On: 24 April 2014, At: 23:40 Publisher: Routledge
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
Total Quality Management & Business
Excellence
Publication details, including instructions for authors and subscription information:
http://www.tandfonline.com/loi/ctqm20
A study on the relationship between
the PDSA cycle of green purchasing and
the performance of the SCOR model
Yeong-Dong Hwang a , Yuan-Feng Wen b & Mu-Chen Chen c aDepartment of Operations Management , Leader University , Tainan, Taiwan, Republic of China
b
Department of Logistics Management , National Kaohsiung Marine University , Kaoshiung, Taiwan, Republic of China c
Institute of Traffic and Transportation , National Chiao Tung University , Taipei, Taiwan, Republic of China
Published online: 14 Dec 2010.
To cite this article: Yeong-Dong Hwang , Yuan-Feng Wen & Mu-Chen Chen (2010) A study
on the relationship between the PDSA cycle of green purchasing and the performance of the SCOR model, Total Quality Management & Business Excellence, 21:12, 1261-1278, DOI: 10.1080/14783363.2010.529361
To link to this article: http://dx.doi.org/10.1080/14783363.2010.529361
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content.
This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &
and-conditions
A study on the relationship between the PDSA cycle of green
purchasing and the performance of the SCOR model
Yeong-Dong Hwanga∗, Yuan-Feng Wenband Mu-Chen Chenc
a
Department of Operations Management, Leader University, Tainan, Taiwan, Republic of China;
b
Department of Logistics Management, National Kaohsiung Marine University, Kaoshiung, Taiwan, Republic of China;cInstitute of Traffic and Transportation, National Chiao Tung University, Taipei, Taiwan, Republic of China
When environmental problems are the focus, conflicts between the general public and company stakeholders affect both regional and global cooperation prompting conflicts in many areas. As a consequence, various initiatives have been designed and adopted that improve environmental performance while maintaining sustainable development. Green purchasing is applied as a useful tool to mitigate the environmental impacts of consumption and to promote clean production technology. The supply chain operations reference (SCOR) model is proposed by a supply chain council as a standard supply chain performance evaluation model. This model has been widely embraced by many modern organisations. The SCOR model can be applied to analyse supply chain performance in a systematic way. It can also aid in communication among all members in the supply chain, and can assist in the development of a design for a better supply chain network. To further improve the performance of the green purchasing process, which is critical in numerous industries, this study explores the relationship between the plan-do-study-act (PDSA) cycle of green purchasing and the SCOR purchasing/sourcing process and its performance indices/metrics. In this study, those companies which produce Taiwanese green label products are taken as samples. The PDSA cycle of green purchasing and the SCOR model are used to construct a structural equation model (SEM). An SEM analysis is conducted to establish the relationship between the PDSA of green purchasing, the sourcing process, and its performance on the SCOR model. The results of this study provide some suggestions for companies conducting green purchasing.
Keywords:green purchasing; PDSA cycle; supply chain operations reference (SCOR) model; structural equation model (SEM)
Introduction
With globalisation development many enterprises face the challenge of global customers by actively constructing new types of business in order to compete with rivals in the marketplace. With the integration of a global economy, enterprises are no longer isolated individuals. Instead, they form a complete supply chain system by cooperating with each other in order to create a higher market value, including procurement, logistics and distribution for ensuring a consistently high degree of customer satisfaction in terms of quality, delivery and cost (Mehta, 2004). In recent years, it has become well-known that a green trend is sweeping across the world. Faced with an awakening environmental consciousness and the formulation of numerous environmental regulations, it is the traditional supply chain that must make the transition by becoming a green supply
ISSN 1478-3363 print/ISSN 1478-3371 online # 2010 Taylor & Francis
DOI: 10.1080/14783363.2010.529361 http://www.informaworld.com
∗Corresponding author. Email: hyd1020@ms11.hinet.net
chain in the future (Gifford, 1997; Walton, Handfield, & Melnyk, 1998). Green purchasing is an important issue and has drawn international attention because it can be used to mitigate the environmental impacts of consumption and promote clean production technology in the green supply chain system. Each company can choose the optimal appropriate green purchasing strategy and can obtain the competitive advantages of the whole green supply chain when facing a highly competitive global market.
The Supply Chain Council (SCC) was founded by Pittiglio Rabin Todd & McGrath, Advanced Manufacturing Research along with over 65 other enterprises in 1996. The supply chain operations reference (SCOR) model was proposed to help enterprises conduct analysis in a systematic way, to promote communication among members and to provide basic business rules for establishing supply chains. The SCOR is a cross-industry standard supply chain model and is an analysis tool of the supply chain obtained from the viewpoint of process, performance evaluation, and best practices.
Research combining green purchasing and the SCOR model is rare. This study explores relationships among the plan-do-study-act (PDSA) cycle of green purchasing, the sourcing process of the SCOR model and the performance of the SCOR model. Companies that produce green label products in Taiwan were selected as questionnaire respondents for conducting structural equation model (SEM) analysis, and to identify significant factors and the relationships of these factors.
Framework and hypotheses
In the following sections, a model consisting of 13 hypotheses is presented, including the PDSA cycle of green purchasing, the impact of the PDSA cycle of green purchasing on the sourcing process of the SCOR model, the impact of the sourcing process of the SCOR model on its performance of green purchasing and the impact of the PDSA cycle of green purchasing on the performance of the SCOR model.
The PDSA cycle of green purchasing
The PDSA cycle, including planning, doing, studying and acting phases, is a methodology for improvement based on the premise that improvement comes from the application of knowledge (Evans, 2005; Fredriksson, 2003), it is sometimes also called the Deming cycle or the Shewhart cycle. Gapp and Fisher (2008) addressed a platform for understand-ing the disadvantages of supply chain benchmarkunderstand-ing by creatunderstand-ing an internal knowledge and learning environment through the PDSA cycle, and then fostered innovation, organ-isational change and quality improvement. In the planning phase, the company establishes a green purchasing team and clearly identifies green purchasing strategies and environ-mental performance indices. In the doing phase, the team systematically collects data and modifies and evaluates tasks and activities that may significantly impact the environ-ment. The studying phase is to effectively develop a performance evaluation system of green purchasing to measure actual performance. Appropriate corrective actions should be conducted for non-conformance with the goal. Finally, the acting phase is to develop a new measurement system to measure environmental performance, to control and main-tain its performance, and to continuously implement the environmental strategies (Zhu, Sarkis, & Lai, 2008). The planning, doing and acting phases for green purchasing under the ISO 14000 structure are proposed by Chen (2005). Some relevant questions of supply chain, such as the source of delivery, delivery patterns and packaging patterns of delivery are illustrated. The PDSA cycle of green purchasing comprises the following four hypotheses:
H1: The planning phase of green purchasing has a significant impact on its doing phase.
