4. Experiment Result
4.1 Data Collection
4.1.3 Central Core papers
documents during the factor ng.
ation Data
SCM documents were collected from the Google scholar search engine. We used “Supply C
mine which documents were the most cited fellows. It was difficulty to determine a core paper dataset. Once this core set of SCM documents was identified, it was necessary to limit search terms to avoid retrieving misty subjects.
The core papers allow a delimitation of the area under study on the basis that a scientific paper can be included when it cites one or more such source papers (Acedo, Barroso, & Galan, 2006). The most widely used criterion is the number of cites of papers, therefore, we take the most significant works representing the study field to be the core
analysis and multidimensional scali
In this study, because of SCM being a field over the past decades, so we primarily collected data by means of a cited number, year and authors of papers. Some part core papers belong to Science Citation Index (SCI) or Social Sciences Citation Index (SSCI). The core papers represent assemblies’ documents which share SCM subject, theory, or common methodology and describe current investigation. In addition, by using co-citation method, the more coherent and integrated discipline or sub-areas of SCM is the more scientific community determined.
23
r list with assigned numbers
No.
citations (2007)
Table 4 Core pape
Title Count of Impact Factor
v01 Supply Chain Management: A Strategic Perspective (Bechtel & Jayaram,
239 -- 1997)
v02 Supply Chain Management: More Than a New Name for Logistics
531 --
v03 Supply Chain Redesign (Hewitt, 1994) 76 --
v04 Characteristics of Supply Chain Management and Purchasing and Logistics Strategy (Cooper & Ellram (Cooper et al., 1997)
the Implications for
, 1993) 259 --
Supply Chain Management : Implementation Issues and Research
er, 2000) 387 --
v06
e Supply Chain: The Impact of n (Chen, Drezner, Ryan, &
Simchi-Levi, 2000)
468 1.931
v11
An empirical investigation into supply chain management: A perspective
of Information Sharing in a Two-Level Supply Chain (Lee, So,
0) 438 1.931
v18 Supply chain partnerships: Opportunities for operations research (Maloni
& Benton, 1997) 234 1.096
v19 The four roles of supply chain management in construction (Vrijhoef &
Koskela, 2000) 106 --
v20 Supply chain postponement and speculation strategies: How to choose the
right strategy (Pagh & Cooper, 1998) 152 --
v21 Performance measures and metrics in a supply chain environment
(Gunasekaran, Patel, & Tirtiroglu, 2001) 227 1.054
v22 The Agile Supply Chain Competing in Volatile Markets (Christopher,
2000) 233 0.911
v05 Opportunities (Lambert & Coop
Issues in Supply Chain Management (Lambert & Cooper, 2000) 443 0.911 v07 The Role of the Internet in Supply Chain Management(Lancioni et al.,
2000) 172 0.911
v08 The Bullwhip Effect in Supply Chains (Lee, Padmanabhan, & Whang,
1997) 934 0.849
v09 Information Distortion in a Supply Chain: The Bullwhip Effect (Lee,
Padmanabhan, & Whang, 2004) 1308 1.931
v10
Quantifying the Bullwhip Effect in a Simpl Forecasting, Lead Times, and Informatio
Supply chain design and analysis: Models and methods (Beamon, 1998) 380 0.995
v12 on partnerships (Spekman, Kamauff Jr, & Myhr, 1998) 237 -- v13 Defining supply chain management (Mentzer et al., 2001) 249 --
v14 A framework of supply chain management literature (Tan, 2001) 200 -- v15 Defining supply chain management: a historical perspective and practical
guidelines (Lummus & Vokurka, 1999) 132 --
v16 Supply Chain Inventory Management and the Value of Shared Information
(Cachon & Fisher, 2000) 448 1.931
v17 The Value
& Tang, 200
24
No. Title Count of Impact Factor citations (2007)
v23 An integrated model for the design of agile supply chains (Christopher &
Towill, 2001) 121 --
v24 etoric and reality of supply chain integration (Fawcett & Magnan,
86 -- v25 will revolutionize supply chain logistics (Bowersox,
113 -- 0.911
1.435 Supply chain management in theory and practice: a passing fad or a
v32 96 --
v33 management processes (Croxton, Garcia-Dastugue,
76 --
v34 427 0.849
v35 Squaring lean supply with supply chain management (Lamming, 1996) 142 1.054 v36 Supply-Chain Management: The Industrial Organisation Perspective
192 -- v37 WHAT IS THE RIGHT SUPPLY CHAIN FOR YOUR PRODUCT?
