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This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

The purpose of this paper is to examine the automotive product recall risk in terms of social sustainability performance and to evaluate the role of buyer‒supplier relationships in improving social sustainability during product recall crises.

A multi-methodology approach is used to empirically analyse the interrelationship between the proposed constructs and enablers of the buyer‒supplier relationship. Structural equation modelling and interpretive structural modelling are followed to analyse the data gathered thorough a questionnaire survey of 204 executives and interviews with 15 managers from the automotive industry.

The results of the study provide evidence regarding the impact of the responsible buyer‒supplier relationship on customer recall concerns and the social sustainability performance of supply chains (SCs). This study also leads to the development of a conceptual model, providing a relationship between the three key concepts used in this study.

Following social sustainability principles, this study addresses the importance of developing strong, responsible relational ties with suppliers to reduce vehicle recalls or successfully recover from a product recall crisis.

This study contributes to the literature by providing theoretical and empirical insights for developing socially responsible SCs and confirming the role of the buyer‒supplier governance mechanism during product recalls in the context of the automotive industry.

The purpose of this chapter is to reflect the impact of mergers and acquisitions processes on performance of Islamic banking industry in the United Kingdom through studying within.

The present research uses explanatory approach in order to examine the research problems, methodology used in the research is quantitative methods through calculating the long-term share prices performance of the UK Islamic banks’ sample. First, the researchers use the control Islamic bank in the event-time approach. The researchers calculate annual abnormal returns using the buy-and-hold abnormal return (BHAR) method over a period of five years, counting from the quarter of a year when the transaction is said to be effective.

The research findings found that there are significant differences in the Islamic mergers and acquisitions post-long-run performance of the UK Islamic banks to the control the crises that face the United Kingdom from 2007 to 2010. However, the acquiring Islamic bank in high-tech industries had a negative effect on their long-term performance.

The present research has been applied for the Islamic banking industry in the United Kingdom after the Western Europe industry from 2007 to 2010.

The main implementations of the present research is valuing UK banks carried out the Islamic mergers and acquisitions of a broad range of management disciplines encompassing the financial, strategic, behavioral, operational, and cross-cultural aspects of this challenging and high-risk activity.

The Islamic mergers and acquisitions have placed a significant amount of value added on the motivation of large banks for engaging in banking mergers and acquisitions’ transactions.

The purpose of this paper is to determine if companies in the modular and offsite construction (MOC) industry are agile or not and its level of application for agility principles, which allows for quick responses to the increasingly dynamic nature of industry environments.

This paper proposes an agility assessment framework for MOC that uses 48 assessment attributes organized into four categories: metrics, drivers, enablers and capabilities. A questionnaire approach was used to disseminate the framework globally in 19 countries and synthesize its relevance to the MOC industry. The questionnaire had 55 complete responses, majority of respondents work in managerial positions for MOC manufacturing facilities and onsite general contractors.

It was found that the lowest metric score for adapting to change was for cost since controlling cost would be difficult for any changes required after the design freeze stage. The top agility driver was found to be the need to respond to the wide variety of customer expectations, while the lowest driver was the existence of competing priorities. The top agility enabler was vendor partnership, which can be related to current postpandemic supply chain disruptions. Regarding technological capabilities, Europe and the USA acquired better scores compared to Asia, Latin America and Africa.

This study contributes to the MOC body of knowledge by creating an agility assessment tool for MOC firms to analyze their agile approach and environment, identifying the preliminary importance of agility assessment attributes and determining significant agile differences between the main MOC industry groups.

Construction projects are complex projects taking place in dynamic environments, which necessitates accounting for different uncertainties during the planning stage. There is a significant lack of management tools for repetitive projects accounting for uncertainties in the construction environment. The purpose of this paper is to present an algorithm for the optimized scheduling of repetitive construction projects under uncertainty.

Fuzzy set theory is utilized to model uncertainties associated with various input parameters. The developed algorithm has two main components: optimization component and buffering component. The optimization component presents a dynamic programming approach that processes fuzzy numbers. The buffering component converts the optimized fuzzy schedule into a deterministic schedule and inserts time buffers to protect the schedule against anticipated delays. Agreement Index (AI) is used to capture the user’s desired level of confidence in the produced schedule while sizing buffers. The algorithm is capable of optimizing for cost or time objectives. An example project drawn from literature is analysed to demonstrate the capabilities of the developed algorithm and to allow comparison of results to those previously generated.

Testing the algorithm revealed several findings. Fuzzy numbers can be utilized to capture uncertainty in various inputs without the need for historical data. The modified algorithm is capable of optimizing schedules, for different objectives, under uncertainty. Finally AI can be used to capture users’ desired confidence in the final schedule.

Project planners can utilize this algorithm to optimize repetitive projects schedules, while modelling uncertainty in different input parameters, without the need for relevant historical data.

The purpose of this paper is to present a newly developed multi-objective optimization method for the time, cost and work interruptions for repetitive scheduling while considering uncertainties associated with different input parameters.

The design of the developed method is based on integrating six modules: uncertainty and defuzzification module using fuzzy set theory, schedule calculations module using the integration of linear scheduling method (LSM) and critical chain project management (CCPM), cost calculations module that considers direct and indirect costs, delay penalty, and work interruptions cost, multi-objective optimization module using Evolver © 7.5.2 as a genetic algorithm (GA) software, module for identifying multiple critical sequences and schedule buffers, and reporting module.

For duration optimization that utilizes fuzzy inputs without interruptions or adding buffers, duration and cost generated by the developed method are found to be 90 and 99 percent of those reported in the literature, respectively. For cost optimization that utilizes fuzzy inputs without interruptions, project duration generated by the developed method is found to be 93 percent of that reported in the literature after adding buffers. The developed method accelerates the generation of optimum schedules.

Unlike methods reported in the literature, the proposed method is the first multi-objective optimization method that integrates LSM and the CCPM. This method considers uncertainties of productivity rates, quantities and availability of resources while utilizing multi-objective GA function to minimize project duration, cost and work interruptions simultaneously. Schedule buffers are assigned whether optimized schedule allows for interruptions or not. This method considers delay and work interruption penalties, and bonus payments.

The purpose of this paper is to investigate the effect of a focus loan strategy on Islamic banks’ (IB) performance in three areas: sectoral, geographic and the type of Islamic instrument. This paper specifically addresses two questions. First, should IBs focus or diversify their loan portfolios? Second, how does focus in lending affect IBs’ returns and risk?

The panel generalized linear squared method was used for regressions throughout the paper. Data used in the analysis were extracted from IBs’ publicly available regulatory reports in the Gulf Cooperation Council countries. The sample is an unbalanced panel that includes financial data on 26 banks during the period 2010–2018.

Focusing on Islamic instruments and economic sectors would harm IBs’ profitability while reducing their risks. Geographic focus increased the profitability of IBs, but it also increased their default risk. The focus in Islamic instruments was beneficial when risk is low to moderate, but when the risk of an IB increased, it was better to diversify across Islamic instruments. Focus in geographical areas, on the other hand, had a non-linear U-shaped relationship with return, which means that when IBs’ risk is high, focusing their loans in one geographic area enhances their returns.

This paper fills the existing gap in Islamic banking literature regarding the focus/diversification dilemma. It is the first attempt to study the effect of focus in three areas (sectoral, geographic and instrument used) on the return and risk of IBs.