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Service Facility Location Attracting customers Chap. 8 第七章.
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Transcript of Service Facility Location Attracting customers Chap. 8 第七章.
Service Facility Location
Attracting customersChap. 8第七章
Strategic location considerations
• Flexibility– Ability to react to changing economic situations• Facility is capital-intensive long term commitment• Reduce risk from regional economic downturns
• Competitive position– Establish itself relative to competitors• Multiple locations
– Market awareness
• Acquire prime location before market developed
• Demand management– Ability to control quality, quantity, and timing of
demand• Hotel
– Fixed nature of the facility– Locate near a diverse set of market generators
• Focus– Offering the same narrowly defined service at
many location• Cookie-cutter approach
• Competitive Clustering– Reaction to observed consumer behavior• Comparison before purchase• Motor mile
– Cluster of dealers
• Motel chains– Occupancy is higher if locate with many competitors
• Saturation marketing– Group outlets of the same firm tightly• In urban and other high-traffic areas
– Au Bon Pain, Café • Clustered about 25 cafés in the Boston area• Some of them fewer than 100 yards apart• Advantages
– Reduce advertising, easier supervision, customer awareness– Intercept impulse customers with little time to shop or eat
• Marketing Intermediaries– Service is created and consumed simultaneously• Not suitable for “channel-of-distribution” concept
» Make lots of shoes and sell thru many channel– 美國前總統柯林頓演講費為 30 萬美元一場
– Insurance products can use intermediaries• 旅行平安險在機場或業務代表都可以買
– Bank Credits• Credit cards are distributed thru many different
channels
• Substitution of communication for travel– Paramedics and nurse practitioners• Use communication with distance hospital
– Save patients’ trip to hospitals
– Direct payroll deposit• Save employee’s trip to banks for deposits• Free bank’s office from congestion
• Separation of front from back office– Front office closed to customers– Back office near the available cheap labors
• Impact of the Internet on service location– Websites are virtual locations for e-tailers
• Customers’ physical travel becomes irrelevant
– Products shipping• Still a concern• Easy to access overnight shippers
– 24/7 call centers• Strategically locate around the world
– India, Ireland, and Jamaica– Operate normal daylight shift– Educated English literate low-wage labor
– “Competitive clustering” around a website• Small off-Broadway theaters
– Southern New Jersey– No central theatre district exist– Scatter across eight counties
• Shared website– Allow potential patron to browse available plays– Direct link to theatre for ticket
• Site consideration
• Geographic Information Systems– Capture. Store,
manipulate, analyze, manage, and present all type of spatial or geographical data
Stanford Geospatial Center
– Water main ruptured• Level of storage tank lowering dramatically
– To locate a leak» Explore 2000 acres» Stopping periodically and listen for leaking water
• GIS– Show geographical coordinates of each water line and valve– Pressure-sensitive valves and data logic control– Locate the leak precisely from the office
– Immediate-response team• Wildfire, earthquake, and tsunami
– Data• Bird populations, plant diseases, fuel management
– Use GIS to find ideal location
Facility location modeling considerations
• Geographic presentation– Travel distance
– Number of facilities• One
– Easy, ex. Travel distance
• Many– Service capacity– Level of service– Area served
– Optimization criteria• Maximize some measure of benefit• Private sector criteria
– Cost of building and operating facilities– Cost of transportation
• Public sector criteria– Lack of agreement on goals– Difficult to measure benefit
» Travel distance» Demand created
– Effects of optimization criteria on location
Facility location techniques
• Minimize the average walk– Concession along beach of Waikiki
• Cross-median approach for a single facility– Minimize the total travel distance
• Huff model for a retail outlet– Maximize profit– Gravity model• Mass (estimate customer demand) / (distance)2
• Location set covering for multiple facilities– Minimal number and location of facilities– Serve all demand points– Within some specified maximal service distance
Regression analysis in location decision
• Forecast the performance of a standard location
• Several independent variables– Size, competitors nearby, traffic, …
• Minicase– Case 8.1 Health Maintenance Organization– Case 8.2 Athol furniture, Inc.
– No local cases needed. Show your reasoning in solving problems