Assessing the impact of digital tools on the recruitment process using the design thinking methodology

Magdalenić, Danijela; Luić, Ljerka Article Assessing the impact of digital tools on the recruitment process using the design thinking methodology Administrative Sciences Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Magdalenić, Danijela; Luić, Ljerka (2025) : Assessing the impact of digital tools on the recruitment process using the design thinking methodology, Administrative Sciences, ISSN 2076-3387, MDPI, Basel, Vol. 15, Iss. 4, pp. 1-17, https://doi.org/10.3390/admsci15040139 This Version is available at: https://hdl.handle.net/10419/321283 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Received: 14 March 2025 Revised: 3 April 2025 Accepted: 4 April 2025 Published: 9 April 2025 Citation: Magdaleni´c, D., & Lui´c, L. (2025). Assessing the Impact of Digital Tools on the Recruitment Process Using the Design Thinking Methodology. Administrative Sciences, 15(4), 139. https://doi.org/10.3390/ admsci15040139 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article Assessing the Impact of Digital Tools on the Recruitment Process Using the Design Thinking Methodology Danijela Magdaleni´c * and Ljerka Lui´c Postgraduate Studies, University North, 48000 Koprivnica, Croatia; [email protected] *Correspondence: [email protected] Abstract: This study explores the information–communication discourse in modern recruitment by applying the Design Thinking (DT) methodology to enhance employee selection and integration strategies. By incorporating digital tools and empathetic approaches, this study examines innovative practices that improve candidate experience and ensure alignment with organizational culture. This study follows the DT framework, encompassing empathy, problem definition, and ideation, with a research sample including candidates, employees, and HR professionals. Methods such as desk research, interviews, diary methods, and P/C matrix diagonalization, supported by original metrics, assess the effectiveness of these approaches. The findings highlight that digital tools, particularly gamification and online assessments, significantly enhance recruitment quality, increase efficiency, reduce hiring time, and improve cultural alignment. Additionally, this study develops informational constructs of knowledge, skills, and attitudes, offering deeper insights into key factors for successful hiring. By integrating new media and technological solutions, this research contributes to transforming traditional recruitment practices into more candidatecentred processes. Further evaluation through complementary studies is recommended to determine the long-term impact of digital tools on recruitment outcomes and employee selection success. Keywords: design thinking; recruitment; information–communication discourse; digital tools; informational constructs 1. Introduction The recruitment and selection process is crucial for the successful functioning of organizations, yet traditional selection methods are often time-consuming, inefficient, and fail to meet the needs of both candidates and organizations. In today’s corporate environment, characterized by rapid changes and intense competition for talent, innovative approaches to human resource management have become a necessity. Digitalization has proven to be a key factor in shaping how companies manage resources, engage with clients, and incorporate sustainability into their business models (Manuti & Pasquale, 2017). Technologies such as the Internet of Things (IoT), artificial intelligence (AI), and blockchain are revolutionizing resource management by enhancing transparency and simplifying administrative processes (Ronˇcevi´c et al.,2024). Within this context, digital technologies—including the IoT, big data, AI, virtual and augmented reality, and digital platforms—exert a powerful transformative influence, fundamentally redefining value creation (Dragiˇcevi´c et al.,2023). Advancements in information and communication technologies have transformed recruitment, selection, and hiring processes, prompting organizations to adopt contemporary methods that reduce costs, enhance efficiency, and strengthen competitive advantages Adm. Sci. 2025,15, 139 https://doi.org/10.3390/admsci15040139 Adm. Sci. 2025,15, 139 2 of 17 (Baši´c & ´ Culibrk,2021;Abuladze & Hasimi,2023;El Ouakili,2025). Gamification has also emerged as an innovative technique to engage candidates and improve the effectiveness of recruitment strategies, making the process more dynamic and aligned with modern candidate expectations (Vorecol,2024). Holm’s (2009) research suggests that e-recruitment increases the number of applications, shortens the time from job advertisement to offer acceptance by two-thirds, and reduces costs. The integration of new technologies into the selection and hiring process enables organizations to make faster, more accurate, and more objective decisions, improving the candidate experience and increasing the efficiency of HR processes (Albassam,2023). The DT methodology, which fosters creative problem-solving, innovation development, and user-centricity, represents a potential solution for optimizing these processes (T. A. Kelley,2001;Martin,2009;Rauth et al.,2010;Liedtka,2014b;Glen et al.,2015;Kolko,2015;Beckman,2020;Björklund et al.,2020;Johann et al.,2020). This paper distinguishes