Browsing by Author "Hashemkhani Zolfani, Sarfaraz"
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- ItemAnalysing larg supply chain management comoptitive strategies in iranian cement industries(Technical university of Liberec, Czech Republic, 2017-10-02) Jamali, Gholamreza; Karimi Asl, Elham; Hashemkhani Zolfani, Sarfaraz; Šaparauskas, Jonas; Ekonomická fakultaIn the contemporary highly competitive international business environment companies have to exercise great care in devising entry strategies for foreign markets. Therefore, supply chain management (SCM) is considered a strategic factor for the better attainment of organizational goals such as enhanced competitiveness, improved customer service and increased profitability. Because the, Supply chain management as a vital challenge to the Cement industry and developing infrastructure as a whole has been posed by scholars. This article analyses Lean, Agile, Resilient, and Green (LARG) supply chain management competitive strategies in Iranian cement industries. The lean, agile, resilient and green SCM paradigms had been adopted to improve the SC performance. We used Step-wise Weight Assessment Ratio Analysis (SWARA) technique to weighting strengths, weaknesses, opportunities and threats (SWOT) based on LARG supply chain management practices for 11 Iranian cement companies. Then the Strategic Position and Action Evaluation (SPACE) matrix used to check if which strategy is appropriate. In the SPACE matrix we assessed Iranian cement industries across four dimensions include: Industry Attractiveness (IA), Environmental Stability (ES), Competitive Advantage (CA) and Financial Strength (FS). The results showed that Iranian cement industries can follow an aggressive strategy as it leverages its strengths into the opportunities. Iranian cement industries are also blessed because it has a good competitive advantage in an industry which is considered to be attractive. Among the strategic choices, develop new local markets strategy has the first priority, followed by the; Increase production capacity, Export markets development, Diversification in product with QSPM method. Finally, some actions recommended for Iranian cement industries in such a strong position.
- ItemProspective MADM and Sensitivity Analysis of the Experts Based on Causal Layered Analysis (CLA)(Technická Univerzita v Liberci, ) Hashemkhani Zolfani, Sarfaraz; Yazdani, Morteza; Zavadskas, Edmundas Kazimieras; Hasheminasab, Hamidreza; Ekonomická fakulta“Multiple Attribute Decision Making (MADM)” is an expert based field which is working based on real data and experts’ opinions. So many studies have been doing based on MADM methods which they usually use qualitative data based on experts’ ideas. Decisions based on the experts’ opinion shall be carefully designed to cope the real problems uncertainty. This uncertainty will be even more intricate if combining the problem with the ambiguity of the future study. Prospective MADM is a future based type of MADM field which is concentrating on decision making and policy making about the future. Prospective MADM (PMADM) can have both explorative and descriptive paradigms in the studies but it will more useful to be applied for strategic planning. In this regard, experts’ role would be even more challenging because one/some possible future/futures will be partially designed based on their opinions. Future and prediction always complicates the decision environment, especially methodologies founded on experts’ judgement. Considering experts’ preferences, attitude, and background, they may be a major source of inaccurate results. Causal Layered Analysis (CLA) is well-known “Futures Studies” method which is qualitative and usually is supporting other methods such as “Backcasting” and “Scenario Planning”. CLA has a deep point of view to the subjects to support a future with all those changes which are necessary for the main goal/goals. In this study, this idea will be proposed that CLA can be added to PMADM outline to decrease the risk of unsuitable decisions for the future and for this aim a case study about energy and CO2 consumption in policy making level proposed and a hybrid MADM method based on BWM-CoCoSo applied in the PMADM outline for the procedure.