Supplier-Buyer Relationships in Indian Manufacturing Environment: An Empirical Study

Supplier-Buyer Relationships in Indian Manufacturing Environment: An Empirical Study

A. J. Gujar

Research Scholar, Government College of Engineering, Amravati, India

Prof. (Dr.) P. M. Khodke

Principal, Government College of Engineering, Karad, India

Abstract This paper presents an empirical study of supplier-buyer relationships practices in the Indian manufacturing industries. Although the research in the area of supply chain management (SCM) has grown in recent time, the literature has yet to furnish an accepted explanation for supplier- buyer relationships are to be manifested in SCM given external and internal uncertainties to explore procurement flexibility. These manufacturing industries have been involved in such supplier-buyer relationships management practices to the extent of their participation as suppliers, distributors and in other capacities as business partners. This study confirms and validates that Indian manufacturing industries are facing significant pressures from external as well as internal stakeholders to adopt such relationships practices. Initial results gave a better understanding of which procurement flexibility is preferred when facing different environmental challenges. The results indicate strong, positive, and direct relationships between factors affecting supplier-buyer relationships and external as well as internal uncertainties.

Keywords supplier-buyer relationships; procurement flexibility; empirical study; manufacturing industries; multiple linear regression

1. INTRODUCTION

   The term supply chain management (SCM) was introduced in the 1980s and the concept has changed quite in the past decades. Its function has always been procurement, manufacturing, distribution, marketing and after sales service. There are several players with conflicting objectives in every supply chain network; the conflicting objectives of such players have led to delays, excessive inventory, lack of production capacity, material distribution problems, poor customer service, and wasted resources. Important link in supply chain exist on the upstream section of the supply chain network i.e. between manufacturer and his suppliers. All the entities in supply chain are suppliers and manufacturers who add value along the supply chain. A successful relationship is one in which there is mutual sharing of risk and rewards, clear understanding of each others roles and responsibilities, high level of commitment and trust, long-term orientation, mutual information sharing, a sincere desire to win and responsiveness towards each others and end customers need. A supply chain network consists of supplier, manufacturer and customer, as shown in Fig. 1.

   Supply chain is a network of facilities and distribution options that performs the functions of procurement of

   materials, transformation of these materials into intermediate and finished products and delivery to customers.

   Fig 1. Schematic representation of a typical supply chain

   SCM has been defined in several ways by incorporating the end-to-end activities such as purchasing, manufacturing, selling, marketing, after sales service and management of various relationships with suppliers and customers. SCM should not be confused with supplier management. SCM covers a far broader scope

   Manufacturers face an increasingly uncertain internal as well as external environment. Therefore, in todays competitive environment, it is critical that manufacturing industries have organizational flexibility in real time to respond to environmental uncertainties. Flexibility is the organizations ability to meet an increasing variety of customers expectation without additional costs, time, organizational disruptions, or performance losses. It is widely argued that in order to be competitive, it is critical that manufacturing industries organizations respond to such uncertainties as rapidly as possible.

   To be competitive and enhance their competitive advantage, manufacturers also create strategic alliances; i.e. relationships with their suppliers and buyers via transferring information and materials/product flow to each other. Consequently, developing and maintaining flexible and responsive supply chain networks could make the difference between survival and demise for manufacturing firms and, consequently, the supply chain networks future competitiveness and the continued survival of the entities within them.

   The supplier-buyer relationship role is repeated along the supply chain network between the entities. Although the activities between the various entities along the supply chain network are different and independent of each other, desirable flexibility elements and dimensions remain the same; hence, the supplier-buyer flexibility elements and dimensions are repeated along the supply chain network, but in different environments and situations.

   There is, however, inadequate research in the Indian manufacturing sector in terms of supplier capabilities or

   procurement activities. The current research is developed to fill that gap by identifying the various constraints and strategic procurement activities of Indian manufacturers.

