Multi-criteria supplier selection model using the analytic hierarchy process approach

Seven-waste framework of waste identification and elimination for computer-based administrative work

Purpose

This paper tries to generalize business process improvement (BPI) methodology. It utilizes the seven-waste framework as an essential step in the methodology. While the seven-waste concept is usually applied for manufacturing activities, this paper tries to explore the applicability of it to office-work activities. Also, this paper demonstrates that information technology can be used as a tool for reducing waste in the office-work.

Design/methodology/approach

A comprehensive literature review of BPI methodology studies was conducted in order to propose systematic flowcharts to represent the sequence of processes involved in each step of BPI methodology. The proposed flowcharts are applied to a case study in supply chain planning and allocation planning at a manufacturing company. The seven-waste framework is designed as part of the step, in which equivalency between the definition of waste found on the production floor and waste found in office work is presented.

Findings

The BPI methodology generally follows five steps: initialization, selection, design, implementation and evaluation. The seven-waste framework is effectively applied in the selection step. The case study shows that information technology can be used as a tool in business process improvement to reduce waste in the business process.

Practical implications

The case study indicates that the proposed framework and methodology are proven able to reduce the three key performance indicators. They are the number of steps from 54 to 24 (55% reduction), processing time from 890 min to 313.5 min (64% reduction) and the number of the manual process from 41 to 17 (59% reduction).

Originality/value

This paper proposes a generalization of BPI methodology, the seven-waste framework in the selection step of the BPI methodology, the seven-waste concept in office-work activity and the use of information technology for BPI by reducing waste in office-work activity.

Analysis of demand risks for the Indian automotive sector in globally competitive environment

Purpose

The purpose of this study is to understand the different types of risks affecting the demand for the automotive sector in India. The study is further trying to illustrate an approach for analyzing the relative intensities of these risks in the present uncertain business environment.

Design/methodology/approach

Risk on the overall demand is assessed by a combined Bayesian – multi-criteria decision-making approach. Data related to the different factors, affecting their product demand is collected from major automobile firms. Then, weights for these factors are evaluated by applying the analytic hierarchy process approach. Further, these weights are used in the Bayesian analysis network to evaluate the risk intensity for different subgroups, namely, political, economic, social, technological and environmental.

Findings

From the literature and experts’ opinion, total 16 risk factors have been finalized and these are further grouped into 5 categories i.e. political, economic, social, technological and environmental. It is observed that the demand for organizations functioning in the automotive sector is more vulnerable to economic risk as compared to other risks considered in the study.

Practical implications

Managers and decision makers of associated organizations can use the proposed framework to assess the demand risks so as to pre-evaluate their demand corresponding to future changes. Factors can be added or removed and importance could be assigned to different risk factors according to the prevailing business environment for an organization or sector. This will also help the organizations to conduct a more effective risk management in an uncertain business environment.

Originality/value

The study will help in better understanding of the various demand risks prevalent in the Indian auto sector. The methodology used, provides a novel approach for assessing the macroeconomic demand risks and can be used by the firms working in the automotive sector. The proposed methodology could be used for assessing supply chain risk or any other business initiative risk. The suggested approach will help managers in devising flexible management techniques so as to mitigate the risk.

Investigating interdependencies of sustainable supplier selection criteria: an appraisal using ISM

Purpose

Because of the increased global competition and the need for environment consciousness, organisations have started focusing on incorporating sustainability dimensions into suppler selection criteria. In the past decade, sustainable supplier selection has received much attention from researchers as well as industry practitioners. The purpose of this paper is to identify various sustainable supplier selection criteria (SSSC) and underlying interdependencies among prominent selection criteria to develop a framework for sustainability dimensions.

Design/methodology/approach

The sustainable criteria for supplier selection were established through comprehensive literature review. An interpretive structural modelling (ISM) approach is used to investigate the interrelationships among these criteria.

Findings

A total of 21 SSSC under 3 dimensions (social, environmental and economic) are established. Ten criteria related to quality, capability, flexibility, waste management, pollution prevention, local community, employment practice, labour, etc. are exhibiting strong driving as well as dependence power, as demonstrated through ISM and matriced’ impacts croises-multiplication applique’ and classement (MICMAC) analysis. The findings show that delivery/service, eco design and rights of stakeholders are the “key” criteria having a high-driving and low-dependence power. These criteria require high attention from managers, while other criteria having low-driving and high-dependence power require secondary actions.

Research limitations/implications

The inter-relations for the development of ISM model and MICMAC analysis were obtained through the opinion of industry experts and academicians, which may tend to be subjectively biased. Further exploration is proposed to statistically validate the developed interdependency model.

Practical implications

This paper might act as a reference for the supplier development managers of organisations by providing an appraisal of various SSSC based on their interdependencies.

