and
ease of use, maintenance and data updating, as well as implementation
and usage costs, all of which ensure the long-term viability of the plat-
form. Furthermore, the question of ownership would need to be thor-
oughly addressed to ensure platform trustworthiness (by a neutral
entity).
Beyond these limitations, one of the most signicant barriers is the
lack of legal incentives in the solar industry. Initiatives in other industry
sectors such as the ELV Directive have shown how legal incentives and
regulations promote data sharing on a neutrally managed platform, and
thereby contribute to implementing circular strategies (Gerrard and
Kandlikar, 2007). However, this development may take a new turn with
the upcoming update of the Ecodesign Directive, which promotes the
introduction of DPPs to electronically register, process, and share
product-related information among supply chain businesses, authorities
and consumers to increase data transparency (European Commission,
2022).
7. Conclusion and future research
Global crises accentuate the need for smart solutions able to expand
the use of solar energy without intensifying resource depletion. We have
therefore proposed designing a digital platform potentially able to
counteract the current challenge of insufcient information exchange
within the solar industry, and thereby to foster the CE transition. The
resulting platform artefact comprises (1) two use cases that promote
data collection among different VC stages and (2) a relational database
schema that logically maps the required information to realize these use
cases.
Our study makes two main contributions. First, we introduce a novel
approach to supporting the implementation of circular practices in the
solar industry based on data that is shared between VC stakeholders on a
common intermediary. We have also highlighted the data required
across the PV life cycle to enable these practices. Second, our artefact
can enable more controlled second life operations, which involve
improved traceability and testing infrastructure for reuse. Additionally,
extensive DPP-based product information means the platform facilitates
efciently recycling PV modules otherwise unsuitable for a second life
cycle.
One limitation of our study is the comparatively small number of
European solar industry stakeholders that participated in our study,
resulting in a limited data set for developing, demonstrating, and eval-
uating the artefact. We acknowledge this limitation as part of the
explanatory nature of the chosen DSR methodology. As the pilot
implementation of the prototype will be followed up in Switzerland,
further development will need to involve additional stakeholders and
iterations.
This paper provides a starting point for future research, among
others, on the automation potential of data entry to minimize platform
users’ implementation effort. This adjustment might involve automating
the registration of new assets on the platform (e.g., by scanning the
product identier of each PV module). Future studies might also
investigate connecting the proposed artefact to other databases and
systems to enable frequently updated data transfer from one IS to
another via Application Programming Interface. Another challenge that
should be tackled in future research is the integration of time series-
based performance data to more precisely forecast performance degra-
dation and thus the reuse potential of PV assets. Finally, future studies
should discuss the scalability of the proposed concept to the European
level, which would require closely examining the relevant legislation,
the involved actors, and the available data sources.
CRediT authorship contribution statement
¨
Assia Boukhatmi: Conceptualization, Project administration,
Methodology, Investigation, Visualization, Writing – original draft,
Writing – review & editing. Roger Nyffenegger: Project administration,
Conceptualization, Investigation, Writing – original draft, Writing – re-
view & editing. Stefan N. Gr¨
osser: Supervision, Conceptualization,
Validation, Funding acquisition, Investigation, Writing – review &
editing.
Declaration of competing interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
Data availability
The data that has been used is condential.
Acknowledgments
The authors acknowledge the valuable contribution of all project
partners within the project Circusol (call: H2020-EU.3.5.4). This project
has received funding from the European Union’s Horizon 2020 research
and innovation programme under grant agreement 776680.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.jclepro.2023.137992.
Appendix
Hypotheses (H1–H9) to validate interest of PV value chain stake-
holders in using a common platform to foster circular practices.
Hypotheses evaluated by manufacturers (H1–H3):
H1. Manufacturers are interested in product data to predict market
developments and improve their own products.
H2. Manufacturers are interested in usage data to underline the
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Journal of Cleaner Production 418 (2023) 137992
12
reliable performance and therefore the quality of their panels, possibly
with a label.