2. REVIEW OF LITERATURE

   It can be seen that the globally accepTABLE definition of SCM does not exist. The common thread in any definition is that SCM seeks to integrate performance measures over multiple firms or processes, rather than taking perspective of a single firm or process. The study of Koste and Malhotra (1999) have pointed out the relationship between the different flexibility dimensions and come to a hierarchy of flexibility dimensions, also called a vertical classification as shown in Fig. 2. This hierarchy consists of different tiers in which the lower tiers, which are more tactical, contain the flexibility dimensions that serve as building blocks for the upper tiers, which are more strategic.

   Fig. 2. Hierarchy of flexibility dimensions (Koste and Malhotra, 1999)

   Majority of literature speaks about concept of organizational structural design but establishing the compatibility and capabilities of the existing organizational structure needs more efforts. It is also necessary for all the organizations involved in the supply chain to think alike and ensure that their links are connected smoothly (Handfield and Betchel 2002).

   Buyer supplier relationship depends upon strategic requirements of the organization, supplier performance, mode of operation and personal factors. Strategic issues may be who to choose as a partner and for what type of product or service. Out of these mode of operation may be pricing, structure, information exchange levels, technology are qualitative and rest three i.e. business area, product or process are quantitative (Mohanty and Gahan 2012). Researchers have found few parameters like innovation and technology, strategic collaboration and new product influencing supplier- manufacturer relationship.

   1. Framework for supply chain performance measurement

      Framework for measurement of performance of any supply chain depends on the extent to which flexibility can be achieved. Supply chain needs to flexible so as accommodate foreseen and unforeseen uncertainties in supply chain environment. It is imperative to identify the uncertainties based on which flexibility dimensions are decided. After determining dimensions, a mechanism is required to be evolved to measure the extent of achievement. This is done by deciding the appropriate elements.

      1. Uncertainty

         Uncertainty can be defined as the state of being unsure of something due to some reasons. ncertainty affects the internal as well as external business environment in which firms compete and is changing continuously. The literature available on uncertainty is scattered and does not pinpoint the specific sources of uncertainty. Important sources of uncertainty identified in the literature and inherent in a supply chain are customer demand (Davis 1993; Gerwin 1993; Wilding 1998; Petrovic et al. 1999; Li et al. 2001; Simangunsong et al. 2012), customer reliability (Gerwin 1993; Petrovic et al. 1999; An-Yuan Chang 2011). Additionally, raw materials prices (Badri et al. 2000; Priem et al. 2002; An-Yuan Chang 2011), raw materials availability (Swamidass and Newell 1987; Anupindi and Akella 1993; Wilding 1998; Gullu et al. 1999; Badri et al. 2000; An-Yuan Chang 2011), inflation (Davis 1993; Simangunsong et al. 2012), technology (Swamidass and Newell 1987; Gerwin 1993; Simangunsong et al. 2012), productivity (Davis 1993; Gerwin 1993; Li et al. 2001; Priem et al. 2002; Simangunsong et al. 2012), quality and quality of supply (Davis 1993; An-Yuan Chang 2011), and price variations due to exchange rate fluctuations (Badri et al. 2000; Priem et al. 2002; An-Yuan Chang 2011) are other sources for uncertainty. Moreover, increasing global competition (Badri et al. 2000; Priem et al. 2002; Simangunsong et al. 2012), accelerating technological change (Badri et al. 2000; An-Yuan Chang 2011), and expanding customer expectations (An-Yuan Chang 2011) are creating a turbulent environment.

         It can therefore be seen that the factors of uncertainty are derived from two areas, namely external and internal. In any supply chain, it is expected that, the uncertainties within nodes

         i.e. internal uncertainties should be taken care off by concerned node / organization. The uncertainties causing due to external factors are environmental uncertainty. The internal uncertainties represent the ability of the system to adapt, whereas the external uncertainties are market-oriented representing the ability of the system to meet customer demands.

