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Procedía Engineering 97 (2014) 2136-2146
Procedía Engineering
www.elsevier.com/locate/procedia
12th GLOBAL CONGRESS ON MANUFACTURING AND MANAGEMENT, GCMM 2014
Addressing the Root Cause Impediments for Supplier Development in Manufacturing Environment
C.V.Sunil Kumara,Srikanta Routroyb*
aResearch Scholar, Mechanical Engineering Department, Birla Institute of Technology & Science Pilani, Pilani Campus (Rajasthan) - 333 031,
INDIA, Email: cvenkata_sunil@yahoo.com bAssociate Professor, Mechanical Engineering Department, Birla Institute of Technology & Science Pilani, Pilani Campus (Rajasthan) - 333
031, INDIA, Email: srikantaroutroy@gmail.com
Abstract
The manufacturing supply chains, designed for delivering the best to the customer should operate by following systems approach, where planning and execution are strategically carried out protecting the interests of each stakeholder. Supplier Development (SD) is one such sourcing strategy that a manufacturing company devise to strengthen its critical but fragile supply base, portraying mutual interests in the formulation. However in reality, many companies even though capable enough in conceiving and materializing their SD strategies yet, are miserably falling short off due to tremendous misdirected flow of resources. Often, the bitter experiences from the results due to misdirected SD efforts, the companies are pushed to draw wrong conclusions and inevitably search for other misdirected efforts without addressing the root cause impediments. In concrete, the misdirection in SD has its deep roots along various tangible and intangible issues of the operation field. Therefore, a manufacturer needs to bring these issues to the surface, critically analyze and uproot them for smooth development of its supply base strength. In this paper, a methodology is proposed using Interpretive Structural Modeling (ISM) - Fuzzy Matriced Impacts Croises Multiplication Appliqueeaun Classement (FMICMAC) algorithm for systematic analysis of impediments of SD. To demonstrate its utility, a case study was conducted in an Indian manufacturing company and the proposed methodology is applied to it in order to explain the salient features of the concept.
© 2014 PublishedbyElsevierLtd.Thisisanopenaccess article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
Selection and peer-review under responsibility of the Organizing Committee of GCMM 2014
Keywords: Supplier Development; Manufacturing Supply Chain Analysis; Impediments for Supplier Development; Interpretive Structural Modeling
* Corresponding author. Srikanta Routroy, Tel.: +0-969-409-6456; fax: +0-000-000-0000 . E-mail address: srikantaroutroy@gmail.com
1877-7058 © 2014 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
Selection and peer-review under responsibility of the Organizing Committee of GCMM 2014 doi: 10. 1016/j .proeng .2014.12.457
1 Introduction
In today's highly competitive business arena, manufacturing firms cannot afford to run in silos but they must adopt systems approach and gain competitive advantage over others [1]. This is because the ability to compete is no more only limited to the manufacturer but also dependent on the other supply chain partners, especially on suppliers. Since the competition is not between the firms but between the supply chains [2], it is inevitable for a focal manufacturing firm to lookout for its supply chain partners in order to derive competitive inputs and services [3]. Moreover, this dependency to compete has been growing more and more as many firms are increasingly opting to outsource and focus more upon their core competencies [4]. Owing to this divided competency and increasing dependency on the suppliers, manufacturers are confronted with opportunities as well as threats and emergencies posed by their supply chain partners. In order to take advantage of the opportunities created and offered as well as mitigate the threats posed from the supply side, manufacturer adopts many supply management strategies. Among these strategies, manufacturer often adopt SD, wherein manufacturer takes numerous initiatives to assist its suppliers and make them capable to meet its various objectives [5]. However, in spite of manufacturer's endeavors to assist its suppliers, it is most frequently challenged by various impediments in implementing SD Programs (SDPs) [4,6]. These impediments are variegated and explicit to specific environments. Moreover, often there exists complex relationship between these impediments leaving the manufacturer clueless which one to focus. So, standard approaches to overcome SD Impediments (SDIs) in general do not help the manufacturing firms. This is often why many manufacturing firms complain or conclude that SD is not the right strategy they should have chosen. In fact many manufacturing firms quickly come to this type of conclusions that nothing materialize for their firm and develop strong resistance for transformation. Indeed any kind of strategy turnout unsuitable unless right impediments are identified and root cause among them are addressed. However, many at times manufacturing companies fail to identify the right ones to focus due to complex and chaotic relationship amidst them. Thus, considering all the aforementioned issues, this paper attempts to propose an approach to identify the right impediments to focus and monitor for smooth running of SDPs.
