Supply Chain Management with Leanness and Agility: A Value Network Perspective with a B2B Apparel Case Study

Transcription

1 J Jpn Ind Manage Assoc 64, , 2014 Original Paper Supply Chain Management with Leanness and Agility: A Value Network Perspective with a B2B Apparel Case Study Nayanapriya GUNAWARDHANA 1, Sadami SUZUKI 1 and Takao ENKAWA 1 Abstract: Supply chain management (SCM) utilizes lean, agile and hybrid (leagile) supply chain models to stimulate consequences of increased globalization and behavioral changes of information rich consumers. Although SCM conceptually inherits a holistic view, firm level analysis occupies the majority of research. This research work attempts to uncover a new approach for SCM, exploring leanness and agility of value networks. Through a case study of six different global apparel value networks, the research provides important insights to SCM. While providing evidence that SCM is more accurately measured in the value network level, results reveal that different value networks focus on different areas of SCM. Further, owing to lean-agile characteristics of value networks, they develop unique capabilities in SCM. The paper proposes and tests a framework with lean-agile filtration for customer segmentation in a B2B context. Key words: Supply chain, demand chains, value network, SCM orientation, SCM capabilities 1 INTRODUCTION A high degree of internationalization of operations, technological developments, dramatic changes of customer requirements, and demand for variety and rapidity have created new dimensions of competition for business firms. Consequently, competition has gone beyond a firm s control and it is often said that competition now is between supply chains, rather than between individual firms. These developments in the business environment have accelerated research on supply chain management (SCM). As a result, there are several concepts developed by both researchers and practitioners to stimulate the complexity and competition. Lean, agile and leagile supply chain concepts as well as production paradigms such as quick response and mass customization are such developments. The lean manufacturing concept was first introduced as a weapon of success by Toyota, named the Toyota Production System. Lean enterprise was the conceptual extension of the lean manufacturing concept which adopted the holistic view of SCM [1]. The main idea behind the lean supply chain concept was to compete with cost by minimizing every sort of waste including time. Leveled schedules and smoothing demand were prerequisites for lean supply chains. Markets changed rapidly calling for variety (offered rapidly) which caused high uncertainty in demand and changes. Agile supply chains came as a solution aiming at responding to changes rapidly. Subsequently, different types of leagile supply chains were introduced. This can be seen as a hybrid or a mixed approach of lean and agile 1 Department of Industrial Engineering and Management, Tokyo Institute of Technology, Tokyo, Japan Received: October 29, 2012 Accepted: September 19, 2013 supply chain concepts. There is a popular argument that either pure lean or pure agile supply chains are not practical for a company to adopt, therefore the appropriate strategic mix of conceptual characteristics of the two concepts has to be found, implementing a hybrid approach [1],[2]. Supply chain orientation is defined as the recognition of the systemic, strategic implications of the tactical activities involved in managing the various flows in a supply chain. [3] This definition indicates that SCM orientation refers to the areas that a particular supply chain focuses on in order to deliver the desired output to the market managing various flows of supply. SCM capability is defined as the building blocks for SC strategy and the source of competitive advantage for firm success. [4] This gives the insight that the capabilities are the underlying latent factors which are combinations of SCM practices emphasized by the management in order to meet customer requirements. For a specific product or a product portfolio, customer requirements of a particular market segment for variety, variability and time-to-market dictate the needed leanness and agility within the value network engaged in serving that particular market segment. Consequently, a retailer serving different market segments will need different value networks with different upstream members (vendors, suppliers) to cater to market segments demanding different levels of leanness/agility. The current context with outsourcing in matured industries develops vendors and suppliers who act on moving up in the value chain, developing broad capabilities to cater to diversity [5], [6]. The resulting value networks will give vendors and suppliers a customer portfolio with different lean-agile requirements. In this context, there are three questions to be researched. 1) What is the level of analysis that this Vol.64 No.4E (2014) 591

