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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">115</journal-id>
      <journal-id journal-id-type="index">urn:lsid:arphahub.com:pub:32e1b97d-7003-598d-92e7-0ceb44416cc9</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">BRICS Journal of Economics</journal-title>
        <abbrev-journal-title xml:lang="en">brics-econ</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">2712-7702</issn>
      <issn pub-type="epub">2712-7508</issn>
      <publisher>
        <publisher-name>BRICS Journal of Economics</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.3897/brics-econ.7.e166608</article-id>
      <article-id pub-id-type="publisher-id">166608</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group subj-group-type="scientific_subject">
          <subject>(G41) Role and Effects of Psychological</subject>
          <subject> Emotional</subject>
          <subject> Social</subject>
          <subject> and Cognitive Factors on Decision Making in Financial Markets</subject>
          <subject>(G) Financial Economics</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Exploring the link between financial literacy and career engagement among students of Russian business schools</article-title>
      </title-group>
      <contrib-group content-type="authors">
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Zavyalova</surname>
            <given-names>Elena</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0000-0002-6098-8335</uri>
          <xref ref-type="aff" rid="A1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Bordunos</surname>
            <given-names>Aleksandra</given-names>
          </name>
          <email xlink:type="simple">abordunos@bk.ru</email>
          <uri content-type="orcid">https://orcid.org/0000-0003-0347-3180</uri>
          <xref ref-type="aff" rid="A1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Tserkovnaia</surname>
            <given-names>Victoriia</given-names>
          </name>
          <xref ref-type="aff" rid="A2">2</xref>
        </contrib>
      </contrib-group>
      <aff id="A1">
        <label>1</label>
        <addr-line content-type="verbatim">GSOM SPbU (Russia)</addr-line>
        <institution>GSOM SPbU</institution>
        <addr-line content-type="city">Saint Petersburg</addr-line>
        <country>Russia</country>
      </aff>
      <aff id="A2">
        <label>2</label>
        <addr-line content-type="verbatim">Nagoya University of Comerce and Business (Japan)</addr-line>
        <institution>Nagoya University of Comerce and Business</institution>
        <addr-line content-type="city">Nagoya</addr-line>
        <country>Japan</country>
        <uri content-type="ror">https://ror.org/04chrp450</uri>
      </aff>
      <author-notes>
        <fn fn-type="corresp">
          <p>Corresponding author: Aleksandra Bordunos (<email xlink:type="simple">abordunos@bk.ru</email>)</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Academic editor: Sheresheva M.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2026</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>30</day>
        <month>09</month>
        <year>2026</year>
      </pub-date>
      <volume>7</volume>
      <issue>3</issue>
      <fpage>61</fpage>
      <lpage>75</lpage>
      <uri content-type="arpha" xlink:href="http://openbiodiv.net/37852080-AF29-5EA2-9E63-931ABB4DB668">37852080-AF29-5EA2-9E63-931ABB4DB668</uri>
      <history>
        <date date-type="received">
          <day>25</day>
          <month>07</month>
          <year>2025</year>
        </date>
        <date date-type="accepted">
          <day>08</day>
          <month>03</month>
          <year>2026</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Elena Zavyalova, Aleksandra Bordunos, Victoriia Tserkovnaia</copyright-statement>
        <license license-type="creative-commons-attribution" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">
          <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
        </license>
      </permissions>
      <abstract>
        <label>Abstract</label>
        <p>Business schools seek to promote financial literacy and career engagement among undergraduate and graduate students, equipping them with the skills to navigate real-world financial challenges effectively and take the initiative in their career development. This improves students’ future employability and long-term professional success, while also enhancing the reputations of business schools and their positions in international and domestic rankings. Such rankings increasingly rely on graduate employability, career readiness and the inclusion of financial education in curricula, which aligns with market demands and government education strategies.</p>
        <p>This study investigates the relationship between financial literacy and career engagement among business school students. Financial literacy is assessed using the Financial Wellbeing questionnaire, while proactive career behavior is measured using the Career Engagement scale. Regression analysis, controlling for gender, region and academic year, reveals that financial literacy significantly predicts career success.</p>
        <p>These findings provide policymakers and educators with empirical evidence that, beyond improving financial outcomes, cultivating financial literacy from a behavioral perspective within business education fosters greater career engagement. This dual focus is in line with Russia’s and other BRICS countries’ strategic goals of developing skilled, adaptable professionals who can contribute to sustained economic growth.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>financial literacy</kwd>
        <kwd>career engagement</kwd>
        <kwd>business education</kwd>
        <kwd>financial wellbeing</kwd>
        <kwd>Russia</kwd>
        <kwd>BRICS countries</kwd>
        <kwd>financial education strategy.</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>JEL</meta-name>
          <meta-value>G41</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
    <notes>
      <sec sec-type="Citation" id="sec1">
        <title>Citation</title>
