Research Proposals Final 2

7/17/2019 Research Proposals Final 2

http://slidepdf.com/reader/full/research-proposals-final-2 1/13

Determinants of Foreign Direct Investment in

Angeles City, Pampanga

By

Galang, Sweetsell

Gutierrez, Zyrr

orales, ar!orie

"ongio, A#egail

Department of Accountancy

$olyAngel %niversity

Author’s Note

Correspon&ence concerning t'is article s'oul& #e a&&resse& to Sweetsell Galang, Zyrr

Gutierrez, ar!orie orales, A#egail "ongio, Department of Accountancy, College of Business

an& Accountancy, $olyAngel%niversity, Sto( )osario St( Angeles City( Contact*

!!st+-.ya'oo(com, rina'/sa0ura.ya'oo(com, iyanice+1.gmail(com,

relem2-1.gmail(com

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mailto:[email protected]











Greenwic' Pizza is a small Filipino entrepreneurs'ip w'ic' is pioneere& #y rs(

Cresi&a"ueres for t'e &evelopment of its #usiness( It starte& as a small over4t'e4counter

pizza store in Green'ills Commercial Center in -56- an& #y -551, it grew to 2 #ranc'es( It

was t'en 7olli#ee Foo&s Corporation saw its 'uge potential in venturing into t'e growing

mar0et of pizza an& &ecisively o#taine& a &eal ac8uiring 9: of Greenwic'4 t'e #iggest

pizza c'ain in t'e P'ilippines(Greenwic' ;+-<

In a tec'nology #ase& competitive mar0etplace, ac'ieving service e=cellence 'as

#ecome critical for success( "'is proposal a&&resses a 0ey element of service strategy, t'e

a#ility to compete on cycle time, an& it a&&resses a fun&amental measure of progress

against t'at strategy, inventory levels( Inventory levels re>ect 'ow every aspects of t'e

#usiness are performing wit' 8uestion to as0* Is t'e setup time is s'ort? Is t'e process

relia#le? Are t'e response to c'ange fast an& @nally t'e customer satis@e& "'e goal of t'is

stu&y is to provi&e speci@c e=ample of 'ow to re&uce cycle time an& its inventory

component(

"'is proposal aim to foun& out if t'e sales forecast 'as an impact in accurate supply

forecasting &ue to customer &eman& an& #y comparing t'e system t'at t'e Greenwic'

Pizza C'ain use& t'e manual approac' an& t'e propose& automate& #ase& forecasting

w'ere t'e point at w'ic' an item s'oul& #e or&ere& t'an an or&er occurs w'en t'e

pre&etermine& minimum level of inventory is reac'e& an& after reac'ing t'e minimum re4

or&er point, an conomic r&er uantity ;< can #e use& as a #asis w'ic' can #e

minimize t'e use of manual computation to compute or&ering 8uantity, re4or&er point,

stoc0room re8uirement, an& inventory costs(

"'e general o#!ective of t'is researc' is to assess t'e factors in c'oosing #etween

t'e manual an& automate& approac' in forecasting an& or&ering management( ne of t'e

speci@c o#!ectives of t'e stu&y is to &etermine t'e accurate forecasting an& or&ering of

supplies(

"'e stu&y is signi@cant for Greenwic' Pizza C'ain in provi&ing information regar&ing

its current status in using manual forecasting supplies(

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"'e company can use t'e stu&y to i&entify t'e pro#lems t'ey are currently

encountering to #e a#le to a&apt t'e possi#le solutions an& plan t'e actions, w'ic' can

improve its #usiness operations(

"'is stu&y may also useas a gui&e an& a&&itional reference #y t'e future researc'ers

w'o aims to con&uct a similar stu&y(

Forecasting an& replenis'ing mo&els of inventories 'ave t'e aim of &etermining or&er

8uantities to minimize t'e sum of total overage costs an& un&erage costs(

Accor&ing to Eeger ;+-1<, proper forecasting ensures to satisfy t'e &eman& of t'e

customers #y 'aving enoug' supply( An overestimation of &eman& lea&s to an outsize

inventory an& 'ig' costs w'ile un&erestimating &eman&ma0es many value& customers

wont get t'e pro&ucts t'ey want t'at lea&s to unsatis@e& consumers(

Figure 1 Conceptual Framework

"o stay well a'ea& in t'e competition, must a&apt &ynamically a new stan&ar& an&

c'ange inventory forecasting an& or&ering from e=isting pus' mo&els ;manual< to a fully

automate& an& integrate& pull system capa#le of accurately analyzing e=isting inventory,

systematically an& relia#ly optimizing replenis'ment(

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IHP%" P)CSS %"P%"

Fig. 1 Conceptual Framework

Level

of

Stocks

Time Series for

Forecasting

Technique

Economic Order

Quantity EOQ!