H2: The doing phase of green purchasing has a significant impact on its studying phase.
H3: The studying phase of green purchasing has a significant impact on its acting phase.
H4: The acting phase of green purchasing has a significant impact on its planning phase.
The impact of PDSA cycle of green purchasing on sourcing process of the SCOR model
Under green purchasing, green suppliers, waste management, packaging problems, environmental regulations, resource reduction, resource reuse, and resource recycling are considered. In addition, support from top management, environmental targets revised, educational training and environmental evaluation are all advantageous when trying to achieve expected outcomes from the sourcing process (Carter, Ellram, & Ready, 1998; Min & Galle, 1997, 2001; Schlegelmilch, Bohlen, & Diamantopoulos, 1996).
The SCOR model belongs to a supply chain performance evaluation model. It provides a consistent supply chain management framework, including business process perform-ance, evaluation, and best practices. It can assist all participants of a supply chain, includ-ing manufacturers, first and second-tier suppliers, downstream retailers/distributors/ logistics service providers, and customers, allowing effective communication via the SCOR model and improved the efficiency of supply chain management thereafter.
The SCOR model contains six levels. Its outlines and comments are shown in Table 1 (Xelocity, 2008; Supply-Chain Council, 2006). Level 1 is the top level that deals with process types and defines the supply chain as six key management processes: plan, source, make, deliver, return and enable. This level should clearly define the business objectives of the organisation. Level 2 shows the core process categories. Level 3 presents the process elements that are used to describe various activities and provides a greater insight into the operation of the supply chain. Although levels 4, 5 and 6 are not defined, they can be redefined and redrawn based on a companies’ actual condition. Level 4 specifies supply chain management practices that will help achieve competitive advantage, and is known as task. Level 5 plans the activities for each task, and level 6 describes the rules of activities.
The SCOR sourcing type for level 2 and level 3 has three processes and 17 process elements, respectively. Level 2 shows a sourcing process that includes source stocked product, source make-to-order product and source engineer-to-order product. The sourcing process element of the first two processes for level 3 includes schedule product deliveries, product receiving, product verification, product transfer, and supplier payment authoris-ation. Beside the above-mentioned five items, the third process also includes identification of supply sources and a final suppliers’ selection/negotiation. The PDSA cycle of green purchasing can not only mitigate environmental impacts, but also improve the operation of the sourcing process (Choi & Eboch, 1998; Choi & Hartley, 1996; Ofori, 2000).
H5: The planning phase of green purchasing has a significant impact on sourcing process
elements of the SCOR model.
H6: The doing phase of green purchasing has a significant impact on sourcing process
elements of the SCOR model.
H7: The studying phase of green purchasing has a significant impact on sourcing process
elements of the SCOR model.
H8: The acting phase of green purchasing has a significant impact on sourcing process
elements of the SCOR model.
Table 1. The outline and comment of the SCOR model.
Level Description Outline Comments
1 Top level (process types)
Level 1 defines the scope and content for the SCOR model Here basis of competition performance targets are set 2 Configuration level (process categories) Plan: P1to P5 Source: S1to S3 Make: M1to M3 Deliver: D1to D4 Return: SR1to SR3; DR1to DR3
Enable: EP, ES, EM, ED, ER
A company’s supply chain can be configured-to-order at level 2 from core process categories Companies implement
their operations strategy through the configuration they choose for their supply chain 3 Process element level (decompose processes) Plan: P1.1to P1.4; P2.1to P2.4; P3.1to P3.4; P4.1to P4.4; P5.1to P5.4 Source: S1.1to S1.5; S2.1to S2.5; S3.1to S3.7 Make: M1.1to M1.6; M2.1to M2.6; M3.1to M3.7 Deliver: D1.1to D1.15; D2.1to D2.15; D3.1to D3.15; D4.1to D4.7 Return: SR1.1to SR1.5; SR2.1to SR2.5; SR3.1 to SR3.5; DR1.1to DR1.4; DR2.1to DR2.4; DR3.1to DR3.4 Enable: EP1to EP9; ES1to ES9; EM1to EM8; ED1to ED8; ER1to ER8 Level 3 defines a company’s ability to compete successfully in its chosen markets Companies fine tune
their operations strategy at level 3 4 Implementation level (decompose process elements)
Plan: tasks (undefined) Source: tasks (undefined) Make: tasks (undefined) Deliver: tasks (undefined) Return: tasks (undefined) Enable: tasks (undefined)
Companies implement specific supply-chain management practices at this level Level 4 defines practices to achieve competitive advantage and to adapt to changing business conditions 5 Undefined (decompose tasks)
Plan: activities (undefined) Source: activities (undefined) Make: activities (undefined) Deliver: activities (undefined) Return: activities (undefined) Enable: activities (undefined)
The activities can be defined according to the companies’ actual conditions
6 Undefined (analyze rule detailed for activities)
Plan: rules (undefined) Source: rules (undefined) Make: rules (undefined) Deliver: rules (undefined) Return: rules (undefined) Enable: rules (undefined)
The rules can be analyzed according to the companies’ actual conditions
The impact of sourcing process of the SCOR model on its performance for green purchasing
The SCOR is a supply chain performance evaluation model, which can provide three levels of performance metrics. It has been successfully applied to many cases worldwide (Bolstorff, 2003a). At this time, the application of the SCOR model in green purchasing per-formance measurement is rare. The SCOR can be applied to develop action-oriented metrics that effectively measure the progress of supply chain projects (Bolstorff, 2004). The SCOR provides companies with a picture of how the processes from start to finish can be improved (Kevan, 2005) and supports cross-industry diagnostics since its standar-dised process definitions and metrics fit all types of business operations and environments (Bolstorff, 2002, 2003b). Lockamy and McCormack (2004) investigated the relationship between supply chain management planning practices and performance based on the plan-ning, sourcing, making and delivering decision processes provided in the SCOR model. The concept based on the SCOR model evaluated different configurations of process chains with different sets of parameters describing realistic production and inventory processes (Roder & Tibken, 2006). Wang, Huang, and Dismukes (2004) evaluated the performance metrics of the SCOR model for suppliers by using an analytic hierarchy process and determined the strategies of the supply chain. The Taiwanese thin film transistor-liquid crystal display (TFT-LCD) industry was selected as a sample case study by Hwang, Lin, and Lyu (2008) and important performance metrics for the sourcing processes were explored.