The paper is organized as follows: section 2 presents the literature review conducted on significance of SD and SDIs; section 3 presents the proposed methodology to find root cause impediments; section 4 deals with analysis of SDIs using the proposed methodology applied to an Indian manufacturing company; section 5 interprets the results and presents the discussions and Section 6 shows the conclusions drawn from the interpretation of the results.
2 Literature review
From the past few years, SD has acquired lot of significance and it is continuously evolving with innovative ways of improving supplier's performance in meeting manufacturer's requirements. Leenders [7] was first to mention the term "Supplier Development" (SD). The SD has been defined and studied by various researchers, academicians and practitioners in different situations [4,7,8,9,10,11,12,13,14,15] with a central focus of enhancing the capability of the supplier with an aim to create win-win environment between manufacturer and suppliers. It improves the performance of the supplier in multi-dimensions like enhancement of quality; improvement in delivery; reduction of cost; transfer of knowledge; enhancement of technological and product design capability; better service; supplier innovation capability and better time to market [16,17,18,19,20,21,22,23]. However successful implementations of SDPs are obstructed by various SDIs. Since, SDPs adopted for improving suppliers' performance in meeting manufacturer's requirements must be strategically planned and executed. Not all the suppliers need to be developed [24], as some suppliers may not be supplying critical and strategic items and even if so, suppliers may not be oligopolistic in nature, in that case manufacturer can choose supplier switching [25]. Sometimes suppliers may be well to do but less inclined in serving the manufacturer because of low preferential status ascribed to the manufacturer [26]. Suppliers may be truly incapable in meeting manufacturer's requirements but may be supplying very innovative items, and then in that case manufacturer may choose acquiring supplier's technology [4]. Along the running timeline of SDPs, suppliers once who were incapable would have become capable enough or still incapable in meeting manufacturer's requirements at different degrees, which calls for proportionate SD efforts to be adopted. Sometimes other factors like supplier-manufacturer relationship life cycle, product and process life cycles, technological change, manufacturer and (or) supplier's changing interests with respect to their customers'
requirements, increasing level of competition...etc., may call completely different set of SD initiatives to be proposed. Thus, it's a great challenge for a manufacturer to understand the system's dynamics and strategically decide for successful implementation of SDPs. However, the need for transformation can be determined through proper supplier performance evaluation and feedback systems. Once it is identified that the current system is no more valid then, the manufacturer will have to identify the changes in impediments or include new impediments hindering SD progress. In this process, identifying the right root cause SDIs is important to a manufacturer for mitigating the SDIs on the whole. This is because unless the root cause SDIs are identified and addressed, other SDIs keep on arising even though they are addressed. However, the root cause SDIs can only be identified and addressed through complete understanding of SDPs along various dimensions like its characteristic variables, performance variables, operating conditions, internal and external constraints etc. Although many researchers have pointed out much regarding various SDIs that companies come across while implementing SDPs, there are no many studies available viz. studies that categorically identify and address the root cause impediments that a manufacturing company has to dynamically focus for smooth running of SDPs. This process has to be timed in practice by the manufacturer for moving ahead of the competition and eventually to become the leader. Following SDIs were chosen for analysis in the current study, Lack of Mutual Trust (LMT) [49,50,51,52,59,60], Poor Communication and Feedback systems (PCF) [53,54,55,56,59], Lack of Adaptability (LAT) [57], Mismatch in Goals and Objectives (MGO) [51,58,59], Lack of Top management Commitment (LTC) [5, 54, 59, 60], Poor Profit and Risk sharing mechanisms (PPR) [5,59], Poor Devolution of Authority(PDA) [18], Poor Technology and Knowledge transfer(PTK) [5], Poor Conflict Management (PCM) [56,61,62], Lack of Total cost Perspective (LTP) [64,65], Lack of Coordination (LCD) [66], Lack of Compatibility (LCT) [discussion with experts], Lack of Turnout Time (LTT) [discussion with experts], Employee Attrition Rate (EAR) [discussion with experts]. In the next section, the methodology of the process to be practiced is discussed in detail.
