EBIZ GAME: A SCALABLE ONLINE BUSINESS SIMULATION GAME FOR ENTREPRENEURSHIP TRAINING

Size: px
Start display at page:

Download "EBIZ GAME: A SCALABLE ONLINE BUSINESS SIMULATION GAME FOR ENTREPRENEURSHIP TRAINING"

Transcription

1 EBIZ GAME: A SCALABLE ONLINE BUSINESS SIMULATION GAME FOR ENTREPRENEURSHIP TRAINING Yue Poh LAI Ngee A Polytechc [email protected] Ta Log SIAU Ngee A Polytechc [email protected] ABSTRACT Ths artcle exames how a scalable web-based busess smulato game was evolved ad developed; ad how t ca be used as a exercse etrepreeurshp trag ad as compettve platform. The use of smulato offers etrepreeurshp educators may structoal opportutes that would be uavalable to studets wthout the use of smulatos. The ebzgame smulates the compettve ad dyamc busess evromet ad allows studets to role-play o a teractve bass as drectors of a small busess. Through smulato, studets ca sharpe ther busess acume, develop desrable process sklls ad demostrate problem solvg ad thkg sklls; ad creatvty ad ovato. Ths artcle exames how the game was evolved, developed ad used for etrepreeurshp trag ad compettos. XML, N-ter archtecture ad load-balacg techques are used to mplemet ths web-based game. INTRODUCTION The ebzgame offers a smulato that ecompasses may of the factors that occur day-to-day busess operatos of a small busess. It has bee used for trag at least sx batches of etrepreeurshp studets sce July 997. It has also bee ru successfully as a competto for the past 3 years. At the Award Presetato Ceremoy o 24 th March 200 of the competto orgazed for secodary schools, the Guest-of-Hoor, Mss Leog Yop Poo, Deputy Drector, Humates ad Aesthetcs Brach, Currculum Plag ad Developmet Dvso, Mstry of Educato, hghlghted to all partcpatg teams that techology was eutral. Uless the key busess cocepts, prcples ad processes were uderstood, appled ad tegrated to the busess operato, the most sophstcated hardware ad software would be effectve. Ultmately, etrepreeural sklls ad busess acume were stll largely resposble for the log-term success of ay busess. Her commet emphaszes the eed to fully corporate the smulato to all aspects of the etrepreeurshp course. Busess smulato games should ot stad aloe classroom use. They are of lmted effectveess f ot successfully corporated to all classroom strateges ad evaluato methods. Although wg s mportat ay games, studets should be costatly remded that the prmary objectve of playg the smulato game s learg. I fact the loser of the game has more to lear f he draws lessos from the mstakes made the game. Welldeveloped smulato games should be cluded ad corporated to all class dscussos ad lectures. If ot, studets may vew stad-aloe smulato games as tmefllers ad as rrelevat materals. Thus studets must be gve a overvew of the topcs before playg the smulato game ad a debrefg whe the game s over. It took almost a year to complete developg the game ad the developmet process could be dvded to two phases. The frst phase volved formulatg the basc structure of the game ad gatherg the vast amout of backgroud, techcal ad facal formato eeded to ehace the game s realsm. A major requremet of the game s that t must sophstcated eough to expose the studet who s playg the game to prepare hm for busess stuatos; ad yet ot too complcated (or complex) for hm to uderstad ad apply the basc maagemet prcples. The secod phase cossted of developg the game to a form that could be hadled by the departmet server ad wrtg all the ecessary software. At the secod phase, the varous documets to be used the game were also wrtte. The prototype game was thoroughly plot tested by the July 999 Semester studets order to elmate ay obvous flaws. I cojucto wth the lauch a teral competto was orgazed. Oly the were the fal documets produced ad the go-ahead gve to ru the 270

2 game as a school competto durg the comg academc year. THE SIMULATION GAME OBJECTIVES HOW THE EBIZGAME WAS EVOLVED A wdely accepted defto of smulato descrbes t as a pedagogcal method of attemptg to reflect actual stuatos through use of games, scearos, role-playg, soco-drama, ad decsos-makg expereces (Ades 983; Lodo 970). Ths defto provdes us wth a broad base from whch smulatos may be developed ad does ot lmt etrepreeurshp educators to the cotemporary oto that all smulatos are computer based. Ngee A Polytechc started usg smulatos etrepreeurshp courses July 99 whe t set up the campus as a practce outlet a retal shop wth a shop space of about 300 sq meters, called The Studet Shop. The shop was completely ru by 70 studets the Small Busess Maagemet course. Ths was where they got hads-o trag o how to start ther ow busess, how to keep vetory, take a loa from a bak, keep accouts ad geerate proft ad loss statemet at the ed of a semester. They also leart how to promote ad make sales. Ths experetal approach allows the studet to obta a level of compreheso ad skll developmet rug a small busess that s seldom attaed through tradtoal teachg methods. However, as the umber of etrepreeurshp studets doubled to more tha 300, t was foud dffcult, f ot mpossble, to roster so may studets to ru The Studet Shop. Thus July 994 The Studet Shop was dssolved ad replaced by m-stores the atrum of the Admstratve Block. Ths busess format offered greater flexblty to studets, as they were o loger lmted by space ad tme. They could ope ther stores beyod the scheduled tutoral hours as log as space was avalable ad they had o more classes. However, oe ma set back of these smulatos s that studets would cur huge moetary losses f ther goods were ot movg fast as they had oly about te weeks to clear ther goods. They were so obsessed wth sales that they eglected proper plag ad developg effectve strateges. I early 998 Mr Khoo Ch Hea, Prcpal of Ngee A Polytechc, floated the dea of developg our ow computer-smulated busess game for etrepreeurshp trag as the IT frastructure the campus was suffcet to cater to mass partcpato of ay computer smulato games. Oe ma advatage of a computer-smulated busess game s that t ca smulate a real lfe stuato where studets could experece rug a busess; ad yet do ot have to worry about currg persoal moetary losses. The tmele of rug the busess could also be made loger by the smulato so that studets ca practce log-term plag ad strategy formulato. Thus ths led to the developmet of the ebzgame ad July 999 the m-stores operato was dssolved ad replaced by the smulato game. Although t was always hoped that the ebzgame would be fu to compete, t was teded that t should meet several serous ad mportat educatoal objectves:. fosterg etrepreeural sprt studets by provdg them the experece of rug a busess whe workg as a team for a compay a smulated busess evromet; 2. develop creatve ad crtcal thkg sklls by provdg them the opportuty to pla ad formulate wg strateges; 3. hoe aalytcal sklls through the aalyss ad terpretato of facal formato ad applcato of busess cocepts for decsomakg; ad 4. promote teamwork amog studets. I addto to these objectves, the smulato also helps studets to () stregthe oral ad wrtte commucato sklls, (2) develop strog problem-solvg sklls, ad experece applcato of busess theores ad cocepts. The game must also meet the followg desg objectves:. A smple-to-use, easy-to-uderstad user terface for player ad game admstrator. 2. Adequate resposveess (web page loadg tme) for the game-play frot ed used by the players ad game admstrator. 3. A game that s capable of supportg ulmted umber of users ole cocurretly; oly lmted by the hardware archtecture. 4. Adequate flexblty the database desg to accommodate future ehacemets. 5. Itegrato wth the departmet s overall Eterprse Archtecture. The followg secto lsts some of the mportat busess cocepts that ca be leart from the smulato whch are essetal to the etrepreeurshp currculum:. Methods of sales forecastg, e.g. expoetal smoothg or smple tred aalyss 2. Factors fluecg sales volume, e.g. promoto ad R&D spedg 3. Stock ad producto plag 4. Cash flow ad budget plag 5. Dfferece betwee profts ad cash 6. Market research ad compettve aalyss 7. Tred aalyss for opportutes 8. Breakeve aalyss ad sales 9. Proft plag ad prce 0. Ecoomc ad maagemet cocepts lke shape of a cost curve, law of dmshg returs, ecoomes of scale. Rato aalyss ad bechmarkg for motorg 27

