This paper aims at presenting a customer order scheduling environment in which the setup times are explicit and depend on the production sequence. The considered objective function is the total tardiness minimization. Since the variant under study is NP-hard, we propose a mixed-integer linear programming (MILP) model, an adaptation of the Order-Scheduling Modified Due-Date heuristic (OMDD) (referred to as Order-Scheduling Modified Due-Date Setup (OMMD-S)), an adaptation of the Framinan and Perez-Gonzalez heuristic (FP) (hereinafter referred to as Framinan and Perez-Gonzalez Setup (FP-S)), a matheuristic with Same Permutation in All Machines (SPAM), and the hybrid matheuristic SPAM-SJPO based on Job-Position Oscillation (JPO). The algorithms under comparison have been compared on an extensive benchmark of randomly generated test instances, considering two performance measures: Relative Deviation Index (RDI) and Success Rate (SR). For the small-size evaluated instances, the SPAM is the most efficient algorithm, presenting the better values of RDI and SR. For the large-size evaluated instances, the hybrid matheuristic SPAM-JPO and MILP model are the most efficient methods.

The export development of small and medium enterprises (SMEs) in Indonesia is still very low, resulting in their contribution to national exports being very small as well. Government bodies and relevant stakeholders are actively pursuing initiatives to enhance the export performance of SMEs. These efforts include improving the quality of human and social capital and promoting the integration of digital technology into SME operations. This examination evaluates the impact of human capital (HC), social capital (SC), and the utilization of digital technology on the export performance of SMEs. The investigation adopted a survey approach on all export-oriented SMEs listed on the Bank Indonesia website. Data was obtained through the distribution of questionnaires to 614 SMEs. Data analysis was conducted using PLS SEM. The research findings indicate that human capital, social capital, and digital technology have a positive and significant influence on the export performance of SMEs in Indonesia.

This paper aims to explore the influence of digital supply chain flexibility in five-star Hotels on smart quality systems together with its mediating effect through sustainable procurement practices within KSA. The methodology used is quantitative, based on data collected from a sample of five-star Hotels in KSA. Based on the above findings, this study argues about an integral part of DSCF (Digital Supply Chain Flexibility), SP and SQS for adopting theoretical framework. In this study, partial least squares-structural equation modelling (PLS-SEM) was used to validate the hypotheses. Digital supply chain flexibility has a significant positive relationship with sustainable procurement practices and smart quality systems in five-star Hotels. This means that actions such as fostering sustainable procurement practices could act on the ability of digital supply chain flexibility to boost smart quality systems, which play a role in enhancing operational efficiency and service quality. This paper contributes to the examination of various strategies for digital supply chains with sustainable procurement practices and creative quality systems within the hospitality sector; particularly focusing on KSA. Although the research findings are constrained to five-star Hotels from KSA they offer important directions for future research in different hospitality settings. These results provide practical information for hotels managers and policymakers on how digital supply chain flexibility, and sustainable procurement practices combined would contribute to the high-quality service provision as well as operational resilience of five-star Hotels. While these lessons have been drawn from the KSA market, they are also relevant to other hospitality markets with hospitality markets worldwide. This is the first study to examine Mediating Role of Sustainable Procurement and Digital Supply Chain Flexibility Impact on Smart Quality Systems Study in Five-Star Hospitals in KSA.

Hybrid algorithms are widely used today to increase the performance of existing algorithms. In this paper, a new hybrid algorithm called IMVOSA that is based on multi-verse optimizer (MVO) and simulated annealing (SA) is used. In this model, a new method called the black hole selection (BHS) is proposed, in which exploration and exploitation can be increased. In the BHS method, the acceptance probability feature of the SA algorithm is used to increase exploitation by searching for the best regions found by the MVO algorithm. The proposed IMVOSA algorithm has been tested on 50 benchmark functions. The performance of IMVOSA has been compared with other latest and well-known metaheuristic algorithms. The consequences show that IMVOSA produces highly successful and competitive results.

The study sought to determine the direct impact of accounting system quality (IQ, SQ, and SEQ) on AIS in large Yemeni industrial enterprises as well as the moderating effect of the US on the relationship of IQ, SQ, and SEQ with AIS in large Yemeni industrial companies. A survey instrument was developed to gather data from 287 employees of large industrial companies in Yemen. The structural equation model analysis was used to analyze data collected. The results revealed that SQ and SEQ affect AIS, while IQ does not affect AIS. Importantly, the US does not moderate the effect of IQ, SQ, and SEQ on AIS.

