Proposing a new methodology for prioritising the investment strategies in the private sector of Iran

This article proposes a systematic and organised approach for group decision-making in the presence of the uncertainty involved in expert judgments as used in multi-criteria decision-making (MCDM) issues. This procedure comprises the selection of the optimum alternative with respect to the evaluation criteria under consideration, in particular to select the strategy of investing. However, the selection of the investment strategy is difficult on account of considering the numerous quantitative and qualitative parameters like benefits, opportunities, costs, and risks. However, it is possible that these parameters have a significant influence on each other. A decision-making trial and evaluation laboratory (DEMATEL), used to define the influential network of elements, can be employed to construct a network relationship map (NRM). On the other hand, according to whether the information is incomplete or unavailable, uncertainty is an inseparable part of making decision for solving the MCDM problems. Therefore, this article proposes a new hybrid model based on analytic hierarchical process (AHP), DEMATEL, and echnique for Order of Preference by Similarity to Ideal Solution (TOPSIS) techniques under fuzzy environment to evaluate the problem of the selection of the investment strategy. To achieve the aim, a three-step process is presented to solve a sophisticated problem. First, the AHP method is employed to break down the investment problem into simple structure and calculate the importance weights of criteria by using a pairwise comparison process. Second, the DEMATEL technique is applied for considering interdependence and dependencies and computing the global weights of benefit, opportunities, cost, and risk (BOCR) factors. Finally, the fuzzy TOPSIS methodology is used for prioritising the possible alternatives. To demonstrate the potential application of the proposed model, a numerical example is illustrated and investigated. The results show that the proposed model has a high ability to prioritise the strategies of investing

An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi- criteria decision approach for the selection of solar-thermal power plant investment projects

In this paper the AHP (Analytic Hierarchy Process) and the ANP (Analytic Network Process) are applied to help the managing board of an important Spanish solar power investment company to decide whether to invest in a particular solar-thermal power plant project and, if so, to determine the order of priority of the projects in the company's portfolio. Project management goes through a long process, from obtaining the required construction permits and authorizations, negotiating with different stakeholders, complying with complex legal regulations, to solving the technical problems associated with plant construction and distribution of the energy generated. The whole process involves high engineering costs. The decision approach proposed in this paper consists of three phases. In the first two phases, the managing board must decide whether to accept or reject a project according to a set of criteria previously identified by the technical team. The third phase consists of establishing a priority order among the projects that have proven to be economically profitable based on project risk levels and execution time delays. This work analyzes the criteria that should be taken into account to accept or reject proposals for investment, as well as the risks used to prioritize some projects over others.The translation of this paper has been funded by the Universitat Politecnica de Valencia.Aragonés Beltrán, P.; Chaparro González, FV.; Pastor Ferrando, JP.; Pla Rubio, A. (2014). An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi- criteria decision approach for the selection of solar-thermal power plant investment projects. Energy. 66:222-238. doi:10.1016/j.energy.2013.12.016S2222386

Using a hybrid decision-making model to evaluate the sustainable development performance of high-tech listed companies

In this study, we use a triple bottom-line concept including economic, social and environmental performance as the sustainable development performance evaluation categories for companies. Moreover, an integrated model based on grey relational analysis, decision-making trial and evaluation laboratory, analytic network process and the technique for order preference by similarity to ideal solution is proposed for solving a corporate sustainability performance evaluation and ranking problem. In order to verify the proposed model, we adopt 34 high-tech listed companies in Taiwan as the research object to measure companies’ sustainable development performance and ranking in 2013. The results can be used as an important basis for management decision-making, and can also serve as reference for banks and investors when developing investment strategy

Navigating SWOT-FANP with GSM method to prioritize the strategic location

[[abstract]]This paper proposes a SWOT-FANP (strengths, weaknesses, opportunities, and threats – fuzzy analytic network process) analysis, together with the grand strategy matrix method (GSM) to deal with the multiple-criteria decision-making problem of location selection for a second tier city in China. This hybrid method can not only combine both qualitative and quantitative information and utilize fuzzy logic to eliminate vagueness, subjectivity, and imprecision, it can also clearly represents the competitive position of second-tier cities on a the quadrant coordinate to help an enterprise choose a strategy for development. To this end, I empirically chose a multinational pharmaceutical enterprise (MNE) as an illustrative example. The results reveal that Suzhou and Chongqing cities are in the best positions in the competition as a result of having external opportunities for development and internal competing strength. Moreover, the MNE could adopt a niche-focus strategy for the market by focusing on specific ailments to which people in Chinese communities are vulnerable to strengthen their competitive strengths. This study demonstrates and validates that such an enhanced methodology is viable and highly capable of providing enriched insights regarding strategic decision-making management in complex real-world situations.[[journaltype]]國外[[incitationindex]]SSCI[[ispeerreviewed]]Y[[booktype]]紙本[[countrycodes]]LT

Identification and Prioritization of Risk and Its Effect of the Renewable Energy Life Cycle Based on Performance and Risk Indicators

