Strategic management is a process of determining a business long-term objectives and the way to achieve these goals. Considering importance of strategic planning in long-term competitive power of organizations, different frameworks are proposed to formulate strategies. How to choose the best strategy is a challenging activity due to its multi criteria nature and lack of information. In this paper, a method comprised of grey DEMATEL-grey analytic network process is proposed to deal with this challenge. The proposed method considered interrelationship among factors using DEMATEL and then these relations are applied in strategy ranking by ANP. The uncertainty and lack of information is handled using grey numbers. Application of the proposed method is illustrated in an ecotourism company.

Inventory classification is a fundamental issue in the development of inventory policy that assigns each inventory item to several classes with different levels of importance. This classification is the main determinant of a suitable inventory control policy of inventory classes. Therefore, a great deal of research is done on solving this problem. Usually, the problem of inventory classification is considered in a multi-criteria and uncertain environment. The proposed method in this paper inspired by the notion of heterogeneous decision-making problems in which decision-makers deal with different types of data. To this aim, a mathematical modeling-based approach is proposed considering different types of uncertainty in classification information. Demand information is considered to be stochastic due to its time-varying nature and cost information is considered to be fuzzy due to its cognitive ambiguity. A hybrid algorithm based on chance-constrained and possibilistic programming is proposed to solve the problems. Considering the stochastic nature of demand information, solving the proposed model using the hybrid algorithm, the classification of items to three classes of extremely important, class A, moderately important, class B, and relatively unimportant, class C, items are determined along with a minimum inventory level required to deal with the stochasticity of demands information. The proposed approach is applied to a case study of classifying 51 inventory items. The obtained results assigned 22%, 39%, and 39% of the items to A, B, and C classes, respectively. Keywords Multi-criteria inventory classification Á Chance-constrained programming Á Possibilistic programming Communicated by V. Loia.

Nowadays, the importance of supply chain management and its effect on business performance is undeniable. Boosting competitive environment makes every single firm adopt an assignable supply chain strategy. This study is one of the rare practical researches that recognize key factors related to the application of a successful and efficient supply chain strategy. So far, many researchers have conducted studies on responsive supply chain strategy; but in this study, it is sought to focus on efficient supply chain strategies due to increasing need for organizations to enhance efficiency and reduce costs. Structural equation modelling using SmartPLS software is used to examine the research assumptions. Analysis of the structural model showed that there is a positive relationship between implementation of efficient supply chain strategy with supply chain performance; therefore the main research hypothesis is confirmed. Research revealed internal integration, top management support and information technology as efficient supply chain characteristics that have positive effects on supply chain performance. To reduce costs of implementation of efficient supply chain strategy, it is necessary to invest in factors that influence supply chain performance positively.