Designing a Smart Product-Service System to support digital crowdfunding platforms.

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Learn more: PMC Disclaimer | PMC Copyright Notice Sci Rep . 2026 Feb 17;16:9468. doi: 10.1038/s41598-026-40194-2 Search in PMC Search in PubMed View in NLM Catalog Add to search Designing a Smart Product-Service System to support digital crowdfunding platforms Mariusz Salwin Mariusz Salwin 1 Institute of Production Systems Organization, Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, 86 Narbutta St, 02-524 Warsaw, Poland Find articles by Mariusz Salwin 1, ✉ , Aneta Ewa Waszkiewicz Aneta Ewa Waszkiewicz 2 Warsaw School of Economics (SGH), College of World Economy, Department of International Finance, 6/8 Madalińskiego Street, 02-513 Warsaw, Poland Find articles by Aneta Ewa Waszkiewicz 2 Author information Article notes Copyright and License information 1 Institute of Production Systems Organization, Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, 86 Narbutta St, 02-524 Warsaw, Poland 2 Warsaw School of Economics (SGH), College of World Economy, Department of International Finance, 6/8 Madalińskiego Street, 02-513 Warsaw, Poland ✉ Corresponding author. Received 2025 Sep 16; Accepted 2026 Feb 11; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13004886  PMID: 41699033 Abstract This paper aims to develop a Smart Product-Service System (SPSS) model focused on a crowdfunding platform. This goal was achieved through a systematic literature review of PSS and PSS design in industry, a crowdfunding market analysis, and interactive design workshops conducted at a conference on alternative financing attended by representatives from businesses, investors, research institutions, and government agencies. These activities allowed the authors to gain valuable insights, which were implemented in the Smart Service Canvas—an SPSS analysis and design tool. The result is an SPSS that encompasses tangible (IT infrastructure), intangible (crowdfunding support services), and digital (platform and mobile application) elements. This solution enables the integration of technologies such as artificial intelligence (AI), blockchain, and High-Performance Computing (HPC) to improve the efficiency, transparency, and security of crowdfunding campaigns (CFC) and related activities. The contribution of this work is the development of a novel approach that combines SPSS with crowdfunding. This represents a crucial step towards automating and digitizing financing processes in the age of digital transformation. Furthermore, the research approach to designing the new SPSS presented in this article emphasizes the combination of diverse perspectives on crowdfunding with practical and theoretical knowledge in this field. Interactive design workshops offer a qualitative research approach to design, positively influencing and enhancing training methods that engage participants. Keywords: Smart Product-Service System (SPSS), Crowdfunding (CF), Crowdfunding platform Subject terms: Engineering, Mathematics and computing Authors : Introduction Over the last decades, changes related to the functioning of the economy have been visible. One of the main ones is the emergence of alternative forms of financing (crowdfunding (CF), private equity, venture capital, peer-to-peer platforms) 1 – 3 . The fundamental factor here is the development of the Internet, digital platforms, mobile applications, and new technologies that enhance digital transformation 4 , 5 . This is paramount in expanding access to information and facilitating transaction processes 6 . Thanks to this, companies and individuals (initiators of crowdfunding campaigns (ICFC)) have gained completely new opportunities related to direct connection with investors 7 , 8 . Apart from well-known financial institutions such as banks and stock exchanges 9 – 11 . The aforementioned digitalization is particularly conducive to the spread of CF as one of the alternative financing methods 12 . The USA is considered to be the cradle of modern CF. Its spread was strongly related to 2008, when there was a need to respond to the financial crisis and the collapse of traditional forms of financing. In turn, its evolution was strongly related to the year 2020 with the need to change the nature and scale of CF, which was a response to the crisis related to the COVID-19 pandemic and the related need to finance social and economic challenges 13 – 15 . All this influenced the rapid increase in interest in CF as a widely available and flexible instrument of financial support 16 . CF is an alternative method of financing various types of activities or projects 17 , 18 . In this case, projects are financed by the community (a large number of one-offs and small payments made by interested people) or investors who are or will be organized around them 19 . CF allows the ICFC to access capital without affecting the company’s management, allows for a better understanding of the market, and allows for the use of investors’ knowledge to improve and shape the projects for which money is raised 5 , 20 . On the other hand, it is an organizational, administrative, and accounting challenge for them, is associated with the need to analyze legal and tax regulations, and generates the need to incur additional costs related to the crowdfunding campaigns (CFC) 6 , 21 . Therefore, the decision to use crowdfunding as an alternative method of financing by companies and individuals requires considering the potential benefits and losses that this form of financing can bring, also in strategic areas of business activity 21 . The CFC requires experience and a significant commitment to communication and promotion, which absorbs the resources of the ICFC and generates costs. The decisions of top management and managers determine the choice of crowdfunding. They must assess whether this financing fits into the organization’s strategy and consider its compliance with business goals 1 , 2 . Additionally, managers are responsible for reducing risk and ensuring an appropriate management level of CFC management to maximize the chance of success 6 . Usually their lack of experience running a CFC usually becomes a serious challenge. This activity requires a wide range of skills related to effective communication, marketing, project management, and understanding the behavior of potential supporters 15 . Lack of experience means that managers often underestimate the importance of developing a detailed plan, including an attractive project presentation, a schedule of activities, or a promotional strategy. As a result, many CFC fail due to unclear communication of the funding purpose, insufficient visibility, or lack of adequate motivation for backers 22 . In this case, the Smart Product-Service System (SPSS) can effectively respond to changes related to the functioning of the economy and digitalization and provide support for companies and individuals (ICFC) 4 , 18 . SPSS is a new generation of Product-Service Systems (PSS) that delivers new values, functionalities, and business models focusing on digital resources 23 , 24 . It offers a more personalized, integrated, and at the same time, sustainable approach to CF with a virtual platform enabling numerous interactions between ICFC and stakeholders (a small community of one-time donors and investors), which, in the era of the digital revolution, can be a fundamental advantage 18 . Using SPSS in the context of CF will expand its use by increasing the attractiveness of the CFC by offering comprehensive solutions that better meet the needs of ICFC. This will be possible thanks to generating added value through additional supporting services that guarantee the CFC success 24 . They allow for ongoing monitoring of the CFC progress, informing supporters and guaranteeing access to additional services after completion. Additionally, it can solve fundamental issues related to risk, transparency, and lack of trust and eliminate many of the challenges that limit the potential of CF 25 , 26 . This paper aims to develop a Smart Product-Service System (SPSS) model oriented towards a CF platform. The SPSS developed in this paper was created during interactive workshops conducted at a conference on alternative sources of financing, which was attended by representatives of 10 companies using CF, 10 investors, 10 research institutions and 5 state agencies dealing with the development of economic programs. The analysis and design tool SPSS, part of the interactive workshops, Smart Service Canvas, was used to develop the model. This paper demonstrates the application of SPSS for CF and shows the first results of the workshops. In this study, the development of SPSS for CF was based on proven theoretical foundations in SPSS design. First, the Value Co-Creation Theory was utilized. According to this theory, system value is generated from the outcome of interactions among all stakeholders 27 . Second, the Sociotechnical Systems Theory was applied. This theory assumes the need to balance technological and social elements in complex systems 28 . Third, the Sustainable PSS Framework was adopted. This framework emphasizes the need to integrate economic, environmental, and social aspects in the development of innovative SPSS 29 – 31 . Building on this proven theoretical foundation, the SPSS for CF was developed. The solution proposed in this study combines material, digital, and service elements. This creates a SPSS that supports the co-creation of value between investors, the platform, and ICFC. Based on this framework, the developed SPSS model for crowdfunding combines material, digital, and service components, creating a system that supports the co-creation of value among the platform, investors, and ICFC. The paper is structured as follows: the first part is the introduction. The next part presents the research methodology. The third part contains the literature analysis. The next part presents an analysis of the CF sector. The fifth part presents the interactive demonstration workshop. The fifth part contains Smart Product-Service System for crowdfunding. The last part is the discussion and conclusions. Systematic literature review Product-service system in industrial practice This part focuses on analyzing the literature on SPSS in the industry. Examples operating in the industry include Yulon Group, Yahoo!, eBay, Amazon, Kickstarter, Indiegogo, Uber, SAP, Priceline, GE Aviation, Siemens, and Philips HealthSuite. The analyzed SPSS were developed by renowned companies operating globally. The solutions developed and supported by modern digital technologies play a fundamental role in the transformation of modern industry. Thanks to this, they allow for better adaptation to customer needs and their satisfaction. These are developed solutions tailored to various industries, which enable the optimization of various types of processes to which they are addressed. Further research is necessary to develop a new SPSS and improve existing solutions 32 , 33 . Product-service system design This section focuses on the analysis of the literature on SPSS design. The classification presented in Table 1 was developed based on an analysis of the scope of applications of PSS design methods presented in the literature. The industry categories represent the economic sectors considered by the authors in their research on the development and validation of specific PSS design methods. Not all of the PSS design methods considered were assigned to specific economic