applying fuzzy sets for erp systems selection within ...

APPLYING FUZZY SETS FOR ERP SYSTEMS SELECTION WITHIN THE CONSTRUCTION INDUSTRY M. P. Barreiros 1, A. Grilo2, V. Cruz-Machado2, M. R. Cabrita2 1

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YKK, Portugal UNIDEMI, Departamento de Engenharia Mecânica e Industrial, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Portugal procurement [9]. A four phase implementation method has been proposed to obtain information and to help to make necessary decisions. These processes include: self-evaluation for the feasibility of ERP implementation; request for quotation; ERP evaluation and ERP contract and negotiation [11].

Abstract: Construction companies over the last years the have been implementing ERP systems to integrate their business processes and to become more efficient. Due to the complexity of the factors involved in the construction industry, the selection of an ERP system is a difficult process. This paper proposes a methodology applying the fuzzy set theory to the selection process an ERP system for companies within the construction industry.

2.1. Critical success factors for ERP implementation The selection process is a critical factor for successful implementation of ERP systems. Many companies fail to evaluate whether a software system is adequate to the company's strategy and business processes. One explanation for this failure might be that companies define the system requirements without the necessary knowledge of ERP systems and about the ERP software market, selecting by comparison with other companies who have also purchased ERP systems and have succeeded, without taking into account the uniqueness of each company’s business processes, resources and strategies.

Keywords: ERP systems; Information Systems; Fuzzy Sets, Construction Companies

1. Introduction The construction sector is considered to be one of the most highly fragmented, inefficient and geographically dispersed industries [2]. Over the last years construction companies have been implementing ERP systems to integrate their business processes to become more efficient. The selection of a ERP solution can increase the chances of success in adopting the ERP systems. Selection is therefore a critical factor for successful implementation.

For a successful ERP implementation and adaptation, Chung has conducted extensive surveys [2], demonstrating that intention to use and quality are associated with ERP implementation success. The factor that promotes the adoption of these systems is the usefulness of the ERP. These systems should be seen as useful to increase the chances of ERP success.

Whenever the selection of a software package is poorly made, the inadequacy of the systems solution to a company’s processes and strategies will imply major changes, leading to resource consumption of the company, and it becomes a high risk endeavor. The mismatch puts at risk the successful implementation of ERP and the company's survival. Due to the complexity of the factors involved, specially within the construction industry, there is no unique and unequivocal method for ERP system selection. This paper proposes a methodology focusing mainly on construction industry through the application of the fuzzy set theory and considering the critical success factors for ERP implementation. However, the methodology, with adaptations, can be can be used in the selection of an ERP in any industry.

The analysis of the data of the survey shows that function, subjective norm, output, perceived ease of use, and result demonstrability were highly associated with perceived usefulness and based on this result, the study gives recommendations to raise usefulness of the ERP. Function - Functions of the ERP system should cover the company’s important business functions and processes. It is also important to select the ERP that can support the critical functions of the company. Subjective norm - All workers and managers in the company should use the ERP in order to increase the company’s business value and productivity. Output - To increase the feasibility of using the ERP, the company should improve the quality of the product during its implementation, especially in the management and performance reports. Perceived ease of use - The ERP system should be easy to use A complex system is less useful, and also makes users hesitant to use it. Results demonstrability: The Company must define what the positive results that can be expected using the ERP, before or during their implementation.

2. Enterprise Resource Planning (ERP) Systems Enterprise Resource Planning (ERP) software systems are aimed at the integration of business processes and functions of a company. They allow a comprehensive view of any business, enabling data sharing and practices in real time. [8] ERP systems may contribute to the total integration of information flows within a company, within and crossing functions like finance, accounting, human resources, supply chain and

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for the system to accommodate expanded management functions. As time goes by, other functional modules and new users may be added to the system. Remotely accessible: Each project is constructed on a specific site. Remote accessibility enables project managers and other site personnel to remotely access central information and obtain the updated project progress information. Transparent: The construction industry is traditionally resistant to new technology. One of the effective strategies to overcome this obstacle is to provide a self-explanatory mechanism in the system to allow users to trace down relevant reasoning for decisions or recommendations resulted in the system. Reliable and robust: Correct historical cost data must be retrieved from the cost database for supporting estimating; a purchase order must be reviewed and be approved in a right sequence, etc..