between two key terms: the DT method and the DT methodology. DT as a method refers to a way of thinking that combines analytical and intuitive approaches, emphasizing empathy, creativity, and the iterative adaptation of solutions based on user needs (Brown,2009;Dunne,2018). It does not rely on traditional scientific research instruments such as surveys but rather employs observation and interaction to gain a better understanding of the user experience (Ní Shé et al.,2021;Li et al.,2018). This aligns with the idea that Design Thinking fosters user-centred problem-solving by engaging directly with stakeholders in real-world contexts (Brown,2009;Baran,2017). On the other hand, DT as a methodology entails a structured process consisting of five clearly defined stages: empathy, definition, ideation, prototyping, and testing (Mariani et al.,2025). This approach is widely recognized for developing innovative solutions through iterative testing and refinement (Alqahtani,2022). The methodological framework of Design Thinking enables organizations to integrate creativity into their strategic decision-making while maintaining flexibility to adapt based on feedback (Baran,2017). Design Thinking (DT) methodology, originating from product and service design practices, has gained increasing attention in broader business contexts. Brown (2009) emphasizes DT’s focus on user empathy, making it particularly suitable for addressing complex problems such as recruitment processes. Cross (2011) highlights how DT enables the creation of innovative solutions through collaboration and iterative approaches, crucial for adapting recruitment processes to dynamic labour markets. In the context of human resource management, Liedtka and Ogilvie (2011) argue that applying the DT methodology can enhance processes through a better understanding of candidate and organizational needs. The authors suggest that empathy towards candidates can be used to shape experiences that improve their satisfaction during the selection process. Thus, the use of the DT methodology encourages the development of more empathetic thinking and effective strategies for facing challenges, particularly those inadequately addressed by traditional rational–analytical approaches (Micheli et al.,2019). Recent academic research underscores the transformative potential of Design Thinking in HR practices. Sivathanu (2019) demonstrates how organizations like Airbnb have leveraged Design Thinking principles to improve employee experience while achieving competitive advantage through innovative HR practices such as cultural transformation programmes. Zafar et al. (2023) explore how predictive workforce analytics combined with Design Thinking can enhance training evaluation practices by enabling evidence-based decision-making in workforce management. Piwowar-Sulej and Austen (2021) highlight how Design Thinking can be applied strategically to improve the image of HR departments by fostering collaboration across organizational units. These studies collectively illustrate how Design Thinking contributes not only to operational efficiency but also to strategic alignment between employee satisfaction and organizational goals. Adm. Sci. 2025,15, 139 3 of 17 Design Thinking is a creative, non-linear process used for innovation. While nonlinear, it is important to note that this does not mean there are no specific steps to follow for the process to be effective (Bariˇcevi´c Debelec & Lui´c,2023). This human-centred approach allows designers and teams to better understand user needs and develop relevant and useful solutions. Essentially, DT combines creativity with a structured approach, resulting in innovative ideas and products. The application of the DT methodology has recently expanded beyond its traditional use in product and service design (Antoljak & Kosovi´c,2018). After being extracted from the design context, DT has become a significant concept in management and innovation research (Johansson-Sköldberg et al.,2013). Through a sequence of steps such as empathy, problem definition, ideation, prototyping, and testing, DT enables teams to explore different perspectives and develop solutions that meet real user needs. Existing studies (Brown,2009;Kimbell,2011;Brown & Martin,2015;Liedtka,2014a; Carlgren et al.,2016) indicate the benefits of this methodology, including increased participant engagement and a better understanding of end-user needs. The user-centric focus allows for a better understanding of their needs, thoughts, emotions, and motivations, which forms the basis for shaping and redefining problems and generating ideas. The process of shaping and redefining problems is crucial for seeing new perspectives, while idea generation develops creative solutions (Au,2024). However, the application of DT in the recruitment process and its implementation in human resources is insufficiently researched, particularly in the context of aligning candidates with organizational culture and optimizing selection procedures using digital tools. Van Aken and Chandrasekaran (2015) highlighted that DT is particularly useful in solving problems that require balancing human and technical aspects. Their research suggests that the iterative prototyping process can help identify the most effective recruitment approaches, especially when the goal is to reduce employee turnover. Schrage (2014) adds that experimenting with inexpensive prototypes allows organizations to test new recruitment methods without significant investments. This is particularly relevant in the context of developing digital tools that can support the selection process, such as online interview platforms or applicant tracking systems (ATSs). 