Document2

5th International Conference on Enterprise Systems, Accounting and Logistics (5th ICESAL 08) 7-8 July 2008, Crete Island, Greece

A Survey on ERP Package Selection and Evaluation Methods and Frameworks

Leila Saroukhani, Arash Niknafs, Shahab Bayati and Zahra Saleki

Department of Information Technology, Tarbiat Modares University, Tehran, Iran [email protected], [email protected], [email protected], [email protected]

Abstract

Selecting the right ERP package for an organization is an important and critical issue which requires a thorough and careful evaluation of all possible choices. The difficulty and complexity of the factors influencing this evaluation process have made many managers and decision makers to look for a reliable and automated method of decision making, so that the accuracy, speed and comprehensiveness that they were looking for could be achieved. In this paper we are trying to review the methods that outburst after these needs and there will be some comparison between the methods. We will also talk about different dimensions of the selection and evaluation methods and after counting some advantage and disadvantages of some methods we provide some proposals and future works as new horizons of solution.

Keywords: ERP; project selection; MCDA.

1. Introduction

Many fields of industry are experiencing some kind of rapid changes which are mainly caused by the rapidly growing and changing technology (Dey, 2005). However, these changes in information and communication technologies have contributed too much of their worldwide success. In this rapidly changing environment success come after rapid and careful enough reactions. One of these reactions is selecting strategic project and software packages for an organization to obtain and sustain competitive advantage in comparison with its rivals within and outside its industry. In addition to this, the projects that a manager evaluates and finds worth funding should contribute to the organizations vision. Thats why selection and evaluation of projects especially strategic projects like ERP projects- become more important and critical. The decision to fund or not to fund a project becomes more vital, when its related costs (such as time, money and other resources) are high and its effects (after implementation) on organization are intense. Implementing ERP projects in an organization requires the consideration of different dimensions such as cultural, change management and etc.

ISBN CD-ROM PROCEEDINGS: 978-960-287-105-8

97


ERP (Enterprise resource planning) is the term for an information integrating system in an organization. And this information can range from financial, accounting, human resource information to even customer information (Davenport, 1999). ERP systems have recently been known as a strategic weapon for organizations which are dependent on and using information technology to a huge extend (Yang et al., 2007). Although there has been done a lot of work on ERP systems with vendors such as SAP, Oracle, PeopleSoft and other vendors there are still industries that lack an especially designed ERP (Yang et al., 2007). When companies from such industries decide to choose a package they face a lot of choices which are not the best and are not developed by the best vendors and they hardly contain best practices. So the selection of a good choice becomes more critical and time taking. That is the time when managers or decision makers get to the point that they should apply a full proof method that takes every single issue into account and in a short time helps them with the process of evaluation and selection. In the related literature there are some papers which discuss the formation of a portfolio of projects from a list of available solutions. But here we are talking about the frameworks used to help decision maker choose among a large number of possible choices while considering a large numbers of factors. Most of such frameworks are about R&D and ERP projects evaluation and selection. As discussed in (Wei et al., 2005) due to the changing environment and especial issues with ERP systems, the process of evaluating ERP packages is difficult. Implementing such projects (like ERP systems, etc.) is some thing more than installing an application. Every choice will affect the whole organizations shape and structure in a different way (Kumar et al., 2002). The proposed frameworks try to combine the experts knowledge with the accuracy and power of their algorithms to overcome such challenges with project evaluation processes. Before we go to section 2 we clarify our description of main concepts (ERP and MCDA) in this paper as they are indicated in different related research papers.

1.1. ERP (Enterprise Resource Planning)

There are many definitions for ERP or Enterprise Resource Planning like the one we point in introduction. The ERP system is an increasingly popular management tool. This is confirmed by the importance of research publication in management and business journals (Botta-Genoulaz et al.,2005) also we can say The ERP system was developed and derived from the previous MRP (Materials Requirement Planning) system and MRPII (Manufacturing Resource Planning) system (Yang et al.,2007). Nowadays, ERPs attempts to integrate all departments and functions across a company onto a single computer system that can serve all those different departments particular needs (Koch et al., 1999). It is also said it is an information system that manages and integrates all areas of a business like produce, plan, buy, manufacture, sell, distribute accounting and services (Scalle and Cotteleer, 1999). The key characteristics of ERP systems are summarized below (Chand et al. 2005). 1. ERP systems are off-the-shelf pre-written software with sufficient flexibility to integrate most of the business processes of an enterprise.