2.2. Usability of ERP systems The project-based nature of the construction industry, has many different players involved, with different levels of training and expertise that also generate and require different types of information. Hence, it is necessary to adopt ERP systems that are accessible to most of these users. This should be taken into special consideration to the usability of these systems. The Enterprise Resource Planning systems have generally complex interfaces, and despite the expected benefits of their implementation, these systems have been classified as very complex [1]. It is necessary to implement user-interfaces that are easy to use, easy to learn and that support the needs of users [1]. The usability criteria proposed are [1]: Navigation and access to information which will enable access to information, menus, reports, options effectively; Presentation: another of the criteria identified in usability survey of ERP systems is that the screen is complex and the output is difficult to understand and interpret; Task support: often a lag between the ERP system and business processes produces more complexity and resistance to the use of these systems. Learn ability: ERP systems are generally considered complex to learn and use. [8]; Customization: an important factor of ERP is to be customizable.

3. Fuzzy sets The specificities of ERP for the construction sector, and particularly for contractors, let us consider that for the ERP selection there shall be a specific methodology that is not so much based on precise requirements analysis, but rather being able to deal with more fuzziness selection process. The theory of fuzzy sets was introduced by Zadeh in 1965 as a mathematical theory applied to diffuse concepts. Thereafter, the application of this theory in information systems has grown [13]. A fuzzy set can be defined as a class with fuzzy boundaries. If X is defined as the universe of members i.e. X = {x1 , x 2 . . . . . X n } , , and Y the fuzzy set of X, then:

2.3. ERP systems Use in Construction Companies To facilitate various users in the construction industry in accepting and using the system a set of criteria may be considered. Hence, an ERP system should have [9]:

Y = {( x1, fy ( X1 )), ( x2 , fy ( X 2 )), ... ,( xn , fy ( X n ))},

Project-orientation: Every construction project is expected to be completed on time and within budget. The ERP system should be able to manage different projects and to be able of reporting and predicting the status of each project, and on an aggregated perspective. Integrated: Construction companies have front-office functions (e.g. on-site). In an ERP system these front office functions should be integrated with back-office, and able to work off-line and on-line. Every office should have access to the same information according to their functions and needs. Paralleled and distributed: Multiple management functions are concurrently carried out by managers in various offices across a company. Therefore, an integrated ERP system must use parallel and distributed technology in order to support multiple concurrent applications or requests. Open and expandable: Applications are needed for supporting management functions and will vary significantly from company to company. An open and expandable architecture allows a company to tailor applications to fit the business needs. Meanwhile, new applications can be added. Scalable: An ERP system must be able to facilitate the strategic development of a company for many years to come. Scalability is reflected in the need

And fA is the degree of membership of xi in Y. If the universe of members is an infinite set, then the fuzzy set of Y is: A=

∫

fy (xi )/x i , x i ∈ X. [11]

The fuzzy set theory can be applied to ERP evaluation and selection. The attributes can be classified in three classes: critical; objective and subjective [10]. The critical criteria are the important attributes that each ERP must have. The objective attributes can be defined in monetary terms. These attributes can be: ERP package costs; IT costs and consulting costs. The objective factors can be expressed in monetary terms, so they not constitute a problem in selecting ERP software. Subjective attributes are expressed in qualitative terms and therefore they are more difficult to evaluate. With the fuzzy set theory the subjective criteria can be converted into quantitative measures that are easier to evaluate. The subjective terms can be expressed in

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satisfaction levels. These levels vary normally from “Extremely good” to “Extremely bad”. These levels can be adapted to a particular situation. A table with eleven satisfaction levels has been proposed to evaluate, and then define a mapping function T, which maps a satisfaction level to the maximum degree of satisfaction of the corresponding satisfaction level, where T: X →[0,1] [5].

accordance with his opinion regarding to each factor. Both subjective and objective criteria were evaluated. TABLE 2 EVALUATION FOR EACH CRITERION

A method proposed assumes five-point numerical values [10]: minimum; two modal values and a maximum weight (Table 1). With the fuzzy set theory, the subjective terms are converted to quantifiable evaluations that generally take a triangle or a trapezoidal shape with different weighs.

