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Article

Manoj Hudnurkar and Suhas Suresh Ambekar

The purpose of this paper is to design, develop, implement and validate a multi-criteria decision model for measuring supplier satisfaction through a case study.

Abstract

Purpose

The purpose of this paper is to design, develop, implement and validate a multi-criteria decision model for measuring supplier satisfaction through a case study.

Design/methodology/approach

A three-stage methodology was used to develop a framework to measure supplier satisfaction. The framework involved factors and Key Performance Indicators (KPIs) from literature and exploratory study. Further, using the framework, a multi-dimensional decision model to calculate Supplier Satisfaction Index was developed. The proposed decision framework was implemented as a real-world case study in an Indian manufacturing organization.

Findings

The study makes two major contributions: first, it develops a framework to measure supplier satisfaction using factors and KPIs suitable to the buyer organization; second, the model developed to calculate supplier satisfaction helps in understanding overall satisfaction of suppliers along with the level of satisfaction of each supplier. The model can also be used to suggest improvements to buyer organizations on specific factors and KPIs under each factor.

Research limitations/implications

Supplier satisfaction plays an important role in multinational companies (MNCs), so the sample of practitioners considered in this study is relevant. However, it is likely that the small sample size of only suppliers and companies selected solely from the Indian manufacturing MNCs may have introduced some bias.

Practical implications

A comprehensive framework for enhancing the relationship with suppliers will be instrumental in deciding, managing and improving the level of supplier satisfaction.

Originality/value

This approach provides purchase managers with the flexibility of selecting factors and KPIs at every level of analysis and also a single index to establish supplier’s satisfaction with a buyer company.

Details

International Journal of Productivity and Performance Management, vol. 68 no. 8
Type: Research Article
ISSN: 1741-0401

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Article

P.L. Meena and S.P. Sarmah

The purpose of this study is to develop a scale and model to measure suppliers' satisfaction index (SSI) in buyer‐suppliers relationships.

Abstract

Purpose

The purpose of this study is to develop a scale and model to measure suppliers' satisfaction index (SSI) in buyer‐suppliers relationships.

Design/methodology/approach

Based on the literature review and opinion of the suppliers, this paper first explores the factors that influence suppliers' satisfaction (SS). Subsequently a questionnaire is designed based on these factors and survey was conducted among 300 suppliers' organizations. Partial least square (PLS) approach is used to validate the model and investigate the relationships of factors or constructs with SS. Finally, the authors compute the extent of SSI using analytical hierarchy process (AHP).

Findings

The results indicate that purchase policy, payment policy, coordination policy and corporate image of the buying firm have positive impact on SS. The purchase policy and corporate image have strong impact on SS compared to other factors. The computed value of SSI in this study is 65.25 on the scale of 1‐100.

Research limitations/implications

The data used in this study are collected only from the suppliers of an Indian PSU. The proposed method can also be used by other industries for measuring the value of SS. In the future, one can carry out a study by measuring the satisfaction of both parties simultaneously. Moreover, generalizability of the findings to other industries or other countries is open to scrutiny.

Originality/value

This paper develops a new scale to measure SS and explores the relationships of different factors with SS and among each other. Finally, a method is proposed to compute the current level of SSI.

Details

Industrial Management & Data Systems, vol. 112 no. 8
Type: Research Article
ISSN: 0263-5577

Keywords

Content available
Article

Chunguang Bai and Ahmet Satir

There is great uncertainty and volatility in the evaluation and measurement of green supplier satisfaction. The purpose of this paper is to fill this gap based on the…

Abstract

Purpose

There is great uncertainty and volatility in the evaluation and measurement of green supplier satisfaction. The purpose of this paper is to fill this gap based on the information entropy theory (IET) to describe the probability of green supplier satisfaction degree.

Design/methodology/approach

The authors introduce a formal model using analytic hierarchy process (AHP), IET and entropy technique for order preference by similarity to an ideal solution (TOPSIS) method to evaluate green supplier satisfaction and promote them for the better implementation of green supply chain management practices.

Findings

The first finding is developing an effective framework for green supplier satisfaction, incorporating various measures of environmental dimension. Second, a hybrid uncertainty decision method is introduced, by integrating AHP and IET and entropy-TOPSIS.

Research limitations/implications

One of the main limitations of the research is that the authors introduced a conceptual example. Real-world applications need to investigate the accuracy and effectiveness of these measures, and the operational feasibility of this method.

Originality/value

This is one of the first works to provide a comprehensive appraisal model for evaluation of green supplier satisfaction. This study and research method can form general guidelines, and organizations can increasingly benefit from using green supplier satisfaction evaluation as a management tool. Green supplier satisfaction evaluation is just the beginning.

