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Digital Platforms for the Common Good: Social Innovation for Active Citizenship and ESG

Gabelli School of Business, Fordham University, New York, NY 10023, USA
Department of Social Science and Policy Studies, Worcester Polytechnic Institute, Worcester, MA 01609, USA
Author to whom correspondence should be addressed.
Sustainability 2022, 14(2), 639;
Submission received: 27 October 2021 / Revised: 21 December 2021 / Accepted: 5 January 2022 / Published: 7 January 2022


The platform business model has attracted significant attention in business research and practice. However, much of the existing literature studies commercial platforms that seek to maximize profit. In contrast, we focus on a platform for volunteers that aims to maximize social impact. This business model is called a platform for the common good. The article proposes a Causal Loop Diagram (CLD) model that explains how a platform for the common good creates value. Our model maps the key strategic feedback loops that constitute the core structure of the platform and explains its growth and performance through time. We show that multiple types of network effects create interlocking, reinforcing feedback loops. Overall, the article contributes towards a dynamic theory of the platforms for the common good. Moreover, the article provides insights for social entrepreneurs who seek to build, understand, and optimize platforms that maximize social value and managers of companies that seek to participate in such platforms. Social entrepreneurs should seek to leverage the critical feedback loops of their platform.

1. Introduction

The platform business model has attracted significant attention in business research and practice. However, much of the existing literature studies commercial platforms that maximize profit [1,2,3,4]. This article explores the dynamic complexity of platforms for non-commercial services that seek to maximize social value. We call such a social impact platform a platform for the common good.
Platforms add value by coordinating multiple stakeholders. For example, Uber connects car owners and riders. Platforms for the common good, which constitute the fastest-growing social business category [5], make it possible for multiple stakeholders to come together and interact to maximize social value creation. Social value refers to the beneficial outcomes to the broad community to alleviate social problems [6].
This article aims to understand the precise mechanism through which a platform for the common good creates social value and explains the platform’s success. We use a systems approach [7], and we build a model inspired by the Ethelon platform ( that supports volunteering in Greece. Our model identifies important variables and maps key strategic feedback loops that constitute the core structure of the platform for the common good.
This article’s main contribution is that it identifies a generic structure of a digital platform that enables volunteerism working with nonprofits and companies involved in Environmental, Social, and Governance (ESG) activities. The article integrates several research themes: platforms, social innovation, ESG, and active citizenship. This article contributes to the growing literature on the platform business model [8,9,10,11,12,13,14] and the economics for the common good [15,16]. Moreover, the article provides insights for leaders who seek to build, understand, and optimize such platforms in the context of social innovation.
The rest of the article is structured as follows. Section 2 discusses the background of this research. The methods are explained in Section 3. The model and results are presented in Section 4, while Section 5 discusses insights and implications. We conclude in Section 6.

2. Background

We discuss the platform for the common good and its stakeholders. Our research is motivated by the Ethelon platform (, and the stakeholders are Individual Volunteers, Companies, and Institutions (nonprofits, municipalities, and others).

2.1. Platform for the Common Good

“Social innovation refers to innovative activities and services that are motivated by the goal of meeting a social need” [17]; thus, social innovations provide solutions to societal problems. The social innovation process involves identifying an unmet need, generating an idea of how to meet that need, testing the idea in practice, scaling up, and, as the reality changes, adapting the idea [18]. Because social innovation is a challenging process, there is a growing need to understand models for social innovation [19], how to build organizations for a social purpose [20,21,22,23,24], and the implications of the social sector for business education [25].
Unlike commercial platforms, the Ethelon platform ( is a social enterprise that seeks a viable business model to maximize social impact. Ethelon was created in 2016 by the merger of two organizations, Volunteer4Greece and GloVo. The goal was to become the main point of reference for volunteering in Greece. The organization promotes active citizenship by creating and publicizing volunteer opportunities for young people, students, professionals, families, and retirees. Since 2012, the two organizations have supported over 10,000 specific volunteer positions through more than 150,000 volunteer applications, serving the needs of more than 370 nonprofits and institutions. They created a network of more than 15,500 active volunteers, and organized and supported more than 850 social actions. They implemented more than 120 corporate volunteer programs, contributing more than 1,300,000 h of volunteering (data as of early 2021, based on Ethelon documents and
Figure 1 shows the key conceptual elements of a platform for the common good inspired by Ethelon. The platform uses Internet technologies to maximize social impact by facilitating the interaction of its stakeholders.

