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Many thanks. Just select your click then download button, and complete an offer to start downloading the ebook. If there is a survey it only takes 5 minutes, try any survey which works for you. Download Now! Register a free 1 month Trial Account. Download as many books as you like Personal use Cancel the membership at any time if not satisfied. Join Over Happy Readers. Reply 1 Like Follow 1 hour ago. Prater, Biehl, and Smith trading partners had been identified.

These five experts had have used case studies to show how firms have more than ten years of experience in the area of purchasing successfully made a tradeoff between vulnerability and supply and supply chain management.

Literature related to agility of chain agility. Within a Svensson has stated that lean, responsive, and agile period of fifteen days, a brainstorming session was organized supply chains require satisfactory or high levels of perceived to identify the variables.

Initially, only four variables as trust of companies towards suppliers and customers. Power, mentioned by Christopher were considered. Later on during Sohal, and Rahman have identified some of the factors brain storming session, experts from the case supply chain critical for successful agile organizations in managing their expressed their views to include more number of variables for supply chains.

Stratton and Warburton have explored the agility improvement of their supply chain. In all, twenty-six role of inventory and capacity in developing agile supply chain variables had been identified in this session. The number was for an apparel manufacturer. Lau, Wong, Pun, and Chin reduced to fifteen as some variables were of same nature. The have developed an infra-structural framework for the design literature related to these fifteen variables had been circulated and development of an agile supply chain system, which is among the experts.

After seven days, a session was organized characterized by its ability to cope with unpredictable changes to establish the relationship among the variables. Since the related to the management of suppliers and flow of parts relationships among all variables could not be established in within the value chain of the entire production network. Yusuf, this session, so another meeting was conducted to complete Gunasekaran, Adeleye, and Sivayoganathan have pre- this task.

Characteristics of agile supply chain modified from Harrison et al. The market sensitiveness of a supply chain is a particular variable helps to achieve the other variables? Collaboration improves trust diagram were circulated among the experts for any further among trading partners, which motivates them to share busi- modification.

Identified variables are: 2. Delivery speed DS 2. Here delivery speed refers to the ability to Supply chain system. Data accuracy DA development, common systems and shared information Chris- topher, This extended form of co-operation in the supply Data accuracy DA is one of the important factors, which chain is becoming ever more prevalent as companies focus on influence the performance of a supply chain. It is defined as the managing their core competencies and outsource all other accuracy of the data used by different trading partners in making activities.

In a supply suppliers and alliance partners becomes inevitable and, hence, a chain, most of the retailers do not know their demand with new style of relationship is essential.

With inaccurate forecasts, the quality of and commitment must prevail. Along with process integration materials ordered does not match the demand. These errors in comes joint strategy determination, buyer—supplier teams, the retailer's forecasts are passed to the supplier in the form of transparency of information and even open-book accounting.

The demand variability can be checked if data accuracy is maintained along the supply chain Lee, Padma- 2. The use of information technology to share data between 2.

New product introduction NPI buyers and suppliers is, in effect, creating a virtual supply chain. Virtual supply chains are information based rather than inven- Ability to introduce new product has become very tory based. Conventional logistics systems are based upon a important for supply chains that want to have a competitive paradigm that seeks to identify the optimal quantities of inven- superiority. Initially quality was the model to follow in terms tory ands where it should be located.

Complex formulae and of competitive strategy; however, more recently, new product algorithms exist to support this inventory-based business model. This is Paradoxically, what we are now learning is that once we have especially important in a business e.

Electronic Introducing a new product into the market can certainly Data Interchange EDI and the Internet have enabled partners in bring significant benefits, including greater market share and the supply chain to act upon the same data i.

Lead time reduction LTR margins, and may be most critical, the loss of customers' goodwill. Lead time reduction is the elapsed time from order to delivery. Lead-time reduction within the supply-production- 2. Centralized and collaborative planning CCP distribution chain is the mechanism for time-based competition.

Management of time, specifically lead-time, can be a com- Effective supply chain integration and synchronization petitive advantage. To gain control over lead-time, the first step is among partners can eliminate excess inventory, reduce lead an analysis of the status quo. Companies are now or components. Managing time is the mirror image of managing moving towards collaborative SCM in an effort to reduce the quality, cost, innovation and productivity.

A comprehensive lead-time reduc- waste in the supply chain, but increased responsiveness, tion strategy should attack all bottlenecks in the system, begin- customer satisfaction, and competitiveness among all members ning with those most inhibitive to throughput.

Thus, collaborative SCM systems allow organizations to progress beyond mere operational-level infor- 2. To achieve improved level of service, it is im- the control of process. Quality improvement QI service viewed as important by critical downstream customers. Customer service is frequently cited as an important objective Quality improvement is recognized by Management of of supply chain management SCM.

