A model of market positioning of destinations based on online customer reviews of lodgings

sus ainabili y A icle A Model o Ma ke Posi ioning o Des ina ions Based on Online Cus ome Re iews o Lodgings Manuel Rod íguez-Díaz 1,*, Rosa Rod íguez-Díaz 1, Ana C is ina Rod íguez-Vol es 2and C ina Isabel Rod íguez-Vol es 2 1 Depa men o Economics and Business, Uni e si y o Las Palmas de G an Cana ia, 35001 Las Palmas, Spain; osa. [email p o ec ed] 2Depa men Uni e si y o A lán ico Medio, 35017 Las Palmas de G an Cana ia, Spain; [email p o ec ed] (A.C.R.-V.); [email p o ec ed] (C.I.R.-V.) *Co espondence: manuel. [email p o ec ed] Recei ed: 10 Decembe 2017; Accep ed: 27 Decembe 2017; Published: 29 Decembe 2017 Abs ac : The aim o his s udy is o de elop a me hodology o de e mine he compe i i e online posi ioning o lodging companies in di e en ou is des ina ions. The ise o he digi al age has allowed many cus ome s o sha e hei opinions h ough specialized websi es, p o iding a dynamic and cons an ly upda ed e alua ion o he ma ke . In his con ex , compe i i eness is an essen ial ac o in he economic sus ainabili y o des ina ions. The compe i i e posi ioning o des ina ions is de e mined by he scale o a iables used by Booking.com. The p ice and lodging ca ego y a iables a e also used, as well as h ee new a iables de i ed om he ini ial scale: he quali y a e age, alue and added alue. This me hodology p o ides a ool o de e mine he le el o compe i i eness o he lodging o e ed in ou is des ina ions, based on which, ac ions can be aken o imp o e des ina ions’ posi ioning. Keywo ds: ou ism des ina ion; online cus ome e iew; ma ke posi ioning 1. In oduc ion Tou is des ina ions’ compe i i eness is based on hei abili y o o e a ac i e and up- o-da e lodging and in as uc u es [ 1 – 10 ]. Today, compe i i eness can also be seen in e ms o he image con eyed by lodgings and des ina ions [ 11 – 13 ]. In he digi al age, he e is an in ensi e exchange o in o ma ion be ween use s and companies and lodgings’ image on he In e ne is a c i ical ac o in hei compe i i eness [ 14 ]. Opinions sha ed by cus ome s on specialized pages build an online epu a ion ha is he basis o many cus ome pu chasing decisions [ 15 – 17 ]. This in o ma ion also de e mines he compe i i e posi ioning o lodgings and ou is des ina ions [18]. A ou is des ina ion is composed o a se o esou ces and capaci ies o ganized o ob ain a le el o compe i i eness ha gua an ees i s sus ainabili y [ 10 ]. The e o e, i is a complex ne wo k o a ious ac o s in ol ed in achie ing hei indi idual and collec i e objec i es h ough he p oduc s and se ices o e ed [ 5 , 19 – 27 ]. Due o he digi aliza ion o ou ism ma ke s, he image and p omo ion o ou is des ina ions a e dynamic ac o s ha mus be cons an ly moni o ed o main ain compe i i eness [ 28 , 29 ]. In his con ex , ou is des ina ions’ o ganiza ion allows hem o achie e a compe i i e posi ioning in ela ion o hei main compe i o s [ 18 ]. This p ocess equi es leade ship, usually by he au ho ized public adminis a ion, in o de o coo dina e he a ious s akeholde s in ol ed [8,30–32]. A des ina ion’s compe i i eness is based on en i onmen al, cul u al and economic sus ainabili y, o e ing highe alue o i s cus ome s compa ed o o he compe ing des ina ions [ 33 – 35 ]. In his con ex , des ina ions compe e wi h each o he , which means ha des ina ion ma ke ing o ganiza ions (DMO) need ools o es ablish hei ma ke posi ioning [ 36 ]. Hooley e al. [ 37 ] (p. 105) s a e ha “ he compe i i e posi ioning a i m chooses o occupy is a combina ion o i s choice o a ge ma ke Sus ainabili y 2018,10, 78; doi:10.3390/su10010078 www.mdpi.com/jou nal/sus ainabili y Sus ainabili y 2018,10, 78 2 o 20 and he di e en ial ad an age i is seeking o c ea e as a means o