      2. Flexibility Dimensions

         Dimension is defined as the competence and capabilities, which is related to the characteristics and functions of the situation / system. Flexibility is a complex concept partly because of its multidimensional construct. The literature classifies flexibility as shown in TABLE 1.

         TABLE 1. SUPPLY CHAIN FLEXIBILITY DIMENSIONS

         There is no unified agreement among researchers on the supply chain flexibility classification. The difficulty in classifying flexibility rose due to large number of dimensions in manufacturing flexibility itself.

         It can be seen from literature that, only cross functional and cross company efforts to increase flexibility and eliminate uncertainties can create the level of performance.

         Although some researchers have started addressing flexibility from the supply chain perspective, a majority of the current literature continues to address flexibility from the viewpoint of a manufacturing system or a production system as a single entity in supply chain. While the manufacturing flexibility literature provides a bottom-up view of flexibility in an organisation, it is perhaps business strategy literature that provides the top-down view. Manufacturing flexibility research can be used to help determine the components of supply chain flexibility and consequently of procurement flexibility. The literature presented and most relevant to dimensions of supplier-buyer flexibility in context with procurement flexibility has been reproduced in TABLE 2, so as to assist in identifying flexibility dimensions appropriately.

         TABLE 2. SUMMARY OF SUPPLY CHAIN FLEXIBILITY DIMENSIONS

         In summary, each author used different dimensions to identify supply chain flexibility, as is done in the manufacturing flexibility literature. However, in the supply chain context the dimensions should be related to supply chain functions.

      3. Flexibility Elements

   After identifying dimensions of flexibility, it becomes imperative to measure each of these dimensions so as to measure performance of supply chain. Further it is also possible to have more than one measure for a particular dimension. The performance measures so identified are regarded as element. Element is a construct / attributes which describe the dimensions of flexibility more elaborately.

   Flexibility elements vary in accordance with the strategies employed within various manufacturing industries. Therefore, by intention and design various industries will have a different emphasis on the dimensions as well as elements. Flexibility elements proposed by various researchers are presented in TABLE 3.

   TABLE 3. SUMMARY OF SUPPLY CHAIN FLEXIBILITY ELEMENTS

   The different elements identified by various investigators indicate that the range, mobility and uniformity can measure all flexibility dimensions irrespective of whether flexibility is being measured for individual node or a pair of node of any supply chain.

   Efficiency is the capability to react within the time constraints efficiently, while Responsiveness is quality of reacting in various situations which measures speed. Efficiency and responsiveness are related to time limits and measured in

   number which is representing range element. Robustness is the characteristic of strongness and indicates the strength which refers to unforeseen environmental uncertainties which is representing uniformity element. Versatility is a measure of the range of activities and refers to accommodating foreseen environmental uncertainties.

   Some of the findings from the review of literature are as follows:

   • The scanning of literature reveals that though ample information is available on purchasing and supplier- manufacturer relationship, it does not speak on measurement scale for supplier-manufacturer procurement flexibility. Procurement is critical in the manufacturing sector as it maintains the continuous production of components, materials and products. If there is a disruption in the supply, the production process is hampered. The literature reveals lack of established generalizable measures of flexibility in procurement relationships.

   • Majority literature is focused on manufacturing flexibility. However, the manufacturing flexibility dimensions, with modifications, may be used to align the procurement flexibility dimensions within the definition of supply chain management. An attempt is necessary in this direction to narrow the identified gap.

     Therefore supply chain flexibility has to be examined from an integrative and customer oriented perspective.

3. DEVELOPMENT OF RESEARCH HYPOTHESES

   In the context of supplier-buyer relationship to explore procurement flexibility, there are number of management practices suggested in literature. The same strategy / practice can have different degrees of importance at each level of the supply chain in manufacturing industries. In fact, the decision- making in selecting the appropriate strategies / practices remains to be daunting challenge to supply chain management managers.

