Banking financial performance (BFP) has been recognized as a causation of human resource management (HRM). The causal linkages from HRM practices to BFP are different. Nevertheless, almost none of the studies has ranked and compared this difference among the practices of HRM in enhancing BFP. The current study applied an analytic hierarchy process to rank the relative importance of HRM practices. For the robustness of the results from the process of analytic hierarchy, the current work employed an analytic hierarchy process to reassess the relatively important levels of HRM practices on BFP as well. The findings are robust across both of the techniques. The practice of training and development (TT) plays the most critical part in BFP, followed by the practice of performance evaluation (PN) and the practice of reward system (RM) as the third most important. In contrast, the practice of recruitment and selection (RN) takes the least important position in BFP. Moreover, the findings also provide statistical evidence on the causal links from the practices of HRM to BFP. This work makes some contribution to how managers should decide on HRM practices in order to obtain the best possible BFP.

The contribution of protected areas towards conservation and protection of biodiversity cannot be over emphasized. Likewise, the dependence of local communities on forest and natural resources cannot be overlooked. Hence for the long term viability of forest reserves and wildlife protected area, the relationship of local people living close to these areas are of key importance if conflict of use can be mitigated. Admittedly, decision-making with respect to forest resource use and protection are complex due to the multiple interests of the major stakeholders. Stakeholder involvement in the planning, management and policy analysis can help resolve conflicts, and increase the commitment of local people to support conservation of protected areas. In this paper, we employ the SWOT-AHP methodology, with the aid of the Priority Estimation Tool (PriEsT), to evaluate and prioritize three management strategies for the Kakum conservation area in Ghana, as a means to facilitate conservation while ensuring benefits to local people. Considering the management objectives of the conservation area, seventeen SWOT sub-factors were identified and used in rating the three alternative management strategies. Among the strength sub-factors, enforcement of protection regulations (S4) is the most important. Similarly, limited funds for patrolling and outreach programs (W3), local people’s interest in alternative livelihood (O4) and the presence of illegal activities (T3) are the most important weakness, opportunity and threat sub-factors respectively. The management strategy “institute village committees to support monitoring and protection of resources” (A1) has the highest priority rating, indicating that management authorities must pay more attention to collaborative management. We propose that to improve on protected area management in Ghana, more management strategy studies must be conducted. However, these studies may apply the fuzzy AHP technique since it is supposed to have a better capacity to handle uncertainties in human judgments during decision-making.

Supplier evaluation and selection play a vital role in establishing an effective supply chain for any firm. The supplier evaluation not only enables the firm to know the performance of suppliers, but also gives an indication of the ability of the firm itself to gain competitive advantage. The appropriate evaluation is the basis for the subsequent selection of the best supplier. This paper presents a hybrid methodology using Data Envelopment Analysis (DEA), Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA) to evaluate suppliers and to identify the best supplier for a firm. In this work, super efficiency and cross efficiency methods of DEA are employed to determine the efficiencies and the performance scores of the suppliers respectively. On the basis of super efficiency and cross efficiency scores, the list of efficient suppliers with high performance is identified and GRA methodology is adopted to identify the best supplier. A case study is presented to demonstrate the proposed hybrid methodology.

The evaluation and selection of energy technologies involve a large number of attributes whose selection and weighting is decided in accordance with the social, environmental, technical and economic framework. In the present work an integrated multiple attribute decision making methodology is developed by combining graph theory and analytic hierarchy process methods to deal with the evaluation and selection of energy technologies. The energy technology selection attributes digraph enables a quick visual appraisal of the energy technology selection attributes and their interrelationships. The preference index provides a total objective score for comparison of energy technologies alternatives. Application of matrix permanent offers a better appreciation of the considered attributes and helps to analyze the different alternatives from combinatorial viewpoint. The AHP is used to assign relative weights to the attributes. Four examples of evaluation and selection of energy technologies are considered in order to demonstrate and validate the proposed method.

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. Recently, DEA has been extended to examine the efficiency of network structures, where there are lots of sub-processes that are linked with intermediate parameters. These intermediate parameters can be considered as the outputs of the first stage and simultaneously as the inputs for the second stage. In contrast to the traditional DEA analysis, network DEA analysis aims to measure different sub-processes’ efficiencies in addition to the total efficiency. Lots of network DEA technique has been used recently, but none of them uses Analytic Hierarchy Process (AHP) in network DEA for assessing a network’s efficiency. In this paper, AHP methodology is used for considering the importance of each sub-process and network DEA is used for measuring total and partial efficiencies based on the importance of each department measured from AHP methodology. In this regard, the case of Iranian Handmade Carpet Industry (IHCI) is used.

Considering the importance and extensive range of decision-making, scientists from various fields have had many discussions on this issue. Various models have been proposed to facilitate decision-making and have had much utilization. In many site selection problems, multiple objectives must be obtained, simultaneously. This study uses a mathematical model to select a suitable location for the refinery in the multi attribute environment. The proposed model uses a large amount of qualitative and quantitative information in the frame of multi objective functions for the first time in the refinery site selection and is flexible enough to use decision makers’ opinions in order to achieve goals. For this reason, after a brief overview of the selected area characteristics, using analytic hierarchy process (AHP) for weighting the criteria, a mathematical operation research model is proposed to determine the best alternatives.