905 --
v38 nt: Strategies for Reducing Cost
670 --
v39 616 --
v40 anagement: an analytical framework for critical literature
220 -- v41 nagement: Relationships, Chains and Networks (Harland,
282 1.534
v42 408 --
v43 gration on operating performance
54 --
v44 277 --
v45 chain migration from lean and functional to agile and customized
(Christopher & Towill, 2000) 148 0.913
The rh 2002)
Ten mega-trends that Closs, & Stank, 2000)
v26 New Managerial Challenges from Supply Chain Opportunities (Ballou,
Gilbert, & Mukherjee, 2000) 122
v27 Special research focus on supply chain linkages: Challenges for design and
management in the 21st century (Mabert & Venkataramanan, 1998) 113
v28 fundamental change? (Chandra & Kumar, 2000) 81 --
v29 Causal linkages in supply chain management: An exploratory study of
North American manufacturing firms (Narasimhan & Jayaram, 1998) 111 1.435 v30 Power, value and supply chain management (Cox, 1999) 129 0.913 v31 Leagility: Integrating the lean and agile manufacturing paradigms in the
total supply chain (Naylor et al., 1999) 249 0.995
A Total Cost/Value Model for Supply Chain Competitiveness (Cavinato, 1992)
The supply chain Lambert, & Rogers, 2001)
Effective supply chain management (Davis, 1993)
(Ellram, 1991) (Fisher, 2003)
Logistics and Supply Chain Manageme and Improving Service (Christopher, 1999)
Introduction to supply chain management (Handfield & Nichols, 1999) Supply chain m
review (Croom et al., 2000) Supply Chain Ma
1996)
Integrating the supply chain (Stevens, 1989) The impact of supply chain inte (Armistead & Mapes, 1993)
International supply chain management (Houlihan, 1985) Supply
25
(
No. Title Count of
citations
Impact Factor 2007)
v46 Supply chain management and advanced planning––basics, overview and
challenges (Stadtler, 2005) 71 1.096
v47 Information sharing in a supply chain (Lee & Whang, 2000) 323 0.356
) 2.054
v48 The nature of interfirm partnering in supply chain management (Mentzer,
Min, & Zacharia, 2000 100
26
Results and discussio
of ial netw sing
pa lar "ego e) is
"embedded" (connected to) its "neighborhood" (the actors that are connected to ego, and their connections to one another) and to the larger graph (Hanneman, 2001).
To illustrate, figure 9 depicts the papers of k-core analysis of social network. Subgroup can be identified by the measurements of component. So we can focus on the subgroup and the number of citations of papers. To use K-core function of UCINET 6.0 program would run to form the different color subgroup of social community.
On the left side, paper number 54, 74, 95, 157, 170 and 178 have no relationship with other members of the social network community. Other papers form the social network community of SCM. We could regard the strong relationship of papers which are inside the blue round shape as the hub.
4.2 n
UCINET 6.0 is a good helpful tool to deal with the complexity soc ork. U colors and shapes is a useful ways to convey information about what “type” of actor each node is. A good drawing can also help us to better understand how a rticu " (nod
Figure 9 Papers of Social network analysis
27
28
UCINET 6.0 can use a node shape to deal with the complexity of social network. By using UCINET 6.0, we could find out the part in which each node has cited number larger than 50 times. As described in Figure 10, 48 nodes were surrounded by a blue round.
From the 48 core papers above, we built a ro (see Figure 11). Then, we transformed the co-citation matrix in atrix. However, we could not find the weak relationships among papers.
w co-citation Matrix to a Pearson correlation m
Figure 10 Principal component of Social network
Figure 11 Co-citation Matrix
Table 5 shows the results of the factorial analysis with varimax rotation which has the advantage of showing the loads on more than one factor and expresses the importance of the variables loading on a given factor. We rank the factor loadings on papers with a 0.40 minimum cutoff point. Six factors are extracted, and they explain 74.464% of total variance.
The first factor accounts for 43.404% of the variance and the second for 10.583%. The other results are 9.008% (factor 3), 5.735% (factor 4), 2.931% (factor 5) and 2.803% (factor 6).