sectors. Cases in which a method was not linked to a specific economic sector resulted in its assignment to the “No reference – potentially arbitrary” category. This fact underscores their universal applicability, enabling them to be utilized across diverse industries, regardless of their specific characteristics. Table 1. PSS design methods - classification. No Industry Number of methods 1. No reference - potentially arbitrary 14 2. Domestic appliances, consumer electronics and other equipment sector 13 3. Mechanical engineering 12 4. Production sector 11 5. Logistics and transport 10 6. Construction and environmental engineering 6 7. Other sectors 4 8. Energy sector 4 9. Electronics sector 3 10. IT sector 3 11. Food sector 3 12. Training sector 2 13. Telecommunications sector 2 Open in a new tab All methods available for this study were classified for specific industries (Table 1 ). It is worth emphasizing that some methods are applicable across various economic sectors. The most significant number, 13 methods, are targeted at the domestic appliances, consumer electronics, and other equipment sectors. It should be noted that 14 methods are very general (“No reference – potentially arbitrary”). The literature in the analyzed scope does not mention design methods that are addressed to CF 34 , 35 . In the next stage of the analysis, PSS design methods were classified based on verification criteria (verified in industry, within research projects, or proposed by scientists) and the type of PSS that can be designed using a given method. Table 2 presents a classification of available PSS design methods. The analysis indicates that several PSS types can be applied to one of the available PSS design methods. Table 2. PSS design methods - classification. No Verified in industrial practice Verified in scientific projects Proposed by scientists 1. Integration-oriented PSS 8 10 13 2. Product-oriented PSS 8 13 19 3. Service-oriented PSS 16 15 20 4. Use-oriented PSS 13 15 11 5. Results-oriented PSS 12 17 9 Open in a new tab Summary of literature review and research gaps Literature research shows that PSS is widely used across various industries 36 – 38 . This concept aims to integrate products and services, enhancing efficiency and personalization, while also supporting sustainable development strategies 39 – 41 . Recent years have seen a shift from classic PSS to more advanced SPSS, which are enhanced with modern digital technologies that ensure automation and adaptability 42 , 43 . The literature indicates that this is one of the fundamental directions in the development of contemporary business models, which offer the opportunity to generate entirely new added value for producers and customers 17 , 44 , 45 . Despite the growing number of studies on PSS, most of them focus on industrial and technological cases 31 , 46 , 47 . The application and potential of SPSS in the areas of digital services, banking, and financial reporting are overlooked. Individual studies only suggest the possibility of using SPSS within financial ecosystems 17 , 44 , 45 . No studies have been found that demonstrate the use of SPSS in the context of financial reporting platforms, which are a rapidly developing element of the digital economy 48 . This gap concerns the lack of empirical and conceptual models linking SPSS with financial reporting processes, investment decision automation, or digital support for ICFC 5 , 6 . Therefore, this study proposes a PSS for crowdfunding, filling a research gap. The developed solution integrates three fundamental elements: tangible (IT infrastructure), intangible (crowdfunding support services), and digital (platform, application, and technology). The PSS for crowdfunding presented in this study was developed based on an analysis of the literature, the crowdfunding market, and an interactive design workshop at a conference on alternative financing sources. The developed solution represents an attempt to transfer SPSS design theories to the alternative financing sector. This offers an entirely new and previously unexplored perspective on the potential for co-creating value, automating financial processes, and enhancing transparency in the digital landscape. Research methodology This paper aims to develop a Smart Product-Service System (SPSS) model focused on a crowdfunding platform. The paper asks two research questions: Are there opportunities to use SPSS in CF? What benefits can a CF platform-oriented SPSS bring to ICFC, investors, and platforms? The analyses presented several suggestions for developing SPSS for CF, which will increase efficiency and shorten the fundraising time. The paper provides information on the potential of using a CF platform-oriented PSS model and explains what benefits can result from it for fundraising entities, investors, and platforms. The methodology adopted in this paper consists of the following four phases: Systematic literature review - within this phase, the authors focused on two equal activities: reviewing previous works on PSS in the industry and reviewing PSS design methods. For this purpose, they used the term “Product-Service System in industry” or its synonyms, searching databases (ProQues, Springer Link, Science Direct, Taylor & Francis Online, EBSCOhost, Scopus, Emerald, Insight, Web of Science, Ingenta, Dimensions, Wilma, IEEE Xplore Digital Library and Google Scholar). The selection criteria were works written in English, including papers published in journals, conference proceedings, book chapters, reports, and white papers. As a result of the search, 140 works from 2001 to 2023 were found, describing PSS models operating in the industry. Then, the authors used the same databases and time frame to find the term “Product-Service System design” or its synonyms. They found 74 papers (including scientific papers, conference materials, monograph chapters, and books) describing 70 PSS design methods. CF market analysis. This stage focuses on the analysis of CF platforms and CF users. Industry reports were analyzed for this purpose. Interactive design workshops - The workshops aimed to obtain as much information as possible needed to create SPSS for the CF. The workshops were held in four consecutive sessions: Training session: It was held in the form of a multimedia presentation with short videos and quizzes. It aimed to discuss practical and theoretical issues related to SPSS and CF. Brainstorming session: From this session on, participants worked divided into four groups (Group 1 (G1) - enterprises using CF, Group 2 (G2) - investors, Group 3 (G3) research institutions, Group 4 (G4) state agencies dealing with the development of economic programs). It was carried out to define the design criteria for SPSS for CF. Its participants identified important issues from the point of view of the SPSS philosophy (problems and challenges regarding CF, requirements for PSS for CF, benefits that PSS for CF can bring, services, payment system, and new technologies supporting this solution). The authors obtained informed consent from all study participants. Presentation session: It focused on the presentation and discussion of the effects of the Brainstorming session. Each group had 15 min for the presentation. Then, the authors analyzed the presentation and indicated common areas for all four groups. needs regarding digitalization, security, and efficiency of CF. Feedback and evaluation session: This session was carried out in three stages: debate, evaluation of solutions of each group, and setting priorities for the development of SPSS for CF. Debate: each of the four groups presented conclusions from the presentations of others and indicated comments regarding them. The groups asked each other questions, which they answered and dispelled their doubts. Evaluation of the developed solutions: The groups evaluated their solutions on a scale of 1 (very bad) to 5 (very good). The highest-rated points are indicated here. Establishing priorities for the development of SPSS for CF: based on previous sessions and stages of this session, all participants established key points that SPSS for CF should meet. 4. Designing SPSS for CF: Based on information obtained from the literature review, CF market analysis, and interactive workshops, the authors developed SPSS for CF. An innovative design tool, Smart Service Canvas, was used here. The developed solution was then presented to the workshop participants and discussed and improved. The developed SPSS considered the priorities indicated by the workshop participants and the most desirable services and technologies to ensure maximum benefits for all CF participants. To confirm the practical utility of the proposed SPSS for CF, a preliminary qualitative validation process was conducted. It was divided into two phases. The first phase involved expert evaluation of the proposed SPSS for CF during interactive workshops. The second phase involved an analysis of the proposed SPSS for CF consistency with the theoretical assumptions of SPSS. Crowdfunding market The CF market is a new, dynamically developing financial market segment worldwide. Globally, in 2019, it reached a value of EUR 11.6 billion. This market is expected to grow with a Compound Annual Growth Rate of 16.2% from 2020 to 2025. The market’s growth is driven by both the growing number of CF platforms and the growing interest of investors, individuals, and entrepreneurs in this alternative form of financing. A characteristic feature of the CF market is democratizing access to capital. This means that everyone, regardless of resources or location, can support various activities or ventures or collect funds independently. Unlike traditional financing forms, CF is based on direct relations between ICFC, supporters, and investors, reducing transaction costs and excluding intermediaries. The fundamental element that distinguishes CF is its diversity. It includes donations, equity, lending, and rewards. This market plays a fundamental role in financing creative projects, innovative initiatives, startups and social ventures that usually do not have access to traditional sources of financing 49 , 50 . Additionally, it allows for building a community around them. This translates into early customer engagement and developing loyalty 51 , 52 . An important aspect is transparency – supporters and investors always have access to information about the ventures and can monitor their progress 53 , 54 . A specific feature of CF is the low entry threshold for supporters and investors, which allows for greater inclusiveness. In addition, CF supports innovations, allowing ideas to be tested earlier. Thanks to this, it provides capital and contributes to social acceptance and market verification of new projects 49 , 50 . CF platforms allow ICFC to obtain financial resources for various activities or implement projects from donors. This is a relatively new and dynamically developing area of the CF market, and its value in the coming years is forecasted at hundreds of billions of euros. Recent years have been associated with its rapid development. CF platforms have become more popular and have become increasingly important in financing various projects. Many of them offer various options and forms of financing, such as donation, equity, lending, or reward. They offer several benefits, including easier access to capital, increased marketing reach, and the ability to build a global community of supporters interested in a given project. Thanks to this, they significantly