Accepted: 28 February 2016 Achieving competitive advantage enables an organization to create a defensible position against its competitors. It also allows organizations to differentiate themselves from competitors. This study aims to investigate impact of knowledge management practices on supply chain quality management and competitive advantage in Alyaf Company, Iran. This research is functional in purpose and data gathering and data analysis is descriptive-correlation. The statistical population is consists of 25 company executives and experts in the supply chain of Alyaf Company; opinions of 68 of its members were used as a selective sample identified by simple random sampling method. Primary data was collected through questionnaire and structural equation modeling was used to assess relationships between variables. The results of structural equation modeling show a positive and significant causal relationship between knowledge management practices and supply chain quality management. Direct relationship between knowledge management and competitive advantage was not confirmed but the relationship between these two variables was confirmed indirectly.

No abstract

In this study, a novel method was proposed to predict the size and content of the nanoparticle aggregates/agglomerates in polymer nanocomposites based on the characteristics of the mixer, cohesion energy between nanoparticles and their content in the system. The internal energy equilibrium was evaluated by calculating the induced mixing energy by the mixer, aggregation, and agglomeration energies. An analytical model was designed to predict the tensile modulus of the system based on dispersion content and size of the aggregates/agglomerates. In addition, the tensile modulus of the aggregates/agglomerates was defined by developing Wacke's empirical equation. Two sets of PP and PA6 nanocomposite samples, containing 1–3 vol% of silica nanoparticles, were prepared and tested to verify the theoretical results. The applied nanoparticles were subjected to surface modification processes to maximize their compatibility with their surrounding polymer matrix. Different tests, including FE‐SEM, contact‐angle and tensile, were used to determine the mechanical/physical characteristics of the samples. The predicted results for the size of the aggregated/agglomerated domains were very close to those defined using FE‐SEM tests. On the other hand, the predicted tensile moduli based on the content, size and mechanical characteristics of the aggregated/agglomerated domains were acceptably accurate considering the tensile test results.

This paper develops an MILP model, named Satisfactory-Green Vehicle Routing Problem. It consists of routing a heterogeneous fleet of vehicles in order to serve a set of customers within predefined time windows. In this model in addition to the traditional objective of the VRP, both the pollution and customers' satisfaction have been taken into account. Meanwhile, the introduced model prepares an effective dashboard for decision-makers that determines appropriate routes, the best mixed fleet, speed and idle time of vehicles. Additionally, some new factors evaluate the greening of each decision based on three criteria. This model applies piecewise linear functions (PLFs) to linearize a nonlinear fuzzy interval for incorporating customers' satisfaction into other linear objectives. We have presented a mixed integer linear programming formulation for the S-GVRP. This model enriches managerial insights by providing trade-offs between customers' satisfaction, total costs and emission levels. Finally, we have provided a numerical study for showing the applicability of the model.

No abstract