H3. Manufacturers benet from recovery data of all panels to draw
conclusions on suitable designs. In addition, they can act as buyers of
their own second-hand panels or raw materials.
Hypotheses evaluated by service providers (H4–H6):
H4. Service providers are interested in product data in order to be able
to incorporate ndings regarding modularity, material composition, etc.
into their panel selection and thus offer better advice.
H5. Service providers are interested in usage data to gain insights
regarding the performance of other panels and system installations.
H6. Service providers benet from recovery data of all panels to have
better conclusions on reuse and recyclability of panels. In addition, they
can act as buyers of second-hand panels if necessary.
Hypotheses evaluated by recyclers (H7–H9):
H7. Recyclers are interested in product data to align recycling activ-
ities with panel construction methods and materials used.
H8. Recyclers are interested in usage data to better plan recycling
activities because it is known when which panels become available.
H9. Recyclers benet from recovery data to better assess aggregate
recovery of individual panel types.
References
Berg, H., Wilts, H., 2019. Digital platforms as market places for the circular
economy—requirements and challenges. NachhaltigkeitsManagementForum |
Sustain. Manag. Forum 27 (1), 1–9. https://doi.org/10.1007/s00550-018-0468-9.
Bonina, C., Koskinen, K., Eaton, B., Gawer, A., 2021. Digital platforms for development:
foundations and research agenda. Inf. Syst. J. 31 (6), 869–902. https://doi.org/
10.1111/isj.12326.
Bressanelli, G., Adrodegari, F., Pigosso, D.C.A., Parida, V., 2022. Towards the smart
circular economy paradigm: a denition, conceptualization, and research agenda.
Sustainability 14 (9). https://doi.org/10.3390/su14094960. Art. 9.
Butler, T., 2011. Compliance with institutional imperatives on environmental
sustainability: building theory on the role of Green IS. J. Strat. Inf. Syst. 20 (1), 6–26.
https://doi.org/10.1016/j.jsis.2010.09.006.
Çetin, S., De Wolf, C., Bocken, N., 2021. Circular digital built environment: an emerging
framework. Sustainability 13 (11). https://doi.org/10.3390/su13116348. Art. 11.
Charnley, F., Tiwari, D., Hutabarat, W., Moreno, M., Okorie, O., Tiwari, A., 2019.
Simulation to enable a data-driven circular economy. Sustainability 11 (12). https://
doi.org/10.3390/su11123379. Art. 12.
Chung, L., Nixon, B.A., Yu, E., Mylopoulos, J., 2012. Non-Functional Requirements in
Software Engineering. Springer Science & Business Media.
Ciulli, F., Kolk, A., Boe-Lillegraven, S., 2020a. Circularity brokers: digital platform
organizations and waste recovery in food supply chains. J. Bus. Ethics 167 (2),
299–331. https://doi.org/10.1007/s10551-019-04160-5.
Ciulli, F., Kolk, A., Boe-Lillegraven, S., 2020b. Circularity brokers: digital platform
organizations and waste recovery in food supply chains. J. Bus. Ethics 167 (2),
299–331. https://doi.org/10.1007/s10551-019-04160-5.
Crowe, M., Sheppard, L., 2012. Mind mapping research methods. Qual. Quantity 46 (5),
1493–1504. https://doi.org/10.1007/s11135-011-9463-8.
Dantas, T.E.T., de-Souza, E.D., Destro, I.R., Hammes, G., Rodriguez, C.M.T., Soares, S.R.,
2021. How the combination of circular economy and industry 4.0 can contribute
towards achieving the sustainable development goals. Sustain. Prod. Consum. 26,
213–227. https://doi.org/10.1016/j.spc.2020.10.005.
Demestichas, K., Daskalakis, E., 2020. Information and communication technology
solutions for the circular economy. Sustainability 12 (18). https://doi.org/10.3390/
su12187272. Art. 18.