increase the chances of ICFC to realize their vision. However, there are also several challenges and risks associated with their use, including difficulties related to attracting investors, problems with data security and privacy, and the need to run a complex promotional and advertising CFC 49 , 50 . The largest CF markets in the world include the USA, Great Britain, and China. In 2019, the CF market in the USA amounted to EUR 6.6 billion, in Great Britain - EUR 3.1 billion, and in China - EUR 1.9 billion. This market is developing dynamically in Poland, but it is relatively small compared to more developed markets, such as the USA or Great Britain. In 2019, the value of this market in Poland was EUR 110 million 49 , 50 . For the CF market, the progressive digitization of the economy plays a key role. This alternative form of financing draws many benefits from digitization, opening up new and previously unavailable opportunities for ICFC, supporters, and investors. Blockchain, artificial intelligence, Big Data, and social media play a fundamental role in the ongoing transformation of this market by increasing its accessibility, efficiency, and transparency. Digitization gives the ICFC the opportunity to reach a broad group of potential investors in a cost-effective and fast way. Something like this was practically impossible in traditional forms of financing. CF platforms have allowed for an automated and digitized fundraising process. This has made it possible to simplify the interaction between ICFC and supporters 49 , 50 . An analysis of reports revealed seven main problems hindering the dynamic development of CF (Table 3 ). The first is the lack of transparency and data security. This is one of the main barriers hindering the growth of CF. Opaque financial flows and unclear fund allocation mechanisms maximize the potential risk of fraud. CFC typically do not disclose how the funds raised are used. Furthermore, investors lack tools to monitor them after the financing is completed. Research in this area suggests that as many as 45% of investors withdraw from participation in subsequent CFC. This is due to the lack of access to information on project progress 51 – 55 . Another frequently encountered problem is the low efficiency and high failure rate of CFC. CF reports emphasize that currently, up to 60–70% of CFC fail. This is primarily due to the ICFC’s low managerial competence, poor planning, and lack of operational support. It is important to note that the success of a CFC depends on the ICFC ability to manage risk and investor relations. This is also lacking in current CF platforms. The lack of support for ICFC services further exacerbates this barrier 53 – 56 . Another barrier is limited integration between technology and service components. Commercially available CF platforms do not guarantee this, as they focus solely on the financial transaction 53 – 55 , 57 . The lack of monitoring and accountability after CFC completion is another visible barrier in the market. There are no available mechanisms for monitoring project progress after CFC completion. Investors, in many cases, do not receive current data and information regarding the use of funds. It is worth noting that 38% of CFC do not implement promised projects within one year of securing funding 53 – 55 , 57 , 58 . There is also a noticeable lack of tools for analyzing the risk and success of CFC. Currently, investor decisions are not based on empirical data, but primarily on emotions, intuition, and social outcomes 53 – 58 . Additional barriers include differences in data structure and the absence of common interoperability standards. This poses a significant challenge for data analytics and cross-platform collaboration. It is worth noting that CF platforms currently operate in information silos. It limits the ability to exchange data, audit, and compare CFC and ongoing projects 53 – 59 . There is a noticeable gap in the competencies of ICFC and other stakeholders. They lack the appropriate skills for planning, running, communicating, managing, and evaluating CFC. This leads to errors that prevent CFC from being successful, even though the very concept of the project for which they are raising funds is interesting and valuable from a business perspective 53 – 59 . These barriers underscore the ineffectiveness of the current CF ecosystem. It operates in a fragmented and uncoordinated manner, lacking unified mechanisms that connect technology, services, and users. Table 3. Relationships between workshop results and SPSS functions. No Problem Impact on the CF sector Literature 1. Lack of transparency Decline in investor confidence 52 – 56 2. Low campaign effectiveness High failure rate 54 – 57 3. Lack of technology and service integration Process fragmentation 54 – 56 , 58 4. Lack of post-CFC monitoring and accountability Loss of project credibility 54 – 56 , 58 , 59 5. Lack of risk assessment tools Incorrect investment decisions 54 – 59 6. Lack of interoperability Limited scalability 54 – 60 7. Competency gap Low user efficiency 54 – 60 Open in a new tab Interactive demonstration workshop To develop SPSS for CF, an interactive workshop was held at a conference on alternative sources of financing. The workshop included representatives of 20 companies, 10 research institutions, and 5 state agencies dealing with the development of economic programs. The selection of representatives was deliberate. This resulted from the fact that the aforementioned entities can jointly contribute to increasing CF efficiency, innovation, and transparency. This will support the development of innovation, entrepreneurship, and, consequently, the entire economy. The workshop lasted one working day and was held in November 2023. It included two stages carried out with breaks: Training session - was an introduction to CF and SPSS. Design session - focused on using the knowledge acquired so far. It was carried out in two stages with breaks. Moderators led it. Presentation session - the results of the SPSS design for CF were presented here. Feedback and evaluation session - This session aimed to improve, further develop, and evaluate the SPSS project. It focused on the comments and questions the teams had for each other about the presented SPSS project. Training session The training session was conducted in the form of a multimedia presentation. Short videos and quizzes were used here. All this aimed to increase the involvement of the participants. This session combined theoretical knowledge with practice and allowed its participants to understand the operation of PSS and CF and see the benefits of using SPSS in CF. This session aimed to discuss practical and theoretical issues related to SPSS and CF. The participants were introduced to the elementary issues related to SPSS. Its history, classification, design methods, differences between products and services, and practical cases regarding the operation of SPSS in enterprises were presented. There were also videos illustrating how such solutions work precisely. Intelligent technologies used in SPSS and their application were presented. Then, issues related to CF were presented. Its genesis, mode of operation, types, and evolution were characterized. An overview of operating CF platforms and their mode of operation was made. Legal issues and aspects important from the point of view of ICFC and investors were indicated. The activities before, during, and after the CFC were discussed in detail. The strengths, risks, and barriers of using CF. CF was indicated. Then, the evolution of CF-related to the digitalization of the economy and the benefits of using intelligent technologies in this area were discussed. There were also videos illustrating how CF works precisely. The next part presents issues related to the use of SPSS in CF in the era of digitalization of the economy. Finally, intelligent technologies used in SPSS and CF were indicated, as well as their benefits to these two solutions. The components of SPSS and the possibilities of its use in CF were discussed. Then, there was a part in which interactive quizzes and discussions were held. Brainstorming session This stage began with the division into four groups (Group 1 (G1) – enterprises using CF, Group 2 (G2) – investors, Group 3 (G3) – research institutions, Group 4 (G4) – state agencies dealing with the development of economic programs). Such division into groups allowed for the collection of a wide range of information from participants representing different perspectives and competencies. This phase aimed to define the design criteria for SPSS for CF. The brainstorming session was divided into the following phases: defining the problems related to CF, listing the challenges related to CF, listing the requirements that each group sets for PSS for CF, defining the benefits that PSS for CF will bring, selecting the services that should be in PSS for CF, defining the fees related to PSS for CF, listing new technologies supporting this solution. Each group held an internal discussion and listed the issues in the bullet points above. Table 3 presents the outcomes of this session, which provide suggestions for designing a PSS for CF. To ensure clarity, we limited the number of notes in each field to five. Table 4 presents the fundamental input data. These data constitute the input to the Smart Service Canvas (Fig. 1 ). for developing a PSS for CF (Fig. 2 ). Table 4. PSS design suggestions for CF. Stage Area G1 G2 G3 G4 1. Problems Changing legal regulations Insufficient legal protection for investors Lack of legislative and legal support Lack of appropriate framework for CF development Difficulties in attracting and retaining investor interest Difficulties in enforcing obligations from ICFC after the end of the CFC Problems with building long-term relationships with investors Lack of cooperation between agencies and ICFC, investors, and CF platforms Lack of experience in running effective CFC and post-CFC support Problems with access to reliable information about projects Difficulties in ensuring full transparency Low level of use of modern digital tools High costs of CFC High investment risk Limited ICFC funds for CFC Difficulties in monitoring CF effectiveness Problems with intellectual property protection Risk of fraud and unfair financial practices Low public awareness and lack of trust in CF Limited support for CF education 2. Challenges Improving the digital infrastructure of CF platforms Analysis of the risk of projects available on CF platforms Clarification of legal regulations regarding CF Improve cooperation between agencies and ICFC, investors, and CF platforms Providing greater support to ICFC Improvement of transparency of projects and reliable information about ICFC Monitoring the use of funds from CF Implement international CF standards Solution improving ICFC credibility Possibility of withdrawal from investment Support for CF development by state institutions Clarify legal regulations supporting CF development Clear and transparent legal regulations for CF Reduction of the probability of fraud and failure to fulfill promises by ICFC Raising the level of trust in projects for which funds are collected Improve competencies and level of knowledge in the field of CF Reducing CFC costs Improvement of mechanisms for protecting investor rights Provision of additional services related to CF Acquiring new investors interested in CF 3. Benefits Lower costs Improvement of investment security Increased transparency