2 appropriateness can be identified for an organization with diverse customer profiles? 2) How do companies set their orientations for SCM with such diverse customers? 3)What capabilities do such diverse value networks develop to cope with different customer requirements? This research intends to address these issues, through an in-depth case study in six global apparel value networks in a garment vendor in Sri Lanka. Even though these are operated by a single vendor, they are distingushing in their business model, lean-agile configurations, and supply chain strategies. Focused demand chains (FDCs) defined by customer-based units (which is equal to value networks detailed in section 2.1) have been the company s approach to manage this diversity, which enables utilization of appropriate resources based on demand chain characteristics. With insights from past literature, the FDCs can be defined as structured units in an organization which are formed as different entities with different policies and supporting services aiming to serve diversified demands from distinguishing customer profile of the organization [7] - [9]. Section 2 provides a summary on literature related to supply chains, demand chains, value network concepts together with related research on leanness and agility in the supply chain context followed by an introduction of the Logistics scorecard (LSC), the main tool utilized in the research. Section 3 derives research hypotheses. Section 4 details the analytical approach with a case study description followed by results and discussion in section 5. Section 6 concludes the paper. 2 LITERATURE REVIEW 2.1 Supply Chain, Demand Chain, And Value Network Strategic focus on customers has been stressed in both marketing and SCM literature as the market characteristics changed rapidly in the past couple of decades [10], [11]. Literature suggests several strategic approaches for such a market orientation. The basic argument of all approaches and propositions is that SCM has to be designed from the customer backwards focusing on both efficiency and effectiveness in contrast to the traditional factory outward approach focused merely on efficiency [12] - [14]. A processoriented proposition for such customer-backward operations management calls for integrating marketing and SCM [10], [12] and bringing forward the notation of demand chain management (DCM) [10], [15]. Furthermore in the conceptual viewpoint, there is a strong argument that a value chain combines the separately operationalized supply chain (SC) and the demand chain (DC) [13], [14], [16], [17]. The demand chain is defined as an understanding of current and future customer expectations, market characteristics, and of the available response alternatives to meet these through the deployment of operational processes. [16] Another definition for the demand chain is a supply chain that emphasizes market mediation to a greater degree than its role of ensuring efficient physical supply of the product. [18] Supply chain on the other hand has been defined as the process of transferring goods from their points of origin to markets or to end consumers [19] Thus, DC and SC differ in their definitions as well. Langabeer et al. [20] is one of the most cited sources in distinguishing DC and SC. They argue that SCs are efficiencyfocused while DCs focus on effectiveness. SC processes are focused on execution while DC processes are focused more on planning and delivering value. The key driver of SCs is cost while it is cash flow and profitability for DCs. SCs are short-term oriented and DCs are long-term oriented. SC is typically the domain of tactical manufacturing and logistics personnel while DC is the domain of marketing, sales and strategic operations managers. These observations in the literature support the view that SCs and DCs are separate entities that form the total value chain. Moreover with the impact of outsourcing, the term network is rather more appropriate than the term chain. Since we also focus on segmenting or profiling customers for a customer-centric SCM approach, we absorbed these viewpoints in the literature and created the research framework. The upstream member s (tier 1 vendor) context is B2B which is our focus and we propose a SC segmentation based on leanness and agility of the customers. Value networks referred here are illustrated in Fig 1. There are six different value networks (referred to as FDCs in line with the company terminology and literature) since there are six different retailers. Customer segments are not in the research scope since vendor selection is based on the customer segment as it is the normal practice evidenced by many retailers [12] (Pages 58-60). Fig. 1 Value network focused in the research. 592 J Jpn Ind Manage Assoc

3 2.2 Leanness and Agility A Review A survey of the literature related to lean and agile supply spectrum revealed that there is a broad range of research, in terms of research focus, research method and level of analysis (whether the measured level is the company or the supply chain). Findings of the literature review are summarized in Table 1. The larger proportion of research occupies the strategy comparison area emphasizing that these concepts are entangled and still not concrete. Another major finding from the survey of literature was that most research takes supply chain as the level of measure. However, in-depth analysis revealed that these studies measure the supply chain for a range of products offered to a range of customers in their Table 1 Summarized categories of related literature Focus 1) Strategy comparison [2], [3], [4], [7], [9], [13], [15] 