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eScholar is the institutional repository for research conducted at UMT and maintains a large collection of theses, dissertations and projects produced by UMT graduates as part of their respective degree programs. It includes (but not limited to):
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Analyzing the impact of digital financial inclusion on women’s empowerment in Pakistan
(UMT,Lahore, 2026) Khush Bakht Sohail
This study examines that how digital financial inclusion can help in empowering women of Pakistan, which is a country where majority of the women still struggle to get basic financial services. Even though digital financial services have been growing immensely around the world, women living in Pakistan still face many barriers. The barriers range from mobility limitations to lower literacy rates. In addition to that there are deep-rooted cultural norms present in the Pakistani society that restrict financial independence of women. Utilizing the data from global Findex 2021, this research work basically applied principal component analysis (PCA) in order to create a combined form of indicator which can be used to represent digital financial inclusion and women empowerment. The results found through this research work revealed that there exist a positive and significant connection between digital financial inclusion and women empowerment. So, we can say that when women are given better access to the digital financial services, they will be able to play a significant role in the economy hence having a better say in their personal and household decisions. In addition to it the study also found that there exists a strong positive link between employment and women empowerment which implies that if more women get employed in the workforce, they will have a better status in the society. The study also found that women belonging to the higher income groups living in Pakistan show a negative relation with empowerment levels this can be linked with the conservative social environment present in the rich households of Pakistani society. These results obtained by the regression analysis underline the need of formulating and implementing targeted policies that can specifically increase the participation of women in digital financial services. The implementation of such policies can benefit the whole society as they can involve more women in the financial sector hence increasing the financial activities. ix The results obtained by this research work gives an insight to the financial institutes and policy makers.
Corporate psychopathy in pakistani organizations
(UMT,Lahore, 2026) Izah Khalid
Corporate psychopathy is a growing concern in organizational research, particularly regarding its impact on employee behavior, workplace culture, and organizational dysfunction. Most of the existing literature focuses on corporate psychopathy in Western contexts, this study examines the manifestation of corporate psychopathy in Pakistani organizations, where hierarchical structures, collectivist values, high power distance culture, and gendered workplace norms influence the expression and consequences of psychopathic leadership. This is a qualitative study that used constructivist grounded theory methodology to develop a theory about corporate psychopathy that explains how corporate psychopathy is embedded within organizational structures and perpetuated by cultural and gendered dynamics. The study explores five main interrelated themes: core behavioral traits of corporate psychopaths, changes in employee behavior under psychopathic leadership, organizational dysfunction as a self reinforcing system, gendered expressions of psychopathy, and cultural influences shaping psychopathy in Pakistani workplaces. For data collection first conducted a pilot study to identify the target respondents then data were collected through semi-structured face-to-face interviews with 17 employees from various organizations in Pakistan. Further analyzed collected data using open codes, theoretical codes, memo writing, and themes to identify emergent patterns and relationships. The research findings led to the generation of a new theory named the Sociocultural Psychopathy-Dysfunction Nexus (SPDN) Theory for understanding how corporate psychopathy, employee behavioral adaptation, organizational dysfunction, gendered dynamics, and cultural reinforcements interact to shape toxic work environments. In managerial implications, the study provides a road map for organizations to identify corporate psychopaths, manage them, or prevent or mitigate their effects on organizational outcomes. Future research should extend the findings through comparative cross-cultural studies and mixed-method approaches to further validate and refine the current research. Keywords: Corporate psychopath, cultural influence, organizational dysfunction, behavioral changes, gendered nature, constructivist grounded theory, toxic work environment
Dynamic connectedness among equity sectors
(UMT,Lahore, 2026) Muhammad Zahid Iqbal
Uncertainty remains a central concern for investors, firms, portfolio managers, analysts, regulators, and policymakers in making economic decisions, with systemic risk posing a major threat. The transmission of systemic risk depends on the interlinkages and interconnectedness among financial markets and sectors. With Pakistan being an emerging economy, this study examines sectoral interdependencies within the Pakistan Stock Exchange (PSX). Using prices, free-float shares, and corporate announcements data for all listed firms, sectoral equity indices are constructed based on the float-adjusted market capitalization approach. The study mainly aims to assess the dynamic connectedness among 16 equity sectors in the PSX during 2009–2023, focusing on both return and volatility spillovers under various conditions. Utilizing a Time-Varying Parameter VAR (TVP-VAR) framework, the study computes the Diebold–Yilmaz spillover indices in the time domain and extend the analysis to the frequency domain (short-run vs. long-run). It further incorporates quantile regression (QVAR) techniques to capture tail behavior (bearish vs. bullish regimes) and separate positive (“good”) and negative (“bad”) volatility spillovers to assess asymmetry. The study also emphasizes net, directional, and pairwise connectedness measures, providing a granular view of transmission channels among sectors. Considering the network