FEMIB 2024 Abstracts


Area 1 - Accounting and Finance

Full Papers
Paper Nr: 17
Title:

Applications of Artificial Intelligence in Sustainability Assessment and Risk Management in European Banking

Authors:

Dominic Strube, Christian Daase and Jennifer Schietzel-Kalkbrenner

Abstract: This article addresses the evolving dynamics of sustainability risks in the banking sector, with a particular focus on the integration of artificial intelligence (AI) in risk assessment and management. The impact of environmental, social, and governance (ESG) factors on creditworthiness evaluation is examined and highlights the complexities and challenges that financial institutions face in adapting their risk management frameworks to accommodate these sustainability risks. The paper underscores the difficulties banks face in effectively incorporating ESG considerations, primarily due to the absence of standardized methodologies and the intricate interplay between ESG components and banking risk elements. In this context, the potential of AI applications is critically assessed, especially those utilizing large datasets, to identify complex patterns and correlations that often elude human analysts. This investigation includes both the opportunities AI presents in enhancing the precision of risk assessments and the associated challenges, including issues related to the opacity and control of complex, self-learning AI models, as well as regulatory and privacy concerns. Finally, the article presents a schematic approach through which banks can actively integrate sustainability risks into their risk management strategies, emphasizing the need for ongoing research and development in this crucial area.
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Paper Nr: 21
Title:

Safeguarding Downside Risk in Portfolio Insurance: Navigating Swiss Stock Market Regimes with Options, Trading Signals, and Financial Products

Authors:

Sylvestre Blanc, Emmanuel Fragnière, Francesc Naya and Nils Tuchschmid

Abstract: Our research uses options to safeguard equity portfolios from downside risk. Despite the cost challenges of passive put protection, we explore leveraging diverse market signals, backward and forward-looking ones, to enhance portfolio risk-return balance while maintaining acceptable safeguards. These signals aid in selecting underlying assets for option positions, aiming to achieve protection while minimizing put premium expenditure. Certain signals, like "trend" or "low volatility”, either empirical or implied, demonstrate added value, although their effectiveness depends on market conditions (or regimes). We also evaluate whether a set of trading rules can enhance the efficiency of such strategies. Our study highlights the importance of financial product safety, akin to safety measures for industrial products. By doing so, we underline the importance of portfolio insurance in finance. Further developments will aim at implementing a trading system that offers greater adaptability to different market regimes, for example high volatility phases, and under real market conditions.
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Paper Nr: 27
Title:

Internal Audit: Friend or Foe of Innovation in an Organization: Case of Czech Banking Sector

Authors:

Vladimír Petrík

Abstract: Internal audit should provide objective assurance services regarding the fulfilment of the bank’s objectives and its management and administration, based, among other things, on risk assessment. The aim is to identify, describe and analyze the current state of application of innovation audit performed by the internal audit department in banks operating in the Czech Republic. Methods of qualitative research, analysis of bank documents and interviews with internal audit managers are used. The result of the research is the identification and description of the current state of tasks and the role of internal audit in relation to innovation management in banks. Banks in innovation management have been found to face various barriers based on legacy of unconnected information systems, low innovation appetite (non-perception of competitive threats), unexposed innovation processes and low decision-making flexibility. It was found that banks do not identify innovation risk as part of their risk assessment and do not apply specific control processes to it. These facts have practical implications following the recommendation to systematize the innovation process in banks, to include innovation risk in the bank’s risk assessment and to use the possibilities of the bank’s internal audit department to eliminate this risk and assess related processes.
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Short Papers
Paper Nr: 34
Title:

Stock Market Forecasting Using Machine Learning Models Through Volatility-Driven Trading Strategies

Authors:

Ivan Letteri

Abstract: The purpose of our research was to explore volatility-based trading strategies in financial markets to leverage market dynamics for capital gain. We sought to introduce a strategy that integrated statistical analysis with machine learning to predict stock market trends. Our method involved using the k-means++ clustering algorithm to examine the mean volatility of the nine largest stocks in both the NYSE and Nasdaq markets. The clusters formed the basis for understanding relationships among stocks based on their volatility patterns. We further subjected the mid-volatility clustered dataset to the Granger Causality Test, which helped identify stocks with strong predictive connections. These stocks were crucial in formulating our trading strategy, serving as trend indicators for decisions on target stock trades. Our empirical approach included thorough backtesting and performance analysis. Our findings demonstrated the effectiveness of our method in exploiting profitable trading opportunities. This was achieved through predictive insights derived from volatility clusters and Granger causality relationships among stocks. In conclusion, our research contributed to the field of volatility-based trading strategies by offering a methodology that combined a statistical approach with machine learning. This enhanced the predictability of stock market trends.
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Area 2 - Emerging Areas in FEMIB

Short Papers
Paper Nr: 70
Title:

Generative AI Risk Management in Digital Economy

Authors:

Victor Chang, Leigh Draper and Simin Yu

Abstract: In Healthcare Procurement, This Study Delves into the Integration of Generative AI, Focusing on Its Application within HealthTrust Europe’s marketing and communication frameworks. By analyzing the interplay between innovative AI-driven content personalization and the associated ethical, security, and operational risks, the research offers a nuanced perspective on leveraging technology for enhanced efficiency and engagement. The study employs qualitative research methods to assess risks and propose mitigation strategies, advocating for best practices in AI governance and risk management. It emphasizes the importance of maintaining network security, data integrity, and ethical standards in deploying AI solutions.
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Area 3 - IT Business

Full Papers
Paper Nr: 83
Title:

ChatGPT in Higher Education: A Risk Management Approach to Academic Integrity, Critical Thinking, and Workforce Readiness

Authors:

Victor Chang, Yasmin Ansari and Mitra Arami

Abstract: This paper critically explores the role of ChatGPT in higher education, with a particular emphasis on preserving the academic integrity of student assessments via a risk management paradigm. A literature analysis was conducted to understand existing strategies for addressing academic misconduct and the necessity of equipping students with skills suitable for an AI-driven workforce. The paper’s unique contribution lies in its use of a risk management approach to enable educators to identify potential risks, devise mitigation strategies, and ultimately apply a proposed conceptual framework in educational environments. The paper concludes with identifying practical limitations and proposed future research areas, focusing on the uncertainties that emerge from the evolution of AI LLMs and the integration of comprehensive AI tools that pose new risks and opportunities.
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Short Papers
Paper Nr: 25
Title:

Applying Text Analytics Methodology to Analyze Project Reports

Authors:

Irina Arhipova, Liga Paura, Nikolajs Bumanis, Gatis Vitols, Vladimirs Salajevs, Aldis Erglis, Gundars Berzins and Evija Ansonska

Abstract: The goal of this article is to develop a support methodology for Driving Urban Transition (DUT) partnership to ensure that the knowledge gathered from ERA-NET Urban Accessibility and Connectivity (EN-UAC, 2023) projects, to repeatedly identify the requirements of programme entities and define specific topics for future calls. Fifteen projects under the Horizon 2020 ERA-NET initiative have been analysed to detect similarity between projects, uniqueness of the projects, project compliance with DUT and SRIA, and gap between projects and DUT, SRIA methodology. A particular focus in the analysis was on the project “Individual Mobility Budgets as a Foundation for Social and Ethical Carbon Reduction” (MyFairShare). Text mining methods were used for documents analysis. The similarity between the documents detected by the cluster algorithm and they were compared using words, as a result, the documents were combined into three clusters: “Strategy implementation and network infrastructure”; “Transport accessibility and policy” and “Urban city mobility”. The identification of unique terms shown the terms energy, ecosystem and climate are unique for DUT&SRIA and are not found in 15 EN-UAC project applications and the next specific topics for future calls can be within the subject of energy, climate and ecosystem.
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Area 4 - Management