   This study tries to expand the internal and external uncertainties affecting on the supplier-buyer relationship practices in Indian manufacturing industries, which has been explored in this research study to the external uncertainties as requirements of fluctuating customer demand which is affecting manufacturing strategy, Substitute imported products are affecting product sales, Changing government regulations and tariffs are affecting company / organization, and product obsolescence rate (Fig. 3). This generates the first hypothesis of this study H1 as:

   H1: The supplier-buyer relationship in manufacturing industries is affected by various external uncertainties.

   Fig. 3. Development of research hypotheses for this study

   Manufacturing industries are not only influenced by external uncertainties i.e. environmental concerns like recycling, competitors actio, and frequently changing the price by suppliers but also internal uncertainties affect supplier-buyer relationships. The above uncertainties compiled one hypothesis on internal uncertainties which may be expressed as H2:

   H2: The supplier-buyer relationship in manufacturing industries is also affected by internal uncertainties.

   As discussed above, the addition of internal uncertainties reasonably compliments the external uncertainties in explaining the supplier-buyer relationships. A manufacturing industrys internal uncertainties may be viewed as intermediate variables to adjust the influences of external uncertainties. This generates one more hypothesis on the relationship of external uncertainties and internal uncertainties in supplier-buyer relationships in this study, which may be documented as H3:

   H3: The relationships between an industrys external uncertainties and factors affecting supplier-buyer relationships are mediated by internal uncertainties.

   The manufacturing industries in India have been classified with respect to purchase volume of that industry in a that financial year, type of industry which is classified according to National Industries Classification (NIC) code, and no. of employees working in that manufacturing industry. The three hypotheses for these control variables, namely, purchase volume, type of NIC, no. of employees and can be documented as H41, H42, and H43:

   H41: There is a significant difference in the mean scores for different industries purchase volumes in respect of different factors affecting supplier-buyer relationships.

   H42: There is a significant difference in the mean scores for different type of NIC codes of industries in respect of different factors affecting supplier-buyer relationships.

   H43: There is a significant difference in the mean scores for different industries based on no. of employees in respect of different factors affecting supplier-buyer relationships.

   In order to establish that the manufacturing industries population do indeed carry out different practices of supplier- buyer relationships in a heterogeneous manner given the heterogeneity in purchase volume, type of NIC, no. of employees, these hypotheses, namely, H41, H42 and H43 have been particularly presented in order to communicate to a wider (industrial) audience.

4. RESEARCH METHODOLOGY

   The research methodology aids the researchers in allocation of limited resources by posing crucial choices. Its essentials are depicted in Fig. 4.

   1. Exploring data

      In this study, a survey questionnaire for measurement of factors affecting on supplier-buyer relationships to explore procurement flexibility in manufacturing industries of India was developed based on research of Mohanty and Prakash (2013). It was pilot tested with 15 respondents working in manufacturing industries having sound knowledge of supply chain management practices and procurement activities. It helped including internal and external uncertainties for supplier-buyer relationships in the study. Accordingly, the research framework for this study was developed (see Fig. 4), which is the basis for testing of research hypotheses.

      Fig. 4. Schematic diagram of research methodology

      The survey for studying supplier-buyer relationship practices were carried out in two stages. Data were collected from questionnaires administered in January 2013 for identifying factors of supplier-buyer relationships in the first stage of survey. The questionnaire used in this research had 23

      statements (see TABLE 4) for mapping the profile of the target respondents from manufacturing industries in India, where respondents had to agree on a scale of 1-7. Likert scale with seven responses for each item with scores ranging from

      strongly disagree 1 to strongly agree 7 is used in the measuring instrument. To improve the content validity after the first stage of survey, the measurement items relating to critical supplier-buyer relationship practices were assessed by four academic experts in supply chain management, who accepted for critical supplier-buyer relationship practices/measures to include six sub-constructs as flexibility in relationships, namely information exchange, supplier integration, supply chain strategy, design adaptability, supplier flexibility, and supplier logistics as a result of the factor analysis of the first stage of survey (see TABLE 5).

