Title 1 

Strategic Financial Agility: A Case-Based Exploration of Growth Tactics in Post-Pandemic Mid-Sized Enterprises.

Methodology 

Qualitative – Multiple case study using semi-structured interviews and document analysis.

Description 

This study explores how mid-sized enterprises developed and adapted financial strategies for sustainable growth in the aftermath of the COVID-19 pandemic. It focuses on decision-making processes, leadership narratives, and contextual financial tactics used across different industries. Data will be gathered through semi-structured interviews with CFOs and financial strategists, supplemented by internal financial planning documents and growth records. The goal is to extract industry-specific themes and best practices that define "financial agility."

Key References:

1. Jibril, A. B., Amoah, J., Panigrahi, R. R., & Gochhait, S. (2024). Digital transformation in emerging markets: the role of technology adoption and innovative marketing strategies among SMEs in the post-pandemic era. International Journal of Organisational Analysis.
2. Bhattacharyya, S. S., & Thakre, S. (2021). Coronavirus pandemic and economic lockdown; study of strategic initiatives and tactical responses of firms. International Journal of Organisational Analysis, 29(5), 1240-1268.
3. Angelakis, A., & Manioudis, M. (2025). The Role of SMEs Within a Turbulent and Constantly Changing Business Environment: Trends, Challenges and Sustainable Growth Policies in Europe. In The Economic Impact of Small and Medium-Sized Enterprises: Analytical Approaches to Growth and Innovation Challenges Amid Crises in Europe (pp. 21-39). Cham: Springer Nature Switzerland.

Title 2 

Evaluating the Impact of Strategic Capital Allocation, Digital Finance Adoption, and Risk Appetite on Financial Growth Trajectories of Manufacturing Firms.

Methodology 

Quantitative – Survey-based with Structural Equation Modelling (SEM).

Description 

This research quantitatively examines the relationships among strategic capital allocation, digital finance adoption, organisational risk appetite, and financial growth outcomes in Indian manufacturing firms. A structured questionnaire will be administered to financial executives, and SEM will be employed to test the hypothesised model. The study aims to uncover the direct and mediated effects of digital transformation and financial decision-making on organisational growth performance.

Key References:

1. Amin, A. R. S., & Adil, M. (2025). Evaluation of the Relationship Between Capital Budget and Financing Decisions in Firm Growth. Economics and Digital Business Review, 6(1).
2. Mao, J., Xie, J., Gao, Y., Tang, Q., Li, Z., & Zhang, B. (2024). Navigating Growth: The Nexus of Supply Chain Finance, Digital Maturity, and Financial Health in Chinese A-Share Listed Corporations. Sustainability, 16(13), 5418.
3. Wu, X., Liu, Y., & Xia, B. (2024). Industrial technology progress, digital finance development and corporate risk-taking: Evidence from China's listed firms. PLOS ONE, 19(3), e0298734.

Title 3 

Strategising for Sustainable Financial Growth: An Integrated Analysis of CFO Perspectives and Organisational Performance Metrics.

Methodology 

Mixed Methods – Explanatory Sequential Design (Quantitative → Qualitative)

Description 

The study begins with a survey of CFOs across various industries to quantitatively identify key financial growth strategies and their correlation with firm performance using SEM. Following this, qualitative interviews with a select group of CFOs will provide deeper insights into the rationale behind these strategies, including contextual enablers and barriers. This design ensures validation of patterns observed in the data and reveals nuanced strategy-development behaviours, offering actionable insights for practitioners.

Key References:

1. Flamholtz, E., & Hua, W. (2002). Strategic Organizational Development, Growing Pains and Corporate Financial Performance: An Empirical Test. European Management Journal, 20(5), 527-536.
2. Banker, R. D., Mashruwala, R., & Tripathy, A. (2006). Generic strategies and sustainability of financial performance. Strategic Management Journal, 12(1), 33-46.
3. Ittner, C. D., Larcker, D. F., & Randall, T. (2003). Performance implications of strategic performance measurement in financial services firms. Accounting, Organisations and Society, 28(7-8), 715-741.

