Trust Model Based On Islamic Business Ethics and Social Network Analysis

Buyers and sellers in e-commerce market such as e-auction form a virtual community. They use the feedback system to rate each other following a completed transaction and these ratings are used to build their reputation in the virtual community.  Existing reputation systems can often be easily manipulated by forming cohesive group in giving fake user feedbacks to increase their respective reputation. This practice is a clear violation of Islamic business ethics. In addition, there is currently no real-time support for reputation system and this causes users to be misinformed on the reputation of a seller. To improve the reputation system this study developed a trust framework based on business Islamic ethics. In this paper, a trust model which evaluates conformance to nine Islamic business ethical codes is proposed to calculate users’ initial trust value based on their ethical behavior. The trust model proposed the Islamic business ethics algorithm which calculates the user compliance to Islamic business ethics (IBE) score based on trading partner’s feedbacks. Because of feedback frauds can still occur, this study introduces a cohesive group algorithm to track users who collaborate to give false feedbacks. The cohesive group algorithm applied k-core algorithms which is capable of determining the strength of the relationship of every user in the cohesive group. The cohesive group algorithm also proposed a cohesive score to determine the feedback reliability of every user’s transaction based on the user’s k-core and the highest k-core. In the group user reputation (trust score) is measured by considering the feedback reliability status for all transactions. A reputation prototype system for e-auction was developed as the test bed to validate the trust model through simulation of the set of initial experiments, showing the feasibility and benefit of the model

Efficient Simulation of Structural Faults for the Reliability Evaluation at System-Level

In recent technology nodes, reliability is considered a part of the standard design ¿ow at all levels of embedded system design. While techniques that use only low-level models at gate- and register transfer-level offer high accuracy, they are too inefficient to consider the overall application of the embedded system. Multi-level models with high abstraction are essential to efficiently evaluate the impact of physical defects on the system. This paper provides a methodology that leverages state-of-the-art techniques for efficient fault simulation of structural faults together with transaction-level modeling. This way it is possible to accurately evaluate the impact of the faults on the entire hardware/software system. A case study of a system consisting of hardware and software for image compression and data encryption is presented and the method is compared to a standard gate/RT mixed-level approac

Climate Change Reporting: A Resource Based Perspective

Kajian ini dilakukan untuk mengkaji tahap serta faktor yang mengalakkan laporan pemanasan global di antara syarikat-syarikat yang tersenarai di Bursa Malaysia. This study investigates the extent of climate change disclosure among Malaysian public listed companies

Risk Mitigation Of Outsourcing Manufacturing Process: A Study On The Semiconductor Manufacturing Organizations In Malaysia

Penggunaan perkhidmatan pihak ketiga daripada proses pembuatan semikonduktor menjadi sebahagian daripada strategi korporat sebuah organisasi yang didorong oleh kelebihan kos dan fleksibiliti dalam ketidakpastian. Outsourcing of semiconductor manufacturing process is becoming integral part of the corporate strategy of an organization which is driven by cost advantage and flexibility during uncertainty

System Reliability Evaluation Using Concurrent Multi-Level Simulation of Structural Faults

This paper provides a methodology that leverages state-of-the-art techniques for efficient fault simulation of structural faults together with transaction level modeling. This way it is possible to accurately evaluate the impact of the faults on the entire hardware/software syste

Predictive Modeling for Fair and Efficient Transaction Inclusion in Proof-of-Work Blockchain Systems

This dissertation investigates the strategic integration of Proof-of-Work(PoW)-based blockchains and ML models to improve transaction inclusion, and consequently molding transaction fees, for clients using cryptocurrencies such as Bitcoin. The research begins with an in-depth exploration of the Bitcoin fee market, focusing on the interdependence between users and miners, and the emergence of a fee market in PoW-based blockchains. Our observations are used to formalize a transaction inclusion pattern. To support our research, we developed the Blockchain Analytics System (BAS) to acquire, store, and pre-process a local dataset of the Bitcoin blockchain. BAS employs various methods for data acquisition, including web scraping, web browser APIs, and direct access to the blockchain using Bitcoin Core software. We utilize time-series data analysis as a tool for predicting future trends, and transactions are sampled on a monthly basis with a fixed interval, incorporating a notion of relative time represented by block-creation epochs. We create a comprehensive model for transaction inclusion in a PoW-based blockchain system, with a focus on factors of revenue and fairness. Revenue serves as an incentive for miners to participate in the network and validate transactions, while fairness ensures equal opportunity for all users to have their transactions included upon paying an adequate fee value. The ML architecture used for prediction consists of three critical stages: the ingestion engine, the pre-processing stage, and the ML model. The ingestion engine processes and transforms raw data obtained from the blockchain, while the pre-processing phase transforms the data further into a suitable form for analysis, including feature extraction and additional data processing to generate a complete dataset. Our ML model showcases its effectiveness in predicting transaction inclusion, with an accuracy of more than 90%. Such a model enables users to save at least 10% on transaction fees while maintaining a likelihood of inclusion above 80%. Furthermore, adopting such model based on fairness and revenue, demonstrates that miners' average loss is never higher than 1.3%. Our research proves the efficacy of a formal transaction inclusion model and ML prototype in predicting transaction inclusion. The insights gained from our study shed light on the underlying mechanisms governing miners' decisions, improving the overall user experience, and enhancing the trust and reliability of cryptocurrencies. Consequently, this enables Bitcoin users to better select suitable fees and predict transaction inclusion with notable precision, contributing to the continued growth and adoption of cryptocurrencies

DEVELOPING AND VALIDATING A QUALITY ASSESSMENT SCALE FOR WEB PORTALS

The Web portals business model has spread rapidly over the last few years. Despite this, there have been very few scholarly findings about which services and characteristics make a Web site a portal and which dimensions determine the customers’ evaluation of the portal’s quality. Taking the example of financial portals, the authors develop a theoretical framework of the Web portal quality construct by determining the number and nature of corresponding dimensions, which are: security and trust, basic services quality, cross-buying services quality, added values, transaction support and relationship quality. To measure the six portal quality dimensions, multi item measurement scales are developed and validated.Construct Validation, Customer Retention, E-Banking, E- Loyalty, Service Quality, Web Portals

Online Travel Service Quality: The Importance of Pre-Transaction Services

The Internet revolution has led to significant changes in the way travel agencies interact with customers. Travel websites are used to different degrees, and for a variety of combinations of pre-transaction, transaction and post-transaction services. A better understanding of how customers interact with online services will help providers improve service quality to levels that satisfy or even delight customers, and thus create loyalty. This article provides a comprehensive review of the literature on online service quality, applies the theory to online travel offerings, and reports on an empirical study of quality perceptions of pre-transaction services provided on three travel websites. Effects on customer perceived quality were measured for process and outcome dimensions of online services. Implications for the design of online travel services and suggestions for further research are formulated.Economics ;