3 performace 2. Iterrelatos of departmets mportace of coordato ad proper plag DESCRIPTION OF THE SIMULATION ebzgame smulates a olgopolstc dustry. Three to eght compaes compete a sgle-product market sellg a cosumer good. At every perod, the partcpats submt decsos o prce, producto, promoto, plat vestmet, R & D, trag ad developmet, ad market research. The smulato automatcally grats repaymet or borrowg of loas. Each perod represets a quarter. The ecoomc evromet of the dustry s cotrolled by a umber of parameters cludg R&D, prce ad promoto sestvty factors. Thus the ecoomc evromet ca be chaged every perod by the game admstrator by adjustg the parameters. At the begg of every perod, each compay receves varous reports cludg the cost parameters report that cotas values of some cost parameters, e.g. plat purchase prce, credt lmt ad terest rate. Lkewse, at the ed of each perod, each compay receves varous reports cludg a dustry report o dustry bechmarks, market statstcs such as producto, sales ad vetory, ad market research data. A summary table of the varous reports s show Table. Studets ca eve use the bult- graphg program to draw charts for some of these market statstcs. Table :Varous Reports Geerated by the Smulato Idustry Report Plat Ivestmet Report Compay Report Labor Report Maagemet Report Marketg ad R & D Report Decso Aalyss Report Ivetory Report Face Report Cost Parameters Report Producto Report The usual competto cossts of two rouds, wth each roud made up of usually seve perods. It operates o a kock-out bass whereby the wers of the prelmary roud wll go o to compete the fal (ext) roud of play, ad the wer evetually emerges. I each roud, the teams are grouped to dfferet clusters of three to eght teams each. Each cluster plays a game, whch s depedet from the other games. However, all clusters beg each roud wth a detcal busess backgroud. At the ed of a roud, the performaces of partcpatg teams are evaluated o a set of crtera. The wg teams the proceed o to the ext roud of play. The wg crtera clude accumulated proft, sales growth, et proft marg, product attractveess, retur o equty, market share, ad plat capacty. As a learg exercse for studets takg the Maagg a Small Busess module, studets oly play oe roud ad tradtoally the smulato s ru mmedately after seve weeks of lectures coverg all the aspects of startg ad rug a small busess. It s also mportat to make studets go through a admstrator s brefg ad a tral ru before playg the game as certa aspects of game-play mght prove too complcated for a frst tme player. Before the game starts the role of each team member should be decded ad chose from oe of the followg:. Maagg Drector resposble for co-coordatg the decsos of the other team members 2. Sales Drector resposble for sales forecastg, break eve aalyss ad settg the prces 3. Marketg Drector resposble for market research, promoto ad R&D for product developmet 4. Producto Drector resposble for producto ad vetory cotrol 5. Facal Drector resposble for terpretg the accouts ad forecastg cash flow 6. Plag Drector resposble for plag plat capacty, trag ad developmet, ad proft plag (If less tha sx members per team are playg, the roles ca be combed, e.g. the Facal Drector ca be resposble for plag.) Much of the learg from a smulato or game takes place through processes of reflecto (Kolb 99) after the experece rather tha durg t. Log after the partcpato s over, learg cotues to take place. I ths respect t s crtcally mportat to help studets to process what they have expereced. Thus, at the ed of the Fal Roud, every team has to submt a wrtte report ( Drectors Report ) o the lessos leart from the game. The best drectors report team wll the be vted to gve a short oral presetato of ts report. Ths s followed wth a debrefg by the game admstrator. The debrefg helps the studets to lear from ther expereces by processg those expereces effectvely. WHAT THE GAME ADMINISTRATOR COULD DO The game s made extremely flexble to the game admstrator. It provdes a template for the admstrator to chage the product descrpto. Its default parameters ca easly be chaged. Thus the admstrator ca create oe game to smulate oe product ad aother game to smulate aother product; ad make both games smulate dfferet ecoomc codtos, cost structures ad market resposes. 272

4 The admstrator ca select whch market research data are made avalable to the studets ad at what prces. The game has a template for the admstrator to create ew qualtatve case studes. These case studes preset maagemet dlemmas or crtcal cdets faced by the compay. They are created usg Flash amato as show Fgure. Fgure. A Example of Crtcal Icdet WHAT THE PLAYER COULD DO As a tured-based game, the players make decsos every perod. They ca be the frst or last to make decsos. They ca call up data about past performace, facal records, promoto, R&D ad plat vestmet, operatg ad producto costs, or aythg else thought ecessary. Furthermore, the game has very teractve capabltes. The players ca commucate wth other players ole through the game webste. If they eed cosultato, they ca also commucate wth the game admstrator o a prvate bass. The game has a Joural for the admstrator to update the players about the chages the ecoomc evromet. Studets wll also be gve ews to read. The ews s dvded to two sectos: publc ews ad prvate ews. The prvate ews gves specfc advce to the players o ther curret stuato. Reports are geerated mmedately after the closg of each perod ad studets ca dsplay most of the market statstcs provded usg the bult- graphg program. HOW THE ACTUAL SIMULATION GAME WAS DEVELOPED We bega by researchg varous busess demad models that could be used for the game. It took us sx moths to buld a game model based o our requremets. The game model cossts of three compoets as show Fgure 2. The puts (decsos) etered are frst valdated to see that they are wth the lmts set by the game admstrator ad the game model. Other logcal costrats are also checked at ths pot. The valdated puts are the appled to the demad model together wth the hstory. The output of the demad model wll be saved as hstory ad feedback to the model later. The reports wll the be geerated based o the output of the demad model. 273