Title 4 

Reckoning with Risk: An Industry-Wise Exploration of Executive Decision-Making Under Financial Uncertainty

Methodology 

Qualitative – In-depth interviews and thematic analysis

Description 

This study investigates how senior finance executives in different industries perceive and respond to financial risk, especially in volatile market conditions. It examines the narratives, mental models, and organisational contexts that shape risk management strategies. The research draws insights through semi-structured interviews with CFOs, risk officers, and treasury heads, aiming to develop an industry-sensitive typology of decision-making heuristics under risk.

Key References:

1. Shivaani, M. V., Jain, P. K., Yadav, S. S., Shivaani, M. V., Jain, P. K., & Yadav, S. S. (2019). Normative Framework for Risk Disclosure Index and Its Empirical Analysis. Understanding Corporate Risk: A Study of Risk Measurement, Disclosure and Governance, 65-167.
2. Vyas, P., & Paliwal, P. (2022). A Strategic Response to Disruption in the Crude Oil Industry: Insights from Contemporary Literature. Pacific Business Review International, 14(9).
3. Jain, P. K., Singh, S., Yadav, S. S., Jain, P. K., Singh, S., & Yadav, S. S. (2013). Capital Budgeting Decisions. Financial Management Practices: An Empirical Study of Indian Corporates, 37-76.

Title 5 

Financial Resilience: Examining the Impact of Risk Governance, Tech Adoption, and Capital Allocation on Risk Mitigation Outcomes Using SEM

Methodology 

Quantitative – Survey-based study with data analysed through Structural Equation Modelling (SEM)

Description 

This study develops a multi-dimensional model linking organisational risk governance frameworks, financial technology adoption, and capital allocation efficiency to overall risk mitigation outcomes. Target respondents include finance managers and risk analysts from mid to large corporations. The findings will identify critical levers influencing firm-level financial resilience, useful for developing data-driven risk strategies.

Key References:

1. Lu, Q., Wang, X., & Wang, Y. (2023). Enhancing supply chain resilience with supply chain governance and finance: The enabling role of digital technology adoption. Business Process Management Journal, 29(4), 944-964.
2. Butler, T., & Brooks, R. (2021). Achieving operational resilience in the financial industry: Insights from complex adaptive systems theory and implications for risk management. Journal of Risk Management in Financial Institutions, 14(4), 395-407.
3. Budiasih, Y. (2024). Financial risk management and its effect on the financial stability of information technology companies. International Journal of Financial Economics, 1(5), 1097-1108.

Title 6 

From Insight to Impact: A Mixed Methods Study on the Integration of Predictive Analytics in Strategic Financial Risk Management

Methodology 

Mixed Methods – Quantitative SEM analysis followed by qualitative case studies

Description 

This research explores how predictive analytics tools are reshaping strategic financial risk management practices. The first phase employs a structured survey to quantify relationships between analytics capabilities, leadership support, and effectiveness of risk responses. SEM is used for path analysis. The second phase delves deeper through case studies in three industries (e.g., manufacturing, tech, and BFSI), offering rich insights into implementation dynamics, challenges, and impact trajectories.

Key References:

1. Elumilade, O. O., Ogundeji, I. A., Ozoemenam, G. O. D. W. I. N., Omokhoa, H. E., & Omowole, B. M. (2023). The role of data analytics in strengthening financial risk assessment and strategic decision-making. Iconic Research and Engineering Journals, 6(10).
2. Nahar, J., Hossain, M. S., Rahman, M. M., & Hossain, M. A. (2024). Advanced Predictive Analytics for Comprehensive Risk Assessment in Financial Markets: Strategic Applications and Sector-Wide Implications. Global Mainstream Journal of Business, Economics, Development & Project Management, 3(4), 39-53.
3. Oyedokun, O., Ewim, S. E., & Oyeyemi, O. P. (2024). Leveraging advanced financial analytics for predictive risk management and strategic decision-making in global markets. Global Journal of Research in Multidisciplinary Studies, 2(02), 016-026.

Title 7 

Narratives of Impact: Exploring How Investment Professionals Construct the Meaning and Value of Sustainability in Financial Decision-Making

Methodology 

Qualitative – In-depth interviews with portfolio managers and ESG analysts; thematic analysis

Description 

This study explores how industry professionals conceptualise and interpret sustainability within investment decisions. By focusing on the language, narratives, and frameworks used in practice, the research aims to uncover the implicit values and organisational norms shaping ESG investment choices. This case-based qualitative study will provide insight into the human and cultural dimensions of sustainable investing, which are often overlooked in purely metrics-driven studies.