secu ing ha ma ke ”. The e o e, he des ina ion’s posi ioning should be based on consume s’ needs. Companies compe ing in a ma ke a e assessed by cus ome s on he basis o a numbe o a iables o a ibu es [38]. Cu en ly, he In e ne makes a la ge amoun o quan i a i e and quali a i e in o ma ion a ailable o use s and manage s ha can be used o de e mine he compe i i e posi ioning o lodgings and ou is des ina ions [ 18 ]. This in o ma ion collec ed in specialized da abases shapes he online epu a ion o hospi ali y i ms, i hey a e analyzed indi idually and des ina ions, when analyzing lodging o e as a whole. As a esul , he pe o mance o companies and ou is des ina ions inc easingly depends on he epu a ion gene a ed by social media [ 39 – 42 ]. The quan i a i e a iables ha a e usually e alua ed by clien s on specialized websi es measu e he quali y o he pe cei ed se ice and he pe cei ed alue [ 43 ]. Thus, some au ho s ha e p oposed new a iables based on he a o emen ioned scales, such as he a e age se ice quali y and added alue, whe e quali y o se ice and lodging p ice a e linked [ 18 ]. In his ega d, he compe i i e posi ioning o ou is des ina ions can be de e mined om hese quan i a i e a iables e alua ed by cus ome s. The aim o his s udy is o design and implemen a me hodology o posi ioning ou is des ina ions based on hei lodging o e . To his end, he quan i a i e a iables measu ed wi h he online scale o cus ome e alua ion on he Booking.com websi e will be used. O he a iables such as a e age quali y o se ice, alue pe cei ed and added alue will also be included. To he ex en ha he cus ome ob ains a compe i i e alue o e o he se ices sough , s/he will be mo e likely o pay a highe p ice, which will lead o an inc ease in des ina ions’ p oduc i i y [44,45]. This pape begins by e iewing he li e a u e on online epu a ion and he quan i a i e a iables used o measu e i , as well as he empi ical me hodology o be used o de e mine he compe i i e posi ioning o h ee ou is des ina ions: Sou h o G an Cana ia (Cana y Islands, Spain), Sou h o Tene i e (Cana y Islands, Spain) and Agadi (Mo occo). The esul s ob ained a e de eloped om he pe spec i e o he a e age quali y o se ice, added alue and p ice. In addi ion, a mul iple eg ession analysis is ca ied ou o de e mine he ela ionship be ween he pe cei ed quali y a e age and he pe cei ed alue in each des ina ion s udied. Finally, he main conclusions ob ained a e p esen ed, as well as he implica ions o esea ch and p ac ice o he p oposed me hodology o he compe i i e posi ioning o ou is des ina ions. 2. Li e a u e Re iew Cus ome s’ online opinions can be sha ed h ough quan i a i e a iables o quali a i e commen s [ 46 ]. These opinions gene a e a s a e o opinion ha shapes wha is known as he online epu a ion, which is made up o a se ies o e alua ions, opinions, images, o ideos abou he goods o se ices ha cus ome s con ac [ 17 ]. Einwille [ 47 ] s a es ha he online epu a ion is an in e ac i e p ocess o in o ma ion exchange among di e en ac o s (companies, cus ome s and use s) h ough di e en social media. In his con ex , he online epu a ion is beyond he di ec con ol o companies, al hough hey can in luence i h ough a communica ion ac i i y s a egically aimed a cus ome s o p omo e he image o goods, se ices, b ands and companies [48]. In he case o ou ism, he in oduc ion o digi iza ion has mean ha he online epu a ion la gely de e mines he comme cial and inancial pe o mance o lodging and ou ism des ina ions [ 49 , 50 ]. Engagemen and isibili y a e key ac o s in main aining an e ec i e communica ion ac i i y on he In e ne whe e cus ome s can access a la ge amoun o in o ma ion abou possible aca ion al e na i es. This si ua ion has led o di e en ypes o esea ch on cus ome s’ online pu chasing beha