        <p>Zavyalova, E., Bordunos, A., &amp; Tserkovnaia, V. (2026). Exploring the link between financial literacy and career engagement among students of Russian business schools. <italic>BRICS Journal of Economics, 7</italic>(2), 61–75. <ext-link xlink:type="simple" ext-link-type="doi" xlink:href="10.3897/brics-econ.7.e166608">https://doi.org/10.3897/brics-econ.7.e166608</ext-link></p>
      </sec>
    </notes>
  </front>
  <body>
    <sec sec-type="Introduction" id="sec2">
      <title>Introduction</title>
      <p>In the rapidly evolving economic landscape of the BRICS countries, financial literacy is increasingly recognized as a crucial competency for ensuring individual financial well-being. The Russian Federation’s updated Strategy for Financial Literacy Improvement and Development of Financial Culture until 2030 emphasizes the need to enhance national financial education frameworks in order to empower citizens in the face of digitalization and global economic integration. By the end of the previous period (2017–2023), financial literacy programmes had reached approximately 78% of school students and 69% of college and university students. Today, business school curricula covering financial literacy appear to reach 100% of students.</p>
      <p>Meanwhile, the Russian Federation’s Youth Development Strategy until 2025 (with provisions extending to 2030) places further emphasis on the importance of career well-being and supports students in building resilient educational and career trajectories. While the benefits of financial literacy are well established, this research explores the idea that financial literacy can foster career engagement among young professionals.</p>
      <p>For business schools in particular, integrating financial literacy and nurturing career engagement among students is paramount. Moreover, both parties benefit from this approach. Financial literacy and career engagement prepare graduates for sustainable long-term professional success and improved quality of life. Business schools’ reputation and ranking are influenced by metrics such as graduate employability, as well as how well they align with market demands and national educational strategies.</p>
      <p>Drawing upon a sample of students from a leading Russian business school in Saint-Petersburg, we aim to answer the following research question:</p>
      <p><italic>RQ: How do different facets of financial literacy, including attitudes towards expenses, spending behavior, debt management and saving habits, relate to levels of career engagement</italic>?</p>
      <p>We expect our findings to provide valuable insights for educators, policymakers and business leaders in Russia and other BRICS countries. They will highlight the benefits of combining financial education with career development initiatives in order to cultivate a generation of young professionals who are resilient, financially savvy and proactive.</p>
    </sec>
    <sec sec-type="Methodology" id="sec3">
      <title>Methodology</title>
      <p><italic>Literature review and theoretical model</italic>. Firstly, we conducted a systematic literature review using the OpenAlex platform, a comprehensive research discovery tool that is openly accessible. The review aimed to identify recent and relevant scholarly articles exploring the relationship between students’ financial literacy and any career-related factors. The following keywords were therefore applied: ‘financial literacy’ AND ‘students’ AND ‘career’. The search was restricted to the ‘article’ type, including only peer-reviewed journal articles written in English ensuring the quality and reliability of the literature included in the analysis.</p>
      <p>The search yielded 93 results, including ten proceeding papers (see Figure <xref ref-type="fig" rid="F1">1</xref>). Of these, only two were in the field of career development, while the majority (k = 23) were in financial literacy research. None were related to career engagement, emphasizing the novelty of this research.</p>
      <fig id="F1">
        <object-id content-type="doi">10.3897/brics-econ.7.e166608.figure1</object-id>
        <object-id content-type="arpha">0E30C7D9-3EA7-500B-8610-18FE73357330</object-id>
        <label>Figure 1.</label>
        <caption>
          <p>Articles involved in screening</p>
        </caption>
        <graphic xlink:href="brics-econ-07-061-g001.jpg" id="oo_1794507.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1794507</uri>
        </graphic>
      </fig>
      <p>Fig. <xref ref-type="fig" rid="F2">2</xref> represents interconnections between 44 the most relevant publications, excluding articles lacking <bold>digital object identifier</bold> (<abbrev xlink:title="digital object identifier">DOI</abbrev>). In the map, nodes symbolize distinct scholarly works, while edges represent references or collaborative authorship, enabling the detection of thematic groups, prominent contributions and the field’s network structure. Articles towards the right are more recent, towards the top have more citations. The larger the node, the more citations in has.</p>
      <fig id="F2">
        <object-id content-type="doi">10.3897/brics-econ.7.e166608.figure2</object-id>
        <object-id content-type="arpha">DDD3179B-C9FD-5C28-BB77-8ADFDAB9F85C</object-id>
        <label>Figure 2.</label>
        <caption>
          <p>Bibliometric visualization of the scholarly landscape related to financial literacy and career development, performed in Litmaps</p>
        </caption>
        <graphic xlink:href="brics-econ-07-061-g002.jpg" id="oo_1794508.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1794508</uri>
        </graphic>
      </fig>
      <p>The visualization displays a moderately dense network with distinct temporal patterns, where earlier works (<xref ref-type="bibr" rid="B6">Cook , 2013</xref>; <xref ref-type="bibr" rid="B10">Karger, 2015</xref>) occupy peripheral positions, suggesting their role as established references rather than active nodes of current debate. A central cluster emerges around mid-period publications (<xref ref-type="bibr" rid="B13">Longobardi et al., 2018</xref>; <xref ref-type="bibr" rid="B18">Shi et al., 2019</xref>; <xref ref-type="bibr" rid="B7">Hagadorn &amp; Lahousse, 2019</xref>; <xref ref-type="bibr" rid="B12">Krische &amp; Mislin, 2020</xref>; <xref ref-type="bibr" rid="B3">Cedeño et al., 2021</xref>), indicating robust scholarly dialogue and conceptual convergence during this phase of field development.</p>