Despeisse, M., Baumers, M., Brown, P., Charnley, F., Ford, S.J., Garmulewicz, A.,
Knowles, S., Minshall, T.H.W., Mortara, L., Reed-Tsochas, F.P., Rowley, J., 2017.
Unlocking value for a circular economy through 3D printing: a research agenda.
Technol. Forecast. Soc. Change 115, 75–84. https://doi.org/10.1016/j.
techfore.2016.09.021.
Diniz, E.H., Yamaguchi, J.A., Rachael dos Santos, T., Pereira de Carvalho, A., Al´
ego, A.S.,
Carvalho, M., 2021. Greening inventories: blockchain to improve the GHG protocol
program in scope 2. J. Clean. Prod. 291, 125900 https://doi.org/10.1016/j.
jclepro.2021.125900.
Dresch, A., Lacerda, D.P., Antunes, J.A.V., 2015. h. In: Dresch, A., Lacerda, D.P.,
Antunes, J.A.V. (Eds.), Design science researc, Design Science Research: A Method
for Science and Technology Advancement. Springer International Publishing,
pp. 67–102. https://doi.org/10.1007/978-3-319-07374-3_4.
EU action plan for the Circular Economy, 2015. (testimony of European Union). https://e
ur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52015DC0614.
European Commission, 2022. Proposal for Ecodesign for Sustainable Products
Regulation. https://environment.ec.europa.eu/publications/proposal-ecodesign-su
stainable-products-regulation_en.
Farooque, M., Zhang, A., Thürer, M., Qu, T., Huisingh, D., 2019. Circular supply chain
management: a denition and structured literature review. J. Clean. Prod. 228,
882–900. https://doi.org/10.1016/j.jclepro.2019.04.303.
Franco, M.A., Groesser, S.N., 2021. A systematic literature review of the solar
photovoltaic value chain for a circular economy. Sustainability 13 (17). https://doi.
org/10.3390/su13179615. Art. 17.
Gawer, A., 2009a. Platforms, Markets and Innovation. Edward Elgar Publishing.
Gawer, A., 2009b. Platforms, Markets and Innovation. Edward Elgar Publishing.
Geissdoerfer, M., Savaget, P., Bocken, N.M.P., Hultink, E.J., 2017. The Circular Economy
– a new sustainability paradigm? J. Clean. Prod. 143, 757–768. https://doi.org/
10.1016/j.jclepro.2016.12.048.
Gerrard, J., Kandlikar, M., 2007. Is European end-of-life vehicle legislation living up to
expectations? Assessing the impact of the ELV Directive on ‘green’ innovation and
vehicle recovery. J. Clean. Prod. 15 (1), 17–27. https://doi.org/10.1016/j.
jclepro.2005.06.004.
Gimpel, H., Graf-Drasch, V., Hawlitschek, F., Neumeier, K., 2021. Designing smart and
sustainable irrigation: a case study. J. Clean. Prod. 315, 128048 https://doi.org/
10.1016/j.jclepro.2021.128048.
Graulich, K., Bulach, W., Betz, J., Dolega, P., Hermann, C., Bilsen, V., Bley, F.,
Watkins, E., Stainforth, T., 2021. Emerging Waste Streams – Challenges and
Opportunities.
Gregor, S., Hevner, A.R., 2013. Positioning and presenting design science research for
maximum impact. MIS Q. 37 (2), 337–355.
Grunwald, A., 2017. In: Zacher, L.W. (Ed.), Technology assessment and policy advice in
the eld of sustainable development, Technology, Society and Sustainability:
Selected Concepts, Issues and Cases. Springer International Publishing, pp. 203–221.
https://doi.org/10.1007/978-3-319-47164-8_14.
Halstenberg, F.A., Lindow, K., Stark, R., 2017. Utilization of product lifecycle data from
PLM systems in platforms for industrial symbiosis. Procedia Manuf. 8, 369–376.
https://doi.org/10.1016/j.promfg.2017.02.047.