98


2. ERP systems are at least an order larger than any traditional business application software. They are large in terms of function point measure. They are large in terms of business functionality. They are large in terms of the data items in the database. They are large in terms of the operational and management reports that can be generated. 3. ERP systems are very complex. Besides the usual correlation between size and complexity, there is an inherent data structures complexity in ERP systems because ERP modules do not share data bypassing it from one module to another module but makes it available to different modules via common data structures. 4. ERP systems are built on generic business rules and procedures. Thus, each implementation requires tailoring and customizing the modules based on the business practices of the organization. This often entails reengineering many of the current business processes. 5. The organizational reach of ERP systems is wide, and therefore an ERP implementation requires dealing with a very large portion of the business operations of the organization. 6. ERP systems are costly to buy and more expensive to implement in an organization. One information planning decision involves project selection from among a portfolio of options. This involves multiple steps, including selection and weighing of alternatives. Choice and weighing on criteria become crucial in the selection of the projects to pursue. A survey conducted by the authors found that organizations with an expectation of future IS importance rely heavily on organizational goals, management support and environmental factors. Organizations with low strategic expectations of are rely more heavily on management support, political considerations, and risk. The results allow managers to position selection criteria according to their strategic use of information technology (Jiang and Klein, 1999). There are four classes of organization that have very different needs for IS and technology: Strategic organization, Turnaround organization, Factory Organization and support organization. So the IS professionals must be able to make more informed decisions on the IS mission and resource allocation for competing IS projects and pay more attention to these six subcategories of IS evaluation criteria : financial , organizational, competing, environment, technical, risk, and management(Jiang and Klein, 1999).

1.2. Multi criteria evaluation (decision) analysis

A number of methods have been applied to ERP or other information system (IS) selection including scoring, ranking, mathematical optimization, and multi-criteria decision analysis. The scoring (Lucas and Moore, 1976) method is intuitive, but too simple to truly reflect opinions of the decision makers. Buss (1983) proposed a ranking approach to compare computer projects. This method also has the same limitation with scoring method. Mathematical optimization such as goal programming, 01 programming, and nonlinear programming have been applied to resource optimization for IS selection. Santhanam and Kyparisis (1995, 1996) proposed a nonlinear programming model in the IS selection process. Lee and Kim (2000) combined Santhanam and Kyparisis model with analytic network process (ANP) and a 01 goal-


99


programming model to select an IS project. Badri et al. (2001) presented a 01 goal programming model to select an IS project considering multiple criteria including benefits, hardware, software and other costs, risk factors, preferences of decision makers and users, completion time, and training time constraints. However, the applicability of these methods is often weakened by sophisticated mathematic models or limited attributes to carry out in a real-world ERP system selection decision, especially when some attributes are not readily quantifiable, and not too easy for managers to understand (wei et.al ,2005). Select a portfolio of projects is a process that includes many sequence steps and it is not only summarizes in evaluating, ranking and optimization of them (ghasemzade, Archer, 2000), but also not a new method that mixed with fuzzy logic could solve many of these problems. This method that is named AHP3 was introduced by Saaty at 1980. After a while, a similar method with more and better advantages was created (visualdecision, 2008) that could be a new way for research in the future. This method, first presented by J.P.Brans at 1982, is now its very useful for recommended systems. All the methods discussed above investigate and compare projects from different areas like AHP, so they have multi-objective methods. These methods can be designed by Genetic Algorithm, Neural Network or fuzzy logic that use for solving multi-objective problems as revolutionary algorithm in (Coelo Coelo et al, 2007) book. The other model, that directly used for selection ERP Package, is Santhanam and Kyparisis (1995, 1996) model to optimize resource allocation allowing for the interaction of factors (risk , goals, financial advantages, available resources, interdependencies between other information systems that have existed in organization, dependency of resources and technical dependencies that play important roles in decision making for selecting an information system); illustrated that optimize previous model.

2. Literature review

In this section we will investigate the literature review in relationship with the topic of paper that the results will be illustrate in conclusion section.