io [ 51 – 53 ], he quali y o he se ice ecei ed and cus ome sa is ac ion [ 15 , 54 ] and he p icing and e enue o lodgings [41]. Cus ome s’ online opinions ha e been esea ched in he ou ism sec o [ 43 ]. Online cus ome e iews a e de ined by Mudambi and Schu [ 55 ] as he e alua ions o p oduc s o se ices made by cus ome s on hi d-pa y websi es, which ha e a di ec e ec on he image o companies. The cons an low o in o ma ion p oduced by clien s has become a s a egic ac o in companies’ communica ion Sus ainabili y 2018,10, 78 3 o 20 because i es ablishes a public e alua ion o he pe cei ed se ice quali y and alue [ 18 , 43 , 54 ]. Cu en ly, lodging manage s ha e o cons an ly analyze cus ome s’ opinions in o de o e alua e he quali y o he se ice p o ided and se he p icing policy [ 43 , 46 ], as an e ec i e way o de e mine cus ome pe cep ions and sa is ac ion le els and es ablish dynamic compe i i e s a egies [51,56–58]. Online cus ome e alua ions on he main ou ism web po als measu e pe cei ed alue and pe cei ed se ice quali y [ 18 , 43 ]. In he specialized managemen and ma ke ing li e a u e, c ea ing alue o he inal consume is a key concep in de eloping a sus ained compe i i e ad an age [ 59 – 64 ]. Value mus be unde s ood om he cus ome ’s pe spec i e, in o de o o e he mos added alue possible and om companies’ in e nal pe spec i e because hey mus be compe i i e and p o i able a he same ime [ 65 , 66 ]. When a company o o ganiza ion e icien ly o e s a highe added alue han compe i o s, i achie es a mo e compe i i e posi ioning in he ma ke [67]. In he case o se ice companies, alue c ea ion de e mines hei s a egy and ac ics because i is a subjec i e concep om he pe spec i e o cus ome s and se ice wo ke s who pe o m he se ice [ 68 ]. Fo Holb ook [ 69 ], alue c ea ion is a ela i e p e e ence ela ed o a subjec ’s expe ience when in e ac ing wi h an objec , wi h he subjec being he consume and he objec being he good o se ice s/he acqui es. Mo eo e , Zei haml [ 70 ] ca ied ou a s udy es ablishing ou possible de ini ions o alue: (a) low p ice; (b) wha he cus ome wan s in a good o se ice; (c) he quali y he cus ome ge s o wha s/he pays; and (d) wha he cus ome ge s o wha he gi es. Rus and Oli e [ 71 ] ha e s udied he concep o alue, es ablishing ha i is di ec ly ela ed o he u ili y o he quali y o e ed o he clien and in e sely ela ed o he disu ili y o he p ice s/he has o pay. Pe cei ed alue has been measu ed h ough di e en me hods [ 71 – 73 ] and i is ela ed o he quali y o se ice [ 74 ], cus ome sa is ac ion [ 75 ] and p ice paid [ 76 ]. In he a ea o ou ism, pe cei ed alue has been s udied by Rod íguez-Díaz e al. [ 18 ] in ela ion o he added alue c ea ed by he lodgings and he eliabili y and alidi y o he scales o a iables used by he specialized websi es o ob ain cus ome alua ions [ 46 , 50 ]. An essen ial aspec o he academic deba e in ou ism is o de e mine he di e ence be ween quali y o se ice and cus ome sa is ac ion. To es [ 77 ] s a es ha quali y o se ice is a p ocess wi h an ou come ha is gene ally measu ed in quan i a i e e ms, whe eas sa is ac ion is ela ed o an o e all assessmen by cus ome s, o en exp essed in quali a i e e ms h ough opinions. In his con ex , cus ome sa is ac ion is de e mined h ough con en analysis o cus ome s’ w i en e iews [49,78]. This s udy uses he in o ma ion collec ed on he Booking.com websi e, which con ains quan i a i e and quali a i e in o ma ion. In o de o s udy he compe i i e posi ioning o ou is des ina ions h ough he a ings o hei lodging o e , only he quan i a i e a iables ha measu e he quali y o he pe cei ed se ice and he pe cei ed alue will be used [ 18 , 43 ]. I should be emphasized ha , acco ding o P ebensen e al. [ 79 ], he pe cei ed alue in ou ism is usually measu ed wi h