Automated or

"anual A roach

$emand from

%ustomers

Target Sales

&roduct

%haracteristics



An eective forecasting management solution nee& to #e a#le to e=actly pre&ict

inventory nee&s an& vigorously a&apt to c'anging &eman& patterns wit' statistical stoc0

&eman& forecasting ;'ler, +-+<(

Simplifying or&er at t'e store level wit' automate& system suggeste& or&ering #ase&

on sales forecast, con@gura#le par levels, 'istorical e=pen&iture patterns, an& on4'an&

inventory levels(

In t'e past few years, improvements in tec'nology 'ave allowe& #usinesses to ta0e

a&vantage of 'ig' volumes of &etaile& &ata in t'e &evelopment of accurate forecaste&

consumer &eman& patterns( Jim K et(al, ;+6<

Stevenson ;-55-< i&enti@e& some approac'es to Forecasting*

-(< ualitative et'o& w'ic' consists mainly of su#!ective inputs, w'ic' often &efy

precise numerical &escription(

+(< uantitative et'o& t'at involves eit'er t'e e=tension of c'ronological

information or &evelopment of associative t'at attempts to utilize t'e causal varia#les to

ma0e a forecast(

(< 7u&gmental Forecast rely on analysis of su#!ective inputs o#taine& from various

sources suc' as consumer surveys, t'e sales stas, managers an& e=ecutives(

1(< Forecast #ase& on $istorical Data &eepens on uncovering relations'ips #etween

parameters t'at can #e use& to outloo0 values of one of t'em( t'ers simply attempt to

pro!ect past e=perience into t'e future( ften use 'istorical, or time series, &ata an& ot'ers

attempt to i&entify speci@c patterns in t'e &ata(

"'e importance of &eman& forecasting forecast can lea& to timely intro&uction of

pro&ucts, opening of facilities an& a&!ustments in inventory levels(

ualitative met'o&s rely upon su#!ective opinions or persons intuition a#out in

forecasting an& placing an or&er of supply in t'e mar0et( "'ese met'o&s are most

appropriate w'en t'ere is little 'istorical &ata to wor0 wit' t'at #ase& on sales target( L'en

a new line of pro&ucts is intro&uce& in t'e mar0et, people can ma0e forecasts #ase& on

comparisons wit' ot'er pro&ucts t'at t'ey consi&er similar(

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http://www.crunchtime.com/solutions/inventory-management/






"'e causal met'o&s of forecasting assume t'at &eman& is strongly relate& to

particular mar0et or environmental t'at a customer 'as an option to c'oose( For instance, a

causal relations'ip e=ists #etween price an& &eman&( If prices are lowere&, &eman& can #e

e=pecte& to increase an& vice versa(

Anot'er met'o& is t'e time series,w'ic' t'e most common form in forecasting("'ey

are #ase& on t'e assumption t'at 'istorical patterns of &eman& are goo& in&icator of future

&eman& forecasting( "'ese met'o&s are #est w'en t'ere is a relia#le source of 'istorical

#eing forecast are sta#le an& 'ave &eman& patterns t'at &o not vary muc' from one year to

t'e ne=t(

Accor&ing to Dilwort' ;+<, forecast is an inference of w'at li0ely to 'appen in t'e

future an& #usiness must &evelop forecasts of t'e level of &eman& t'at t'e company s'oul&

#e prepare to meet(

avic' ;-556< Economic Order Quantity 'EOQ( can #e use& in planning t'e

purc'ases of supplies( Forecasting ualitative tec'ni8ues s'oul& #e consi&ere& w'en

relevant information is li0ely to #e unsta#le &uring t'e forecast 'orizon(

Eync' ;+< a&&e&, t'e 0ey point in cost or #ene@t is t'at all suc' #roa&er #ene@ts

in t'is area is concerne& wit' t'e 8uanti@cation of suc' #ene@ts of t'e cost t'at may #e

associate& wit' t'em(

Given t'e cost structure of a store, t'ere is an or&er 8uantity t'at is can #e use& an&

t'e most cost eective amount to purc'ase at a time( "'is is calle& t'e economic order