5 Fgure 2. The Game Model THE DEMAND MODEL The modelg of the demad model s the heart of the game. The desgg ad developg of ths model s prmarly a art. Theoretcal demad model was used as the basele ths model. Good desg s a ecessary but ot suffcet codto of a busess smulato. Therefore, real busess expereces from several experts were corporated to the model. Ths makes the model realstc ad practcal. The algorthm of the demad model s show below:. Calculate productvty of the frm 2. Calculate product qualty of the frm 3. Calculate the meas of the ecoomc parameters 4. Calculate the expoetal smoothed parameters 5. Calculate market demad 6. Calculate frm demad Ths demad model was mplemeted wth referece to the Suggested System for Modelg Demad by Steve C. Gold ad Thomas F. Pray s (990). There are three types of fuctoal forms the teral modelg of demad computerzed busess smulatos (Gold ad Pray, 990): lear, olear, ad log-lear. The lear form has the property of varable prce elastcty but costrats the margal mpacts of the depedet varables to be costat. The olear fuctos vary wdely form ad ature ad have propertes cosstet wth moder demad theory. Log-lear fuctos allow margal mpacts to chage wth the level of the depedet varable but ot flexble eough to model flecto pots. The demad model mplemeted the ebzgame cludes a umber of propertes:. The use of smple comparso to calculate the productvty of the frm 2. The use of accumulated R&D vestmet to calculate the product qualty 3. The use of harmoc mea to approxmate the market prce as compared to the covetoal mea calculato whch overstates the average dustry prce 4. The use of scalg factors ad expoetal smoothg to capture ter-temporal effects ad allow the desger to cotrol the mportace of hstory o curret demad 5. The use of multplcatve fuctoal form, whch s stable ad possesses varable elastctes. The followg sectos hghlght some of the algorthms used.. CALCULATE PRODUCTIVITY OF THE FIRM The productvty of the frm depeds o the vestmet the Trag & Developmet of the workers the frm. The frm s productvty s calculated usg Equato. TD Fp Bp Vp TD = + Hghest Fp s the frm s productvty TD s the frm s Trag & Developmet Vp s a varable set by the game admstrator Bp s the basele productvty set by the game admstrator 2. CALCULATE PRODUCT QUALITY OF THE FIRM Qualty of the Product depeds o the cumulatve R&D vestmet. Whe the game s frst created, a set of predefed values for the qualty levels are created usg Equato 2. QualtyLevel = R& D ( Y QualtyLevel) (2) MAX R&D MAX = Maxmum R&D lmt set by the game admstrator Y = desger s specfed value (Y>) () 274

6 3. CALCULATE THE MEANS FOR THE ECONOMIC PARAMETERS Averages for Promoto ad R&D are calculated usg Equato 4 ad 5 to determe the market demad later. As harmoc mea computes the average by weghtg low values relatvely more tha hgher values, t s used to calculate the average prce as show Equato 3. Average Pr ce = = p (3) P = ap + (-a)p o ; where 0 < a < (9) Promo = bpromo + (-b)promo o ; where 0 < b < (0) R&D = c R&D + (-c) R&D o ; where 0 < c < () P = expoetally smoothed prce Promo = expoetally smoothed Promoto R&D = expoetally smoothed R&D X = scalg factor of prce Y = scalg factor of promoto Z = scalg factor of R&D a = mpact of Prce over a durato b = mpact of Promoto over a durato c = mpact of R&D over a durato Average Pro moto = AverageR & D = = = = Total umber of frm p = frm s prce Promo = frm s Promoto R&D = frm s R&D ( Pr ) omo ( R & D ) 4. CALCULATE THE EXPONENTIAL SMOOTHED PARAMETERS (4) (5) Where subscrpt: o dcates a perod-old smoothed value dcates the most curret value 5. CALCULATE MARKET DEMAND The market demad depeds o the average prce, promoto ad R&D of the frms, the umber of frms ad the dsturbace factor. Frstly, the market demad s calculated usg Equato 2. The the result of Equato 2 s appled to Equato 3. Fally, the result Equato 3 s appled to Equato 4. Q g P omo R D ( g 2+ gp 3 ) ( 4 5Pr ) ( 6 7 & Pr g g omo & g = gr D) (2) Q = Q( ) + Q (3) Q = Q( + D) (4) The demad of the product ot oly depeds o the curret decsos but also o the hstorcal decsos. Expoetal smoothg s a coveet techque allowg smulato desgers to specfy the role ad mportace of hstory o curret demad. The parameters are multpled by a scalg factor before they are expoetally smoothed as show Equatos 6, 7 ad 8. These scalg factors are desger s specfed values. The results from Equatos 6, 7 ad 8 are appled to Equatos 9, 0 ad respectvely. X P= P + 00 Y Pr omo = Pr omo + 00 Z R& D = R& D + 00 (6) (7) (8) Q = Idustry demad P = Average Prce the dustry Promo = Average promoto the dustry R&D = Average R&D the dustry = Number of frms D = Dsturbace factor g to g 7 are desger s specfed values. g s a scalg factor 6. CALCULATE FIRM DEMAND There are 3 steps to calculate the frm s demad. The frst step s to calculate the frm s total weght usg a weghtg fucto. It s a varable elastcty multplcatve fucto. It determes the magtude of the value that s used to calculate the market share of the frm as a fucto of the total market demad. 275

7 WkPk = ( + ) (Pr omo+ k) ( R& D+ k) ( PQ+ k ) ( k2+ kp 3 ) ( k5+ km 6 ) ( k8+ kr 9 ) ( k+ k2td ) W = weght of the frm P = expoetally smoothed prce of the frm Promo = expoetally smoothed promoto of the frm R&D = expoetally smoothed R&D of the frm PQ = Product Qualty of the frm k 0 to k 2 = desger s specfed values (5) The values assged to the parameters (k 2, k 3, k 5, k 6, k 8, k 9, k, k 2 ) deped o the desger s specfcato cocerg frm-level elastcty. The purpose of k, k 4, k 7 ad k 0 s to prevet the weght from becomg zero. K 0 s a scalg factor ad ca be arbtrarly assged a value to esure that the frm s weghts are ot too large or too small for computato accuracy. The ext step s to calculate the frm s share. The share equato s show Equato 6. S = W = W S = frm s Share W = weght of the frm (6) The frm s share wll be coverted to quatty usg the quatty fucto as show Equato 7. q = SQ (7) S = frm s Share Q = Idustry demad q = Quatty demad of the frm Fally the dustry demad s recalculated based o the summato of the frm s demad as show Equato 8. Ths s to avod roudg error that may occur. Q= q (8) = ARCHITECTURE After the prototype of the game model was verfed, the game model was bult to SQL Server usg storedprocedures ad fuctos. Most of the busess logc was processed the database. Next, we bega to desg the webste terface. I order to make ths webste scalable, most of the processg was doe o the clet-sde (web browser). ActveX cotrols, Flash applets, ad DOM were used. The graphs were redered o the clet s web browser usg a ActveX cotrol. The reports were redered o the clet s web browser usg XML, XSLT ad DOM. All the reports geerated by the game were saved as XML fles whe the perod was closed. The closg of the perod was the most processor tesve task of the game. The decsos of all the players ad the settgs set by the admstrator were appled to the game model ths task. The reports of the perod were also geerated ths task. All ths processg was dstrbuted betwee the database server ad the web applcato server. The busess logc was calculated the database server; whereas the reports were geerated by the web server ad saved a fle server. A pool of persstece database coecto was created whe the game was frst loaded the server. Ths was to reduce the overhead of havg recreatg the same coecto aga ad aga whe the game was playg. As show Fgure 3, the software archtecture of the game s dvded to 5 logc layers:. User Servce Layer: Ths layer provdes access for clets (PC ad Pocket PC) to the applcato. It cossts of web pages ad web servces. 2. Busess Layer: Ths layer provdes terfaces to the User Servce Layer to hadle player s decsos, report browsg, web avgato, ews browsg, chattg fuctoalty ad admstrato of the game. 3. Data Access Layer: Ths layer provdes data servces to the Busess Layer. Coecto Poolg was mplemeted at ths layer. 4. System Framework: Ths layer provdes applcato cofgurato, excepto hadlg ad loggg of the game. 5. Commo Abstract: Ths layer provdes commo structures used the game. Q = Idustry demad q = Quatty demad of the frm 276