2) Evaluating strategies [6], [8], [10] with drivers 3) Strategy combination [11], [19], [20] models Level of analysis 1) Aggregate firm level [8], [9], [10], [7], [13] 2) Supply chain centered toward a downstream company [2], [3], [4], [6], [11], [15], [19], [20] Method 1) Conceptual with illustrations (case study) 2) Empirical/ empirical validation (survey) 3) Empirical (modelingsimulation, ANP, ISM) [3], [4], [10], [11], [19], [20] [7], [8], [9], [13] [2], [6], [15] aggregate level. Further, all this supply chain level research was either conceptual with qualitative case study illustration or modeling, but not empirical using surveys or any analysis tool. In research methods, case study dominates as it is said to be appropriate for defining and exploring a concept. A major gap can be identified in the literature with regard to level of analysis, since there is a bias towards downstream supply chain concentrating more on the front-end retailer. A single study was found with evidence that one particular company can have different FDCs [7], but it does not directly discuss lean/agile paradigm placements of FDCs. Therefore, we intend to fill that gap by focusing on an apparel manufacturer that caters to six global retailers. Further, this was conducted and focused on as exploratory research on supply chain management orientation and capabilities of demand chains in the microorganizational level. The micro-organizational level can be defined as the supply chain analysis level which considers the FDCs within one particular organization which is one member in the supply/ demand chain network. The intention of this approach is to provide in-depth insights on behavioral patterns of SCM, which differ even within one company, owing to the diversity of the company s customer profile. This research marks novelty in two classification streams as 1) research focus on strategy comparisons in terms of SCM orientation and capabilities (this combines the past research focuses; strategy comparison and evaluating strategies with drivers), and 2) a new level of analysis of FDCs with a microorganizational perspective eliminating the bias of evaluation in a downstream supply chain member. 2.3 SCM Logistics Scorecard The SCM logistics scorecard (LSC) is a tool to measure SCM performance which originated in Japan and has been applied in practice since The LSC is a joint creation of the Tokyo Institute of Technology and Japan Institute of Logistics Systems. It aims to achieve a balance between the dimensions of management/operational orientation, and performance/ performance driver orientation since the existing scorecards have been found as biased to one paradigm [21]. The LSC comprises four areas to assess SCM performance with 22 measurement items (Table 4). To reduce the response biases while enabling proper rating with no ambiguity on the current performance level, each measurement item is given five descriptive performance levels instead of using the Likert scale alone. The LSC which is a self-evaluating tool has been utilized in research on different SCM aspects such as cross-country SCM performance [22], impact of institutional environments on SCM performance [21], impact of ownership on SCM performance [23] and differences between high-tech and low-tech companies in SCM [24]. 3 RESEARCH HYPOTHESES 3.1 SCM Orientation Minimizing resistance to change, trust development among SC partners, centralized and collaborative planning have been identified as drivers for agile supply chains [25]. Workforce development is a key factor in the process of transition from a lean SC to an agile SC [26]. Long-term SC partnerships are desirable in a lean approach. Contrastingly, agile SCs demand fluid clusters, and flexibility to cater to the unanticipated demand fluctuations so that partnerships in agile SCs are not that concrete [27]. These drivers are directly related to the strategic alignment of a demand chain. Strategic alignment can be measured with items related to governing strategy and importance, information sharing and contractual bond with customers and suppliers, internal focus on customer satisfaction, employee training and Vol.64 No.4E (2014) 593

4 Table 2 Characteristics of focused demand chains Distribution channels FDC 1 3 Specialty stores Internet FDC 2 Mainly Internet, Phone 3 Catalogue, Store FDC 3 3 Specialty stores Internet FDC 4 38 Specialty stores Department stores Internet FDC 5 3 Specialty stores Internet FDC 6 Mainly Internet 2 Catalogue Market segments Volume & batch size No. of markets Make-tostock % Strategies College girls High Medium Quick response (reduce the base order, quickly replenish) All ages men & Low Low Mass customization women (Min. < 50) (MTS< 10%) Speedy logistics Young men & High High Mass production women Wide product range All ages men & High High Mass production women Wide product range Short lead times for vendors Young women Low- Medium Quick response (reduce the Medium base order, quickly replenish) Young Women Low Low Mass customization Speed logistics evaluation towards customer satisfaction and system optimization. Since most of them are seen as critical elements for the agile SC approach, it can be argued that comparative importance given for strategic interorganizational alignment should be high for agile