29 29
30
Table 5 Factor analysis with factor loadings at 0.40 or higher
No. Authors Year Factor v 33 Croxton,Garcia-Dastugue, Lambert, &
Rogers 2001 .836
v 06 Lambert & Cooper 2000 .835 v 26 Ballou, Gilbert, & Mukherjee 2000 .829
v 14 Tan 2001 .817
v 15 Lummus & Vokurka 1999 .806
v 38 Christopher 1999 .778
v 27 Mabert & Venkataramanan 1998 .760
v 07 Lancioni et al. 2000 .753
v 02 Cooper, Lambert, & Pagh 1997 .724
v 11 Beamon 1998 .705 .401
v 19 Vrijhoef & Koskela 2000 .700
v 21 Gunasekaran, Patel, & Tirtiroglu 2001 .696 .426
v 35 Lamming 1996 .688
v 28 Chandra & Kumar 2000 .680
v 24 Fawcett & Magnan 2002 .680 .460
v 34 Davis 1993 .636 .456
v 29 Narasimhan & Jayaram 1998 .625
v 25 Bowersox, Closs, & Stank 2000 .554
v 30 Cox 1999 .534 .444
v 10 Chen, Drezner, Ryan, & Sim .879
v 17 Lee, So, & Tang 3
v 1
v 08 Lee, Padmanabhan, & Whang 1997 .793
v 47 Lee & Whang 2000 .632 .427
6 Cachon & Fisher 2000 .840
v 09 Lee, Padmanabhan, & Whang 2004 .730
31
In T , Factor 1 is the best primary factor, and the factor name is “Effective managed fra o pective of SCM”. It includes 28 core papers. Many kinds of topics are covered in this factor. 28 core papers are divided to five groups.
e des papers [v13], [v15] and [v39], and it introduces and defines the
su c
e rs [v1], [v4], [v14], [v30], [v33] and [v37] (overlaps in the Fa 6 perspective as C er & Ellram (1993) [v4] focus on purchasing and logistics strategy, Tan (2001) reviews the literature to mer e the modern ear of
a i opera , ma and logistics ma ent, and
Croxton et al. (2001) [v33] provide strategic and operational descriptions of ea h of the eight supply chain processes.
e d group of papers [v2], [v5], [v6], [v11], [v18] (overlaps in the Factor 2), [v26], [v27], [v28], [v32] and [v35] proposes the concept, theory, model, and guidance for business
lea e issues to m ke a decision
an nage the SCM well.
e apers [v3], [v7], [v21], [v25] and [v34] focus on the effective and eff c ewitt (1994) [v3] propo pply chain redesign pro e the process eff c ness. Lancioni et al. (2000) [v7] discuss how the internet is be s major components of supply chains. Bowersox et al. (2000) [v21]
indicate the ten mega-trends which would ly substantial change in logistics practices able 5
mew rk & strategic pers
Th first group inclu pply hain management.
Th second group of pape
ctor ) focuses on strategic such oop
g
holist c and strategic approach to tions terials, nagem c
Th thir
ders and managers to overcom of challenges, and hope them a d ma
Th fourth group of p
icien y issues. H ses su to im v
icien y and process effective ing u ed in managing the
imp
32
am s hain partners as they strug o establish efficient, effective, and relevant product/service solutions for end-customer. Gunasekaran et al. (2001) [v21] and Davis (1993) [v34] address the performance measures in supply chain.
do not share a common voice and have moved slowly to bridge the gaps that separate them. Vrijhoef & Koskela (2000) [v19
ir proposed conceptual framework to investigate the key causal linkages in SCM by using structural equation modeling techniques.
effect in a supply chain. Chen et al. (2000) [v10] propose two factors which are demand forecasting and order lead time in their model, and assume them to cause the bullwhip effect. And they demonstrate that the bullwhip effect can be reduced, but not completely eliminated. Information system technology can now work a tight coordination between supply chain partners. The researches of [v16], [v17], [v18] and [v47] are all about information sharing. Information technique, such as Electronic Data Interchange (EDI) and Vend
ong upply c gle t
Other group of papers [v12], [v19], [v24] and [v29] is about empirical analysis. For instance, Spekman et al. (1998) [v12] indicate that buyers and sellers
] identify that SCM has four specific roles in construction, and Narasimhan &
Jayaram(1998) [v29] test the
The Factor 2 “Information sharing issue in SCM” covers 7 papers [v8], [v9], [v10] [v16], [v17], [v18] and [v47], and another paper [v11] (locates in the Factor 2). The big reason for causing “bullwhip effect” is information distortion. The issue is related to bullwhip effect papers which are [v8], [v9], and [v10] papers. Lee et al. (1997) [v8], (2004) [v9] discuss the phenomenon of bullwhip
or-Managed-Inventory (VMI), plays an important role in SCM for sharing information.
Cachon & Fisher (2000) [v16] hope to improve increasing delivery frequency by reducing shipment batch sizes, and Lee et al. (2000) [v17] hope to provide significant inventory reduction and cost savings to the manufacturer, Beamon (1998) [v11] provides a focused review of literature in multi-stage supply chain modeling, and it addresses the demand
33
v20], [v22], [v23] and [v31]
papers, and other papers [v21], [v24], [v30] and [v34] which is primarily located in the Facto
ding supply chains from a strategic as well as from an operational perspective. Papers [v21] and [v34] propose a framework for m
distortion and variance amplification issues of supply chain modeling.
