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Decision support model for hub localisation - A study at a company in the 3PL industry

Josefsson, Sara LU and Medin, Andreas LU (2012) MTT820 20121
Engineering Logistics
Abstract
Background:
With todays’ requirement of shorter product life cycles and faster time-to-market, producing companies experience an increased demand for faster transports in the supply chain. This puts pressure on freight forwarders to offer their customers a timely and reliable transport service at a reasonable price. Another challenge for the freight forwarders in Sweden is to provide such services in all parts of the country. Therefore, the actors in the 3PL industry must find an appropriate design for their transportation network which can enable these transports. This pressure is felt by Company X, which is the Swedish division of one of the largest freight forwarders of road transports in Europe. The network is operated by hauliers and... (More)
Background:
With todays’ requirement of shorter product life cycles and faster time-to-market, producing companies experience an increased demand for faster transports in the supply chain. This puts pressure on freight forwarders to offer their customers a timely and reliable transport service at a reasonable price. Another challenge for the freight forwarders in Sweden is to provide such services in all parts of the country. Therefore, the actors in the 3PL industry must find an appropriate design for their transportation network which can enable these transports. This pressure is felt by Company X, which is the Swedish division of one of the largest freight forwarders of road transports in Europe. The network is operated by hauliers and contains of 25 terminals where some of them also function as hubs, which consolidate goods in order to increase the utilization of transports. Company X are now facing problems in meeting the scheduled delivery time for deliveries to northern Sweden. Since Company X strives for meeting its customers’ expectations it is wishful to develop a model based on a set of factors, which can evaluate the localisation of a hub and be a support for future decisions. Moreover, there has not been an evaluation of the main hub and its connected lines in the transportation network for many years. An analysis of the current network according to the model will therefore be conducted to identify the optimal hub localisation.

Purpose:
The purpose of this master thesis consists of two parts; first, to develop a model, which can evaluate the localisation of a hub, and second, to perform an analysis of the current hub location to find an optimal one according to the model.
Research questions:
The master thesis will answer the following questions to achieve the purpose:
- Which factors have to be taken into consideration by Company X when deciding where to locate a hub?
- How should the alternative hub localisations be identified and evaluated to arrive at a decision support for an optimal hub localisation?
- What is the optimal hub localisation for the chosen lines according to the developed model and how reliable is the result?

Method:
The thesis is based on a systems approach since synergy effects are expected to arise between the factors in the constructed model. The development of the model is considered to be an exploratory and a normative study while the second part of the purpose will be an explanatory study. Both qualitative and quantitative data will be used in order to develop the model and to perform the analysis. The model is validated according to four steps to ensure the validity, reliability and objectivity. The validity of the analysis is investigated through performed sensitivity analyses.

Conclusions:
A number of factors affecting facility localisation were found in the literature and these were analysed to identify factors affecting the hub localisation for Company X. The following 16 factors were finally recognised to be considered when deciding where to locate a hub for Company X; highway access, labour availability, delivery time to customers, driving and rest periods, environmental regulations, construction feasibility, railway access, congestion, living costs and family conditions, location costs, wages, weather, closeness to similar companies, cost of return goods flows from northern Sweden, and closeness to nearby terminal to support goods handling at hub.

A decision support model has been created consisting of four sub models. With a set of fixed data a Centre-of-Gravity analysis can be completed where a centre of gravity is achieved. A number of alternatives which fulfil the qualifiers, factors that the hub location needs to fulfil, are obtained. Next, the alternatives are evaluated according to a set of parameters, factors which are wishful to fulfil for the locations, and a parameter score is calculated. Moreover, the transportation cost for the alternatives is estimated. The output of the model is to be used as a decision support for hub localisation.