of financing Increase the availability of capital Greater transparency of financial processes Access to international markets Possibility of international cooperation Education and development of competencies Better access to global investors Transparency of investment processes Increased visibility of projects Fraud prevention Faster fundraising and reduction of CFC duration Faster financial settlements Easier management of CFC Transparent monitoring and auditing of the use of funds Support in preparing, running, and post-CFC Increased credibility of projects Access to data and analyses from CFC Support for innovative solutions 4. Services Legal, marketing, and technical support Mobile application Training Decentralized Finance (DeFi) Mobile application Personalized investment recommendations and investment reports Support in strategy planning Basic market data analysis CFC success simulations Advanced risk analysis Virtual workshops with experts Integration with external data sources Automation of agreements and transactions Alerts and notifications Market analyses Support in strategy planning Advanced risk analysis and risk management support Scenario simulations for investors Access to CFC history Investment reports 5. Fees Subscription fee Membership fee Subscription fee License Commission on collected funds Investment commission Data integration fee Subscription fee Transaction fee Cost of securing transactions Transaction fee Commission on collected funds 6. New Technologies Artificial intelligence (AI) Cybersecurity systems High-Performance Computing (HPC) Big Data Cybersecurity systems Blockchain Blockchain Blockchain Quantum Computing (QC) Big Data Quantum Computing (QC) Artificial intelligence (AI) AR/VR AR/VR Artificial Intelligence (AI) Systems Cybersecurity High-Performance Computing (HPC) Artificial intelligence (AI) AR/VR High-Performance Computing (HPC) Open in a new tab Fig. 1. Open in a new tab Smart Service Canvas for Smart Product-Service System for Crowdfunding. Fig. 2. Open in a new tab Smart Product-Service System for Crowdfunding - Concept. Presentation session This session focused on presenting and discussing the effects of the Brainstorming session, which are presented in Table 4 . The authors, as moderators of the session, presented the rules and schedule of the presentation. Each group had 15 min for the presentation. The groups were presented in the order G1, G2, G3, and G4. Each group started their presentation with a short introduction. Then, they discussed the problems and challenges related to CF. Then, the groups presented the requirements that each set for PSS for CF and the expected benefits. Next, the groups presented the services that should be provided within the PSS for CF, proposed payment models, and indicated new technologies that should support this solution. The analysis of the presentations shows that the groups have common needs regarding the digitalization, security, and efficiency of CF. The presentations indicate that the implementation of SPSS for CF can minimize the number of G1 problems through automation, management and legal support, and new digital technologies. G2 gains greater transparency, security, and access to global projects. Ultimately, this can lead to increased G2 involvement in CF. G3 sees SPSS as an opportunity for the development of ICFF, new sources of financing, and data exchange. On the other hand, G4 points to the optimization of budgets, investment monitoring, and support for innovation. This session indicates that all groups in the problem area indicated issues related to legal regulations, protection of rights and interests in CF, and transparency and credibility of projects. Recurring problems include high costs, difficulties in monitoring, and lack of experience. In the area of challenges, each group highlights the need to develop and implement specific legal regulations, improving digital infrastructure. All groups emphasize the key benefits of SPSS for CF, such as minimizing costs, improving transparency, better management of the CFC, and access to a larger group of investors. The following are indicated as standard services: technical, analytical, and legal support, risk analysis, and mobile application. Regarding fees for PSS for CF, the groups most often mention subscription fees, transaction fees, and commissions. New technologies supporting this solution are most often mentioned: AI, cybersecurity systems, Blockchain and QC. Feedback and evaluation session The feedback and evaluation session was carried out in three stages: debate, evaluation of each group’s solutions, and setting priorities for developing SPSS for CF. During the debate, each of the four groups presented conclusions from the presentations of the others and indicated comments on them. The groups asked each other questions, which they answered and dispelled their doubts. G1 questions and comments focused on the high costs of the CFC, support in its implementation, and legal regulations. G2, in turn, is concerned with transparency and investment risk. G3 referred to digital transformation and the use of digital tools in CF, while G4 was concerned with the lack of broad cooperation between all CF participants. This stage enabled the exchange of experiences between group representatives. This led to identifying common areas that are key for everyone in the development of SPSS for CF. Then, the developed solutions were evaluated. The groups mutually assessed their solutions on a scale of 1 (very bad) to 5 (very good). Their usefulness for CF participants and the possibilities they provide in developing SPSS were considered here. In the case of G1, the highest scores were given to legal, marketing, and technical support, support in preparing, running, and after completing the CFC, and transaction automation. In the case of G2, the highest scores were given to scenario simulations, personalized investment recommendations, and risk analysis tools. In the case of G3, the highest scores were given to access to data and analyses from the CFC and CF training. The highest-rated G4 solutions were Decentralized Finance (DeFi), financial transparency, and education and competence development. The highest-rated fee model was the subscription fee and the commission on the collected funds. Blockchain, AI, QC, and HPC were considered the most important parts of SPSS for CF. The last stage focused on setting priorities for the development of SPSS for CF. Based on the previous sessions and stages of this session, all participants established five key points that SPSS for CF should meet: Support for ICFC – providing support at every stage of the CFC, including tools, training, and consultations with experts appropriate to the situation and needs. Implementing new technologies – SPSS for CF must use the latest technologies in transaction security, data analysis, training, and CFC optimization. Improved security – development of solutions that eliminate the possibility of theft of ICFC ideas and the risk of fraud and unfair financial practices. Improved technical features of the digital platform – use of a scalable platform with high data throughput, interoperability, low latency, and high availability and reliability. Reduction of CFC costs – development of a practical solution based on technology that automates all processes related to the preparation and implementation of CFC in order to reduce expenses. This session ended with a summary. During the meeting, the participants emphasized the need for new solutions for CF. They also indicated that one of the opportunities is the development of SPSS for CF, which can affect the increase in the efficiency of collections and the development of platforms and digital services based on data. Smart Product-Service System for crowdfunding The literature research conducted, as well as the results of workshops with participants (G1-G4) representing various organizations, enabled us to identify fundamental problems that limit the effectiveness and credibility of CF. Based on this, five main points were formulated, which SPSS for CF aims to address: lack of competence and preparedness of ICFC – most ICFC lack basic knowledge of marketing, project management, and investor communication, resulting in low CFC effectiveness; risk of fraud and unreliable projects – a lack of practical project control tools and ICFC credibility contributes to fraud and a loss of trust; ineffective communication between participants – a lack of effective communication mechanisms limits contact between stakeholders; failed or delayed deliveries after CFC completion – lack of control and oversight over the implementation process of projects funded by CF; lack of transparency, control, and oversight over the flow of collected funds – traditional CF platforms typically do not allow for complete transaction verification and monitoring of the use of collected funds; Table 5 presents key challenges in CF and how the SPSS for CF developed in this article aims to address them. To address these challenges, the proposed solution combines digital technologies and services to provide comprehensive support to all stakeholders. Table 5. Key problems in CF and ways to solve them in the SPSS. No Identified problem SPSS for CF to address the problem Solution Mechanism 1. ICFC lack of competence and limited knowledge regarding CFC management Mentoring and education Online training, expert support, automated AI-based action recommendations 2. Risk of fraud and fraudulent projects Blockchain and smart contracts Transaction transparency, identity verification, and milestone-based fund locking 3. Poor communication between ICFC and investors Interactive communication and reporting panel Two-way communication, real-time updates, and automated notifications 4. Delays or failed deliveries after CFC Integration with IoT systems and a logistics module Real-time production and delivery monitoring and automated progress reporting 5. Lack of financial transparency Escrow system and blockchain Fund flow control, full transaction auditability, and elimination of intermediaries 6. Lack of regulatory compliance monitoring AI Automatic verification of compliance with tax regulations, AML, and GDPR 7. Lack of long-term support after CFC Support and consulting after CFC completion Implementation support, mentoring, and project outcome monitoring Open in a new tab Based on the knowledge gained, the authors developed the final solution. An innovative design tool called Smart Service Canvas was used here. It allows for addressing many aspects simultaneously and quickly obtaining a solution. At the same time, to make the whole thing clear in each field, we limited the number of notes to three (Fig. 1 ). The Smart Service Canvas enables the identification of complex relationships between all model elements. In the analyzed case, it distinguishes three main user groups from the client’s perspective: crowdfunding platforms, ICFC, and investors. Platforms aim to enhance transparency, mitigate fraud risk, and enhance transaction security. ICFC need support in preparing and promoting crowdfunding campaigns, as well as communicating with investors. Investors, on the other hand, expect reliable and professional recommendations, as well as forecasts of project success. The answer to these requirements is a value perspective. Its central element is a value perspective based on AI and data analysis. The proposed solution utilizes AI, HPC, and scoring algorithms to predict