2.2. Individual Volunteers

Active citizenship, defined as the role of citizens in the public domain, has a transformative potential [26]. Ethelon was created to meet the need of individuals to participate actively in society [27]. People were interested in participating in initiatives, but they did not know the how, where, and when. Ethelon’s way of collecting all the information in one place and communicating them clearly through the platform website and the weekly newsletter made it much easier for people to start volunteering. Instead of spending hours searching the Web, they could either visit or receive a newsletter informing them of the current volunteering opportunities. Opportunities are both short- and long-term. Volunteers can apply to participate based on their time, location, talent, and interests.
The platform promotes civic participation and engagement. A total of 52% of the users who have joined Ethelon have never volunteered before, according to 2018 data. That metric proves how Ethelon developed the volunteering culture. The benefits differ across volunteer age groups.
Ages 16–25: For this group, joining Ethelon creates an opportunity to belong in a community with the same values with them, have access to opportunities where they could learn new hard and soft skills, add experiences in their resume (especially during the years that unemployment in Greece was increasing), network personally and professionally, and have fun.
Ages 25–65: After finding their first job, this group may stop participating actively, according to 2016 data. Only one out of ten continued volunteering. Corporate employee volunteering programs provided a solution to this issue, as this group can now volunteer through the programs that Ethelon develops for their companies. That includes skill-based volunteering based on their corporate expertise or other hands-on experiences outside of the office.
Ages 65+: There is a big issue in society for those who have just retired. After 40+ years of waking up and going to work every day, they do not have an active role and feel less valuable. Ethelon designed a program named Synenergo that, in addition to capacity building programs in English and computers, provided seniors the opportunity to be active and socialize through volunteering.

2.3. Nonprofits and Other Institutions

Nonprofit organizations: Most nonprofit organizations struggled to find volunteers to cover their needs in 2012. Their pool of volunteers was limited, and they did not have the resources to access new ones. Through, nonprofits were able to save time and money. They were able to upload their short- and long-term volunteering opportunities. They could reach thousands of volunteers and evaluate their applications similar to a job-posting site. Moreover, Ethelon delivered training programs to empower volunteers, leading to better experiences. By monitoring the opportunities that nonprofits upload to the platform, Ethelon makes proposals to companies for potential volunteering actions and develops partnerships between companies and nonprofits, creating an additional revenue stream for the sustainability of nonprofits in Greece.
Events and long-term programs: Similarly to the way nonprofits benefited from the platform, various events like music concerts, marathons, TEDx, and more, are using this pool of volunteers to assist them with the implementation of their events. Ethelon can be an outsourcing vendor responsible for recruiting, selecting, training, and managing volunteers. Ethelon can also take responsibility for long-term volunteer programs, like collaborating with the Stavros Niarchos Foundation Culture Center to manage their volunteering program for the first nine months after the launch.
Government and municipalities: The platform collaborates with various municipalities around Greece to renovate public spaces through partnerships between nonprofits and companies. For example, Ethelon developed a volunteer program for the city of Athens in collaboration with Aegean Airlines and the city’s airport to improve the reception of international tourists.
Educational institutions:Ethelon delivers interactive workshops to high school students to cultivate the habit of volunteering. International universities have partnered with Ethelon to design volunteer opportunities in Greek communities for students who come to the country on short cultural trips.