Harms, R., Linton, J.D., 2016. Willingness to pay for eco-certied refurbished products:
the effects of environmental attitudes and knowledge. J. Ind. Ecol. 20 (4), 893–904.
https://doi.org/10.1111/jiec.12301.
Hevner, 2007. A three cycle view of design science research. Scand. J. Inf. Syst. 19.
Hevner, A., Chatterjee, S., 2010. In: Hevner, A., Chatterjee, S. (Eds.), Design science
research in information systems, Design Research in Information Systems: Theory
and Practice. Springer US, pp. 9–22. https://doi.org/10.1007/978-1-4419-5653-8_2.
Hevner, March, S.T., Park, J., Ram, S., 2004. Design science in information systems
research. MIS Q. 28 (1), 75–105. https://doi.org/10.2307/25148625.
Hilpert, H., Kranz, J., Schumann, M., 2013. Leveraging green IS in logistics: developing
an artifact for greenhouse gas emission tracking. Bus. Inf. Syst. Eng. 5 (5), 315–325.
https://doi.org/10.1007/s12599-013-0285-1.
Honic, M., Kovacic, I., Aschenbrenner, P., Ragossnig, A., 2021. Material Passports for the
end-of-life stage of buildings: challenges and potentials. J. Clean. Prod. 319, 128702
https://doi.org/10.1016/j.jclepro.2021.128702.
IDIS, 2022. https://www.idis2.com/discover.php.
International Renewable Energy Agency, 2019. Retrieved June 20, 2022, from. https://
www.irena.org/-/media/Files/IRENA/Agency/Publication/2019/Nov/IREN
A_Future_of_Solar_PV_2019.pdf.
J¨
ager-Roschko, M., Petersen, M., 2022a. Advancing the circular economy through
information sharing: a systematic literature review. J. Clean. Prod., 133210 https://
doi.org/10.1016/j.jclepro.2022.133210.
J¨
ager-Roschko, M., Petersen, M., 2022b. Advancing the circular economy through
information sharing: a systematic literature review. J. Clean. Prod. 369, 133210
https://doi.org/10.1016/j.jclepro.2022.133210.
Johnson, P., Duberley, J., 2000. Understanding Management Research. SAGE
Publications Ltd. https://doi.org/10.4135/9780857020185.
Kallio, H., Pietil¨
a, A.-M., Johnson, M., Kangasniemi, M., 2016. Systematic
methodological review: developing a framework for a qualitative semi-structured
interview guide. J. Adv. Nurs. 72 (12), 2954–2965. https://doi.org/10.1111/
jan.13031.
Konietzko, J., Bocken, N., Hultink, E., 2019. Online Platforms and the Circular Economy,
pp. 435–450. https://doi.org/10.1007/978-3-319-97385-2_23.
Koskinen, K., Bonina, C., Eaton, B., 2019. In: Nielsen, P., Kimaro, H.C. (Eds.), Digital
platforms in the global south: foundations and research agenda, Information and
Communication Technologies for Development. Strengthening Southern-Driven
Cooperation as a Catalyst for ICT4D. Springer International Publishing, pp. 319–330.
https://doi.org/10.1007/978-3-030-18400-1_26.
Kristoffersen, E., Aremu, O.O., Blomsma, F., Mikalef, P., Li, J., 2019. In: Pappas, I.O.,
Mikalef, P., Dwivedi, Y.K., Jaccheri, L., Krogstie, J., M¨
antym¨
aki, M. (Eds.), Exploring
the relationship between data science and circular economy: an enhanced CRISP-DM
process model, Digital Transformation for a Sustainable Society in the 21st Century.
Springer International Publishing, pp. 177–189. https://doi.org/10.1007/978-3-
030-29374-1_15.
Kristoffersen, E., Blomsma, F., Mikalef, P., Li, J., 2020a. The smart circular economy: a
digital-enabled circular strategies framework for manufacturing companies. J. Bus.
Res. 120, 241–261. https://doi.org/10.1016/j.jbusres.2020.07.044.