supply chains: H1: Orientation towards strategic interorganizational alignment is higher in agile FDCs than in lean demand chains. Highly agile companies are said to be more customer focused [27], [28] while highly lean companies are product centered [27]. Planning becomes a key driver for agility of a supply chain [25] and manufacturing flexibility has a direct positive impact on agility of a firm or a system, whereas logistics/distribution flexibility doesn t prove a direct impact [29]. In characterizing the agile supply with virtual integration, it has been argued that agile SCs are more knowledge-based while lean SCs are more operations-based [27] indicating that agile SCs should give more emphasis to planning than lean SCs which are driven by leveled schedules. Lean SCs are driven by cost while agile SCs call for service and availability [30] so that planning becomes comparatively more critical for agile SCs than for lean SCs while logistics performance shows much importance for lean SCs. LSC, when specifying the performance levels for each assessment items states the best practice as Level 5. When planning and execution is considered, all items under this SCM area consider the integrated collaborative practice within the supply chain as the best practice. This means that higher area score represents chain-wide integrated collaborative practices. With these arguments it is preassumed that: H2: Agile FDCs focus more on collaborative planning and execution than logistics performance, being contrasting to lean FDCs which focus comparatively high on logistics performance than collaborative planning. Lean SCs call for operations-based integration while agile demand chains call for knowledge-based integration [27] meaning that utilization of information technology is more focused towards the operations side in lean SCs while agile SCs utilization is focused towards knowledge and information sharing. Thus, technologies such as EDI, RFID, etc. (which are operational applications) are more important for lean SCs. This is further supported by the fact that lean SCs prefer long-term SC partnerships so that technological establishments such as EDI are preferred in this paradigm while fluid clusters demanded or practiced in the agile paradigm calls for flexible, short-term partnerships based on the availability. In this sense, IT utilization in agile SCs can be more on information sharing and knowledge management than in its operational side: H3: Orientation towards IT utilization in operational aspects is higher in lean FDCs than agile demand chains. 3.2 SCM Capability Agile and lean supply chains have been contrasted in many ways providing clues that these supply chains differ in terms of inherent SCM capabilities. Capabilities developed in agile SCs should be highly flexible and service oriented while those of lean SCs should be focused on cost optimization with a leveled demand scheduling [31]. To investigate the differences in demand chains between the two paradigms we propose that: H4: SCM capabilities differ with leanness and agility in the demand chain, owing to the demand chains focus on cost and service/availability. 4 METHODOLOGY 4.1 Case Study The Focal FDCs In order to investigate SCM in the microorganizational level, a survey was carried out in a 594 J Jpn Ind Manage Assoc

5 Table 3 Utilizing the DWV 3 model for assessing demand chain agility Variable Lean Agile Duration of life cycle Measured by the product change over considering the main type of products (higher the change-over lower the life cycle) Time window for delivery Measured by the lead-time for manufacturing Volume Measured by the average quantity per product/ per style Variety Measured by the variation in terms of styling and value additions Variability Measured through the number of replenishments per season High 1 Low 1 Lean Hybrid/Leagile Agile Medium 2 Medium 2 Low 3 High 3 FDC 3 FDC 1 FDC 2 LEAN FDC 4 Fig. 2 Placement of FDCs in the lean-agile paradigm based on DWV 3 analysis company having six different FDCs operating with SBUs. It is an apparel manufacturing company catering to global retailers mainly in the US and Europe. FDCs in the company operate for each individual retailer and the SBUs comprise two FDCs per SBU which share managerial and other supportive resources as well as manufacturing facilities. The company s yearly earnings are approximate to 12 billion yen and the total number of employees exceeds including skilled labor. Table 2 summarizes the characteristics of the FDCs emphasizing that they are different in many SCM attributes. Researching inside one company controls many factors affecting SCM performance and approaches (as found in the literature) such as ownership, industry, institutional environment and firm size. FDC 5 FDC 6 AGILE through lean supply and medium-sized volumes while the sales are monitored daily to forecast the replenishment in a very limited time with or without process changes to adopt postponement. 