2.4. Corporations

Our research provides insights for companies adopting ESG practices [28] and related CSR activities, such as employee volunteer programs. Current research treats ESG and CSR as interchangeable and talks about a company’s ESG/CSR profile [29]. We follow that convention too.
Corporations that emphasize ESG/CSR may aim to increase their CSR reputation, increase employee engagement, attract recruits, make their products more attractive to sustainability-sensitive consumers, or minimize ESG-related risks, such as climate change.
Corporations aim to cover two primary needs through the platform. They increase employee engagement by providing exciting volunteering opportunities for their employees. People prefer to work for companies that represent and believe in something. Through CSR initiatives, companies improve their reputation [30]. Those benefits are happening through the partnerships with nonprofits that the Ethelon team designs, which lead either to employee volunteering programs or long-term and sustainability partnerships.
A particular category of companies that benefit from the Ethelon platform are brands that want to connect and relate with the Ethelon community of volunteers. The companies sponsor either a specific event or design exclusive partnerships with Ethelon to either develop a positive reputation or recruit the volunteers as their audience.

2.5. Other Stakeholders

Ethelon aims to support people in need, including refugees, people with disabilities, older adults, and more. The more volunteers, nonprofits, and corporations are joining the platform, the biggest the potential impact. Other authors have discussed how platforms can enhance the private sector engagement in humanitarian relief operations [31] and help fight food waste [32].
Media in need of positive news are often interested in sharing stories and initiatives from Ethelon. In addition, media can gain access to other organizations that use the Ethelon platform.

3. Methods

We use the systems approach [7,33,34,35,36,37,38] to build a Causal Loop Diagram (CLD) model of a digital platform for volunteers that seeks to maximize social value through greater stakeholder participation. The model maps the complex interaction between important variables and identifies strategic feedback effects. This model is used to understand how a platform for the common good creates value and why it may succeed or fail. Dynamic modeling provides a valuable representation of a business model [39,40,41].
Our model was built based on many semi-structured interviews with an Ethelon cofounder (second co-author) between October 2020 and February 2021. Data from the Ethelon website and other reports and data detailing the platform history and activities were also used as inputs into the modeling process.
We followed an iterative process of drafting and then refining the model. We identified key stakeholders and variables. Then we identified causal links between variables. Causal links may create feedback loops, which become visible only through the modeling process. A feedback loop is reinforcing (a change in a variable reinforces itself via the loop), or balancing (a change in a variable is balanced via the loop). The structure and interaction of the feedback loops determine the system behavior through time. Feedback analysis provides further insight into the behavior of the system and may suggest leverage points within organizations.
The validity of a CLD model can be established by consulting with various sources, such as relevant literature and domain experts [42,43,44]. We conducted numerous semi-structured interviews with domain experts, including the Ethelon co-founder, who has close to 10 years of social innovation industry experience.

4. Model and Results

Our CLD model identifies important variables and maps key strategic feedback loops that constitute the core structure of the platform for the common good. The model is shown in Figure 2. A positive link between two variables in the CLD means that an increase in the first variable leads to an increase in the second variable. A negative link has a reverse effect.
As already discussed earlier, the platform connects Individual Volunteers, Companies, and Institutions (nonprofits, municipalities, and others). The model shows the precise mechanism through which the platform brings those stakeholders together and facilitates their interactions. It focuses on crucial feedback loops that determine platform performance driven primarily by network effects [45] and peer effects, as we discuss below.
Our research identifies several reinforcing feedback loops (R1–R5) that constitute the core structure of the platform for the common good. Below, we describe these loops and then explain their contribution to the platform’s success by performing a feedback loop analysis.

4.1. Reinforcing Feedback Loop R1 (More Volunteers, More Institutions)

Institutions join the platform to find volunteers for their projects, while the volunteers seek volunteer opportunities. An increase in the number of Individual Volunteers increases the Platform Attractiveness to Institutions. That increases the number of Institutions that use the platform and the number of Opportunities for Volunteers. As a result, the Platform Attractiveness to Individual Volunteers goes up, leading to a further increase of the Individual Volunteers. This feedback loop consists of two cross-side network effects: Institutions benefit from more volunteers, and volunteers benefit from more institutions on the platform. This feedback loop is akin to the pattern we observe in a generic commercial platform: the availability of more content, apps, and services on a generic digital platform attracts more users, attracting even more content, apps, and services [46,47,48,49].