8 Fgure 3. Software Archtecture The game was hosted o two web servers, whch are coected to a load balacer. The reports were stored as XML fles aother server. The database was stored a dedcated database server the web farm. The hardware archtecture s show Fgure 4. Fgure 4. Hardware Archtecture By addg addtoal web server we wll crease the capacty of the applcato. The reports of the game are saved as XML fles the XML Report Server. Ths s to off load the database whe the game starts ad the players are accessg the reports. By dog so the game s able to hadle a larger umber of cocurret users. A servce aget was bult to allow the game admstrator to schedule batch jobs (for closg of a perod) to ru automatcally o the server. A computer-automated stress test was coducted wth the use of three computers to determe the maxmum load of the game. Sevety-two cocurret users were smulated to play the game. Eght users a group were smulated to play a game. Each user was smulated to access the game cotuously durg the stress test ad to put radom values to the game. Ths was to provde a more accurate load-testg result. The game was able to hadle a maxmum of e cocurret competto clusters durg the stress test. 277

9 THE COMPETITIONS HELD BETWEEN 999 AND 2002 Thrty-fve teams comprsg 79 studets takg the Maagg a Small Busess (MSB) module, took part the frst ru of the ebzgame competto, whch was held the July 999 Semester. The competto was the exteded to secodary three studets the subsequet two years. I the Year 200 competto, twety-oe teams (oe team per school) took part; ad the Year 2002 competto, fortyseve teams took part. They played the game from ther ow schools, as the game was web-based. At the ed of the Prelmary Roud the best team from each cluster proceeded o to the Fal Roud, whch was held NgeeA Campus. The wers were gve attractve przes. For the secodary school studets, they have to udergo two separate days of etrepreeurshp trag before playg the game. The trag gves them a overvew of maagemet prcples ad cocepts ad some smple accoutg kowledge. All MSB teams were asked to complete a detaled questoare, whch was subsequetly aalyzed by the teachg staff of that module. The resposes to Questo 0 the questoare show a overall hgh level of satsfacto (see Table 2). The feedback receved from the partcpatg secodary schools had bee a great success, ad t was clear that the competto should be ru aga. Table 2: Resposes to Questo 0 of the Questoare, 2002 Jauary Semester 0. Please dcate whether the game helps you : Agree(%) Usure(%) Dsagree(%) (a) Uderstadg cocepts (b) Practcal applcatos of cocepts (c) Developg fredly relatos/rapport The game s stll ru regularly wth NgeeA as part of hads-o trag for studets takg the Maagg a Small Busess module, ad s also ru as a ope competto for secodary schools. The co-authors (who were prmarly resposble for the computer modelg) have ot bee allowed to rest o ther laurels. Wth the support from Teachg & Learg Cetre (TLC) ad Ngee A Idustry Techology Exchage Cetre (NITEC) they wll approach a software compay to get t coverted to a Chese verso ad lauch t Cha. Cha s chose because the cultural dffereces betwee Sgapore ad Cha are ot great. Furthermore Cha s kee to try out ew methods of teachg etrepreeurshp based o feedback from recet vsts to Cha by NgeeA staff. CONCLUSION I ths paper we descrbed how the ebzgame, a scalable web-based smulato game, offers a soluto to the problem of helpg studets the Maagg a Small Busess module atta the ecessary competeces both based o ad buldg upo a currculum whch smulato plays a cetral role. The ebzgame has bult- features (parameters) whereby the admstrator ca vary the complexty of the game so that t could ft wth ay etrepreeurshp currculum requremets ragg from Secodary School to Polytechc levels. The game s webbased so t s accessble to partcpats aywhere ad ths meas eve studets from dfferet places (eve coutres) ca come together as a team to play t. Ths opes a ew dmeso to cross-cultural behavoral learg. The dvdual learer s experece s a experece of dscovery ad of learg about the realty beg modeled by explorg t. Its structoal value les the trasferablty ad applcablty of the choces made to other lfe actvtes ad ther behavoral choces there. Ths ca be called the valdty of the smulato or game (Lederma, 994). REFERENCES Ades, Joh. (983). The use ad developmet of smulato educatoal admstrato. Upublshed mauscrpt. Kolb, D.A., Rub, I.M., & Oslad, J.S. (99). Orgasatoal Behavour-A Experetal Approach. Eglewood Clffs, NJ: Pretce-Hall. Lederma, L.C. (994). Smulato ad Gamg: Vol. 25. Gve a small chld a hammer ad soo everythg eeds hammerg. Lodo, H. J. (970). The futlty of testg: Smulato as a "test" case. Educatoal Leadershp, Steve C. Gold, & Thomas F. Pray. (990). James W. Getry (Ed.), Gude To Busess Gamg ad Experetal Learg. East Bruswck / Page, Lodo: NICHOLS/GP. 278

Average Price Ratios

Average Price Ratios Average Prce Ratos Morgstar Methodology Paper August 3, 2005 2005 Morgstar, Ic. All rghts reserved. The formato ths documet s the property of Morgstar, Ic. Reproducto or trascrpto by ay meas, whole or

More information

CHAPTER 2. Time Value of Money 6-1

CHAPTER 2. Time Value of Money 6-1 CHAPTER 2 Tme Value of Moey 6- Tme Value of Moey (TVM) Tme Les Future value & Preset value Rates of retur Autes & Perpetutes Ueve cash Flow Streams Amortzato 6-2 Tme les 0 2 3 % CF 0 CF CF 2 CF 3 Show

More information

10.5 Future Value and Present Value of a General Annuity Due

10.5 Future Value and Present Value of a General Annuity Due Chapter 10 Autes 371 5. Thomas leases a car worth $4,000 at.99% compouded mothly. He agrees to make 36 lease paymets of $330 each at the begg of every moth. What s the buyout prce (resdual value of the

More information

APPENDIX III THE ENVELOPE PROPERTY

APPENDIX III THE ENVELOPE PROPERTY Apped III APPENDIX III THE ENVELOPE PROPERTY Optmzato mposes a very strog structure o the problem cosdered Ths s the reaso why eoclasscal ecoomcs whch assumes optmzg behavour has bee the most successful

More information

Classic Problems at a Glance using the TVM Solver

Classic Problems at a Glance using the TVM Solver C H A P T E R 2 Classc Problems at a Glace usg the TVM Solver The table below llustrates the most commo types of classc face problems. The formulas are gve for each calculato. A bref troducto to usg the

More information

The impact of service-oriented architecture on the scheduling algorithm in cloud computing

The impact of service-oriented architecture on the scheduling algorithm in cloud computing Iteratoal Research Joural of Appled ad Basc Sceces 2015 Avalable ole at www.rjabs.com ISSN 2251-838X / Vol, 9 (3): 387-392 Scece Explorer Publcatos The mpact of servce-oreted archtecture o the schedulg

More information

Report 52 Fixed Maturity EUR Industrial Bond Funds

Report 52 Fixed Maturity EUR Industrial Bond Funds Rep52, Computed & Prted: 17/06/2015 11:53 Report 52 Fxed Maturty EUR Idustral Bod Fuds From Dec 2008 to Dec 2014 31/12/2008 31 December 1999 31/12/2014 Bechmark Noe Defto of the frm ad geeral formato:

More information

T = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are :

T = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are : Bullets bods Let s descrbe frst a fxed rate bod wthout amortzg a more geeral way : Let s ote : C the aual fxed rate t s a percetage N the otoal freq ( 2 4 ) the umber of coupo per year R the redempto of

More information

Projection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li

Projection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li Iteratoal Joural of Scece Vol No7 05 ISSN: 83-4890 Proecto model for Computer Network Securty Evaluato wth terval-valued tutostc fuzzy formato Qgxag L School of Software Egeerg Chogqg Uversty of rts ad

More information

Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R =

Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R = Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS Objectves of the Topc: Beg able to formalse ad solve practcal ad mathematcal problems, whch the subjects of loa amortsato ad maagemet of cumulatve fuds are

More information

1. The Time Value of Money

1. The Time Value of Money Corporate Face [00-0345]. The Tme Value of Moey. Compoudg ad Dscoutg Captalzato (compoudg, fdg future values) s a process of movg a value forward tme. It yelds the future value gve the relevat compoudg

More information

FINANCIAL MATHEMATICS 12 MARCH 2014

FINANCIAL MATHEMATICS 12 MARCH 2014 FINNCIL MTHEMTICS 12 MRCH 2014 I ths lesso we: Lesso Descrpto Make use of logarthms to calculate the value of, the tme perod, the equato P1 or P1. Solve problems volvg preset value ad future value autes.

More information

Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering

Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering Moder Appled Scece October, 2009 Applcatos of Support Vector Mache Based o Boolea Kerel to Spam Flterg Shugag Lu & Keb Cu School of Computer scece ad techology, North Cha Electrc Power Uversty Hebe 071003,

More information

RUSSIAN ROULETTE AND PARTICLE SPLITTING

RUSSIAN ROULETTE AND PARTICLE SPLITTING RUSSAN ROULETTE AND PARTCLE SPLTTNG M. Ragheb 3/7/203 NTRODUCTON To stuatos are ecoutered partcle trasport smulatos:. a multplyg medum, a partcle such as a eutro a cosmc ray partcle or a photo may geerate

More information

The Time Value of Money

The Time Value of Money The Tme Value of Moey 1 Iversemet Optos Year: 1624 Property Traded: Mahatta Islad Prce : $24.00, FV of $24 @ 6%: FV = $24 (1+0.06) 388 = $158.08 bllo Opto 1 0 1 2 3 4 5 t ($519.37) 0 0 0 0 $1,000 Opto

More information

Performance Attribution. Methodology Overview

Performance Attribution. Methodology Overview erformace Attrbuto Methodology Overvew Faba SUAREZ March 2004 erformace Attrbuto Methodology 1.1 Itroducto erformace Attrbuto s a set of techques that performace aalysts use to expla why a portfolo's performace

More information

Automated Event Registration System in Corporation

Automated Event Registration System in Corporation teratoal Joural of Advaces Computer Scece ad Techology JACST), Vol., No., Pages : 0-0 0) Specal ssue of CACST 0 - Held durg 09-0 May, 0 Malaysa Automated Evet Regstrato System Corporato Zafer Al-Makhadmee

More information

Banking (Early Repayment of Housing Loans) Order, 5762 2002 1

Banking (Early Repayment of Housing Loans) Order, 5762 2002 1 akg (Early Repaymet of Housg Loas) Order, 5762 2002 y vrtue of the power vested me uder Secto 3 of the akg Ordace 94 (hereafter, the Ordace ), followg cosultato wth the Commttee, ad wth the approval of

More information

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree , pp.277-288 http://dx.do.org/10.14257/juesst.2015.8.1.25 A New Bayesa Network Method for Computg Bottom Evet's Structural Importace Degree usg Jotree Wag Yao ad Su Q School of Aeroautcs, Northwester Polytechcal

More information

Green Master based on MapReduce Cluster

Green Master based on MapReduce Cluster Gree Master based o MapReduce Cluster Mg-Zh Wu, Yu-Chag L, We-Tsog Lee, Yu-Su L, Fog-Hao Lu Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of

More information

6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis

6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis 6.7 Network aalyss Le data that explctly store topologcal formato are called etwork data. Besdes spatal operatos, several methods of spatal aalyss are applcable to etwork data. Fgure: Network data Refereces

More information

ECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil

ECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil ECONOMIC CHOICE OF OPTIMUM FEEDER CABE CONSIDERING RISK ANAYSIS I Camargo, F Fgueredo, M De Olvera Uversty of Brasla (UB) ad The Brazla Regulatory Agecy (ANEE), Brazl The choce of the approprate cable

More information

A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS

A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS L et al.: A Dstrbuted Reputato Broker Framework for Web Servce Applcatos A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS Kwe-Jay L Departmet of Electrcal Egeerg ad Computer Scece

More information

DYNAMIC FACTOR ANALYSIS OF FINANCIAL VIABILITY OF LATVIAN SERVICE SECTOR COMPANIES

DYNAMIC FACTOR ANALYSIS OF FINANCIAL VIABILITY OF LATVIAN SERVICE SECTOR COMPANIES DYNAMIC FACTOR ANALYSIS OF FINANCIAL VIABILITY OF LATVIAN SERVICE SECTOR COMPANIES Nadezhda Koleda 1, Natalja Lace 2 1 Rga Techcal Uversty, Latva, [email protected] 2 Rga Techcal Uversty, Latva, [email protected]

More information

of the relationship between time and the value of money.

of the relationship between time and the value of money. TIME AND THE VALUE OF MONEY Most agrbusess maagers are famlar wth the terms compoudg, dscoutg, auty, ad captalzato. That s, most agrbusess maagers have a tutve uderstadg that each term mples some relatoshp

More information

Numerical Methods with MS Excel

Numerical Methods with MS Excel TMME, vol4, o.1, p.84 Numercal Methods wth MS Excel M. El-Gebely & B. Yushau 1 Departmet of Mathematcal Sceces Kg Fahd Uversty of Petroleum & Merals. Dhahra, Saud Araba. Abstract: I ths ote we show how

More information

IDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki

IDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki IDENIFICAION OF HE DYNAMICS OF HE GOOGLE S RANKING ALGORIHM A. Khak Sedgh, Mehd Roudak Cotrol Dvso, Departmet of Electrcal Egeerg, K.N.oos Uversty of echology P. O. Box: 16315-1355, ehra, Ira [email protected],

More information

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability Egeerg, 203, 5, 4-8 http://dx.do.org/0.4236/eg.203.59b003 Publshed Ole September 203 (http://www.scrp.org/joural/eg) Mateace Schedulg of Dstrbuto System wth Optmal Ecoomy ad Relablty Syua Hog, Hafeg L,

More information

Load and Resistance Factor Design (LRFD)

Load and Resistance Factor Design (LRFD) 53:134 Structural Desg II Load ad Resstace Factor Desg (LRFD) Specfcatos ad Buldg Codes: Structural steel desg of buldgs the US s prcpally based o the specfcatos of the Amerca Isttute of Steel Costructo

More information

A Parallel Transmission Remote Backup System

A Parallel Transmission Remote Backup System 2012 2d Iteratoal Coferece o Idustral Techology ad Maagemet (ICITM 2012) IPCSIT vol 49 (2012) (2012) IACSIT Press, Sgapore DOI: 107763/IPCSIT2012V495 2 A Parallel Trasmsso Remote Backup System Che Yu College