3 Methodology
The aim of the proposed methodology is to obtain root cause impediments under different categories (i.e. from supplier's side/ manufacturer's side/ from both the sides/ from external environment/ others) and facilitate the manufacturer to construct action plans accordingly to overcome these SDIs. The methodology initiates with identification of major categories from which large number of impediments arouse in the implementation of SDPs. Then under each category, generic set of SDIs are to be identified, screened and subjected to further analysis. For analyzing and establishing the relationship between SDIs under each category, the ISM integrated with FMICMAC algorithm is used, programmed in MATLAB 7.10.0 (R2010a). The step by step procedure of ISM and FMICMAC algorithm is presented in the section 3.2. Inputs from the experts are taken at two stages (i.e. in first stage on binary scale and in second stage on fuzzy scale). In the first stage, the Contextual Relationship Matrix (CRM) among the right SDIs under each category is developed on the basis of team of multiple experts' judgments (see section 3.2.1). The CRMs under each category is fed into the ISM algorithm coded in the MATLAB. The CRMs subsequently get transformed as per the steps in the ISM algorithm, mentioned in the section 3.2.1. The ISM algorithm gives outputs to draw fruitful insights in terms of driving and dependence powers of each SDI, relationship between SDIs, level partitioning of SDIs, structural/ ISM model and classification of SDIs. The results obtained from the ISM algorithm give certain understandings regarding SDIs however, to improve their analysis; ISM is integrated with FMICMAC analysis giving the experts enough degrees of freedom in expressing their views. The same team of experts consulted for developing CRM must be asked to express their views regarding the possible strength of relationship between SDIs. This is the second stage of inputs taken from the experts. The following sections detail the proposed methodology for analyzing the SDIs.
3.2 ISM - fuzzy MICMAC methodology for analyzing SDIs
Stringent studies must be employed for the analysis of SDIs such that type of relationships (influencing/ influenced/ both / none) between them and significance of relationships (ranking in terms of influencing and influenced) are determined which in turn will provide more insights in SDP implementation. In the current study, ISM integrated with FMICMAC is chosen and the following sections will also justify its adoption.
3.2.1 ISM Algorithm
ISM methodology has the ability to draw the order and direction of relationships among impediments/barriers/ obstacles of a complex system [27]. ISM is a qualitative tool used by a number of researchers in various environments i.e. green SC management [28,29, 30, 31,32,33,34], supply management [35, 36], logistics [37, 38], SC risks [39], barriers to corporate social responsibility [40], selection of best SC practices [41]; barrier analysis for product service system [42], enablers of SC competitiveness [43], barriers of SC collaboration [44]; energy conservation [45], quality management [46], modeling success factors in national R & D organizations [47], enablers for integration in SC management [48] etc. In the current study the relationships between the SDIs have to be studied in terms of driving and dependence powers in SDP environment in order to implement SDP effectively. Therefore, ISM methodology is adopted to know these relationships among the SDIs and develop a structural framework of SDIs for SD. The ISM methodology used in this paper is discussed below:
Step-1 The irredundant, properly accounted, relevant and significant SDIs are considered to develop Structural Self-Interaction Matrix (SSIM) based on contextual relationships among the SDIs. These contextual relationships show the way they are related to each other in the manufacturing SC environment where the study is carried out. They are created considering the experts' judgment. Four symbols (A: SDI 'j' leads to SDI 'i'; V: SDI 'i' leads to SDI 'j'; X: SDI 'i' leads to SDI 'j' and SDI 'j' leads to SDI 'i' and O: No relationship between SDI 'i' and SDI 'j') are used for the type of the relation that exists between the SDIs ('i' and 'j').
Step-2 The Initial Reachability Matrix (IRM) is developed by converting SSIM into a binary matrix, substituting V, A, X and O by 1 and 0 [5].
Step-3 The Final Reachability Matrix (FRM) is developed from IRM considering transitivity in the contextual relations of SDIs. Transitivity in the relationship is determined as follows: if SDI "i" is related to SDI 'j' and SDI 'j' is related to SDI 'k', then SDI 'i' is related to SDI 'k'. Then the (i, k) entry in the FRM becomes 1*. Step-4 Driving and dependence power of each SDI is determined by taking summation of the elements along the rows and columns of FRM respectively. The SDIs are ranked on the basis of driving and dependence powers. Step-5 The level partitions are developed by segregating FRM into different levels. It starts with developing the reachability and antecedent sets for each SDI from the FRM. The reachability set of a SDI contains factor itself and other factors to which it may reach whereas antecedent set contains SDI itself and other SDIs, which may reach to it. The SDIs for which the reachability and intersection sets are same, occupy the top-level in the ISM hierarchy. The top-level SDIs are separated out from the initial set of SDIs and then the process is repeated until all the SDIs are assigned to a level.
Step-6 From the obtained level partitions a lower triangular matrix or canonical matrix is developed. It is just another form of FRM in which SDIs are positioned and clustered according to their level. This canonical matrix forms the basis for developing a directed graph called as digraph. If there is a relationship between SDI 'i' and SDI 'j', this is shown by an arrow which points from SDI 'i' to SDI 'j'.
Step-7 The structural model of SDIs is generated by eliminating the transitivity links in the diagraph (obtained in the step-6) and considering the level partitions (in step-5) and FRM (in step-4).
Step-8 The structural model of SDIs developed in Step-7 is reviewed for conceptual accuracy. If it is not conceptually accurate, then go to Step-1.