      TABLE 4. CRITICAL PRACTICES FOR SUPPLIER-BUYER RELATIONSHIP IMPLEMENTATION

      TABLE 5. FACTOR ANALYSIS OF SUPPLIER-BUYER RELATIONSHIPS STATEMENTS

   2. Displaying data using factors

      In the first stage of survey based on convenience sampling,

      123 final completed and accepTABLE questionnaires comprising of 23 items revealed a six-factor structure that explained 64.625% of total variance as shown in TABLE 5. The criteria for retaining the six factors were Eigen values greater than one and the ability to describe and label each factor. To assess the reliability of responses, Cronbachs alpha coefficient was calculated, and is found to be accepTABLE for the items within each factor solution. Also, Kaiser-Meyer- Olkin (KMO) measure of sampling adequacy was found to be 0.825, which is considered adequate. There is the obligatory requirement of 0.60 or above for Cronbachs alpha coefficient to demonstrate internal consistency of the established scales (Nunnally 1988). Likewise, the minimum accepTABLE value of KMO is 0.5 (Prakash, Mohanty, and Kallurkar 2011). Therefore, it can be concluded that the matrix did not suffer from multicollinearity or singularity.

      This establishes the face validity of supplier-buyer relationship factors (TABLE 5), which are briefly described below:

      • Information Exchange Flexibility – Receiving and providing sufficient range of information from manufacturer and/or to suppliers with accuracy and in real time is necessary. Suppliers willing to share critical information with manufacturers and information system (IS) are well integrated at suppliers and manufacturer end and also routine transfer of

        information on invoicing is done without human Intervention is essential one for the effective supplier-buyer relationships.

      • Supplier Integration Flexibility To cope up with, volatile situation at manufacturer end, suppliers are capable and easily adjust to changes in demand schedules by carrying sufficient inventory. If not, manufacturers are capable change over to different suppliers easily in a short time and at a low cost. Such flexibility is essential at manufacturer and supplier end to strengthen the relationships.

      • Supply Chain Strategy Flexibility – Organizational structure of manufacturer has the flexibility to improve operational relationships with their suppliers, also they have a range of organizational strategies for supplier integration and these organizational strategies are easy but are costly to implement in short time for better supplier-buyer relationships. Such flexibility is required at manufacturer and supplier end to strengthen the relationships.

      • Design Adaptability Flexibility Suppliers can deliver new components/materials at a low price and with the same quality and they can implement product design changes at a low cost and with the same quality. Such flexibility is required at supplier end to strengthen the relationships.

      • Supplier Flexibility – Suppliers can deliver new components/materials easily and in a short time and implement product design changes easily and in a short time and also time required for suppliers to switch from one part mix to another is short. Such flexibility is required at supplier end to strengthen the relationships.

      • Supplier Logistics Flexibility – Suppliers can deliver materials and components along various routes and modify these routes easily and in a real time. All material handling rotes exhibit similar performance levels. Such flexibility is required at supplier end to strengthen the reltionships.

        The result of the factor analysis has established for professionals in procurement/purchase that it is becoming increasingly important to be flexible by applying the flexibility principles to all facets of the supplier-buyer relationship: information exchange, supplier integration, organisational strategy, supplier flexibility and logistics to explore procurement flexibility.

   3. Examining data using pretesting through principal axis factoring

   Generally, when measures are developed, some type of pre- test should be performed. It ensures that items not behaving statistically as expected may need to be refined or deleted. The pre-test is carried out building the confirmatory factor analysis. At this stage, each scale dimension of supplier-buyer relationship was subjected to PAF using varimax rotation on data of 123 respondents, which had provided the results of EFA as information exchange flexibility, supplier integration flexibility, supply chain strategy flexibility,

   design adaptability flexibility, supplier flexibility, and

   supplier logistics flexibility. The purpose of subjecting the items in a sub-scale to PAF was to verify if all of the items loaded highly on a single factor. The final loadings for each sub-scale are summarized in TABLE 6.

