Search results

Islamic banking is an increasingly important factor in the UK financial environment. With Islamic banks entering the industry in significant numbers – and competing directly with the incumbent “conventional” ones – the question of selection criteria of the banks' customers is of obvious interest. The purpose of this paper is to study the decision‐making process of a sample of UK customers and the factors that may influence them.

The paper uses a sample of 156 UK questionnaire respondents, comprising Muslim and non‐Muslim bank customers alike. The methodological approach is partly borrowed from Masood et al. with the chosen questions aimed at finding out what drives the selection process of bank customers.

The paper's major findings show that, irrespective of the demographic features and the religion of the respondents, the criterion “low services charges” is the top customers' criteria. The Islamic nature of the bank is, however, placed second, pointing to the importance of religious orientation.

The major limitation of the paper relates to the size of the sample of respondents. The findings of the paper are likely to be of interest to UK banks determining how best to attract customers in the new era. Future research may usefully focus on an international comparison of bank selection criteria by employing an index of religiosity.

The paper is of particular value because it focuses on the choice of banking in the context of the recent significant growth in the Islamic banking industry in the UK.

The protection of industrial heritage emerged as a major concern when those buildings and installations representative of the industry, became at risk. North Africa, considered the geographical gateway to European countries, experienced enormous industrial activity during the French colonial era. Industrial buildings such as the flour mills, were built during this era of colonial rule. Today, a lack of legislation concerning industrial heritage has left this type of buildings with no protection, leading this paper to a preservation process. The aim of this paper is to locate and identify the flour mills of the 19th and 20th centuries in Algeria.

This research consists of cross-referencing data from archived documents against the geographical location.

The results obtained are the first step in the process of preservation. The success of this research can be summarized as follows: identification of 88.46% of the flour mills in Algeria by means of the inventory data collected, and their location, with the use of a crisp logic, the remaining 9.62% with the use of fuzzy logic by the attribution of a “fuzzy radius” with a total localization and identification of 98.08%.

The use of both crisp (Boolean) and fuzzy logic as part of the geographical localization method.

This paper is motivated by the heated debates preceding the introduction of additional regulatory requirements of Basel III on capital conservation buffer (CCB) and regulatory leverage (RLEV) in banks of emerging markets. The paper aims to examine which policy ratio can improve bank efficiency (BE), in one of the most resilient banking settings in the Middle East and North Africa (MENA) region.

The analysis is performed on a sample of 13 banks for the period 2010–2018 in Egypt and proceeds in two steps. In the first step, the data envelopment analysis model is used to derive bank-specific efficiency scores. In the second step, BE scores are regressed on the two types of regulatory capital and a set of control variables.

The paper is motivated by regulatory debates on the viability of RLEV and CCB in enhancing BE. The results show that higher RLEV and CCB are associated with a reduction in BE and that RLEV is highly associated with BE compared to CCB. Hence, results are relevant to policymakers in designing measures for improving BE in emerging markets.

The findings contribute to a small but growing stream of research on capital adequacy in emerging markets. This study provides results on the viability of risk-based vs non-risk-based capital requirements. The findings are also relevant to bank regulators in similar emerging market settings in their efforts to introduce and phase in minimum leverage requirements according to Basel III.

Simulation has attracted increasing attention in lean production research as a response to address the complexities of the production environment and difficulties of dealing with changes within a system. Considerable growth of using simulation to facilitate lean acceptance and implementation has been observed across different projects and sectors. However, a thorough review of the development and use of simulation in lean production research is limited.

This study aims to address this gap by reviewing 311 journal papers published in the past two decades on this specific research area and identify the state-of-the-art development and propose future research directions.

The review shows that current studies related to simulation in lean production research can be categorised into two major research streams, namely, simulation assisted lean facilitation and evaluation, and simulation-based lean education and training. Under the first research stream, a total of 19 application areas have been identified which applied both lean and simulation in their studies. The evolution of the simulation techniques used in these studies has been analysed as well. Meanwhile, four types of simulation games have been identified in the stream of simulation-based lean education and training and the impact and applicability of the different simulation and games have been discussed. A framework for engaging lean and simulation is suggested based on the review of the existing studies. The analysis in both streams also highlights the importance of stakeholder engagement and the utilisation of information technologies for future studies.