Details

Modern Supply Chain Research and Applications, vol. 2 no. 2
Type: Research Article
ISSN: 2631-3871

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Article

Lisa Hüttinger, Holger Schiele and Dennis Schröer

This paper aims to understand the factors that influence a supplier’s choice to treat selected customers more preferentially than others. Suppliers often lack the…

Abstract

Purpose

This paper aims to understand the factors that influence a supplier’s choice to treat selected customers more preferentially than others. Suppliers often lack the resources to treat all their customers equally, instead having to make choices to treat some customers as preferred. Empirical evidence indicates that preferential treatment by suppliers provides substantial benefits for the purchasing firm.

Design/methodology/approach

This study applies a mixed-methods approach. First, a qualitative analysis of a sample of buyers from an automotive manufacturer was conducted. In the second step, the findings were triangulated via a quantitative survey among key account managers of the automotive firm’s suppliers.

Findings

This paper is the first to provide quantitative data collected from a large sample of automotive suppliers about the drivers of preferential customer treatment. The authors were able to show that the growth opportunities for suppliers and customers’ operative excellence, reliability and relational behavior are factors that induce suppliers to award preferential customer treatment. In contrast, innovation potential for suppliers, customers’ support of suppliers, supplier involvement and contact accessibility do not show a significant effect on suppliers’ behavioral intentions toward preferential customer treatment.

Originality/value

The mixed-methods approach is introduced as a form of academic enquiry in supply chain management. The factors influencing preferential customer treatment by suppliers are explored in discussions with purchasers and validated in a subsequent survey among suppliers. Recommendations for managerial practice and theory are drawn.

Details

Supply Chain Management: An International Journal, vol. 19 no. 5/6
Type: Research Article
ISSN: 1359-8546

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Article

Nada Saleh Badawi and Moustafa Battor

The purpose of this paper is to investigate the influence of social capital and relationship quality on key account management (KAM) effectiveness.

Abstract

Purpose

The purpose of this paper is to investigate the influence of social capital and relationship quality on key account management (KAM) effectiveness.

Design/methodology/approach

Based on the literature, the authors designed a framework that links social capital, relationship quality and KAM effectiveness. Data were collected through a self-administered questionnaire. Using data from a sample of 172 business-to-business supplier firms, the authors examined this model.

Findings

The research results provide empirical support to the importance of relational aspects of KAM by showing how the relational aspects of relationship quality and social capital influence the effectiveness of the supplier-key account relationship.

Originality/value

The authors add to the literature on relational KAM by integrating theoretical perspectives on social capital, relationship quality and KAM. They develop a model that investigates the antecedents of the effectiveness of supplier–key account relationships from a relational perspective. The study explains the relationships between six constructs representing social capital (ability, benevolence, integrity, flexibility, information exchange and solidarity) and three constructs representing relationship quality (trust, satisfaction and relationship atmosphere), together with the relationships between these three constructs of relationship quality and KAM effectiveness.

Details

Journal of Business & Industrial Marketing, vol. 35 no. 1
Type: Research Article
ISSN: 0885-8624

Keywords

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Article

Andrew Lee‐Mortimer

Especially in a recession, organisations should try and support one another by developing supplier partnerships to help reduce both costs and risks. Some companies have…

Abstract

Especially in a recession, organisations should try and support one another by developing supplier partnerships to help reduce both costs and risks. Some companies have already initiated such programmes and uncovered some impressive results.

Details

The TQM Magazine, vol. 5 no. 1
Type: Research Article
ISSN: 0954-478X

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Article

Ip‐Shing Fan, Steve Russell and Richard Lunn

With the high level of outsourcing in aerospace engineering and manufacture, the effective use of knowledge across the supply chain is acknowledged to be crucial to the…

Abstract

With the high level of outsourcing in aerospace engineering and manufacture, the effective use of knowledge across the supply chain is acknowledged to be crucial to the success of any projects. “Knowledge”, however, may have different meanings and context. Presents a view of the supplier knowledge in relation to the product engineering process. The different types of supplier knowledge in the five key stages of the aerospace product development process are explained. An existing joint supplier improvement information system is used to illustrate best practice in supply‐base management. Tools that could be used in the different modes of supplier involvement are briefly introduced. Represents part of the results of three industrial research projects that interacted with the supply bases of two large British aerospace companies.

Details

Aircraft Engineering and Aerospace Technology, vol. 72 no. 1
Type: Research Article
ISSN: 0002-2667

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Article

Srikanta Routroy and Sudeep Kumar Pradhan

The first objective of this paper is to identify the critical success factors (CSFs) and their corresponding key performance indicators (KPIs) for supplier development…

Abstract

Purpose

The first objective of this paper is to identify the critical success factors (CSFs) and their corresponding key performance indicators (KPIs) for supplier development (SD) in a manufacturing environment. The second objective is to develop a methodology to analyze and evaluate the performance for SD using CSFs and their KPIs over the time.

Design/methodology/approach

In all, 13 CSFs and their corresponding KPIs for SD are established through an extensive literature review, discussion held with managers/engineers in different Indian manufacturing companies and conducting brainstorming sessions. A methodology is proposed using analytic hierarchy process (AHP) and performance value analysis to assess and evaluate the performance of SD over the time.

