SUPPLY CHAIN EFFICIENCY WITH COLLABORATION

Increasing Grocery Store Supply Chain Efficiency with Collaboration through the Use of more Policy-Oriented Systems Dynamics Approach

TABLE OF CONTENTS

CHAPTER 1: RETAIL SECTOR4

1.1 grocery Retail sector4

1.2 Characteristic of retail supply chain6

1.2.1 Demand Management7

1.2.2 Warehouse Management Systems (WMS)7

1.2.3 Radio Frequency Identification (RFID)7

1.2.4 Transportation Management Systems8

1.2.5 Supplier Relationship Management (SRM)8

1.2.6 Point of Sale (POS) Systems8

1.2.7 Merchandising Systems8

1.2.8 ERP - Distribution9

CHAPTER 2: LITERATURE REVIEW10

2.1 Measuring Supply Chain Performance of Order Algorithm10

2.2 Supply Chain Inventory Management10

2.3 Challenges in Inventory Management Systems11

2.4 Performance measure Criteria, Inventory Management and Different Order Algorithms in Supply Chain12

2.4.1 Inventory control with deterministic demand and independent ordering13

2.4.2 Inventory control in a store system without stock outs13

2.4. 3 Inventory control in a store system with permitted shortages and backorders13

2.4.4 Inventory control in a factory warehouse with finite production rate14

2.4.6 Inventory control in a store system in terms of a random demand with normal distribution15

2.5 Review Supply Chain Simulation Modelling and System Thinking16

Assumptions and model equations19

IOBPCS model21

VIOBPCS model21

APIOBPCS model23

APVIOBPCS model24

CONWIP model24

2.6 Comparisons of Algorithm models for Inventory and Order management30

2.6.1 Rate of demand for items31

2.6.2 Production rate of the supplier31

2.6.3 Procurement lead time32

2.6.4 Costs associated with systems operation32

2.7 Simulation Modelling Approaches in Inventory Supply Chain34

2.8 Review From Previous Studies36

2.8.1 Demand Forecasts Using Bayesian Procedure36

2.8.2 Time Series Autoregressive Models38

2.8.3 Inventory Models40

2.8.4 Limitations of the Past Research41

2.8.5 Overcoming the Limitations42

2.9 Comparisons of the Models: Discrete Event Simulation, System Dynamics and Agent Based Simulation43

2.9.1 Introduction43

2.9.2 Introducing the Techniques44

REFERENCES49

CHAPTER 1: RETAIL SECTOR

1.1 Grocery Retail sector

Many UK households have seen their spending power squeezed over the last year by a combination of rising prices and static or declining earnings. Rising commodity prices have had an effect in UK stores over the first half of 2011, and an unprecedented eruption of civil unrest in North Africa and the Middle East raised oil prices to record levels (Ding & Puterman, 2005). Such is the impact of rising oil prices on the UK shopper that the UK government has introduced a new “stabiliser” to help moderate the pressure on domestic budgets. This fuel stabiliser means that fuel duty will increase in line with the Retail Price Index (RPI) measure of inflation when oil prices are high. However, in years when crude falls below a set trigger price for a sustained period, the government will increase fuel duty by RPI plus 1p per litre (Ding & Benyoucef, 2004).

The current downturn in the UK has resulted in numerous challenges for UK retailers and consumers alike. Consumers are increasingly value focused in their purchase decisions as they try to counteract the effects of rising inflation, food and fuel costs on their disposable income. This has resulted in promotions playing an increasingly important part in retailer strategies as they fight to retain their market share and maintain loyalty among their shoppers (De Alba, 1993).

Throughout 2011 UK retailers have been increasing their focus on value with bigger, bolder initiatives in an attempt to drive footfall. In September 2011 Tesco announced a £500m investment in price cuts while Sainsbury?s has ...