iRepository (Institute of Business Administration)
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Users Influence the Users: How Powerful are the User-Generated Content in Shaping the Other User Purchase Behavior
No full textWith the extension of the internet from computers to mobile, the flow of information has evolved around the globe. Whether it is the choice of a restaurant or buying a new car, people flick it on their phones to make a decision. As a result, the trend of reviews has become a vital source of information for internet users that also affects the sales of various products and consumer picks, as is evident from the studies
Exploring the Concept of Quasi Equity
No full textInvestigate how industry professionals interpret and apply the concept of virtual entities and quasi-equity in practice. And propose a framework for harmonizing regulatory and accounting standards in a way that preserves both financial integrity and Shariah principles
IBA’s Centre of Excellence in Journalism marks ‘a decade of excellence’ in evolving Pakistan’s media landscape
No full textThe Centre for Excellence in Journalism (CEJ-IBA) marked its 10th anniversary with “A Decade of Excellence” at IBA City Campus. The event brought together journalists, academics, diplomats, and students to reflect on CEJ’s contributions to ethical and innovative journalism. Dr. S. Akbar Zaidi stressed the need to reassess journalism in the AI era, while US Consul General Scott Urbom praised CEJ’s role in press freedom and journalist empowerment. Hamid Mir and Azhar Abbas highlighted challenges of censorship and harassment faced by the media. Shahzaib Jillani acknowledged CEJ’s decade-long journey of training thousands of journalists. Panel discussions on AI in journalism and fact-checking via iVerify further underlined CEJ’s evolving role. Since its inception in 2015, CEJ has pioneered initiatives that strengthened transparency, skills, and democratic dialogue in Pakistan’s media landscape
Forecasting Turkish Lira Via Combination of ANN and Econometrics Approaches -An Emerging Market Case Study
No full textThis study aims to forecast the Turkish Lira to US Dollar exchange rate from January 2011 to December 2024, withholding the 2024 data for forecasting. The study utilizes four econometric models (ARIMA, Naïve, exponential smoothing, and NARDL) along with one Artificial Neural Network model (ANN). It heeds the recommendation of Poon and Granger (2003) to combine these models and assess their predictive accuracy using two methods: equal-weights and variance-covariance. The study finds that the combined model outperforms individual models in predicting the exchange rate. The fusion of ANN and NARDL emerges as particularly effective in forecasting the Turkish Lira\u27s performance. This highlights the significance of macro-economic fundamentals and asymmetric lag values in enhancing forecasting efficiency, surpassing other individual and combined models. Notably, the combined ANN-NARDL model achieves the lowest MAPE value, at 0.014, underscoring its robustness. The research outcomes are of practical importance to various stakeholders, including policymakers, economists, academics, traders, and more. They offer valuable insights for making informed investment decisions and managing exposure to exchange rate risk. The research helps to comprehend fluctuations in exchange rates and the utility of combining different models for more accurate predictions
People Strategy for PwC Pakistan
No full textThis study explores the A.F. Ferguson & Co. (PwC Pakistan) people strategy redesign, as required by its long-standing talent retention, skills acquisition and workforce preparedness issues in the professional services industry. The research is placed against a background of accelerating digital change, changing employee demands, and the increased competition over talented employees. PwC Pakistan experiences a high turnover within core service lines, dependency on the traditional HR systems, and a high level of skills shortages, which includes data analytics, leadership advancement, and cybersecurity.
The mixed-method research design was used and three components were assessed: (1) Competitor strategy benchmarking, comparing the human capital practices of PwC Pakistan with the best global and local firms; (2) Exit data analysis, determining the attrition data by department, role, gender; and (3) Skills gap analysis, analysis of the workforce capabilities in line with strategic needs. Results show that PwC Pakistan is falling behind competitors in using agile HR tools and contemporary talent management systems. The attrition is the greatest at the Assistant Manager level, and the shortage of skills is threatening future competitiveness.
The paper will end with evidence-based recommendations to update HR systems, enhance employee engagement, and people strategy consistency with benchmarks in the global market. These insights form part of the discussion of strategic human capital management in emerging markets and gives a road map on how an organization can be transformed
A Modular Approach to Cluster-based Ensemble Learning: Optimizing Subspace Design and Classifier Aggregation
No full textIn ensemble learning, a promising strategy for improving base learners is to train them on different subspaces (subsets) of the dataset. However, generating meaningful and diverse subspaces that lead to strong individual classifiers remains a significant challenge, particularly in the presence of class imbalance within subspaces. Poorly constructed subspaces can produce weak learners that ultimately degrade ensemble performance. This thesis proposes a modular approach to address this. It starts with employing a clustering technique to generate candidate subspaces that capture the intrinsic structure of the data. Next, recognizing that not all clusters are equally informative, it incorporates an evolutionary optimization process to filter out low-quality subspaces and retain only the most promising ones. Furthermore, a second optimization step is applied to explore whether further improvements in ensemble performance can be achieved by selecting an optimal subset of base classifiers from a diverse pool and aggregating complementary models more effectively.
Experiments were conducted on a variety of small and large benchmark datasets. The results show that excluding highly imbalanced or homogenous subspaces from the set of candidate subspaces improves ensemble performance across most datasets. Furthermore, removing Support Vector Machine (SVM)-based weak learners from the classifier pool enhanced computational efficiency without compromising accuracy.