      <p>The map demonstrates significant recent momentum, with a notable concentration of 2024-2025 publications (<xref ref-type="bibr" rid="B9">Kang et al., 2024</xref>; <xref ref-type="bibr" rid="B17">Pashaei et al., 2024</xref>; <xref ref-type="bibr" rid="B5">Chetioui et al., 2024</xref>; <xref ref-type="bibr" rid="B11">Kavak &amp; Sakiz 2025</xref>) positioned across multiple regions of the network. This dispersion suggests diversification of research interests rather than consolidation around a single paradigm. The spatial distribution indicates that while core themes maintain continuity, the field is actively expanding its boundaries, incorporating new contexts (refugee students, Generation Z, emerging markets) and integrating contemporary concerns such as digital capabilities and entrepreneurial education into financial literacy discourse.</p>
      <p>This systematic approach allowed us to identify existing empirical evidence and conceptual frameworks and to position the current study within the broader academic discourse on financial literacy and career development in higher education.</p>
      <p>Financial literacy is often perceived from a multidimensional perspective, with the three most common aspects being attitude, behavior and cognitive knowledge, which are all necessary for making wise financial decisions or taking appropriate action (<xref ref-type="bibr" rid="B14">Meadows &amp; Mejrii, 2021</xref>). A similar framework was applied by NAFI in its research on financial literacy in Russia (NAFI, 2023), which highlighted the greatest need for financial literacy among younger individuals. Previous studies (<xref ref-type="bibr" rid="B4">Çera &amp; Tuzi, 2019</xref>) have revealed differences in financial literacy based on gender: young men tend to be more willing to take risks, take the initiative and improve their financial knowledge, whereas young women tend to focus more on managing money and expenditure-related concerns. As financial literacy was found to be lower among younger citizens and women, our research primarily focused on these two more vulnerable categories.</p>
      <p>According to Human Capital Theory (<abbrev xlink:title="Human Capital Theory">HCT</abbrev>), financial literacy can be viewed as an investment that enhances career-related skills (<xref ref-type="bibr" rid="B16">Nandini &amp; Latif, 2024</xref>). Among the career-related factors mentioned in the preselected articles, there is a relationship with job-obtainment self-efficacy and job-readiness (<xref ref-type="bibr" rid="B3">Cedeño et al., 2021</xref>). Despite turbulent times, financial literacy plays a significant role in young professionals’ increased interest in well-paying job opportunities, as well as adding to their competitiveness in the labor market. It is a crucial competency during a crisis (<xref ref-type="bibr" rid="B15">Mohta, 2020</xref>). Studies show that improving financial literacy can help students navigate career transitions and manage student loans, salary negotiations and entrepreneurial risk. They also reveal that there are gender disparities in financial literacy, which impact career equity (<xref ref-type="bibr" rid="B15">Mohta, 2020</xref>; <xref ref-type="bibr" rid="B1">Bhayankaram, 2024</xref>). Furthermore, studies emphasize that combining financial education with entrepreneurship can greatly increase student ambition to pursue an entrepreneurial career (<xref ref-type="bibr" rid="B9">Kang et al., 2024</xref>).</p>
      <p>Our research focuses on the recently emerging concept of “career engagement”, developed by <xref ref-type="bibr" rid="B8">Hirschi and colleagues (2014)</xref>, which is defined as the degree to which people proactively develop their careers through various proactive behaviors. While financial literacy has been increasingly recognized as an essential part of business school curricula due to its crucial role in personal and professional decisions, career engagement is still largely a voluntary and self-motivated behavior. However, although financial literacy is commonly understood at the level of knowledge, career engagement occurs at the level of action. Therefore, modern scholars argue that financial education should also be behaviorally informed (e.g., <xref ref-type="bibr" rid="B2">de Bruijn et al., 2022</xref>). The proposed adjustments are based on motivation and behavior change theories, which state that, despite knowledge and skills, there is a high role for personal dispositions and beliefs related to self-regulation, which can hinder healthy financial behaviors. The authors propose focusing not only on income types but also on how to manage bills, deal with bailiffs and bank accounts, balance the budget in the short-term, resist temptation, prioritize expenses, keep accounting records and manage finances in the long-term.</p>
      <p>In summary, we argue that financial literacy is an important precursor to career engagement for several reasons. Firstly, it provides a foundation for informed decision-making by equipping individuals with the knowledge and skills needed to manage personal resources effectively, assess risks, and plan for the future. These capabilities foster confidence and a sense of control, which are crucial psychological prerequisites for taking the initiative in career development. Financial literacy reduces financial stress by providing a solid grasp of financial concepts, which reduces economic uncertainty and stress. These conditions often hinder long-term planning, including further career development. Once financial concerns have been addressed, individuals can allocate their cognitive and emotional resources towards career exploration, personal development and networking. This enhances self-efficacy and agency: financial literacy builds self-efficacy by empowering individuals to handle complex financial tasks. This empowerment can be transferred to career contexts, encouraging students to actively shape their career trajectories instead of passively responding to external circumstances. Financial literacy and career-related skills complement each other in educational initiatives: financial literacy provides the practical tools and frameworks that encourage proactive behaviors such as setting goals, seeking opportunities, and managing resources within a career. Improving financial literacy does not only prepare students for financial independence, but also for agile career management, making them more competitive and resilient in an ever-changing professional landscape.</p>