campaign success and assess risk, while Big Data and QC are used for automatic investor segmentation and trend analysis. Data is a key resource. This includes information on all users, their investment requirements, crowdfunding campaign history, financial indicators, and market trends. Thanks to SPSS analytical capabilities, it can generate personalized recommendations, automatically evaluate projects, and support investor decision-making. The ecosystem perspective considers a digital platform that combines various data sources and financing channels (including banks, venture capital institutions, and decentralized finance (DeFi)). Smart contracts and blockchain play a key role here. These two instruments guarantee transparency and automate fund management. Furthermore, they ensure a refund in the event of a default on a CF campaign. The digital platform utilizes an Open Banking API, enabling the automated flow of information and interoperability with financial markets. The matching perspective enables interactive CF campaign management dashboards, automated analyses, and real-time result simulations. The level of user interaction is high, featuring automated investment recommendations, consultations, and campaign monitoring. Revenue is primarily derived from commissions on successful CF campaigns, fees for advanced services, and premium subscriptions. This allows for value balancing for all previously identified users. The relationships between the individual Smart Service Canvas elements in the SPSS for CF context are strongly interconnected. Data on user behavior feeds the analytical components of SPSS. They then generate individual value for each user in the form of forecasts, recommendations, and automated investment decisions. Furthermore, the infrastructure of the technological ecosystem provides the foundation for interaction, security, and quality. The revenue model, in turn, illustrates the effectiveness of adapting the generated value to the requirements set by market participants. As a result, the Smart Service Canvas enables the documentation of multifaceted, dynamic interdependencies between users, data, technology, and economic value in SPSS for CF. Then, SPSS was presented to the workshop participants, discussed, and improved. The results of the work are presented in the Fig. 2 ; Tables 6 , 7 and 8 . The proposed SPSS for CF constitutes an integrated ecosystem. It combines three main components: tangible, intangible, and digital, creating a coherent solution that supports CF processes. The tangible component of the solution is the IT infrastructure (servers and data centers, modules for encryption and transaction protection, user interfaces, payment terminals, API systems, miners, and decentralized networks). This infrastructure underpins the operation of the CF platform. It is responsible for the secure transmission and reliable processing of data between all stakeholders. The intangible component comprises the services provided, as detailed in Table 5 . These services generate and deliver added value in the form of knowledge, decision support, and recommendations, thus acting as a mediator between the technology and the user. This is managed by the SPSS service module, which adapts all available services to the user’s profile, needs, and requirements. The digital component comprises the digital platform and mobile application. This is the central element of the PSS for CF and serves an integral function. The value of this solution stems primarily from the combination of advanced digital technologies that directly analyze data, optimizing CFC preparation and execution, investment processes, security, and transparency. This component automates a range of processes related to project verification, CFC performance monitoring, risk analysis, and investment recommendations. Data generated in the tangible component (including user activity) is transferred to the digital component. There, it is processed by advanced digital tools and analyzed for patterns and risks. The results of these analyses, which support user decisions in the form of advisory reports and dynamic recommendations, are then transferred to the intangible component. Feedback from the service component (including ratings, opinions, and investor behavior) is returned to the digital component, thereby feeding the learning process of the PSS for CF. As a result, the PSS for CF creates a cyclical ecosystem of data, services, and decisions. Each of these three components serves a complementary function. Their integration enables a seamless flow of information and facilitates continuous service improvement. In practice, this improves trust, CFC effectiveness, and user satisfaction. Table 6. Service packages in the developed SPSS for CF. No. Service Package Services No. Service Package Services 1. Basic Access to campaign history 2. Advanced Automatic CF campaign analysis Payment system integration Dynamic fund allocation Regulation compliance monitoring Integration with external data sources Basic market data analysis Intelligent AI recommendations Basic marketing tools Real-time CFC monitoring Basic technical support Personalized investment reports Basic CFC management Notification system CFC progress reports AR/VR training for users Project and investor registration Strategy planning support Standard investment reports Advanced marketing tools 3. Premium Big Data analytics for the CF market 4. Elite AI platform for CFC management Automatic adjustment of CFC strategy Advanced integration with external platforms Automatic KPI reporting Cost optimization with HPC Blockchain and DeFi integration Dynamic portfolio management Smart contracts for transactions Virtual workshops with experts Real-time process monitoring Real-time risk management Optimization of investment strategies Access to global financial trends Personalized advisory and legal support Scenario simulations for investors CFC success predictive simulations Individual strategic consulting Advanced risk analysis QC for market analysis Open in a new tab Table 7. Extended service features SPSS for CF. No Functional area Description Supporting Technologies Value for users 1. Escrow services Secure storage and automatic release of funds upon achieving project goals Blockchain and smart contracts Trust, eliminating the risk of misuse of resources 2. Expert mentoring Automatic matching of mentors to projects, online consulting sessions AI and SPSS expert database Knowledge transfer, implementation support, competence development 3. Automated compliance checks AML, GDPR, tax, and financial law compliance checks AI and semantic rules and Big Data Regulatory compliance, legal risk reduction 4. Integrated logistics support Monitoring of product implementation and distribution after CFC IoT and Blockchain Transparency of deliveries, guarantee of fulfillment of obligations Open in a new tab Table 8. Smart Product-Service system for Crowdfunding - Concept. Benefits for the ICFC Benefits for a CFC Benefits for the project being funded Benefits for the investor Benefits for the CF platform Simplified legal and accounting services Elimination of human errors in the financing process Increased market visibility Faster access to reliable information User identity verification and fraud prevention Marketing strategy optimization Dynamic analysis of CFC progress Increased chance of full funding Direct communication with project creators More users Increased credibility Better access to investors Precise risk analysis Greater investment security More successful CFC Dynamic consulting Reduced risk of failure Anticipating potential obstacles Personalized recommendations Full transaction transparency Open in a new tab Figure 2 also illustrates the relationships between the aforementioned SPSS for CF components. The physical component forms the physical foundation of SPSS for CF. The intangible component creates a layer of added value for all stakeholders. The digital component, in turn, collects data from the physical component, analyzes it, and dynamically adapts services based on the data, thus fulfilling an integrative function. The relationships between these components are reciprocal. Data generated in the digital environment enables automatic optimization of service processes. Stakeholder activity provides a source of data enabling further improvement of each component. This PSS for CF enables continuous learning based on current data and the co-creation of value by all stakeholders. An important element of SPSS for CF are services. They support all parties participating in CF and are intended to provide them with optimal conditions for using CF. Thanks to them, activities related to managing CFC, investments, and financing are dynamically adjusted for users. SPSS activity in this area focuses on the constant exchange of data and information, automatic coordination of resources, and adaptation of services in real time. Services in SPSS are delivered on demand and scaled depending on the requirements of the parties participating in CF. This means that SPSS automatically diagnoses users’ needs and adjusts the range of services they can access. The CF platform here is tasked with coordinating the entire process of alternative financing, from the moment of user registration through the preparation and running of the CFC to post - CFC activities and finalization of the investment. Within SPSS, individual services are interconnected, and their functioning is focused on optimizing activities and analyzing data in real time. SPSS guarantees users constant access to services. They are launched and managed digitally. User activity is monitored, and interactions and resources are adjusted based on it. Each phase of the process is controlled and optimized. This is aimed at increasing the efficiency of operations and reducing risk. All services are integrated in one digital environment. This allows for their harmonized operation and ongoing mutual complementation. The developed SPSS operates in a continuous improvement model. This means that SPSS analyzes data and information, optimizes and updates services, and adapts to changing user needs and market requirements. Table 5 presents services organized into four packages. This illustration expands on the functional structure of SPSS for CF (Fig. 2 ), illustrating how specific solutions meet the requirements and needs of participants (G1-G4) representing different perspectives and competencies defined in Table 8 . This demonstrates that the proposed SPSS for CF was developed based on a coherent logical sequence (starting from needs identification, through conceptual design, to its visualization and operational description). It is essential to note that the challenges and problems identified during the workshops closely align with the functions and services of SPSS for CF. The participants’ priorities (G1-G4) correspond to the structure of the component and service packages, and the digital enabling technologies correspond to the digital integration mechanisms. This illustrates how the research results were applied to develop a specific solution. The proposed solution supports all phases of CFC (pre- CFC, during, and post- CFC). In addition to the services listed in Table 7 , SPSS for CF offers four advanced functionalities. These improve the safety, effectiveness, and sustainability of CF outcomes. SPSS for CF incorporates an escrow function. This allows investors’ funds to be stored in a secure, blockchain-based