4.3 Case study and Analytical Approach As stated before, LSC comprises four areas of SCM with 22 items of measurement each corresponding to a tactical SCM practice. The four assessment areas (which collectively become areas that the tactical activities are focused on) correspond well to the hypothesized SCM orientations. A higher average score of one area compared to another implies that the focus on the prior area is higher than the latter area of 4.2 Characterizing Value Networks with the DWV 3 Model We performed the analysis of FDCs utilizing the DWV 3 model [32] which has been utilized in a case study [7] to segment one lighting manufacturer to four different FDCs. The DWV 3 model is a widely utilized and cited tool for segmentation of supply chains due to its five broad dimensions that cover all characteristics affecting differentiations of supply chains [7], [11]. Table 3 illustrates the analysis criteria and Fig. 2 shows the resulting placements of FDCs along the lean-agile paradigm. Details in Table 2 further prove the fact that FDCs in the case study differ significantly. FDC 2 and FDC 6 which are MTO supply chains, have comparatively higher agile attributes, when responsiveness and flexibility is taken as the factor for agility [2], [28], [33]. FDC1 and FDC 5 with quick response strategies are close to the hybrid lean agile supply chain approach, which serves for the base demand with a reduction of forecast reliance Fig. 3 The research framework Vol.64 No.4E (2014) 595

6 SCM for a particular FDC. On the other hand, if the area score of a particular FDC is higher than that of another FDC, it implies that the prior FDC has a comparatively higher focus on that particular area of SCM. With this argument, the FDCs were analyzed using the average score of each area to test the hypotheses. SCM capabilities are the latent factors showing higher influence on total performance according to the cited definition in the introduction. For the 22 items of LSC, when grouped to factors with the corresponding factor score (Table 4), a particular group consists of the highest correlating practices for the factor. As argued in SCM capability criteria, factor scores of extracted factors covering these 22 measurement items were utilized to assess SCM capabilities. The research framework is outlined in Fig. 3. We collected responses for the LSC from employees of the six FDCs selecting respondents to cover all supply chain related job functions. Multiple responses per FDC increase the accuracy since perceptional biases are eliminated when multiple evaluations are done for the same FDC. The respondents were chosen as employees with and above the executive category to enhance the quality of data. The respondents comprised four main employment levels as: executive, senior executive, assistant manager and manager in each FDC. CEO, chief operational officers, and heads of FDCs represented the strategic management whom we interviewed with a structured questionnaire to enhance our knowledge on FDCs and to obtain qualitative data. Altogether 119 responses (74 from operational level, 42 from tactical level and 3 from strategic level) were gathered during the period of August to September in d.f. = 5 : 113 F-value p-value Strategic alignment Planning & Execution Logistics Performance IT utilization We performed the collection through the LSC as groups and individuals depending on the convenience of participants. That enabled them to provide true evaluations, avoiding reporting errors and biases due to fatigue and busyness. We explained the research outline and the contents of the LSC at the start of every data collection session. Further, we stressed that the evaluation boundary is the respective FDC that they are working in, but not the company in its aggregate level. Although respondents were allowed for discussions and information sharing during the survey, they were requested to give their own rating for the FDC. One session lasted for minutes. We used qualitative and quantitative data gathered from the senior management to analyze the FDCs, specially to characterize them with the DWV 3 model. 5 RESULTS AND DISCUSSION 5.1 SCM Orientation of Value Networks Average scores of the four assessment areas in the LSC were compared with ANOVA tests to assess the significance of the differences among the FDCs. Figure 4 illustrates the analysis results for FDCs separately in the graph on the left side, while the graph on the right side shows the results when FDCs are coupled in terms of the proximity in the lean-agile paradigm (illustrated in Fig. 2). As the graph in the left side and the ANOVA table above reveal, there is a statistically significant difference between FDCs, in terms of SCM orientation in the three areas; 1) planning and execution, 2) logistics performance and 3) IT utilization. As illustrated more clearly by the coupled FDC analysis, it can be seen that the agile FDCs score is higher than leagile and lean FDCs in strategic alignment towards SCM, which measures efforts to establish proper integration with d.f. = 2 : 116 F-value p-value Strategic alignment Planning & Execution Logistics Performance IT utilization Agile Lean Fig. 4 SCM orientations in individual FDCs (left side) lean, agile and hybrid groups (right) 596 J Jpn Ind Manage Assoc

