Suchergebnisse

International Journal of Advanced Computer Science and Applications(IJACSA), 8(11), 2017 ; Companies are facing different challenges in order to adapt to their environmental context. They should be aware of the changes on the social, political, ecological and economical levels. Moreover, they should act in an efficient and rapid manner by leveraging new and reconfigurable resources. Organizational agility is the firm's key dynamic capability which enables it to deal with changes and exploit them as opportunities. Firms' objective is thus to attain a higher degree of agility which can help them to perform durably. In this article, a new model based on analytical hierarchy process (AHP) method is proposed. This can help companies to raise their agility level by deploying the most suitable agility enablers which can be either general or specific when related to information technologies. They can thus develop the most appropriate strategy towards agility regarding their internal and external contexts. ; http://thesai.org/Downloads/Volume8No11/Paper_19-An_AHP_Model_towards_an_Agile_Enterprise.pdf

An enterprise resource planning (ERP) system is an integrated software solution, typically offered by a vendor as a package that supports the seamless integration of all the information flowing through a company. Business information systems is an area of the greatest significance in any business enterprise today. ERP projects are a growing segment of this vital area. The objective of customization in ERP implementation is to achieve a fit between the ERP system and the process that the system supports. Widespread literature review has been done to study the issues in ERP implementation. Customization is found to be the major annoyance in most of the ERP projects. Literature review also shows that the AHP is the preeminent slant among the various methodologies applied to ERP projects in the past for prioritizing the attributes. Hence, in this paper we have applied the analytical hierarchy process (AHP) to a framework for evaluating ERP implementation choices. The upshot of the study is the identification of various customization possibilities for ERP implementation. This study is meant to help managers think about the various feasible customization options available to them. The application of AHP to the framework is exemplified and the epitome of findings is discussed. Future research work that can be done in customization is also indicated.

AbstractThe problem considered here involves the selection of an alternative by a group of decision makers in a context that involves the aggregating of votes from a preferential ballot. A popular approach for solving such problems is the well‐known weighting problem formulation. However, with such a formulation two issues become of critical importance: (a) the weights should reflect the decision‐making group's belief on the importance of each rank position and (b) the weights should accord each alternative a fair (if not its best) assessment. Many researchers have studied this problem and proposed various solution strategies. None of these strategies, however, appears to have adequately addressed both issues. The objective of this research is to develop a group decision‐making model that solves the problem in a manner that adequately addresses the two critical issues identified, as well as allows for sensitivity analysis and is fairly robust with respect to the various paradoxes identified in voting systems.

AbstractWe consider first a variant of the analytic hierarchy process (AHP) with a one‐parametric class of geometric scales to quantify human comparative judgement and with a multiplicative structure: logarithmic regression to calculate the impact scores of the alternatives at the first evaluation level and a geometric‐mean aggregation rule to calculate the final scores at the second level. We demonstrate that the rank order of the impact scores and final scores is scale‐independent. Finally we show that the multiplicative AHP is an exponential version of the simple multi‐attribute rating technique (SMART). In fact, the multiplicative AHP is concerned with ratios of intervals on the dimension of desirability, whereas SMART analyses differences in the corresponding orders of magnitude.