The findings of this study are expected to provide useful references for the future development and application of simulation in lean production research.

This paper conducted a broad and extensive review of simulation integrated lean production research. An in-depth examination of the retrieved papers was conducted through a structured and quantitative analysis to understand the current body of knowledge.

Although Islamic banks offer superior financial services than other interest-based conventional banks, they could not expand their share and dominate the markets in several Islamic countries. This problem could be attributed to some causes not addressed. The current study proposes Islamic financial literacy as an important factor that could help aggress this problem. Due to a wide variety of Islamic financial services and the lack of understanding of these services, the banks' small business customers are indifferent between Islamic and interested-based conventional services to finance their business.

This study uses the exploratory technique of multiple correspondence analysis to detect any potential role of Islamic financial literacy in customers' preference for Islamic banks over conventional ones. The potential effect was tested with other essential factors, such as the customers' age, gender, and educational level. This analysis was conducted on a data set from 2061 banks' small businesses customers using the mall-intercept survey method.

The study shows a low level of Islamic financial literacy among Yemeni banks' small business owners' customers. Furthermore, despite integrating some critical factors that could influence the actual bank selection process among Yemini banks' customers, the authors found a decisive potential role of Islamic financial literacy as one of the key determinants of bank selection preferences.

This is the first paper to explore the potential role of Islamic financial literacy on the actual selection between Islamic Banks and their counterparts: the conventional banks in Yemen. The research results could build a more comprehensive theoretical model on Islamic banks' customer behavior.

The purpose of this article is to analyze the existing studies on the application of artificial intelligence (AI) in lean construction management (LCM). Further, this study offers a classification scheme that specifies different categories of AI tools, as applied to the field of LCM to support various principles of LCM.

This research adopts the systematic literature review (SLR) process, which consists of five consecutive steps: planning, searching, screening, extraction and synthesis and reporting. As a supplement to SLR, a bibliometric analysis is performed to examine the quantity and citation impact of the reviewed papers.

In this paper, seven key areas related to the principles of LCM for which AI tools have been used are identified. The findings of this research clarify how AI can assist in bolstering the practice of LCM. Further, this article presents directions for the future evolution of AI tools in LCM based on the current emerging trends.

This paper advances the LCM systems by offering a lens through which construction managers can better understand key concepts in the linkage of AI to LCM.

This research offers a new classification scheme that allows researchers to properly recall, identify and group various applications of AI categories in the construction industry based on various principles of LCM. In addition, this study provides a source of references for researchers in the LCM discipline, which advances knowledge and facilitates theory development in the field.

Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.

This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.

Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.

This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

In Islamic finance (IF), the safety-first rule of investing (hifdh al mal) is held to be of utmost importance. In view of the instability in the global financial markets, the IF portfolio manager (mudharib) is committed, according to Sharia, to make use of advanced models and reliable tools. This paper seeks to address these issues.

In this paper, the limitations of the standard models used in the IF industry are reviewed. Then, a framework was set forth for a reliable modeling of the IF markets, especially in extreme events and highly volatile periods. Based on the empirical evidence, the framework offers an improved tool to ameliorate the evaluation of Islamic stock market risk exposure and to reduce the costs of Islamic risk management.

Based on the empirical evidence, the framework offers an improved tool to ameliorate the evaluation of Islamic stock market risk exposure and to reduce the costs of Islamic risk management.

In IF, the portfolio manager – mudharib – according to Sharia, should ensure the adequacy of the mathematical and statistical tools used to model and control portfolio risk. This task became more complicated because of the increase in risk, as measured via market volatility, during the financial crisis that began in the summer of 2007. Sharia condemns the portfolio manager who demonstrates negligence and may hold him accountable for losses for failing to select the proper analytical tools. As Sharia guidelines hold the safety-first principle of investing rule (hifdh al mal) to be of utmost importance, the portfolio manager should avoid speculative investments and strategies that would lead to significant losses during periods of high market volatility.