Step-9 Based on the driving and dependence powers obtained in the step-4, MICMAC/ Fuzzy MICMAC is analysis can be carried out (see section 3.2.2).
3.2.2 Fuzzy MICMAC Analysis
Although MICMAC analysis can classify SDIs, there is a limitation in the process. Since the relationships between SDIs are recorded in terms of binary values (either 0 or 1), there is no enough degree of freedom for experts in expressing the strength of relationship between the SDIs. To resolve the above issue FMICMAC analysis can be carried out. The steps mentioned below are to be followed to conduct FMICMAC analysis:
Step-1 In the FRM (see step-4 of the ISM algorithm in the section 3.2.1), replace all the diagonal elements along
with the transitive relationships with 0's to obtain a Binary Direct Relationship Matrix (BDRM).
Step-2 Using the same experts' judgments (see step-1 of the ISM algorithm in the section 3.2.1), the relationships
between the SDIs in the BDRM should be recollected to obtain fuzzy Direct Relationship Matrix (FuDRM).
Step-3 The FuDRM's power is raised by fuzzy matrix multiplication (rule: C = max k {min (aik, bkj)} where A =
[aik], B = [b^]) till it is converged. The convergence point can be determined where the driving and dependence
powers of SDIs are stabilized or cyclic in their variation with certain periodicity.
Step-4 Based on the new driving and dependence powers obtained from the final converged matrix, driver dependence diagram is to be plotted (with dependence power along the X-axis and driving power along the Y-axis) and SDIs are to be classified in to four groups (i.e. autonomous having lower dependence and driver power, dependent having higher dependence and lower driver power, lin]age having higher dependence and driver power and independent having lower dependence and higher driving power).
Fig.1 Flowchart of the proposed methodology for analyzing SDIs
4 Implementation of proposed methodology in an Indian Automotive Component Manufacturing Company
An Indian automotive component manufacturing company was approached to implement the above proposed methodology for analyzing the SDIs. The company is a large scale manufacturer and a prominent supplier for many automobile companies in India and abroad. The case company is well ]nown for its order winning capability and organizational culture. The company has a specific SD department with various SDPs running. Although at present, the company is able to bag orders and attract clients with its SDP initiatives nonetheless it has some serious problems under cover in SDP implementation. After holding detailed discussions with the people at operational, tactical and strategic levels involved in SD activities, some gross to subtle problems were uncovered which were seriously affecting the SDP's effectiveness and company's performance. A team of multiple experts (i.e. twelve) from the cross functional departments having more than 7-10 years of experience in the case company were brought on to a common platform. When discussed with the experts regarding the implementation of SDPs there were different aggressive opinions among the experts. Most of the experts expressed that though none of them deny the presence of problems at the suppliers' side, manufacturer's side, from both the sides together and some from the external environment, it was SDIs from both the sides are seriously affecting the SD efforts in the case company. Taking this concern particularly in to consideration, SDIs arousing from both the sides together were concentrated in
the current study. The above proposed methodology and its objectives were explained to the company experts and were asked to give their opinions at two stages. The company experts were motivated with the proposed methodology and agreed to cooperate but repeatedly cautioned not to reveal the identity of the company. So, in order to protect the interests of the company, it is named as company 'A' in the current discussion. Initially, thirty SDIs were identified through literature survey, brain storming and experts' opinions. These SDIs were subjected to the redundancy test to eliminate alike SDIs and obtained generic set of 20 SDIs. At this stage the experts' team was asked to reflect about the company A's SDP environment which churned out a range of issues while practically implementing SDPs. The generic set of 20 SDIs was discussed with the team of experts to check for accountancy, relevancy, and significance of SDIs whether or not the right list of SDIs are chosen for analysis. After going through the series of screening tests, it was concluded 14 SDIs mentioned in the literature review section were significant for the company's SDPs implementation. For analyzing 14 SDIs, experts' collective opinions were taken and further analysis was carried as mentioned in Section 3.
5 Results and discussions
The results obtained after implementation of the proposed methodology as mentioned in section 4 are interpreted under four sections (i.e. level partitioning, development of digraph, development of ISM Model and SDIs classification). Each section is discussed in detail below.
5.1 Level partitioning
Level partitioning is the basis for constructing ISM model of the system under study. In the current study, SDIs were leveled across four levels in four iterations. PCF is positioned in the level-IV and it is having high driving power while PPR, PDA and PTK at III level. These bottommost levels' SDIs represent the impediments that can be assuaged easily as well as used to lessen the other SDIs located on the higher levels. The SDIs: LMT, LAT, MGO, PCM, LTT and EAR are positioned in the level-I and have high dependence power (i.e. closer to 14) with different driving powers. The SDIs positioned in this level represent the long standing subtle impediments due to which current SDP implementation process is obstructed. The SDIs positioned in the other levels can be treated as those which are to be tactically addressed in the SDP implementation process.