2. Materials and Methods 2.1. Research Problem The research problem in this study focuses on understanding how the application of Design Thinking (DT) methodology can enhance the employee recruitment and selection process. Specifically, it investigates the extent to which innovative tools, such as gamification and digital platforms, can improve candidate experience, increase selection efficiency, and reduce the mismatch between candidates and organizational culture. While there are indications of the usefulness of such approaches, comprehensive research exploring their impact and providing guidelines for their practical implementation is lacking. Traditional recruitment processes face numerous challenges, including lengthy selection procedures, candidate misalignment with organizational culture, and the frequent inability to select the best candidate for a given position. These issues can result in high employee turnover rates, reduced team productivity, and increased recruitment costs. With the increasing presence of technology and digital tools in recruitment processes, an opportunity arises to implement innovative methodologies that can improve the selection process, increase efficiency, and ensure better employee alignment with organizational values. However, despite DT’s potential, existing research rarely explores its application in this specific context. Adm. Sci. 2025,15, 139 4 of 17 The lack of integration of empathetic and creative approaches in recruitment processes creates an opportunity to investigate how DT can address these challenges. It is crucial to understand how this methodology can expedite the selection process, increase precision, and ensure the selection of the best candidate for a specific position. To address these challenges, this study establishes a general research objective and three specific objectives derived from it, aimed at analysing key aspects of applying the DT methodology in the recruitment process. The general objective of this research is to determine the “impact of digital tools and Design Thinking methodology” on the selection process, employee alignment with organizational culture, and the accuracy of candidate selection, while the specific objectives are defined below: C1. Analyse the impact of digital tools on the selection process and time to hire. C2. Examine the influence of Design Thinking’s iterative approach on employee alignment with organizational culture. C3. Evaluate how the application of the Design Thinking method improves the precision of selecting the best candidates. Each specific objective is directed at investigating different aspects of DT application in HR processes and is therefore associated with a corresponding hypothesis to be tested during the study: H1: Digital tools improve the quality of the selection process and reduce time to hire. (Explanation: Digital tools, such as automated selection platforms, data analytics–big data, and artificial intelligence, enable the faster and more efficient processing of candidate applications. The use of these tools can shorten the time required for resume analysis, preselection, and interviews, thus reducing the duration of the selection process. Additionally, digital tools allow for a faster connection with candidates, improving the speed of the entire recruitment process. This hypothesis is based on the belief that digitalization makes the selection process more efficient and precise, shortening time to hire and enabling organizations to find suitable candidates more quickly). H2: The iterative approach of Design Thinking improves employee alignment with organizational culture. (Explanation: DT uses an iterative approach that focuses on understanding user needs, testing solutions, and adapting them based on feedback. When applied to the selection process, this approach allows for a better understanding of candidates through multiple iterations, interviews, and testing. Through this process, the organization can better assess how a candidate fits into its culture and values. By using empathy and testing through DT, organizations can better understand candidates’ personal characteristics and their ability to align with the specifics of organizational culture, thereby improving alignment and reducing the risk of future mismatches). H3: The application of the Design Thinking method increases the precision of selecting the best candidates. (Explanation: The DT method focuses on creative problem-solving and a deep understanding of the needs of all stakeholders, including candidates. By using empathy in the research phase, DT allows organizations to better understand candidates’ motivation, values, and behaviour. The iterative process of testing and prototyping ensures that selection criteria and decisions are based on feedback. Using DT enables the selection of candidates based on their ability to respond to real challenges within the organization, thereby increasing the precision of selecting the best candidates who meet the organization’s needs). Adm. Sci. 2025,15, 139 5 of 17 2.2. Research Design The pilot