H9: The sourcing process elements of the SCOR model of green purchasing has a significant
impact on its performance.
The impact of the PDSA cycle of green purchasing on the performance of the SCOR model
In general, the major performance metrics of green purchasing include quality, delivery time, capacity of manufacturing systems, price, financial status, capability of R&D and packaging cost (Choi and Hartley, 1996; Hemsworth, Sanchez-Rodriguez, & Bidgood, 2008; Noci, 1997; Park, Hartley, & Wilson, 2001). Gapp and Fisher (2008) identified and reviewed benchmarking approaches in terms of both the internal and external elements of benchmarking with a focus on process, content and performance metric. Level 1 per-formance metrics of the SCOR model include perfect order fulfillment, upside supply chain flexibility, upside supply chain adaptability, downside supply chain adaptability, supply chain management cost, cost of goods sold, cash-to-cash cycle time, and return on supply chain fixed assets (Xelocity, 2008). The SCOR model also explicitly defines the performance metrics of level 2 and level 3 for companies to use. Under green purchas-ing, the overall performance of companies can be enhanced by evaluating the environ-mental performance of suppliers and relevant performances of the whole supply chain system (Hervani, Helms, & Sarkis, 2005; Mebratu, 2001; Rao & Holt, 2005; Vachon & Klassen, 2008; Zhu, Sarkis, & Geng, 2005; Zhu, Sarkis, & Lai, 2007a, 2007b). As a result, performance evaluation will be more definite if green purchasing can be used in conjunction with the performance metrics of the SCOR model.
H10: The planning phase of green purchasing has a significant impact on level 1 performance
of the SCOR model.
H11: The doing phase of green purchasing has a significant impact on level 1 performance of
the SCOR model.
H12: The studying phase of green purchasing has a significant impact on level 1 performance
of the SCOR model.
H13: The acting phase of green purchasing has a significant impact on level 1 performance of
the SCOR model.
Methodology
First, expert-opinion and related literature surveys are conducted (Chen, 2005; Choi & Hartley, 1996; Evans, 2005; Hwang et al., 2008; Ofori, 2000; Sarkis, 2003; Seuring & Muller, 2008; Vachon & Klassen, 2008; Zhu et al., 2007a, 2007b, 2008) are conducted to obtain an in-depth understanding of the relationship between the PDSA cycle of green pur-chasing, sourcing process and its effect on the performance of the SCOR model and further to design a questionnaire. A SEM framework is then constructed to verify the hypotheses. Sample description
Because most manufacturers of green label products in Taiwan engage in production and purchasing based on the sourcing process of purchase-to-stock policy, the sourcing stocked product of the SCOR model is selected in this study. The sourcing stocked process comprises of five process elements, including schedule product deliveries (S1.1),
receive product (S1.2), verify product (S1.3), transfer product (S1.4) and authorise supplier
payment (S1.5). Level 1 contains nine common performance metrics, but level 2 processes
and level 3 process elements are with corresponding performance metrics respectively. The performance metrics and their definitions of the SCOR sourcing stocked product at levels 1, 2 and 3 are shown in Tables 2 and 3, respectively. In the SCOR sourcing stocked product, level 2 processes and level 3 process elements include nine and 27 performance metrics respectively. To construct the SEM, the questionnaire shown in
Table 2. The performance metric of SCOR sourcing stocked product at levels 1, 2 and 3.
Attribute Metric (code)
Reliability Perfect order fulfillment (R1), % schedules generated with supplier’s lead time
(R1.1), % schedules changed within suppliers’ lead time (R1.2), % orders/lines
received complete (R1.3), % orders/lines received on-time to demand
requirement (R1.4), % orders/line received damage free (R1.5), % orders/lines
received with correct shipping documents (R1.6), % orders/lines received defect
free (R1.7), % product transferred on-time to demand requirement (R1.8),
% product transferred without transaction errors (R1.9), % product transferred
complete (R1.10), % product transferred damage free (R1.11), % of faultless
invoices (R1.12)
Responsiveness Order fulfillment cycle time (RP1), source cycle time (RP1.1), schedule product
deliveries cycle time (RP1.1.1), receive product cycle time (RP1.1.2), very
product cycle time (RP1.1.3), transfer product cycle time (RP1.1.4), authorise
supplier payment cycle time (RP1.1.5)
Flexibility Upside supply chain flexibility (F1), upside supply chain adaptability (F2),
downside supply chain adaptability (F3)
Cost Supply chain management cost (C1), cost of goods sold (C2), product acquisition
costs as % of source stocked product costs (C2.1), schedule deliveries costs as a
% of product acquisition costs in source stocked product costs (C2.1.1), receiving
cost as a % of product acquisition costs in source stocked product costs (C2.1.2),
verification costs as a % of product acquisition costs in source stocked product costs (C2.1.3), transfer & product storage costs as a % of product acquisition
costs in source stocked product costs (C2.1.4), costs per invoice as a % of product
acquisition costs in source stocked product costs (C2.1.5)
Asset Cash-to-cash cycle time (Aa), return on supply chain fixed assets (Ab)
Appendix is designed as six unobserved/latent variables and 37 observed/manifest vari-ables. These observed variables are abbreviated as P1, P2, P3, P4, D1, D2, D3, D4, D5, D6,
D7, S1, S2, S3, S4, S5, S6, A1, A2, A3, A4, A5, A6, S1.1, S1.2, S1.3, S1.4, S1.5, R1, RP1.1, F1, F2, F3,
C1, C2, Aaand Ab. These variables are used to evaluate the relationship between green
purchasing/sourcing process and its performance. Targeted purchasing staff from 325 green label manufacturers participated in the study. A total number of 218 questionnaires were returned, the response rate was 67%. A Likert scale was designed for the questionnaire using a scale of 1 to 5: 1 denoting very unimportant, 3 indicating neutral, and 5 representing very important.