Full Papers
Paper Nr: 6
Title:

What Do Customers Demand? Inclusive and Sustainable Entrepreneurial Marketing

Authors:

João M. S. Carvalho

Abstract: There is a lack of research that links start-ups' entrepreneurial marketing with the increased customers' demand for inclusivity and sustainability. This paper proposes and substantiates a new conceptual model – Inclusive and Sustainable Entrepreneurial Marketing. This model includes the context and resources as the base for value creation; objectives and entrepreneurial will for developing a business model, followed by planned and unplanned actions, and inclusivity and societal sustainability as the significant impacts. The empirical substantiation of the model followed a design-science approach and was done through 55 interviews with entrepreneurs. Most entrepreneurs do not consider societal sustainability and inclusivity as primary objectives. However, these goals present an increased prevalence among the customers' current requirements. This paper contributes to the theoretical and empirical development of entrepreneurial marketing studies.
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Paper Nr: 38
Title:

The Recruiting Process as an Attractiveness Factor: How Do Companies Manage to Position Themselves Competitively as Employers?

Authors:

Jennifer Schietzel-Kalkbrenner, Niklas Petelkau, Dominic Strube and Christian Daase

Abstract: The question of how companies manage to position themselves as attractive employers is one of the most important strategic challenges for the future of all companies in times of demographic change and the associated and constantly growing employment gap on the labor market. As various studies show how important the right design of recruiting processes can be for this, the article is dedicated to the question of how a conscious design of recruiting can support companies in combating the shortage of skilled employees, especially in relation to Generation Z. The aim is to provide science-based recommendations to companies that consider the current zeitgeist and are intended to make companies question their own approach to recruiting. The theoretical foundations were developed as part of systematic literature research. More in-depth and up-to-date findings were obtained through two expert interviews and an online survey of Generation Z. The results show that companies need to do more today than they did a few years ago. A successful recruiting process should build on a strong employer branding foundation and should be taken to a more personal level. This includes knowing the expectations of candidates on the job market and authentically presenting yourself to the outside world as an attractive employer. In addition to honest insights into the company through its own employees as brand ambassadors and the implementation of the latest trends, such as mobile applications, the onboarding process is particularly important. This begins directly with the signing of the contract and is ideally characterized by the consideration of professional and social integration. This is becoming increasingly important, especially for younger employees in today’s world.
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Paper Nr: 58
Title:

Developing a Framework for City Brand-Image Promotion via Social Media Communication

Authors:

Shuying You, Kyriakos Christofi, Elena Tsappi and George Papageorgiou

Abstract: This paper introduces a framework for utilizing social media in the development of city branding and image enhancement. Amidst the evolving digital landscape, the study emphasizes the transformative potential of social media in reinforcing societal, cultural, and economic attributes vital to city branding. It combines advanced Information and Communication Technology (ICT) with traditional marketing tactics to propose a groundbreaking approach to advertising and brand promotion. The paper highlights the application of innovative methods like social listening, netnography, and machine learning to analyze intricate patterns in consumer communication and behavior. These techniques aim to provide deeper insights into consumer dynamics, crucial for fostering sustainable urban development and enhancing city branding strategies. This work contributes significantly to the understanding of digital tools in city marketing, highlighting their potential in shaping the future of urban development.
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Paper Nr: 69
Title:

Leveraging Multimodal Large Language Models and Natural Language Processing Techniques for Comprehensive ESG Risk Score Prediction

Authors:

