M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.

The construct of employees' job satisfaction has been gaining an increasing scholarly attention as one of the crucial determinants of organizational effectiveness and success. Specifically, it has been very much acknowledged by both researchers and academics that employees are the most valuable assets of an organization and play the crucial role in achieving its overall objectives. These arguments justify the attention given to studying the psychological characteristics of employees and what determine their job satisfaction that impacts the organizational performance. In addition to that, transformational leadership has been proven to have a significant effect on the employees' job satisfaction through enhancing the employees' perception of empowerment. Despite this fact, the dynamic role of transformational style on enhancing the level of satisfaction among the empowered individuals has been greatly neglected. It has been, also, proven in the literature that employees' satisfaction directly affects the customers' satisfaction and subsequently the overall organizational performance. In Yemen, as it the case on many developing countries, employees of an organization should be satisfied as the first step to achieve a better organizational performance associated with customers' satisfaction. The poor performance of Yemeni banks, as customer-oriented business, can be, somehow, attributed to the low level of employees' job satisfaction. This paper, however, aims to examine the joint effect of employees' psychological empowerment and transformational leadership on the employees' job satisfaction. To achieve this purpose, responses of a sample of 160 employees from the Yemeni Islamic banks have been examined. The findings of this study confirmed the direct effect of employees' psychological empowerment and transformational leadership on the employees' job satisfaction. On the other hand, the moderating effect of transformational leadership on the relationship between employees' psychological empowerment and the employees' job satisfaction was not supported. These findings were, finally, discussed in the lights of the limitations of the study and future research directions were offered.

SUMMARYAn M/G/C/C state dependent queuing network measures the performance of a system whose service rate decreases with the increasing number of residing entities. However, the performance in terms of throughputs, levels of congestions, the expected number of entities, and the expected service time is typically analyzed based on a series of arrival rates without any further discussion on the optimal arrival rate. This paper derives the optimal arrival rates of corridors in a topological network using calculus and numerical analysis approaches. These optimal rates are then used as capacity parameters in the network's flow model to obtain the optimal arrival rates that maximize its total throughput. To ease the construction and performance evaluation of the network, we design and construct an M/G/C/C framework based on the Object-Oriented Programming approach that integrates the LINGO software as an optimization tool. The framework is then tested on virtual and real networks. This framework can be used to develop a more advanced traffic management tool for studying and managing traffic flow through a complex network. Copyright © 2015 John Wiley & Sons, Ltd.KEY WORDS: M/G/C/C state dependent; network flow model; queuing system; performance evaluation; topological network INTRODUCTIONQueuing networks have long been used to explore the effects of capacity constrained resources on common performance measures such as throughputs and response time. The resources' service times in most queuing systems strictly fluctuate according to a statistical distribution regardless of the number of residing entities. Examples of systems that follow this behavior include service, production, and manufacturing processes. Other systems meanwhile physically adjust their service times based on the current number of entities. This behavior can be best described using an M/G/C/C state dependent queuing network. The M/G/C/C network imitates how residing entities affect a resource's service time and influence its system's performance. Common performance measures collected are the throughput, blocking probability, expected number of entities, and expected service time. The service time becomes longer when the number of requesting entities increases. However, any decrement of the number will speed up the processing time to offer better service. Examples of systems that follow this behavior are entities moving through a constrained network; for example, a corridor and road.The maximum number of residing entities in an M/G/C/C system is limited by the capacity of its resource. Because the capacity (i.e., the available space to accommodate entities) is fixed, the only parameter that can be controlled to improve its performance is the current number of residing entities. The number is implicitly influenced by the arrival rates of entities into the system. Slow arrival rates † Transp. 2016; 50:96-119 Published online 11 September 2015 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002DOI: 10. /atr.1330 make the system process the re...

Abstract:The objective of this research paper is to demonstrate the application of hybrid Knowledge-Based System, Gauging Absences of Pre-Requisites (GAP), and Analytic Hierarchy Process (AHP) approaches for selecting the improvement programs for Collaborative Lean Manufacturing Management (CLMM) System. In this research, a generic Knowledge-Based System is developed to measure the level of CLMM adoption in automotive manufacturers compared to the ideal system. Using the embedded GAP and AHP technique, the key lean manufacturing improvement programs can be prioritised by using both qualitative and quantitative criteria. The analysis covers the planning stage of the KBCLMM. The utilisation of the approach is demonstrated with an illustrative example.

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This study estimates technical, allocative, and cost efficiency using cost DEA model under both constant returns to scale (CRS) and variable returns to scale (VRS) respectively using survey data of 70 rice farmers from Kedah, Malaysia. In case of cost efficiency only 4.29% of the farmers were 100% technically efficient under CRS while it is increased into 16.90% under VRS. The average technical, allocative and cost efficiencies were estimated at 0.28, 0.878 and 0.255 respectively under CRS while they were increased into 0.61, 0.883 and 0.533 respectively under VRS.

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