Key References:

1. Siegrist, M., Bowman, G., Mervine, E., & Southam, C. (2020). Embedding environment and sustainability into corporate financial decision‐making. Accounting & Finance, 60(1), 129-147.
2. Ziolo, M., Filipiak, B. Z., Bąk, I., & Cheba, K. (2019). How to design more sustainable financial systems: The roles of environmental, social, and governance factors in the decision-making process. Sustainability, 11(20), 5604.
3. Martin, L. (2015). Incorporating values into sustainability decision-making. Journal of Cleaner Production, 105, 146-156.

Title 8 

Evaluating the Influence of Environmental, Social, and Governance Integration on Perceived Financial Performance: A Structural Equation Modelling Approach

Methodology 

Quantitative – Structured questionnaire; SEM using SmartPLS

Description 

This study investigates the causal relationships between the integration of ESG factors into investment strategies and perceived financial performance among institutional investors. The model includes mediating variables such as investor confidence and risk perception, allowing a comprehensive test of how ESG practices are believed to affect profitability and resilience. Data will be collected from industry professionals via survey, ensuring feasibility and industry relevance.

Key References:

1. Chen, S., Song, Y., & Gao, P. (2023). Environmental, social, and governance (ESG) performance and financial outcomes: Analysing the impact of ESG on financial performance. Journal of Environmental Management, 345, 118829.
2. Velte, P. (2017). Does ESG performance have an impact on financial performance? Evidence from Germany. Journal of Global Responsibility, 8(2), 169-178.
3. Lee, M. T., & Suh, I. (2022). Understanding the effects of Environment, Social, and Governance conduct on financial performance: Arguments for a process and integrated modelling approach. Sustainable Technology and Entrepreneurship, 1(1), 100004.

Title 9 

Beyond Compliance: A Mixed Methods Inquiry into the Drivers and Outcomes of Proactive Sustainable Investment Strategies in Mid-cap Firms

Methodology 

Mixed Methods – Phase 1: Survey with SEM; Phase 2: Case studies with semi-structured interviews.

Description 

This research examines both the quantitative impact and qualitative motivations behind sustainable investing practices among mid-cap firms. The first phase applies SEM to identify statistically significant predictors of sustainable investment outcomes, such as innovation capacity and stakeholder pressure. The second phase uses case-based interviews to deepen the understanding of why certain firms exceed compliance and adopt proactive ESG strategies. The combination provides a comprehensive view of strategy formulation and performance.

Key References:

1. Carballo‐Penela, A., & Castromán‐Diz, J. L. (2015). Environmental policies for sustainable development: an analysis of the drivers of proactive environmental strategies in the service sector. Business Strategy and the Environment, 24(8), 802-818.
2. Tomar, L., Seth, S., Pathan, M. I., Yadav, P., & Mahato, M. K. (2024). Green Investments and Corporate Social Responsibility: Driving Forces for Sustainable Business Growth. Economic Sciences, 20(2), 329-337.
3. Chan, R. Y., Lai, J. W., & Kim, N. (2022). Strategic motives and performance implications of proactive versus reactive environmental strategies in corporate sustainable development. Business Strategy and the Environment, 31(5), 2127-2142.

Title 10 

Intuition Behind Strategic Capital Allocation: A Case-Based Inquiry into Executive Financial Judgement in Volatile Markets

Methodology 

Qualitative – Multiple case study using semi-structured interviews

Description 

This research explores how senior finance executives in mid to large-scale establishments exercise judgement in capital allocation decisions under conditions of uncertainty and market volatility. Drawing insights from in-depth interviews and thematic analysis, the study uncovers underlying behavioural, experiential, and contextual factors influencing decision-making that are not captured in formal models. The findings will be grounded in decision theory and behavioural finance perspectives.

Key References:

1. Grant, M., & Nilsson, F. (2020). The production of strategic and financial rationales in capital investments: Judgments based on intuitive expertise. The British Accounting Review, 52(3), 100861.
2. Ismaulina, I. (2025). The Experience of Financial Managers in Investment Decision-Making in Multinational Companies: A Phenomenological Study on Challenges and Strategies in Managing Market Volatility and Economic Risks. Journal of Economic and Financial Studies, 1(1), 28-37.
3. Gervais, S. (2010). Capital budgeting and other investment decisions. Behavioural Finance: Investors, Corporations, and Markets.