study of this research, which uses the DT methodology to optimize the recruitment process, employed a qualitative approach to collect relevant data, test new ideas, and evaluate results. This approach integrates multiple qualitative research methods to ensure a holistic analysis and optimization of the recruitment process. Secondary sources were searched using a systematic literature review (SLR) of the existing academic and professional literature, which is particularly effective for researching complex phenomena as it synthesizes existing knowledge and identifies research gaps (Kitchenham & Charters, 2007;Tranfield et al.,2003). In addition to the SLR, qualitative primary data collection was conducted through semi-structured interviews and diary studies, ensuring methodological triangulation. The snowball sampling method was employed to select the primary research sample, ensuring a diverse range of insights from companies in the construction sector in north-western Croatia. The study began by targeting four key participant groups: inexperienced workers, experienced workers, supervisors, and HR professionals. These groups were chosen to provide a comprehensive perspective on the recruitment and selection processes within the sector. As the study progressed, additional participants were identified through referrals, allowing for a broader and more representative sample. To evaluate cultural alignment, specialized questionnaires were used: the Organizational Culture Assessment Instrument (OCAI) (Cameron & Quinn,2011) and Cultural Intelligence (CQ) Self-Assessment (Ang & Van Dyne,2008). These tools enable a better understanding of how candidates fit into the organizational culture, values, and mission of the company. After initial interviews, participants recommended other relevant individuals from their network, allowing for rapid recruitment and access to hard-to-reach groups. To ensure diversity and avoid bias, demographic and professional characteristics of participants were analysed, and targeted selection was additionally applied. Although the study does not employ traditional statistical validation, the robustness of the findings is ensured through method triangulation, the cross-validation of responses across participant groups, and iterative feedback loops. This approach aligns with qualitative research rigour, ensuring the internal validity and transferability of findings. This approach provided qualitative insights from key stakeholders, laying the foundation for further research phases and the development of innovative solutions in recruitment in the construction sector. Following the pilot study, the primary research study is planned, based on insights from the pilot study, and encompasses all 5 phases of DT. The validity of methods are assessed through continuous validation cycles, where each iterative phase of the DT process informs and refines the next, ensuring the cumulative confirmation of research insights. The goal is to confirm the validity of methods, collect representative data, and draw final conclusions. Table 1 presents the conceptual framework for the Design Thinking methodology in improving worker experience in the construction sector. Table 1. A description of the concept and methodology of the DT process in 3 steps. Steps Concept Description Methodology 1. Empathy Understand the challenges and needs of all participants in the selection process in the construction sector. -Desk method, interviews, diary method with HR professionals, shift managers, and workers -Snowball method for gathering diverse perspectives 2. Define Clearly define key problems in the selection process and create meaningful guidelines for improvements. -Diagonalization of Process/Class (P/C) Matrix for problem analysis and solution prioritization -Grouping key needs and defining selection problems Adm. Sci. 2025,15, 139 6 of 17 Table 1. Cont. Steps Concept Description Methodology 3. Ideate Generate innovative solutions to optimize selection, reduce hiring duration, and improve candidate–organization alignment. -Virtual brainstorming and post-it notes in MIRO tool -Generating ideas on the question: “How can digital tools accelerate and improve the selection process?” -Sketching digital solutions for selection optimization The Design Thinking (DT) approach comprises five key phases of the design process: empathy, define, ideate, prototype, and test (Brown,2009;Stanford d.school,2010; D. Kelley & Kelley,2013). In this study, the preliminary research focuses on implementing the first three phases. The empathy phase forms the foundation of the user-centred approach, enabling a deeper understanding of user needs and challenges. Three methods were applied in this study: an analysis of the available relevant literature (desk research), one-on-one interviews, and the diary method. Utilizing these techniques provided insight into users’ thought processes, their requirements, and existing challenges in the recruitment process, providing a basis for developing innovative and practical solutions that can enhance the efficiency and quality of candidate selection. A. The empathy phase represents a crucial component of this research. The aim of this phase is to understand the actual needs of organizations and candidates. The research study concerned was conducted with the informed consent of all the participants regarding ethical