quantity ;< an& it is calculate& as follows*

M N+%'C

w'ere*

% M annual usage rate

M or&ering cost

C M cost per unit

' M 'ol&ing cost per year as a percentage of unit cost

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"'e conomic r&er uantity or formula wor0s to calculate an or&er 8uantity

t'at results in t'e most eOcient investment in inventories( Ociency means t'e lowest total

unit cost for eac' inventory items(

$ugo ;+< e=plaine&, if a certain inventory item 'as a 'ig' usage rate it means

e=pensive, t'e conomic r&er uantity or formula recommen&s a low or&er 8uantity

w'ic' results in more or&ers per year #ut less money investe& in eac' or&er( If anot'er

inventory item 'as a low usage rate an& it is ine=pensive, t'e formula recommen&s a

'ig' or&er 8uantity( "'is means fewer or&ers per year #ut since t'e unit cost is low, it still

results in t'e most eOcient amount of money to invest(

Accor&ing to Stair, et( al, ;-556< conomic r&er uantity o#!ective of t'is inventory

control tec'ni8ue is to minimize or&ering an& carrying costs(

Assumptions of conomic &er uantity ;<*

-( Deman& is i&enti@e& an& never c'anges(+( "'e lea& time ;point in time #etween t'e or&er &ate an& t'e receipt of t'e or&er<

is 0nown an& constant(( "'e receipt of inventory is instantaneous ;inventory from an or&er receives in one

#atc', at moment in time<1( If or&ers are places t'e rig't time, stoc0 outs of s'ortages can #e avoi&e&(

$owever, $opp ;+9< a&&e&t'at a function of t'e loa& on t'e stoc0room is t'e cost

of replenis'ment, ot'er lot4sizing proce&ures, #ase& on &ynamics sc'e&uling approac'es,

are more suita#le t'an conomic r&er uantity( Hevert'eless, t'e formula provi&es a

#asic tool for controlling t'e cycle an& carrying costs(

In&ee&, increase& sales target, a #etter customer service, re&uce& i&le time, #etter

response to mar0et &eman&s, give a&vance notice so managers can see t'e planne&

sc'e&ule #efore actual release of or&ers an& ai&s capacity planning to 'ave an accurate

forecast(

(

"'e stu&y aims to i&entify t'e following factors*

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-( L'y are accurate forecasting an& or&ering important

+( $ow to compute for actual or&ers #y using t'e Daily Supplies )e8uisition Form

;anual Approac'< an& Lee0ly Supplies )e8uisition Form "emplates ;Automate&

Approac'<

( Do t'e &aily sales 'ave relevance in forecasting supplies

1( L'at are t'e tools an& proce&ure use& in supplies or&ering

Forecasting an& or&ering is very important it 'elps to &etermine& w'en to or&er an&

ensure t'at supplies to #e use& are fres' an& of 'ig' 8uality an& 'ave t'e rig't 8uantity at

t'e rig't time so t'at it will not e=perience t'e eects of over stac0ing or zero stoc0s(

An automate& or&ering system can &etermine t'e minimum an& ma=imum or&ers of

certain stoc0s #ase& on pro!ecte& inventory cost an& storage area(

$ry Forecasted Stocks 'FS( ) * of $ays + Average $aily ,sage 'A$,(

L'ere*

Q of Days 4 Q of &ays #ase& on an items or&ering cycle(

Ave( Daily %sage R average consumption of a speci@c item per &ay(

-akery and .et Forecasted Stocks 'FS( ) Ad/usted Sales + Stock Factor

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Ad/ustmen

Actua

l

Order

Forecast

ed Stocks

'FS(

Ending

0nventor

y

Stocks

in

Transit



L'ere*

A&!uste& Sales R forecaste& sales #ase& on an items or&ering cycle(

Stoc0 Factor R average consumption of a speci@c item per peso volume of sales( ;In

Greenwic', stoc0 factor is #ase& on a per - peso volume of sales, w'ic' pre&etermine& #y

Jitc'en anager<(

Stoc0 Factor M "otal Stan&ar& %sage"otal Sales Eess Tat

"'e proper relations'ip #etween sales an& inventory can #etter #e well maintaine&(