Title 11 

Modelling the Interplay of Financial Literacy, Risk Culture, and Investment Governance on Corporate Capital Structure Decisions

Methodology 

Quantitative – Survey-based with Structural Equation Modelling

Description 

This study quantitatively investigates how internal capabilities - such as the financial literacy of decision-makers, embedded risk culture, and investment governance protocols - affect corporate capital structure decisions. Using data collected from financial managers across diverse industries, the research applies SEM to examine direct and mediated relationships, offering empirical insights for enhancing corporate financial policy frameworks.

Key References:

1. Erfan, N., & Elgiziry, K. (2016). The impact of managerial risk culture on the capital structure and the investment decision of corporations in Egypt. International Research Journal of Applied Finance, 7(12), 356-371.
2. Chow, Y. P., Muhammad, J., Bany-Ariffin, A. N., & Cheng, F. F. (2018). Macroeconomic uncertainty, corporate governance and corporate capital structure. International Journal of Managerial Finance, 14(3), 301-321.
3. Çam, İ., & Özer, G. (2022). The influence of country governance on the capital structure and investment financing decisions of firms: An international investigation. Borsa Istanbul Review, 22(2), 257-271.

Title 12 

Bridging the Gap Between Financial Policy Intentions and Practice: A Mixed Methods Exploration of Investment Decision-Making in Indian Manufacturing Firms

Methodology 

Explanatory Sequential Mixed Methods – Quantitative SEM followed by qualitative interviews

Description 

This study first employs a survey to model the influence of organisational priorities, stakeholder pressure, and financial constraints on long-term investment decision-making using SEM. Based on patterns emerging from the quantitative phase, follow-up qualitative interviews with CFOs and investment heads deepen the understanding of divergences between formal policy and real-world practices. The research aims to identify both structural and human drivers that impact financial decision execution in practice.

Key References:

1. Husain, M., & Pistelli, M. (2016). Where good intentions meet good business practice. Report, The Mix, Washington, DC.
2. Marais, L., & Cloete, J. (2017). Housing policy and private sector housing finance: Policy intent and market directions in South Africa. Habitat International, 61, 22-30.
3. Hayashi, M., & Edwards, D. B. (2015). Policy intention versus policy implementation. The Political Economy of Schooling in Cambodia, Issues of Quality and Equity, 77-98.

Title 13 

Unpacking the Influence of Behavioural Biases and Digital Information Overload on Corporate Investment Decisions in Emerging Markets

Methodology 

Quantitative; Structural Equation Modelling (SEM)

Description 

This study investigates how cognitive biases (like overconfidence, anchoring, and herding) interact with the deluge of digital financial information to influence investment decisions among professionals in emerging market industries. Using SEM, it models the interrelationship between behavioural constructs, perceived information quality, and investment performance expectations, drawing responses from industry-based investors and financial analysts.

Key References:

1. Haidari, M. N. (2023). Impact of Decision-Making on Investment Performance: A Comprehensive Analysis. Journal of Asian Development Studies, 12(4), 980-990.
2. Hrnjic, E., Reeb, D. M., & Yeung, B. (2019). Financial decisions, behavioural biases, and governance in emerging markets. In The Oxford Handbook of Management in Emerging Markets (p. 161). Oxford University Press.
3. Gabhane, D., Sharma, A., & Mukherjee, R. (2023). Behavioural finance: exploring the influence of cognitive biases on investment decisions. Boletin de Literatura Oral-The Literary Journal, 10(1), 3133-3141.

Title 14 

Evolving Risk Narratives in Institutional Investment: A Multi-Case Exploration of Post-Pandemic Portfolio Realignments

Methodology 

Qualitative; Case study method with in-depth interviews and document analysis

Description 

Focusing on 3-5 major institutional investors or corporate treasury departments, this research explores how perceptions of systemic risk have changed post-COVID-19 and how those narratives shaped strategic shifts in investment approaches. The study collects qualitative data through semi-structured interviews and internal investment policy reviews, aiming to understand decision-making under uncertainty beyond what numbers can capture.