For smaller datasets, Particle Swarm Optimization (PSO) boosted performance when applied to both cluster filtering and classifier selections. In contrast, for larger datasets, Binary PSO for subspace optimization and SHAP-based methods for classifier selection yielded superior results. Notably, for large datasets, the second optimization step—focused on base-classifier selection—did not offer further performance gains; optimal subspace selection alone was sufficient to match or surpass state-of-the-art ensemble methods such as Random Forest and XGBoost.
These findings highlight that while optimization techniques for subspace generation and classifier aggregation are effective, their efficacy varies with dataset size and complexity, and strategies effective on smaller datasets may not generalize well to larger ones
A Meta-analysis of Supply Chain Resilience: Developments and Future Research Directions
No full textThis meta-analysis examines the precursors of supply chain resilience (SCR) by consolidating results from 107 empirical studies. Seventeen SC antecedents/ capabilities, such as agility, adaptability, and technological capabilities, were examined for their influence on SCR, with all hypotheses validated, demonstrating a positive correlation. Technological capability appeared as the most commonly analyzed factor. Moderator studies were performed according to industry type (manufacturing versus others) and national development classification (developed versus developing/underdeveloped). Findings indicate a growing academic interest in emerging nations, including India, Jordan, Indonesia, and Nepal, reflecting a change in research emphasis. The research enhances SCR theory by integrating actual data, emphasizing key factors, and providing insights for the execution of resilience strategies in various circumstances, therefore bolstering more resilient and adaptable global supply networks
Structure of Gold Finance Products in the Financial Industry: Trends, Features, & Market Insights
No full textIt is common for households in Pakistan to have a portion of their total savings in form of gold ornaments. Gold is considered amongst the most stable commodities and hence, a secure investment as a medium-to-long-term investment, in addition to being readily acceptable in exchange for cash. Due to these reasons, selling off gold ornaments to meet financial needs is often considered the last resort. There is also a significant degree of cultural and societal pressure on families to avoid selling gold. This makes the concept of diluting gold investments a taboo for a large part of Pakistani society. These social customs built a substantial need for financing cash flows that would ensure retention of investments in gold and at the same time provide liquidity to customers. While adding to the benefits, it also creates an opportunity for financial institutions & banks to offer a workable financing option to customers and build a secure assets portfolio that is promising for healthy returns to the investors. JS Bank Gold Finance has been designed to capitalize on the above opportunity by providing financing against gold/ gold ornaments to individuals and businesses for meeting investment or business needs. JS Gold Finance product enables the bank to tap the untapped market for building a Gold Finance base. It also adds to the product menu of the bank and provides branches with opportunities to further expand their customer base to cross-sell other Gold Finance products suitable to customer needs. To capitalize these opportunities, JS Bank aims to revamp and expand its gold finance product offerings. The bank aims to introduce a diversity of gold-backed financing products, offering flexible tenure, competitive interest rates, and a range of financing limits to appeal to various market segments. Additionally, JS Bank seeks to enhance customer experience by streamlining and digitizing the application and approval processes, ensuring faster loan disbursements, and offering more flexible collateral choices. These enhancements will enable the bank to appeal to new customer markets, strengthen customer loyalty, and improve profitability, positioning JS Bank as a leader in the gold finance market
Bias in AI vs. human product recommendations and its impact on consumer trust, attitude toward the product, and purchase intention
No full textPurpose – In this study, we will focus on examining the impact of biased versus unbiased product recommendations originating from two different sources (human expert and AI) on how consumers’ trust is shaped leading towards purchase intentions and attitude toward the product. The study also explores how persuasion knowledge moderates these relationships. For the research, we will focus on Millennial and Generation Z consumers purchasing a functional, high- involvement product: the NextGen Pro smartphone.
Design/methodology/approach – We conducted two separate studies, each with a total of 200 participants, where a between-subjects experimental designs was employed to test out the hypothesis. We compared the impact of biased and unbiased recommendations from human expert and AI algorithms on consumer trust, purchase intention, and attitude towards products. The focus was on a functional product category i.e. a fictitious smartphone brand NextGen Pro.
Findings – Across the two studies, findings demonstrate that consumer trust plays a crucial role in influencing how consumers form attitude towards product and their intention to purchase a product in response to the recommendations. In Study 1, biased recommendations (particularly from AI) led to reduced consumer trust, while unbiased recommendations enhanced trust regardless of source. Study 2 revealed that persuasion knowledge moderated these effects, with highly aware consumers showing greater skepticism toward biased messages, whether they be from AI or human sources.
Originality/value – The study is among of the first to explore how bias in recommendations influences consumer trust, attitude formation towards a certain product and purchase intention across a functional product, specifically among Millennials and Gen Z cohorts. It also identifies persuasion knowledge as a key moderator, demonstrating how consumers’ perception of persuasive intent shapes the impact of biased recommendations on decision-making
Automated End-to-End Newsletter Generator for Streaming Content
No full textThis project presents a fully automated, end-to-end solution for generating OTT (Over-the-Top) streaming newsletters. It is designed specifically for organizations like a leading VPN provider that aim to highlight newly available streaming content to their global user base without the labor-intensive manual processes traditionally involved. The system integrates web scraping, AIpowered copywriting, image generation, and HTML formatting, providing a complete newsletter generation pipeline accessible via a graphical interface. Compared to existing tools like Mailchimp, Phrasee, or Canva, our tool stands out due to its vertical integration and VPNspecific deeplink capabilities. The solution significantly reduces production time, ensures consistency, and offers scalability for multilingual, country-specific campaigns