   TABLE 6. SCALE PURIFICATION

   4.4. Examining data using pre-testing through testing reliability for pre-tested dimensions

   In the second stage of survey, we have selected our respondents across India who are directly associated with procurement/purchase department in manufacturing industries. We have used purposive non-probability sampling in this study, as we believed that some specific people can have only the information required in the survey. We had distributed 900 questionnaires in the independent sample; out of which 423 completed questionnaires were collected and analysed successful with the reliability test (TABLE 7). In this stage, we had also included external and internal uncertainties as we suggested formerly in the pilot testing.

   For the second stage of survey, only pre-tested dimensions along with measures for the external uncertainties comprised fluctuating customer demand; substitute imported products, changing government regulations & tariffs, and product obsolescence rate; and measures for the internal uncertainties comprised environmental concern like recycling, competitors action, and frequently price change from suppliers.

   Data were collected using independent samples in the second stage of survey from questionnaires administered in December 2013 for studying the research hypotheses.

   TABLE 7. RELIABILITY ANALYSIS

   1. Data preparation for hypotheses testing

      1. Descriptive statistics

         The control variables indicate manufacturing industries where the total size of independent sample was 423. 5.20% of the textile manufacturing companies (NIC code 17), 3.30% of the paper and paper product manufacturing companies (NIC code 21), 10.87% of the chemicals and chemical products manufacturing companies (NIC code 24), 5.20% of the rubber & plastic products manufacturing companies (NIC code 25), 11.11% of the basic metals related manufacturing companies (NIC code 27), 14.18% of the fabricated metal products, except machinery & equipment manufacturing companies (NIC code 28), 33.09% of the machinery & equipment manufacturing companies (NIC code 29), 4.96% of the electrical machinery & apparatus manufacturing companies (NIC code 31), 4.49% of the radio, television, & communication equipment manufacturing companies (NIC code 32), 2.36% of the medical, precision, & optical instruments manufacturing companies (NIC code 33), 2.60% of the motor vehicles, trailers, & semi-trailers manufacturing companies (NIC code 34), and 2.60% of the other transport equipment manufacturing companies (NIC code 35). It can be seen that majorly all types of manufacturing industries adequately either by size or by type.

      2. Operationalisation of the variables

   Dependent variable: The dependent variable in this study is factors affecting supplier-buyer relationships; a companys overall supplier-buyer relationships practice level. Six factors of supplier-buyer relationships activities were identified to estimate a companys overall level of supplier-buyer relationships practices in the current Indian context (TABLE 5

   – 7).

   Control Variables: They are size, type and the industrial sector to which it belongs.

   Independent Variables: A seven-point Likert scale was used to measure the importance, strength or degree of each item in respect of external uncertainties and internal uncertainties variables, where each item with scores ranging from strongly disagree 1 to strongly agree 7 is used in the measuring instrument to estimate its relationship with factors affecting supplier-buyer relationships to explore procurement flexibility. These have been considered as determinantal

   reasons for implementation of supplier-buyer relationship activities. Various items of external uncertainties were fluctuating customer demand (FCD), substitute imported products (SIP), changing government regulations and tariffs (CGRT), and product obsolescence rate (POR). Various items of internal uncertainties are recycling (RCY), competitors action (COA), and frequently price change from suppliers (FPCS).

5. RESULTS AND DISCUSSION

   1. Checking for suitability of independent variables

      Pearson rank correlation was used to give a preliminary observation of the relationships between the overall level of supplier-buyer relationship practices and the determinant factors identified earlier. The correlation matrix is shown in TABLE 8.

      TABLE 8. CORRELATION COEFFICIENTS OF SUPPLIER-BUYER RELATIONSHIP FLEXIBILITY AND THE DETERMINANT FACTORS

      This indicates that supplier-buyer relationship flexibility is significantly correlated with all external uncertainties variables, and internal uncertainties variables like RCY and FPCS. Standard multiple regressions were performed with factors affecting suppler-buyer relationships flexibility as the dependent variable and each of the determinant factors and controls as independent variables. The results are listed in TABLE 9.