      <p>Thus, viewing financial literacy as a driver of career engagement reveals a strategic approach for educational institutions: by promoting financial education, they can indirectly encourage students to engage voluntarily with their careers. Figure <xref ref-type="fig" rid="F3">3</xref> illustrates the theoretical framework of the research.</p>
      <fig id="F3">
        <object-id content-type="doi">10.3897/brics-econ.7.e166608.figure3</object-id>
        <object-id content-type="arpha">78AA75A6-4E66-59AF-911C-AE1380ABA05A</object-id>
        <label>Figure 3.</label>
        <caption>
          <p>Theoretical framework of the research</p>
        </caption>
        <graphic xlink:href="brics-econ-07-061-g003.jpg" id="oo_1794509.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1794509</uri>
        </graphic>
      </fig>
      <p>The research is positioned within the financial literacy research domain, aiming to contribute to it by linking financial literacy to emerging career constructs, particularly ‘career sustainability’, shifting attention from raising awareness to the role of personal dispositions, beliefs and behaviors.</p>
      <p><italic>Data collection and sample structure</italic>. In the second step, we conducted a survey and distributed it among students using snowball sampling to increase credibility. This non-probability sampling technique involves existing study participants recruiting future participants from among their acquaintances. The process begins with the researcher identifying a small number of initial participants, known as ‘seeds’, who meet the study criteria. These participants then refer others within their social networks who also qualify for the study. The additional effort made to increase credibility was related to the fact that it was peer-to-peer communication: our co-author, who is a student, collected information from their peers.</p>
      <p>The study sample consisted of 165 students, all aged between 20 and 24. The sample included students from four academic levels within the same business school, ensuring the group was relatively homogeneous in terms of educational environment and age. All of them were studying management. The demographic control variables collected were gender, year of study and region of residence.</p>
      <p>Data collection was conducted via an online questionnaire distributed using Google Forms, a free platform. To encourage participation and increase response rates from this student population, several incentive mechanisms were implemented. At the beginning of the survey, participants were informed that the researcher would donate 10 Russian rubles to the Kovcheg animal shelter in Yaroslavl for each completed questionnaire, up to a total of 2,000 rubles. This charitable contribution was advertised in the official social media groups of third- and fourth-year Business School students on the VK platform.</p>
      <p>Additionally, respondents who provided their contact details in the optional final question were entered into a prize draw to win one of two gift vouchers, each worth 1,000 roubles, for one of two well-known stores, depending on their preference. The results of the prize draw were publicly announced within the same student groups.</p>
      <p>Given the specialized nature of the survey topic, many participants were unfamiliar with key terms related to career engagement and financial literacy, including its components such as knowledge, skills, and attitudes. To address this, brief explanatory notes clarifying these concepts were provided before each relevant section of the questionnaire. Post-survey feedback indicated that many respondents found these clarifications helpful both for their general understanding and for grasping the research objectives.</p>
      <p>The questionnaire consisted primarily of closed-ended items to ensure standardized responses that could be analyzed quantitatively. The instrument included validated scales to measure financial literacy and proactive career behavior, as well as demographic and control questions. This approach aligns with the best practices of survey methodology by balancing data quality with respondent engagement and leveraging ethical incentives to maximize participation while maintaining anonymity and voluntary consent.</p>
      <p>Table <xref ref-type="table" rid="T1">1</xref> shows the demographic and educational background of the study participants. The gender breakdown shows that female students constitute 76.4% of the sample, while male students account for the remaining 23.6%. In terms of academic level, most respondents were enrolled in bachelor’s programmes, with 28.5% in their third year and 61.2% in their fourth year. A smaller proportion of participants were Master’s students, at 9.1% in the first year and 1.2% in the second. In terms of geographical distribution, the vast majority of participants (87.9%) reside in Saint Petersburg, while 12.1% live in the surrounding Leningrad region. This reflects the institution’s primary catchment area and provides context for interpreting the findings within regional socio-economic settings.</p>
      <table-wrap id="T1" position="float" orientation="portrait">
        <label>Table 1.</label>
        <caption>
          <p>Sample Characteristics</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <th rowspan="1" colspan="1">
                <bold>Characteristic</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>Response Options</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>Number of Respondents (n, %)</bold>
              </th>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Sex</td>
              <td rowspan="1" colspan="1">Male (coded as 0)</td>
              <td rowspan="1" colspan="1">39 (23.6%)</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1">Female (coded as 1)</td>
              <td rowspan="1" colspan="1">126 (76.4%)</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Year of Study</td>