The linguist rating from each decision maker was then aggregated for each criterion. In this case the aggregated values are showed in the Table 2. For each criteria were calculated the aggregate value of all decision makers weights attribution in order to form a new distribution with a minimum, modal and maximum values. In the case for criteria C1 the lower bound is calculated as:

TABLE 1: SATISFACTION LEVELS

Lower bound =

F + I + VI + I 0, 2 + 0,5 + 0,7 + 0,5 = = 0, 475 4 4

This calculation is based on Table 1 and Table 2. For the same decision vector is calculated the middle and upper bounds, with a triangular distribution: 4. Case Study of Evaluation and Selection of an ERP System Based on Fuzzy Sets

F + I + VI + I 0, 5 + 0, 7 + 1 + 0, 7 = = 0, 725 4 4 F + I + VI + I 0,8 + 1 + 1 + 1 Upper bound = = = 0,95 4 4

Middle weights =

The studied company, designated as EM for anonymous purposes, is a general contractor in Portugal. The company belongs to a group that was established in 1978 and operates in different business sectors. The selection of the ERP system was made using the fuzzy set theory and following the following steps: selfevaluation for the feasibility of ERP implementation; request for quotation; ERP evaluation and ERP contract and negotiation. This paper is focused mainly on the selection process of the ERP.

TABLE 3: WEIGHTS OF CRITERIA

In the evaluation process were selected the criteria to evaluate the ERP systems (Ci). The criteria were divided into subjective and objective categories. In this case, the criteria selected were: Subjective: C1function; C2 - Subjective norm; C3 – Output; C4 Perceived ease of use; C5, Result demonstrability. The objective criteria were ERP system costs and consulting costs.

4.2. Evaluation of relative weight of each ERP relative to each subjective criterion The decision makers evaluated then each criterion relative to each possible ERP system using the linguistic attributes The evaluation of each possible ERP is: Very Bad (VB); Between Very Bad and Bad (BVB & B); Bad (B); Between Bad and Fair (BB & F); Fair (F); Between Fair and Good (BF & G); Good (G); Between Good and Very Good (BG & VG) and Very Good (VG). The evaluation weights is showed in Table 4.

4.1. Evaluation of the relative weights of criteria Each criteria was classified in accordance with the following weights: Very Important (VI); Important (I); Fair (F); Weak (W) and very weak (VW). The weighs were determined by the decision makers selected for the evaluation of the ERP systems (Di). Each decision maker gave a linguist rating for each criterion in

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case, the costs criteria) need to be converted into a dimensionless form. The ERP with the minimum cost should have the highest rating. The data can be converted with the following formula:

TABLE 4: LINGUISTIC ATTRIBUTES

t i = {t i × (t1−1 + t 2 −1 + t 3 −1 + ...t n −1 )} −1

tn can be defined as the cost factor for ERP n, and ti as the sum of the costs. Rn is the total relative cost. 4.4. Calculation of the total cost for each alternative ERP system The objective criteria of cost were then evaluated. Four values for each possible ERP system were determined, estimating the costs. For example, for the ERP system 1, the consulting costs are 3, 5, 6 or 7 monetary units. Estimates of the costs of ERP package (t1), IT equipment (t2), consulting costs (t3) and total (ti = t1 + t2 + t3) for the three systems are presented in Table 7:

In Table 5 is depicted an example of aplication os the linguistic attributes for ERP system 1. TABLE 5: EVALUATION OF THE ERP SYSTEM 1

TABLE 7 OBJECTIVE CRITERIA

If Sij was the weight given by decision maker i for criteria j, the lower, middle and upper bounds can be determined as follows for ERP system 1. For ERP system 1, the lower limit of the total cost is the sum of the estimates of lower cost, 12 + 8 + 3 = 23. Total costs are then inverted and expressed in percentage in accordance with table 7. The higher cost occupies now the last place and with values greater than unity. The figures for each ERP are shown in the second column of the table below. For the ERP 1 the values and their ranking are: 100/27= 3.70; 100 / 26 = 3.85; 100 / 25 = 4, 100 / 23 = 4.35. The totals in the last line, the sum of the values are lower, intermediate and higher in each ERP and correspond to the distribution of the objective criterion. For example, 3.70 + 3.70 + 4 = 11.4 is the lowest value. Dividing the value calculated earlier, reversed the lower cost, intermediate and higher, every ERP, the lower value, intermediate and higher, respectively, the distribution of the objective criterion, we obtain the distribution of the final ranking of the ERP systems, for criterion C6, SiC6 indicated in the last column of the table above. For the lower bound of ERP 1: 4.35 / 11.41 = 0.38.