Key References:

1. Suhonen, A., & Vatanen, K. (2024). Do Alternative Risk Premia Diversify? New Evidence for the Post-Pandemic Era. Journal of Portfolio Management, 50(5).
2. Ramseur, S. (2021). Portfolio management and occupancy planning in a post-pandemic world. Corporate Real Estate Journal, 10(3), 304-309.
3. Ahmar, A. S., Alsa, Y. A., Alfairus, M. Q., Rais, Z., & Rahman, A. (2025). Assessing Investment Risk in the Post-Pandemic Entertainment Industry: A Statistical Analysis of Portfolio Returns and Risk Measures. Quantitative Economics and Management Studies, 6(1), 9-19.

Title 15 

Environmental Social Governance Driven Investment Trends in Industrial Firms: Integrating Perception Metrics with Portfolio Data

Methodology 

Mixed Methods; Exploratory sequential design

Description 

This research explores how environmental, social, and governance (ESG) considerations are transforming investment trends within industrial sectors. It begins with focus groups and semi-structured interviews to uncover the key ESG drivers affecting investment behaviour. These insights are then quantitatively validated through a structured questionnaire analysed using SEM, targeting sustainability officers, CFOs, and institutional investors.

Key References:

1. Ahmad, H., Yaqub, M., & Lee, S. H. (2024). Environmental-, social-, and governance-related factors for business investment and sustainability: A scientometric review of global trends. Environment, Development and Sustainability, 26(2), 2965-2987.
2. Puaschunder, J. M. (2017). Ethical, environmental, social and governance-oriented investments. Archives of Business Research, 5(8), 151-159.
3. Dmuchowski, P., Dmuchowski, W., Baczewska-Dąbrowska, A. H., & Gworek, B. (2023). Environmental, social, and governance (ESG) model; impacts and sustainable investment - Global trends and Poland's perspective. Journal of Environmental Management, 329, 117023.

Title 16 

Emotional Triggers in Wealth Management Decisions: A Sectoral Inquiry into the Lived Experiences of High-Net-Worth Professionals

Methodology 

Qualitative – Interpretive Phenomenological Analysis (IPA) using in-depth semi-structured interviews with senior professionals across sectors (e.g., IT, Pharma, Manufacturing).

Description 

This study aims to explore the emotional and psychological underpinnings that influence wealth management decisions among high-net-worth professionals. The research delves into how trust, risk perception, legacy aspirations, and life-stage transitions shape wealth allocation strategies. The findings can aid wealth managers in personalising their advisory frameworks beyond traditional financial profiling.

Key References:

1. Garad, A. (2024). Mindful wealth management: thematic integration and analysis of mindfulness in financial decision-making. Journal of Alternative Finance, 1(3), 252-268.
2. Dibb, S., Merendino, A., Aslam, H., Appleyard, L., & Brambley, W. (2021). Whose rationality? Muddling through the messy emotional reality of financial decision-making. Journal of Business Research, 131, 826-838.
3. Othman, N. N. (2024). Emotional Economics: The Role of Psychological Biases in Personal Investment Outcomes. Available at SSRN 4844927.

Title 17 

Assessing the Determinants of Digital Wealth Management Adoption among Mid-Career Professionals: A Structural Equation Modelling Approach

Methodology 

Quantitative – Survey-based research using SEM to validate a model incorporating constructs like trust in technology, perceived value, financial literacy, platform usability, and advisory support.

Description 

This study quantitatively examines the behavioural and perceptual factors that drive the adoption of digital wealth management platforms (e.g., robot-advisors) among mid-career industry professionals. SEM is used to test the interplay between enabling factors and user intent, offering insights for fintech firms on user-centric feature development.

Key References:

1. Mahapatra, G., & Dash, S. (2021). Future of mid-career education in a transforming work context: A review of literature and directions for future research. South Asian Journal of Management, 28(3).
2. Alharoon, S., & Aldhmour, F. M. (2025). Investigating the impact of digital health technology adoption on female physicians' work-life balance in Bahrain. International Journal of Organisational Analysis, 33(4), 718-742.
3. Nkonde, R. K., & Kabwe, M. (2025). Factors Affecting Financial Management Practices in Public Institutions in Zambia. African Journal of Commercial Studies, 6(2), 71-79.

Title 18 

Integrated Wealth Management for Professionals: Exploring Behavioural Segments and Investment Patterns through a Mixed Methods Lens

Methodology 

Mixed Methods – Quantitative cluster analysis followed by qualitative focus group discussions.

