Management Performance Evaluation Model of Korean Construction Firms ()
1. Introduction
As Peter Drucker asserted, the adage “If you cannot measure it, you cannot manage it” is true in all corporate management activities, from manufacturing to IT. Performance measurement is an important management process that can be utilized to identify the fulfillment of annual management plans and provide feedback for subsequent management plans [1]. In the construction industry, performance measurements are complicated, as it is difficult to predict the productivity of projects due to the uncertainty in construction sites and contracting indi vidually [2].
Especially, since Korea’s economy has changed rapidly due to the sharp rise of raw material prices such crude oil, the rapid increase in overseas plant construction contracts from 2004, the Korea construction firms need to be established effectively their management strategies to ensure the competitiveness including various characteristics such as financial and non-financial aspects. In addition, it is necessary to systematically measure management performance in order to investigate whether or not the annual plans are successful.
Traditionally, the management performance was measured in terms of financial aspects, including the current net profit, the investment rate, and the return on equity (ROE) [3]. However, with the increased development of IT in the 1990s, studies on measurement factors and methods began to focus on intellectual resources [4-6]. Meanwhile, in Korea, management performance measurement models for construction firms were developed [6-8]. However, the proposed key performance indicators (KPIs) were insufficient for measuring the non-financial management performances of Korean construction firms [9]. Previous studies did not suggest a systematic scoring method for non-financial factors. Therefore, to effecttively measure management performance, it is essential to develop a performance measurement model that reflects the characteristics of Korean construction firms. In this study, our objective was to develop a management performance evaluation model (MAPEC) for Korean construction firms.
2. Previous Studies
Currently, most corporations focus on financial aspects in their management performance measurements, as these are easy to measure [10]. However, it is difficult to evaluate the long-term potential of a corporation only on the basis of financial aspects. This potential indicates the non-financial aspects such as brand, image, work environment, etc. In other words, although these aspects do not reflect directly the financial factors such as profitability and growth, the aspects influences continuously on the management performance in the long term. Therefore, it is necessary to identify and manage qualitative factors that result in long-term economic value.
Beginning in the 1990s, with the advent of the concept of intellectual resources, many researchers investigated qualitative factors related to management performance measurement. As shown in Table 1, performance measurement indicators of construction project of [11] can be divided into four indicators: project efficiency, impact on customers, business success and preparation for the future. First, in the project efficiency phase, it is measured whether or not the project is completed on time and budget. Second, the satisfaction of customers is measured. Third, in the business success phase, it is measured whether or not the management performance is improved after completion of the project. Fourth, it is measured how reflect the performance to the management for the future.
C. S. Lim, and M. Z. Mohamed evaluated performances such as time, cost quality and safety from both micro and macro viewpoints of developers, contractors, and customers [12]. R. Atkinson measured performance by
Table 1. Previous literature of KPI [11-13].
dividing it into delivery and post-delivery phases [13]. First, in the delivery stage, the cost, time quality and efficiency is evaluated. Second, after completion of a project, the impact of performance to customers is evaluated. Although many studies have been conducted regarding management performance evaluation, only general indicators show in the studies, which did not consider the characteristics of Korea construction industry.
As an alternative to the traditional approach, [9] proposed a Balanced Scorecard (BSC), which included nonfinancial aspects related to performance evaluation in the long term. The BSC aims for a better understanding of the correct strategies and key performance factors for a more comprehensive insight into current businesses. As shown in Table 2, the BSC is divided into four perspectives (i.e., financial, customer, internal business process and learning and growth). The BSC is appropriate for construction firms since the key performance indicators are defined in consideration of diverse environments such as market customers and culture. In this study, the BSC were applied to determine KPIs for Korean construction firms and then interviewed experts to estimate the weights of each KPI.
In terms of the performance measurement in construction industry, [14] suggested the construction performance measurement process conceptual framework. The framework represents the input and output of the process how to measure the performance as dividing into six perspectives such as financial, customer, internal business, innovation & learning, project, and suppliers. In addition, [15] analyzed the correlation between the change of managerial environment and the business performance of Korea construction firms. Although this study has been conducted regarding the management
performance of Korea construction firms, it did not investigate how to measure the performance. [16] suggest a simulation method to show management effectiveness of various strategies.