2.1. General view approaches

Some approaches are applied to the process of buying and selecting a package and present some algorithm and factor for it.

Model of the ERP acquisition process (MERPAP)

Among general models, Verville and Halingten in 2003 applied a six-stage model for buying process of ERP software that is known as MERPAP (Model of the ERP Acquisition process). This model includes six steps as below:

1- Planning process: one of the major findings of this study is that the MERPAP, unlike the process (es) used for other types of organizational buying, includes a planning process during which the acquisition teams addressed as many issues as possible and planned the various activities and phases (processes) of the


100


MERPAP. The planning process of the MERPAP (MERPAP-P) contains seven categories. 1- Acquisition team formation: this first element played an important role in the success of each of the acquisition projects. 2- Acquisition strategies: The strategies that each team developed for the ERP acquisition helped reduce some of the uncertainty associated with this process, 3- Requirements definition, 4- Establish selection/choice and evaluation criteria, 5- Acquisition issues, 6-

2- sists of two principal elements: information

3- ate

4- E)

5- C), as a process, followed as a natural result

6- iness

process that was continuous throughout most of the MERPAP.

e other. Shields recommends them for selecting dy selection.

en developed. The final decision is determined by the highest total

Marketplace analysis, 7- Deliverables Information search process: It conscreening and information sources. Selection process: It consists of only two principal elements: EvaluRFI/RFP/RFQ Responses and Create Short list of Vendors/Technologies. Evaluation process: The evaluation process of the MERPAP (MERPAP-consists of three distinct areas of evaluation: vendor, functional, and technical. Choice process: Choice (MERPAP-of the abovementioned processes. Negotiations process: the negotiation process (MERPAP-N) of the MERPAP is divided into two types of negotiations, business and legal, and it is the busnegotiations

Shields approach

In (shields, 2001) approach, a suitable package have the situation below: 1-Fitness , 2- functionality, 3- flexibility with environmental change, 4- can be extended to work with other departments in organization, 5- good support services during implementation process,6- Hosting capabilities, 7- implement completely with after buying and support services These seven points are known as general characteristics of a package. Also buyer(producer) should have some characteristics that Shields illustrated in his paper, but we want to get familiar with factors and methods depending on packages, additionally he introduced a three based approach which includes: detailed requirement, key requirement and proof of concept for selecting a package or vendor. Now we should decide which approach is better than thcomplex, normal and spee

Wei and Wang approach

(Wei & Wang,2004) proposed a comprehensive framework for selecting an ERP project that combines data obtained from professional studies with that surveyed from interviews with vendors (external professional reports and subjective data obtained from internal interviews with vendors). A hierarchical attribute structure including project, software, and vendor factors has been provided for evaluating ERP projects. In their work, fuzzy set theory is used to aggregate the linguistic evaluation descriptions and weights. An integration model that uses the fuzzy average method and fuzzy integral ranking has beintegral value.


101


Karsak and Ozogul approach

(Karsak & Ozogul, 2007) developed a decision framework for ERP software selection based on quality function deployment (QFD), fuzzy linear regression and zeroone goal programming. Their proposed framework enables both company demands and ERP system characteristics to be considered, and provides the means for incorporating not only the relationships between company demands and ERP system characteristics but

ed to determine the ERP system alternative that minimizes the weighted sum of deviations from the maximum achievable

ak & Ozogul, 2007).

y and the relationships between them are identified. Their proposal also offers some advantages in comparison with the IEEE Std 1062/1998, as indicated in

he literature that can help us in decision making process or any person

e business goals and strategies of an enterprise. This method emphasizes on

aspects. For example, Schniederjans and Wilson (1991) utilized the AHP method to

also the interactions between ERP system characteristics through adopting the QFD principles. The developed framework integrates ERP characteristics obtained from vendors in the market and the list of customer requirements by taking into account the company profile and strategic selection criteria. Using QFD provides the means for incorporating the relationships between user demands and software characteristics and also the relationships between software characteristics disregarding the unrealistic preferential independence assumption frequently encountered in earlier IS selection studies using MCDM techniques (Karsak & Ozogul, 2007). The target values for ERP characteristics and the maximum achievable values for customer requirements are obtained using fuzzy linear regression. The ZOGP model is employ

values for company needs (Kars

Bueno and Salmeron approach

(Bueno & Salmeron, 2008) applied a Fuzzy Cognitive Map based approach capable of offering a definitively organized and structural outline in the acquisition of an ERP tool. Also, this proposed model offers a selection model where the more relevant criteria, their intensit

their paper.

