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ÖgeDynamic market modeling with heterogeneous agents: Applications in diverse markets(Graduate School, 2023-10-18)Financial markets, with a staggering market capitalization of 94 trillion US dollars in 2020, hold utmost importance in finance and economics. To comprehend their dynamics and price behavior, numerous models have been proposed, such as the Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT). However, these traditional approaches often fall short in capturing extreme market situations and the complexities of crashing market crises. In response to this limitation, agent-based modeling (ABM) has emerged as a paradigm shift, offering more realistic assumptions and allowing for emergent behavior due to interactions among heterogeneous agents. This study utilizes ABM to investigate financial market microstructure and stock market behavior through the creation of two distinct market models. The first model, an artificial stock market, aims to replicate real market price features and explore the impact of various trading strategies. Incorporating agents with realistic trading strategies, the model reveals insights into the competition among different strategies, highlighting the dominance of computationally powerful agents. Moreover, the presence of noise traders is observed to contribute to market liquidity and movement. Overall, the ABM approach successfully reproduces stylized facts observed in real markets and provides a bottom-up understanding of market dynamics. The second model is a hybrid limit order book simulator that combines historic NASDAQ messages and actual market orders to create a more realistic trading mechanism. By examining the impact of order size, market volatility, market capitalization, and stock trading volume, the simulator demonstrates a close resemblance between simulated and actual market prices. Notably, larger order sizes lead to greater price impact, while higher volatility stocks exhibit more significant price impacts. Additionally, market capitalization and stock trading volume are shown to influence bid-ask spreads. Although the study has some limitations, such as the need for further exploration of agent heterogeneity in fundamental markets, it contributes valuable insights into financial market microstructure dynamics. The developed limit order book simulator offers a platform for testing stock market hypotheses and evaluating trading strategies, paving the way for future research in financial stock markets and optimal portfolio selection. The agent-based modeling approach and its ability to capture complex market interactions provide promising avenues for understanding financial markets at a granular level and making informed decisions in the world of finance.
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ÖgeExamining the role of employee social intrapreneurial behaviour and job satisfaction as mediators of employee commitment(Graduate School, 2023-12-25)The primary objective of this research is to investigate and establish a comprehensive understanding of the correlation between an innovative organizational culture, employee intrapreneurial behavior, authentic leadership, employee job satisfaction, and employee job commitment in the manufacturing sector of Kuwait, which is a developed economy. To identify any gaps in current research, literature reviews examine the fundamental concepts and their associated domains by dissecting their definitions, dimensions, and significance. The analysis of pertinent research revealed major gaps in knowledge. Consequently, a novel framework has been established. The framework investigates the phenomenon of employee social intrapreneurial behavior by integrating many dimensions, including idea generation, idea promotion, and idea realization. Additionally, employee social intrapreneurial behavior can be defined as: "Is a behavior displayed by personnel employed within an organization, regardless of the type of organization. Employees feel appreciated and a part of the organization's success. They generate societal ideas for new procedures, services, or products." This investigation makes use of a methodology grounded in Pragmatism and the ontological tenets of Objectivism. The study employs a deductive methodology, which involves testing a theoretical framework and investigating the relationship between independent and dependent variables. The study issues were addressed using a quantitative methodology. The survey was employed as the principal methodology for data collection. The research population consists of employees at various tiers of hierarchy within the manufacturing sector in Kuwait. There were a total of 233 participants, with small, medium, and large businesses represented in the sample. The participants were selected using a stratified sampling procedure. The collection of quantitative data was carried out through the utilization of a self-administered and electronic Arabic questionnaire. Subsequently, the acquired quantitative data was subjected to analysis using the Statistical Package for Social Sciences (SPSS) version 28. An further significant contribution that this work makes is the creation of a oneof- a-kind instrument. The questionnaire that was used in this investigation was developed through a procedure that consisted of three stages. The first thing that needed to be done was to investigate