Kristoffersen, E., Blomsma, F., Mikalef, P., Li, J., 2020b. The smart circular economy: a
digital-enabled circular strategies framework for manufacturing companies. J. Bus.
Res. 120, 241–261. https://doi.org/10.1016/j.jbusres.2020.07.044.
Kuechler, W., Vaishnavi, V., 2011. Promoting relevance in IS research: an informing
system for design science research. Inf. Sci.: Int. J. Emerg. Transdiscipl. 14, 125–138.
https://doi.org/10.28945/1498.
¨
A. Boukhatmi et al.
Journal of Cleaner Production 418 (2023) 137992
13
Kvale, S., 1996. InterViews: an introduction to qualitative research interviewing. Am. J.
Eval. 19, 267–270. https://doi.org/10.1016/S1098-2140(99)80208-2.
Lewandowski, M., 2016. Designing the business models for circular economy—towards
the conceptual framework. Sustainability 8 (1). https://doi.org/10.3390/
su8010043. Art. 1.
Lieder, M., Rashid, A., 2016. Towards circular economy implementation: a
comprehensive review in context of manufacturing industry. J. Clean. Prod. 115,
36–51. https://doi.org/10.1016/j.jclepro.2015.12.042.
March, S.T., Smith, G.F., 1995. Design and natural science research on information
technology. Decis. Support Syst. 15 (4), 251–266. https://doi.org/10.1016/0167-
9236(94)00041-2.
March, S.T., Storey, V.C., 2008. Design science in the information systems discipline: an
introduction to the special issue on design science research. MIS Q. 32 (4), 725–730.
https://doi.org/10.2307/25148869.
Matinmikko, J., Kinnunen, S.-K., Sinkkonen, T., K¨
arri, T., 2022. Towards sustainable
feasibility studies for P2X investments. J. Clean. Prod. 365, 132641 https://doi.org/
10.1016/j.jclepro.2022.132641.
McIntyre, D.P., Srinivasan, A., 2017. Networks, platforms, and strategy: emerging views
and next steps. Strat. Manag. J. 38 (1), 141–160. https://doi.org/10.1002/smj.2596.
Moreno, M., Court, R., Wright, M., Charnley, F., 2019. Opportunities for redistributed
manufacturing and digital intelligence as enablers of a circular economy. Int. J.
Sustain. Eng. 12 (2), 77–94. https://doi.org/10.1080/19397038.2018.1508316.
Mossali, E., Diani, M., Colledani, M., 2020. DigiPrime: digital platform for circular
economy in cross-sectorial sustainable value networks. Proceedings 65 (1). https://
doi.org/10.3390/proceedings2020065001. Art. 1.
Mulhall, D., Ayed, A.-C., Schroeder, J., Hansen, K., Wautelet, T., 2022. The product
circularity data sheet—a standardized digital ngerprint for circular economy data
about products. Energies 15 (9). https://doi.org/10.3390/en15093397. Art. 9.
Okorie, O., Salonitis, K., Charnley, F., Moreno, M., Turner, C., Tiwari, A., 2018.
Digitisation and the circular economy: a review of current research and future
trends. Energies 11 (11). https://doi.org/10.3390/en11113009. Art. 11.
Okoroigwe, F.C., Okoroigwe, E.C., Ajayi, O.O., Agbo, S.N., Chukwuma, J.N., 2020.
Photovoltaic modules waste management: ethical issues for developing nations.
Energy Technol. 8 (11), 2000543 https://doi.org/10.1002/ente.202000543.
Pagoropoulos, A., Pigosso, D.C.A., McAloone, T.C., 2017a. The emergent role of digital
technologies in the circular economy: a review. Procedia CIRP 64, 19–24. https://
doi.org/10.1016/j.procir.2017.02.047.
Pagoropoulos, A., Pigosso, D.C.A., McAloone, T.C., 2017b. The emergent role of digital
technologies in the circular economy: a review. Procedia CIRP 64, 19–24. https://
doi.org/10.1016/j.procir.2017.02.047.