Based on the analysis of the chosen transport lines the optimal hub location could not be distinguished, according to the model. Uppsala was the best alternative according to the parameter score, however, Gävle got the lowest transportation costs. Since the difference between the alternatives’ score and cost was marginal, it was not possible to identify the optimal hub localisation. In addition, there are aspects which are not included in this analysis that need to be considered before making a decision. (Less)
Please use this url to cite or link to this publication:
author
Josefsson, Sara LU and Medin, Andreas LU
supervisor
organization
alternative title
Modell för beslutsunderlag vid lokalisering av hubb - En studie på ett företag i 3PL-branschen
course
MTT820 20121
year
type
M1 - University Diploma
subject
keywords
Facility localisation, optimal hub location, decision support model
report number
5734
other publication id
ISRN LUTMDN/tmtp--5734--SE
language
English
id
3048452
date added to LUP
2012-09-21 12:01:47
date last changed
2013-02-12 11:28:33
@misc{3048452,
  abstract     = {Background:
With todays’ requirement of shorter product life cycles and faster time-to-market, producing companies experience an increased demand for faster transports in the supply chain. This puts pressure on freight forwarders to offer their customers a timely and reliable transport service at a reasonable price. Another challenge for the freight forwarders in Sweden is to provide such services in all parts of the country. Therefore, the actors in the 3PL industry must find an appropriate design for their transportation network which can enable these transports. This pressure is felt by Company X, which is the Swedish division of one of the largest freight forwarders of road transports in Europe. The network is operated by hauliers and contains of 25 terminals where some of them also function as hubs, which consolidate goods in order to increase the utilization of transports. Company X are now facing problems in meeting the scheduled delivery time for deliveries to northern Sweden. Since Company X strives for meeting its customers’ expectations it is wishful to develop a model based on a set of factors, which can evaluate the localisation of a hub and be a support for future decisions. Moreover, there has not been an evaluation of the main hub and its connected lines in the transportation network for many years. An analysis of the current network according to the model will therefore be conducted to identify the optimal hub localisation.

Purpose:
The purpose of this master thesis consists of two parts; first, to develop a model, which can evaluate the localisation of a hub, and second, to perform an analysis of the current hub location to find an optimal one according to the model.
Research questions:
The master thesis will answer the following questions to achieve the purpose:
- Which factors have to be taken into consideration by Company X when deciding where to locate a hub?
- How should the alternative hub localisations be identified and evaluated to arrive at a decision support for an optimal hub localisation?
- What is the optimal hub localisation for the chosen lines according to the developed model and how reliable is the result?

Method:
The thesis is based on a systems approach since synergy effects are expected to arise between the factors in the constructed model. The development of the model is considered to be an exploratory and a normative study while the second part of the purpose will be an explanatory study. Both qualitative and quantitative data will be used in order to develop the model and to perform the analysis. The model is validated according to four steps to ensure the validity, reliability and objectivity. The validity of the analysis is investigated through performed sensitivity analyses.

Conclusions:
A number of factors affecting facility localisation were found in the literature and these were analysed to identify factors affecting the hub localisation for Company X. The following 16 factors were finally recognised to be considered when deciding where to locate a hub for Company X; highway access, labour availability, delivery time to customers, driving and rest periods, environmental regulations, construction feasibility, railway access, congestion, living costs and family conditions, location costs, wages, weather, closeness to similar companies, cost of return goods flows from northern Sweden, and closeness to nearby terminal to support goods handling at hub.

A decision support model has been created consisting of four sub models. With a set of fixed data a Centre-of-Gravity analysis can be completed where a centre of gravity is achieved. A number of alternatives which fulfil the qualifiers, factors that the hub location needs to fulfil, are obtained. Next, the alternatives are evaluated according to a set of parameters, factors which are wishful to fulfil for the locations, and a parameter score is calculated. Moreover, the transportation cost for the alternatives is estimated. The output of the model is to be used as a decision support for hub localisation.

Based on the analysis of the chosen transport lines the optimal hub location could not be distinguished, according to the model. Uppsala was the best alternative according to the parameter score, however, Gävle got the lowest transportation costs. Since the difference between the alternatives’ score and cost was marginal, it was not possible to identify the optimal hub localisation. In addition, there are aspects which are not included in this analysis that need to be considered before making a decision.},
  author       = {Josefsson, Sara and Medin, Andreas},
  keyword      = {Facility localisation,optimal hub location,decision support model},
  language     = {eng},
  note         = {Student Paper},
  title        = {Decision support model for hub localisation - A study at a company in the 3PL industry},
  year         = {2012},
}