and enhance the components of verified surveys. Individuals who were in agreement with the goals of the study were invited to participate in the study in their initial appearance. Following the completion of the second phase, the elements that were in agreement with the objectives of the research were amended. For the purpose of enhancing the questionnaire and making it easier to collect the necessary data, the researcher produced additional items connected to the dimension of "employee social intrapreneurial behaviour" during the third phase of the study process. The ultimate questionnaire is comprised of a collection of dimensions and elements that have not been utilised in the past for the purpose of evaluating the social and intrapreneurial behaviour of employees. This study contributes significantly by presenting a novel conceptual framework that incorporates many factors to examine the mediating role of employee social intrapreneurial conduct and job satisfaction in the association between innovative organizational culture and employee commitment. This study represents the initial empirical investigation, based on the researcher's current understanding, into the correlation between these subjects. Moreover, this study included quantitative data to assess the effectiveness of the model, with a particular focus on the manufacturing sector in Kuwait. The findings of the study revealed a significant and positive impact of employee social intrapreneurial behavior, with job satisfaction serving as a mediating variable. The study addresses the existing gaps in knowledge and introduces an innovative contribution.The inclusion of this information serves to enhance and enhance the existing corpus of knowledge and practical applications. This study seeks to clarify the intricacies of employee social intrapreneurial behaviour and its consequential importance for owners and managerial staff. In organisations, the existence of intrapreneurial personnel has a vital role in promoting innovation, which subsequently enhances the firms' capacity to achieve a competitive advantage (Guerrero and Peña-Legazkue, 2013). The Generation Z cohort is playing a crucial role in promoting intrapreneurial behaviours in the workplace. Managers must prioritise employee satisfaction and provide a pleasant work environment tailored to their individual needs. The individuals of Generation Z will make up the workforce of the future, and it is essential for companies to learn about the peculiarities of this generation in order to adapt. Those who are more likely to move around in their jobs are people who are determined to go up the corporate ladder no matter what it takes. They can switch between multiple workplaces as needed, much like a monkey might hop from tree to tree. For this reason, individuals need not worry about securing a regular pay check or a permanent office space because they do not get too attached to any one company. Those who are endowed with these traits are less likely to doubt themselves and more likely to take the lead. People that lean towards pragmatism are more likely to respect personal space and do well in less formal, indirect environments. These people are breaking away from traditional office work culture and building a new social structure as they do their jobs online from anywhere in the world. On top of that, they are quite active in creating their own online communities. This group's members are more likely to be intelligent than wise, and they seem at home in the technological world. Despite their limited skill in expressing themselves verbally and emotionally, these individuals are capable of achieving their dreams, no matter how great the cost. The people in issue will not act alone to implement their creative ideas, but rather they will collaborate for the common good. Hence, it is crucial to familiarise oneself with their requirements and ensure their satisfaction. This research offers empirical evidence that is consistent with the theoretical frameworks of the Self-Determination Theory, the Social Exchange Theory, and the Planned Behaviour Theory, which are discussed in the third chapter of this thesis. This research constructed a three-part sequential framework to describe the process by which an innovative organisational culture is established and its subsequent impact on employee behaviour, particularly in terms of intrapreneurship. The framework was developed in order to explain the relationship between the two. A shared innovative mentality that can be internalised as a habitual practice over a period of time can be developed through active participation in the process of developing such a mindset. The theoretical framework of the research has the potential to improve managers' comprehension of the significance of intrapreneurship and the ways in which organisations can assist its development at both the individual and organisational levels. Future research could take a direct approach to investigate the impact of factors and their impact on the correlation between an innovative organizational culture and employee engagement/employee performance. Future studies could use a mixed research methodology using semi-structured interviews with management executives. personnel of companies. Future research could investigate the impact of Coaching leadership style on employees' intrapreneurship behavior in the specific context of Kuwait.
