Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach

Ho, William; Bennett, David; Mak, KL; Chuah, Kong Bieng; Lee, C. K. M.; Hall, Matthew

doi:10.1016/j.eswa.2012.03.009

Cited by 160 publications

(97 citation statements)

References 14 publications

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“…AHP decomposes complex problems into separate small-size sub-problems in terms of different evaluation objectives such as cost optimization, timely delivery, and flexibility, among others. Each sub-problem is a single objective decision making problem that can be solved quite easily Ho, 2008;Ho et al, 2012;Subramanian and Ramanathan, 2012;Rajesha and Malligab, 2013). Furthermore, SCA is used to predict supply disruptions by supply chain mapping and enterprise social networking to identify the sources of supply uncertainties and manage ongoing collaborative relationship with suppliers (Souza, 2014).…”

Section: Logistics and Supply Chain Strategy Strategic Sourcingmentioning

confidence: 99%

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Wang

Gunasekaran

Ngai

et al. 2016

International Journal of Production Economics

1,108

750

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The amount of data produced and communicated over the Internet is significantly increasing, thereby creating challenges for the organizations that would like to reap the benefits from analyzing this massive influx of big data. This is because big data can provide unique insights into, inter alia, market trends, customer buying patterns, and maintenance cycles, as well as into ways of lowering costs and enabling more targeted business decisions. Realizing the importance of big data business analytics (BDBA), we review and classify the literature on the application of BDBA on logistics and supply chain management (LSCM) -that we define as supply chain analytics (SCA), based on the nature of analytics (descriptive, predictive, prescriptive) and the focus of the LSCM (strategy and operations). To assess the extent to which SCA is applied within LSCM, we propose a maturity framework of SCA, based on four capability levels, that is, functional, process-based, collaborative, agile SCA, and sustainable SCA. We highlight the role of SCA in LSCM and denote the use of methodologies and techniques to collect, disseminate, analyze, and use big data driven information. Furthermore, we stress the need for managers to understand BDBA and SCA as strategic assets that should be integrated across business activities to enable integrated enterprise business analytics. Finally, we outline the limitations of our study and future research directions.

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Section: Logistics and Supply Chain Strategy Strategic Sourcingmentioning

confidence: 99%

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Wang

Gunasekaran

Ngai

et al. 2016

International Journal of Production Economics

1,108

750

View full text Add to dashboard Cite

show abstract

“…It is critical to select a 3PLs provider, who is able to provide flexible, tailor-made solutions to meet their changing needs (Ho et al 2012). Adding services criteria to the 3PLs provider selection framework improves the selection quality.…”

Section: Max Services (Sr)mentioning

confidence: 99%

“…He determined compatibility, financial stability, flexibility, operational performance, quality management, and reputation as criteria. Ho et al (2012) proposed an integrated quality function deployment (QFD) and Fuzzy AHP for 3PLs provider selection in China. They used 6 criteria which are delivery, risk, technology, quality, cost, and flexibility.…”

Section: Pls Provider Selectionmentioning

confidence: 99%

Third-Party Logistics (3pls) Provider Selection via Fuzzy Ahp and Edas Integrated Model

Ecer

2017

Technological and Economic Development of Economy

141

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Abstract. In the global competitive environment, companies not only improve the quality of service and increase the efficiency, they also decrease the cost by means of third-party logistics (3PLs). 3PLs, therefore, is an important strategy for companies desiring to gain a competitive advantage and 3PLs provider selection plays a critical role for the success of outsourcing. Nevertheless, the level of uncertainty in the selection process is relatively high and need to be carefully considered. Hence, in order to select a proper 3PLs provider, integration of the Fuzzy AHP and Evaluation based on Distance from Average Solution (EDAS) has offered a novel integrated model, in which Fuzzy AHP is used for calculating priority weights of each criteria and EDAS is employed to achieve the final ranking of 3PLs providers. Besides, in order to demonstrate the applicability of the proposed model, it is validated by a case study. Cost together with quality, and professionalism are found to be the most important factors for 3PLs provider selection. Consequently, the advantage of this model is that it is simple to apprehend and easy to apply. The use of the proposed model leads to the selection of suitable alternative successfully in other selection problems.

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“…Fuzzy AHP elaborates the standard AHP method into a fuzzy approach by using fuzzy numbers instead of crisp values. Similar to the AHP, fuzzy AHP has also been applied to many different studies, such as supply chain planning, outsourcing, and site selection [34][35][36].…”

Section: Fuzzy Pairwise Comparison Methodsmentioning

confidence: 99%

Hesitant fuzzy pairwise comparison for software cost estimation: a case study in Turkey

Başar¹

2017

Turk J Elec Eng & Comp Sci

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Estimating the cost of software is a complex process for almost all engineering companies. Uncertainties about development method, design, estimation process, data, and processing affect the accuracy of estimation. Underestimation results in fewer resources being committed than the project really needs, an unrealistic schedule, and low quality outputs.On the other hand, overestimation wastes resources and causes loss of customer credit. Thus, choosing the appropriate cost estimation method is crucial. Studies in the literature emphasize the importance of empirical, analytical methods and expert judgement. Certain cost estimation techniques have been widely studied in the literature. However, there are limited studies using fuzzy approaches for software cost estimation. This paper presents a hesitant fuzzy pairwise comparison (HFPC) used in the hesitant fuzzy analytic hierarchy process for software cost estimation problems by using expert judgement. For this purpose, first a number of criteria are selected with the help of expert judgements from the Turkish banking sector and information technology industry. Subsequently, the HFPC method is presented to estimate the cost of software projects. In order to analyze the efficiency of the proposed approach, it is applied to a software cost estimation problem for a Turkish company. It is seen that the proposed method provides efficient estimations due to low deviation between the real effort and estimated cost. The results are also approved by experts working in the relevant software company.

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Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach

Cited by 160 publications

References 14 publications

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Third-Party Logistics (3pls) Provider Selection via Fuzzy Ahp and Edas Integrated Model

Hesitant fuzzy pairwise comparison for software cost estimation: a case study in Turkey

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