Originality/value

This study contributes to the knowledge base by proposing a framework of the interrelationships of the SSSC and also provides an additional perspective for managing these criteria based on ISM.

Municipal solid waste management considering NGO’s role in consumer environmental awareness and government regulations for air pollution

Purpose

The purpose of this study is twofold: first, to examine the role of non-governmental organizations (NGOs) in increasing customer environmental awareness (CEA) to decrease the municipal solid waste (MSW), and secondly, to examine the effect of government policies in the amount of air pollution caused by transfer stations (TSs).

Design/methodology/approach

This study proposes a mixed-integer nonlinear programming model. For solving this multi-objective problem, the authors use epsilon constraint method, which presented eight Pareto solutions. For selecting the best solution, the analytic hierarchy process approach is used. The presented model is applied on a real case study, and the results are discussed and sensitivity analysis is implemented on the parameters of the concern.

Findings

This study confirms the assumption that by allocating budget to NGOs for increasing CEA, the produced waste will be decreased.

Research limitations/implications

In the present study, the authors only investigate air pollution caused by TS. Future studies can investigate other types of pollution. Furthermore, uncertainty in the amount of produced waste can be variable making the problem closer to the real environment. In this case, robust optimization may have better results.

Practical implications

Based on the results of sensitivity analysis, some implications obtain that can highlight by managers in the decision-making process. The operational costs of TS have a critical aspect in founding TS, so using new technology and high-tech machines for operational processes of TSs, can result in decreasing the running cost of TSs. Also, the determination of TS capacity is a remarkable issue in optimization, which should be paid special attention to this for the design of TSs in the planning phase of the system. Moreover, collaborating with NGOs has a good effect on increasing CEA that results in a decrease of MSW.

Originality/value

The role of NGOs and government simultaneity has been considered in a green supply chain. Moreover, the authors considered TS between source and disposal that reduce the time of transferring waste. Therefore, this study can be beneficial for the MSW management system, which faces the problems in the lack of capacity and transportation problems and environmental issues by proposing solutions in three studies including economic, environmental and social aspects.

A new weighted fuzzy programming model for supplier selection and order allocation in the food industry

Purpose

The purpose of this paper is to develop a combined intuitionistic fuzzy analytic hierarchy process (IFAHP) and fuzzy multi-objective optimization approach to select suppliers and allocate the orders to them in the bottled water production context.

Design/methodology/approach

First, the primary weights of criteria associated with the supplier selection problem are calculated using the IFAHP technique. Then a fuzzy multi-objective optimization model is developed to allocate the appropriate amount of orders to each supplier.

Findings

The proposed methodology has been successfully implemented in the case of an Iranian food company in its bottled water factory. Results demonstrate our model is capable of practically handling the uncertainty in DMs’ preference that leads to effective and efficient supplier selection and order allocation decisions.

Originality/value

The authors develop a novel hybrid decision-making tool to tackle the uncertainty in decision-makers’ opinions with a demonstrated applicability and some promising outcomes in efficiently allocating the order quantity to suppliers in the area of bottled water production.

Dynamic supplier selection approach for mining equipment company

Purpose

This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.

Design/methodology/approach

An integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.

Findings

The ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.

Practical implications

This paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.

Originality/value

It provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.

Intelligent evaluation of suppliers using extent fuzzy TOPSIS method

Purpose

In a developing economy like India, the contribution of small- and medium-sized enterprises (SMEs) to the national gross domestic product is significant. This sector creates immense employment opportunities and produces economic products and services. To survive in the globalized marked condition, it is essential for SMEs to be competitive on several fronts such as quality, cost, delivery, lead time, flexibility, etc. Hence, it is imperative for them to have a sound supplier base. Therefore, supplier selection problem (SSP) has a vital role to play in supply chain management of SMEs. The paper aims to discuss these issues.

Design/methodology/approach

However, SSP has now become a significant challenge to address due to the complexity, vagueness and various criteria involved in it. Recently, fuzzy Technique for Order Performance by Similarity to Ideal Solution method has been widely used to tackle such problems.

Findings

The present paper aims at developing an intelligent system for SSP, which can consider the multiple criteria and the uncertainty aspects in the decision process. A case study of a small-scale manufacturing company has been presented.

Practical implications

This study provides a guideline for SME sector to implement intelligent systems for supplier selection decision-making problems. Case application concludes that this model improves firm’s decision making and suppliers’ performance.

Originality/value

The proposed intelligent model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment. And it also provides an opportunity for supplier improvement.

Supplier selection for a sustainable supply chain

Purpose

The purpose of this paper is to integrate the “triple bottom line (3BL)” approach in the supplier selection decision. It also aims to consider the feedback effect of the decision on strategic factors that determine the future viability of the firm in the market.