Lit'out inventory control proce&ures in place, t'e store can #e overstoc0e& or un&er

stoc0e&(

A template t'at can &etermine t'e minimum an& ma=imum or&ers of t'e store for

certain stoc0s #ase& on pro!ecte& inventory cost an& storage area( Lit' t'e use of t'is tool,

stores will not #e allowe& to re4or&er items if t'e minimum re4or&er level 'as not yet #een

reac'e&( After reac'ing t'e minimum re4or&er point, new or&ers are enco&e& using t'e

conomic r&er uantity or as #asis(

A&vantages*

-( )e&uces &ry operating supplies inventory level store& insi&e t'e stoc0room #y as

muc' as 1: at any given time ;percentage may vary &epen&ing on t'e stores

average &aily sales an& or&ering fre8uency<+( )e&uces t'e possi#ility of overstoc0ing an& stoc0 outs(( Allows t'e stores to up&ate average &aily sales ta0e out :, average c'ec0 an& lea&

time ;or&ering fre8uency< as nee&e&( "'e template will automatically compute t'e

correspon&ing eect on stoc0room area, inventory costs, economic or&er 8uantity,

ma=imum an& minimum inventory level ;re4or&er point<(1( inimal manual computation is nee&e& to compute or&ering 8uantity, re4or&er point,

stoc0room re8uirement an& inventory costs(

"ethod

1esearch $esign

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"'e researc'er woul& li0e to @n& out t'e connection an& measurement of cause an&

eect relations'ips among varia#les of Greenwic' Pizza C'ain in Angeles City operations

w'ic' ispart of t'e stu&y inclu&e& a personal interview an& &irect o#servation on operations

of t'e store an& inventory to @n& out t'e patterns as well as t'e c'aracteristics of t'e

strategies t'at are implemente&( By t'is reason t'is researc' is classi@e& #ot' comparative

an& time series researc'(

"'e purpose of using t'e comparative researc' was to compare t'e manual an&

automate& #ase& forecasting to recor&, analyze, an& interpret t'e relevant issues of t'e

companys operations process to i&entify in>uential factors in t'e present con&itions of

Greenwic' Pizza c'ain(

"'e time series met'o& was use in &etermining t'e point w'en t'e inventory was in

nee& to re4or&er anot'er supply of goo&s t'at is its minimum t'at ma0es t'e pro&uct

availa#le in t'e mar0et(

&artici#ants

Sampling is not applica#le in t'is researc' since t'e focus of t'e researc' is t'e

analysis in using forecasting met'o&s4 manual an& automate&( "'e researc'ers will #einterviewing @ve ;2< Greenwic' Pizza Corporation Store anager in 2 Greenwic' #ranc'es

aroun& Angeles City as t'e #asis in i&entifying t'e signi@cant &ierences #etween t'e sai&

forecasting met'o&s(

Sources of $ata

Primary an& secon&ary &ata were #ot' use&( "'e primary &ata were gat'ere& #y

interviewing t'e store manager of Greenwic' Pizza C'ain( Interviews were con&ucte& at all

#ranc'es of Greenwic' in Angeles City(

"'e secon&ary &ata were o#taine& from Greenwic' Pizza C'ain $an&#oo0( Boo0s an&

!ournals foun& in %niversity Ei#rary of $oly Angel %niversity(

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Greenwic' Pizza C'ain Branc' in Angeles City*

2reen3ich &i44a %or#5"arquee "all -ranchFrancisco G( Hepomuceno Ave(, Pulungaragul, Angeles CityPampanga, P'ilippines

2reen3ich &i44a %or#5Ne#o "all -ranchGroun& Floor Hepo all DoUa "eresa Avenue corner Saint 7osep' Street Angeles CityPampanga, P'ilippines%ontact Num6er7 ;12< +2455.e6site7 'ttp*www(greenwic'(com(p'

2reen3ich &i44a %or#5"a6alacat -ranch

7enra Bl&g(, cArt'ur $ig'way, a#alacatPampanga, P'ilippines%ontact Num6er7 ;12< -4+11

2reen3ich &i44a %or#5Sto51osario -ranch

7enra all, Sto( )osario St(, Angeles CityPampanga, P'ilippines

"elep'one Ho* ;12< ++4-9

2reen3ich &i44a %or#5S" %lark -ranchClar0@el&Avenue,Angeles CityPampanga, P'ilippines

$ata Analysis8&rocessimg

"'e researc'ers 'ave &etermine& to use linear regression &ata analysis tec'ni8ue to

verify t'at t'e &eman& an& target sales are use& to pre&ict t'e level output of stoc0s(