              <td rowspan="1" colspan="1">3rd Year Bachelor (coded as 3)</td>
              <td rowspan="1" colspan="1">47 (28.5%)</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1">4th Year Bachelor (coded as 4)</td>
              <td rowspan="1" colspan="1">101 (61.2%)</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1">1st Year Master (coded as 5)</td>
              <td rowspan="1" colspan="1">15 (9.1%)</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1">2nd Year Master (coded as 6)</td>
              <td rowspan="1" colspan="1">2 (1.2%)</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Region of Residence</td>
              <td rowspan="1" colspan="1">Saint-Petersburg (coded as 1)</td>
              <td rowspan="1" colspan="1">145 (87.9%)</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1">Leningrad Region (coded as 0)</td>
              <td rowspan="1" colspan="1">20 (12.1%)</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>To gain a better understanding of the sample, we asked additional questions related to individuals’ experience. It transpired that 63.6% of students had received some financial education at previous educational establishments. The proportion of students who received financial guidance from parents or guardians was almost equal: 46.7% did, while 45.5% did not. This highlights the important role of family socialization in developing financial literacy. In terms of budgeting behavior, the most common method was the informal mental tracking of expenses, followed by the use of budgeting software applications. However, a substantial proportion of respondents had no systematic budgeting practices, suggesting room for improvement in financial management skills. In terms of saving, the majority (63%) preferred bank savings accounts, followed by current accounts (52.7%) and saving cash at home (32.7%). Investment products were less popular, likely due to their greater complexity and risk. While most students (61.2%) are aware of their potential future expenses, only around 11.5% consistently plan their spending, indicating a moderate level of financial planning awareness. Almost 70% of students have a clear understanding of their monthly income and expenses, demonstrating a proactive attitude towards personal financial management, which is facilitated by modern digital banking tools.</p>
      <p>Overall, the sample represents business school students with a generally adequate level of financial knowledge and behavior, though the findings highlight the need for deeper financial education, especially given the insufficient coverage at earlier educational stages. This highlights the importance of improving financial literacy programmes to encourage better financial behavior and career-related decision-making among young adults.</p>
      <p><italic>Scales</italic>. This study used the scale by <xref ref-type="bibr" rid="B8">Hirschi et al. (2014)</xref> to assess career engagement. This unidimensional instrument has undergone rigorous psychometric validation in numerous research studies involving various samples of university students. Furthermore, it was initially validated using a sample of students. The scale was measured using a five-point Likert scale (1 = ‘never’ to 5 = ‘very often’), which captured the frequency of various proactive career behaviors over a defined period. The scale demonstrated robust internal consistency (Cronbach’s alpha = 0.88–0.89).</p>
      <p>Financial literacy was measured as a multidimensional construct incorporating knowledge, skills and attitudes. The primary instrument was adapted from the Financial Wellbeing Questionnaire (<abbrev xlink:title="Financial Wellbeing Questionnaire">FWQ</abbrev>) (Bank of Japan Financial Literacy Survey, 2016; NAFI, 2023). A five-point Likert response scale was used, and four factors were identified through factor analysis: 1) impulsivity in spending, 2) self-assessment of financial knowledge, 3) risk aversion and 4) financial discipline. Internal consistency: Cronbach’s alpha = 0.89. The Appendix contains a complete version of the questionnaire with all response options. This structure ensures a comprehensive, reliable and contextually adapted assessment of the key constructs relevant to this research (Table <xref ref-type="table" rid="T2">2</xref>).</p>
      <table-wrap id="T2" position="float" orientation="portrait">
        <label>Table 2.</label>
        <caption>
          <p>Descriptive statistics and correlation matrix of independent variables (n = 165)</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <th rowspan="1" colspan="1">
                <bold>Variable</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>Min</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>Max</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>Mean</bold>
              </th>
              <th rowspan="1" colspan="1"><bold>Std. Dev</bold>.</th>
              <th rowspan="1" colspan="1">
                <bold>1</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>2</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>3</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>4</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>5</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>6</bold>
              </th>
              <th rowspan="1" colspan="1">
                <bold>7</bold>
              </th>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">1. Career engagement</td>
              <td rowspan="1" colspan="1">1.375</td>
              <td rowspan="1" colspan="1">5.000</td>
              <td rowspan="1" colspan="1">3.748</td>
              <td rowspan="1" colspan="1">0.785</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2. finfactor1</td>
              <td rowspan="1" colspan="1">1.333</td>
              <td rowspan="1" colspan="1">5.000</td>
              <td rowspan="1" colspan="1">3.513</td>
              <td rowspan="1" colspan="1">0.810</td>
              <td rowspan="1" colspan="1">-0.054</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">3. finfactor2</td>
              <td rowspan="1" colspan="1">1.500</td>
              <td rowspan="1" colspan="1">5.000</td>
              <td rowspan="1" colspan="1">3.982</td>
