The study explored the influence of the main dimensions of accounting information (AI) relevance and reliability on supply chain performance (supply chain exchange information, supply chain collaboration, supply chain integration) at Noon e-commerce companies in Saudi Arabia. The researcher followed the descriptive analytical approach to describe the study variables based on previous studies and explore the study gap. The study adopted a questionnaire, of which 170 were collected. The data was analyzed using partial least squares (PLS) through structural equation modeling (SEM). The results indicated a positive effect of the relevance and reliability of AI on the dimensions of SC performance (SC exchange information, SC collaboration, SC integration), there is a positive effect of the reliability of AI on the dimensions of supply chain performance (SC exchange information, SC integration) and a negative effect of the reliability of AI on the SC collaboration parties. These results clarified the value and benefit of accounting information in improving supply chain performance.

The study aimed to discover the effect of the main characteristics of accounting information (AI) in achieving sustainable development (SD) in Al-Kharj Governorate by studying the characteristics of (AI) represented in relevance and reliability with independent variables and studying the dimensions of sustainable development (economic, social and environmental). The theoretical and applied study will use the descriptive and analytical approach. Data were collected through a questionnaire distributed to the study sample represented by business organizations in Al-Kharj Governorate. The data is analyzed using structural equation modeling with partial least squares. The expected results of the study are: The relevance of (AI) positively affects the economic dimension of (SD) in Al-Kharj Governorate, the relevance of (AI) positively affects the social dimension of (SD) in Al-Kharj Governorate, the relevance of (AI) positively affects the environmental dimension of (SD) in Al-Kharj Governorate, the reliability of (AI) positively affects the economic dimension of (SD) in Al-Kharj Governorate, the reliability of (AI) no effects on the social dimension of (SD) in Al-Kharj Governorate, the reliability of (AI) no affects the environmental dimension of (SD) in Al-Kharj Governorate.

The study aimed to identify the impact of Accounting Information Systems (AIS) reliability on enhancing the requirements of planning process at Jordanian Commercial Banks, and in order to achieve the objectives of the study the researcher implemented the descriptive analytical approach by reviewing the literature related to AIS and planning process requirements. Researcher also designed a questionnaire to target the executive managers, financial managers, and departments' heads at the (13) Jordanian commercial banks, where (145) questionnaires were distributed, recovered (122), and (118) of those were found to be valid for analysis. The study used the SPSS and the Multiple Regression test to reach the objectives of the study and test its hypotheses. The results indicate a major impact of AIS reliability on fostering the planning process requirements at the Jordanian commercial banks, and recommended the need of managements to focus on AIS to assist for the development of plans and policies related to the various activities, which may be practiced by management.

The hybrid vehicle routing problem is an extension of the green vehicle routing problem where vehicles can use different fuels. In this research, a bi-objective hybrid vehicles routing problem is presented and solved bu considering alternative paths, various lengths and reliabilities. The first objective function minimizes overall system costs and fuel consumption and greenhouse gas emissions, whereas the second objective function maximizes the reliability of the entire system with alternative paths and several reliabilites. The proposed model is formulated as mixed-integer nonlinear programming and a bi-objective simulated annealing (MOSA) algorithm along with the e-constraint method is used as solution strategy. The implementation of the proposed method is presented using some numerical instances.

The medical industry incorporates technology and breaks different types of equipment into three various categories determined according to the technologies and their usage. The first category, which is the focus of this article, consists of devices that are directly linked to the life of the patients, for example a ventilator. The purpose of this study is to develop a new reliability technique, based on the Reliability Block Diagram (RBD) and Petri Net, for Category 1 equipment. The RBD, focuses on showing how the failure of different parts could affect the sub-systems of the equipment and how those failures could cause an overall system failure. The second method, Petri Net, is a tool that is used to analyze various types of information processing systems. Combining these two methods will allow the user to determine the reliability of the different systems and subsystems with various pieces of equipment. The knowledge gained by this analysis will be used to determine the likelihood that the failure of specific subsystems will cause an overall system failure. The overall anticipated result is to thoroughly develop this new methodology. The complete process that is used to finish the calculation process for the subsystems will be shown, in addition to the completion of the final Reliability Block Diagram.