permissibility. At the beginning of the study, participants were informed that their participation was voluntary and that they had the right to withdraw from the study at any time during the experiment without any sanctions. Procedures, principles, and ethical issues related to the collection, analysis, and interpretation of data from the experiment were carefully monitored to ensure the credibility of the research outcomes in all phases of the study. In the empathy phase, three data collection techniques were employed to ensure a deeper insight into employee needs, the recruitment process, and the application of digital tools and the DT methodology. Each technique was focused on different aspects of investigating employee needs to identify key factors influencing the selection process, employee alignment with organizational culture, and precision in candidate selection. These techniques include the following: 1. Desk method (SLR)—Data were collected by analysing relevant sources from existing works on the application of digital tools in HR processes. The search was conducted in Web of Science and Scopus databases, using key terms such as “design thinking”, “employment”, “recruitment”, “digitalization”, and “HR”. This method enabled an understanding of trends in candidate selection and the effectiveness of digital tools in optimizing the selection process and reducing time to hire. 2. One-on-one interviews—Interviews with HR professionals were conducted from 14 February to 26 February 2025 to gather insights on whether the application of the DT methodology can assist in candidate selection. Questions were adapted from questionnaires specialized in assessing cultural alignment (the Organizational Culture Assessment Instrument—OCAI—and Cultural Intelligence Self-Assessment) as they allow for a better understanding of how candidates fit into the company’s organizational culture, values, and mission. The aim was to examine whether the application of digital tools improves the selection process and reduces the time needed to select the best candidate. The interviews enabled a deeper understanding of the impact of the iterative approach on employee alignment with organizational culture and precision in candidate selection. Participants shared their experiences in using Adm. Sci. 2025,15, 139 7 of 17 digital tools for candidate selection and evaluation, and the data collected through interviews were used in the next step to define key needs and selection problems. 3. Diary method—Using this method, candidates and employees were tracked throughout the entire recruitment process. Candidates shared their experiences, which were then documented through diary entries. Their thoughts and reactions to various stages of recruitment were recorded, including their communication with HR professionals, testing, interviews, and reactions to the tools used. This method allowed for a deep understanding of the emotional and practical challenges candidates face in the selection process, while the data were used to evaluate how the DT approach affects the candidate experience. B. The define phase is the next step following the completed empathy phase, in which key needs and challenges in the recruitment process are identified through desk research, interviews, and the diary method. This phase represents a synthesis of collected data and enables the structured shaping of insights gained through analysis. The define phase was conducted in February 2025 and was based on findings from the empathy phase. The next step was to structure and analyse key recruitment challenges in the construction sector and create meaningful guidelines for improvements. To define the most important problems and needs, the diagonalization of the P/C matrix (problems/correlations) was used. For designing solutions in the construction sector, where problems are often operational, strategic, and related to efficiency, the P/C matrix can be useful as it allows for structured problem analysis and the definition of strategic priorities. The definition process included the following steps: 1. Problem identification—Participants listed key problems faced by various actors in construction sector recruitment (e.g., inexperienced workers, experienced workers, supervisors, HR professionals). 2. The categorization of problems and needs—Problems were grouped into broader categories (e.g., a lack of qualified workers, high turnover, lack of sector attractiveness for young people). 3. The diagonalization of the P/C matrix—In this phase, the diagonalization method was used to analyse mutual correlations between problems and needs and determine those with the greatest strategic impact. 