              <td rowspan="1" colspan="1">0.571</td>
              <td rowspan="1" colspan="1">0.124</td>
              <td rowspan="1" colspan="1">0.194*</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">4. finfactor3</td>
              <td rowspan="1" colspan="1">1.000</td>
              <td rowspan="1" colspan="1">5.000</td>
              <td rowspan="1" colspan="1">3.858</td>
              <td rowspan="1" colspan="1">0.769</td>
              <td rowspan="1" colspan="1">-0.065</td>
              <td rowspan="1" colspan="1">0.240**</td>
              <td rowspan="1" colspan="1">-0.009</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">5. finfactor4</td>
              <td rowspan="1" colspan="1">2.000</td>
              <td rowspan="1" colspan="1">5.000</td>
              <td rowspan="1" colspan="1">3.782</td>
              <td rowspan="1" colspan="1">0.729</td>
              <td rowspan="1" colspan="1">0.228**</td>
              <td rowspan="1" colspan="1">0.096</td>
              <td rowspan="1" colspan="1">0.185*</td>
              <td rowspan="1" colspan="1">0.058</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">6. Sex***</td>
              <td rowspan="1" colspan="1">0</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1">0.236</td>
              <td rowspan="1" colspan="1">0.426</td>
              <td rowspan="1" colspan="1">-0.050</td>
              <td rowspan="1" colspan="1">0.011</td>
              <td rowspan="1" colspan="1">0.023</td>
              <td rowspan="1" colspan="1">-0.287**</td>
              <td rowspan="1" colspan="1">-0.030</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">7. Study year</td>
              <td rowspan="1" colspan="1">3.000</td>
              <td rowspan="1" colspan="1">6.000</td>
              <td rowspan="1" colspan="1">3.830</td>
              <td rowspan="1" colspan="1">0.631</td>
              <td rowspan="1" colspan="1">-0.024</td>
              <td rowspan="1" colspan="1">-0.027</td>
              <td rowspan="1" colspan="1">0.110</td>
              <td rowspan="1" colspan="1">-0.038</td>
              <td rowspan="1" colspan="1">0.052</td>
              <td rowspan="1" colspan="1">-0.009</td>
              <td rowspan="1" colspan="1">1</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">8. Region***</td>
              <td rowspan="1" colspan="1">0</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1">0.879</td>
              <td rowspan="1" colspan="1">0.328</td>
              <td rowspan="1" colspan="1">0.164*</td>
              <td rowspan="1" colspan="1">-0.056</td>
              <td rowspan="1" colspan="1">0.025</td>
              <td rowspan="1" colspan="1">-0.080</td>
              <td rowspan="1" colspan="1">0.010</td>
              <td rowspan="1" colspan="1">-0.012</td>
              <td rowspan="1" colspan="1">-0.047</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn>
            <p>* p &lt; 0.05 two-tailed correlation, ** &lt;<italic>0,01</italic> ***Spearman correlation; for the rest - Pearson correlation is used. Financial factors: 1) impulsiveness in spending, 2) self-assessment of financial knowledge, 3) risk aversion, 4) financial discipline.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Analysis of the correlation results between the observations allows them all to be included in the same model as independent variables due to a lack of correlation or a very low level of correlation between them.</p>
    </sec>
    <sec sec-type="Results" id="sec4">
      <title>Results</title>
      <p>Table <xref ref-type="table" rid="T3">3</xref> shows the results of the hierarchical regression analysis. We relied on standardized coefficients for the variables and betas.</p>
      <table-wrap id="T3" position="float" orientation="portrait">
        <label>Table 3.</label>
        <caption>
          <p>Results of the regression analysis</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Model</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Variables</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Standardized B</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>t</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Significance</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Collinearity Statistics</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="10" colspan="1">1 R=0,182 F=1,833  (p-value 0,143)  2  R=0,319 F=2,533  (p-value 0,017)</td>
              <td rowspan="1" colspan="1">Sex</td>
              <td rowspan="1" colspan="1">0.019</td>
              <td rowspan="1" colspan="1">0.248</td>
              <td rowspan="1" colspan="1">0.805</td>
              <td rowspan="1" colspan="1">1,000</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Study year</td>
              <td rowspan="1" colspan="1">-0.017</td>
              <td rowspan="1" colspan="1">-0.215</td>
              <td rowspan="1" colspan="1">0.830</td>
              <td rowspan="1" colspan="1">0.998</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Region</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.179</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>2.308</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.022</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.998</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Sex</td>
              <td rowspan="1" colspan="1">0.027</td>
              <td rowspan="1" colspan="1">0.340</td>
              <td rowspan="1" colspan="1">0.735</td>
              <td rowspan="1" colspan="1">0.913</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Study year</td>
              <td rowspan="1" colspan="1">-0.044</td>
              <td rowspan="1" colspan="1">-0.572</td>
              <td rowspan="1" colspan="1">0.568</td>
              <td rowspan="1" colspan="1">0.981</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Region</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.165</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>2.175</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.031</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.990</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">finfactor1</td>
              <td rowspan="1" colspan="1">-0.075</td>
              <td rowspan="1" colspan="1">-0.934</td>