7 customers and suppliers, workforce improvements for customer satisfaction supporting our first hypothesis. As the graph on the left side with its relevant ANOVA results on top reveals, the relative importance for planning and execution over logistics performance is high in agile FDCs, compared to in lean FDCs while the highest difference is seen in less agile (leagile) FDCs which couple the lean and agile approaches in the FDC business model. This observation supports our second hypothesis stating that agile FDCs put higher focus on collaborative planning and execution compared to logistics performance, in contrast to lean FDCs. Agile FDCs reliance on service and availability as market winners and lean FDCs dependence on cost as the main market winner can be account for this observation. Priority on cost optimization tends to lie with logistics costs in the highly outsourced, expanded supply network context. Further, lean value networks are operating with leveled schedules and demands, so that planning and execution succeed with standardization. Criticality of network-wide collaborative planning in agile contexts were discussed in hypothesizing and it has been empirically validated here. The highest difference between these two elements seen in hybrid FDCs is interesting and this may be explained by its hybrid model with leveled demand (for the base demand with a reduced risk of forecasting) as well as volatile demand (read and react approach looking at recent sales to fill up the buffer needed). Importance given for utilization of IT tools in operations is high in lean FDCs as we hypothesized, with the argument that lean supply requires operations centered on optimization, where the competitive edge lies in operations core with waste minimization. Further, lean supply calls for long-term SC partnerships so that linkages made through IT with a heavy initial investment are fruitful for such value networks. On the other hand, agile supply calls for responsiveness and flexibility working with fluid clusters where long-term SC partnerships are not mandatory or they are desirable rather than essential. Thus, their competencies lie with rapid configuration so that the investment in IT has to be on flexible information sharing along the optional value networks to meet the specific task in the market. Consequently, investment in IT in agile Table 4 Factor extraction to derive SCM capabilities LSC area Assessment item Factor Corporate strategy & inter-org. alignment (1-1) Corporate strategy regarding logistics and its importance (1-2) Definition of supplier contract terms & degree of information sharing (1-3) Definition of customer contract terms & degree of information sharing (1-4) System for measurement and improvement of customer satisfaction (1-5) System for employee training and evaluation (2-1) Strategies for optimizing logistics system resources based on design for logistics Planning & execution (2-2) Understanding of market trends & accuracy of demand forecasting (2-3) Accuracy and adaptability of SCM planning (2-4) Control and tracking of inventory (product/parts/wip): accuracy and visibility (2-5) Process standardization and visibility (3-1) Just-In-Time Logistics performance (3-2) Inventory turnover & cash-to-cash cycle time (3-3) Customer lead time (from order placement to receipt) and load efficiency (3-4) Delivery performance and quality (3-5) Supply chain inventory visibility & opportunity costs (3-6) Environmental activities (3-7) Total logistics cost (4-1) Electronic Data Interchange (EDI) coverage IT Methods & implementation (4-2) Usage of Bar Coding / Automatic Identification and Data Capture (AIDC) (4-3) Effective usage of computers in operations and decision-making (4-4) Open standards and unique identification codes (4-5) Decision-making systems and support to supply chain partners Vol.64 No.4E (2014) 597

8 value networks is heavier on the customer-retailer interface for data mining in the market, since market sensitiveness is the core for them. The highest score in this area is again in hybrid FDCs where the value networks have to invest throughout partners to succeed in forecast oriented demand as well as the read-and-react demand environments. These results reveal that 1) agile FDCs focus more on strategic alignment with the reliance on information sharing and customer-centered operations, 2) relative importance given for collaborative planning and execution over logistics performance is comparatively high in agile value networks than lean value networks while hybrid networks show the highest comparative importance, and 3) utilization of IT tools in operations is the highest in hybrid FDCs and lean FDCs beat agile FDCs on this aspect. Agile value networks show that the IT utilization is high in the retailer-customer interface or rather downstream in the supply chain than between upstream members. 