Findings

From an extensive analysis of the results, under the given circumstances, the growth of SD performance is positive at different progressive points along the time horizon.

Research limitations/implications

This study has not been statistically validated in manufacturing supply chain for complete acceptability.

Practical implications

This study provides insights into the performance evaluation of SD using CSFs and their corresponding KPIs. The managers should capture their manufacturing environment which can reflect their own priority considerations to establish the impact of each KPI on its corresponding CSF.

Originality/value

Although many issues related to SD have been widely researched individually, few studies have been reported with a model to quantify, monitor, analyze, and evaluate the growth of SD performance in manufacturing environment in Indian context. The proposed model has the ability to capture the performance along KPIs and CSFs to draw fruitful conclusions regarding the success of the SD programme.

Details

International Journal of Productivity and Performance Management, vol. 63 no. 2
Type: Research Article
ISSN: 1741-0401

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Article

Manoj Hudnurkar and Urvashi Rathod

The aim of this research was to study collaborative practices with suppliers in multinational manufacturing companies operating in India and to develop a framework for…

Abstract

Purpose

The aim of this research was to study collaborative practices with suppliers in multinational manufacturing companies operating in India and to develop a framework for collaboration with suppliers.

Design/methodology/approach

This study adopted a four-step mixed-methods approach that included qualitative and quantitative methods. Qualitative technique was used to explore the factors and develop a balanced scorecard-based (BSC – balanced scorecard) framework using them. Quantitative technique was used to validate the framework statistically and also by using fuzzy analytical hierarchy process using perception-based ranks given by practitioners.

Findings

The exploratory research resulted in 26 antecedents for collaboration with suppliers in supply chains. Out of these 26, only 19 were considered based on importance given by practitioners. Further, the identified antecedents were classified and mapped based on the perspectives of the BSC. The extended BSC adds business environment and partnership perspectives to existing BSC framework. Some of the important factors identified under these perspectives were transparency of transactions, long-term commitment and trust. The customer perspective was given the utmost importance by the practitioners.

Research limitations/implications

There are certain issues that may limit the completeness of the work in a global context. The number of organizations (21) and respondents (45) may also be insufficient to convey the complete knowledge embedded in the practice of the field.

Originality/value

The study provides practical insights about the factors affecting collaboration with suppliers. A BSC-based framework for collaboration with suppliers was also developed along with the associated importance of each perspective and factors under each perspective, which can prove to be of great value to academics and practitioners involved in relationship with suppliers in supply chain.

Details

Journal of Global Operations and Strategic Sourcing, vol. 10 no. 2
Type: Research Article
ISSN: 2398-5364

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Article

Wynne Chin, Jun-Hwa Cheah, Yide Liu, Hiram Ting, Xin-Jean Lim and Tat Huei Cham

Partial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent…

Abstract

Purpose

Partial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent variables as measured by manifest variables. However, while researchers using PLS-SEM routinely stress the causal-predictive nature of their analyses, the model evaluation assessment relies exclusively on criteria designed to assess the path model's explanatory power. To take full advantage of the purpose of causal prediction in PLS-SEM, it is imperative for researchers to comprehend the efficacy of various quality criteria, such as traditional PLS-SEM criteria, model fit, PLSpredict, cross-validated predictive ability test (CVPAT) and model selection criteria.

Design/methodology/approach

A systematic review was conducted to understand empirical studies employing the use of the causal prediction criteria available for PLS-SEM in the database of Industrial Management and Data Systems (IMDS) and Management Information Systems Quarterly (MISQ). Furthermore, this study discusses the details of each of the procedures for the causal prediction criteria available for PLS-SEM, as well as how these criteria should be interpreted. While the focus of the paper is on demystifying the role of causal prediction modeling in PLS-SEM, the overarching aim is to compare the performance of different quality criteria and to select the appropriate causal-predictive model from a cohort of competing models in the IS field.

Findings

The study found that the traditional PLS-SEM criteria (goodness of fit (GoF) by Tenenhaus, R2 and Q2) and model fit have difficulty determining the appropriate causal-predictive model. In contrast, PLSpredict, CVPAT and model selection criteria (i.e. Bayesian information criterion (BIC), BIC weight, Geweke–Meese criterion (GM), GM weight, HQ and HQC) were found to outperform the traditional criteria in determining the appropriate causal-predictive model, because these criteria provided both in-sample and out-of-sample predictions in PLS-SEM.

Originality/value

This research substantiates the use of the PLSpredict, CVPAT and the model selection criteria (i.e. BIC, BIC weight, GM, GM weight, HQ and HQC). It provides IS researchers and practitioners with the knowledge they need to properly assess, report on and interpret PLS-SEM results when the goal is only causal prediction, thereby contributing to safeguarding the goal of using PLS-SEM in IS studies.

Details

Industrial Management & Data Systems, vol. 120 no. 12
Type: Research Article
ISSN: 0263-5577

Keywords

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