To gain this productive involvement, they have been advised to develop relationships with suppliers. Indeed, the 2. However, by helping firms and its trading partners to find additional ways the exact nature of these relationships and how they can be to cut the manufacturing costs of the products. In the most of the established remain un-clarified. The study proposes that manu- cases, advantages from management accounting practice have facturers and suppliers with co-operative compared with com- limited scope within the boundaries of the firm.

This limitation petitive and independent goals discuss quality issues open- makes it difficult for the firm to take advantage of any cost- mindedly and develop trusting, long-term relationships which in reduction synergies that exists across the traditional supply turn increase the supplier's contributions to total quality chain. Such synergies can only be achieved by coordinating the improvement efforts.

According to Beamon and Ware cost-reduction activities of multiple firms. The objective of inter- improving the quality of all supply chain processes result in organizational cost management programs is to find lower-cost reduced costs, improved resource utilization, and improved solutions than would be possible if the firm and its buyers and process efficiency. Traditional cost management systems often legiti- terial suppliers from other side Prater et al.

Traditionally, mize supply chain activities that result in localized cost minimi- attention has been focused on uncertainty in customer demand; zation that inhibit the supply chain's ability to meet customer however, uncertainty is also inherent in market at supply side. The quality and quantity of raw material delivered from an external supplier may differ from those requested. Uncertainty 2. Customer satisfaction CUS propagates through the supply chain and leads to inefficient processing and non-value adding activities.

Mason-Jones and Customer satisfaction is the customer's reaction to the value Towill give significant importance to minimization of received from the purchase or utilization of the offering. Cus- uncertainty to get internationally competitive performance.

Trust development TD particular product or service. It is especially critical based on use of competitor products. Thus customer satisfac- when two situational forces are present in a transaction: uncer- tion is influenced by the perception of the value delivered as tainty; and asymmetric product information.

Many researchers well as by the perception of the value offered by competition. Trust is perceived supply chain strategy should have focus towards satisfying the as a state of readiness for unguarded interaction with someone or customers. With out satisfied customer, the whole exercise of something Ba, This measurement is organizations and their suppliers.

The nature of trust and needed to integrate the customer specification in design, to set the nature of business transaction often temper the relationships. Contributors Areas in which ISM has been applied 2. Resistance to change has long KM in manufacturing been recognized as a critically important factor that can influence industries the success or otherwise of an organizational change effort. Thus resistance is most commonly linked with In this research, interpretive structural modeling ISM has negative trading partner attitudes or with counter-responsive been applied to develop a framework for a case supply chain to behaviors.

Resistance to change can be handled when there is achieve the following broad objectives: trust development among trading partners and they are involved in the strategic planning. Interpretive structural modeling ISM is an interactive learn- ing process in which a set of different and directly related In the present paper, ISM has been applied to show the inter- elements is structured into a comprehensive systemic model relationships of different variables of supply chain agility.

Warfield, ; Sage, The model so formed portrays the Various steps involved in the ISM technique are illustrated in structure of a complex issue or problem, a system or a field of Fig. ISM methodology helps to impose order and direction variables, questionnaires were sent to original equipment manu- on the complexity of relationships among elements of a system. Out of the question- In the literature various applications of ISM have been found naires sent, usable responses have been received, resulting which are depicted in Table 2.

Cron- the inter-relationships among variables. It provides systemic approach for improving supply consistency of the responses. Out of the usable responses, original equipment ISM is primarily intended as a group learning process. It is structural as on the experts' opinion, in defining the mutual relationships. It is a modeling technique as the 3. Structural self-interaction matrix SSIM specific relationships and overall structure is portrayed in a digraph model.

Variables of supply chain agility are already discussed in ISM starts with an identification of variables, which are previous section and are: market sensitiveness 1 , delivery relevant to the problem or issue and then extends with a group speed 2 , data accuracy 3 , new product introduction 4 , problem-solving technique. Then a contextually relevant sub- centralized and collaborative planning 5 , process integration ordinate relation is chosen. Having decided on the element set 6 , use of IT tools 7 , lead-time reduction 8 , service level and the contextual relation, a structural self-interaction matrix improvement 9 , cost minimization 10 , customer satisfaction SSIM is developed based on pair-wise comparison of vari- 11 , quality improvement 12 , minimizing uncertainty 13 , ables.

In the next step, the SSIM is converted into a reachability trust development 14 , and minimizing resistance to change matrix and its transitivity is checked.

Once transitivity embed- This means that one model, called ISM is derived. No Representing relationship statement into model for improving agility of supply chain Fig. Flow diagram for preparing ISM. Keeping in mind the contextual relationship for each vari- is questioned. Four symbols are used for the type of the able, the existence of a relation between any two sub-variables relation that exists between the two sub-variables under i and j and the associated direction of the relation consideration: V— variable i will help to achieve variable j; Table 3 Structural self-interaction matrix SSIM A— variable j will be achieved by variable i; X— variables i and j will help achieve each other; and Elements 15 14 13 12 11 10 9 8 7 6 5 4 3 2 O— variables j and i are unrelated.