5.2 Development of Digraph
From the FRM, structural model is developed by means of vertices or nodes and lines of edges. Along each SDI 'i' if there is a relationship between SDI 'i' and SDI 'j' it is shown by an arrow pointing from 'i' to 'j'. This graph is called as directed graph or digraph. This digraph is a complex presentation of all details of relationship between SDIs including transitivity links. This is the unrefined stage of ISM model which is very difficult to comprehend and derive interpretations.
5.3 Development of ISM Model
The ISM model (see Figure-2) was generated after removing all the transitivity links present in between SDIs from the diagraph. SDIs in the structural model were arranged in the hierarchy as per the levels partitioned (see section 5.1 to know the significance of levels). Thus, the ISM model developed presents a directional framework for the case company in successfully implementing SDPs and gives clear mental picture of what experts think about the relationship between SDIs, their significance in improving SDP implementation process and the prime impediments to be addressed.
5.4 SDIs Classification
The classification of SDIs for the case company was carried out through both MICMAC and FMICMAC analyses. The MICMAC or FMICMAC analyses are carried out on the basis of driving and dependence powers
however, results from FMICMAC analysis are presented in the current discussion. All 14 SDIs were classified into four clusters and their distribution is discussed as shown below:
Fig.2 ISM model of Supplier Development Impediments
Fnzzv JHCMAC Analv&ia of SDIs
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(Driver) FDA ■ l. | LAT J Li IT
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Fig.3 FMICMAC Driver Dependence Diagram of SDIs
Driver quadrant (High driving power, Low dependence power) : The SDIs i.e. PCF, PPR, PDA, LTC, and MGO were clustered in driver/ independent cluster after taking opinions in terms of possible relationship strength. These SDIs have high driving capacity which means by addressing these SDIs other SDIs can be mitigated. These are the SDIs which have to be addressed at first. The case company can start its action with addressing SDIs i.e. PCF, followed by PDA, PPR, LTC and MGO.
Autonomous quadrant (Low driving power, Low dependence power) : Those SDIs which fall in this quadrant are relatively disconnected from the SDP implementation process. It was found that EAR and LTT of the 14 SDIs fallen in the autonomous cluster. Thus, it was concluded that, only 12 SDIs were relevant for the case company's SDP environment which are obstructing SDP implementation process.
Dependent quadrant (Low driving power, High dependence power): The SDIs i.e. PTK, PCM and LCD were clustered in the dependent quadrant. This signifies that these SDIs' mitigation is mainly dependent on the other SDIs having the capacity to drive. The SDIs falling in this cluster represent that these are the impediments which cannot be addressed directly but through other SDIs.
Linkage quadrant (High driving power, High dependence power: Out of 14 SDIs chosen, 3 SDIs (i.e. LCT, LAT and LMT) are grouped in this cluster having both high driving and high dependence power. Typically the SDIs that fall in this cluster can be attributed as unstable because they have feedback effect i.e. they get affected by their own action and so are difficult to manage. However, these SDIs cannot be ignored and have to be closely monitored regarding their status in making decisions.
6 Conclusions
SDP is an alternative which companies do consider to make its critical suppliers capable. However, many firms often fall short of wasting their SDP efforts in vain because of various SDIs. Many at times it happens that though employees of the firm are aware of SDIs, they do address yet the SDIs keep coming in the way of SDP implementation. This is because the root cause of SDIs are not identified and addressed. Thus, in the current study a methodology is proposed to resolve the aforementioned issue. For validating the utility, the proposed methodology is applied to an Indian automotive component manufacturing company and certain important conclusions were drawn. From the driver dependence diagram, it is clearly observed that not all the SDIs considered are relevant in implementing SDPs in the case company as two SDIs, EAR and LTT had fallen in the autonomous cluster. From the ISM model along with FMICMAC driver dependence diagram, PCF (at level-4 in Figure-2 as well as in driver cluster in Figure-3), PAD, PPR and LTC (at level-3 in Figure-2 as well as in driver cluster in Figure-4) can be inferred as root cause SDIs. To conclude from the ISM model, the PCF is the most influencing SDIs and can be considered as the strongest root cause for the other SDIs. Therefore, PCF of the manufacturer is the prerequisite for implementing SDP which the case company is seriously lacking. Thus, the strong PCF should be established for successfully implementing SDPs. Manufacturer and suppliers' must develop good communication channels i.e. manufacturer's requirements or initiatives must be clearly communicated through proper ways and collect feedback from the suppliers. Also, the case company must empower its employees through proper devolution of authority. The SDIs (i.e. LMT, LAT, MGO, PCM, LTT and EAR) at level-1 in the ISM model can be treated as subtle SDIs and their improvement can be achieved through other SDIs in the lower levels. The change achieved along these SDIs may not immediate and direct nonetheless the manufacturer must constantly pursue after root cause SDIs and gradually mitigate these SDIs. From the case study conducted, it can be concluded that the case company must devise action plans along the root cause SDIs and move towards eliminating hindrance of any sorts from these SDIs. The case company was pleased with the results obtained from this study, however these results cannot be generalized for all, as it is based on single Indian manufacturing company. But SC managers can apply the proposed approach for analyzing the SDIs with respect to their manufacturing environment reflecting their own case situations and priority considerations.