Description 

This research identifies behavioural investor segments among working professionals based on attitudes toward risk, income diversification, and investment goals using quantitative techniques. Qualitative focus groups are then used to interpret the rationale behind segment-specific wealth strategies, bridging numeric patterns with contextual understanding. The outcome supports financial institutions in creating segment-tailored advisory models.

Key References:

1. Lewellen, W. G., Lease, R. C., & Schlarbaum, G. G. (1977). Patterns of investment strategy and behaviour among individual investors. The Journal of Business, 50(3), 296-333.
2. Kumar, S., Goyal, N., & Basu, R. (2018). Profiling emerging market investors: A segmentation approach. International Journal of Bank Marketing, 36(3), 441-455.
3. Nagpal, S., & Bodla, B. S. (2009). Impact of investors' lifestyle on their investment pattern: an empirical study. IUP Journal of Behavioural Finance, 6(2), 28.

Title 19 

Bridging the Last Mile: A Case-Based Exploration of How Fintech Narratives Reshape Financial Inclusion Strategies in Rural Enterprises

Methodology 

Case-based qualitative research using semi-structured interviews and narrative analysis.

Description 

This study investigates how fintech companies and rural enterprises co-create financial inclusion narratives that influence strategic decision-making. By analysing in-depth case studies across different industry sectors (e.g., agriculture, micro-manufacturing), it explores the barriers, enablers, and contextual factors shaping the adoption of inclusive financial technologies. The focus is on lived experiences, stakeholder interpretations, and organisational storytelling around inclusion.

Key References:

1. Nanda, S., & Yunus, Y. A. (2024). Understanding Financial Inclusion Through Fintech: A Qualitative Inquiry into the Role of Technology in Shaping Financial Landscapes. Golden Ratio of Finance Management, 4(1), 14-23.
2. Omowole, B. M., Urefe, O., Mokogwu, C., & Ewim, S. E. (2024). Integrating fintech and innovation in microfinance: Transforming credit accessibility for small businesses. International Journal of Frontline Research and Reviews, 3(1), 090-100.
3. Ding, D., Chong, G., Chuen, D. L. K., & Cheng, T. L. (2018). From ant financial to Alibaba's rural Taobao strategy - how Fintech is transforming social inclusion. In Handbook of Blockchain, Digital Finance, and Inclusion, Volume 1 (pp. 19-35). Academic Press.

Title 20 

Evaluating the Impact of Digital Literacy, Trust, and Service Accessibility on Financial Inclusion among Industrial Workers: A Structural Equation Modelling Approach

Methodology 

Quantitative - using a survey-based design and SEM analysis.

Description 

This study examines the direct and mediating effects of digital literacy, perceived trust in financial institutions, and service accessibility on the level of financial inclusion among industrial workers in semi-urban zones. Data is collected via structured questionnaires from employees across multiple factories and industrial clusters. SEM is employed to test the conceptual model and reveal policy-relevant insights for digital finance providers.

Key References:

1. Al-Shami, S. A., Damayanti, R., Adil, H., & Farhi, F. (2024). Financial and digital financial literacy through social media use towards financial inclusion among batik small enterprises in Indonesia. Heliyon, 10(15).
2. Adel, N. (2024). The impact of digital literacy and technology adoption on financial inclusion in Africa, Asia, and Latin America. Heliyon, 10(24).
3. Broekhoff, M. C., van der Cruijsen, C., & de Haan, J. (2024). Towards financial inclusion: Trust in banks' payment services among groups at risk. Economic Analysis and Policy, 82, 104-123.

Title 21 

From Access to Empowerment: A Mixed Methods Investigation into the Role of Employer-Supported Financial Platforms in Enhancing Financial Inclusion of Blue-Collar Workers

Methodology 

Sequential explanatory mixed methods - survey followed by focus group discussions.

Description 

This research explores how employer-facilitated financial tools (e.g., payroll-linked loans, micro-investment platforms) influence financial inclusion outcomes. Quantitative data collected through structured surveys will test hypothesised relationships using SEM, focusing on factors like financial behaviour, platform usability, and economic empowerment. Qualitative insights from focus groups with workers and HR managers will then contextualise the findings, providing a nuanced understanding of platform impact and user adaptation in industrial environments.