An effective operations of a projection spot welding (PSW) machine is closely related to the effec-tiveness of the maintenance. Timely maintenance can prevent failures and improve reliability and maintainability of the machine. Therefore, establishing the maintenance frequency for the welding machine is one of the most important tasks for plant engineers. In this regard, reliability analysis of the welding machine can be used to establish preventive maintenance intervals (PMI) and to identify the critical parts of the system. In this reliability and maintainability study, analysis of the PSW machine was carried out. The failure and repair data for analysis were obtained from automobile manufacturing company located in Uzbekistan. The machine was divided into three main sub-systems: electrical, pneumatic and hydraulic. Different distributions functions for all sub-systems was tested and their parameters tabulated. Based on estimated parameters of the analyzed distribu-tions, PMI for the PSW machines sub-systems at different reliability levels was calculated. Finally, preventive measures for enhancing the reliability of the PSW machine sub-systems are suggested.

The objective of the present study is to bring out a multidimensional metric to measure service quality delivered by employees serving in Indian small & medium manufacturing enterprises. 144 executives working at top/middle level in different small-medium manufacturing units of north India responded to a questionnaire survey. The respondents were asked to assess service quality being delivered by the shop-floor workers serving their respective units on the 1-5 perception scale. Application of exploratory factor analysis resulted in an interpretable latent structure comprising of 5 determinants and 22 indicator items. Confirmatory factor analysis condensed this scale to bring out the final scale 4 determinants viz., Dependability, Agility, Professionalism and Understanding with 13 indicator statements. This scale thus emerged is tested for validity and reliability using established tools. The study provides a framework to SME managers to assess services of their workforce. It also contributes to researchers to build up more such metrics for similar situations in other sectors so that more concrete generalizations can be made.

A large-scale cloud data center must have a low failure incidence rate and great service dependability and availability. However, due to several issues, such as hardware and software malfunctions that regularly cause task and job failure, large-scale cloud data centers still have high failure rates. These mistakes can have a substantial impact on cloud service dependability and need a large resource allocation to recover from failures. Therefore, it is important to have an efficient management of data recovery to protect organizations data from loss. This paper aims to study some factors that may improve the management of data recovery by using quantitative research design as a methodology. The results of hypothesis testing give strong evidence supporting the positive and significant correlations between the proposed hypotheses and the efficiency of data management recovery. This study finds that the presence of a data center in an organization demands the development of a solid plan for the most effective usage of a software program to handle data recovery.

This study presents a new mathematical model for the design of reliable cellular manufacturing systems, which leads to reduced manufacturing costs, improved product quality and improved total reliability of the manufacturing system. This model is expected to provide a more noticeable improvement in time and solution quality in comparison with other existing models. Each part to be manufactured may select each of the predefined manufacturing routes, such that the total reliability of the system is increased. On the other hand, the model adopts to categorize the machines to determine the manufacturing cells (cell formation) and reduce the transportation costs. Thereby, both criteria of system reliability and manufacturing costs will be simultaneously improved. Due to the complexity of cell formation problems, a two-layer genetic algorithm is applied on the problem in order to achieve near optimal solutions. Furthermore, the performance of the proposed algorithm is shown for solving some computational experiments. Finally, the results of a practical study for designing a cellular manufacturing system as a case study in Iranian Diesel Engine Manufacturing Co., Tabriz, Iran are present.

This qualitative study examined the impact of social media characteristics on the attitude of users toward the use of e-services by the Department of Lands and Survey. The study population comprised users of Department of Lands and Survey e-service, while the study sample comprised 407 users. Data from respondents were analyzed using SEM run using Amos (23). Results showed reliability, security, website design, ease of use, awareness, and digital divide as direct significant antecedents of user attitude toward the use of e-services from the Department of Lands and Survey. Also, all antecedents showed direct significant relationships with user attitude. Results showed a direct significant relationship between user attitude and the use of e-services from the Department of Lands and Survey. Through mediation of user attitude, five indirect significant relationships between the antecedents and the use of e-services from the Department of Lands and Survey were found. The inclusion of new antecedents such as privacy and site content may enhance the understanding of how users use e-services provided by the Department of Lands and Survey.