References
[1] L. M.Ellram, M. C. Cooper, Supply chain management, partnership, and the shipper-third party relationship. International Journal of Logistics Management, 1 (2)(1990), pp. 1-10.
[2] Li, S., Ragu-Nathan, B., Ragu-Nathan, T. S., &SubbaRao, S. (2006). The impact of supply chain management practices on competitive advantage and organizational performance. Omega, 34(2), pp. 107-124.
[3] R.Sukwadi,H. M. Wee, C. C. Yang, Supply Chain Performance Based on the Lean-Agile Operations and Supplier-Firm Partnership: An Empirical Study on the Garment Industry in Indonesia. Journal of Small Business Management, 51(2) (2013), pp. 297-311.
[4]R. B.Handfield, D. R. Krause, T. V.Scannell, R. M. Monczka, Avoid the pitfalls in supplier development. Supply Chains and Total Product Systems: A Reader, 58 (2006).
[5] S.Routroy, S. K.Pradhan, Evaluating the critical success factors of supplier development: a case study. Benchmarking: An International Journal, 20(3) (2013), pp. 322-341.
[6] D. M.Lascelles, B. G.Dale. Examining the barriers to supplier development. International Journal of Quality & Reliability Management, 7(2)(1990), pp. 46-56.
[7] M.R. Leenders, Supplier development. Journal of Purchasing, 2(4) (1966), pp. 47-62.
[8] C.K.Hahn, C.Watts and K.Y. Kim, The supplier development program: a conceptual model. International Journal of Purchasing and Materials
Management, 26(2) (1990), pp. 2-7.
[9] D.R.Krause, L.M. Ellram, Critical elements of supplier development. European Journal of Purchasing and Supply Management, 3(1) (1997), pp. 21-31.
[10] D.R.Krause, The antecedents of buying firms' efforts to improve suppliers. Journal of Operations Management, 17(2) (1999), pp. 205-24.
[11] S. Wagner, A firm's responses to deficient suppliers and competitive advantage. Journal of Business Research, 59 (2006), pp. 686-695.
[12] D.R.Krause, R.B.Handfield, Developing a world class supply base. Center for Advanced Purchasing Studies, (2007), pp. 1-11.
[13] S. B.Modi, V. A.Mabert, Supplier development: improving supplier performance through knowledge transfer.Journal of operations management, 25(1) (2007), pp. 42-64.
[14] A.K.Asare, T.Brashear, J.Yang, J. Kang, The relationship between supplier development and firm performance: the mediating role of marketing process improvement. Journal of Business and Industrial Marketing, 28(6) (2013), pp.523-532.
[15] H.Nagati, C.Rebolledo, Supplier development efforts: The suppliers' point of view. Industrial Marketing Management, 42(2) (2013), pp. 180-188.
[16] R.M.Monczka, J.T.Trent,T.J.Callahan, Supply base strategies to maximize supplier performance. International Journal of Physical Distribution and Logistics Management, 23(4)(1993),pp. 42-54.
[17] J. Morgan, Supplier programs take time to become world class. Purchasing, 19 (1993), pp. 61-63.
[18] J.L.Hartley, G.E. Jones, Process oriented supplier development: building the capability for change.International Journal of Purchasing and Materials Management. 33(3)(1997), pp. 24-29.
[19] F. M. Reed, K. Walsh, Enhancing technological capability through supplier development: a study of the UK aerospace industry. Engineering Management, IEEE Transactions, 49(3) (2002), pp. 231-242.
[20] M.Giannakis, Facilitating learning and knowledge transfer through supplier development. SC Management: An International Journal, 13(113/1) (2008), pp. 62-72.
[21] S.Talluri, R.Narasimhan, W. Chung, Manufacturer cooperation in supplier development under risk.European Journal of Operational Research, 207(1) (2010), pp.165-173.
[22] S.M. Wagner, Indirect and direct supplier development: performance implications of individual and combined effects. IEEE Transactions on Engineering Management, 57(4)(2010), pp. 536-546.