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ÖgeEffects of organizational and individual dynamic capabilities on business model innovation and sme performance(Graduate School, 2024-05-30)Technological developments, limited resource supply, and market volatility challenge especially small and medium business managements, particularly in developing countries. They're trying to upgrade how they work to stay competitive in local and global markets. They are continuously in search of new business models. Research on how dynamic capabilities affect business model innovation and firm performance yields mixed results. Teece introduced dynamic capabilities framework with three dimensions as sensing, seizing, and reconfiguration. However, it doesn't fully explain how these capabilities work and to whom they belong to at the firm. The current dissertation addresses these gaps through two studies. In the first one, the Dynamic Capabilities framework has been used to understand how business model innovation happens in both new and established entrepreneurial firms through semi-structured interviews with owner-managers actively involved in business model innovation decision-making. The study focused on individual and organizational layers of dynamic capabilities and gathered data in the science parks of Istanbul. Through content analysis of nine semi-structured interviews, several key insights emerge: (1) Entrepreneurs come ahead of all other stakeholders in undertaking the main responsibility of each dynamic capability sud-dimension. (2) Organizational layer capabilities come into action in case the organization's frontline people and technology people increase in count. (3) Entrepreneurial team's complementary capabilities are encountered in each sample case. Moreover, organizational layer capabilities manifest prominently when business model innovation activities necessitate broad-based involvement, such as customer engagement and technological experimentation. These mechanisms exhibit variances contingent upon firm size and structural arrangements. Furthermore, entrepreneurs assert control through established routines and organizational culture, particularly evident in smaller enterprises. As these firms evolve, they develop and institutionalize procedures to transform their dynamic capabilities into organizational ones, to sustain innovation. The 10 DC sub-dimensions suggested in this study are grouped under three dimensions of Teece's DC framework. Sensing skills and mechanism: (1) reaching to data, (2) filtering customer data, (3) decomposing and reframing, (4) idea generation and visualization of BM, (5) conceptual validation of visualized BM. Seizing skills and mechanisms: (6) physical validation of targeted BM, (7) decision making, (8) external integrative capabilities (co-creation of solution). Reconfiguring skills and mechanisms: (9) aligning organization to new BM, (10) aligning process to new BM. Those skills and mechanisms are clues for entrepreneurs to develop BMI. Practitioners are recommended to consider their primary responsibility for BMIs processes independent of the size of the firms, to build entrepreneurial teams with partners having the complementary skill set and concentrate on the employees' selection, as well as their adaptation to the firm routines. Additionally, the study complements Teece's Dynamic Capabilities framework on business model innovation extending it into fulfillment layer. The second empirical study investigated the effects of dynamic capabilities on the quality and financial aspects of firm performance in SMEs and the mediating role of BMI in these relations in a developing country context. The following four questions are addressed: • What are the nature and fulfillment layers of DCs employed in technology-based firms engaging in BMI? • How organizational DCs can be categorized according to organizational layers in terms of owner/managerial and employees' levels in SMEs? • Which DCs are more effective on SME performance in terms of quality and financial aspects? • What is the role of BMI in the DCs-performance relations? The sample of the study consists of SMEs involved in BMI processes, and participants were chosen as business owners and top-level managers due to their managerial power over business models and their understanding of the bigger picture in this field. The analysis is conducted on the SMART PLS analysis tool. Partial Least Squares Structural Equation Modeling (PLS-SEM) is compliant in examining small sample sizes, complex models with numerous constructs and indicators. It also offers an advantage in analyzing complex second-order latent constructs and examining reflective and formative structures in the same model. As the result of the study, business model innovation has emerged as a formative second-order construct having three sub-dimensions (value creation, value proposal and value capture). Constructs for owner-manager and employee layer dynamic capabilities also emerged as formative second-order constructs. Employee layer dynamic capabilities construct is also formed by three sub-dimensions such as employee layer sensing, seizing and reconfiguring capabilities. The construct of owner-manager layer dynamic capabilities, on the other hand, is formed by two sub-dimensions. Seizing and reconfiguring dimensions have been merged into one as the result of discriminant analysis. Those employee layer dynamic capabilities and owner-manager layer dynamic capabilities constructs supported their effect on performance factors in the mediation of business model innovation. Business model innovation has a high association with all performance types. Owners' dynamic capabilities have a positive association with financial performance, while their total effect is not significant on quality performance. Conversely, employees' dynamic capabilities show a positive association with quality performance, but their total effect is not significant on financial performance. The findings underscore the paramount significance of business model innovation in determining firm performance. It is revealed that owners and top managers possessing dynamic capabilities apply a positive influence on the financial performance of the firm, even in instances where they do not introduce new business models. Conversely, notwithstanding the presence of dynamic capabilities, they are unable to drive the firm's quality performance without either the engagement of BMI or the active involvement of employees. The dissertation opens a new horizon for future research extending the framework of Dynamic Capabilities to differentiate among organizational layers. As a result, the findings from both qualitative and quantitative studies conducted within the scope of the thesis underscore the significant importance of business model innovation in determining firm performance. It is revealed that firm owners and top-level managers with dynamic capabilities exert a positive influence on the financial performance of the firm even when new business models are not involved. However, it cannot be expected for them to improve the quality performance of the firm without innovating in their business models or active involvement of employees, even if they possess dynamic capabilities.