4.2. Reinforcing Feedback Loop R2 (Community Engagement)

Individual Volunteers seek to socialize with other like-minded volunteers and engage with the community. An increase in the number of Individual Volunteers increases the opportunities for Volunteer Community Engagement and increases the Platform Attractiveness to Individual Volunteers. That leads to an increase of Individual Volunteers on the platform. This reinforcing feedback loop is a same-side (direct) network effect for the Individual Volunteers side on the platform. This feedback loop is akin to direct network effects in social networks or other communication networks.
We should also note that awareness about volunteerism and the platform could play a supporting role here (not shown in Figure 1). Awareness could come from advertising or word-of-mouth. Awareness is distinct from the network effect mechanism, which is about higher value for the volunteers. However, awareness can support the network effect mechanism because it helps potential new participants learn about the platform’s value and make participation decisions.

4.3. Reinforcing Feedback Loop R3 (More Volunteers, More Companies)

Some companies (brands) seek volunteers for various events. An increase in the number of Individual Volunteers increases the Platform Attractiveness to Companies Seeking Volunteers. That leads to an increase in the number of Companies Seeking Volunteers for Events on the platform and an increase in the number of Opportunities for Volunteers. That raises the Platform Attractiveness to Individual Volunteers and leads to a further increase of the Individual Volunteers. This feedback loop consists of two cross-side network effects: companies (brands) seeking volunteers for events benefit from more volunteers, and volunteers benefit from more brands on the platform.

4.4. Reinforcing Feedback Loop R4 (More Companies, More Institutions)

Many companies seek volunteer opportunities for their employees as part of their ESG/CSR programs. An increase in the number of Institutions on the platform increases the Platform Attractiveness to Companies Seeking Volunteer Opportunities for Employees. That leads to an increase in the number of such Companies on the platform and an increase in the number of Employee Volunteers. That raises the Platform Attractiveness to Institutions and leads to a further increase of the Institutions. This feedback loop consists of two cross-side network effects: Companies benefit from more institutions, and institutions benefit from more companies on the platform.

4.5. Reinforcing Feedback Loop R5 (Companies Peer Effect)

An increase in the number of Companies Seeking Volunteer Opportunities for Employees increases the pressure on other peer companies to do the same. It raises the Platform Attractiveness to Companies Seeking Volunteer Opportunities for Employees. The number of such companies on the platform goes up. This reinforcing feedback loop is a peer pressure effect for the Companies Seeking Volunteer Opportunities for Employees side on the platform. It is not a network effect—it is driven by peer influence and awareness about volunteerism and the platform.

4.6. Explanation of Platform Success

The model sheds light on the dynamic complexity of digital platforms for the common good. It identifies the precise mechanism through which a platform for the common good creates social value and explains the platform’s success.
The reinforcing feedback loops across the multiple platform stakeholders (sides) provide the core structure of the platform business model and drive its behavior over time. A reinforcing feedback loop creates exponential growth [7]. Because all the feedback loops are reinforcing in our model, the expected behavior is platform growth over time.
Thus, the structure of the model explains the success of the platform. The platform performance is measured by stakeholder participation, the activity level on the platform, and social value creation. Profit maximization is not a relevant performance metric here, as already discussed. The platform seeks to remain financially sustainable through various revenue streams and cost controls. However, Financial Transparency of the platform is crucial because it contributes to Platform Trust, affecting platform attractiveness for all stakeholders.
We also note that our model focuses on a single platform. It does not include competition-related balancing feedback loops that could constrain future growth. Moreover, a finite number of potential Individual Volunteers, Institutions, and Companies could also constrain the platform growth in the future.

4.7. Feedback Loop Analysis: Interlocking, Reinforcing Feedback Loops

Our model shows that the mechanism through which a platform for volunteers creates value is through reinforcing feedback loops that drive stakeholder participation and interaction. Cross-side and same-side network effects create reinforcing feedback loops, as shown in Figure 2. Note that one same-side network effect does create a feedback loop (e.g., R2). However, a pair of cross-side network effects is necessary to create a feedback loop (e.g., R1, R4, and R3).
The reinforcing feedback loops are not standalone. Figure 2 shows that the model has interlocking, reinforcing feedback loops. We define interlocking feedback loops as loops that reinforce each other.
Consider feedback loops R1 and R2 in Figure 2. R1 and R2 are interlocking and reinforce each other. Increasing the value of a variable in R1 will increase all the other R1 variables (all links are positive) and all the variables in R2.
We identify the following pairs of interlocking, reinforcing feedback loops: (R1, R2), (R1, R4), (R4, R5), and (R2, R3). Then we can construct a graph [50] of these interlocking relations as R3–R2–R1–R4–R5 (the feedback loops are the graph’s nodes, and two feedback loops are linked if they are interlocking).
This simple graph suggests that structurally R1 is the most central feedback loop, based on measures such as the betweenness centrality [51]. An implication is that initiatives to improve platform performance should consider strengthening the R1 feedback loop.