[23] A.Shokri, F. Nabhani,S.N.B. Hodgson, Supplier development practice: Arising the problems of upstream delivery for a food distribution SME in the UK.Robotics and Computer-Integrated Manufacturing, 26(6) (2010), pp.639-646.
[24] A. S.Carr, J. N.Pearson, Strategically managed buyer-supplier relationships and performance outcomes. Journal of operations management, 17(5) (1999), pp. 497-519.
[25] S. M.Wagner, Supplier development practices: an exploratory study. European journal of marketing, 40(5/6) (2006), pp. 554-571.
[26] D. R.Krause, L. M. Ellram, Critical elements of supplier development The buying-firm perspective. European Journal of Purchasing & Supply Management, 3(1)(1997), pp. 21-31.
[27] A.P. Sage, Interpretive structural modeling: methodology for large-scale systems. New York: McGraw-Hill, (1977), pp. 91-164.
[28] A.Diabat, K.Govindan, An analysis of the drivers affecting the implementation of green SC management. Resources, Conservation and Recycling, 55(6) (2011), pp. 659-667.
[29] K.Govindan, D.Kannan, K.Mathiyazhagan, A.B.L.D.S.Jabbour, C.J.C.Jabbour, Analyzing green SC management practices in Brazil's electrical/electronics industry using interpretive structural modelling. International Journal of Environmental Studies, 70(4) (2013), pp. 477493.
[30] K.Mathiyazhagan, A. N.Haq, Analysis of the influential pressures for green SC management adoption-an Indian perspective using interpretive structural modeling. The International Journal of Advanced Manufacturing Technology, 68(1) (2013), pp. 817-833.
[31] S.Luthra, V. Kumar, S. Kumar, A.Haleem, Barriers to implement green SC management in automobile industry using interpretive structural modeling technique: An Indian perspective. Journal of Industrial Engineering and Management, 4(2) (2011), pp. 231-257.
[32] S.Kumar, S.Luthra, A. Haleem, Customer involvement in greening the SC: an interpretive structural modeling methodology. Journal of Industrial Engineering International, 9(1) (2013), pp. 1-13.
[33] G.Kannan, A. N.Haq, P. Sasikumar, S.Arunachalam, Analysis and selection of green suppliers using interpretative structural modelling and analytic hierarchy process.International Journal of Management and Decision Making, 9(2)(2008), pp. 163-182.
[34] R. K.Mudgal, R. Shankar, P.Talib, T.Raj, Greening the SC practices: an Indian perspective of enablers' relationships. International Journal of Advanced Operations Management, 1(2) (2009), pp. 151-176.
[35] K.Govindan, D.Kannan, A.N.Haq, Analyzing supplier development criteria for an automobile industry. Industrial Management and Data Systems, 110(1) (2010), pp. 43-62.
[36] J.Sarkis, S.Talluri, A model for strategic supplier selection.Journal of SC management, 38(1) (2002), pp. 18-28.
[37] G.Kannan, A. N. Haq, P.Sasikumar, S. Arunachalam, Analysis and selection of green suppliers using interpretative structural modelling and analytic hierarchy process.International Journal of Management and Decision Making, 9(2) (2008), pp. 163-182.
[38] J.Thakkar, S. G.Deshmukh, A. D. Gupta, R.Shankar, Selection of third-party logistics (3PL): a hybrid approach using interpretive structural modeling (ISM) and analytic network process (ANP). In SC Forum: An International Journal, BEM-Bordeaux Management School, 6(1) (2005), pp. 32-46.
[39] H. C.Pfohl, P. Gallus, D.Thomas, Interpretive structural modeling of SC risks.International Journal of physical distribution and logistics management, 41(9) (2011), pp. 839-859.
[40] M.N. Faisal, Analysing the barriers to corporate social responsibility in SCs: an interpretive structural modelling approach. International Journal of Logistics: Research and Applications, 13(3)(2010), pp. 179-195.
[41] R. K.Singh, H. O.Sharma, S. K. Garg, Interpretive structural modelling for selection of best SC practices. International Journal of Business Performance and SC Modelling, 2(3) (2010), pp. 237-257.
[42] T. C.Kuo, H. Y. Ma, S. H.Huang,A. H. Hu, C. S.Huang, Barrier analysis for product service system using interpretive structural model. The International Journal of Advanced Manufacturing Technology, 49(1-4) (2010), pp. 407-417.
[43] A.Verma, N.Seth, N. Singhal, Enablers of SC competitiveness: an interpretive structural modelling approach. International Journal of Value Chain Management, 5(3) (2011), pp. 212-231.
[44] A.Ramesh, D.K.Banwet, R. Shankar, Modeling the barriers of SC collaboration.Journal of Modelling in Management, 5(2) (2010), pp. 176193.