Risk management consists of two aspects of risk control and risk assessment in the electricity market. So, risk control should cover the risk and work out of the way of optimal investment portfolios. Thus, the aim of this research is producing solar electricity life cycle profitability. First to identify existing risks in the production of electricity using Delphi technique between 300 experts in 15 Powerhouse. Then, the grey ANP model was the adoption of the New Energy Organization of Iran. The number of risk factors were collected by subject literature in renewable energy in Iran that have analyzed and selected the high-risk factors by ANP GREY method. Finally, to examine the life cycle of solar power, the authors analyzed financial indicators and the life cycle’s factors which relates to performance and risk variables, then, the Regression model used in three stages of life cycle. Finally, the result provides incentives for the energy system to support production renewable electricity and aid to increase the profitability of the renewable energy cycle

An Integrated Fuzzy Multi-Criteria Decision Making Method For Supplier Evaluation

This research investigates the risk exposure arising from the supplier evaluation criteria of cost, quality, delivery, and flexibility of the supplier. Penyelidikan ini bertujuan untuk mengkaji risiko yang timbul daripada kos, kualiti, penghantaran dan fleksibiliti bagi penilaian pembekal

Performance Management Model of Sustainable Safe Production at Deep Mill Level Zone PT. Freeport Indonesia

One of the mine expansions that is expected to accelerate the production rate of PT Freeport Indonesia is the Deep Mill Level Zone (DMLZ) mine. The block caving mining method used at the DMLZ mine results in higher productivity levels at lower operating costs but requires ongoing equipment maintenance. This research aims to describe the factors and criteria that determine the production process, find a performance management model, and find the right strategic priorities to increase productivity at DMLZ mine. We analysed the condition of the maintenance management system at the DMLZ mine to find solutions and strategies so that equipment maintenance could be managed effectively. Sustainable Safe Production performance management is developed based on the Balanced Scorecard (BSC) approach combined with the Analytical Network Process (ANP), which is expected to determine the priority of solutions and strategies based on predetermined criteria and indicators. This performance management model considers six perspectives: finance, customers, production, safety, internal business processes, and learning and growth processes as benchmarks in measuring performance. We explained the determination of priority strategies that can be done to achieve three goals in sustainable safe production management: achieving production targets, safe and healthy mining processes, and achieving operational cost-effectiveness. Keywords: analytical network process (ANP), balanced scorecard (BSC), performance management, safe production, sustainable productio

Unveiling the relation between the challenges and benefits of Operational Excellence and Industry 4.0: A Hybrid Fuzzy Decision-Making Approach

Operational excellence (OpEx) is a direction toward learning and developing an excellent culture in all aspects of an organization. To reach this culture, revolutionizing activities using industry 4.0 (i4.0) technologies might be a significant empowering tool. This study aims to identify the challenges and benefits of both concepts and investigate their interrelationship to be considered in applying industry 4.0 technologies toward operational excellence. The challenges and benefits of OpEx and i4.0 are identified and finalized by reviewing the literature. The causal relations between the considered factors are extracted using the fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) method. Then, the analytical network process (ANP) is applied to determine the importance and weight of the factors (challenges and benefits of OpEx and i4.0) according to the constructed network. The findings illustrated a strong network structure between the factors. First, the causal factors included OpEx and i4.0 challenges, while the OpEx challenges also affected the i4.0 challenges. Both group challenges had a significant effect on OpEx and i4.0 benefits. This means that challenges are the causal factors to be considered in the alignment of i4.0 toward OpEx. Among the OpEx challenges, lack of strategic planning and proper infrastructure were the main influential factors. In contrast, lack of government support and undeveloped business models were identified as the main challenges of i4.0. OpEx and i4.0 concepts are reviewed, and their pros and cons are studied. Previous studies determined an interaction among these concepts. However, from a practical viewpoint, the relation between the challenges and benefits of i4.0 and OpEx was studied for the first time for their alignment

Industry 4.0 enabling sustainable supply chain development in the renewable energy sector:A multi-criteria intelligent approach

The aim of this paper is to provide a multi-criteria decision-making intelligent approach based on Industry 4.0 and Triple Bottom Line principles for sustainable supply chain development in the renewable energy sector. In particular, the solar photovoltaic energy supply chain is used as a case study, encompassing the entire energy production process, from supply to disposal. An exhaustive literature review is conducted to identify the main criteria affecting social, economic and environmental sustainability in the photovoltaic energy supply chain, and to explore the potential impact of Industry 4.0 on sustainability. Subsequently, three Fuzzy Inference Systems combining quantitative and qualitative data are built to calculate the supply chain's social, economic and environmental sustainability. Experts' opinions are used to identify the impact of Industry 4.0 technologies on the three pillars of sustainability for each supply chain stage. Finally, a novel sustainability index, Sustainability Index 4.0, is formulated to compute the overall sustainability of the photovoltaic energy supply chain in seven countries. The results show the applicability and usefulness of the proposed holistic model in helping policy makers, stakeholders and users to make informed decisions for the development of sustainable renewable energy supply chains, taking into account the impact of Industry 4.0 and digital technologies