2.2. Evaluating tools

When the organizational process of selecting package is applied, we should mix these factors to make a final decision. In this section we will illustrate two approaches which we presented in twho does that. The first approach is a mathematical tool and the other one is a managerial one. In (Wei et al,2005) presents a comprehensive framework for selecting a suitable ERP system. The framework can systematically construct the objectives of ERP selection to support thconsistency between objectives of the framework, which is guided by the company strategy. As we mentioned before The AHP method, introduced by Saaty (1980), determines how to determine the priority of a set of alternatives and the relative importance of attributes in a multiple criteria decision-making problem, and has been widely discussed in various


102


determine the relative weights of attributes and applied these weights to a goal programming model for IS selection. But the selection procedures of an ERP system based on Wei method are described below: Step1. Form a project team and collect all possible information about ERP vendors and

ctives to develop the fundamental-objective

asking specific questions, which are formulated

d.

Fig. 1 shows a flowchart for the ERP selection process as a complete framework.

Monitoring Balanced Scorecard

f the four BSC ERP implementation and ERP operational use are shown in Table 1.

Selection with BOCR approach

bout

systems. Step2. Identify the ERP system characteristics. Step3. Construct a structure of objehierarchy and means-objective network. Step4. Extract the attributes for evaluating ERP systems from the structure of objectives. Step5. Filter out unqualified vendors byaccording to the system requirements. Step6. Evaluate the ERP systems using the AHP methoStep7. Discuss the results and make the final decision.

(Chand et al, 2005) use balanced scorecard (BSC) to evaluate ERP packages. The main ability of this method is when non-functional measures about customers satisfaction, internal processes and ability to innovate and learn are combined with financial measures, they assure future financial results. The application of balanced scorecard has been examined in the context of Information Technology (IT) and information systems and four balanced scorecard dimensions of customer, finance, internal business processes and learning and growth as user-oriented are operationalized, although BSC was conceptualized as an approach for strategic management of a firm in which they partition the ERP strategic management processes into a management of ERP implementation and management of operational use of ERP software and they propose a separate balanced scorecard for each part, however, there is an important point and it is, if balanced scorecard dimensions do not connect to the business goals and organizational strategy this approach will direct us to fail, but if they align with each other they will make value for organization. They key question for identification of measures in each o

(Liung and Li, 2007) provide another approach for project selection, Analytic Network Process (ANP) is used to make decisions with regard to benefits (B), opportunities (O), costs (C) and risks (R). Then this decision method is examined by a case study of MES project selection in Chinese undershirt manufacturer although, this case is aenterprise information system project selection but it can be used in broader areas. In many researches and studies benefits, opportunities, costs and risks have been discussed. Financial approaches such as return on investment (ROI), net present value (NPV) and internal rate of return (IRR) have two limitations: 1. they only consider tangible or monetary effects and skip intangible ones. 2. Because the calculation of ROI


103


or NPV or IRR is relatively complex and it is completed mainly by professional financial personnel. The decaled approach is directed to solve these problems. This method involves these steps: 1. Perform enterprise diagnosis. 2. Compare with exemplars 3. Verify problems needed to be overcome and basic function required. 4. Construct the BOCR decision model. 5. Make pair comparisons. 6. Calculate outcomes and make nalysis.

Table 1. Question for ERP performance

a

ERP implementation ERP operation

Financial t of RP implementation?

l?

What is the detailed cosE

What is the financial input necessary for achieving targeted performance leve

Customer he ertain level

Internal process prove usiness

rocesses?

nt in

by

Innovation and learning ntegrate future

hanges?

r future ustomer needs?

Does the ERP softwareefficiently support tindividual needs? Does ERP software imthe internal b

What benefits derives the company from a cof performance? Are internal processes effective and efficieassessing level of performance determined

p

customer perspective? Does ERP system have enough potential fo

Is ERP software flexible enough to ic c

Project selection: Process Analysis

and odification; 3. Project and proposal presentation; 4. Project selection for funding.