5.2 SCM Capabilities of Value Networks Factor analysis was performed with principal axis factoring with Varimax rotation to extract three factors to investigate the capabilities of FDCs characterized along the lean-agile paradigm. Factor analysis revealed a KMO measure of sampling adequacy of revealing meritorious interpretation [34] while MSA value was well above 0.50 for each assessment item of the LSC. Three factors extracted explained 42.94% of the total variance which is evidence for the appropriateness of the analysis. The extracted factors were named considering the items grouped within the factors, focusing on the respective factor loadings accordingly, taking highest absolute valued items as key components of the factor (Table 4). Accordingly, d.f. = 2 : 116 F-value p- value Supply & logistics management Customer integration with ICT System optimization for CS we named the factors as: (1) Supply & logistics management capability (2) Customer integration with ICT (3) System optimization for customer satisfaction The resultant factor scores were compared to gain insights on the SCM capabilities developed by each FDC (left side graph and ANOVA table of Fig. 5) as well as coupled demand chain as lean, hybrid and agile demand chains (right side graph and table of Fig. 5). Comparison of distinguished FDCs reveals mixed result with different FDCs developing uniquely different capabilities for SCM. Clear observations from the analysis are (1) Customer integration with ICT is positive in FDC 3, 4, 1 and 6 (lean and hybrid FDCs) while the most agile value networks see it as a negatively associated capability. This is further evidence for the argument that agile supply forms fluid clusters which is contrasted with lean approach with long-term SC partnerships. (2) Most lean value networks (FDC3) and most agile value networks (FDC2, FDC6) develop only one capability while the mixed models and FDC4 develop at least two of the found capabilities. FDC1 and FDC5 are characterized as hybrid SCs with a lean-agile mixed approach so they have some similarity in developing two out of three capabilities as positive attributes for SCM. This hints that the closer the FDC is towards one particular extreme in leanness and agility, the higher the tendency to develop one key capability as a positive attribute. The exemption of FDC4, which is rather lean, develops all three capabilities as positive attributes. This exception can be explained when the time window for delivery or the d.f. = 2 : 116 F-value p- value Supply & logistics management Customer integration with ICT System optimization for CS Agile Lean Figure 5: SCM Capabilities in individual FDCs (left side) lean, agile and hybrid groups (right). lead time is considered. Although all characteristics 598 J Jpn Ind Manage Assoc

9 are in line with lean supply in this value network, the retailer pressures the vendors for very short lead times with its bargaining power and multiple sourcing strategy so that most vendors on the other hand cater to the demand with vertically integrated supply chains or sourcing in close proximities. For this kind of business model, it can be seen that all the three capabilities are considered as positive attributes of SCM. (3) The overall outcome of coupled FDCs with the proximity in leanness and agility (graph and table on the right side of Fig. 5) provides some insights. First, supply & logistics management (with a distinguished management approach for customer and supplier dyads) is seen positive in both agile and hybrid value networks which inherently need flexibility. This means that they associate the capability to handle the upstream SC to gain flexibility while customer management is done separately through system optimization. Second, customer integration is seen positively by lean and hybrid SCs indicating that leanness calls for it. Third insight on the 3 rd derived capability that internal system optimization for customer satisfaction is seen positively only by agile demand chains (overall) indicating their focus on service level optimization as a strategic priority causing the development of that capability. Lean FDCs tend to meet these capabilities through customer integration as discussed. 6 CONCLUSION Conclusions which are also the implications of the research for practitioners can be viewed as 1) microorganizational view on SCM, proved by the differences between value networks (FDCs) within one particular company, showing that the aggregate level measures and strategy implementation won t work optimally with a diverse customer profile, 2) value networks with different target markets and business models focus on different attributes for SCM, and 3) SCM capabilities developed by value networks are unique for the demand chain which are to cater to the current business model, yet they might not be the optimal conditions. Therefore practitioners can utilize the research framework (Fig. 3) introduced here to assess whether they are on the right track. In terms of research implications, the first insight on micro-organizational level SCM which is in line with the holistic view of SCM is interesting. Further, the research framework outlined here can be utilized for research on leanness-agility while the LSC is a scorecard to measure SCM performance. Investigation on one company is the major limitation for the research in validating the findings for generalization. Extension of the same framework to some more apparel value networks is an obvious future work. Further extensions possible with these insights are to test these findings in other industries and along the value networks to see how these orientations change along these contexts. Application of this framework along a value network will identify the perceptional and alignment gaps between supply chain partners in SCM orientations although they all work towards the same market. Importance of such research will be more pronounced in highly outsourced business environments. REFERENCES [1] Goldsby, T.J., Griffis, S.E. and Roath, A.S.: Modeling Lean, Agile and Leagile Supply Chain