This study unraveled the effects of strategic management and organizational culture on organizational performance. It also determined the most triggering predictor of organizational performance. In this study, strategic management focused particularly on the formulation and implementation strategy. A number of 291 officers from government organizations participated in this study. Self-administered questionnaire was employed for the data collection. The analysis revealed that the performance of government organizations was impacted by organizational culture, dimensions of formulation and implementation strategy. Organizational culture emerged as the most triggering predictor on organizational performance. The study concludes with some implications for practice and theory.

The purpose of this study was to evaluate the student’s talent management of a corporate university in Iran by descriptive-analytic method. The statistical population of the study included all 2200 students of the university. Based on the estimated number at Morgan table, 202 respondents completed the survey instrument. The data collecting tool of the questionnaire was ascertained and its reliability was obtained 78 percent by Cronbach's alpha coefficient. Content validity of the tool was also veri-fied by the experts. For data analysis, the binomial test and Structural Equation Modeling (SEM) were used. The results show that none of the components of talent management (deployment and employment, career progression path, practical learning, performance management, knowledge sharing, self-development, training, appreciation and encouragement) in the studied university was in desire conditions. Other findings of the study also show that among organizational factors, compo-nents of “organizational culture”, “supervisor satisfaction”, “organizational dynamics”, “working environment conditions”, “colleagues”, “prestige and brand of the university” and “growth oppor-tunity” were influential on the students’ talent development. Also, the results of the data analysis show that among the components of job factors, the component of “person-job fitness” affects the development of students' talents.

This paper focuses on the impact of strategic leadership on operational strategy and organizational performance of the automobile industry in Malaysia with a particular focus on Proton (Perusahaan Otomobil Malaysia). Since the mid-1980s a growing body of research on leadership has focused on strategic leadership, in contrast to managerial and visionary leadership. It has focused on how lead-ers make decisions in the short term that guarantees long-term viability of the organization. Senior leaders also have the ability to align human resources in an effective way directly to the business strategy. This article focuses on how national car manufacturer, Proton, exercises strategic leadership to influence its operational strategy and performance. It examines both dependent and inde-pendent variables that influence on strategic leadership with implications for future research.

This paper aims to provide a fuzzy framework for aligning human resources strategies with busi-ness strategies at The University of Applied Science and Technology. This research is an applied research based on the purpose and the research time horizon is cross sectional. In this research, 15 experts are identified using snowball method. The necessary data are gathered based on 3 questionnaires including Delphi questionnaire, human resources (HR) and business strategic questionnaire. The results show that some couples of HR strategies were aligned with business strategies. Then “if-then” rules are described in FuzzyTech software and the study determines which business strat-egies must be aligned with human resources strategies using the analysis. The paper ends by providing some suggestions based on 16 possible scenarios.

The aim of this study is to investigate the effect of the application of service quality on patient satisfaction in Jordanian hospitals using the SERVQUAL model. The study uses samples from Al Hussein Military Hospital in Jordan, where 350 questionnaires were distributed to the admitted patients. The study implements structural equation modeling to examine the effects of the SERVQUAL components; namely tangible, reliable, assurance, empathy and responsiveness on customer satisfaction. The results show that quality of service dimensions affected patient satisfaction. Moreover, the SERVQUAL model also appeared as an appropriate tool for assessing the quality of hospital medical services.

The aim of this research is to understand the effect of product quality, medical price and staff skill on patient’s loyalty through cultural impact in medical tourism. In this study, three exogenous con-structs; namely product quality, medical price, and staff skill constructs were adopted to find their effects on patient’s loyalty. Meanwhile, the cultural impact is also adopted as a mediator construct. This study uses confirmatory approach as Covariance based Structural Equation Modeling (CBSEM) for testing the research hypotheses. The study explores inbound medical tourists loyalty from 324 respondents sampled comprised from different countries using stratified sampling. In terms of the direct effect, the method reveals that medical price and staff skill had positive significant effects on cultural impact and patient loyalty. In terms of indirect effect, the cultural impact mediates the relationships between product quality, medical price, and staff skills on patient’s loyalty.

Nowadays, industries cope with a wide range of situations and/or perturbations that endanger the manufacturing productivity. Traditionally, manufacturing control systems are responsible for managing the manufacturing scheduling and execution, as these have the capability of maintaining the production operations regardless of a given perturbation. Still, the challenge of these systems is to achieve an optimal performance after the perturbations occur. For this reason, manufacturing control systems must incorporate a mechanism with intelligent capabilities to look for optimal performance and operation reactivity regardless of any scenario. This paper proposes a generic control strategy for a manufacturing control system for piloting the execution of a dynamic scheduling problem, considering a new job arrival as the manufacturing perturbation. The study explores a predictive-reactive approach that couples a genetic algorithm for the predictive scheduling and an adaptive genetic algorithm for reactivity control aiming to minimize the weighted tardiness in a dynamic manufacturing scenario. The results obtained from this proposal verify that the effectiveness was improved by using adaptive metaheuristic in a dynamic scheduling problem, considering absorbing the degradation caused by the perturbation.

Cell formation and layout design are two important steps for the implementation of the production systems. The existing models majorly have focused on the cell formation issue and the layout design of machines, but have paid little attention to the placement of cells in dynamic environment. In addition, in most of the available papers, binary variables have been used for cell formation, and other information such as volume of production, operation sequences and production costs have played unimportant roles in the structure of the existing models. In this paper, a nonlinear program-ming model under potentially dynamic conditions is proposed which minimizes the cost associated with the difference between the estimated demands from its expected value. The other purpose of the proposed model includes minimization of the total costs of inter/intra cellular movements of elements (forward and backward movements), the existence of exceptional elements, intercellular displacement of machines and cellular reconfiguration and operational costs and constant cost of machineries. The problem is solved via GAMS and a Genetic Algorithm (GA) is employed to solve the large sized problems and the results are analyzed.

The aim of this study is to explore the determinants of cognitive loyalty in an online shopping envi-ronment. The study established a theoretical model by incorporating both e-service quality model and commitment-trust theory. A total of 937 responses were collected form Indian online shoppers by using the mail survey method. We assessed measurement model and structural model by using SPSS and AMOS. Study outcomes confirm that customer satisfaction, e-trust, commitment, and cognitive loyalty were strongly influenced by e-service quality and perceived value. Further, satisfaction had direct and positive influence on both e-trust and commitment but not on cognitive loyalty. E-trust had a positive impact on e-commitment and cognitive loyalty. Lastly e-commitment had a positive influence on cognitive loyalty. Based on the existing literature, there was a dearth of theo-retical understanding of cognitive loyalty in an emerging economy perspective. Thus, the current study accomplished the critical theoretical gap by encompassing previous investigations. We examined the phenomenon of customer loyalty by integrating e-service quality model and commitment-trust theory in business to consumer e-commerce environment while considering e-satisfaction as a mediator, highlighting the originality and contribution of the current research to the online consumer loyalty literature.

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.