2.3. Performance prediction systems

Companies involved in rapidly changing market are interested in value collaborative efforts aimed at realization of shared benefits. In (Daniel et al, 2003) the project evaluation process employed by the most successful industries were discussed university research center sponsored by national science foundation. The whole paper focused ion the process management issues involved in the formulation and evaluation of research proposals, structural advantages and liabilities associated with the process. These processes are strategically significance, because they define the organization research agenda, focus resource allocations by linking capabilities and commitments and from the performance assessment process. There are four major components in the project evaluation process: 1. proposal generation; 2. Proposal refinementm

There exist many prediction systems that were discussed in (Stensrud, 2001). Tools for prediction of functionality of ERP packages importance and value of these systems are


104


divided into three ways and they can help us in making decision: 1. their ability to ERP projects; 2. their added value to human user beyond making a prediction; 3. their

prediction systems are: CBR1, ANGEL, ACE, ESTOR, neural networks,

differences are based on users requirements, goals and ERP

in criteria according to literature review. 2. Developing a pilot test using 30 key users.

2.4. Neural Networks and SCM3

SCM and ERP and mentioned that integration is necessary for strategic management.

2.5. Localization and cultural consideration

competence and correctness. The performance prediction is divided into two main categories parametric and non parametric. They have been discussed in (Stensrud, 2001). Parametric prediction systems provide a mathematical relation between response variables and predictor variables. Some useful parametric prediction systems that can be used for ERP projects are linear regression models, COCOMO 2.0, COCOTS, REVIC, and Checkpoints. Some non-functional CART, OSR2. A new approach for researches in this field was introduced by (Wu et al, 2007). In that paper they introduce a method for ERP package selection based on computing distances between ERP package and firms requirements. This method helps organization to the location of difference and finds the importance in measuring risks in a simple way. Thesepackage capabilities. The basic challenges in ERP package implementation is in the relation between IT and organization society (Wu et al, 2007). Estimation of ERP success in the view of key users is another way that can helps decision makers to predict functionality of packages in organizations. ERP systems are complex and expensive. Initial analysis of ERP systems characteristics are important for the environment were explored and some users satisfaction instrument were selected for examination using rigorous and systematic interview techniques and iterative developing method. In this method a questionnaire was developed and its validity and reliability was proved. This study has two phases: 1. preparing ma

In addition to the prediction role of neural networks in the last section, we have found a paper using neural networks for analyzing packages from SCM perspective. (Chang et al, 2007) introduce a neural networks evaluation method for ERP performance from SCM perspective. This model can help firms to evaluate their cooperators; the required data were collected from a textile company in Taiwan. The learning theory is based on strategic thrust theory and uses back propagation network as an evaluation tool. The back propagation uses as a tool to reach organization personnel and consultant knowledge, although (Tam et al, 2002) focused on integration of

1 Case Based Reasoning 2 Optimized Set Reduction 3 Supply Chain Management


105


An important thing that should be mentioned in selection and evaluation of ERP package, vendors and also in ERP projects implementation is the cultural and regional role which may conduct to two different results in two different countries or organizational culture. (Yang et al, 2007) expands this topic, in this paper condition of Taiwan and Canada was studied and analyzed. In a report that is about 10 companies in Canada. the three major factors that influence selecting ERP package and vendors were discussed. Another research implemented through 20 Canadian companies shows three important factors including: adequate information systems, accessibility of solution four the business, integration of parallel. Another key factor, important only in Asian countries

k of professional and then shows some solutions for solving ese problems including selecting right package, selecting good team, BPR, education

and outsourcing, ASP4.

is culture, Differences between the culture of ERP package developers and Asian company shows the necessity of localization. In implementing ERP packages three main factors play important role: human resource, technology and process. The implementation of ERP packages in developing countries is complex because of high cost, long time, business process reengineering (BPR). (Yussef et al, 2006) have introduced some problems of implementing ERP projects in China including support of senior manager, high costs and long time. Different culture technical complexity, lacth

4 Application Server provider


106


Fig 1. Comprehensive ERP system selection framework

In small firms major factors are financial, human resource and technical factors. Based on (Yang et al, 2007) research in Taiwan main problems in implementing ERP systems are complexion of work processes. Seven key factors that are important for implementing ERP are system coding, BPR, ERP implementation priorities in the case of tasks, localization, cooperators, consultant, performance and contactors, also this problems can be seen in vendors and IT personnel and education. An important note is that within all evaluation criteria each factor that is related to education of end users is the most important one (Harmon, 2003) told that based on a research data that was gathered from Gartner Groups (Harmon, 2003) argued that implementation of an ERP is a BPR problem so educating users is an important factor to select packages and vendors.