4. Problem prioritization—Based on the obtained results, key challenges requiring urgent and innovative solutions were defined for the subsequent ideation phase. This approach enabled a clear and structured understanding of the problems and laid the foundation for developing effective solutions in the subsequent phases of the DT process. C. The ideation phase was conducted through a collaborative workshop adapted to recruitment in the construction sector. Thirty participants who had recently undergone the selection process in the observed company were chosen for the workshop using the snowball method. All participants were male, living in Croatia, with an average age of 32 years . All participants provided informed consent, and their responses were anonymized to protect their privacy. This study adhered to ethical guidelines to ensure the integrity and confidentiality of collected data. A pilot study was conducted to test the workshop methodology aimed at generating ideas for developing digital tools that could accelerate and improve the selection process in the construction sector. The workshop was held in February 2025 and was conducted virtually using videoconferencing and collaborative tools. Google Meet was used for communication and the MIRO platform for conducting activities. The workshop was structured in five phases: Adm. Sci. 2025,15, 139 8 of 17 1. Introduction—Workshop facilitators introduced themselves and explained the purpose of conducting the workshop, after which each participant had one minute for a brief introduction. 2. Problem definition—Workshop facilitators presented the scenario and defined the problem, using the P/C matrix diagonalization to structurally analyse problems and their interconnections. Participants ranked key challenges in construction sector recruitment according to their impact and solvability, thus defining priority interventions. 3. Ideation—The goal was to encourage participants to generate innovative solutions. Through brainstorming, participants developed innovative solutions, recorded them via MIRO post-it notes, and sketched conceptual models using virtual post-it notes in MIRO, discussing the question: “How can digital tools accelerate and improve the selection process?” This segment lasted 15 min, during which participants freely wrote down and shared their ideas. 4. Prototyping—After selecting key ideas, participants sketched them on paper and then shared them with the workshop facilitators, who moderated further discussion. Finally, a virtual prototype model was created in MIRO, aiming to demonstrate a possible solution for improving recruitment in the construction sector. 5. Conclusion—Workshop facilitators conducted an evaluation activity to gather feedback from participants on the process itself and workshop results. The workshop evaluation collected insights for improving the methodology and further development of solutions aimed at optimizing recruitment in the construction sector. This approach enabled collaborative idea generation and the rapid prototyping of solutions aimed at improving the recruitment process in the construction sector. 3. Results In the context of this study, utilizing the DT methodology, triangulation method, cross-validation of responses across participant groups, and iterative feedback loops ensure methodological rigour. This approach aligns with qualitative research standards, enhancing the internal validity and transferability of findings while supporting data collection, idea testing, and result evaluation. This qualitative approach provides a comprehensive framework for optimizing the recruitment process by capturing in-depth insights and ensuring a nuanced understanding of the selection dynamics. The research results were collected through the following: (1) a systematic literature review (SLR), (2) interviews with HR professionals and shift managers, and (3) the diary method with candidates and employees . 3.1. Systematic Literature Review (SLR) This research initially employed the systematic literature review (SLR) method to gain a comprehensive and objective insight into existing research. This approach allows for the identification of research gaps and integration of various findings to guide future research. The search strategy in Web of Science (WoS) and Scopus databases was structured to enable the identification of relevant studies. The search focus was on peer-reviewed journals indexed in the SSCI and ESCI, covering publications from 2020 to 2025. To direct the search towards the most important aspects of the research, key terms related to “Design Thinking”, the “digitalization of employment”, and “selection processes” were used. This ensured that the search encompassed only relevant scientific papers in English pertaining to the application of DT in the context of employment and human resource management. The aim of this strategy was to collect a wide range of studies analysing how digital tools and the iterative approach of DT can enhance selection processes and improve candidate alignment with organizational culture. Adm. Sci. 2025,15, 139 15 of 17 Alqahtani, A. F. A. (2022). Harnessing the power of design thinking for open innovation [Doctoral dissertation, University of Technology Sydney]. OPUS at UTS. Available online: http://hdl.handle.net/10453/168930 (accessed on 15 January 2025). Ang, S., & Van Dyne, L. (2008). Conceptualization of cultural intelligence: Definition, distinctiveness, and nomological network. In S. Ang, & L. Van Dyne (Eds.), Handbook of cultural intelligence: Theory, measurement, and applications (pp. 3–15). M.E. Sharpe. Available online: https://www.culturalq.com (accessed on 15 January 2025). Antoljak, V., & Kosovi´c, M. (2018). Design thinking za nedizajnere: Kako riješiti poslovne probleme i uspješno inovirati. Školska knjiga—Sense savjetovanja. Au, E. Y. L. (2024). Leveraging design thinking to enhance engineering teaching: An operational model. IEEE Transactions on Education, 68, 95–102. [CrossRef] Bailey, M., Harney, B., & Pearce, A. (2019). Global entrepreneurial talent management: Challenges