More information

TESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION

TESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION TESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION Cosm TOMOZEI 1 Assstat-Lecturer, PhD C. Vasle Alecsadr Uversty of Bacău, Romaa Departmet of Mathematcs

More information

Chapter 3 0.06 = 3000 ( 1.015 ( 1 ) Present Value of an Annuity. Section 4 Present Value of an Annuity; Amortization

Chapter 3 0.06 = 3000 ( 1.015 ( 1 ) Present Value of an Annuity. Section 4 Present Value of an Annuity; Amortization Chapter 3 Mathematcs of Face Secto 4 Preset Value of a Auty; Amortzato Preset Value of a Auty I ths secto, we wll address the problem of determg the amout that should be deposted to a accout ow at a gve

More information

The Application of Intuitionistic Fuzzy Set TOPSIS Method in Employee Performance Appraisal

The Application of Intuitionistic Fuzzy Set TOPSIS Method in Employee Performance Appraisal Vol.8, No.3 (05), pp.39-344 http://dx.do.org/0.457/uesst.05.8.3.3 The pplcato of Itutostc Fuzzy Set TOPSIS Method Employee Performace pprasal Wag Yghu ad L Welu * School of Ecoomcs ad Maagemet, Shazhuag

More information

A Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time

A Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time Joural of Na Ka, Vol. 0, No., pp.5-9 (20) 5 A Study of Urelated Parallel-Mache Schedulg wth Deteroratg Mateace Actvtes to Mze the Total Copleto Te Suh-Jeq Yag, Ja-Yuar Guo, Hs-Tao Lee Departet of Idustral

More information

Fault Tree Analysis of Software Reliability Allocation

Fault Tree Analysis of Software Reliability Allocation Fault Tree Aalyss of Software Relablty Allocato Jawe XIANG, Kokch FUTATSUGI School of Iformato Scece, Japa Advaced Isttute of Scece ad Techology - Asahda, Tatsuokuch, Ishkawa, 92-292 Japa ad Yaxag HE Computer

More information

The analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0

The analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0 Chapter 2 Autes ad loas A auty s a sequece of paymets wth fxed frequecy. The term auty orgally referred to aual paymets (hece the ame), but t s ow also used for paymets wth ay frequecy. Autes appear may

More information

The paper presents Constant Rebalanced Portfolio first introduced by Thomas

The paper presents Constant Rebalanced Portfolio first introduced by Thomas Itroducto The paper presets Costat Rebalaced Portfolo frst troduced by Thomas Cover. There are several weakesses of ths approach. Oe s that t s extremely hard to fd the optmal weghts ad the secod weakess

More information

Discrete-Event Simulation of Network Systems Using Distributed Object Computing

Discrete-Event Simulation of Network Systems Using Distributed Object Computing Dscrete-Evet Smulato of Network Systems Usg Dstrbuted Object Computg Welog Hu Arzoa Ceter for Itegratve M&S Computer Scece & Egeerg Dept. Fulto School of Egeerg Arzoa State Uversty, Tempe, Arzoa, 85281-8809

More information

SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN

SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN Wojcech Zelńsk Departmet of Ecoometrcs ad Statstcs Warsaw Uversty of Lfe Sceces Nowoursyowska 66, -787 Warszawa e-mal: wojtekzelsk@statystykafo Zofa Hausz,

More information

AP Statistics 2006 Free-Response Questions Form B

AP Statistics 2006 Free-Response Questions Form B AP Statstcs 006 Free-Respose Questos Form B The College Board: Coectg Studets to College Success The College Board s a ot-for-proft membershp assocato whose msso s to coect studets to college success ad

More information

Forecasting Trend and Stock Price with Adaptive Extended Kalman Filter Data Fusion

Forecasting Trend and Stock Price with Adaptive Extended Kalman Filter Data Fusion 2011 Iteratoal Coferece o Ecoomcs ad Face Research IPEDR vol.4 (2011 (2011 IACSIT Press, Sgapore Forecastg Tred ad Stoc Prce wth Adaptve Exteded alma Flter Data Fuso Betollah Abar Moghaddam Faculty of

More information

ANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data

ANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data ANOVA Notes Page Aalss of Varace for a Oe-Wa Classfcato of Data Cosder a sgle factor or treatmet doe at levels (e, there are,, 3, dfferet varatos o the prescrbed treatmet) Wth a gve treatmet level there

More information

The Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev

The Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev The Gompertz-Makeham dstrbuto by Fredrk Norström Master s thess Mathematcal Statstcs, Umeå Uversty, 997 Supervsor: Yur Belyaev Abstract Ths work s about the Gompertz-Makeham dstrbuto. The dstrbuto has

More information

Statistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology

Statistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology I The Name of God, The Compassoate, The ercful Name: Problems' eys Studet ID#:. Statstcal Patter Recogto (CE-725) Departmet of Computer Egeerg Sharf Uversty of Techology Fal Exam Soluto - Sprg 202 (50

More information

A PRACTICAL SOFTWARE TOOL FOR GENERATOR MAINTENANCE SCHEDULING AND DISPATCHING

A PRACTICAL SOFTWARE TOOL FOR GENERATOR MAINTENANCE SCHEDULING AND DISPATCHING West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) 57-63 A RACTICAL SOFTWARE TOOL FOR GENERATOR MAINTENANCE SCHEDULING AND DISATCHING C. Sharma & S. Bahadoorsgh

More information

Capacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy

Capacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy SCHOOL OF OPERATIONS RESEARCH AND INDUSTRIAL ENGINEERING COLLEGE OF ENGINEERING CORNELL UNIVERSITY ITHACA, NY 4853-380 TECHNICAL REPORT Jue 200 Capactated Producto Plag ad Ivetory Cotrol whe Demad s Upredctable

More information

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ " 1

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ  1 STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS Recall Assumpto E(Y x) η 0 + η x (lear codtoal mea fucto) Data (x, y ), (x 2, y 2 ),, (x, y ) Least squares estmator ˆ E (Y x) ˆ " 0 + ˆ " x, where ˆ

More information

Impact of Interference on the GPRS Multislot Link Level Performance

Impact of Interference on the GPRS Multislot Link Level Performance Impact of Iterferece o the GPRS Multslot Lk Level Performace Javer Gozalvez ad Joh Dulop Uversty of Strathclyde - Departmet of Electroc ad Electrcal Egeerg - George St - Glasgow G-XW- Scotlad Ph.: + 8

More information

Paper: Events Sponsorship: Managing a Mutually Beneficial Partnership

Paper: Events Sponsorship: Managing a Mutually Beneficial Partnership 5th Iteratoal Scetfc Coferece Toursm Treds ad Advaces the 21st Cetury May 30-Jue 2, 2013, Rhodes, Greece Paper: Evets Sposorshp: Maagg a Mutually Beefcal Partershp Dr Maros D. SOTERIADES Departmet of Toursm

More information

Application of Grey Relational Analysis in Computer Communication

Application of Grey Relational Analysis in Computer Communication Applcato of Grey Relatoal Aalyss Computer Commucato Network Securty Evaluato Jgcha J Applcato of Grey Relatoal Aalyss Computer Commucato Network Securty Evaluato *1 Jgcha J *1, Frst ad Correspodg Author