107


3. Conclusion and Future Work

Evaluating and selecting and ERP package which fits the organizations needs and also satisfies different criteria is a complicated process. It is also one of the most important and strategic decision making processes that a manager may go through during his/her management period. It seems that the ERP systems -as they are nowadays- have not been produced before. They are more popular and more vendors are offering such systems in their new integrated form. Due to the recent growth of ERP systems production, the evaluation and selection frameworks emerged. Thats why the literature about the package evaluation and selection is not as old as the dawn of ERP-like systems. As we mentioned before, performance prediction is a category of evaluation methods. There are two types of performance prediction methods which a comparison between these two is illustrated as following:

Table 2. A comparison between parametric and nonparametric methods

Parametric Non- parametric Relationship between the predictor variables and

response variable, e.g. number of interfaces and the effort to produce

them

Make a priori assumptions (express the relationship in mathematical form ) e.g. the expected effort increases monotonically with size

Make no a priori assumptions (they approximate arbitrary functions) e.g. makes no such assumption

Overfitting

---

Arbitrary function approximators suffer from overfitting problem s which are related to the problem of filtering stochastic noise

Trustworthy More confidence Less confidence

Added value

Help user to understand the data by providing an abstraction, or reduction, of the data set. i.e. aid in confirming or rejecting hypotheses regarding returns to scale.

Assist the user in understanding the data by drilling down into the individual data points, i.e. assisting in exploratory data analysis.

Applying the lesson learnt and experts knowledge to the evaluation and selection processes is what every body desires for. Although in (Chang et al., 2007) there has been a solution to such an issue but its clear that still there can be done a lot more with neural networks and genetic algorithm learning methods. These methods facilitate the


108


use of lesson learnt and knowledge in decision processes. Some of their contributions to this issue are discussed in (Menhaj, 2003). If we look at the problem of selecting a package as a multi criteria decision making then we may consider AHP and PROMETHEE as two of the most common solutions to this problem. There are some works that use AHP as the basis of their proposed framework. (Macharis et al., 2004) compares the AHP and PROMETHEE and suggests that in many cases -as in this case- the PROMETHEE method outperforms the AHP method. So the application of PROMETHEE method can be considerable future work. As we saw BSC was used as an evaluating tool. Where BSC is used the dashboard idea comes to mind. Dashboard is another tool for control management in information technology. It provides little details but it can be used like BSC in decision support systems to design systems that can help high level managers infer and decide easily and fast. The amount of literature about cultural and regional issues indicates that the soft side of the environment in which the decision is being made is an important issue. It suggests that not every framework is supposed to work properly in an especial culture and country. It also indicates that not only in countries but also in different organizations with different cultures we should be aware of system implementation methods and consider that a previous successful implementation of a framework in an organization does not mean that it will be successful in our organization too.

References

Botta-Genoulaz, V. Millet, P.A. Grabot, B. (2005). Survey paper : A survey on the recent research literature on ERP systems, Computers in Industry, 56, 510522.

Bueno, S., Salmeron, J., (2008). Fuzzy modeling Enterprise Resource Planning tool selection. Journal of Computer Standards & Interfaces, (30), 137-147.

Chand, D. Hachey, G. Hunton, j. Owhoso, V. Vasudevan, S. (2005). A balanced scorecard based framework for assessing the strategic impacts of ERP systems, Journal of Computers in Industry.

Chang, C. Hwang, H. Hung, M. Chen, S. Yen, D. (2007), A Neural Network Evaluation Model for ERP Performance from SCM Perspective to Enhance Enterprise Competitive Advantage, Journal of Expert systems with applications

Coelo Coelo, C.A. Lamont, G.B. VanVeldhuizen, D.A. (2007). Evolutionary Algorithms for solving Multi-objective problems, 2nd Edition, New York, NY, Springer.

