A new goal-directed benchmarking for supplier selection in the presence of undesirable outputs

Framework to precede collaboration in supply chain

Purpose

The purpose of this paper is to help supply chain (SC) decision makers successfully penetrate through SC collaboration and strengthen their SC in the global market by understanding collaborative activities, and understand how these activities are related to each other in the SC.

Design/methodology/approach

This paper develops a set of collaborative activities from literature, and the developed model is helpful for SC decision makers to monitor their SC activities and take corrective actions to improve collaboration in their SC by using interpretive structural modeling (ISM) and MICMAC analysis.

Findings

This study reveals that collaborative activities increase the value of whole SC. The various activities are modeled on the basis of “an activity influencing other activities” and “an activity influenced by other activities,” which is useful for SC managers to take a decision.

Research limitations/implications

The current study is literature based; therefore, there would be need of more explanation of the activities which lead to understand and implement SC collaboration in case of service and manufacturing industry.

Practical implications

The model of this study is helpful for decision makers to implement supply chain collaboration (SCC) and to understand various SCC activities on the basis of their driving and dependence power.

Originality/value

This research provided insight into skills needed for SC decision makers to implement collaboration in the SC using ISM. The results of the study could be adopted to monitor the existing SCC program or design new collaboration program to meet the global market requirements. To the best of knowledge, there is no reference that discusses SC collaborative activities on the basis of their driving and dependence powers.

Integrated dynamic vendor selection and order allocation problem for the time dependent and stochastic data

Purpose

In this paper, vendor selection and order allocation problem is considered for a buyer dealing in multiple products to be supplied by multiple vendors. Each product has an associated lead time with stochastic demand having stochastic capacity for each vendor across entire time period. Uncertainties related to costs which are further influenced by the periodically changing incremental quantity discounts offered by various vendors. The purpose of this paper is to find an optimal trade-off of vendor selection and order allocation in the presence of uncertainties involving multiple conflicting objectives such as cost minimization, service level/quality level maximization and delivery lead time minimization concurrently.

Design/methodology/approach

Vendor selection problem considered here has a multi-objective optimization design subject to a set of demand, capacity and quantity discount based constraints. These constraints as well as uncertainty related to lead time have been handled using chance constraint approach. The problem is titled as “integrated dynamic vendor selection problem (IDVSP).” The proposed multi-objective IDVSP is solved using both non-pre-emptive goal programming (GP) and weighted sum aggregate objective function (AOF) technique.

Findings

Findings indicate goal achievement for different objectives from both non-pre-emptive GP and AOF procedure. While the goals are satisfactorily achieved as per the target values for cost and lead time, quality/service level was somewhat compromised in order to find an appropriate trade off.

Originality/value

The research work is original as it integrates dynamic as well as stochastic (uncertain) nature of supply chain simultaneously coupled with the concept of incremental quantity discounts on lot sizes.

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.

Supply chain practices and performance: the indirect effects of supply chain integration

Purpose

– The purpose of this paper is to employ a newly developed framework to examine the complex relationship between different components of supply chain practices, supply chain integration (SCI) and supply chain performance (SCP) in the Malaysian electronics sector.

Design/methodology/approach

– This study utilizes survey data of 156 electronics firms in Malaysia and tested the research framework and hypotheses. In addition to the traditional approach of Barron and Kenny (1986), the Sobel test as well as a bootstrapping approach, which is deemed for small sample size, is used to formally test the indirect effects of SCI in the model.

Findings

– SCI has fully and partially mediated the relationship between supply chain management practices (SCMPs) and SCP. SCI fully mediates the relationship between SCP and three of the SCMPs, namely, information quality, agreed vision and goals and postponement strategies. The relationship of supply strategic partnership, customer relation management, information sharing with SCP were partially mediated by SCI. Risk and reward sharing is found to be non-significant. These insights allow managers to effectively utilize the different components of SCMPs for SCI and performance.

Practical implications

– For supply chain practitioners, the results of the study can be useful in integrating SCMPs and SCI on improving SCP. Practitioners should take into account the mediating effect of SCI in designing their supply chain management approach to production.

Originality/value

– To the authors’ best knowledge, this paper is one of the first to address the mediating effect of SCI between SCMPs and overall performance of the supply chain.