Nasim Ekram Nosratian; Mohammad Taghi Taghavi Fard
Abstract
Supply Chain Management (SCM) is an integrated system of planning and control of materials and information, including suppliers, manufacturers, distributors, retailers, and customers. Chain performance measurement is an important issue in SCM. Also, given that the information plays a key role in improving ...
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Supply Chain Management (SCM) is an integrated system of planning and control of materials and information, including suppliers, manufacturers, distributors, retailers, and customers. Chain performance measurement is an important issue in SCM. Also, given that the information plays a key role in improving supply chain performance, the kind and amount of information sharing should be investigated. In this paper, the effect of information sharing on supply chain performance will be evaluated. In this way, 17 different scenarios of information sharing are defined and ranked using the cross-efficiency method. Finally, values for different scenarios using simulations and Rockwell Software Arena V5 are reported. The obtained results show that the proposed model is quite valid and efficient and can be easily applied to real-world cases.
Mehrdad Navabakhsh; Nasser Shahsavari Pour
Abstract
Until the 1980s, the system for assessing the performance of organizations with specific structures has been based on economic and financial indexes. The previous methods that were frequently used for performance assessment were mainly focused on the economic-financial aspects of the organization. However, ...
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Until the 1980s, the system for assessing the performance of organizations with specific structures has been based on economic and financial indexes. The previous methods that were frequently used for performance assessment were mainly focused on the economic-financial aspects of the organization. However, at present, due to vast human needs, sensitive cognitive, fundamental parameters in social organizations that are based on realities, are very effective, and meet scientific criteria have come into vogue. These parameters rely on experience, observation, experiment, hypothesis, and theory. Balanced Scorecard (BSC) seeks to make a balance between financial and economic objectives as outcomes of past performance (past-oriented indexes) and three indexes of customer processes, learning and growth, and development of human and social forces (future-oriented).Data Envelopment Analysis (DEA) is a non-parametric method for measuring the outputs or efficiency of homogeneous units with different inputs and outputs. However, in cases where there are numerous inputs and outputs with some similarities, their efficiency can be measured by two-level DEA, i.e., classifying them and using common weights.In primitive social institutions, the inputs of social systems are mainly limited and clear. However, in modern, complex, standardized systems, the input is both expanded and diversified. Therefore, in this paper, we have tried to use BSC as an instrument for designing performance assessment indexes and two-level DEA as an instrument for measurement.
Reza Rasinojehdehi; Seyyed Esmaeil Najafi
Abstract
Network security is paramount in safeguarding the integrity of computer networks and the data they host. The primary objective of network security is to protect data from cyber-attacks and ensure the overall reliability of the network. A robust network security strategy deploys various solutions to shield ...
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Network security is paramount in safeguarding the integrity of computer networks and the data they host. The primary objective of network security is to protect data from cyber-attacks and ensure the overall reliability of the network. A robust network security strategy deploys various solutions to shield data within networks, safeguarding both users and organizations from potential threats. This paper introduces a novel approach to evaluating computer network security using Data Envelopment Analysis (DEA), a mathematical method designed to measure the performance of Decision-Making Units (DMUs) employing identical inputs to yield identical outputs. We present a practical application of DEA to assess the security of 10 distinct networks, treating them as DMUs. The resulting performance measurements allow us to classify computer network security into four levels: "terribly insecure," "insecure," "safe," and "very safe. To optimize the discriminating power of DEA, we employ Principal Component Analysis (PCA) to reduce the number of inputs and outputs. It not only enhances the precision of our evaluation but also ensures that the number of DMUs remains well-suited to the analysis. As a rule of thumb, the number of DMUs should be at least three times larger than the sum of the numbers of inputs and outputs to maintain DEA's discriminating power. Through the combined application of DEA and PCA, this research contributes a comprehensive and efficient method for evaluating and classifying computer network security, providing valuable insights for enhancing overall network resilience against cyber threats.
