Managing uncertainty in logistics service supply chain

Choy, King Lun; Li, Chung‐Lun; So, Stuart; Lau, Henry C. W.; Kwok, S. K.; Leung, Dennis W.K.

doi:10.1504/ijram.2007.011408

Cited by 71 publications

(50 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Davis 1993;Mason-Jones and Towill 1998;Lee 2003;Ho, Chi, and Tai 2005;Choy et al 2007;Datta and Christopher 2011;Simangunsong, Hendry, and Stevenson 2012), uncertainty plays a critical role in decision making within industrial supply chains. It is driven by the availability of reliable information and knowledge when making an assessment of the future (Bernstein 1998).…”

Section: Uncertainty and Industrial Servicesmentioning

confidence: 99%

“…Other researchers have attempted to align supply chain strategies with uncertainties that exist in demand, supply, control systems and manufacturing processes (e.g. Lee 2003;Choy et al 2007). However, an analysis of the literature suggests limited studies on the uncertainties that characterise industrial service delivery or on the uncertainties that are experienced explicitly within the context of contracting strategies for industrial service delivery.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identifying uncertainties for industrial service delivery: a systems approach

Erkoyuncu

Durugbo

Roy

2013

International Journal of Production Research

View full text Add to dashboard Cite

Service delivery by industrial firms is increasingly seen as an influential factor for sustained profits. Across industry, this is typically achieved through long term contracts that aim to achieve performance, results, solutions, and so on. However, the increasing shift towards a service-oriented approach for production has created a number of challenges that originate from uncertainties that are experienced across supply networks.Along these lines, this research adopts a soft systems based approach to identify and categorise the uncertainties that are experienced particularly at the bidding stage of service contracts. These uncertainties significantly affect the cost and performance of service-oriented projects. This article presents the findings of a 3-year study with 22 aerospace experts from naval and defence industries that acted as key informants. It seeks to contribute to knowledge in research and industry by identifying and categorising uncertainties for industrial service delivery. Using the findings of the study, the article concludes by discussing implications and future challenges for academe and practice.

show abstract

Section: Uncertainty and Industrial Servicesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identifying uncertainties for industrial service delivery: a systems approach

Erkoyuncu

Durugbo

Roy

2013

International Journal of Production Research

View full text Add to dashboard Cite

show abstract

“…Tian Yu [1] put forward the general model of the logistics service supply chain, namely the integrated logistics service provider -an integrated logistics service provider -manufacturing, retail enterprise model, and the logistics service provider refers to the traditional functional logistics enterprises, such as transport enterprises, warehousing enterprises. After that, the Xiuxia et al [2], Cai Yunfei et al [3], Guo Mei et al [4], Zhang Dehai et al [5], Choy et al [6] studied this model in different ways. The theoretical system is being gradually improved, but quantitative research is relatively less.…”

Section: Introductionmentioning

confidence: 99%

Pricing Strategy of Logistics Service Supply Chain Considering Different Reciprocal Preference

Lü¹,

Qin²

2017

dtssehs

View full text Add to dashboard Cite

Abstract. This paper studies the influence of reciprocity preference on decision-making behaviour and supply chain benefits under different reciprocity preferences-chain members have independent preference and the integrator has liner preference. The Stackelberg game is used to analyze the influence of preference coefficient on supply chain decision and the outcome. It is found that there is a reasonable area of preference. When members have different independent preference, the supplier's service asking price decreases with her own preference, but increases with the integrator's preference, and the quality of service increases with integrator's preference at the reasonable area. The integrator's profits increases with preference of itself, utility increases with provider's preference. And the provider's utility increases with preference of integrator and provider. Besides, the influence of preference coefficient on supply chain decisions and results depends on the value of the reciprocal dependency coefficient.

show abstract

“…Taking the logistics service supply chain (LSSC) as an example, a logistics service integrator (LSI) integrates the service capacities of several functional logistics service providers (FLSPs) and offers customers with a variety of logistics services with integrated capacity (Choy et al 2007;Liu et al 2011). Generally, when an LSI receives logistics service orders from customers, it will allocate the orders to FLSPs, who will then fulfil the orders.…”

Section: Introductionmentioning

confidence: 99%

An order allocation model in multi-period logistics service supply chain based on cumulative prospect theory and capacity matching constraint

Liu

et al. 2014

International Journal of Production Research

View full text Add to dashboard Cite

By considering a two-echelon supply chain that consists of a logistics service integrator (LSI) and several functional logistics service provider (FLSP), this study builds a comprehensive subjective utility (CSU) function of FLSP in multiperiod based on cumulative prospect theory and establishes an order allocation model in multi-period logistics service supply chain. This model considers three goals: to minimise the cost of LSI, to maximise the satisfaction of the FLSP and to maximise the capacity matching degree among different logistics capacities. This study uses an improved technique for order performance by similarity to ideal solution to obtain the optimal solution. A numerical example is given by software MATLAB 7.8. The effects of the behavioural parameters of FLSPs on order allocation are also discussed. When the LSI allocates orders, the FLSP, who has larger ratio of loss to gain range by the sensitivity decreasing rate, should be selected to obtain a large value of CSU. No obvious rule is found for the influence of the loss aversion coefficient of FLSPs on the CSU of FLSPs in a multi-period.

show abstract

Managing uncertainty in logistics service supply chain

Cited by 71 publications

References 17 publications

Identifying uncertainties for industrial service delivery: a systems approach

Identifying uncertainties for industrial service delivery: a systems approach

Pricing Strategy of Logistics Service Supply Chain Considering Different Reciprocal Preference

An order allocation model in multi-period logistics service supply chain based on cumulative prospect theory and capacity matching constraint

Contact Info

Product

Resources

About