      TABLE 9. GOODNESS OF FIT OF THE MODEL

      The level of multicollinearity between the variables was tested by an inspection of the condition index and variance proportions in the SPSS collinearity diagnostics TABLE. According to the criteria given by Tabachnick and Fidell (2001), multi collinearity is not a problem in this analysis since each condition index is less than 30 and the variance proportions are much less than 50.

      This study has used four alternative models using multiple regression analysis, which is listed below:

      • Model 1: With predictors as (constant), FCD, SIP, CGRT, POR and dependent variable as Suppl. – Buyer relationship.

      • Model 2: With predictors as (constant), RCY, COA, FPCS and dependent variable as Suppl. – Buyer relationship.

      • Model 3: With predictors as (constant), FCD, SIP, CGRT, POR, RCY, COA, FPCS and dependent variable as Suppl. – Buyer relationship.

      • Model 4: With predictors as (constant), FCD, SIP, CGRT, POR, RCY, COA, FPCS, Purchase volume, NIC Code, No. of Employees and dependent variable as Suppl. – Buyer relationship.

      The best value of R2 has been obtained for Model 4 as 0.626, which means that 62.6% of variation is explained (see TABLE 9), which does establish discriminant validity, which is the extent to which a measure does not correlate with other constructs from which it is supposed to differ. The Adjusted R2 adjusts for the number of explanatory terms (independent variables) in a model and increases only if the new independent variable(s) improve(s) the model more than would be expected by chance.

   2. Selecting the best multiple linearregression Model for Hypotheses Testing

   The best model has been found to be Model 4, which applies control variables mediating the determinant external and internal uncertainties for determining the supplier-buyer relationships to explore procurement flexibility, whose regression results are shown in TABLEs 13. Additionally, regression results have been shown in TABLEs 10-12 for Model 1, Model 2, and Model 3, respectively.

   According to TABLEs 9 and 13, therefore, the best model as

   Model 4 can be written as:

   Supplier-Buyer Relationships = 5.376 + [Purchase volume (0.156) + NIC Code (-0.070) + No. of Employees (0.066) + FCD (0.154) + SIP (-0.095) + CGRT (0.006) + POR (0.094)

   + RCY (0.146) + COA (0.094) + FPCS (0.053) ……………… (1)

   TABLE 10. REGRESSION RESULTS FOR MODEL 1 OF SUPPLIER- BUYER RELATIONSHIP

   TABLE 11. REGRESSION RESULTS FOR MODEL 2 OF SUPPLIER- BUYER RELATIONSHIP

   TABLE 12. REGRESSION RESULTS FOR MODEL 3 OF SUPPLIER- BUYER RELATIONSHIP

   TABLE 13. REGRESSION RESULTS FOR MODEL 4 OF SUPPLIER- BUYER RELATIONSHIP

   It is to be seen from TABLE 13 and Equation (1) that the all the variables are included in the Model 4 and in Equation (1), which seen that all this variables are significant, so it may be concluded that Model 4 is the best model, from the multiple regression analysis. This establishes nomological validity, which is the extent to which the scale correlates in theoretically predicted ways with measures of different but related constructs.

   The regression results in TABLE 9 and 13 indicate that H1 is completely supported in general. This implies that fluctuating customer demand is affecting manufacturers manufacturing strategy, substitute imported products are also affecting on their product sales, changing government regulations and tariffs are directly affecting on manufacturing industries, and product obsolescence rate is also low, which are the external uncertainties affecting on supplier-buyer relationships. Among the internal uncertainties, H2 is supported implying that environmental concern like recycling is affecting manufacturing strategy, also difficult to predict competitors action, and manufacturers are suffering from frequently price change from their suppliers.