Abhiram Nandiraju and Siddha Kanthi

Abstract: Companies are subject to stringent expectations in terms of social responsibility, particularly in managing risks associated with their environmental, social, and governance (ESG) practices. These practices are evaluated using ESG risk scores. Traditionally, ESG risk scores are generated by firms like Sustainalytics and MSCI, which primarily focus on larger corporations. Consequently, entities investing in smaller companies, such as venture capital firms, private equity firms, and individual investors, face a challenging and resource-intensive process for initial risk assessment. However, our research has uncovered a novel approach through the application of machine learning techniques and the use of multimodal large language models based on publicly released company reports. This approach enables the prediction of ESG risk scores with an accuracy of 68.09%, offering a viable tool for preliminary analysis. Significantly, this research introduces a pioneering framework that utilizes a new architecture for analyzing ESG practices, transforming the traditional assessment process for both large and small companies alike. Our research shows high accuracy in predicting risk assessments and simplifies the evaluation process. Nonetheless, there is potential for enhancing this accuracy through further refinement of the models, improvements in data extraction, and continued exploration of additional modeling techniques.
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Short Papers
Paper Nr: 37
Title:

The Impacts of Environmental Context on Technology Adoption and Their Invariance Analysis in Chinese Supply Chains

Authors:

Zengwen Yan and Kaining Ge

Abstract: Industry 4.0 technologies are increasingly used by corporations worldwide, but their successful adoption remains problematic. In particular, the manufacturing and logistics industries in China have achieved more promising outputs, supported by the adoption of emerging technologies in their supply chains. It is important to research whether environmental context provides a conducive atmosphere for the corporate adoption of these technologies. The study employs structural equation modelling (SEM) with data collected through 1,441 questionnaires from the manufacturing and related industries across mainland China. This paper focuses on and discusses how environmental context affects technology adoption (TA) and post-performance based on the technology–organisation–environment (TOE) framework. The study finds that in China, the regulatory environment (RE) does not directly affect technology adoption and performance (TAP); rather, the business innovation environment (BIE), greatly affected by the RE, influences TAP. This study enriches the content on environmental context, examines the robustness and generalizability of the results.
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Paper Nr: 44
Title:

Modeling Organizational Culture, Transformational Leadership, Motivation, Job Satisfaction: Muhammadiyah Aisyiyah College’s Nursing Lecturer

Authors:

Miciko and Dewi Nusraningrum

Abstract: Research on the effect of organizational culture and transformational leadership on the job satisfaction of nursing lecturers mediated by motivation has never been conducted at Muhammadiyah Aisyiyah College (PTMA). The study's objective is to analyze the influence of organizational culture and transformational leadership on job satisfaction through motivation as mediation. 230 nursing faculty lecturers in Central Java, Indonesia became respondents to this study. SEM analysis is used to test hypotheses with the help of the SmartPLS analysis tool. The findings in this research specify that organizational culture and motivation have no direct consequence on job satisfaction. Organizational culture, besides transformational leadership, directly impacts motivation, and transformational leadership to job satisfaction. However, motivation does not have an intermediating role in the connection between organizational culture and transformational leadership to job satisfaction. The results of this study revealed that PTMA's organizational culture has become part of the work culture for lecturers at the nurse faculty.
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Paper Nr: 72
Title:

Research on Incentive Mechanism of Enterprise Personnel's Self-Determined Salary

Authors:

Lingyu Ji

Abstract: Salary mechanism is the core issue of enterprise distribution system, and it is also important content of enterprise economic goal realization and management decision. The salary incentive mechanism of the traditional enterprise personnel comes completely from the unified work performance evaluation system, which is a kind of incentive behaviour of the management decision-makers. The research holds that the incentive mechanism of compensation which is conducive to the economic development and management optimization of enterprises should be the common incentive behaviour of enterprise decision-makers and employees. Based on self-determination theory (SDT), this paper proposes an incentive mechanism for self-determined salary, establishes a mathematical model of this salary mechanism, and points out the quantitative characteristics of the relationship between self-determined target salary and enterprise plan target salary. According to the three psychological needs of SDT, this paper describes the autonomy, competence and relationship of enterprise personnel salary, and on this basis, puts forward the basic hypothesis of running the autonomous salary incentive mechanism.
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