4.8. Interventions

The model allows us to see why and how an intervention propagates through the system. For instance, an intervention that increases the number of Individual Volunteers will be reinforced in R1, R2, R3, and then in R4 and R5. Another intervention could be increasing Platform Trust because that variable affects all feedback loops (see Figure 2).
More powerful leverage points include strengthening existing reinforcing feedback loops, creating new desirable feedback loops (see Section 5.3), and changing the system’s rules or goals in a desirable direction [52].

5. Discussion

This research seeks to understand how platforms for the common good create value. We summarize the contributions, discuss implications for managers, and provide some additional insights on the digital transformation of platforms.

5.1. Summary of Contributions

While most platforms research focuses on commercial profit-maximizing platforms [1,4], this research defines the platform for the common good and provides a new dynamic model to understand such platforms.
A platform for the common good maximizes social value by bringing together multiple stakeholders (volunteers, companies, nonprofits, and other institutions) enabled by digital technologies. Nobel laureate Jean Tirole argues: “The quest for the common good, therefore, involves constructing institutions to reconcile, as far as possible, the interests of the individual with the general interest.” [15] (p. 3). This research shows that a platform for the common good is a new institution that fulfills that role.
Most importantly, prior research fails to provide a comprehensive value-creation mechanism for the platform. The main contribution of this work is that it takes a systems approach and develops a dynamic (CLD) model, a generic structure that explains how platforms for the common good create value. We show that the feedback loop is a valuable concept. We identify the feedback loop structure that drives behavior, and we analyze that structure to derive further insights and implications. It pushes the research agenda of analyzing platforms as complex systems and accounts for dynamic complexity as a business model feature to be understood and leveraged [53,54]. The model is the first contribution towards a dynamic theory of platforms of the common good.
Our work also adds to platform theory [14,47,55] by demonstrating how network effects create reinforcing feedback loops. We show that multiple types of network effects may interact to create interlocking, reinforcing feedback loops. The value of the systems approach is that it allows us to map and investigate all those interactions and see how a change in one part of the system may affect the whole system over time.
Our research supports a shift towards a more (socially) responsible platform economy and society [56,57]. The platform for the common good is a responsible platform by definition as its main aim is to maximize social value through stakeholder participation. However, more work is needed to expand the debate of the responsibilities of commercial platforms [58] and to clarify when a commercial platform is a responsible platform. Platforms could create shared value [59] and aid development [60]. Platforms could function as gatekeepers of social impact [61] and aid sustainability [62,63].

5.2. Implications for Managers and Social Entrepreneurs

Our research provides several insights for social entrepreneurs and managers. We provide a new approach that should be useful to social entrepreneurs. In particular, they can learn new concepts and a new approach to understanding their business model focused on feedback loops and causal loop diagrams.
We illustrate the critical role of network effects in the context of social innovation platforms. We identify and explain several relevant network effects (same-side and cross-side). Social entrepreneurs may not be aware of those network effects because network effects are typically studied in commercial consumer markets. Even when one is aware of network effects, understanding the strength and consequences of those effects requires careful analysis.
A systems approach to business models calls for mapping the structure of a business model using CLDs. It is a powerful approach in the fast-changing digital economy. Such feedback thinking can help managers map the core structure of their business model that drives behavior and business performance. Due to complex causality, delays, and feedback loops, the behavior of a business model is often counterintuitive and difficult to comprehend. Failure to take a systems approach that recognizes complex causality and feedback loops may result in managerial decisions that have unintended consequences. An implication is that business and entrepreneurship education should emphasize systems thinking skills for entrepreneurs and managers. This insight is in-line with other recent calls to “get savvy with systems” [16].
Social entrepreneurs need to understand and invest in the vital feedback loops in their business model. They should seek to create, rewire, strengthen, and accelerate feedback loops in the business model [54]. Managers and entrepreneurs need to evaluate whether the feedback loops work for or against their organization. They also need to consider leveraging those feedback loops in their innovation initiatives. Reinforcing loops can drive a virtuous phase of growth but also speed up a decline and collapse after a negative shock to a system.
Lastly, managers of corporations and nonprofits can benefit from joining platforms for the common good. The platform provides corporations with new opportunities to connect with volunteers and nonprofits, promote their ESG initiatives, and gain visibility in the community. Moreover, the platform aids nonprofits in finding volunteers and achieving their goals for social benefit. Nonprofits may also collaborate with corporations to support their financial sustainability.