Design/methodology/approach

A multi-criteria decision model is developed that considers simultaneously the impact of three dimensions of 3BL approach and their sub-dimensions on the supplier selection decision. The proposed model is evaluated for a large white goods manufacturer using the analytic network process (ANP) approach.

Findings

The ANP considers the impact of variables, sub-variables, and their interdependencies simultaneously. The outcome of the model is the relative priorities for the firms considered as potential suppliers.

Practical implications

This research was conducted in one of the largest developing economies. The impact of integrating sustainability would be widespread due to the huge market in which the company operates. The results of this research can provide support to the decision makers in arriving at an optimal decision considering all sustainability dimensions.

Originality/value

The novelty of the approach lies in the application of multi-criteria model integrating sustainability dimensions with a feedback effect for supplier selection. The case company would benefit by showing its commitment toward environment and social responsibility leading to improved brand image and sustainable business.

Measuring the supply chain risk in offshoring countries using data envelopment analysis and the analytic hierarchy process

Purpose

An indiscreet strategy of offshoring from low-cost countries (LCCs) can do more harm than good, since invisible supply chain risks may increase hidden costs and subsequently more than offset cost-saving opportunities. Considering the potential impact of these risks on offshoring, the purpose of this paper is to identify risk factors that significantly hinder the efficiency of offshoring and then measure specific risks associated with offshoring in foreign countries.

Design/methodology/approach

This paper develops performance metrics for gauging the offshoring attractiveness of potential sourcing countries using data envelopment analysis and then identifies the benchmark sourcing country using the analytic hierarchy process (AHP).

Findings

This study reveals that, defying the conventional wisdom, LCCs are not necessarily the most desirable offshoring destinations. This study also discovers that LCCs tend to be less business friendly, less logistically efficient, and riskier to source than their high-income country counterparts.

Originality/value

This paper is one of the first to introduce the concept of wealth creation efficiency for an offshoring decision and consider a host of key determinants such as wealth creation efficiency, logistics efficiency, business friendliness, and various supply chain risks for selecting the most desirable offshoring destination.

Embedding risk in closed-loop supply chain network design

Purpose

The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and logistics operations. The modeling approach adopted aims at the embedding supply chain risks in a closed-loop supply chain (CLSC) network design process and suggests optimal supply chain configuration and risk mitigation strategies.

Design/methodology/approach

The method proposes a closed-loop supply chain network and identifies the network parameter and variables required for closing the loop. Mixed-integer-linear-programming-based mathematical modeling approach is used to formulate the research problem. The solutions and test results are obtained from CPLEX solver.

Findings

The outcomes of the proposed model were demonstrated through a case study conducted in an Indian hospital furniture manufacturing firm. The modern supply chain is mapped to make it closed loop, and potential risks in its supply chain are identified. The supply chain network of the firm is redesigned through embedding risk in the modeling process. It was found that companies can be in great profit if they follow closed-loop practices and simultaneously keep a check on risks as well. The cost of making the supply chain risk averse was found to be insignificant.

Practical implications

Although the study was conducted in a practical case situation, the obtained results are not indiscriminate to the other circumstances. However, the approach followed and proposed methodology can be applied to many industries once a firm decides to redesign its supply chain for closing its loop or model under risks.

Originality/value

By using the identified CLSC parameters and applying the proposed network design methodology, a firm can design/redesign their supply chain network to counter the risk and accordingly come up with planned mitigation strategies to achieve a certain degree of robustness.

A fuzzy goal programming approach for selecting sustainable suppliers

Purpose

Due to the ever increasing concern toward sustainability, suppliers nowadays are evaluated on the basis of environmental performances. The data on supplier’s performance are not always available in quantitative form and evaluating supplier on the basis of qualitative data is a challenging task. The purpose of this paper is to develop a framework for the selection of suppliers by evaluating them on the basis of both quantitative and qualitative data.

Design/methodology/approach

Literature on sustainability, green supply chain and lean practices related to supplier selection is critically reviewed. Based on this, a two phase fuzzy goal programming approach integrating hyperbolic membership function is proposed to solve the complex supplier selection problem.

Findings

Results obtained through the proposed approach are compared to the traditional models (Jadidi et al., 2014; Ozkok and Tiryaki, 2011; Zimmermann, 1978) of supplier selection and were found to be optimal as it achieves higher aspiration level.

Practical implications

The proposed model is adaptive to solve real world problems of supplier selection as all criteria do not possess the same weights, so the managers can change the criteria and their weights according to their requirement.

Originality/value

This paper provides the decision makers a robust framework to evaluate and select sustainable supplier based on both quantitative and qualitative data. The results obtained through the proposed model achieve greater satisfaction level as compared to those achieved by traditional methods.