The situations are as follows: reachability set consists of the element itself and other 1. If the i, j entry in the SSIM is V, then the i, j entry in the elements, which it may help to achieve, whereas the reachability matrix becomes 1 and the j, i entry becomes 0. If the i, j entry in the SSIM is A, then the i, j entry in the elements, which may help achieving it. Then the intersection matrix becomes 0 and the j, i entry becomes 1.

The elements for 3. If the i, j entry in the SSIM is X, then the i, j entry in the which the reachability and intersection sets are same are the matrix becomes 1 and the j, i entry also becomes 1. The top-level 4. If the i, j entry in the SSIM is O, then the i, j entry in the elements of the hierarchy would not help to achieve any matrix becomes 0 and the j, i entry also becomes 0. Once top-level elements are identified, it is separated out from the Following these rules, initial reachability matrix for the rest of the elements.

Then, the same process is repeated to find variables is prepared as shown in Table 4. In the present case, the gap if any in the opinion collected during development of variables along with their reachability set, antecedent set, structural self-instructional matrix. The Final reachability ma- intersection set and the levels are shown in Table 6.

The trix is presented in Table 5. Partitioning the reachability matrix In Table 6, the element 10 cost minimization , element 11 customer satisfaction , and element 12 quality improvement The matrix is partitioned, by assessing the reachability and are found at level I.

Thus, they will be positioned at the top of antecedent sets for each variable Warfield, The hierarchy of the ISM model. After removing elements 10, 11 and 12 from Table 6, we get second and third column of Table 7. Table 4 In Table 7, the element 4 new product introduction and Initial reachability matrix element 9 service level improvement are put at level II. Elements 4 new product introduction and 9 service 9 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 level improvement are at level II.

Element 8 lead-time reduction is at level 12 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 IV. Market sensitiveness element 1 and data accuracy 13 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 element 3 emerge at level V and VI, respectively.

Final iteration brings out 4. Development of digraph level VIII elements as centralized and collaborative planning 5 , process integration 6 , and use of IT tools 7. Based on the conical form of reachability matrix, the initial digraph including transitive links is obtained. After removing 3. Developing conical matrix indirect links, the final digraph is obtained, as shown in Fig. From Fig. These variables have appeared at the top of the collaborative planning, and process integration.

Effective centralized and collaborative planning 5 , process integration 6 , and use of IT tools 7 provide an 5. Minimizing uncertainty helps indicates the dependence and driving power, respectively. For example, ele- products in the market. Delivery speed provides better service ment 4 has fourth rank in dependence and ninth in driving level, which results into improved level in customer power; while element 2 has third rank in dependence and eighth satisfaction Lead-time reduction minimizes all sort of rank in driving power.

When variables are placed according to waste including time; therefore experts feel that improvement their driving and dependence power, variables are grouped into in quality level 12 can be achieved with effective lead-time four clusters. Four clusters are presented in Fig. Improvement in customer satisfaction level is also First cluster includes variables that have weak driver achieved with better quality level.

These variables are relatively Trust development element 14 also influences data accu- disconnected from the system, with which they have only few racy element 3. Improved level of trust among trading partners links, which may be strong.

These are autonomous variables. Minimizing resistance to change among power but strong dependence. These are termed as dependent trading partners helps in improving market sensitiveness.

Lead- variables. Variables in third cluster have strong driving power time reduction 8 influences cost minimization This and strong dependence. These variables fall into the category implies that a sound strategic planning for lead-time reduction is of independent or linkage variables.

These variables are a prerequisite to effective cost minimization. Use of IT tools 7 unstable. Any action on these variables will have an effect on is helpful in centralized and collaborative planning 5 , and others and also a feed back effect on themselves. Fourth process integration 6. Experts feel that use of IT tools, cluster includes independent variables having strong driving centralized and collaborative planning, and process integration power but weak dependence.

Use of IT tools 7 , centralized help to develop integration of links within the supply chain. There is no linkage variable having strong driving and strong dependence power. Discussion 6 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 7 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 The results of the study indicate that supply chain agility depends on customer satisfaction, quality improvement, cost minimization, delivery speed, new product introduction, service to enhance supply chain agility. Therefore, management of the level improvement, and lead-time reduction.

The top-level vari- case supply chain should focus its attention to build up a strong ables, having weak driving power, have strong dependence on network of trading partners through better use of IT tools, cen- other variables.

Christopher and Towill , Van Hoek et al. These variables depend on other variables like Similar inter-dependent action plans could emerge out of the information enrichment, networking and collaboration across combinations of these variables. For example, data accuracy the supply chain Christopher, Bottom level variables use element 3 , market sensitiveness element 1 and lead-time of IT tools, centralized and collaborative planning, and process reduction element 8 are variables having a medium driver integration are considered as strong drivers of supply chain power and medium dependence.

These variables need consistent agility Yusuf et al. These variables help to achieve attention of the management in enhancing supply chain agility. Slight variation in the level of these variables may