Forecasting Model Fro Dry Bulk Freight

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Forecasting
 model
 for
 dry
 bulk
 sea
 freight
 
Facilitating
 Lantmännen
 to
 make
 better
 procurement
 decisions
 
Frans
 Kaltea
  Joel
 Odland
 
  Division
 of
 Engineering
 Logistics
  Faculty
 of
 Engineering
  Box
 118
  SE
 221
 00
 Lund,
 Sweden
 
  This
 article
 is
 a
 summary
 of
 a
 master
 thesis
 written
 at
 the
 Division
 of
 Engineering
 Logistics,
  Department
 of
 Industrial
 Management
 and
 Logistics,
 Faculty
 of
 Engineering,
 Lund
 university.
 The
  master
 thesis
 was
 initiated
 as
 a
 result
 of
 an
 identified
 need
 of
 increased
 understanding
 of
 the
 sea
  freight
 market
 within
 Lantmännen’s
 sea
 freight
 procurement
 organization.
 The
 main
 purpose
 of
 the
  thesis
 was
 to
 develop
 a
 price
 prediction
 model.
 The
 model
 should
 provide
 Lantmännen
 with
  information
 that
 facilitates
 better
 decision
 making
 when
 procuring
 sea
 freight
 services.
 A
 secondary
  purpose
 was
 to
 develop
 a
 process
 for
 the
 development
 of
 price
 indices
 and
 forecasting
 models.
 This
  article
 presents
 a
 background
 of
 the
 problem
 and
 describes
 how
 the
 model
 was
 created.
 

  Introduction
 
 
Lantmännen
 is
 one
 of
 Nordic’s
 largest
  companies
 within
 food,
 energy,
 machinery
  and
 agriculture.
 The
 company
 is
 engaged
 in
  business
 activities
 throughout
 the
 whole
 value
  chain:
 “from
 field
 to
 fork”.
  For
 Lantmännen,
 sea
 freight
 is
 the
 second
  most
 used
 transportation
 method
 after
 road
  transport.
 Lantmännen
 purchases,
  approximately,
 1300
 separate
 ship
 freights
  yearly,
 with
 an
 average
 load
 of
 1700
 ton
 per
  ship.
 On
 average
 Lantmännen
 yearly
 ships
 2.8
  million
 tons,
 mainly
 grain
 and
 input
 goods
 to
  feedstuff
 production
 on
 dry
 bulk
 ships.1
  Lantmännen
 had
 identified
 a
 need
 to
 better
  understand
 what
 is
 affecting
 the
 freight
 rates,
  for
 sea
 transports,
 offered
 to
 them
 by
  shipowners
 and
 shipbrokers.
 In
 order
 to
 help
  them
 get
 an
 increased
 understanding,
 an
  investigation
 of
 how
 the
 rates
 are
 constructed
  was
 needed.
 This
 investigation
 early
 identified
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1

a
 fact
 about
 the
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