SEM
The questionnaire was designed based on the PDSA cycle of green purchasing, sourcing stocked product and level 1 performance of the SCOR model. It can be used to determine
Table 3. The performance metric definition of SCOR sourcing stocked product at level 1, 2 and 3.
Metric code
Attribute Level 1 Level 2 Level 3 Definition
Reliability R1 R1 R1.1 R1.12
(12 metrics)
The percentage of orders meeting delivery performance with complete and accurate documentation and no delivery damage. Components include all items and quantities on-time using customer’s definition of on-time, and documentation - packing slips, bills of lading, invoices, etc.
Responsiveness RP1 RP1.1 RP1.1 RP1.5
(5 metrics)
The average actual cycle time consistently achieved to fulfill customer orders. For each individual order, this cycle time starts from the order receipt and ends with customer acceptance of the order
Flexibility F1 F1 F1 The number of days required to achieve an
unplanned sustainable 20% increase in quantities delivered
F2 F2 F2 The maximum sustainable percentage increase
in quantity delivered that can be achieved in 30 days
F3 F3 F3 The reduction in quantities ordered sustainable
at 30 days prior to delivery with no inventory or cost penalties
Cost C1 C1 C1 All direct and indirect expenses associated
with operating SCOR business across the supply chain
C2 C2.1 C2.1.1 C2.1.5
(5 metrics)
Asset Aa Aa Aa The time it takes for an investment made to
flow back into a company after it has spent for raw materials
Ab Ab Ab Measures the return an organization receives
on its invested capital in supply chain fixed assets.
This includes the fixed assets used in plan, source, make, deliver, and return
the SEM shown in Figure 1. The observed variables were obtained based on the question-naire and the SCOR sourcing process. The questionquestion-naire had a total of 37 items: 23 items belonging to the PDSA cycle of green purchasing, five items referred to sourcing stocked product of the SCOR model, and nine items related to level 1 performance of the SCOR model. The PDSA cycle of green purchasing comprises four phases of planning, doing, studying and acting, which include 4, 7, 6 and 6 items, respectively.
Results
The results obtained from the SEM analysis include a goodness-of-fit measurement and relationships. They are described below, respectively.
Goodness-of-fit measurement
Goodness-of-fit tests are used to determine whether the model is rejected or not. The Goodness-of-fit measurements are classified into three categories: an absolute fit measure-ment; an incremental fit measuremeasure-ment; and a parsimonious fit measurement. The absolute fit measurement includes chi-square (x2), goodness-of-fit index (GFI), adjusted goodness
Figure 1. The architecture of structural equation model.
of fit index (AGFI), root mean square residual (RMR) and root mean square error of approximation (RMSEA). The incremental fit measurement includes normed fit index (NFI), Trucker-Lewis index (TLI)/non-normed fit index and comparative fit index (CFI). The third category is either normed chi-square (NC) or Chi-square/degree of freedom. Among them, the values of GFI, AGFI, NFI, TLI and CFI over 0.9 were the optimal status; the result of goodness-of-fit measure can also be good if the values are larger than 0.8 (Joreskog, 1993; Kline, 1998; Maruyama, 1997). In addition, if the result of goodness-of-fit measure is good, then smaller values of p for x2, RMR, RMSEA and NC should be better (less than 0.05, 0.05, 0.1 and 2, respectively). At first all the observed variables are selected to construct the SEM. The result of goodness-of-fit measurement was not good. This is called the original model. In order to improve the goodness-of-fit measurement of the model, 16 insignificant observed variables, includ-ing P3, P4, D2, D7, S4, S5, S6, A3, A4, A5, A6, S1.3, F1, F2, F3and Ab, were deleted. This is
called the revised model. Tables 4 and 5 show the analysis results for goodness-of-fit measurement and observed variables, respectively. The revised model has values of GFI, AGFI, NFI, TLI and CFI over 0.8 and the values of p for x2, RMR, RMSEA and NC are ,0.001, 0.023, 0.051 and 1.512, respectively, and thus the goodness-of-fit measurement was good. Because the revised model obtained better results in the good-ness-of-fit measurement than the original model, the revised model was used for the relationship study.
Results of relationship
Table 6 shows the analytic results of unobserved variables in the revised model. Among them, H1, H2, H4, H7, H8, H9, H10, H11 and H12 are significant, which means paths of
these unobserved variables exist. H3, H5, H6, H12 and H13 are insignificant, which
means that the mutual effects of these unobserved variables could be neglected. For the PDSA cycle of green purchasing, three hypothesis are significant, including H1 (the
phase of planning will have an impact on the phase of doing), H2(the phase of doing
will have an impact on the phase of studying), and H4(the phase of acting will have an
impact on the phase of planning). In respect of the relationship between the PDSA cycle of green purchasing and the sourcing stocked product of the SCOR model, the phases of studying and acting will have an impact on the sourcing stocked product of the SCOR model (H7 & H8). In respect of the PDSA cycle of green purchasing and
level 1 performance of the SCOR model, the phases of planning and doing will have an impact on level 1 performance of the SCOR model (H10& H11). In addition, the sourcing
Table 4. The analysis results of goodness-of-fit measurement for the original and revised models.
Type Index The original model The revised model
Absolute fit measure x2( p value) 960.345 (,0.001) 956.53 (,0.001)
GFI 0.818 0.840
AGFI 0.784 0.813
RMR 0.039 0.023
RMSEA 0.053 0.051
Incremental fit measure NFI 0.616 0.810
TLI 0.775 0.841
CFI 0.800 0.880
Parsimonious fit measure NC 1.619 1.512
Table 5. The analysis results of observed variables for the original and revised models.