Key References:

1. Dedeoğlu, S., Şahankaya Adar, A., & Sırali, Y. (2021). Supporting women's employment through institutional collaboration on early childhood care and education. Ankara: International Labour Organisation.
2. Arnow-Richman, R. (2002). Accommodation Subverted: The Future of Work/Family Initiatives in a Me, Inc. World. Tex. J. Women & L., 12, 345.
3. Rahrig Jenkins, K., Stiehl, E., Bales, S., & Sherman, B. (2022). Employee Sources of Stress and Their Associations with Absenteeism: Differences by Wage Category. Journal of Occupational and Environmental Medicine, 64(7), 614-620.

Title 22 

Trust and Risk Perception in Fintech Partnerships: Voices from Financial Service Executives

Methodology 

Qualitative – In-depth semi-structured interviews and focus group discussions

Description 

This research explores how executives in traditional financial institutions perceive trust, regulatory alignment, and risk when engaging with fintech startups. It aims to understand the nuanced decision-making processes and organisational readiness for digital financial collaboration. Data will be collected from senior professionals through interviews and focus groups, allowing rich narratives to emerge around industry-specific concerns, innovation adoption, and strategic alignment.

Key References:

1. Ali, M., Raza, S. A., Khamis, B., Puah, C. H., & Amin, H. (2021). How perceived risk, benefit and trust determine user Fintech adoption: a new dimension for Islamic finance. Foresight, 23(4), 403-420.
2. Appiah, T., & Agblewornu, V. V. (2025). The interplay of perceived benefit, perceived risk, and trust in Fintech adoption: Insights from Sub-Saharan Africa. Heliyon.
3. Bakken, A. K. R., & Skjeltorp, M. (2022). Managing Asymmetric Alliances: An Exploration of the Interplay between Dependence and Trust in Fintech-Bank Partnerships (master’s thesis, NTNU).

Title 23

Unpacking the Digital Investment Experience: An SEM-Based Study on the Role of Fintech Affordances in Shaping Retail Investor Confidence and Continuity

Methodology

Quantitative - Structured questionnaire survey analysed using Structural Equation Modelling (SEM)

Description

This research investigates how specific affordances of fintech platforms - such as intuitive interface, algorithmic guidance, data visualisation, and real-time insights - affect retail investors' confidence, perceived investment autonomy, and continued usage. By developing and testing a structural model, the study provides empirical insights into how digital financial tools psychologically and behaviourally influence modern investors. Data will be collected from retail users of fintech investment platforms across urban financial hubs.

Key References:

1. Tan, G. K. S. (2022). The 'fintech revolution' is here! The disruptive impact of fintech on retail financial practices. Finance and Society, 8(2), 129-148.
2. Kaniadakis, A., & Foster, P. (2024). The role of fintech startups and big banks in shaping trust expectations from blockchain use in mainstream financial markets. Technological Forecasting and Social Change, 203, 123376.
3. Budiman, A. I., Arifin, F., Ahmed, A. M., Utami, D., Setiawan, B., & Gariba, M. I. (2023). Gender Differences in the Antecedents of Fintech P2p Financing with Moderating Effect of Taxation. Available at SSRN 5171397.

Title 24

From Disruption to Integration: A Mixed-Methods Study on Fintech Adoption in Corporate Treasury Management

Methodology

Sequential Explanatory Mixed Methods

Quantitative - questionnaire

Qualitative - semi-structured interviews

Description

This study first quantifies the impact of fintech tools on efficiency, compliance, and decision-making within corporate treasury departments using a questionnaire and SEM analysis. In the second phase, it complements the findings with insights from treasury managers through interviews, uncovering contextual and strategic drivers behind fintech adoption. This design allows for both statistical validation and depth of understanding, especially relevant for mid-to-senior professionals in finance departments.

Key References:

1. Abiola-Adams, O., Azubuike, C., Sule, A. K., & Okon, R. (2025). Treasury innovation: The role of technology in enhancing strategic treasury operations and financial performance. Gulf Journal of Advance Business Research, 3(1), 157-171.
2. Polak, P., Nelischer, C., Guo, H., & Robertson, D. C. (2020). "Intelligent" finance and treasury management: what we can expect. AI & Society, 35(3), 715-726.
3. Hong, J., Wang, N., & Zhou, T. (2025). The effects of FinTech adoption on bank loan spreads. Managerial Finance, 51(5), 749-764.