[45] J.P.Saxena, Sushil and P.Vrat, Scenario building: a critical study of energy conservation in the Indian cement industry. Technological Forecasting and Social Change, 41(2) (1992), pp. 121 - 146
[46] S.Sahney, D.K.Banwet, S. Karunes, An integrated framework of indices or quality management in education: a faculty perspective.The TQM Journal, 20(5) (2008), pp. 502-519.
[47] Jyoti, D.K.Banwet, S.G. Deshmukh, (2010). 'Modelling the success factors for national RandD organizations: a case of India', Journal of Modelling in Management, Vol. 5, No. 2, pp. 158-175.
[48]V.C.Pandey, G. Suresh, R.Shankar, An Interpretive Structural Modeling of enabler variables for integration in SC management. Productivity, 46(1)(2005), pp. 93-108.
[49] T.Laaksonen, T.Jarimo, H. I. Kulmala, Cooperative strategies in customer-supplier relationships: The role of interfirm trust. International Journal of Production Economics, 120(1) (2009), pp. 79-87.
[50] Y.Liu, Y.Li, L.Zhang, Control mechanisms across a buyer-supplier relationship quality matrix. Journal of Business Research, 63(1) (2010), pp. 3-12.
[51] P. Kumar, R. Shankar, S. S.Yadav, An analysis of supplier development issues in global context: an approach of fuzzy based modelling. International Journal of Logistics Systems and Management, 11(3) (2012), pp. 407-428.
[52] D. Y.Kim, V.Kumar, U. Kumar, Performance assessment framework for supply chain partnership. Supply Chain Management: An International Journal, 15(3) (2010), pp. 187-195.
[53] X.Fu, Q. Zhu, J.Sarkis, Evaluating green supplier development programs at a telecommunications systems provider. International Journal of Production Economics, 140(1) (2012), pp. 357-367.
[54] C.Bai, J.Sarkis, Evaluating supplier development programs with a grey based rough set methodology. Expert Systems with Applications, 38(11) (2011), pp. 13505-13517.
[55] P.Humphreys, T.Cadden, L.Wen-Li, M.McHugh, An investigation into supplier development activities and their influence on performance in the Chinese electronics industry. Production Planning and Control, 22(2) (2011), 137-156.
[56] P.Arroyo-López, E. Holmen, L.de Boer, How do supplier development programs affect suppliers?: Insights for suppliers, buyers and governments from an empirical study in Mexico. Business Process Management Journal, 18(4) (2012), pp. 680-707.
[57] K.Gebert, Performance-control in buyer-supplier relationships: Development of a contingency-based framework for analysis. In Performance Control in Buyer-Supplier Relationships.Springer Fachmedien Wiesbaden, (2014),pp. 64-99.
[58] M.Lockstrom, J. Schadel, R.Moser, N. J Harrison, Successful supplier integration in the Chinese automotive industry: a theoretical framework. International Journal of Integrated Supply Management, 5(3) (2010), pp. 260-283.
[59] M. K.Mohanty, P.Gahan, S.Choudhury, Why most of the supplier development programs fail in discrete manufacturing-findings from selected Indian discrete manufacturing industries. International Journal of Management Science and Engineering Management, 9(3) (2014), pp. 1-11.
[60] S. K.Mahapatra, A.Das, R.,Narasimhan A contingent theory of supplier management initiatives: effects of competitive intensity and product life cycle. Journal of Operations Management, 30(5)(2012), pp. 406-422.
[61] F.Wynstra, J. C.Anderson, , J. A.Narus, M. Wouters, Supplier Development Responsibility and NPD Project Outcomes: The Roles of Monetary Quantification of Differences and Supporting-Detail Gathering. Journal of Product Innovation Management, 29(S1)(2012), pp. 103-123.
[62] W.Li, P. K.Humphreys, A. C.Yeung, C. E. Cheng, The impact of supplier development on buyer competitive advantage: A path analytic model. International Journal of Production Economics, 135(1) (2012), 353-366.
[63] C.Blome, H D.ollos, Paulraj, A, Green procurement and green supplier development: antecedents and effects on supplier performance. International Journal of Production Research, 52(1) (2014), 32-49
[64] A.Aksoy, N. Öztürk, Supplier selection and performance evaluation in just-in-time production environments. Expert Systems with Applications, 38(5) (2011)., 6351-6359.
[65] H. Schiele, Early supplier integration: the dual role of purchasing in new product development. R&D Management, 40(2) (2010), pp. 138153.
[66] Y.Hong, J. L. Hartley, Managing the supplier-supplier interface in product development: The moderating role of technological newness. Journal of Supply Chain Management, 47(3)(2011), pp. 43-62.