Strategies, J. Bus. Logist., Vol. 27, No. 1, pp (2006) [2] Bruce, M., Daly, L. and Towers, N.: Lean or Agile: A Solution for Supply Chain Management in the Textiles and Clothing Industry?, Int. J. Oper. Prod. Manage., Vol. 24, No. 2, pp (2004) [3] Mentzer, J.T., Witt, W.D., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D. and Zacharia, Z.G.: Defining Supply Chain Management, J. Bus. Logist., Vol. 22, No. 2 (2001) [4] Morash, E.A.: Supply Chain Strategies, Capabilities and Performance, Transp. J., pp (Fall 2001) [5] Sleigh, A. and von Lewinski, H., Moving Up the Value Chain, Outlook, Vol. 3, pp (2006) [6] Gereffi, G. and Memedovic, O.: The Global Apparel Value Chain: What Prospects for Upgrading by Developing Countries, United Nations Industrial Development Organization (UNIDO), (2003). [Online] Available: [7] Childerhouse, P., Aitken, J. and Towill, D.R.: Analysis and Design of Focued Demand Chains, J. Oper. Manage., Vol. 20, pp (2002) [8] Van der Vaart, T. and Donk D.V.: Buyer Focus: Evaluation of a New Concept for Supply Chain Integration, Int. J. Prod. Econ., Vol. 92, pp (2004) [9] Skinner, W.: :The Focused Factory, Harv. Bus. Rev., Vol. 52, No. 3, pp (1974) [10] Jŭttner, U., Christopher, M. and Baker, S.: Demand Chain Management-Integrating Marketing and Supply Chain Management, Ind. Mark. Manage., Vol. 36, pp (2007) [11] Childerhouse, P. and Towill, D.R. Enabling Seamless Market-orientated Supply Chains," Int. J. Logist. Syst. Manage., Vol. 2, No. 4, pp (2006) [12] Christopher, M.: Logistics and Supply Chain Management: Creating Value-Adding Networks, Pearson Education (2005) [13] Rainbird, M.: Demand and Supply Chains: The Value Catalyst, Int. J. Phys. Distrib. Logist. Manage., Vol. 34, No. 3/4, pp (2004) Vol.64 No.4E (2014) 599

10 [14] Jacobs, D.: The Promise of Demand Chain Management in Fashion, J. Fashion Mark. Manage., Vol. 10, No. 1, pp (2006) [15] Jŭttner U., Godsell, J. and Christopher, M.G.: Demand Chain Alignment Competence - Delivering Value Through Product Life Cycle Management, Ind. Mark. Manage., Vol. 35, No. 8, pp (2006) [16] Walters, D. and Rainbird, M.: The Demand Chain as an Integral Component of the Value Chain, J. Consum. Mark., Vol.21, No. 7, pp (2004) [17] Collin, J., Eloranta, E. and Holmstrom, J.: How to Design the Right Supply Chains for Your Customers, Supply Chain Manage. Int. J., Vol. 14, No. 6, pp (2009) [18] Treville, S.D., Shapiro, R.D. and Hameri, A.P.: From Supply Chain to Demand Chain: The Role of Lead Time Reduction in Improving Demand Performance, J. Oper. Manage., Vol. 21, pp (2004) [19] Holmstrom J., Louhiluoto P., Vasara A. and Hoover W.: The Other End of the Supply Chain, Supply Chain Forum Int. J., Vol. 2, No. 1, pp (2001) [20] Langabeer J.R. and Rose, J.: Creating Demand Driven Supply Chains: How to Profit from Demand Chain Management, Chandos Publishing, Oxford (2001) [21] Yaibuathet, K., Enkawa, T. and Suzuki, S.: Influences of Institutional Environment Toward the Development of Supply Chain Management, Int. J. Prod. Econ., Vol. 115, pp (2008) [22] Yaibuathet, K., Enkawa, T. and Suzuki, S.: Supply Chain Performance and Its Influential Factors: Cross National Analysis, Jpn. Ind. Manage. Assoc., Vol. 57, pp (2007) [23] Yaibuathet, K., Enkawa, T. and Suzuki, S.: Supply Chain Operational Performance Analysis: Thai Manufacturing Sector, in Proceedings of the 7th Asia Pacific Industrial Engineering and Management Systems Conference, Bankok, Thailand (2006) [24] Tippayawong, K.Y., Patitad, P., Sopadang, A. and Enkawa, T.: Factors Affecting Efficient Supply Chain Operational Performance of High and Low Technology Companies in Thailand, Manage. Sci. Eng., Vol. 4, No. 3, pp (2010) [25] Agarwal, A., Shankar, R. and Tiwari, M.K.: Modeling Agility of Supply Chain, Ind. Mark. Manage., Vol. 36, pp (2007) [26] Narasimhan, R., Swink, M. and Kim, S.W.: Disentangling Leanness and Agility: An Empirical Investigation, J. Oper. Manage., Vol. 24, pp (2006) [27] Van Hoek, R.I., Harrison, A. and Christopher, M.: Measuring Agile Capabilities in the Supply Chain, Int. J. Oper. Prod. Manage., Vol. 21, No. 1, pp (2001) [28] Power D.J., Sohal A.S. and Rahman, S.U.: Critical Success Factors in Agile Supply Chain Management - An Empirical Study, Int. J. Phys. Distrib. Logist. Manage., Vol. 31, No. 4, pp (2001) [29] Swafford P.M., Ghosh, S. and Murthy, N.: The Antecedents of Supply Chain Agility of a Firm: Scale Development and Model Testing, J. Oper. Manage., Vol. 24, pp (2006) [30] Naylor, J.B., Naim, M.M. and Berry, D.: Leagility: Integrating the Lean and Agile Manufacturing Paradigms in the Total Supply Chain," Int. J. Prod. Econ., Vol. 62, pp (1999) [31] Hallgren, M. and Olhager, J.: Lean and Agile Manufacturing: External and Internal Drivers and Performance Outcomes, Int. J. Oper. Prod. Manage., Vol. 29, No. 10, pp (2009) [32] Christopher, M. and Towill, D.: Marrying Lean and Agile Paradigms, in Proceedings of EUROMA, Ghent, Belgium (2000) [33] Agarwal, A., Shankar, R. and Tiwari, M.: Modeling the Metrics of Lean, Agile and Leagile Supply Chain: An ANP-based Approach," Eur. J. Oper. Res., Vol. 173, pp (2006) [34] Hair Jr. J.F., Black, W.C., Babin, B.J., Anderson, R.E. and Tatham, R.L.: Multivariate Data Analysis, Sixth Edition, Dorling Kindersley (India) Pvt. Ltd., New Delhi (2008) 600 J Jpn Ind Manage Assoc