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This study aims to investigate the various competencies a graduate should hold to prepare them for graduate building surveying roles from employers’ perspective.

This study uses a sequential exploratory mixed-method approach by informing a quantitative study with the finding from a qualitative study.

Based on exploratory factor analysis, the study found that 13 essential competencies are valued by the employers when recruiting building surveying graduates, as they are requisites for effective job performance. Personal management skills, technical surveying knowledge and knowledge of the Royal Institute of Chartered Surveyor standards are the essential competencies based on the level of variance extracted by the three components. Other competency categories include client management skills, being goal-driven and self-motivated, optimistic personality traits, strong mental resilience, building maintenance and management knowledge and time management skills, among others that are explained in the paper.

The essential competencies were dependent on maintaining a balance between knowledge, skills and personality-based competencies. Measures and approaches for gaining the essential competencies, as well as their level of significance, are further discussed. The study will be of significant benefits to employers of graduate building surveyors, academic institutions that are seeking to improve their graduate employability, as well as students who are preparing for the world of work.

In this paper, the authors extend the goal-directed benchmarking theory proposed by Stewart for benchmarking and selecting suppliers. This extension is in recognition of the fact that benchmarking for suppliers is more than a pure monitoring process and includes a component of future planning. The paper aims to discuss these issues.

In this paper, the proposed model utilizes a goal programming structure to find points on the efficient frontier which are realistically attainable by suppliers in the presence of undesirable outputs, but at the same time achieving a closer method to long-term organizational goals (as distinct from the local performance of individual suppliers).

The contributions of the current paper are as follows: the proposed model considers undesirable outputs in the context of goal-directed benchmarking. The proposed model does not demand weights from the decision maker. The proposed model can be easily computerized, enabling it to serve as a decision making tool to assist decision makers. For the first time, the proposed model is applied for the supplier selection and benchmarking.

To the best of knowledge of the authors, there is not any reference that discusses supplier selection problem and benchmarking in the presence of undesirable outputs in the context of goal-directed benchmarking.

The application of automated systems is rapidly increasing in different industries and organizations. In this regard, computerized maintenance management systems (CMMS) using information technology play an important role in the automating production systems. The purpose of this paper is to investigate the impacts of CMMSs and relevant supportive organizational factors on the effectiveness of total productive maintenance.

This study is classified as a quantitative survey-based research using structural equation modeling. The scope of the study includes manufacturing companies in Iran. A total of 125 questionnaires from 60 companies were collected from January to March 2014 to help validate the conceptual model and test the hypotheses.

The results support the concept CMMSs positively relates to relevant supportive organizational factors (resource allocation, decision-making structure, senior management support, employees’ involvement and effective instruction) on the effectiveness of total productive maintenance. The relevant supportive organizational factors can also be seen as the predictors of CMMSs.

This study integrates the CMMSs and relevant supportive organizational factors in a robust model to examine the effectiveness of total productive maintenance. This study also examines the impacts of CMMSs and relevant supportive organizational factors on total productive maintenance which seems to not be done previously.

The main aim of this research is to rank and prioritize the solutions to address the challenges for the successful implementation of talent management (TM) in government banks in Iran.

This paper has identified the challenges of TM implementation in government banks and proposed the solutions to address these challenges through a review of the extant literature. The identified challenges and solutions were ranked using two multi-criteria decision-making (MCDM) methods called PROMETHEE and VIKOR based on the insights from 20 senior managers of government banks in Iran.

The challenges and solutions were categorized into cultural, managerial, human resources and environmental-related factors. “Building culture of TM in organizations”, “making TM as an ongoing process in organizations”, “commitment of senior managers to TM process”, “managing TM pipeline” and “focusing on meritocracy in recruitment and selections” were ranked as the top solutions to address cultural, managerial, human resources and environmental challenges, respectively.

The findings can provide a comprehensive view of different types of challenges and solutions in the TM process for government organizations and institutions. It also provides helpful insights for top managers to define their organizations' strategies effectively and to implement the TM process by ranking and prioritizing the solutions to address their challenges.

The main contribution of this study is to develop a comprehensive framework in which, identification of different types of challenges in the implementation of TM processes can be addressed and the approaches to remove or mitigate the effects of these challenges are ranked by using two well-established MCDM techniques.

This paper aims to investigate the steady flow and heat transfer of a Cu-Al₂O₃/water hybrid nanofluid over a nonlinear permeable stretching/shrinking surface with radiation effects. The surface velocity condition is assumed to be of the power-law form with an exponent of 1/3. The governing equations of the problem are converted into a system of similarity equations by using a similarity transformation.

The problem is solved numerically using the boundary value problem solver (bvp4c) in Matlab software. The results of the skin friction coefficient and the local Nusselt number as well as the velocity and temperature profiles are presented through graphs and tables for several values of the parameters. The effects of these parameters on the flow and heat transfer characteristics are examined and discussed.