The Factor 3 “Agile and lean SCM’s strategies” includes [
r1. Pagh & Cooper (1998) [20] identify a framework for selecting postponement and speculation strategies to achieve delivery of products in a timely and cost-effective manner.
Christopher (2000) [v22] suggests that the key to survive in these changed conditions is through “agility”, in particular, by the creation of responsive supply chains. Christopher et al.
(2001) [v23] and Naylor et al. (1999) [v31] indicate the role of “lean” and “agile” into supply chains. Cox (1999) [v30] indicates a case which makes for understan
easuring the performance of supply chain management. Christopher &
Towill (2000) [v45] propose a cyclic migratory model which describes the PC supply chain attributes during its evolution from traditional to its present customized “leagile” operation.
As have described from above statements, according to the business adopting different strategic of SCM would result different performance for managing the supply chain management.
The Factor 4 “Integrated evolution of SCM” owns 6 papers which are [v40], [v43], [v44], [v45], [v46] and [v48]. Croom et al. (2000) [v40] recognize that developments in SCM require multi-disciplinarity. Armistead & Mapes (1993) [v43] investigate the contribution of new manufacturing techniques and approaches to increase integration across the value chain on manufacturing performance. Houlihan (1985) [44] describes the approaches how to manage change in international chains. Christopher & Towill (2000) [v45] encourage “supply chain migration from lean and functional to agile and customized”. Stadtler (2005)[v46]
points out interdisciplinary research incorporating computer science, accounting and
34
solution capabilities.
Mentzer et al. (2000) [48] provides an inclusive “partnering” phenomenon with the environm
y of functional products and responsive supply of innovative product).
organizational theory, etc., for their great progress in modeling and
ental pressures, antecedents, orientation and consequences of strategic and operational partnering for vertical relationships within retail supply chains.
The Factor 5 “Collaborative Supply Chain” involves papers: [v41] and [v42], and paper [v47] which locates in the Factor 2. Harland (1996) [v41] summarizes the system approach that how to manage relationships, chains and networks in SCM. Stevens (1989)[v42] points out involving some degree of collaboration to solve bottlenecks in the supply chain, and overcome bumps in demand or supply. Lee & Whang (2000) [v47] describe the types of information shared because it is a basic enabler for supply chain partners to work in tight coordination.
Finally, the Factor 6 is “Choosing right supply chain”. Fisher (2003) [v37] indicates the cause of plaguing problems, which many supply chains is a mismatch between the type of product (they are either primarily functional or primarily innovative) and the type of supply chain (they are efficient suppl
35
or 4 has paper [v40], Factor 5 has papers [v41] and [v42], and Factor 6 has paper [v37].
Table 6 Factor Topics
In Figure 12, by using social network analysis, we could group each factor inside a blue round shape. In total 178 papers, we measure the importance of each paper in the social network by using degree criterion, then for each factor encloses the papers whose degree is larger than or equal to 70 inside a green circle. We consider them maybe play important roles in the SCM. Factor 1 has papers [v2], [v5], [v6], [v12], [v13], [v14], [v38] and [v39]. Factor 2 has papers [v8] and [v9], Fact
Figure 12 Factors of Social network Factor 1: Effective managed framework & strategic
perspective of SCM
Factor 2: Information sharing issues in SCM Factor 3: Agile and lean SCM’s strategies Factor 4: Integrated evolution of SCM Factor 5: Collaborative Supply Chain Factor 6: Choosing right supply chain
Factor 1
Factor 6 Factor 3
Factor 5
Factor 4
Factor 2
36
After comparing the results of Figure 12 and Figure 13, we found that the papers [v2], [v5], [v6], [v8], [v9], [v13], [v14], [v37], [v38] and [v39] are in the red round shape in the center of Figure 13. Furthermore, by double checking the results of high importance of papers, we could find these main trends papers which play important roles in SCM field ([v12] and [v40] are excluded). However, others papers [v41] and [v42] have high importance in minor trends papers.
In Figure 13, Factor 1 locates in quadrant II, III, IV, Factor 2 locates quadrant I, Factor3 locates in IV, Factor 4 and Factor 5 locate in quadrant I and IV and Factor6 locates in III.
Factor 1, Factor 3 and Factor 6 are about “effective framework or strategic perspective of SCM”, and the topics of SCM of Factor 4, Factor 5 are related to “integration and collaboration of SCM”. Therefore, we learn that Factor 2 plays as a bridge between the group1 (includes Factor1, Factor3 and Factor 6) and group2 (includes Factor 4 and Factor 5).
