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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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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
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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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"'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
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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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