An analytic network process approach to the selection of logistics service providers for air cargo

Yang, Yanni; Hui, Yi; Leung, Lawrence C.; Chen, Gang

doi:10.1057/jors.2009.111

Cited by 29 publications

(23 citation statements)

References 29 publications

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“…The LSQ is defined as a set of performance factors, measured by the ability to distribute products in accordance with customer requirements (Yang et al, 2010). Various empirical studies have shown a relationship with company performance and CS, such as those of Mentzer et al (1999Mentzer et al ( , 2001), Panayides and So (2005) and Saura et al (2008).…”

Section: Lsq and Csmentioning

confidence: 99%

Logistic service quality as a mediator between logistics capabilities and customer satisfaction

Fernandes

Moori

Filho

2018

REGE

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Purpose A way that companies have found to respond to the challenges of customer satisfaction (CS) is the development logistics services quality. In this sense, the purpose of this paper is to estimate the quality of logistical service as a mediator factor in the relationship between logistics capabilities (LC) and CS. For this, an exploratory survey of the descriptive type was carried out with 117 companies in the Brazilian market of lubricant oil. The collected data, modeled in structural equations, have shown evidence that the quality of logistics services totally mediates the relation between the LC and the satisfaction of clients. Design/methodology/approach In order to respond to the research problem and to meet the stated objective, a study was carried out in two phases. The first used an exploratory qualitative design, and involved recorded in-depth interviews with five clients and five managers of a lubricant oil producer located in the municipality of Umuarama and nearby areas in Paraná state, Brazil. The second used an exploratory survey of the descriptive type was carried out with 117 companies in the Brazilian market of lubricant oil. Findings The collected data, modeled in structural equations, have shown evidence that the quality of logistics services totally mediates the relation between the LC and the satisfaction of clients. Research limitations/implications It is suggested that new studies be conducted in order to increase the size of the sample, since the number of responses obtained (117 respondents), for the number of initial variables (34 measures). Practical implications In the pursuit of CS, the managers of lubricant oil producers should make major investments in LC, to enable the company to be active in the search for logistics solutions, integration and provision of reliable information to its customers. Social implications The studies should also be carried out in other market segments, in order to compare the results obtained in the lubricating oil segment of Brazil and corroborate knowledge about the influence of logistical capabilities on the relation between logistics service quality and CS. Originality/value The logistics services quality perceived by the customers is derived from the service capacity of the producer’s employees and the quality of information provided to the customers.

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Section: Lsq and Csmentioning

confidence: 99%

Logistic service quality as a mediator between logistics capabilities and customer satisfaction

Fernandes

Moori

Filho

2018

REGE

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“…These have included Analytic Hierarchy Process (AHP)/Analytic Network Process (ANP) (Sarkis 2003), ANP (Yang et al 2010), Artificial Neural Network (ANN) (Kuo et al 2010a), Interpretive Structural Modelling (Kannan and Haq 2007), grey system and rough sets Sarkis 2010a, 2010b), DEA ) and multiobjective mixed-integer programming (Abdallah et al 2012). Whilst fuzzy logic has been applied by Erol et al (2011) has been a tendency for researchers to initiate their partner selection criteria without a systematic way to identify, group and filter the potential criteria .…”

Section: Literature Reviewmentioning

confidence: 99%

“…This comprises the three-level hierarchy criteria, shown in Table 1. (Noci 1997, Melnyk et al 2003, Matos and Hall 2007, Kuo et al 2010a Pollution control (Sroufe 2003, Awasthi et al 2010, Tsai 2012 Operations and financial capability (Sha and Che 2006, Luo et al 2009, Burke et al 2009, Yang et al 2010 Partnership and technology management (Amaral and Tsay 2009, Sosic 2011, Cui et al 2012 Low level See Table 2 to Table 7 for more details.…”

Section: Gsc Partner Selection General Hierarchy Criteria Constructionmentioning

confidence: 99%

“…To achieve their main objective, GSCs need capabilities to provide quality product/service (Zhu and Sarkis 2004). This also calls for the ability to meet a high level of production volume flexibility, delivery reliability and capacity and variation in types of products or services (Sha and Che 2006, Yang et al 2010, Cui et al 2012). In addition, order lead time and order fulfilment rate are also very important attributes when evaluating the flexibility of potential partners (Chung et al 2005, Burke et al 2009).…”

Section: ) Operations and Financial Capability 6) Partnership And Tementioning

confidence: 99%

“…The ability of a potential partner to manage technology and knowledge is one of the key attributes in a GSC partner. Thus technical capability, technical advice, technology innovation and knowledge of local business practices are used as indicators of a potential supplier's performance (Hajidimitriou and Georgiou 2002, Yang et al 2010, Cui et al 2012. In regard to technology management, a partner's equipment status, their product familiarity, and repair turnaround time are basic criteria against which potential partners should be evaluated (Xia and Wu 2007, Amaral and Tsay 2009, Cui et al 2012.…”

Section: ) Operations and Financial Capability 6) Partnership And Tementioning

confidence: 99%

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Partner selection in green supply chains using PSO – a practical approach

Barnes

2016

Production Planning & Control

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Partner selection is crucial to green supply chain management as the focal firm is responsible for the environmental performance of the whole supply chain. The construction of appropriate selection criteria is an essential, but often neglected prerequisite in the partner selection process. This paper proposes a three-stage model that combines Dempster-Shafer belief acceptability theory and particle swarm optimization technique for the first time in this application. This enables optimization of both effectiveness, in its consideration of the inter-dependence of a broad range of quantitative and qualitative selection criteria, and efficiency in its use of scarce resources during the criteria construction process to be achieved simultaneously. This also enables both operational and strategic attributes can be selected at different levels of hierarchy criteria in different decision-making environments. The practical efficacy of the model is demonstrated by an application in Company ABC, a large Chinese electronic equipment and instrument manufacturer.

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Supplier Evaluation Using Fuzzy Clustering

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An analytic network process approach to the selection of logistics service providers for air cargo

Cited by 29 publications

References 29 publications

Logistic service quality as a mediator between logistics capabilities and customer satisfaction

Logistic service quality as a mediator between logistics capabilities and customer satisfaction

Partner selection in green supply chains using PSO – a practical approach

Supplier Evaluation Using Fuzzy Clustering

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