   There are no obvious changes in the significances of the regression results of Model 1, Model 2, and Model 3, which proves that the mediation function of internal uncertainties does occur and H3 is fully supported (see TABLE 10-12).

   Again, there are no obvious changes in the significances of the regression results listed in TABLEs 10 13, which means that there exists generally significant control for the mediation function of external uncertainties and H4 is generally supported except the variable NIC code, which stands for H42. The best model Model 4 has established that the manufacturing industries population in India do indeed carry out different phases of supplier-buyer relationships

   management practices, though in a heterogeneous and diverse manner with respect to the heterogeneity and diversity in size and nature of business for manufacturing industries in India.

   The empirical work carried out allows understanding of how the manufacturing industries population dealing with environmental uncertainty matters in a generic sense. This research has established key decision areas for supplier-buyer relationships management, which are validated factors of supplier-buyer relationships management.

6. CONCLUDING REMARKS

Indian manufacturing industries are facing significant pressures from internal as well as external uncertainties environment, to maintain good relationships with supplier; manufacturers are striving for the same to achieve procurement flexibility. Among external uncertainties, fluctuating customer demand and internal uncertainties like environmental concern i.e. recycling are mostly affecting on supplier-buyer relationships in manufacturing sector of India.

It has been also established in Indian manufacturing industries context that external uncertainties and adoption of supplier- buyer relationship management practices are fully mediated by internal uncertainties. The manufacturing industries population in India does indeed carry out different phases of the supplier-buyer relationship management practices, though in a heterogeneous /diversified manner with respect to heterogeneity/diversity in size and nature of business for manufacturing industries in India.

This paper has laid a broad foundation for ongoing programme of research concerning the integration of external and internal uncertainties for supplier-buyer relationships practices in supply chain. Completing this study brings together aspects of theory as well as practice. For theory, this study is an expansion of previous studies on supplier-buyer relationship management practices utilizing data from India, one of the emerging economies, which contributes to the literature of manufacturing industries and supplier-buyer relationship management practices to confirm and expand the scope of theoretical applications. For practice, supplier-buyer relationship management practices in India has been seen to be described by six important factors as information exchange flexibility, supplier integration flexibility, supply chain strategy flexibility, design adaptability flexibility, supplier flexibility, and supplier logistics flexibility.

In summary, a supplier-buyer relationship management practice is about making more efficient of all resources to explore procurement flexibility in between suppliers and manufacturers. When we conduct business, regardless of whether business is in manufacturing, service, or transport; the overall strategy of supplier-buyer relationship management practices is to increase procurement efficiency in manufacturing industries in India.

Precautions were taken in this research study to ensure respondents rated the questions based on their understanding of their positions and the firms where they work. The wording of the survey questions was carefully edited before and after the pre-test to ensure the questions would be salient and applicable to the participants and accepted by experts in the field of supply chain management. Despite these precautions, key limitations in the empirical study are present. These include the lack of correct/proper participant database, weakness associated with cross sectional surveys and constraints on the depth of information provided in survey methodology research and also knowledge of respondents. The determinants/ factors used in this research study are may not be sufficient enough to describe a broader term like supplier-buyer relationship management practices.

Future studies can take other factors affecting on competence and efficacy of supplier-buyer relationship management practices; those are not considered in this study. Future research in this area of supplier-buyer relationship management practices is promising not only for academicians in this area, but also for practitioners seeking to find competitive advantage in the management of supply chain management, operations management in increasingly challenging and competitive global business markets. Also, the future research can apply structural equation modeling for supplier-buyer relationship management practices to explore procurement flexibility, which is a technique to efficiently include a whole range of standard multivariate analysis and analysis of variance.

ACKNOWLEDGMENT

We are grateful to all the research scholars of Mechanical Engineering Department, Government College of Engineering Amravati for their insightful suggestions and also we are thankful to the anonymous reviewers for their valuable comments, which helped us to add value to this paper.

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