More information

The Digital Signature Scheme MQQ-SIG

The Digital Signature Scheme MQQ-SIG The Dgtal Sgature Scheme MQQ-SIG Itellectual Property Statemet ad Techcal Descrpto Frst publshed: 10 October 2010, Last update: 20 December 2010 Dalo Glgorosk 1 ad Rue Stesmo Ødegård 2 ad Rue Erled Jese

More information

Report 05 Global Fixed Income

Report 05 Global Fixed Income Report 05 Global Fxed Icome From Dec 1999 to Dec 2014 31/12/1999 31 December 1999 31/12/2014 Rep05, Computed & Prted: 17/06/2015 11:24 New Performace Idcator (01/01/12) 100% Barclays Aggregate Global Credt

More information

AN ALGORITHM ABOUT PARTNER SELECTION PROBLEM ON CLOUD SERVICE PROVIDER BASED ON GENETIC

AN ALGORITHM ABOUT PARTNER SELECTION PROBLEM ON CLOUD SERVICE PROVIDER BASED ON GENETIC Joural of Theoretcal ad Appled Iformato Techology 0 th Aprl 204. Vol. 62 No. 2005-204 JATIT & LLS. All rghts reserved. ISSN: 992-8645 www.jatt.org E-ISSN: 87-395 AN ALGORITHM ABOUT PARTNER SELECTION PROBLEM

More information

Optimal multi-degree reduction of Bézier curves with constraints of endpoints continuity

Optimal multi-degree reduction of Bézier curves with constraints of endpoints continuity Computer Aded Geometrc Desg 19 (2002 365 377 wwwelsevercom/locate/comad Optmal mult-degree reducto of Bézer curves wth costrats of edpots cotuty Guo-Dog Che, Guo-J Wag State Key Laboratory of CAD&CG, Isttute

More information

Abraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract

Abraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract Preset Value of Autes Uder Radom Rates of Iterest By Abraham Zas Techo I.I.T. Hafa ISRAEL ad Uversty of Hafa, Hafa ISRAEL Abstract Some attempts were made to evaluate the future value (FV) of the expected

More information

How To Make A Supply Chain System Work

How To Make A Supply Chain System Work Iteratoal Joural of Iformato Techology ad Kowledge Maagemet July-December 200, Volume 2, No. 2, pp. 3-35 LATERAL TRANSHIPMENT-A TECHNIQUE FOR INVENTORY CONTROL IN MULTI RETAILER SUPPLY CHAIN SYSTEM Dharamvr

More information

FINANCIAL FORMULAE. Amount of One or Future Value of One ($1, 1, 1, etc.)... 2. Present Value (or Present Worth) of One ($1, 1, 1, etc.)...

FINANCIAL FORMULAE. Amount of One or Future Value of One ($1, 1, 1, etc.)... 2. Present Value (or Present Worth) of One ($1, 1, 1, etc.)... Amout of Oe or Future Value of Oe ($,,, etc.)... 2 Preset Value (or Preset Worth) of Oe ($,,, etc.)... 2 Amout of Oe per Perod... 3 or Future Value of Oe per Perod Preset Value (or Preset Worth) of Oe

More information

Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds.

Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds. Proceedgs of the 21 Wter Smulato Coferece B. Johasso, S. Ja, J. Motoya-Torres, J. Huga, ad E. Yücesa, eds. EMPIRICAL METHODS OR TWO-ECHELON INVENTORY MANAGEMENT WITH SERVICE LEVEL CONSTRAINTS BASED ON

More information

ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS. Janne Peisa Ericsson Research 02420 Jorvas, Finland. Michael Meyer Ericsson Research, Germany

ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS. Janne Peisa Ericsson Research 02420 Jorvas, Finland. Michael Meyer Ericsson Research, Germany ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS Jae Pesa Erco Research 4 Jorvas, Flad Mchael Meyer Erco Research, Germay Abstract Ths paper proposes a farly complex model to aalyze the performace of

More information

Credibility Premium Calculation in Motor Third-Party Liability Insurance

Credibility Premium Calculation in Motor Third-Party Liability Insurance Advaces Mathematcal ad Computatoal Methods Credblty remum Calculato Motor Thrd-arty Lablty Isurace BOHA LIA, JAA KUBAOVÁ epartmet of Mathematcs ad Quattatve Methods Uversty of ardubce Studetská 95, 53

More information

ANNEX 77 FINANCE MANAGEMENT. (Working material) Chief Actuary Prof. Gaida Pettere BTA INSURANCE COMPANY SE

ANNEX 77 FINANCE MANAGEMENT. (Working material) Chief Actuary Prof. Gaida Pettere BTA INSURANCE COMPANY SE ANNEX 77 FINANCE MANAGEMENT (Workg materal) Chef Actuary Prof. Gada Pettere BTA INSURANCE COMPANY SE 1 FUNDAMENTALS of INVESTMENT I THEORY OF INTEREST RATES 1.1 ACCUMULATION Iterest may be regarded as

More information

Optimal replacement and overhaul decisions with imperfect maintenance and warranty contracts

Optimal replacement and overhaul decisions with imperfect maintenance and warranty contracts Optmal replacemet ad overhaul decsos wth mperfect mateace ad warraty cotracts R. Pascual Departmet of Mechacal Egeerg, Uversdad de Chle, Caslla 2777, Satago, Chle Phoe: +56-2-6784591 Fax:+56-2-689657 [email protected]

More information

An SVR-Based Data Farming Technique for Web Application

An SVR-Based Data Farming Technique for Web Application A SVR-Based Data Farmg Techque for Web Appcato Ja L 1 ad Mjg Peg 2 1 Schoo of Ecoomcs ad Maagemet, Behag Uversty 100083 Bejg, P.R. Cha [email protected] 2 Isttute of Systems Scece ad Techoogy, Wuy Uversty, Jagme

More information

Optimization Model in Human Resource Management for Job Allocation in ICT Project

Optimization Model in Human Resource Management for Job Allocation in ICT Project Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project Saghamtra Mohaty Malaya Kumar Nayak 2 2 Professor ad Head Research

More information

Optimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks

Optimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks Optmal Packetzato Iterval for VoIP Applcatos Over IEEE 802.16 Networks Sheha Perera Harsha Srsea Krzysztof Pawlkowsk Departmet of Electrcal & Computer Egeerg Uversty of Caterbury New Zealad [email protected]

More information

COST VOLUME PROFIT MODEL, THE BREAK -EVEN POINT AND THE DECISION MAKING PROCESS IN THE HOSPITALITY INDUSTRY

COST VOLUME PROFIT MODEL, THE BREAK -EVEN POINT AND THE DECISION MAKING PROCESS IN THE HOSPITALITY INDUSTRY COST VOLUME PROFIT MODEL, THE BREAK -EVEN POINT AND THE DECISION MAKING PROCESS IN THE HOSPITALITY INDUSTRY Brcu Sor Uversty December 1st, 1918 Alba Iula Faculty of Sceces Scor e Carme Uversty of Oradea

More information

Beta. A Statistical Analysis of a Stock s Volatility. Courtney Wahlstrom. Iowa State University, Master of School Mathematics. Creative Component