Parker, G.G., Alstyne, M.W.V., Choudary, S.P., 2016. Platform Revolution: How
Networked Markets Are Transforming the Economy and How to Make Them Work
for You. W. W. Norton & Company.
Peltokorpi, A., Talmar, M., Castr´
en, K., Holmstr¨
om, J., 2019. Designing an organizational
system for economically sustainable demand-side management in district heating
and cooling. J. Clean. Prod. 219, 433–442. https://doi.org/10.1016/j.
jclepro.2019.02.106.
Madaster Plattform, 2022. Madaster Switzerland. https://madaster.ch/plattform/.
Prat, N., Comyn-Wattiau, I., Akoka, J., 2015. A taxonomy of evaluation methods for
information systems artifacts. J. Manag. Inf. Syst. 32 (3), 229–267. https://doi.org/
10.1080/07421222.2015.1099390.
Rabaia, M.K.H., Semeraro, C., Olabi, A.-G., 2022. Recent progress towards photovoltaics’
circular economy. J. Clean. Prod. 373, 133864 https://doi.org/10.1016/j.
jclepro.2022.133864.
Ranta, V., Aarikka-Stenroos, L., V¨
ais¨
anen, J.-M., 2021. Digital technologies catalyzing
business model innovation for circular economy—multiple case study. Resour.
Conserv. Recycl. 164, 105155 https://doi.org/10.1016/j.resconrec.2020.105155.
Rauer, J., Kaufmann, L., 2015. Mitigating external barriers to implementing green supply
chain management: a grounded theory investigation of green-tech companies’ rare
earth metals supply chains. J. Supply Chain Manag. 51 (2), 65–88. https://doi.org/
10.1111/jscm.12063.
Rowley, J., 2007. The wisdom hierarchy: representations of the DIKW hierarchy. J. Inf.
Sci. 33 (2), 163–180. https://doi.org/10.1177/0165551506070706.
Scheepens, A.E., Vogtl¨
ander, J.G., Brezet, J.C., 2016. Two life cycle assessment (LCA)
based methods to analyse and design complex (regional) circular economy systems.
Case: making water tourism more sustainable. J. Clean. Prod. 114, 257–268. https://
doi.org/10.1016/j.jclepro.2015.05.075.
Schwanholz, J., Leipold, S., 2020. Sharing for a circular economy? An analysis of digital
sharing platforms’ principles and business models. J. Clean. Prod. 269, 122327
https://doi.org/10.1016/j.jclepro.2020.122327.
Scott, J.T., 2017. The Sustainable Business: A Practitioner’s Guide to Achieving Long-
Term Protability and Competitiveness. Routledge. https://doi.org/10.4324/
9781351276603.
Seidel, S., Recker, J., Pimmer, C., 2010. Enablers and Barriers to the Organizational
Adoption of Sustainable Business Practices, vol. 11.
Seidel, S., Recker, J., vom Brocke, J., 2013. Sensemaking and sustainable practicing:
functional affordances of information systems in green transformations. MIS Q. 37
(4), 1275–1299.
Serna-Guerrero, R., Ikonen, S., Kallela, O., Hakanen, E., 2022. Overcoming data gaps for
an efcient circular economy: a case study on the battery materials ecosystem.
J. Clean. Prod. 374, 133984 https://doi.org/10.1016/j.jclepro.2022.133984.
Sherman, R., 2014. Business Intelligence Guidebook: from Data Integration to Analytics.
Newnes.
Siow, E., Tiropanis, T., Hall, W., 2018. Analytics for the Internet of Things: a survey.
ACM Comput. Surv. 51 (4) https://doi.org/10.1145/3204947, 74:1-74:36.
Sumper, A., Robledo-García, M., Villaf´
ala-Robles, R., Bergas-Jan´
e, J., Andr´
es-Peir´
o, J.,
2011. Life-cycle assessment of a photovoltaic system in Catalonia (Spain). Renew.
Sustain. Energy Rev. 15 (8), 3888–3896. https://doi.org/10.1016/j.
rser.2011.07.023.