environment. Funds are automatically released upon reaching agreed-upon project milestones. This strengthens trust between participants and eliminates the risk of misuse of funds. ICFC expert mentoring pairs experts from various fields (finance, marketing, law, logistics, and technology) with mentors based on the project type and its specific development requirements. This feature supports competency development and product implementation. Automated compliance monitoring analyzes CFC and projects for compliance with current tax, financial, and data protection regulations. SPSS for CF utilizes AI to diagnose potential violations and automatically recommends corrective actions. Integrated logistics support focuses on supply coordination and value chain management after CFC completion. Integration with IoT and logistics operators enables the CF platform to continuously monitor the production and distribution process of products financed by CF, providing the ability to report progress to investors. An important element of the developed SPSS for CF is the digital platform. It handles transactions, dynamically adapts to users current needs, and provides them with services needed at a given time. The flexible settlement model guarantees ICFC and investors the option of choosing a financing strategy that depends on the project, investment period, and risk. The platform manages the financial infrastructure and ownership rights, while ICFC and investors only use the available tools. As a result, ICFC can focus on their core business instead of wasting time on activities related to managing the CFC. The foundation of this model is the use of modern technologies. AI allows for automatic analysis of the CFC and forecasting its duration and success. QC enables risk modeling, which is a new level of diagnostics of potential opportunities and threats related to the CFC of a specific project. Thanks to advanced algorithms, analyzing historical data, market trends, and investor profiles is possible. All this provides personalized recommendations for CFC and optimizes financing strategies. Additionally, SPSS allows for remote resource management. In the context of CF, it means monitoring financial flows, analyzing the return on investment, and automatically adjusting investment strategies in real time. The use of smart contracts and blockchain will ensure the transparency of financial processes and guarantee their security. Smart contracts automatically regulate the flow of financial resources, releasing them only when the established conditions are met. This excludes the risk of misuse of financial resources and fraud. Blockchain allows for tracking each transaction and complete verification of the identity of users. This makes it possible to minimize administrative costs. For projects that involve the physical production or delivery of equipment (e.g., technological devices, engineering solutions), SPSS for CF integrates with IoT. IoT devices (sensors, telemetry systems) transmit project progress data—e.g., production stages, resource consumption, or timely completion—directly to the CF platform. This data is stored in the blockchain and analyzed by AI. This provides investors with real-time insight into the project’s progress, enabling them to respond quickly to potential deviations. The proposed SPSS for CF distinguishes between technologies that can be implemented in the short term and those with long-term development. HPC is an operational technology that can be utilized in current technological and market conditions. QC serves as a forward-looking technology. HPC is used in PSS for CF to handle large data sets, advanced CFC analytics, simulate investment scenarios, and optimize processes in near real time. Currently, HPC is the most accessible and mature solution for implementing the predictive and analytical functions of SPSS for CF. QC, on the other hand, is a long-term component of SPSS for CF. In the future, it may enable much more advanced calculations, including portfolio optimization, multidimensional risk modeling, and analysis of nonlinear market dependencies. Currently, it is a conceptual element that indicates a possible evolutionary path for SPSS for CF. This approach allows for maintaining a balance between the practical utility of the developed solution and its innovativeness and long-term development potential. In this case, SPSS is associated with implementing dynamic financial models. Thanks to them, investors can modify their investment decisions in real time. Instead of one-time investments, SPSS allows the adjustment of the investment portfolio to the current market situation. This is particularly important for the financial liquidity of ICFC and the platform. Integration of the developed solution with HPC and Big Data will guarantee analyses of market changes on a global scale, forecasting possible investment opportunities and threats. The implementation of SPSS will benefit all parties participating in CF. ICFC will be able to focus on implementing their projects. From now on, they will not waste time managing financial, accounting, and legal formalities because all these activities will be automated and verified by an intelligent system. Investors, on the other hand, will have access to safe and optimized investment models. This will reduce the risk of financial losses and maximize their involvement and activity in CF. In turn, thanks to long-term cooperation with ICFC and investors, CF platforms can generate predictable and stable revenues. An important aspect of SPSS for CF is the dynamic update of financing models. ICFC can modify their financing strategies, adapting them to changes in the market and investor preferences. SPSS also guarantees continuous risk analysis and forecasting of potential problems, eliminating interruptions in project financing. Using new technologies means that all parties participating in CF have constant access to educational materials and online training. This increases their knowledge of CF and competencies in this area. This solution indicates the educational function of the developed solution, which can accelerate the acquisition of knowledge in the field of alternative forms of financing. To confirm the practical utility of the proposed PSS for CF, a preliminary qualitative validation process was conducted. It was divided into two phases (Table 9 ). The first phase involved expert evaluation of the proposed PSS for CF during interactive workshops. The second phase involved an analysis of the proposed PSS for CF’s consistency with the theoretical assumptions of SPSS. Table 9. Summary of the SPSS for CF validation process. No Phase Aim Methodology / Participants Evaluation criteria Explanation of the evaluation criteria 1. Expert evaluation of the proposed SPSS for CF Assessing the practical relevance, logic, and usefulness of SPSS for CF Participants of the evaluation session of the ready SPSS for CF were divided into four groups (G1-G4); tools: questionnaire, focus groups Model understandability Level of structural clarity and logical connections between all elements Usability and User Value Potential of SPSS for CF in solving real problems faced by CF market participants Implementability Prospects for implementation using existing organizational infrastructure and available technology Transparency and Security The solution’s ability to guarantee data security, financial transparency, and transaction verification Market compatibility Adaptation of SPSS for CF functionality to users Sustainability Level of integration of social, economic, and environmental aspects in SPSS for CF 2. Analysis of the compatibility of the proposed SPSS for CF with the theoretical assumptions of SPSS Assessing the conformity of SPSS for CF with the SPSS theoretical framework Comparative analysis of the SPSS structure for CF with literature assumptions Component integration Degree of integration of physical, service, and digital components Value Co-creation User involvement in the SPSS development process Life cycle The extent to which SPSS for CF covers the full service lifecycle (from CFC planning, through its implementation and monitoring, to the post-implementation stage) Interoperability The ability of SPSS for CF to integrate with other platforms, financial systems, and databases while maintaining consistent information flow Social impact The impact of SPSS for CF on the development of participant competencies, improving public trust, and supporting education about CF Open in a new tab An expert evaluation of the proposed PSS for CF was conducted after its presentation. Participants, divided into four groups (G1-G4), then evaluated the results through an expert survey and group discussions. During the validation process, G1-G4 evaluated the results based on six criteria (Table 8 ). The evaluation was based on a scale of 1 to 5 (1 – very low, 5 – very high). The overall PSS for CF was 4,4, with a standard deviation of 0.52. This result indicates a high level of acceptance of the proposed solution. The highest-rated categories included model understandability (4,5), transparency, and security (4,5). This confirms that the developed PSS for CF is transparent, while the use and integration of technologies were considered credible. Slightly lower scores were given for implementation feasibility (4,25). Participants representing the four groups justified this evaluation by citing the need to define specific technical requirements. The high coefficient of agreement (Kendall’s W = 0,82) confirmed the consistency of the G1-G4 opinions and underscores the clear assessment of the value of the proposed PSS for CF. At this stage, the PSS for CF was assessed as transparent, conceptually coherent, and practical. Furthermore, G1-G4 noted that its structure meets the actual requirements of CF market participants. The expert evaluation of the proposed PSS for CF emphasizes that the developed solution can increase trust, security, and efficiency of CF processes. This will be achieved through the integration of technological and service components into a single digital environment. The analysis of the proposed PSS for CF compliance with SPSS theoretical assumptions was theoretical and analytical in nature. This phase involved a thorough assessment of the proposed solution’s compatibility with the established SPSS conceptual framework. The goal was to verify whether the PSS for CF exemplified the fundamental SPSS design principles and the current rationale for combining technologies, services, and value-generating processes. The analysis demonstrated substantial compliance with the fundamental SPSS design principles (Table 9 ). The PSS for CF integrates physical, digital, and service components. This aligns with the principle of a holistic approach to value generation 43 , 48 , 60 . The modern digital technologies employed in this solution confirm its compliance with the SPSS paradigm, where they serve as an active element in value generation 60 – 62 . Furthermore, they enable continuous improvement of the PSS for CF, consistent with life-cycle-oriented design 63 – 65 . Furthermore, the SPSS proposed in this article reflects the concept of the CF service lifecycle, enabling project management from initiation to CFC completion and subsequent reporting of results 66 – 68 . In terms of interoperability, the developed solution enables integration with databases, payment systems, and external analytical modules 48 , 60 , 63 . This confirms its flexibility and compliance