Identifying and Ranking Factors affecting the Successful Implementation of ERP by using Fuzzy Delphi and Fuzzy Analytical Hierarchy Process

The enterprise resource planning system is business process management software used to integrate the existing organizational information and used for the concentrated control and management of all facets of the operations. To successfully implement the enterprise resource planning systems, it seems necessary to identify and pay attention to the effective factors of its implementation. This study aims to identify and rank these factors by using fuzzy Delphi and fuzzy analytic hierarchy process. Based on the experts’ opinions, the effective factors in terms of the experts’ opinions are identified in the first step. These factors are then ranked based on the opinions of the experts of the tile and ceramic industry in Yazd. Eight main factors are identified and their priorities are the users, experts, organization, software, technical-technologies, cultural, managerial and economical dimensions, respectively.


Introduction
In the today's competitive world, the planning systems and the integrated databases constitute the essential components of the large enterprises.This requirement increases as the enterprises become larger.Enterprise resource planning is one of the most comprehensive information systems which have been recently employed.The capacity of ERP systems in integrating the processes and the information of different operating fields through a concentrated database led this system to be introduced as a prerequisite of success in the 21 st century.The ERP providers argue that their product has been examined several times and created based on frequent experiences.Finally, they will provide excellent solutions for different sectors of the industry.This reality is sustainable in many enterprises; however, the experiences reveal that these products are not much more useful in many other enterprises.Since the emergence of ERP, the success factors of ERP have been considered as the main challenges of the researchers .In the competitive markets, enterprise resource planning helps in enhancing the capabilities in response to the environmental changes.The enterprises seeking for quick changes in the market tend to achieve some advantages such as better communications with the customers, improved time cycle, higher quality, higher volume of sales, higher earnings, shorter time periods for developing the products and higher market shares.Because of the increasing pressure to implement the information systems based on cooperation between the business partners, it can be concluded that the successful employment of ERP might increase the efficiency of the supply chains.Therefore, identifying the effective factors of successful implementation of ERP has received increasing attention (Arabi et al, 2011).Since the introduction of ERP in 1990s, its application has been much debated in different fields in Iran.These studies have examined the organizational issues solved by this system and the advantages and disadvantages.Many studies have also reported a list of factors impacting the successful implementation of enterprise resource planning.The software, enterprise and management factors are among the most important factors (Francoise et al, 2009).The prior literature has shown that these factors have different rankings and classifications based on the diverse nature of the statistical populations.It must be mentioned that a fair insight about the effective factors of ERP implementation is achieved by more investigations in each country setting.Therefore, it seems necessary to conduct a study to enhance the insights of the managers, employees, researchers and experts of the enterprise resource planning.The remaining of the paper is organized as follows.The second section reviews the prior literature and the literature on the ERP system.The methodology is described in the third section.The findings are discussed in the fourth section and the suggestions are provided as the final section of the study.

Theoretical Framework Enterprise Resource Planning
Enterprise resource planning is a solution based on information technology, whichis used to manage the enterprise resources by an integrated high speed system with high quality to conduct the planning and operating process of the enterprise.Finally, ERP is an integrated system seeking for the more effective management of all resources and integrating the tasks and departments of an enterprise based on a computerized system by which it could meet the specific requirements.This is accomplished by a software package which makes it possible to share information and communicate with different sections of the enterprise.This software constitutes of several modules with different tasks.Most ERP software packages are so flexible that the buyers are able to install and employ some or all of the required modules.
ERP is a technology or system used for the more effective management of all resources in an enterprise.The resources are managed by the automation or integration of all processes and promoting the organizational efficiency (Berchet and Habchi, 2005, 588-605).

The Factors Affecting on the Successful Implementation of ERP
A complete listing of all success factors has been provided based on the prior studies and the main index and the subsidiary indexes are categorized as follows and a summary of the definitions is provided in the table below.

Research Questions
The first question: What are the factors affecting on the successful implementation of ERP by using fuzzy Delphi technique?The second question: What is the ranking of the factors affecting on the successful implementation of ERP by using the fuzzy analytic hierarchy process (FAHP)?

Research Methodology
This is a descriptive survey classified as an applied study in terms of the research objectives.The two populations have been considered in this study.To identify the factors by fuzzy Delphi approach, the university experts have been selected based on judgments and the opinions of the experts and professors in this field.To rank the identified factors based on FAHP, the top executives of the tile and ceramic industry of Yazd have been selected as the second population.

Analytic Hierarchy Process
Analytic hierarchy process (AHP) is a technique first introduced by Saaty to allocate the scarce resources and satisfy the planning requirements of the army: This technique has been known as one of the most popular multiple criteria decision making methods (MCDM) and used to solve the unstructured problems in different fields of human interests and needs such as politics, economics, social science and management.AHP is composed of six main steps as follows: 1. Defining the unstructured problems and clearly describing the goals and consequences.2. Converting the complex problems into a hierarchy structure by the decision criteria.3. Having a paired comparison of the decision metrics by the comparative scales.4. Using the eigenvalues of the comparison matrixes to estimate the relative weights of the decision criteria.5. Checking the consistency ratio of the scales to ensure that the judgments are integrated.Summing the relative weights of the decision criteria to calculate the final weights (Asian et al, 2009).