In this paper it is presented an improvement of the branch and bound algorithm for the permutation flow shop problem with blocking-in-process and setup times with the objective of minimizing the total flow time and tardiness, which is known to be NP-Hard when there are two or more machines involved. With that objective in mind, a new machine-based lower bound that exploits some structural properties of the problem. A database with 27 classes of problems, varying in number of jobs (n) and number of machines (m) was used to perform the computational experiments. Results show that the algorithm can deal with most of the problems with less than 20 jobs in less than one hour. Thus, the method proposed in this work can solve the scheduling of many applications in manufacturing environments with limited buffers and separated setup times.

The paper presents a fresh empirical approach for clarifying the impact of Jordan's most prevalent forms of ownership on the link between the “fair value (FV)” model share of assets and auditing costs. Using information gathered from 105 Jordanian financial listed companies spanning 2005 to 2018, ordinary least squares regression is applied in this paper. While financial institution ownership variables cause the opposite to be observed, family ownership decreases the link among the share of assets at FV and audit expenses. Family ownership results in decreased auditing costs paid only for “Level 1” assets; conversely, the extremely uncertain FV assets “Level 2 & 3” show the opposite. Financial institutional ownership demonstrates that auditing FV Level 1 leads to higher auditing costs. When relating FV Levels 2 and 3, the moderating effect of financial institutional ownership was significantly negative. No significant moderating effect of government ownership is confirmed. The inconclusive and limited empirical explanation of audit costs resulting from the FV model from a Western setting motivates our investigation. This study is considered as a unique study as it takes into account the most prevalent types of ownership in the Jordanian context in the FV studies reviewing auditees in Jordan. New evidence is generated by documenting audit characteristics of Jordan, a developing country, and its institutional environment and compliance with the FV model. The results are useful to regulators and policymakers in regulating the auditing profession and resolving FV audit-related conflicts and issues.

The rapid advancement of technology has substantially impacted numerous sectors, including the banking industry. It is now apparent that the banking industry is affected by the innovative role that the Internet of Things (IoT) plays, which affects a multitude of operations and services. This study uses a quantitative approach and PLS-SEM to investigate the widespread impact of Internet of Things (IoT) technology on the Excel Performance of Islamic Banks in the UAE. The study integrates the Resource-Based View (RBV), Islamic Banking Theories, and Fraud Triangle Theory to create a complete framework. The research's reliability is supported by a sample of 407 replies from 504 participants. The findings strongly support the hypotheses that IoT integration improves Islamic banking performance in the UAE, such as data analytics, customer service, automation systems, fraud detection capabilities, and asset-backed finance, while aligning with Sharia Principles and improving risk-sharing mechanisms. However, the influence of IoT on escalating fraudulent activities and hence negatively impacting performance was not proven. The study emphasizes the importance of IoT in improving operational efficiency and customer satisfaction in Islamic banks in the UAE.

An assignment problem (AP) usually deals with how a set of persons/tasks can be assigned to a set of tasks/persons on a one-to-one basis in an optimal manner. It has been observed that balancing among the persons and jobs in several real-world situations is very hard, thus such scenarios can be seen as unbalanced assignment models (UAP) being a lack of workforce. The solution techniques presented in the literature for solving UAP’s depend on the assumption to allocate some of the tasks to fictitious persons; those tasks assigned to dummy persons are ignored at the end. However, some situations in which it is inevitable to assign more tasks to a single person. This paper addresses a practical variant of UAP called k-cardinality unbalanced assignment problem (k-UAP), in which only of persons are asked to perform jobs and all the persons should perform at least one and at most jobs. The k-UAP aims to determine the optimal assignment between persons and jobs. To tackle this problem optimally, an enumerative Lexi-search algorithm (LSA) is proposed. A comparative study is carried out to measure the efficiency of the proposed algorithm. The computational results indicate that the suggested LSA is having the great capability of solving the smaller and moderate instances optimally.

This research aims to analyze the importance of Islamic Moderation (IM), which is the most prominent factor in the tourism attractiveness of the Kingdom of Saudi Arabia. This has made it an integrated and sustainable tourism destination throughout the year. The study applies a quantitative survey method and selects a probability sample of 470 questionnaires to collect data in the Jeddah region of the Kingdom of Saudi Arabia, using a probability sampling method. After employing purposive sampling to select the participants, a structural equation model (SEM) is employed to analyze the data. The proposed theoretical framework is utilized to examine the mediating role of Islamic Destination Image (IDI), in the correlation between Islamic Moderation (IM) and Destination Attractiveness (DA). Upon revisiting previous research, the study discovers several studies that concentrate on the concepts, mechanisms, and characteristics of moderation, the significance of disseminating moderate thought, addressing extremist thought, and its impact on the economy and international and regional relations. An examination of the total effect yields the conclusion that Islamic Moderation (IM) has a positive impact on Destination Attractiveness (DA); this effect is both positive and strong, both directly and indirectly. The Islamic Moderation (IM) has a significant, positive, and significant impact on the Islamic Destination Image (IDI).