with SPSS open architecture principles. From a social impact perspective, SPSS for CF supports digital education 4 , 69 , 70 . Additionally, it offers expert mentoring and guarantees the transparency of financing processes. All this fosters increased trust and inclusiveness in CF. The second phase confirms that SPSS for CF aligns with the theoretical principles of SPSS design. This solution can be considered an example of an entirely new generation of SPSS, in which the source of innovative advantage lies in the integration of process, technological, and social elements. SPSS for CF meets all theoretical validation criteria (Table 9 ). This confirms its deep grounding in the scientific literature on PSS design and its potential for practical application in CF. The conclusions from the second stage confirm that the developed SPSS model is consistent with the theoretical principles of PSS and SPSS design and can be considered an example of a new generation of intelligent service systems, in which the integration of technological, process, and social components is a source of innovative advantage. The model meets all five theoretical validation criteria, confirming its solid grounding in the scientific literature and its potential for practical applications in the digital financial services sector. Discussion The SPSS for CF proposed in this paper (Fig. 1 ), developed using the Smart Service Canvas (Fig. 2 ), integrates tangible, intangible, and digital components to support CF. This solution is based on the principles of value co-creation. ICFC, investors, and platforms interact based on real-time data. The technological infrastructure, i.e., the tangible component, ensures the proper functioning of SPSS for CF, as well as the protection of transactions and data. The set of supporting services (Table 5 ) constitutes the intangible component. Intelligent technologies constitute the digital component, enabling automated decision-making, risk assessment, financial flow transparency, and customization. Furthermore, it combines the previously mentioned tangible and intangible components. The proposed SPSS for CF highlights three significant innovations. The first is dynamic service personalization. This allows for the tailoring of support to the specific user and the stage of the CFC process. Transaction auditing and automated control are also included. They operate based on blockchain and smart contracts, thus reducing the risk of fraud. The third is the cyclical learning of SPSS for CF. Analyzing historical data optimizes financing processes and suggests the best options and strategies. Compared to other SPSSs used in business practice, the proposed solution focuses on intangible aspects of value. This includes trust, transparency, and interaction, which are fundamental to CF. Besides improving the efficiency and security of financing processes, SPSS for CF enables the formulation of rules for designing innovative digital services, which can then be replicated in other industries. The findings of the interactive design workshops were fundamental to the proposed SPSS for CF. Each stage of these workshops provided a source of data that was directly transformed into the functions and components of the developed SPSS. Based on the workshops, relationships between the workshop findings and SPSS functions were established, which are presented in the Table 10 . Table 10. Relationships between workshop findings and SPSS functions. No Workshop Outcomes SPSS-based component SPSS Functionality Description SPSS Component 1. The need for continuous support for the ICCF Consulting and education Provides consultations, training, and recommendations related to the preparation, management, and evaluation of CCFs. Intangible 2. Improving efficiency and cost reduction CCF process automation Automates project registration, settlement, and CCF progress reporting. Digital 3. Improving security and transparency Blockchain and smart contacts Ensures auditability and data integrity, and enables user identity verification. Digital 4. Improving the digital infrastructure of CF Platforms HPC module and API architecture Supports integration with external systems and real-time data processing. Tangible and digital 5. Individualizing services and access to analytical data AI and investment recommendation Analysis of user behavior and recommendations regarding investment strategies, training, or CCFs. Digital 6. Improving CCF management and investor communication Interactive CF management Provides real-time CCF monitoring, report generation, and investor communication. Intangible and digital 7. Improving trust between CF participants Smart contracts and trust rating system Automatically enforces financing conditions and enables campaign credibility assessment. Digital 8. Education and development of digital competencies Training platform and knowledge base Access to e-learning resources, materials, and certified courses on CF and SPSS. Intangible Open in a new tab The proposed SPSS for CF is a direct result of interactive design workshops conducted at a conference on alternative financing sources. The workshops aimed to identify the real needs, requirements, barriers, and expectations of participants, divided into four groups (G1-G4), which served as the foundation for the structure, components, and functions of SPSS for CF. During the workshops, participants (G1-G4) identified the most important areas from a CF perspective (Table 11 ). Each of these areas was transformed into a specific element of SPSS for CF. Therefore, the workshops were not merely a diagnostic phase. However, a process of value co-creation, in which participants divided into four groups (G1-G4) actively participated in defining the functions and operation of SPSS for CF. Table 11. Relationship between workshop results and SPSS for CF. No Areas identified during workshops Reporting groups Key results Functionality SPSS for CF Reference SPSS for CF Digital technologies used Effect on users 1. Lack of transparency and trust G1, G2, G4 The Need for Full Transaction and Settlement Visibility Transaction monitoring and automation Audit Guarantee and Security of Financial Operations Blockchain, Smart Contracts, Big Data Automatic contract enforcement and real-time fund tracking 2. Risk of fraud and lack of security G2, G3, G4 Implementation of Data Verification and Security Mechanisms Digital security and identity verification User Authentication and Anomaly Detection Cybersecurity systems, AI, Big Data Improved trust and reduced fraud risk 3. Lack of support during the campaign G1, G3 The Need to Use Analytical Tools and Consulting in CFC Planning Service packages supporting ICFC CFC Data Analysis and Automated Recommendations AI/ML, Big Data, HPC Predicted CFC success and marketing recommendations 4. Lack of monitoring mechanisms after the campaign ends G1, G2 Reporting Project Progress and Communicating with Investors Monitoring and reporting after CFC completion Continuous CFC Progress Tracking and Automated Reporting IoT, Blockchain, AI Continuous investor updates on project implementation 5. Competence gap and need for education G3, G4 The Need for Practical Training and Simulations Training services, mentoring, and consulting AR/VR and AI-Based Training and Simulations AR/VR, AI Improved competencies and understanding of the CF process 6. Low interoperability of CF systems G4 Lack of Data Integration and API Standards Data integration Data Integration Between Various Financial Computing Platforms Open API, Big Data Easier collaboration between CF platforms 7. High costs and low campaign effectiveness G1, G2 Automation of Operations and Settlements Modern fee system Dynamic CFC Cost and Time Management AI, HPC, QC Reduced CFC costs and time Open in a new tab Although the SPSS for CF proposed in this paper focuses on improving CFC efficiency and minimizing operating costs, its implementation requires high upfront costs (Table 12 ). These capital expenditures are typical for advanced, digital systems based on intelligent technologies. They primarily include the development and integration of a digital platform, the implementation of analytical tools (including AI, Big Data, HPC), ensuring regulatory compliance and security, and stakeholder development. It is important to note that these expenditures are one-time or short-term in nature. However, the benefits (including minimizing the number of failed CFC, improving the quality of investment decisions, and automating processes) are scalable and long-term. From this perspective, a SPSS for CF should be viewed as a strategic infrastructure investment. Its return will occur as the number of ICFC and the number of CFC served increase. Table 12. The structure of initial costs and long-term savings in SPSS for CF. No Category Cost and activity scope Cost Type Time horizon Economic Impact 1. Digital platform development Platform design and implementation, mobile app, API Initial investment Short-term The foundation operations of SPSS for CF 2. Digital technology integration AI, Big Data, Blockchain, HPC, cybersecurity Initial investment Short-term Process automation and analytics 3. Organizational and regulatory integration Compliance, licensing, audits, process customization Initial investment Short-term Legal risk reduction 4. Competency development User training, mentoring, AR/VR modules Development investment Medium-term Higher campaign efficiency 5. Process automation Transaction management, reporting, monitoring Operating savings Medium- and long-term Reduced administrative costs 6. Reducing failed CFC Risk prediction, AI decision support Indirect savings Long-term Increased CFC success rate Open in a new tab Conclusion The paper focuses on CF. This is a relatively new and dynamically developing segment of the financial market. It allows ICFC and investors to join forces to finance various types of social projects, innovations, products, and business projects. In recent years, it has evolved significantly and become a tool supporting business projects and startups. Crowd-lending models dominate in it. A significant increase in the use of digital technologies, which allows for much better forecasting of the success of a CFC and diagnostics of market trends, has accelerated the development of CF. The available literature indicates a lack of SPSS solutions dedicated to CF. In turn, the analysis of the CF market indicates the need for new solutions for this market related to the ongoing digitalization. This work complements the literature on the use of SPSS in CF. Theoretical and practical issues related to SPSS and CF were analyzed here. The new SPSS project was implemented during interactive workshops conducted at the conference on alternative sources of financing. In the context of CF, SPSS is associated with implementing innovative solutions for CF platforms that are of great importance in the digitalization of services and improving the efficiency of financing processes. SPSS allows for improving activities related to the collection of funds, predictive financial analyses, and investor data management. Additionally, thanks to tools such as smart contracts and blockchain, it guarantees automatic enforcement of contracts. Implementing SPSS solutions to CF platforms will allow for faster evaluation of projects and automatic validation mechanisms that exclude projects and investments with poor efficiency, thus improving investor confidence. More accurate matching of offers to investors