Tao, M., Fthenakis, V., Ebin, B., Steenari, B.-M., Butler, E., Sinha, P., Corkish, R.,
Wambach, K., Simon, E.S., 2020. Major challenges and opportunities in silicon solar
module recycling. Prog. Photovoltaics Res. Appl. 28 (10), 1077–1088. https://doi.
org/10.1002/pip.3316.
T¨
auscher, K., Laudien, S.M., 2018. Understanding platform business models: a mixed
methods study of marketplaces. Eur. Manag. J. 36 (3), 319–329. https://doi.org/
10.1016/j.emj.2017.06.005.
Thomas, L.D.W., Autio, E., Gann, D.M., 2014. Architectural leverage: putting platforms
in context. Acad. Manag. Perspect. 28 (2), 198–219. https://doi.org/10.5465/
amp.2011.0105.
Tu, M., Chung, W.-H., Chiu, C.-K., Chung, W., Tzeng, Y., 2017. A novel IoT-based
dynamic carbon footprint approach to reducing uncertainties in carbon footprint
assessment of a solar PV supply chain. In: 2017 4th International Conference on
Industrial Engineering and Applications (ICIEA), pp. 249–254. https://doi.org/
10.1109/IEA.2017.7939216.
van Aken, J., Romme, G., 2012. A design science approach to evidence-based
management. In: The Oxford Handbook of Evidence-Based Management, pp. 43–57.
https://doi.org/10.1093/oxfordhb/9780199763986.013.0003.
van der Heide, A., 2022. Labelling and Certication Protocols for Second Life PV
Modules. https://www.circusol.eu/en/nieuws/95/new-deliverable-labelling-and-c
ertication-protocols-for-second-life-pv-modules.
van der Heide, A., Tous, L., Wambach, K., Poortmans, J., Clyncke, J., Voroshazi, E., 2022.
Towards a successful re-use of decommissioned photovoltaic modules. Prog.
Photovoltaics Res. Appl. 30 (8), 910–920. https://doi.org/10.1002/pip.3490.
Wade, A., Sinha, P., Drozdiak, K., Brutsch, E., 2017. Beyond Waste – The Fate of End-of-
Life Photovoltaic Panels from Large Scale PV Installations in the EU The Socio-
Economic Benets of High Value Recycling Compared to Re-Use.
Walden, J., Steinbrecher, A., Marinkovic, M., 2021. Digital product passports as enabler
of the circular economy. Chem. Ing. Tech. 93 (11), 1717–1727. https://doi.org/
10.1002/cite.202100121.
Walls, J.G., Widmeyer, G.R., Sawy, O.A.E., 1992. Building an Information System Design
Theory for Vigilant EIS. Information Systems Research. https://doi.org/10.1287/
isre.3.1.36.
Watson, R., 2008. Green IS: Building Sustainable Business Practices, vol. 17. Information
Systems.
Weichhart, G., Molina, A., Chen, D., Whitman, L., Vernadat, F., 2015. Challenges and
current developments for sensing, smart and sustainable enterprise systems. Comput.
Ind. 79 https://doi.org/10.1016/j.compind.2015.07.002.
Wiliam, D., Black, P., 2006. Meanings and Consequences: a basis for distinguishing
formative and summative functions of assessment? Br. Educ. Res. J. https://doi.org/
10.1080/0141192960220502.
World Economic Forum, 2016. Shaping the Future of Construction: A Breakthrough in
Mindset and Technology. World Economic Forum. https://www.weforum.org/re
ports/shaping-the-future-of-construction-a-breakthrough-in-mindset-and-technolog
y/.
Zutshi, A., Grilo, A., 2019. The emergence of digital platforms: a conceptual platform
architecture and impact on industrial engineering. Comput. Ind. Eng. 136, 546–555.
https://doi.org/10.1016/j.cie.2019.07.027.
¨
A. Boukhatmi et al.