Unobserved variable
Observed
variable The original model The revised model
p value Factor loading Cronbach a p value Factor loading Cronbach a Planning P1 ,0.001 0.991 0.403 Fixed parameter 0.952 0.952 P2 ,0.001 0.947 ,0.001 0.914 P3 0.752 0.021 P4 Fixed parameter 0.316 Doing D1 ,0.001 0.934 0.622 Fixed parameter 0.940 0.876 D2 Fixed parameter 0.373 D3 ,0.001 0.606 ,0.001 0.641 D4 ,0.001 0.975 ,0.001 0.960 D5 ,0.001 0.646 ,0.001 0.716 D6 ,0.001 0.574 ,0.001 0.604 D7 0.697 0.026 Studying S1 ,0.001 0.936 0.573 Fixed parameter 0.941 0.798 S2 ,0.001 0.574 ,0.001 0.614 S3 ,0.001 0.900 ,0.001 0.899 S4 0.177 0.100 S5 0.060 0.175 S6 Fixed parameter 0.295 Acting A1 ,0.001 0.935 0.475 Fixed parameter 0.933 0.908 A2 ,0.001 0.914 ,0.001 0.870 A3 0.894 0.009 A4 Fixed parameter 0.325 A5 0.429 0.053 A6 0.629 0.032 Sourcing stocked product of SCOR model S1.1 Fixed parameter 0.966 0.777 Fixed parameter 0.949 0.955 S1.2 ,0.001 0.982 ,0.001 0.995 S1.3 0.394 0.362 S1.4 ,0.001 0.923 ,0.001 0.963 S1.5 ,0.001 0.775 ,0.001 0.796 Level 1 performance of SCOR model R1 Fixed parameter 0.733 0.704 Fixed parameter 0.806 0.878 RP1 ,0.001 0.814 ,0.001 0.874 F1 0.062 0.110 F2 0.980 0.001 F3 0.786 0.016 C1 ,0.001 0.708 ,0.001 0.705 C2 ,0.001 0.924 ,0.001 0.961 Aa ,0.001 0.907 ,0.001 0.855 Ab 0.709 0.022
stocked product of the SCOR model under green purchasing will have an impact on its level 1 performance (H9).
Discussions
This study investigated the observed variables for the PDSA cycle of green purchasing, sourcing stocked product and level 1 performance of the SCOR model, and the last two vari-ables belong to SCOR model. The significant observed varivari-ables obtained for the PDSA cycle of green purchasing and SCOR model through SEM analysis are discussed below.
PDSA cycle of green purchasing
In the planning phase, two observed variables shown in Table 5, including P1and P2, are
significant. Variable P1is used to describe the environmental objectives and targets in
detail. The company has to clearly describe the practice and measurement of green pur-chasing in order to achieve the defined environmental objectives and targets and to ensure all purchase, practice, and procedures are set. Variable P2is to develop the
knowl-edge in respect of green purchasing practices. The economic and environmental impacts of green purchasing are evaluated through appropriate evaluation tools, and some related factors conforming to the environment should also be found.
Variables D1, D3, D4, D5and D6are significant in the doing phase. Variable D1is
gen-erated to meet the requirements of ISO 14000. Variable D3gathered and analysed related
data for the environmental impact of green purchasing. Variable D4 asked suppliers to
provide reliable product environmental conditions and data for a life cycle assessment according to ISO 14040. Variable D5was used to select suppliers with ISO 14000
certi-fication. To build up customer’s confidence, the suppliers which have been validated to have green products by third parties are selected (Mendelson & Polonsky, 1995; Stanfford & Hartman, 1996). Variable D6was used to consider logistics systems which are presented
in three types including the source of delivery, delivery patterns and packaging patterns for delivery (Chen, 2005; Sarkis, 2003).
In the studying phase, S1, S2 and S3 are significant. Variable S1 describes that
appropriate corrections should be conducted for non-conformance with predetermined objectives and targets in environmental performance. Variable S2supports ISO 14031 Table 6. The analysis results of unobserved variables for the revised model.
Hypothesis Path Factor loading p value Impact
H1 Planning Doing 0.986 ,0.001 Significant
H2 Doing Studying 0.403 0.024 Significant
H3 Studying Acting 0.225 0.242 Insignificant
H4 Acting Planning 1.046 ,0.001 Significant
H5 Planning Sourcing 0.101 0.783 Insignificant
H6 Doing Sourcing 0.024 0.940 Insignificant
H7 Studying Sourcing 0.339 ,0.001 Significant
H8 Acting Sourcing 0.902 ,0.001 Significant
H9 Sourcing Performance 0.374 ,0.001 Significant
H10 Planning Performance 0.739 ,0.001 Significant
H11 Doing Performance 1.641 ,0.001 Significant
H12 Studying Performance 0.01 0.330 Insignificant
H13 Acting Performance 0.045 0.114 Insignificant
certification. This is an internal process and management tool designed for providing man-agers with reliable and verifiable information and to determine whether the organisation’s environmental performance meet the standard or not (Kuhre, 1998). Variable S3was used
to develop a new measurement system for measuring the environmental performance of green purchasing. Through monitoring a series of processes, non-compliance with objec-tives and targets of green purchasing can be fed back to managers, and then form a new environmental strategy (Chen, 2005; Hammer, 1997).
In the acting phase, A1and A2are significant. Variable A1represents the standardised
processes and procedures for green purchasing. These processes and procedures can be standardised for conformance with objectives and targets. Variable A2increases
purcha-sers’ capability. This increases purchapurcha-sers’ knowledge of implementing green purchasing practices through training and to learn new methods for solving problems.
SCOR model
The results of the SEM analysis for sourcing stocked product and level 1 performance of the SCOR model are shown in Table 5, and are explained as follows. There are five sig-nificant performance metrics at level 1 which are perfect order fulfillment (R1), order
ful-fillment cycle time (RP1), supply chain management cost (C1), cost of goods sold (C2) and
cash-to-cash cycle time (Aa). Many studies on green supply chain focused on reduced
cycle times, improved quality through waste reduction, customer focus and cooperation (Choi & Eboch, 1998; Gapp & Fisher, 2008; Vachon & Klassen, 2008; Zhu et al., 2007a; Zhu & Sarkis, 2004). Past research suggests that companies should select good pro-cesses/strategies between environmental impact and costs to decrease the environmental impact of thegreen supply chain (Neto, Bloemhof-Ruwaard, Nunen, & Heck, 2008; Rao & Holt, 2005; Sarkis, 2003). Table 7 shows the performance metrics of the SCOR sourcing stocked product at levels 2 and 3 which are extended from level 1 performance metrics through the SEM analysis. Level 2 contains five significant performance metrics as well, including R1, source cycle time (RP1.1), C1, C2 and Aa. Level 3 comprises five
process elements, including S1.1, S1.2, S1.3, S1.4 and S1.5. The marks shown in Table 7
with P represent the performance metrics defined by the SCOR sourcing stocked product at level 3, and marked areas denote significant metrics obtained.