Because of time series met'o& an& comparative researc' &esign t'at researc'ers are

convince& t'at t'e use of linear regression &ata analysis will #e t'e most eective &ata

processing tec'ni8ue #ecause t'e sai& &ata processing tec'ni8ue is use& for pre&icting t'e

un0nown value of anot'er varia#le(

"'e researc'ers will #e using a mo&el to test t'e or&er to pre&ict a certain outcome of

#usiness operations in maintaining t'eir inventory( "'e mo&el consists of a &epen&ent an&

an in&epen&ent varia#le( "'e researc'ers 'ave &etermine& t'at customers &eman&, pro&uct

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c'aracteristics an& target sales are t'e in&epen&ent varia#le use& to pre&ict t'e level of

inventory stoc0s w'et'er it may #e properly manage& w'ic' may lea& to eOcient inventory

forecast or overun&ervaluation of inventory( "'e pre&ictions on t'e level of inventory stoc0s

will #e assigne& as t'e &epen&ent varia#le( "'us t'e e8uation woul& #e e=presse& as*

9 ) a : 6;

.here7 9 < inde#endent varia6le '%ustomer’s $emand= Target Sales( a > 6 < ,nkno3n constants ; < $e#endent ?aria6le 'Level of Stocks(

%sing t'e mo&el presente& a#ove, t'e researc'ers can assess w'et'er &eman& from

customers, target sales an& pro&uct c'aracteristics can #e use& to pre&ict t'e eOciency or

overun&ervaluation of inventory( "'e e8uation itself can #e teste& to verify t'e outcomes

t'at it will pro&uce( "'is can #e &one #y e=amining t'e varia#les in analyzing t'e outcome,

t'e researc'ers will #e using t'e latest &ata processing software to verify t'at t'e linear

regression e8uation as state& an& presente& a#ove is relia#le an& correct(

)eferences

-OO@S7

$ugos, ic'ael, Essentials of Supply Chain Management +n& &ition, 7o'n Liley K Sons, Inc(,

%SA, +

$opp, Lallace, Supply Chain Science, International &ition, (cGraw $ill, +9

Eync', Purchasing and Supply Management , -+t' &ition, cGraw $ill, +

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$opp, )(, Supply Chain Excellence: hand!ook for dramatic impro"ement using the

modelcGraw $ill, +

Stair, et(al, Managing Purchases t'&ition cGraw $ill, -556

ONL0NE O,1NALS=

urty(;+<(Forecasting for Supply Chain and Portfolio Management.)etrieve& from articles

'ttp*www(personal(engin(umic'(e&umurty(p&fwww(retali=(com

Jim, et( Al ;+6<(Method and System for Forecasting Future #rder $e%uirements.)etrieve&

from articles 'ttp*www(fres'patents(comet'o&4an&4system4for4forecasting4future4or&er4

re8uirements4&t+96ptan+9-++6(p'p

'ler, ;+-+<, Supply Chain Management.)etrieve& from articles

'ttp*www(#uyersmeetingpoint(coma#out4uslatest4news264-4+24+-+4supply4c'ain4

management4lessons4from4pizza4'ut

Eeger, ;+-1<, &emand and Supply Management' )etrieve& from articles

'ttp*scm(ncsu(e&uscm4articlesarticlecpfr4mo&el4+(4&eman&4an&4suply4management4

colla#orative4planning4forecastinQ2www(retali=(com

Stevenson, ;-55-<, &emand Forecasting in a Supply Chain, )etrieve& from articles

'ttp*www(learningace(com&oc69999f1-+a629&26#c+#22-a29e#5c'apter464

&eman&4forecasting4in4a4supply4c'ain

"AN,ALS 8 BAN$-OO@S

Foundation of Store Management )evise& &ition +-,#yGreenwic' Pizza Corporation

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http://www.personal.engin.umich.edu/murty/.pdf

http://www.retalix.com/

http://www.freshpatents.com/Method-and-system-for-forecasting-future-order-requirements-dt20080703ptan20080162270.php


http://www.buyersmeetingpoint.com/about-us/latest-news3/570-10-25-2012-supply-chain-management-lessons-from-pizza-hut


http://scm.ncsu.edu/scm-articles/article/cpfr-model-2.-demand-and-suply-management-collaborative-planning-forecastin#5



http://www.learningace.com/doc/7688366/868f412a758d537b3c2b551a58e3b693/chapter-7-demand-forecasting-in-a-supply-chain


http://www.personal.engin.umich.edu/murty/.pdf













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Documents

Research Proposals Final 2