and opportunities for HRD— Designing a design thinking approach to HRD. International Journal of HRD Practice, Policy and Research,4(2), 9–23. [CrossRef] Baran, G. (2017). Design thinking as a source of management innovation. International Journal of Contemporary Management,16(3), 51–71. [CrossRef] Bariˇcevi´c Debelec, M., & Lui´c, L. (2023). From active learning to innovative thinking: The influence of learning the design thinking process among students. Education Sciences,13, 455. [CrossRef] Baši´c, T., & ´ Culibrk, J. (2021, February 15–18). Primena digitalnih alata u procesima regrutacije i zapošljavanja. XXVII Skup TRENDOVI RAZVOJA: “ON-LINE NASTAVA NA UNIVERZITETIMA”, Novi Sad, Serbia. Beckman, S. L. (2020). To frame or reframe: Where might design thinking research go next? California Management Review,62, 144–162. [CrossRef] Björklund, T., Maula, H., Soule, S. A., & Maula, J. (2020). Integrating design into organisations: The coevolution of design capabilities. California Management Review 62, 100–124. [CrossRef] Brown, T. (2009). Change by design: How design thinking creates new alternatives for business and society. Harper Business. Brown, T., & Martin, R. (2015). Design for action: How to use design thinking to create a new strategy for a better world. Harvard Business Review,93(9), 56–64. Brumec, J. (1993). Optimizacija strukture složenih informacijskih sustava. Journal of Information and Organizational Sciences,17(1), 1–23. Available online: https://hrcak.srce.hr/79434 (accessed on 28 January 2025). Cameron, K. S., & Quinn, R. E. (2011). Diagnosing and changing organizational culture: Based on the competing values framework (3rd ed.). Jossey-Bass. Available online: https://www.ocai-online.com (accessed on 28 January 2025). Carlgren, L., Rauth, I., & Elmquist, M. (2016). Framing design thinking: The concept in idea and enactment. Creativity and Innovation Management,25(1), 38–57. [CrossRef] Chuang, A., & Sackett, P. R. (2005). The perceived importance of person-job fit and person-organization fit between and within interview stages. Social Behavior and Personality: An International Journal,33(3), 209–226. [CrossRef] Cross, N. (2011). Design thinking: Understanding how designers think and work. Bloomsbury Academic. Dragiˇcevi´c, N., Vladova, G., & Ullrich, A. (2023). Design thinking capabilities in the digital world: A bibliometric analysis of emerging trends. Frontiers in Education,7, 1012478. [CrossRef] Dunne, D. (2018). Implementing design thinking in organizations: An exploratory study. Journal of Organization Design,7(1), 16. [CrossRef] Ebrahim, S. S., & Rajab, H. A. (2025). The future of HR: The role of AI-powered recruitment in shaping the modern workforce. Open Access Library Journal,12, 1–22. [CrossRef] El Ouakili, O. (2025). The impact of artificial intelligence (AI) on recruitment process. Open Journal of Business and Management,13, 749–762. [CrossRef] Ginting, S., Diantoro, K., Cindrakasih, R. R., Mubarak, R., & Suseno. (2024). The impact of digital transformation on talent recruitment strategies in modern human resource management. Jurnal Minfo Polgan,12(2), 2833. [CrossRef] Glen, R., Suciu, C., Baughn, C. C., & Anson, R. (2015). Teaching design thinking in business schools. The International Journal of Management Education,13, 182–192. [CrossRef] Goher, G., Masrom, M., Amrin, A., & Abd Rahim, N. (2021). Disruptive technologies for labor market information system implementation enhancement in the UAE: A conceptual perspective. International Journal of Advanced Computer Science and Applications, 12(2), 370. [CrossRef] Hoffman, B. J., & Woehr, D. J. (2006). A quantitative review of the relationship between person–organization fit and behavioral outcomes. Journal of Vocational Behavior,68(3), 389–399. [CrossRef] Holm, A. B. (2009, May 6–7). Virtual HRM: A case of e-recruitment. 3rd International Workshop on Human Resource Information Systems—Volume 1: HRIS (pp. 49–58), Milan, Italy. [CrossRef] Iyer, R., & Khutale, A. C. (2024). Evaluation of the effectiveness of digital recruitment platforms at Full Stack Guru. International Journal of Creative Research Thoughts (IJCRT),12(12), 108–122. Available online: https://www.ijcrt.org/papers/IJCRT2412671.pdf (accessed on 17 January 2025). Adm. Sci. 2025,15, 139 16 of 17 Johann, D. A., Nunes, A. D. F. P., Santos, G. B. D., Silva, D. J. C. D., Bresciani, S. A. T., & Lopes, L. F. D. (2020). Mapping of scientific production on design thinking as a tool for entrepreneurship education: A bibliometric study of a decade. World Journal of Entrepreneurship, Management and Sustainable Development,16, 271–285. [CrossRef] Johansson-Sköldberg, U., Woodilla, J., & Çetinkaya, M. (2013). Design thinking: Past, present and possible futures. Creativity and Innovation Management,22, 121–146. [CrossRef] Kelley, D., & Kelley, T. (2013). Creative confidence: Unleashing the creative potential within us all. Crown Business. Kelley, T. A. (2001). The art of innovation: Lessons in creativity from IDEO, America’s leading design firm. Broadway Business. Kimbell, L. (2011). Rethinking design thinking: Part I. Design and Culture,3(3), 285–306. [CrossRef] Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Keele University and Durham University Joint Report. Kolko, J. (2015). Design thinking comes of age. Harvard Business Review 93, 66–71. Lee, Y.-F. E., Wang, T.-H., Foo, M.-T., & Lam, K.