From the above result, we could see the critical role of information sharing issues in the inter-relationships between a company and its collaborative participants, and the intra-relationships among the divisions in a company.
The multidimensional analysis provides a graphic vision of the different trends. In Figure 13, the y-axis shows the division between “The framework and strategic perspective of SCM”
trends and “Information sharing & Integration of SCM” trends. We name the “Information sharing & Integration of SCM” in which there are three kinds of factors (which are Factor 2
“Information sharing issues in SCM”, Factor 4 “Integrated evolution of SCM”, and Factor 5
“Collaborative Supply Chain”) in the right-hand side. Then we name the “The framework and strategic perspective of SCM” in which also has other three kinds of factors (which are Factor 1 “Effective managed framework & strategic perspective of SCM”, Factor 3 “Agile and lean SCM’s strategies” and Factor 6 “Choosing right supply chain”) in the left-hand side.
37
Figure 13 Multidimensional Scaling
Factor 2 Factor 4
Factor 6 Factor 5 Factor 1
Factor 3
38
5.1 Conclusion
l structure and movement in the SCM and in other areas. According to this study experiment results, we can find the three findings which are w
S map to
5. Conclusion and Future Works
The study combines exploratory factor analysis and social network analysis for SCM to carry an empirical study. We hope that based on our research results to help specialists easily realize the main trends, understand of intellectua
orth summarizing below:
First, by using social network analysis and the threshold of the cited number defined, we found the core papers of SCM field to do factor analysis. The factor analysis extracted six factors, which are “Effective managed framework & strategic perspective of SCM”,
“Information sharing issues in SCM”, “Agile and lean SCM’s strategies”, “Integrated evolution of SCM”, “Collaborative Supply Chain” and “Choosing right supply chain”. We recognized the main trends were factor 1, factor 2, factor 3 and factor 4, and the minor trends were factor 5 and factor 6.
Second, comparing results from factor analysis and social network analysis, we leant the variable numbers of paper [v2], [v5], [v6], [v8], [v9], [v13], [v14], [v37], [v38] and [v39] had higher importance of main trends papers in SCM fields. While others papers [v41] and [v42]
had high importance in minor trends papers. Based on these papers, the specialists would extend the topic and discuss the issues of SCM
Lastly, by multidimensional analysis (MDS) providing a graphic vision of the different trends, we saw that y-axis made a clear division between “The framework and strategic perspective of SCM” trends in the left-hand side and “Information sharing & Integration of SCM” trends in the right-hand-side. We could also match these papers with the MD
se
39
1 nd group 2 (which are Factor 4 and Factor 5).
Researchers might benefit from for their future studies. However, this ly the first exciting step. earch iously required.
e which quadrant they belonged to and the topics they related to. In addition, the other worth point was that “information sharing issues” played a critical bridge between the group (which are Factor1, Factor 3 and Factor 6) a
these findings
study is on Therefore, future res es are obv
40
5.2 Future w
tions in our research, yet they also points out new possibilities for future research.
, and the result of Social network analysis maybe have more findings.
3. To
orks
There are some limita
1. To collect more papers: This method of investigation is not without problems, but it still lacks enough sample core papers to do analyze, in the future research, we can collect more sample papers of SCM fields to do an experiment. Maybe the larger the pool of core papers, then the more reliable the results is
2. To use other search terms about SCM: In our study we only use two search terms which are
“Supply Chain” and “Supply Chain management”. The title of our all core papers has Supply Chain or Supply chain management keywords. In addition, many other papers might use other search terms as related to SCM fields, and they do not use our search terms to be keywords. In the future research, we can investigate more search terms to find more core papers of SCM field in order to make a precise exploratory analysis.
expand other criterions to measure the relationships of papers in SCM: In this work, we use degree criterion of Social network analysis to measure the relationships among the papers.
For the future work, we could add others criterions such as density, closeness and betweenness to measure the network, group and the individual/node position status related to other nodes (Hanneman, 2001).
41
ion and main trends. Strategic Management Journal, 27(7), 621-636.
Armistead, C. G., & Mapes, J. (1993). The impact of supply chain integration on operating from Supply Chain Opportunities. Industrial Marketing Management, 29(1), 7-18.
Beamon, B. M. (1998). Supply chain design and analysis: Models and methods. International
Journal of Production Economics, 55(3), 281-294.
Bechtel, C., & Jayaram, J. (1997). Supply Chain Management: A Strategic Perspective.
Bechtel, C., & Jayaram, J. (1997). Supply Chain Management: A Strategic Perspective.