In the S1.1process element, significant metrics include percentage schedules generated
with suppliers’ lead time (R1.1), percentage of schedules changed with suppliers’ lead time
(R1.2), schedule product deliveries cycle time (RP1.1.1), C1, schedule deliveries cost as 1%
of product acquisition costs in sourcing stocked product (C2.1.1) and Aa. R1.1which defines
the ratio of total number of schedules to the number of schedules which are changed in the suppliers lead time in the measurement period. R1.2 is 100% subtracted by R1.1. C2.1.1
representing the ratio of product acquisition cost to the total cost of scheduled deliveries in sourcing stocked product.
In the S1.2process element, the metrics include the percentage of order/lines received
completely (R1.3), percentage of orders/lines received on-time to demand requirement
(R1.4), percentage of orders/lines received damage free (R1.5), percentage of orders/lines
received with correct shipping documents (R1.6), receive product cycle time (RP1.1.2), C1,
receiving costs as a percentage of product acquisition costs in sourcing stocked product (C2.1.2) and Aa. Among them, the attribute of R1.3, R1.4, R1.5 and R1.6 is reliability and
C2.1.2is cost. The definition of R1.3is the ratio of the total number of orders/lines received
to the total number of orders/lines received in the measurement period. R1.4is the ratio of the
number of total orders/lines needed to meet demand to the number of orders/lines received
on-time to the demand requirements. R1.5and R1.6respectively represent the ratio of orders/
lines received without damage and with correct shipping documents to the total orders/lines processed. C2.1.2represents the ratio of the total cost of product acquisition to the receiving
cost in sourcing stocked product. Because S1.3is not significant, the metrics can be
neg-lected, including the percentage of orders lines received defect free (R1.7), very product
cycle time (RP1.1.3), F1, F2, F3, C1, verification costs as a percentage of product acquisition
costs in sourcing stocked product (C2.1.3), Aaand Ab.
The key performance metrics of S1.4process element are percentage of product
trans-ferred to demand requirement (R1.8), percentage of product transferred without transaction
errors (R1.9), percentage of product transferred complete (R1.10), percentage of product
transferred damage free (R1.11), transfer product cycle time (RP1.1.4), C1, transfer and
product storage costs as a percentage of product acquisition costs in sourcing stocked product (C2.1.4) and Aa; S1.5process element include the percentage of faultless invoices
(R1.12), authorise supplier payment cycle time (RP1.1.5), C1, cost per type of invoice
(C2.1.5) and Aa. R1.8, R1.10 and R1.11 are similar to R1.4, R1.3 and R1.5, respectively.
However, the first three metrics are used for transferring products and the rest are used for orders/lines received. R1.9represents the ratio of the total number of transactions
pro-cessed to the number of transactions propro-cessed without error. C2.1.4and C2.1.5are similar, Table 7. The performance metric of SCOR source stocked product process at levels 2 and 3 through extending from level 1 performance metrics through the SEM analysis.
Level 1 Level 2 Level 3
S1.1 S1.2 S1.3 S1.4 S1.5 Reliability R1 R1 R1.1 3 R1.2 3 R1.3 3 R1.4 3 R1.5 3 R1.6 3 R1.7 3 R1.8 3 R1.9 3 R1.10 3 R1.11 3 R1.12 3 Responsiveness RP1 RP1.1 RP1.1.1 3 RP1.1.2 3 RP1.1.3 3 RP1.1.4 3 RP1.1.5 3 Flexibility F1 F1 F1 3 3 3 3 3 F2 F2 F2 3 3 3 3 3 F3 F3 F3 3 3 3 3 3 Cost C1 C1 C1 3 3 3 3 3 C2 C2.1 C2.1.1 3 C2.1.2 3 C2.1.3 3 C2.1.4 3 C2.1.5 3 Asset Aa Aa Aa 3 3 3 3 3 Ab Ab Ab 3 3 3 3 3
and are used to represent the costs of product transferring and storage and the cost per type of invoice, respectively. R1.12represents the ratio of the total number of invoices processed to
the number of invoices issued without error. In general, the reasons for invoice defects include a change in the customers’ purchase order without their agreement, wrong customer information, wrong product information, wrong price, wrong quantity, terms or date, etc.
Conclusions and suggestions
The SEM was designed to find out the relationship between the PDSA of green purchasing and sourcing process and its performance on the SCOR model. There are 13 hypotheses proposed in this study. Since the p values (,0.001) for eight hypotheses are lower than the significance level (0.05) after analysis, the proposed null hypothesis are accepted. The results are summarised as follows:
(1) The planning phase of green purchasing will affect both the doing phase of green purchasing and level 1 performance of the SCOR model.
(2) The doing phase of green purchasing will affect both the studying phase of green purchasing and level 1 performance of the SCOR model.
(3) The studying phase of green purchasing will affect the sourcing stocked product of the SCOR model.
(4) The acting phase of green purchasing will affect both the planning phase of green purchasing and the sourcing stocked product of the SCOR model.
(5) The sourcing stocked product process of the SCOR model will affect level 1 per-formance of the SCOR model.
The number of observed variables for the PDSA cycle of green purchasing, sourcing stocked product of the SCOR model and level 1 performance of the SCOR model is 23, 5 and 9, respectively. After the SEM analysis, the number of significant variables screened is found to be 12, 4 and 5, respectively. The sourcing stocked product of the SCOR model at level 3 includes 52 performance metrics. By extending the results of level 1 performance, 27 critical performance metrics are screened out of the 52 defined performance metrics for level 3.
As shown in the case analysis, the results obtained are only suitable for companies with green label products in Taiwan. This method also provides an insight into the relationship between green purchasing for the improvement in the green supply chain performance in various industries. In addition, this study is conducted based on the SCOR version 7.0. The newly developed version 9.0 can be adopted for future study (Supply-Chain Council, 2008).
Acknowledgement
The authors wish to acknowledge funding support from the National Science Council of the Republic of China (Taiwan) (NSC 97-2221-E-426-007).
References
Bolstorff, P. (2002). How does SCOR measure up? Supply Chain Technology News, May, 22 – 25. Bolstorff, P. (2003a). Measuring the impact of supply chain performance. Logistics Today,
December, 6 – 11.
Bolstorff, P. (2003b). Measuring the impact of supply chain performance. Logistics Today, December, 6 – 11.