3. Methodology
The MAPEC, intended to measure the management performance of Korean construction firms, consists of a hierarchical structure: Balanced scorecard indicator (BSCI) —Classified performance indicators (CPI)—Key performance indicator (KPI) (Figure 1). The collected corporate performance data are reflected in the hierarchical structure at the beginning of the MAPEC process. KPI analysis, which is positioned at the bottom of the hierarchical structure, assigns weights to the actual performance data and estimates the CPI. The CPI analysis then assigns estimated weights to produce a BSCI, and the comprehensive corporate management performance is estimated using the BSCI. Weights for different factors are estimated in a Fuzzy-Delphi Analytic Hierarchy Process (FD-AHP).
To achieve this study’s objective, the following methodology was conducted: 1) CPIs and KPIs were obtained after reviewing previous studies and actual management measurement data; 2) CPIs and KPIs were selected after checking for duplication and omission; 3) according to the selected indicators, a management performance measurement hierarchy was proposed, and the weights of all of the indicators were estimated using an FD-AHP analysis; 4) each KPI score was evaluated by applying the scoring distribution methods proposed in this study; 5) two Korean construction firms were analyzed and evaluated using the MAPEC developed in this study.
It is difficult to develop an effective performance measurement model that encompasses all kinds of construction firms, such as those that design apartments, infrastructure, and plant development projects, as they cater to different customers and require different KPIs and CPIs for performance measurement [17]. Therefore, the scope of this study was limited to model development
applicable to the top 30 corporations in Korea. Among these corporations, this study focused on firms with both concurrent overseas and domestic projects.
To analyse the experience of experts, Saaty’s Analytic Hierarchy Process (AHP) method has been used widely. However, when the traditional AHP utilizes, the correlation between factors is not considered and the uncertainty and errors would have to determine ranks of factors. The problem such rank reverse may occur. The Fuzzy-Delphi AHP (FD-AHP) method is new decision-making model based on AHP method. In the decision-making issue, by using the pair-wise comparison method, the FD-AHP can determine the optimum alternative among various options [18]. This study utilizes FD-AHP method to establish management performance evaluation model.
4. MAPEC Development
4.1. CPI and KPI
In order to select the CPIs and KPIs, 10 experts were interviewed regarding the performance measurement factors from the top five Korean corporations. As shown in Table 3, among them, three experts are principals of the corporations and two experts are the head of management division. In addition, the rest of experts are the project managers having experience of over 10 years. After interviewing the experts, then the factors were classified and adjusted by the experts.
Based on the CPIs and KPIs, a survey was given to the top management executives in major Korean construction firms, asking for estimations of the weights of each indicator using pair-wise comparison. Table 4 represents the BSCI, CPI, and KPI developed in this study. Finally, 12 CPIs and 31 KPIs were suggested as detailed indicators of the BSCI for Korean construction firms.
4.2. Weight Estimation of BSCI, CPI, and KPI
MAPEC consists of indicators, with weights assigned in
Table 3. Summary of the respondents’ demographic data.
Table 4. BSCI, CPI, and KPI for Korean.
a hierarchical structure. To assign weight for each indicator, interviews were conducted to experts in Korean construction firms using pair-wise comparisons method between indicators. In other words, first, the weight between BSCs indicators was analyzed on the basis of the responses of the interviews. Second, the indicators of CPIs in BSCs were analyzed. Finally, all indicators of KPIs were analyzed by using pair-wise comparisons method.
According to [18], the determinant is calculated as fuzzy vector (
) using Column Vector Geometric Mean Method. The fuzzy vector calculation result shows a minimum (
), arithmetic mean (
), maximum value (
) and the final weight vector (
) estimated using the geometric mean method. In this process, calculation was performed in such a way that the sum of the weights estimated in each phase equaled one. The weights for the BSCIs, CPIs, KPIs calculated by the FD-AHP method are shown in Table 5. In the BSCIs, customer weight was the highest, at 0.34. For the customer CPI, the external customer satisfaction was the highest, at 0.38. For the financial aspects of the BSCI, technological competency in the internal business process, HR development and organizational competency in learning and growth showed the highest weights.
Figure 2(a) shows the BSCI weight analysis. Customers were the most important indicator, followed by Finance. This shows that the paradigm of Korean construction firms is shifting from a financial focus to a customer focus. Figure 2(b) represents the analyzed KPI weights. The amount received from new orders was the most important KPI, followed by the overseas market share rate, the information competency index and the domestic market share rate, which indicates that stakeholders consider order-winning competency and performance to be essential management factors. Order indicator is one of the factors which have not been considered in previous studies. In this study, it was considered to be a major