will enable a hybrid approach to data analysis, simultaneously increasing CF platforms’ attractiveness and value. Using SPSS in CF also means meeting personalized solutions that allow platforms to adapt to various ICFC, investors, projects, and forms of financing. The conclusions drawn from the interactive project workshops are as follows: PSS for CF is an evolution from a simple financing system into a complex ecosystem of digital services, enabling support in CFC preparation, market analysis, predictive forecasting of CFC results, and personalization of services. Additionally, such an ecosystem will allow for the integration of all those interested in CF in one place, which will contribute to the improvement of the use of financial resources, Additional services segregated into packages and provided before, during, and after the CFC allow for offering solutions previously unavailable on the CF market, tailored to the needs of all those interested in CF. SPSS guarantees greater transparency and security by eliminating the risk of fraud thanks to automatic verification of user identity and blocking of suspicious transactions. Additionally, implementing smart contracts will enable the autonomous allocation of funds, eliminating the risk of failure of ICFC to fulfill their obligations. Financial resources are released only after achieving the established project milestones. The developed SPSS guarantees access to educational materials and online training for all parties participating in CF regardless of place and time. This element plays a vital role in gaining new knowledge and improving competencies in the field of CF. In this case, online education guarantees faster adaptation to the rapidly changing market situation. In this case, developing SPSS requires considering emerging and changing legal regulations and the obligation to obtain a permit from the entities competent to supervise financial institutions. Obtaining a license and operating within these regulations guarantee credibility and competitiveness. The model developed in the work is a comprehensive solution, which is the answer that participants of the CF market have been waiting for. Implementing interactive workshops with representatives of various institutions is the basis for creating and implementing SPSS for CF. They indicate several guidelines and circumstances that need to be focused on to develop a solution that guarantees the quick and successful implementation of a CFC and investment security. The paper indicates that cooperation between various market representatives is necessary to create innovative technological solutions. SPSS design for CF in a workshop format allowed all participants to jointly specify market needs, diagnose development barriers, and recognize the potential of new digital technologies in CF. Additionally, this form of design enables more effective acquisition of knowledge in CF and its complex processes. In addition, working in groups enabled the exchange of knowledge and stimulated creativity and workshop participants’ digital competencies. It also increased their motivation and commitment to explore the subject of CF further. Participants greatly appreciated the training session in which they were given a large amount of knowledge in the field of SPSS and CF. The results of the interactive workshops show that implementing innovative workshop methods focusing on real market problems enables the development of theoretical knowledge and practical skills necessary to develop solutions such as SPSS. The SPSS for CF proposed in this paper offers several theoretical implications regarding SPSS and value co-creation. First, it expands the standard approach to SPSS by transferring this concept and areas of the economy that are purely industry-related to the area of digital finance and data-driven services. Furthermore, it demonstrates that SPSS can play the role of a sociotechnical system that integrates people, technologies, and processes. Value is co-created in real time by various user groups (campaign initiators, investors, platform operators). The developed solution expands the theoretical framework of SPSS by integrating AI, blockchain, and predictive analytics as components that support transaction security and decision-making processes. This demonstrates the digital-social dimension of SPSS, where user interactions and data become the primary source of value. Furthermore, the SPSS for CF provides a theoretical foundation and a reference point for further research on the development of services in decentralized environments, as well as in industries that rely on data and collaboration. In addition, it highlights the potential of using the Smart Service Canvas as a flexible tool for defining and evaluating smart financial services. The SPSS for CF developed in this paper also provides several practical implications for implementation frameworks of CF platforms, aiming to enhance efficiency, operational security, and transparency. It also highlights how modern digital technologies can be utilized to enhance CFC automation, dynamically tailor offers, and assess investment risk. For investors, this translates into improved security and individualized investment, while for ICFC, it involves improved management of the financing process and ongoing access to advisory services. Implementing the solution presented in this article requires meeting specific requirements. A technical infrastructure enabling real-time data processing is essential. Furthermore, integration with financial and legal systems that ensure regulatory compliance seems essential. Furthermore, the development of digital skills among platform users and operators is crucial. If these conditions are met, SPSS can become an instrument that allows for the full digitization of financial reporting processes while maintaining full transparency and trust in the relationships between all users. By popularizing digital services, SPSS for Financial Reporting can make a positive contribution to the digital transformation of the micro, small, and medium-sized enterprise sector through the implementation of integrated, intelligent financial services. Furthermore, this solution can support the development of sustainable financial services. Despite its important theoretical and practical contributions, this study has certain limitations. The first is the conceptual nature of the SPSS for CF proposed in the article. This boils down to the fact that the proposed solution was developed at the architectural, service-logic, and technological levels but was not implemented as a functioning IT system. Although this level of abstraction is consistent with the study’s goal and is standard for research conducted in the context of PSS/SPSS design, it limits the prospect of empirically verifying SPSS for CF performance in real market conditions. Another limitation is that the empirical part of the study is based on a single interactive workshop conducted with the participation of four stakeholder groups (Group 1 (G1) – enterprises using CF, Group 2 (G2) – investors, Group 3 (G3) – research institutions, and Group 4 (G4) – state agencies responsible for the development of economic programs). Although the interactive workshop was multifaceted and allowed for the co-development of SPSS for CF with representatives of the four key groups, its single-session nature may limit the generalizability of the results. It should also be noted that this study is geographically limited. The analyses and interactive workshops on the CF sector were conducted primarily within a single geographic area. This indicates that the identified problems, requirements, needs, and regulations may differ significantly in other regions of the world. Differences in legal regulations, the maturity levels of CF markets, and digital infrastructure may affect the feasibility of the direct transfer of the SPSS for CF proposed in the article. An additional limitation may be the validation of SPSS for CF. This validation was preliminary and based on expert assessment and analysis of compliance with the theoretical assumptions of PSS/SPSS. Although this approach is justified in the conceptual research phase, it cannot replace full empirical validation based on quantitative data, pilot tests, or a comparative analysis of CFC results before and after the introduction of SPSS for CF. Future research will focus on developing a comprehensive SPSS business model for CF. The authors plan to conduct surveys of companies operating in various economic sectors that have already used CF and those that intend to use CF. Furthermore, future research will analyze the literature on SPSS design, develop a new SPSS design method, and validate it. Acknowledgements Love and praise God. Mater Misericordiae pray for us. Abbreviations PSS Product-service system SPSS Smart product-service system CF Crowdfunding ICFC Initiators of crowdfunding campaigns CFC Crowdfunding campaigns G1 Group 1 G2 Group 2 G3 Group 3 G4 Group 4 AI Artificial intelligence HPC High-performance computing QC Quantum computing DeFi Decentralized finance AR/VR Augmented and virtual reality KPI Key performance indicators AML Anti-money laundering GDPR General data protection regulation Author contributions Mariusz Salwin - Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Project administration, Supervision Aneta Ewa Waszkiewicz - Warsaw School of Economics (SGH), College of World Economy, Department of International Finance, 6/8 Madalińskiego Street, 02-513 Warsaw, [email protected] - Project administration, Supervision. Funding This research received no external funding. The Authors received no funding for this work. Data availability The data supporting the findings of this study on the development of a Smart Product-Service System (SPSS) model focused on a crowdfunding platform are available upon request from the corresponding author. Due to institutional policy and data privacy considerations, these data are not publicly available. However, interested researchers may obtain access to them upon reasonable request by contacting Mariusz Salwin at [**[email protected]**](mailto: [email protected]) .No proprietary or third-party data were used in this study. Declarations Competing interests The authors declare no competing interests. Ethical approval No experiments involving human tissues were carried out. A statement to confirm that all methods were carried out in accordance with relevant guidelines and regulations. A statement to confirm that all experimental protocols were approved by a named institutional and/or licensing committee. The authors obtained informed consent from all study participants. The study was conducted in accordance with the Declaration of Helsinki, and approved by the ethical standards of the Warsaw University of Technology, laid down in § 1 Sect.  3 of Annex to Decision no. 314/2024 of the Warsaw University of Technology Rector of 2 December 2024 on the establishment of the Team for Ethics of Research Involving Human Beings and introduction of Regulations for the Team*.This is confirmed by the certificate dated October 22, 2025. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Paliyenko, Y. et al. Requirements for a smart product-service system development framework. Proc. Des. Soc. 3 , 3085–3094. 10.1017/pds.2023.309 (2023). [ Google Scholar ] 2. Ashari, F. Smart contract and blockchain for crowdfunding platform. Int. J. Adv. Trends Comput. Sci. 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