Bolstorff, P. (2004). Supply chain by the numbers. Logistics Today, 45(7), 46, 48 – 50.
Carter, C.R., Ellram, L.M., & Ready, K.J. (1998). Environmental purchasing: Benchmarking our German counterparts. International Journal of Purchasing and Materials Management, 34(4), 28–38.
Chen, C.C. (2005). Incorporating green purchasing into the frame of ISO 14000. Journal of Cleaner Production, 13, 927–933.
Choi, T.Y., & Eboch, K. (1998). The TQM paradox: Relations among TQM practices, plant perform-ance, and customer satisfaction. Journal of Operations Management, 17, 59–75.
Choi, T.Y., & Hartley, J.L. (1996). An exploration of supplier selection practices across the supply chain. Journal of Operations Management, 14, 333–343.
Evans, J.R. (2005). Total quality management, organization and strategy (4th ed.). Canada: Thomson & South – Western.
Fredriksson, M. (2003). TQM as a support for societal development – experiences from a Swedish community. Total Quality Management & Business Excellence, 14(2), 225–233.
Gapp, R., & Fisher, R. (2008). Achieving organisational transformation: An action learning approach. Total Quality Management & Business Excellence, 19(6), 609–625.
Gifford, D. (1997). The value of going green. Harvard Business Review, 75(5), 11–12.
Hammer, B.A. (1997). A strategic approach to ISO 14000. Corporate Environmental Strategy, 4(2), 47–52.
Hemsworth, D., Sanchez-Rodriguez, C., & Bidgood, B. (2008). A structural model of the impact of quality management practices and purchasing – related information systems on purchasing performance: A TQM perspective. Total Quality Management & Business Excellence, 19(1 – 2), 149–162.
Hervani, A.A., Helms, M.M., & Sarkis, J. (2005). Performance measurement for green supply chain management. Benchmarking, 12(4), 330–353.
Hwang, Y.D., Lin, Y.C., & Lyu, J.J. (2008). The performance evaluation of SCOR sourcing process – The case study of Taiwan’s TFT – LCD industry. International Journal of Production Economics, 115(2), 411–423.
Joreskog, K.G. (1993). Testing structural equation models. Newbury Park, CA: Sage. Kevan, T (2005). Modeling the future. Frontline Solutions, 6(1), 22–24.
Kline, R.B. (1998). Principles and practice of structure of structural equation modeling. New York: The Guilford Press.
Kuhre, W.L. (1998). ISO 14031: Environmental performance evaluation. Englewood Cliffs, NJ: Prentice – Hall.
Lockamy, A., & McCormack, K. (2004). Linking SCOR planning practices to supply chain perform-ance: An exploratory study. International Journal of Operations & Production Management, 24(11/12), 1192–1218.
Maruyama, G.M. (1997). Basics of structural equation modeling. Thousand Oaks, CA: Sage. Mebratu, D. (2001). Environmental competitiveness ‘Green’ purchasing. International Trade, 2,
11–13.
Mehta, J. (2004). Supply chain management in a global economy. Total Quality Management & Business Excellence, 15(5 – 6), 841–848.
Mendelson, N., & Polonsky, M.J. (1995). Using strategic alliances to develop credible green market-ing. Journal Consumer Marketing, 12(2), 4–18.
Min, H., & Galle, W.P. (1997). Green purchasing strategies: Trends and implications. International Journal of Purchasing and Materials Management, 33(3), 10–17.
Min, H., & Galle, W.P. (2001). Green purchasing practices of US firms. International Journal of Operations & Production Management, 21(9/10), 1222–1238.
Neto, J.Q.F., Bloemhof-Ruwaard, J.M., Nunen, J.A.E.E., & Heck, E. (2008). Designing and evalu-ating sustainable logistics networks. International Journal of Production Economics, 111(2), 195–208.
Noci, G. (1997). Designing ‘green’ vendor rating systems for the assessment of a supplier’s environ-mental performance. European Journal of Purchasing & Supply Management, 3(2), 103–114. Ofori, G. (2000). Greening the construction supply chain in Singapore. European Journal of
Purchasing & Supply Management, 6(3 – 4), 195–206.
Park, S., Hartley, J.L., & Wilson, D. (2001). Quality management practices and their relationship to buyer’s supplier ratings: A study in the Korean automotive industry. Journal of Operations Management, 19, 695–712.
Rao, P., & Holt, D. (2005). Do green supply chains lead to competitiveness and economic per-formance? International Journal of Operations & Production Management, 25(9 – 10), 898–916.
Roder, A., & Tibken, B. (2006). A methodology for modeling inter – company supply chains and for evaluating a method of integrated product and process documentation. European Journal of Operational Research, 169, 1010–1029.
Sarkis, J. (2003). A strategic decision framework for green supply chain management. Journal of Cleaner Production, 11, 397–409.
Schlegelmilch, B.B., Bohlen, G.M., & Diamantopoulos, A. (1996). The link between green purchas-ing decisions and measures of environmental consciousness. European Journal of Marketpurchas-ing, 30(5), 35–55.
Seuring, S., & Muller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16, 1699–1710.
Supply-Chain Council. (2006). Supply chain operations reference model Version 7.0 overview. Retrieved from http://supply_chain.org
Supply-Chain Council. (2008). Supply chain operations reference model Version 9.0 overview. Retrieved from http://www.supply_chain.org/galleries/public_gallery/SCOR%209.0% 20Overview%20Booklet.pdf
Vachon, S., & Klassen, R.D. (2008). Environmental management and manufacturing performance: The role of collaboration in the supply chain. International Journal of Production Economics, 111(2), 299–315.
Walton, S.V., Handfield, R.B., & Melnyk, S.A. (1998). The green supply chain: Integrating suppliers into environmental management processes. International Journal Purchasing Material Management, 34(2), 2–11.
Wang, G., Huang, S.H., & Dismukes, J.P. (2004). Product – driven supply chain selection using inte-grated multi – criteria decision – making methodology. International Journal of Production Economics, 91, 1–15.
Xelocity. (2008). ProcessWizard software. Retrieved from http://www.process_wizard.com Zhu, Q., & Sarkis, J. (2004). Relationships between operational practices and performance among
early adopters of green supply chain management practices in Chinese manufacturing enter-prises. Journal of Operations Management, 22, 265–289.