5.3. AI and Digital Transformation for Social Innovation Business Models

Digital platforms rely on Internet technologies to bring together multiple stakeholders. Social entrepreneurs aiming for continuous improvement and business model innovation should invest in digital transformation. It is essential to take an approach that understands the dynamic impact of technology on business [64]. AI may help the platform grow even more in the future because AI can create new feedback loops that leverage data resources [54]. The platform could rely on algorithms and AI to improve matching quality, increasing participation and engagement. It could automate more tasks, collect data for analytics, and provide a superior experience to platform stakeholders and employees. AI could help automate volunteers’ research for volunteering opportunities and nonprofits; an AI chatbot could connect volunteers with the best opportunities.
The platform could use digital technologies to segment the stakeholders. It could create premium profiles for nonprofits and other stakeholders who want to use the platform more intensively and need more support.
Another opportunity is to use digital technologies to expand the stakeholders. For example, the Ethelon platform could allow the Greek diaspora to connect easily with volunteer opportunities when visiting Greece.
Lastly, digital and non-digital elements of a platform should be well designed and coordinated. People should carefully handle any task that is not easily automated. That would ensure that all platform stakeholders have a unified experience. Platform designers should also be aware of value-sensitive design approaches and challenges [65,66].

6. Conclusions

This article defines and analyzes a platform for the common good business model. The platform seeks to maximize social value through enabling and supporting active citizenship and corporate ESG/CSR. The platform orchestrates a platform ecosystem [67,68,69]. It enables all stakeholders—volunteers, corporations, nonprofits, and other institutions—to come together and interact to maximize social impact. We show that the feedback loop concept is critical in understanding the structure and performance of the platform.
This work has several limitations that provide opportunities for future research. More research that accounts for the dynamic complexity of social innovation platforms is needed. Moreover, the present work does not build any mathematical or computational models—we plan to build and analyze feedback economic models [70] and model sustainability pathways [71] in future work.

Author Contributions

Conceptualization, E.K., K.M. and O.V.P.; methodology, E.K. and O.V.P.; formal analysis, E.K.; writing—original draft preparation, E.K. and K.M.; writing—review and editing, E.K. and O.V.P.; visualization, E.K. and O.V.P.; supervision, E.K.; project administration, E.K. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. A platform for the common good. The platform uses Internet technologies to maximize impact by facilitating the interaction of its stakeholders (source: authors’ own research).
Figure 1. A platform for the common good. The platform uses Internet technologies to maximize impact by facilitating the interaction of its stakeholders (source: authors’ own research).
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Figure 2. The structure of the platform for the common good and its critical feedback.
Figure 2. The structure of the platform for the common good and its critical feedback.
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Katsamakas, E.; Miliaresis, K.; Pavlov, O.V. Digital Platforms for the Common Good: Social Innovation for Active Citizenship and ESG. Sustainability 2022, 14, 639.

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Katsamakas E, Miliaresis K, Pavlov OV. Digital Platforms for the Common Good: Social Innovation for Active Citizenship and ESG. Sustainability. 2022; 14(2):639.

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Katsamakas, Evangelos, Kostapanos Miliaresis, and Oleg V. Pavlov. 2022. "Digital Platforms for the Common Good: Social Innovation for Active Citizenship and ESG" Sustainability 14, no. 2: 639.

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