-F. T. (2023). Embracing DDMT teaching model and design thinking for organization development. Sustainability,15(11), 9031. [CrossRef] Li, F., Huang, W., Ge, L., Wang, J., Rao, Z., & Xi, X. (2018, December 29–30). Teaching of employment guidance course in colleges based on design thinking method. 2018 2nd International Conference on Economic Development and Education Management (ICEDEM 2018), Dalian, China. [CrossRef] Liedtka, J. (2014a). Innovative ways companies are using design thinking. Strategic Leadership,42, 40–45. [CrossRef] Liedtka, J. (2014b). Perspective: Linking design thinking with innovation outcomes through cognitive bias reduction. Journal of Product Innovation Management,32(6), 925–938. [CrossRef] Liedtka, J., & Ogilvie, T. (2011). Designing for growth: A design thinking tool kit for managers. Columbia University Press. Manuti, A., & Pasquale, P. (2017). Digital HR: A critical management approach to the digitilization of organizations. Springer Nature. [CrossRef] Mariani, I., Mortati, M., Rizzo, F., & Deserti, A. (2025). Design thinking as a strategic approach to e-participation: From current barriers to opportunities. Springer Nature. [CrossRef] Martin, R. L. (2009). The design of business: Why design thinking is the next competitive advantage. Harvard Business School Press. Micheli, P., Wilner, S. J. S., Bhatti, S. H., Mura, M., & Beverland, M. B. (2019). Doing design thinking: Conceptual review, synthesis, and research agenda. Journal of Product Innovation Management,36, 124–148. [CrossRef] Minet, A., Wentzel, D., Raff, S., & Garbas, J. (2024). Design thinking in physical and virtual environments: Conceptual foundations, qualitative analysis, and practical implications. Technological Forecasting and Social Change,207, 123596. [CrossRef] Ní Shé, C., Farrell, O., Brunton, J., & Costello, E. (2021). Integrating design thinking into instructional design: The #OpenTeach case study. Australasian Journal of Educational Technology,38(1), 33–52. [CrossRef] Obaid, I., Farooq, M. S., & Abid, A. (2020). Gamification for recruitment and job training: Model, taxonomy, and challenges. IEEE Access,8, 65164–65178. [CrossRef] Piwowar-Sulej, K., & Austen, A. (2021). Using the design thinking concept in HR department image development. IBIMA Conference Proceedings. Available online: https://ibima.org/accepted-paper/using-the-design-thinking-concept-in-hr-department-image -development/ (accessed on 2 April 2025). Rauth, I., Köppen, E., Jobst, B., & Meinel, C. (2010, November 29–December 1). Design thinking: An educational model towards creative confidence. DS 66-2: Proceedings of the 1st International Conference on Design Creativity (ICDC 2010), Kobe, Japan. Resende, G., Tolentino, I., Bernardi, M., & Ferreira, R. (2023). Programa de desenvolvimento dos gestores da Fundação João Pinheiro: Inovação, desenvolvimento de pessoas e design thinking. Revista de Gestão e Secretariado (Management and Administrative Professional Review),14, 13607–13629. [CrossRef] Ronˇcevi´c, A., Gregori´c, M., & Magdaleni´c, D. (2024). Innovative methodological approach of the assessment of the influence of digitalization on the ESG framework in the domain of nautical tourism. In L. Kaliterna Lipovˇcan, R. Medi´c, & O. Ramljak (Eds.), MIC—Vis, 2024: Mediterranean islands conference: Book of abstracts (p. 103). Institute of Social Sciences Ivo Pilar, VERN’ University. Available online: https://www.diva-portal.org/smash/get/diva2:1897772/FULLTEXT01.pdf (accessed on 31 January 2025). S, A., & Bhavikatti, V. I. (2024). A study on e-recruitment and selection. International Journal for Multidisciplinary Research,6(6), 1–10. Available online: https://www.ijfmr.com/research-paper.php?id=29763 (accessed on 28 January 2025). Schrage, M. (2014). The innovator’s hypothesis: How cheap experiments are worth more than good ideas. MIT Press. Sivathanu, B. (2019). Design thinking—A game changer in human resource management. International Journal of Scientific & Technology Research,8(9), 1105–1108. Available online: https://www.ijstr.org/final-print/sep2019/Design-Thinking-A-Game-Changer-In -Human-Resource-Management.pdf (accessed on 2 April 2025). Stanford d.school. (2010). An introduction to design thinking: Process guide. Hasso-Plattner Institute of Design at Stanford. Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management,14(3), 207–222. [CrossRef] Adm. Sci. 2025,15, 139 17 of 17 Van Aken, J. E., & Chandrasekaran, A. (2015). Design thinking in innovation: A research agenda. Journal of Product Innovation Management,32(5), 682–688. Varga, M. (2011). Prikaz informacijskog modela raˇcunovodstvenog sustava. Ekonomski vjesnik: Review of Contemporary Entrepreneurship, Business, and Economic Issues,24(2), 367–379. Available online: https://hrcak.srce.hr/76190 (accessed on 31 January 2025). Vorecol. (2024). Analyzing the impact of gamification on recruitment processes: A case study approach. Available online: https://vorecol .com/blogs/blog-analyzing-the-impact-of-gamification-on-recruitment-processes-a-case-study-approach-176598 (accessed on 18 January 2025). Zafar, N., Asadullah, M. A., Ul Haq, M. Z., Siddiquei, A. N., & Nazir, S. (2023). Design thinking: A cognitive resource for improving workforce analytics and training evaluation. European Journal of Training and Development,47, 653–675. [CrossRef] Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.