structure of the sectors, this study sheds the light on the centrality of the sectoral network, too. Our findings reveal that PSX sectors are highly interdependent, with the Total Connectedness Index (TCI) averaging 68% for volatility and 76% for returns. Connectedness is time-varying, surging above 80% during major crises such as the 2008 09 global financial turmoil, the 2018–19 IMF program, and the COVID-19 shock. In tranquil periods, by contrast, TCI values drop to ~50%, indicating partial decoupling. Directional spillover analysis identifies key transmitter sectors notably Cement, Chemicals, Fertilizer, and Oil & Gas, that consistently propagate shocks to others. Conversely, sectors like Insurance, Food, and Automobile Assemblers are net receivers of spillovers. Frequency-domain results show a stark contrast between returns and volatility: short-term shocks (1–5 days) account for ~73% of return connectedness, whereas long term cycles (>5 days) contribute ~87% of volatility connectedness. This indicates return vii spillovers are transient, while volatility spillovers are persistent. Finally, we document a strong asymmetry in connectedness: negative shocks induce significantly higher spillovers than positive ones, especially during downturns. Asymmetric nature of volatility spillover is further highlighted through cross-Quantile contrasts and reflect systemic shock dominance in stress state. In addition, the heatmaps reinforce that sectoral roles in Pakistan’s equity market are highly dynamic and quantile-dependent. While cyclical sectors consistently emerge as transmitters, defensive and service-oriented sectors remain receivers, and a few sectors such as Banks and Food oscillate between the two depending on prevailing economic and political conditions. These results underscore the importance of accounting for time-variation, horizon, and shock sign in evaluating financial contagion. The evidence supports volatility as a more sensitive measure of systemic contagion than returns. In crises, volatility connectedness rises more sharply, reaches higher levels, and remains elevated for longer, whereas return spillovers spike quickly but fade relatively fast. The findings of this study carry important implications for investors, portfolio managers, regulators, and policymakers seeking better understanding of systemic risk and contagion in the PSX. The evidence that connectedness is dynamic, crisis-sensitive, and asymmetric highlights the need for active monitoring, adaptive risk management, and targeted regulatory oversight. The evidence of sectoral role shifts across regimes suggests that portfolio allocations should be state-contingent. The dominance of downside shocks in returns underscores the behavioral risk of loss-driven contagion. Investors should adopt protective strategies during periods of heightened uncertainty, such as stress testing portfolios against downside scenarios or using put options as insurance. The evidence that systemic centers differ between returns and volatilities suggests that a holistic policy approach is needed. Policymakers should therefore coordinate financial-sector regulations with industrial and energy policies to address both short-term price stability and long-term systemic resilience. Keywords: systemic risk, contagion, dynamic connectedness, TVP-VAR, sectoral connectedness, frequency domain, time domain, QVAR, asymmetric connectedness, emerging market, volatilities.
The Use of AI in Airline Operations to Enhance Passenger Satisfaction with the Mediating Role of Hedonic Motivation
(umt.lahore, 2026) Syed Zainulabdin
Airlines are lacking in the adaptability and incorporation of AI in the current era where AI is necessary in every aspect of life. All the emerging fields use AI as a crucial tool to enhance adaptability and user friendliness in every area concerned with consumer satisfaction and reliability. Airlines are adopting AI, but it is important for AI to be implemented in an effective manner to make the most out of it. The world is adapting to AI in all areas of life at a very fast pace, and it is necessary for the airlines to adopt AI in all disciplines related to customers. Hedonic motivation plays a very important role in the adaptability of AI in the field of aviation. As experiences of the people shape their behaviors, hedonic motivation highly affects the behavior of the passenger’s using airlines, so they must adopt AI as it can affect their performance and can save time and can be cost saving in many areas like predictive maintenance and cost cutting. The use of AI can be beneficial for the airlines. By using AI, passengers’ comfort will be enhanced, and it can highly affect passenger satisfaction, and it can also greatly enhance the passenger loyalty towards the airline, hence increasing the reputation, reliability and revenues generated by the airline, providing long term benefits.
Forecasting climate change and financial market of Pakistan using time series analysis
(UMT,Lahore, 2026) Muhammad Idrees
Pakistan is facing climate and environmental issues consisting Heatwave, Floods, AQI and Earthquake from last three decades badly. Many people are affecting from this change and are distressed to leave their primitive places. Due to climate change all type of business are also in trouble. On the other hand, Pakistan’s economy is facing crises from last many years. On the basis of all these burning issues motivating for research to improve these areas. This research is comprising on two parts. First part about climate change of Pakistan and the rest of part is about the Financial Market of Pakistan. In first part initially I will be predicting temperature of five different cities of Pakistan using machine learning model named Sequence Informer Mixer (SIM) on the dataset 1st January 1941 to 31st December 2023. The results of this proposed prediction model will be compared with existing models like ARIMA or Informer model. Second phase of this research is consisting on Stock Exchange closing price. In this section Pakistan Stock Exchange (PSX) for KSE-100 index daily business dataset will be used from February 22, 2008, to February 23, 2021. Long Short Term Memory (LSTM) with Attention model will be used for forecasting the stock exchange closing prices. Comparison of proposed model with different deep learning models will be done by some evaluation matrices i-e Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE) and Root Mean Square Error (RMSE).