a single-i em scale, such as “ alue o money” o “quali y-p ice ela ionship,” al hough some au ho s ind his ype o measu emen insu icien [ 80 , 81 ]. Howe e , he eali y o In e ne communica ion means ha measu emen scales ha e o be sho in o de o mo i a e use s o espond and so hey no mally include only he mos ele an a iables ela ed o he se ice o be e alua ed. The e o e, he measu emen o pe cei ed alue is gene ally based on a single i em scale closely ela ed o he quali y o he pe cei ed se ice, he u ili y ecei ed and he p ice paid by cus ome s [ 50 ]. Con e sely, pe cei ed quali y o se ice is o en measu ed h ough scales wi h a ious i ems, such as loca ion, s a , com o , acili ies, cleanliness and Wi-Fi [ 43 ]. P ice is a a iable ha can also be ob ained di ec ly om he Booking.com websi e and i is closely linked o he ca ego y [ 82 , 83 ] and he quali y o se ice pe cei ed by cus ome s [ 84 , 85 ]. Thus, when he ca ego y inc eases, p ices also inc ease and he e ec on he alue pe cei ed by cus ome s is nega i e [46,50]. Fo López-Fe nández and Se ano-Bedia [ 86 ] and O’ Conno [ 78 ], cus ome s demand a highe quali y o se ice when a lodging inc eases i s ca ego y because hey ha e o pay a highe p ice. This is e lec ed in he alue-added a iable because Rod íguez-Díaz e al. [ 18 ] demons a ed ha , as he numbe o s a s inc eases, he added alue is educed due o he highe p ice. Rega ding he Sus ainabili y 2018,10, 78 4 o 20 p ice in ou ism, i is usually modi ied acco ding o seasonali y and he le el o demand a any gi en ime [ 87 ]. The e o e, al hough lodgings can ca y ou p omo ions depending on he le el o occupa ion, in gene al i is possible o di e en ia e be ween high and low seasons in des ina ions. These seasons may a y depending on he loca ion o he des ina ions. In he case o he Cana y Islands and Agadi , he high season coincides wi h win e , when mos Medi e anean des ina ions a e closed, whe eas he low season is du ing he sp ing and pa o he summe . Based on he abo e, he compe i i e posi ioning o ou is des ina ions will be de e mined based on he a iables on he Booking.com scales o measu e he quali y o se ice pe cei ed and he pe cei ed alue, p ice, ca ego y and alue-added a iable [18]. 3. Resea ch Me hodology To de e mine he compe i i e posi ioning s udy o ou is des ina ions, in o ma ion was ob ained om 403 lodging complexes. Th ee ou is des ina ions a e analyzed. Two a e om he Cana y Islands (Spain) (Sou h o G an Cana ia and Sou h o Tene i e) and one om Mo occo (Agadi ) and all o hem a e ma ke ed h ough he Booking.com websi e. The des ina ions analyzed a e compe i i e because hey a e all ocused on he sun and beach ou ism segmen . They a e also loca ed below he 30 h pa allel no h, a a simila dis ance o he main ou is ma ke in cen al Eu ope. The Cana y Islands ecei e mo e han 12 million ou is s a yea [ 88 ], whe eas Agadi and he Souss Massa D âa egion ecei e 4 million ou is s a yea [ 89 ]. The o al numbe o cus ome e alua ions o he ou ism companies in hese des ina ions was 69.024. The numbe o lodgings in he des ina ion o he Sou h o G an Cana ia was 272, wi h 38.096 cus ome e alua ions; in he Sou h o Tene i e, he e we e 82 lodgings, wi h 20.950 a ings; and in he des ina ion o Agadi , he e we e 49 lodgings and 9.978 cus ome e iews. The Booking.com websi e con ains a ings by eal cus ome s o lodgings whe e hey s ayed. In addi ion, Rod íguez-Díaz and Espino-Rod íguez [ 46 ] demons a e ha i is he mos eliable and alid da abase a ailable on he In e ne and he compe i i e posi ioning o des ina ions should be pe o med wi h he mos p ecise in o ma ion possible. The scale used by Booking.com consis s o se en a iables measu ed on a 10-poin scale (1 = e y bad e alua ion; 10 = e y good e alua ion). Howe e , Mellinas e al. [ 90 ] indica e ha he o iginal scale has 4 poin s ha a e ans o med in o 10 poin s by means o an adjus men . Fo his eason, he scale is biased, as he lowes e alua ion gi en o a cus ome is 2.5 poin s and he maximum sco e is 10 poin s. The se en- a iable scale used by Booking.com consis s o : s a (S), se ice/ acili ies (F), cleanliness (Cl), com o (Co.), loca ion (L), Wi-Fi (W) and alue o money (V) (see Table 1). Booking.com de e mines he “a e age ho el sco e” (HAS) by calcula ing he a e age o all hese a iables on he scale. O he a iables used in he analysis and ob ained om he same websi e we e “ca ego y” o lodging and “p ice”. The p ice a ies h oughou he yea acco ding o seasonali y and, wi hin he season, acco ding o he le el o demand. Fo his eason, he highes and lowes p ices o each lodging ha e been de e mined in he high (win e ) and low (summe ) seasons o hese des ina ions. The p ices o each lodging we e ob ained by sea ching he Booking.com websi e in he pe iods o ime ha he sec o conside ed he mos common o high and low p ices in each season. In win e , which is high season o hese des ina ions, he highes p ice pe iods a e No embe , Feb ua y and Ma ch, wi h he lowes p ices in he i s wen y days o Decembe and Janua y. In he summe , p ices a e highes a he end o July, Augus and Oc obe , whe eas he lowes p ices a e usually ound in May, June and he i s hal o July. In addi ion, wo new a iables ha e been iden i ied: he quali y a e age (Q) and he added alue (AV). Because Wi-Fi e iciency depends on he des ina ions’ in as uc u e, which is o en beyond he con ol o he lodging, his a iable was no included in he posi ioning s udy. Thus, he a e age quali y (Q) a iable was de e mined by calcula ing he mean o he a iables ha measu e he pe cei ed se ice: s a (S), se ice/ acili ies (F), cleanliness (Cl), com o (Co.) and loca ion (L). The pe cei ed alue (V) is measu ed on Booking.com by means o a single a iable, he alue o money (V). Mo eo e , Sus ainabili y 2018,10, 78 5 o 20 Ye e al. (2014) pe o med a ac o ial analysis o he a iables ha de e mine he pe cei ed quali y o se ice in o de o es ablish whe he he scale was one-dimensional. Following his p ocedu e, Table 2 shows he esul s ob ained om he ac o ial analyses o all he des ina ions as a g oup and each one sepa a ely. The able shows ha he a iance explained by all he des ina ions was 59.438%, whe eas he des ina ion o G an Cana ia ob ained 58.534%, Tene i e 73.699% and Agadi 70.865%. The a iable ha achie ed he lowes ac o load, below 0.5, was cleanliness, wi h he excep ion o he des ina ion o Tene i e (0.904). Table 1. Desc ip ion o a iables. Va iables Desc ip ion Ho el’s a e age sco e (HAS) Re iewe ’s o e all e alua ion o he lodging Ho el s a (S) The e iewe ’s o e all a ing o he lodging s a Se ice/ acili ies (F) The e iewe ’s o e all a ing o he lodging se ice and acili ies Cleanliness (Cl) The e iewe ’s o e all a ing o he cleanliness o he lodging Com o (Co.) The e iewe ’s o e all a ing o he com o o he lodging Loca ion (L) The e iewe ’s o e all a ing o he loca ion o he lodging Value o money (V) The e iewe ’s o e all a ing o he pe cei ed alue o he lodging Wi-Fi (W) The e iewe ’s o e all a ing o he Wi-Fi connec ion P ice (high and low season) The p ice o one nigh in he lodging Ca ego y The s a a ing o he lodging Quali y a e age (Q) A e age o quali y se ice a iables (S, F, Cl, Co., L) Added alue (AV) Di e ence be ween alue (V) and quali y a e age (Q) Table 2. Resul s o ac o analysis. All Des ina ions Va iables Sco e Coe icien s Cleanliness 0.346 Com o 0.909 Loca ion 0.649 Se ice/ acili ies 0.923 S a 0.867 Va iance explained: 59.438% KMO measu e o sampling adequacy: 0.786 Ba le ’s es : 1049.657 Signi icance: 0.000 G an Cana ia Va iables Sco e Coe icien s Cleanliness 0.263 Com