Fuzzy Set Theory
Fuzzy theory was first introduced by LotfiA.Zadeh in 1965 to solve the problems in which there are no clearly defined metrics.The uncertainty (fuzziness) of the human decisions should be considered; otherwise, the results might be misinterpreted.Fuzzy set theory has been growing in terms of different dimensions and divided into two approaches, including fuzzy sets as the mathematical problems and the linguistic approach.The main logic of the linguistic approach is that the real values are the fuzzy sets and the inference rules are approximate values.The triangular fuzzy numbers are special types of trapezoidal fuzzy numbers which are very famous in fuzzy applications.By defining the confidence interval at  level, the triangular fuzzy number is defined: The interval between two fuzzy numbers might be defined by vertexmethod.
are two fuzzy triangular numbers, the interval between them is as follows: A proper decision model should tolerate the uncertainty and vagueness, because the fuzziness is one of the general characteristic of the decisions.Because the decision makers often provide uncertain responses, it seems unreasonable to convert the qualitative preferences into direct estimates.AHP method which requires the selection of the values in pairwise comparison might not be sufficient.The uncertainty should be also considered in some of the pairwise comparisons.The fuzzy linguistic approach might account for the optimism or pessimism tendencies, because the fuzzy linguistic methods are preferred to be used to measure the utility.As a result, in the pairwise comparison environment, fuzzy AHP is prioritized over the traditional AHP method ( Yu, 1990Yu, ,2002)).

Using FAHP to weight the criteria
To calculate the weights of the barriers for implementing value added tax, fuzzy analytic hierarchy process is used.Six main steps should be taken in practice: 1. Create the analytic hierarchy process from the decision factors.Each decision maker is asked to describe the relative importance of each pair of decisions at one level in terms of a nine-point scale.The scores of pairwise comparison are collected and the pairwise comparison matrixes are formed fork decision makers.2. Consistency analysis: The priorities of the factors are compared by calculating the values and eigenvectors.
Where in; W is the eigenvector related to matrix A and the consistency index of the matrix is defined to make sure of the judgments in a pairwise comparison.The consistency index (CI) and consistency ratio (CR) are defined as below: Where in, n is the number of the compared items of the matrix and RI is the random index.Saati proposed that the upper bounds of CR for 3 × 3 matrix is 0.05; and 0.
The upper and lower bounds are defined as below: The matrixes of the upper and lower bounds are defined below: 5.The opinions of the decision makers are combined.Using geometric mean, the fuzzy weights are combined: The combined fuzzy weights of k decision maker is the number of the decision maker. , The weights of the barriers are determined and judged by the experts.Based on their weights, the barriers of implementing value added tax are identified.By collecting the opinions of the experts through a questionnaire, the pairwise comparisons of the decision criteria are made and the weights of the barriers for implementing value added tax are calculated based on FAHP (table4).

Chart 1 :
Membership of a triangular fuzzy number cAcademic Research in Business and Social Sciences February 2014, Vol. 4, No. 2 ISSN: 2222-6990 446 IJARBSS -Impact Factor: 0.305 (Allocated by Global Impact Factor, Australia) www.hrmars.comSource: Lee, A. & et al.,(2008) "A fuzzy AHP and SC approachfor evaluating performance of ITdepartment in the manufacturing industryin Taiwan", Expert Systems withApplications, Vol.34, pp.96-107.As shown in chart 1, the triangular fuzzy number is shown by (a,b,c) and its membership function is as follows: c are the lower and upper bounds.A significant issue in fuzzy sets is  -cut, which and for  -cut and c α isthe strongest cut and the definitive set is as follows: -cut of a fuzzy number is the definitive set of  M ~ which includes all elements of U set which their degrees of membership in M ~ is equal to  .Chart2. -cut of a triangular fuzzy number of M ~ Source: Lee, A. & et al.,(2008) "A fuzzy AHP and SC approachfor evaluating performance of ITdepartment in the manufacturing industryin Taiwan", Expert Systems withApplications, Vol.34, pp.96-107.International Journal of Academic Research in Business and Social Sciences February 2014, Vol. 4, No. 2 ISSN: 2222-6990 447 IJARBSS -Impact Factor: 0.305 (Allocated by Global Impact Factor, Australia) www.hrmars.com selected.The positive upper and lower bounds matrixes related to the decision maker 0   should be selected.Based on the matrix, the weight is calculated and then compute AHP of the weight matrix.
m the fuzzy weight matrix can be calculated for k decision maker and is defined as ) The fuzzy weights of the decision criteria from k decision maker.6.Use the final classification.Based on the equation developed by Wong et al (2006) aclose coefficient is defined for the classification of the decision criteria: Conclusion and DiscussionUsing fuzzy Delphi and opinions of the experts, the factors affecting on the successful implementation of ERP are identified: The managerial factors (financial support of top executives, delegation of authorities by the top executives, performance evaluation, planning, strategic thinking and leadership ability), the cultural factors (teamwork and participative culture and culture of adapting to changes), the organizational factors (firm performance background, reputation and credit of the firm among the customers and the predictive ability and planning capacity), technical-technological factors (the presence of the needed hardware and fundamentals), economic factors (implementation costs, technical support costs, consultant costs and hardware costs), enforcement costs (experience and working background, technical knowledge, the capacity of providing consulting services before enforcement), user factors (commitment, the training level, the working spirit of the user in using software and participation of the user) and software factor (supporting farsi language, defining the system information.General efficiency level, availability, ability to be remembered, preventing error and security).To rank the factors affecting on this step, the opinions of the top executives of tile industry are collected and the weights are determined by using FAHP and pairwise comparison matrix.The results are shown in the table below.Table5.Weight and ranking of the managerial dimensions