Zhu, Q., Sarkis, J., & Geng, Y. (2005). Green supply chain management in China: Pressures, pratices and performance. International Journal of Operations & Production Management, 25(5 – 6), 449–468.
Zhu, Q., Sarkis, J., & Lai, K.H. (2007a). Green supply chain management: Pressures, practices and performance within the Chinese automobile industry. Journal of Cleaner Production, 15, 1041–1052.
Zhu, Q., Sarkis, J., & Lai, K.H. (2007b). Initiatives and outcomes of green supply chain management implementation. Journal of Environmental Management, 85, 179–189.
Zhu, Q., Sarkis, J., & Lai, K.H. (2008). Confirmation of a measurement model for green supply chain management practices implementation. International Journal of Production Economics, 111(2), 261–273.
Appendix Questionnaire
1. Explanation for the planning phase of green purchasing
(1) P1: The company sets up the improvement team for green purchasing, and describe in
detail the strategy of green purchasing in order to achieve stated environmental objec-tives and targets.
(2) P2: Develop knowledge of green purchasing practices in order to analyse economic and
environmental impacts of green purchasing, and to evaluate the compliance with environmental policy, potentially significant environmental impacts, administrative matters, technological options, and cooperative partners.
(3) P3: Top managers need to refine and review the environmental objectives and policies of
green purchasing, and vigorously participate in the plan.
(4) P4: Team members establish the improvement project of green purchasing via historical
data collection and analysis, and identify environmental performance indices for measur-ing project.
2. Explanation for the doing phase of green purchasing
(1) D1: It must be developed to meet requirements of ISO 14001 for documented procedures,
as well as to monitor and measure the key operations and activities that bring significant impacts on the environment.
(2) D2: Managers need to clearly assign tasks to relevant purchasing personnel based on
specific targets and a documentation process.
(3) D3: The company records operations and activities that impact the environment
signifi-cantly, and systematically gathers and evaluates related data for further analysis. (4) D4: The company selects supplier with certification of ISO 14040 and asks them to
conduct life cycle assessment and provide reliable environmental conditions and data for their products.
(5) D5: The company selects supplier with certification of ISO 14001, and reduces costs and
difficulties of the material/service supply process generating minimum environmental impacts.
(6) D6: Managers consider the environmental impacts arising from delivery paths from the
supply source/delivery point to the destination/the warehouse of the firm, including the source of delivery, delivery patterns and packaging patterns for delivery on logistics systems.
(7) D7: The company selects suppliers with green label products or certification of ISO
14020 in order to reduce any environmental impact, and intends to take up social responsibility.
3. Explanation for the studying phase of green purchasing
(1) S1: An effective performance evaluation system is required to develop for measuring the
actual environmental performance of green purchasing; appropriate corrections should be conducted for non-conformance with predetermined objectives and targets. (2) S2: An internal process and management tool used to evaluate an organisation’s
environ-mental performance through ISO 14031, which is designed to provide reliable and ver-ifiable information for management.
(3) S3: It develops an indicator system to measure environmental performance of green
pur-chasing and provides feedback to improve a series of processes.
(4) S4: The company makes a qualitative review on the environmental aspects and impacts,
legal requirements, and relevant data of organisation conformity arising from green pur-chasing, picking out and identifying problems, and conducts corrections to improve the performance.
(5) S5: The company reduces waste of materials for designs and manufacturing according to
ISO 14025 procedures, and develops new resources.
(6) S6: The company conducts life cycle assessment as well as development and
improve-ment for products according to ISO 14040 procedures, which can be references for man-agers’ strategic planning in order to further enlarge the product market.
4. Explanation for the acting phase of green purchasing
(1) A1: The company standardises the process and procedure for projects which conform to
objective and targets of green purchasing.
(2) A2: The company increases purchasers’ knowledge in implementing green purchasing
practices through training, and learns new methods for solving problems.
(3) A3: It develops a new indicator system to measure environmental performance of green
purchasing for controlling and maintaining a company’s compliance with the require-ment for continuous improverequire-ment in environrequire-mental performance.
(4) A4: Top managers proactively participate in project implementation and assist/support
related works.
(5) A5: To conduct analysis to next cycle/planning phase in respect of the non-compliance
with objectives and targets of green purchasing in order to formulate a new environ-mental strategy for continuous improvement in environenviron-mental performance.
(6) A6: Relevant strategies of green purchasing must be helpful for internal and external
coordination/communication and to be embedded in the organisational culture. 5. Explanation of the level 3 process elements of the SCOR model
(1) S1.1: Scheduling and managing individual deliveries of products according to
procure-ment contracts or purchase orders, including electronic data interchange, kaban system, synchronisation between sourcing and making process, consignment inventory management and vendor managed inventory.
(2) S1.2: The process and associated activities of receiving products according to contract
requirements, including suppliers’ certification procedures, bar coding, deliveries balanced, suppliers’ direct delivery and suppliers’ agreements.
(3) S1.3: The process and relevant activities which determine whether products meet
require-ments or not, including supplier certification programs, bar coding, deliveries balanced, supplier direct delivery and replacing defective material for supplier.
(4) S1.4: To transfer accepted products to the appropriate stocking location within the supply
chain, including all of the activities associated with repackaging, staging, transferring and stocking products.
(5) S1.5: There is a payment process which is mutually recognised for suppliers’ products and
services, including invoice collection, invoice matching and the issuance of checks. 6. Explanation of the level 1 performance metrics of the SCOR model
(1) R1: The product is delivered according to specification, location, and delivery time with
no damage, and is accepted by customers.
(2) RP1.1: Cumulative lead-time required for sourcing products from internal and external
suppliers; for example, inside-plant planning, supplier lead time, receiving, handling, etc. (3) F1: The company can achieve an unplanned sustainable 20% increase in delivery
quantity.
(4) F2: The maximum sustainable percentage increase in delivery quantity can be achieved
within 30 days.
(5) F3: Sustainable reduction in order quantity within 30 days priors to delivery can be
accepted with no inventory or cost penalties and with prioritisation of delivery. (6) C1: All direct and indirect expenses associated with operating business processes across
the supply chain.
(7) C2: The cost associated with buying raw materials and producing finished goods includes
direct costs of labor and materials and indirect costs of overhead.
(8) Aa: The time it takes for an investment to flow back into the company after it has been
spent for raw materials.
(9) Ab: The return an organisation receives on its invested capital in supply chain fixed assets.