Results found that dual solutions exist for a certain range of the stretching/shrinking and suction parameters. The increment of the skin friction coefficient and reduction of the local Nusselt number on the shrinking sheet is observed with the increasing of copper (Cu) nanoparticle volume fractions for the upper branch. The skin friction coefficient and the local Nusselt number increase when suction parameter is increased for the upper branch. Meanwhile, the temperature increases in the presence of the radiation parameter for both branches.

The problem of Cu-Al₂O₃/water hybrid nanofluid flow and heat transfer over a nonlinear permeable stretching/shrinking surface with radiation effects is the important originality of the present study where the dual solutions for the flow reversals are obtained.

The purpose of this study is to develop a methodology in which alternate Six Sigma projects are prioritized and selected using appropriate multi-criteria decision-making (MCDM) methods in healthcare organizations. This study addresses a particular gap in implementing a systematic methodology for Six Sigma project prioritization and selection in the healthcare industry.

This study develops a methodology in which alternate Six Sigma projects are prioritized and selected using a modified Kemeny median indicator rank accordance (KEMIRA-M), an MCDM method based on a case study in healthcare organizations. The case study was hypothetically developed in the healthcare industry and presented to demonstrate the proposed framework’s applicability and validity for future decision-makers who will take place in Six Sigma project selection processes.

The study reveals that the Six Sigma project prioritized by KEMIRA-M assign the highest ranks to patient satisfaction, revenue enhancement and sigma level benefit criteria, while resource utilization and process cycle time receive the lowest rank.

The methodology developed in this paper proposes an MCDM-based approach for practitioners to prioritize and select Six Sigma projects in the healthcare industry. The findings regarding patient satisfaction and revenue enhancement mesh with the current trends that dominate and regulate the industry. KEMIRA-M provides flexibility for Six Sigma project selection and uses multiple criteria in two-criteria groups, simultaneously. In this study, a more objective KEMIRA-M method was suggested by implementing two different ranking-based weighting approaches.

This is the first study that implements KEMIRA-M in Six Sigma project prioritization and selection process in the healthcare industry. To overcome previous KEMIRA-M shortcomings, two ranking based weighting approaches were proposed to form a weighting procedure of KEMIRA-M. As the first implementation of the KEMIRA-M weighting procedure, the criteria weighting procedure of the KEMIRA-M method was developed using two different weighting methods based on ranking. The study provides decision-makers with a methodology that considers both benefit and cost type criteria for alternates and gives importance to experts’ rankings related to criteria and the performance values of alternates for criteria.

The objective of this paper is to propose a new data envelopment analysis (DEA) model for assessing sustainability of suppliers with partial impacts between inputs, desirable outputs and undesirable outputs.

This paper examines partial impacts of inputs on desirable and undesirable outputs and applies weak disposability assumption to propose a novel DEA model to determine the sustainability of suppliers.

This paper shows the type of resource sharing in DEA models and takes into account sustainable development and sustainability assessment concepts for sustainable supplier selection problem and develops a DEA model for selecting the most sustainable suppliers with partial sharing of resources. To select the most sustainable suppliers, this model helps managers to consider aggregate efficiency, overall efficiency and bundle efficiency. The paper introduces the supplier which is efficient at all levels as the most sustainable supplier.

For the first time, this paper suggests a new DEA model by partial impact between inputs and good outputs/bad outputs for selecting sustainable supplier and deals with the situations in which each supplier has several subunits. The new model calculates aggregate efficiency, overall efficiency and subunit efficiency of supplier. paper introduces the supplier which is efficient in all levels including aggregate efficiency, overall efficiency and subunit efficiency as the best supplier.

This study aims to examine the relationship between Islamic work ethics (IWE), job embeddedness and knowledge-sharing behaviors. It also tested the mediating effects of job embeddedness and the moderating effects of organizational identification on this relationship.

A total of 396 respondents from Islamic banks in Indonesia participated in this study. Data analyzes for hypothesis testing were conducted using Hayes’ PROCESS macro-based hierarchical regression.

The findings suggest that subscribing to IWEs positively and significantly impacts job embeddedness and knowledge-sharing behaviors. Moreover, job embeddedness was confirmed as a mediator in the relationship between IWEs and knowledge-sharing behavior. Finally, the effects of IWEs on knowledge-sharing behaviors are stronger when employees attain a high level of organizational identification.

By encouraging the adoption of IWEs, organizations can develop job embeddedness and promote knowledge-sharing in the workplace, especially in an Islamic banking context. Therefore, managers should strengthen the mutual understanding among employees regarding IWE principles. They should be consistently applied and disseminated by Islamic banks’ management in the form of a formal code of ethics that applies to all actions within the organization.

This study was conducted to extend the understanding of IWE and its relationship with workplace outcomes in modern organizations. Drawing on the conservation of resources theory, social identity theory and Islamic theology, new insights are provided by explaining the psychological mechanism underlying the relationship between IWEs and knowledge-sharing behaviors while proposing organizational identification as the boundary condition.

To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.