For S11, the lower bound of is given by: Lower bound =

0, 6 + 0,6 + 0,3 + 0 = 0,375 4

The middle and upper bounds were given by: 0,8 + 0,8 + 0,5 + 0,2 = 0,575 4 1 + 1 + 0,7 + 0,7 Upper bound = = 0,85 4

First middle bound =

TABLE 6: FINAL CLASSIFICATION

TABLE 8: INTERMEDIATE CALCULATION

4.3. Objective criteria The objective criteria for the evaluation of the ERP systems were: Package cost; IT equipment cost and Consulting cost. These costs were estimated by RFQ. For ERP 1 the acquisition values would be between 3 and 7. The objective and subjective must have the same dimension and rating, so the objective criteria (in this

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systems in these type of companies is due to be able to have an adequate selection of the ERP packages systems. This paper studied a method for the selection of an ERP system in a construction industry contractor by applying the Fuzzy set theory and researching for the critical factors for the success of these complex systems. In this paper is also discussed some critical factors to the successful implementation of the ERP systems is all the industries in general and in the construction companies in particular. In the selection of the ERP packages each company perform his self evaluation and select the critical factors that lead to a successful implementation.

TABLE 9: CALCULATION OF TOTAL RELATIVE COST

4.5. Final rating To determine the final rating for each ERP system it is determined the average of the weight for each criterion times the relative weight for the respective criterion. The following formula is used: Fi =

6. References

1 × ⎡( SiC1 × WC1 ) + ... + ( SiCn × WCn ) ⎤⎦ , k ⎣

[1] AKASH, SINGH. WESSON, JANET. Evaluation criteria for assessing the usability of ERP systems. Nelson Mandela Metropolitan University. South Africa. 2009.

Where k is the number of criterion considered in the evaluation.

[2] CHUNG, BOO Young et al - Developing ERP Systems Success Model for the Construction Industry. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2009

⎡(0, 475;0, 725; 0, 725;0,95) × ⎤ ⎢ ⎥ 1 ⎢( 0,375; 0,575;0, 65; 0,85) + ...⎥ Fi = × ⎢ 6 + ( 0, 4;0, 675; 0, 675;0,9 ) × ⎥ ⎢ ⎥ ⎢⎣× ( 0, 27; 0,3; 0,33;0,38 ) ⎥⎦

[3] CHUNG, B., SKIBNIEWSKI, M. J., Lucas, H. C., Jr., and KWAK, Y. H. - Analyzing enterprise resource planning systems implementation success factors in the engineering-construction industry. J. Comput. Civ. Eng, 2003. [4] CHEN, Shyi-Ming, Lee , Chia-Hoang - New methods for students' evaluation using fuzzy sets. National Taiwan University of Science and Technology, 1997.

With similar calculations for all ERP systems, the fuzzy suitability is found as in Table 10.

[5] DRAKOPOULOS, John A. - Probabilities, possibilities, and fuzzy sets. Stanford University, 1994.

TABLE 10: FINAL FUZZY SUITABILITY INDEX

[6] FIRMINO, José Augusto Alves et al. ERP e CRM : da empresa à e-empresa : soluções de informação reais para empresas globais. Famalicão; Matosinhos; Lisboa. 1º Ed. Centro Atlântico, 2001.ISBN 972-8426-31-3.[7] [9] HE, LAN, LI, CONGBO. A method for selecting ERP systems based on Fuzzy set theory and Analytical hierarchy process. Global congress on intelligent systems. 2009. [8] IFIEDO, PRINCELY. NAHAR, NAZMUN. Prioritization of enterprise resource planning (ERP) systems success measures: viewpoints of two organization stakeholders group. Department of comp. sci & IS. Agora. 2006.

To find the final rating for each ERP system the fuzzy set limits are added as in Table 11. The system with the highest rating is ERP system 1 (1,492) and this should be the selected ERP. TABLE 11: FINAL RATING

[9] Jonathan Jingsheng Shi, M.ASCE, Daniel W., Halpin, M. ASCE Enterprise Resource Planning for Construction Business Management. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT (2003).

Sum

[10] SULE, Dileep R. - Logistics of Facility Location and Allocation. New York, Marcel Dekker, 2001.

ERP 1

1,492

ERP 2

1,346

ERP 3

1,145

[11] YANG, JYH-BIN et al. Selection of an ERP system for a contruction firm in Taiwan: A case study. Institute of construction management. Taiwan. 2007 [12] YOUNGCHEOl, KANG, William Stephen Thomas, M.ASCE; Robert E. Information Technologies on Performance: JOURNAL OF CONSTRUCTION MANAGEMENT, 2008.

5. Conclusion

J. O’Brien, A.M.ASCE; Chapman. - Impact of Cross Study Comparison. ENGINEERING AND

[13] ZADEH, L.A. - Fuzzy sets, Information and Control 8. California: University of California, 1965

The construction industry is now implementing the ERP systems. One of main difficulty in applying ERP

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