Daniel, H. Z., HEMPEL, D. J. & SRINIVASAN, N. (2003) Project selection: A process analysis. Industrial Marketing Management, 32(1), 39-54.

Davenport, T. (1999). Putting the enterprise into the enterprise system, Harvard Business Review, pp. 121131.

Dey, P. K. (2005). Integrated project evaluation and selection using multiple-attribute decision-making technique, Int. J. Production Economics, 103,90103.


109


Esfahanipour, A. (2005). A framework for decision support systems based on intelligent agents

for stock exchange, Phd Thesis, Industrial engineering department, Tarbiat modares university.

Ghasemzadeh, F. Archer,N. P. (2000). Project portfolio selection through decision support, Decision Support Systems, 29.7388.

Harmon, P. (2003). Business process change : A managers guide improving, redesigning and automating processes, San Francisco, CA, Morgan Kaufmann Publishers.

Jiang, J. J. & KLEIN, G. (1995) Project selection criteria by strategic orientation. Information & Management, 36(2), 63-75.

Karsak, E., C. Ozogul (2007). An integrated decision making approach for ERP system selection, Journal of Expert Systems with Applications.

Koch, C. Slater, D. Baatz, E.(1999). The ABCs of ERP, CIO Magazine, ERP research Center, available from http://www.cio.com/forums/erp/edit/122299-erp.html.

Kumar, V., Maheshwari, B., Kumar, U., (2002). Enterprise resource planning systems adoption process: A survey of Canadian organizations. International Journal of Production Research 40, 509523.

Liang, C., LI, Q. (2007) Enterprise information system project selection with regard to BOCR. International Journal of Project Management.

Lucas, H.C. Moore Jr., J.R., (1976). A multiple-criterion scoring approach to information system project selection. Infor. 14 (1), 112.

Macharis, C., SPRINGAEL, J., BRUCKER, K. D. & VERBEKE, A. (2004) PROMETHEE and AHP: The design of operational synergies in multicriteria analysis. Strengthening PROMETHEE with ideas of AHP. European journal of operational research, 153, 307-317.

Menhaj, M. B. (2003). Computational Intelligence, Tehran, Amirkabir University of Technology center of publication.

Santhanam, R. & KYPARISIS, J. (1995) A multiple criteria decision model for information system project selection. Computers & Operations Research, 22(8), 807-818.

Scalle, C.X. Cotteleer, MJ. (1999), Enterprise resources planning (ERP). Boston, MA: Harvard Business School Publishing.

Shields, M.G. (2001). E-Business and ERP: Rapid Implementation and Project Planning, New York, NY, John Wiley & Sons, Inc.

Stensrud, E. (2001). Alternative approaches to effort prediction of ERP projects, Information and software technology, 43, 413-423

Verville, J. Halingten, A. (2003). A six-stage model of the buying process for ERP software, Industrial Marketing Management, 32, 585 594

VisualDecision Co. Compairing PROMETHEE to AHP (2008), Accessed on Jan. 2008, Available from: http://www.visualdecision.com/promethee_vs_ahp.htm .

Wei, C. Chien, C. Wang, M. J. (2005). An AHP-based approach to ERP system selection, Int. Journal of Production Economics 96,4762.

Wei, C., Wang, M. (2004) A comprehensive framework for selecting an ERP system. International Journal of Project Management, (22), 161-169


110


Wu, J.-H. & WANG, Y.-M. (2007) Measuring ERP success: The key-users viewpoint of the ERP

to produce a viable IS. Organization Computers in Human Behavior, 23(3), 1582-1596. Wu, J.-H., SHIN, S.-S. & HENG, M. S. H. (2007) A methodology for ERP misfit analysis.

Information & Management, 44(8), 666-680. Yang, J. Wu, C. Tsai, C. (2007). Selection of an ERP system for a construction firm in Taiwan: A

case study, Journal of Automation in Construction 16, 787796.

Yusuf, Y., GUNASEKARAN, A. & WU, C. (2006) Implementation of enterprise resource planning in China. Technovation, 26(12), 1324-1336


111

Documents

Document2