Beta. A Statistical Analysis of a Stock s Volatility. Courtney Wahlstrom. Iowa State University, Master of School Mathematics. Creative Component Beta A Statstcal Aalyss of a Stock s Volatlty Courtey Wahlstrom Iowa State Uversty, Master of School Mathematcs Creatve Compoet Fall 008 Amy Froelch, Major Professor Heather Bolles, Commttee Member Travs

More information

Efficient Traceback of DoS Attacks using Small Worlds in MANET

Efficient Traceback of DoS Attacks using Small Worlds in MANET Effcet Traceback of DoS Attacks usg Small Worlds MANET Yog Km, Vshal Sakhla, Ahmed Helmy Departmet. of Electrcal Egeerg, Uversty of Souther Calfora, U.S.A {yogkm, sakhla, helmy}@ceg.usc.edu Abstract Moble

More information

ERP System Flexibility Measurement Based on Fuzzy Analytic Network Process

ERP System Flexibility Measurement Based on Fuzzy Analytic Network Process JOURNAL OF SOFTWARE, VOL. 8, NO. 8, AUGUST 20 4 ERP System Flexblty Measuremet Based o Fuzzy Aalytc Netork Process Xaoguag Zhou ad Bo Lv Doglg School of Ecoomcs ad Maagemet, Uversty of Scece ad Techology

More information

Load Balancing Algorithm based Virtual Machine Dynamic Migration Scheme for Datacenter Application with Optical Networks

Load Balancing Algorithm based Virtual Machine Dynamic Migration Scheme for Datacenter Application with Optical Networks 0 7th Iteratoal ICST Coferece o Commucatos ad Networkg Cha (CHINACOM) Load Balacg Algorthm based Vrtual Mache Dyamc Mgrato Scheme for Dataceter Applcato wth Optcal Networks Xyu Zhag, Yogl Zhao, X Su, Ruyg

More information

Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011

Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011 Cyber Jourals: Multdscplary Jourals cece ad Techology, Joural of elected Areas Telecommucatos (JAT), Jauary dto, 2011 A ovel rtual etwork Mappg Algorthm for Cost Mmzg ZHAG hu-l, QIU Xue-sog tate Key Laboratory

More information

Dynamic Two-phase Truncated Rayleigh Model for Release Date Prediction of Software

Dynamic Two-phase Truncated Rayleigh Model for Release Date Prediction of Software J. Software Egeerg & Applcatos 3 63-69 do:.436/jsea..367 Publshed Ole Jue (http://www.scrp.org/joural/jsea) Dyamc Two-phase Trucated Raylegh Model for Release Date Predcto of Software Lafe Qa Qgchua Yao

More information

A particle Swarm Optimization-based Framework for Agile Software Effort Estimation

A particle Swarm Optimization-based Framework for Agile Software Effort Estimation The Iteratoal Joural Of Egeerg Ad Scece (IJES) olume 3 Issue 6 Pages 30-36 204 ISSN (e): 239 83 ISSN (p): 239 805 A partcle Swarm Optmzato-based Framework for Agle Software Effort Estmato Maga I, & 2 Blamah

More information

Reinsurance and the distribution of term insurance claims

Reinsurance and the distribution of term insurance claims Resurace ad the dstrbuto of term surace clams By Rchard Bruyel FIAA, FNZSA Preseted to the NZ Socety of Actuares Coferece Queestow - November 006 1 1 Itroducto Ths paper vestgates the effect of resurace

More information

DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT

DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT ESTYLF08, Cuecas Meras (Meres - Lagreo), 7-9 de Septembre de 2008 DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT José M. Mergó Aa M. Gl-Lafuete Departmet of Busess Admstrato, Uversty of Barceloa

More information

Using Phase Swapping to Solve Load Phase Balancing by ADSCHNN in LV Distribution Network

Using Phase Swapping to Solve Load Phase Balancing by ADSCHNN in LV Distribution Network Iteratoal Joural of Cotrol ad Automato Vol.7, No.7 (204), pp.-4 http://dx.do.org/0.4257/jca.204.7.7.0 Usg Phase Swappg to Solve Load Phase Balacg by ADSCHNN LV Dstrbuto Network Chu-guo Fe ad Ru Wag College

More information

Dynamic Provisioning Modeling for Virtualized Multi-tier Applications in Cloud Data Center

Dynamic Provisioning Modeling for Virtualized Multi-tier Applications in Cloud Data Center 200 IEEE 3rd Iteratoal Coferece o Cloud Computg Dyamc Provsog Modelg for Vrtualzed Mult-ter Applcatos Cloud Data Ceter Jg B 3 Zhlag Zhu 2 Ruxog Ta 3 Qgbo Wag 3 School of Iformato Scece ad Egeerg College

More information

Chapter Eight. f : R R

Chapter Eight. f : R R Chapter Eght f : R R 8. Itroducto We shall ow tur our atteto to the very mportat specal case of fuctos that are real, or scalar, valued. These are sometmes called scalar felds. I the very, but mportat,

More information

Web Service Composition Optimization Based on Improved Artificial Bee Colony Algorithm

Web Service Composition Optimization Based on Improved Artificial Bee Colony Algorithm JOURNAL OF NETWORKS, VOL. 8, NO. 9, SEPTEMBER 2013 2143 Web Servce Composto Optmzato Based o Improved Artfcal Bee Coloy Algorthm Ju He The key laboratory, The Academy of Equpmet, Beg, Cha Emal: [email protected]

More information

The simple linear Regression Model

The simple linear Regression Model The smple lear Regresso Model Correlato coeffcet s o-parametrc ad just dcates that two varables are assocated wth oe aother, but t does ot gve a deas of the kd of relatoshp. Regresso models help vestgatg

More information

Integrating Production Scheduling and Maintenance: Practical Implications

Integrating Production Scheduling and Maintenance: Practical Implications Proceedgs of the 2012 Iteratoal Coferece o Idustral Egeerg ad Operatos Maagemet Istabul, Turkey, uly 3 6, 2012 Itegratg Producto Schedulg ad Mateace: Practcal Implcatos Lath A. Hadd ad Umar M. Al-Turk

More information

Fuzzy Multi-criteria Method for Revaluation of ERP System Choices Using Real Options

Fuzzy Multi-criteria Method for Revaluation of ERP System Choices Using Real Options Proceedgs of the World Cogress o Egeerg 11 Vol II WCE 11, July 6-8, 11, Lodo, U.K. Fuzzy Mult-crtera Method for Revaluato of ERP System Choces Usg Real Optos A.Cagr Tolga Abstract May corporate had mplemeted

More information

ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN

ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN Colloquum Bometrcum 4 ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN Zofa Hausz, Joaa Tarasńska Departmet of Appled Mathematcs ad Computer Scece Uversty of Lfe Sceces Lubl Akademcka 3, -95 Lubl

More information

Managing Interdependent Information Security Risks: Cyberinsurance, Managed Security Services, and Risk Pooling Arrangements

Managing Interdependent Information Security Risks: Cyberinsurance, Managed Security Services, and Risk Pooling Arrangements Maagg Iterdepedet Iformato Securty Rsks: Cybersurace, Maaged Securty Servces, ad Rsk Poolg Arragemets Xa Zhao Assstat Professor Departmet of Iformato Systems ad Supply Cha Maagemet Brya School of Busess

More information