              <td rowspan="1" colspan="1">0.352</td>
              <td rowspan="1" colspan="1">0.891</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">finfactor2</td>
              <td rowspan="1" colspan="1">0.099</td>
              <td rowspan="1" colspan="1">1.252</td>
              <td rowspan="1" colspan="1">0.213</td>
              <td rowspan="1" colspan="1">0.918</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">finfactor3</td>
              <td rowspan="1" colspan="1">-0.057</td>
              <td rowspan="1" colspan="1">-0.691</td>
              <td rowspan="1" colspan="1">0.491</td>
              <td rowspan="1" colspan="1">0.853</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>finfactor4</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.219</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>2.839</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.005</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>0.958</bold>
              </td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn>
            <p>Financial factors: 1) impulsiveness in spending, 2) self-assessment of financial knowledge, 3) risk aversion, 4) financial discipline.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Adding factors related to financial literacy improves the model’s explanatory power to R = 0.319. This is a significant improvement on Model 1. Model 2 as a whole is statistically significant (F = 2.533, p = 0.017), indicating that the included predictors collectively explain a significant proportion of the variance in the dependent variable. However, sex and study year remain non-significant predictors (p &gt; 0.5), implying there is no evidence to suggest that gender or academic year influence the dependent variable in this sample. Therefore, initiatives related to financial literacy could potentially address the issue of the gender pay gap in the Russian market. The region shows a positive and statistically significant effect, which could be explained by additional efforts to offset extra costs associated with renting accommodation and commuting. Among the financial literacy factors, financial discipline (finfactor4) was found to have a statistically significant positive effect (standardized B = 0.219, p = 0.005). This suggests that a combination of beliefs and behavioral aspects is associated with higher career engagement. Dispositional characteristics and perceived level of awareness all show non-significant effects, indicating that these dimensions are not strong predictors in this model. There were no concerns regarding multicollinearity among the predictors.</p>
    </sec>
    <sec sec-type="Discussion, limitations and conclusion" id="sec5">
      <title>Discussion, limitations and conclusion</title>
      <p>The findings suggest that, although most business school students in our sample had some exposure to financial education, a significant proportion either did not actively participate or did not have access to formal financial literacy programmes during their earlier years of schooling. This gap may contribute to difficulties in adopting responsible financial behavior, as evidenced by the reliance on informal budgeting methods and cash savings rather than more effective financial planning tools or investment products. Our results also highlight the important influence of family on financial knowledge and attitudes: almost half of the respondents reported receiving no financial guidance from their parents or guardians. This finding is consistent with broader literature emphasizing socialization as a key factor in financial literacy development.</p>
      <p>Despite these gaps, a positive trend emerges: most students are aware of their future expenses and have a clear understanding of their monthly income and spending. This awareness, coupled with their use of digital money management tools, suggests promising potential for developing financial competence. In light of the identified shortcomings, integrating thorough financial education programmes into higher education curricula could greatly improve proactive financial behavior. Such programmes could empower students to adopt more sophisticated budgeting and saving techniques, thereby fostering long-term financial stability.</p>
      <p>The results of the regression analysis demonstrate a significant relationship between financial literacy, specifically financial discipline, and career engagement among business school students. This supports the hypothesis that healthy financial behavior and related beliefs contribute to the development of initiative and active career management. This fourth factor reflects the timely payment of bills and overall satisfaction with one’s financial situation. This is likely due to either a stable income or effective resource management. Students who are actively engaged in their careers, through part-time jobs, internships or future planning, are more likely to have sufficient income to meet their financial obligations on time. They are also more likely to feel satisfied with their career prospects and approach financial commitments more consciously, which correlates with their level of professional maturity.</p>
      <p>By contrast, the other factors relate more to personal dispositions (Factors 1 and 3) and subjective self-assessment of knowledge (Factor 2). These do not necessarily demonstrate a direct connection with career engagement. For example, impulsive spending (Factor 1) may be an independent personality trait, and self-assessed financial knowledge (Factor 2) reflects cognitive perception rather than the outcome of career activity. Risk-taking and indebtedness (Factor 3) may be the result of external circumstances, such as student loans, and are not necessarily career-related. Overall, this suggests that financial discipline (Factor 4) is a meaningful indicator of career engagement and professional maturity among business school students.</p>
      <p>In contrast, sex and study year were not significant predictors, indicating that material knowledge and skills play a more crucial role in shaping career engagement than demographic factors. In this way, our research contradicts previous studies which revealed that younger individuals and female students are in a more vulnerable position. This could be explained by the cultural context, the fact that women have been present in the labor market for over 100 years, and the high level of exposure to financial literacy content on the internet. Therefore, information in our country is more accessible to all individuals, regardless of their socio-demographic characteristics.</p>