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ÖgeMarketing campaign management using machine learning techniques: An uplift modeling approach(Graduate School, 2024-06-28)In order to engage customers and increase sales, businesses in today's dynamic business environment devote a large amount of resources to a variety of marketing methods. Businesses utilize a variety of strategies to attract customers' attention and encourage them to make a purchase. However even with a wide range of marketing strategies and channels, a fundamental issue still remains: how can businesses effectively evaluate how their marketing campaigns influence consumer behavior? By focusing on the significance of uplift modeling in determining the true impact of marketing initiatives, this research directly addresses this issue. By identifying the incremental impact of marketing initiatives, uplift modeling provides a more sophisticated approach than common predictive analytics which only forecasts customer behavior. The purpose of this research is to explore the limitations of conventional predictive analytics in marketing, investigate the application of prescriptive analytics specifically uplift modeling and develop a framework for implementing uplift modeling in business-to-business (B2B) marketing instances by examining real-world data from the Turkish telecom industry. In this study, three uplift modeling methodologies (two model approach, class variable transformation and modeling uplift directly) performed on a real-world B2B marketing campaign dataset and shown that the marketing campaign can be optimized by predicting the incremental impact more precisely with uplift models than the conventional predictive models. The results revealed how uplift modeling, which enables for the targeting of customers whose behavior is most likely to be positively influenced by marketing efforts, is helpful in improving resource allocation. Out of all the uplift models, the model that used the class variable transformation approach was able to capture 46% of uplift while targeting only the half of the campaign audience. This finding confirms the earlier research in the uplift modeling literature and shows that uplift models are successful in forecasting the truly responsive customers for a direct marketing campaign. It has been demonstrated that conventional response models are inadequate to distinguish which customers are positively impacted by a marketing treatment whereas uplift models successfully identify which customers will make a purchase due to being influenced by the marketing treatment. It is also shown that in a direct marketing campaign, focusing on a larger target audience may not always yield the greatest or most effective outcomes. Instead, different uplift modeling strategies combined with machine learning algorithms can yield higher uplifts.This study makes significant contribution as being the first to introduce uplift modeling in Turkish literature and being one of the few studies to apply uplift modeling in B2B context in the world-wide academic literature that predominantly focused on researches in B2C. Further, it provides valuable managerial insights for marketers to gain deeper customer insights and foster stronger relationships with customers by leveraging uplift modeling.
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ÖgePortfolio optimization with wavelet analysis and neural fuzzy networks(Graduate School, 2022-12-27)Recently, Robo-advisors have come to the fore in the investment management business both in the world and in Turkey. Robo-advisors can be defined as financial algorithms that generate trading signals and optimize financial assets with machine learning. Robo-advisors, who perform asset management by analyzing data without human intervention, have the potential to provide better returns than traditional portfolio management. Assets under management in the Robo-Advisors segment are projected to reach US$3.2 tn in 2027. According to latest surveys, 63% of Americans are open to using a robo-advisor to manage their investments, with millennials being the most open (75%). Financial asset forecasts are of great importance in portfolio management and the performance of forecasts plays a key role in the success of portfolio managers. This situation has led to an increased interest in models. While most of the models were based on statistical techniques in the past, new modeling techniques have been used recently. The most notable of these are artificial intelligence models such as artificial neural networks and fuzzy logic. In this study, the daily values of Borsa İstanbul 30 Index, Gold and USD / TL exchange rate are tried to be estimated by using Wavelet Analysis and Neural Fuzzy Networks method. Buy / Sell signals are generated from the estimates created by the model. The performance of the portfolio was analyzed assuming that the underlying asset was invested on the days when the model predicted an increase and the investment was not made on the days when it predicted a decrease, and it was evaluated in overnight risk-free interest when not invested. In addition, the model has been tested in artificial indices and stock market indices of other developing countries. While the model showed a successful performance in Russia and China, it remained below the index in South Korea stock exchange. Then, the optimal portfolio was created by using wavelet fuzzy network model estimates and the performance of the portfolio was examined. With the return and standard deviation values produced by the model, optimization was made to obtain the largest Sharpe ratio, and the performance of the portfolio of three assets was compared with the assets' own performances and risk-free interest by re-balancing at different time intervals. The results show that the model created by using wavelet analysis and fuzzy neural networks together gives successful results in predicting the future values of financial assets and further research has potential. Wavelet Neural Network method, in which Artificial Neural Networks are used together with wavelet transform, can be used to predict the future price of assets traded in financial markets such as BIST30, Gold and USD/TL exchange rate. In the future, estimates can be made using the model in this study for financial assets other than gold, USD/TRL and BIST-30. The performance of the model in different market conditions can be tested by repeating the study at different time intervals. In the study, wavelet transform is done using Haar wavelet, financial series can be decomposed into its components by using different wavelets.