Introduction

Modeling and Analysis of Supply ChainCharacteristics using ISM Technique

Inflation in the global market has an impact on manufacturing sector and enforced them to work on various aspects simultaneously i.e. cost reduction, product quality improvement, after sale customer services, variety in mass production, and the exceptional value to the customer perception etc. (Kumar et al., 2014; Li et al., 2005). Leading challenge for all manufacturing industries is how they will conceive the customer perception and fulfil it (Kumar et al., 2015a). Next to this, the increased number of customer also has an impact on the organizational performance. The accommodation of all the facilities within and outside the organizational boundaries seems to be the massive task to control over it (Kumar et al., 2015). From the past three decades, most of the manufacturing giants seem to believe that the answer of all above-said situations lies in supply chain management. Supply Chain Management (SCM) creates the awareness among all the stake holders for focussing on the organizational objectives (Aggarwal et al., 2007).

corporate strategy known as 'Strategic Fit' (Ballou, 2000; Haleem et al., 2012) because dissonance between SCM and corporate strategies could lead to conflict among all stake holders of the organization. Literature reveals that any organization may fail either because of a lack of strategic fit or because its

Research Scholar, Department of Mechanical Engineering, YMCAUST, Faridabad, India.

Associate Professor, Department of Mechanical Engineering, YMCAUST, Faridabad, India.

Joint Director, Technical Education Haryana, Panchkula, India.

Apeejay Journal of Management & Technology

Hugos, 2003). Perhaps with initial benefits, the supply chain of manufacturing sector always 2017. Rajender Kumar, Vikas Kumar and Sultan Singh expect crises because of uncertain situations to happen (Christopher & Towill, 2000; Kumar et al. 2015). The uncertainty in supply chain influences the demand horizon and market trend for the particular product on various aspects (Melnyk et al., 2009). Most of the time the uncertain situations affect because of improper supplier’s collaboration and results in interrupted resource flow to the system. Therefore, it is important for an industry that they design and develop the supply chain as simple and more flexible that facilitates the ongoing processes of the organization. In the organization, the performance is measured under the two broad categories i.e. operational and financial. The operational category includes the productivity, quality, delivery to the customer end, work force safety, morale/motivation to the workforce and the cost of process the material/information, whereas the financial category includes the profit, revenue, inventory and share of the business in the market (Carton, 2004; Tajiri & Gotô, 1992).

Optimized Lead TimeStrong Decision MakingCross Enterprise CollaborationUninterrupted Information FlowInventory ManagementInternal IntegrationFlexible to deal with UncertaintyVendor TroubleshootingSimple in DesignMarket Demand growth

Operational AspectFinancial as well as operational aspectFinancial as well as operational aspectOperational AspectFinancial as well as operational aspectOperational AspectOperational AspectOperational AspectFinancial as well as operational aspectFinancial Aspect

Principle of Working

Define the Work Culture Enabler

Establish the Contextual relationship among the variables

Develop the Self-Structure Intersection Matrix

Develop The Reachability Matrix

Incorporate Transitivity (Final Reachability Matrix)

Perform the Level Partitioning

Develop the Reachability Matrix in Conical Form

Develop Diagraph

Remove Transitivity From the diagraph

Replace variables nodes with relationship statement

Is there any conceptualinconsistency among variables?

Represent relationship statement into model

Yes

No

Methodology

In the present study, Interpretive Structural Modelling (ISM) methodology has been applied to understand the contextual relationships among these identified enablers along with their interdependence and hierarchy levels to implement these commandments in Indian manufacturing sector (Sage, 1977). MICMAC analysis is used to categorize the identified supply chain characteristics according to their importance and contribution in an organization. Figure 1 represents the work flow diagram for using ISM approach to establish the contextual relationship and analysis purpose (Ansari et al., 2013; Luthra et al., 2011).

RM includes the binary matrix consisting of 1s and 0s instead of A, V, X & O notations; and the designation of 0’s & 1’s is based on the following assumptions. If the (i, j) entry in the SSIM is V,

Contextual Relationship Establishment

Reachability Matrix

Later on, the final computation is done by balancing of the binary matrix as given in table 3. This balancing process is done for the sake of desired outcomes. The transitivity is used to balance the matrix

The importance of variables among all is defined with the help of level partitioning in ISM approach. Table 5 represents the level partition for the present study. It can be concluded that the variable SC1, SC5, SC8, and SC9 are at the first level, variables SC2, SC6 and SC7 are at the 2nd level, variables SC3 and SC4 are at the 3rd level, and finally, the variable SC10 is at the 4th Level.

with assumption that if, variable A has the relation with B and variable B is related to C then variable A is also having the relationship with variable C (Haleem et al., 2012). In table 4, transitivity is introduced and known as Final Reachability Matrix.

Level Partitioning

Level-I

Level-II

Level-III

Level-IV

Cross EnterpriseCollaboration

InventoryManagement

OptimizedLead Time

VendorTroubleshooting

Simple inDesign

InternalIntegration

Strong DecisionMaking

Flexible to dealwith

Uncertainty

UninterruptedInformation Flow

MarketDemand Growth

Interprative Structure Modelling

MICMAC Analysis

Results & Discussion

Region 1 :

Dependence Drivers

Linkage Drivers

Driving Drivers

The variables lying in this region having the weak drive as well as dependence on the other variables. So-that these variables can be handle separately. In the present case, there is no variable lying in the autonomous region.

The variables SC8 is lying in this region. The variables in this region has the weak driving power but strong dependent on other variables. This states that vendor troubleshooting never helps to attain the effectiveness and dependent factor on all other variables.

Variable SC1, SC2, SC3, SC4, SC5, SC6, SC7, and SC9 are lying in the linkage region. These variables are having the drive power for SCM and also, dependence on other variables strongly.

The variable SC10 is lying in the driving region. This states that the variable market growth has the strong drive power and helps to drive all other variables. Also, this variable has the weak dependence on others is variable.

References

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