      <p>In the context of ongoing trends in the Russian labor market, where a gender pay gap persists, our data indirectly confirm that financial literacy and related attitudes can help to overcome these inequalities. This is achieved by enhancing women’s confidence in career decisions and shaping their salary expectations.</p>
      <p>Several limitations of this study should be acknowledged. Firstly, the sample consisted exclusively of students from a single business school within a single university. This limits the generalizability of the findings to broader populations and to individuals with professional backgrounds other than management. Secondly, the cross-sectional design limits our ability to draw causal inferences between financial literacy and career engagement. Longitudinal studies provide a deeper insight into these dynamics over time. Third, self-reported questionnaires are subject to social desirability biases, which can lead to overstated reports of financial knowledge and proactive behavior. Furthermore, although region of residence is taken into account in the study, more nuanced economic variables and cultural factors are not considered, despite their potential influence on career behaviors. Next, some relevant psychological and contextual variables, such as additional personality traits and family background that could play a significant role in shaping proactive career behavior, were beyond the scope of this study. Finally, the study relied on self-reported data that may be subject to social desirability biases or inaccuracies. We attempted to address this by using a snowball sampling method, but this approach also had certain limitations that need to be acknowledged.</p>
      <p>Future research could address these limitations and thus deepen the understanding of how financial literacy interacts with career development and informs more targeted educational and policy measures.</p>
      <p>Overall, we believe that this study provides valuable insights into the financial literacy and career-related behavior of young adults in a business school setting. Its practical implications suggest that efforts to improve financial literacy should be comprehensive, combining curriculum improvements, parental involvement, and the innovative use of technology in financial education. This holistic approach is essential for equipping young people with the skills they need to navigate increasingly complex financial and career environments.</p>
    </sec>
  </body>
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        <mixed-citation>Shi, X., Prevett, P., Farnsworth, V., Kwong, K. C., Wan, W., He, F., ... &amp; Zhen, L. (2019). Modelling Changes To Survey Response Items Over Time In A Britain Financial Literacy Education Study. <italic>Journal of Financial Counseling and Planning</italic>, <italic>30</italic>(1), 56-66. <ext-link xlink:href="10.1891/1052-3073.30.1.56" ext-link-type="doi">https://doi.org/10.1891/1052-3073.30.1.56</ext-link></mixed-citation>
      </ref>
    </ref-list>
    <app-group>
      <app id="app1">
        <title>Appendix 1</title>
        <p>
          <bold>Fragment of a survey in a back translated version from the native language</bold>
        </p>
        <p><bold>Financial Literacy</bold>:</p>
        <p>1. Financial Knowledge (reflects a person’s understanding of basic financial terms, characteristics of financial products, inflation, risk-return relationship):</p>
        <p>1.1. How would you rate your level of digital financial literacy, i.e., your knowledge and ability to use financial services via digital technologies such as a personal account on a website or mobile app?</p>
        <p>
          <italic>Excellent knowledge and skills / Good knowledge and skills / Satisfactory knowledge and skills / Unsatisfactory knowledge and skills / No knowledge or skills / Difficult to answer</italic>
        </p>
        <p>1.2. How would you rate your overall financial knowledge compared to other people? Please select only one answer.</p>
        <p>
          <italic>Very high / Fairly high / Above average / Fairly low / Very low / Don’t know</italic>
        </p>
        <p>2. Financial Skills/Behavior (allows assessing a person’s ability to make balanced everyday financial decisions: planning and managing family budget, solving financial problems, etc.):</p>
        <p>2.1. I pay my bills on time. Please select from the following scale from 1 to 5 (5 – agree, 1 – disagree).</p>
        <p>2.2. At the moment, I have too much debt. Please select from the following scale from 1 to 5 (1 – agree, 5 – disagree).</p>
        <p>3. Financial Attitudes (demonstrates a person’s orientation toward achieving long-term financial goals, understanding the need for a reasonable balance between spending and saving):</p>
        <p>3.1. Before I buy something, I carefully consider whether I can afford it. Please select from the following scale from 1 to 5 (5 – agree, 1 – disagree).</p>
        <p>3.2. I prefer spending money rather than saving it for the long term. Please select from the following scale from 1 to 5 (1 – agree, 5 – disagree).</p>
        <p>3.3. I tend to live in the present and do not worry about tomorrow. Please select from the following scale from 1 to 5 (1 – agree, 5 – disagree).</p>
        <p>3.4. I am willing to risk part of my own money in saving or investing. Please select from the following scale from 1 to 5 (5 – agree, 1 – disagree).</p>
        <p>3.5. Overall, thinking about your assets, debts, and savings, how satisfied are you with your current financial situation? Please select from the following scale from 1 to 5 (5 – agree, 1 – disagree).</p>
        <p><bold>Keys</bold>:</p>
        <p>3.1.-3.3. Impulsivity in spending</p>
        <p>1.1., 1.2. Perceived financial knowledge</p>
        <p>2.2., 3.4. Risk aversion</p>
        <p>2.1., 3.5. Financial discipline</p>
      </app>
    </app-group>
  </back>
</article>