o 0.913 Loca ion 0.681 Se ice/ acili ies 0.909 S a 0.855 Va iance explained: 58.534% KMO measu e o sampling adequacy: 0.788 Ba le ’s es : 660.689 Signi icance: 0.000 Tene i e Va iables Sco e Coe icien s Cleanliness 0.904 Com o 0.928 Loca ion 0.610 Se ice/ acili ies 0.945 S a 0.859 Va iance explained: 73.699% KMO measu e o sampling adequacy: 0.838 Ba le ’s es : 334.259 Signi icance: 0.000 Agadi Sus ainabili y 2018,10, 78 6 o 20 Table 2. Con . All Des ina ions Va iables Sco e Coe icien s Cleanliness 0.346 Com o 0.909 Loca ion 0.649 Se ice/ acili ies 0.923 S a 0.867 Va iance explained: 70.865% KMO measu e o sampling adequacy: 0.830 Ba le ’s es : 198.362 Signi icance: 0.000 The added alue is quan i a i ely de e mined in his s udy ollowing he p ocedu e p oposed by Rod íguez-Díaz e al. [ 18 ], whe e he added alue is he esul o sub ac ing he quali y a e age (Q) om he pe cei ed alue (V). When a cus ome hinks he se ice ecei ed co esponds o he p ice s/he has paid, he alue added will be ze o. Howe e , i he cus ome belie es ha he p ice paid is highe han he se ice ecei ed, s/he will end o sco e he pe cei ed alue below he quali y a e age, esul ing in a nega i e added alue. Finally, i he cus ome s iew he p ice paid o be less han he se ice ecei ed, he added alue will be posi i e because he pe cei ed alue will be highe han he quali y a e age. The la e usually occu s in high-class lodgings, whe e a high s anda d o se ice quali y is o e ed bu he p ice paid by cus ome s is high. In hese cases, clien s a e o en e y s ic and gene ally assess pe cei ed alue (V) below he a e age quali y o pe cei ed se ice (Q). 4. Analysis o Resul s Using he a iables desc ibed abo e, he compe i i e posi ioning analysis o ou is des ina ions is ca ied ou in h ee s ages. The i s s age e alua es he alue pe cei ed by cus ome s in ou is des ina ions o de e mine i s ela ionship wi h he se ice, p ice and ca ego y a iables because he la e wo cons uc s can be e alua ed wi h he in o ma ion a ailable on Booking.com, in addi ion o being heo e ically closely ela ed. Nex , he compe i i e posi ioning o des ina ions is de e mined acco ding o he quali y a e age, added alue and maximum p ice in high season. Finally, he compe i i e posi ioning o he lodgings acco ding o he ca ego y is ca ied ou , showing ha companies in hese des ina ions compe e based on he a iables desc ibed in he p e ious s age. 4.1. Cus ome Value E alua ion In o de o s udy he ela ionships be ween pe cei ed alue and pe cei ed se ice quali y, p ice and ca ego y, a mul iple eg ession analysis was ca ied ou , whe e he dependen a iable was pe cei ed alue and he independen a iables we e i e a iables om he scale o pe cei ed se ice, ou p ice a iables and he ca ego y o lodging a iable. Table 3shows he esul s ob ained o all he des ina ions oge he and hen o each o hem indi idually. The analysis o all he lodgings in he h ee des ina ions a he same ime e eals ha he adjus ed R2 is qui e high, 0.629. Howe e , no all he a iables a e signi ican ly ela ed. The ca ego y o lodgings is signi ican ly (0.0000) and in e sely ( − 0.2041) ela ed o he pe cei ed alue o he lodgings, con i ming he obse a ions o López-Fe nández and Se ano-Bedia [ 86 ], O’ Conno [ 78 ] and Rod íguez-Díaz e al. [ 18 ], who ound ha cus ome s in highe ca ego y accommoda ions hink hey pay a highe p ice han he quali y o se ice ecei ed. O he a iables ha a e signi ican ly and di ec ly ela ed o pe cei ed alue a e cleanliness (0.2791), com o (0.1518) and s a (0.1625). The analysis o he indi idual des ina ions shows ha G an Cana ia has he smalles adjus ed R2, 0.505, al hough i is s ill high. In his case, only he ca ego y ( − 0.1346) and cleaning (0.2206) a iables a e signi ican . Meanwhile, he des ina ion o Tene i e ob ains a highe adjus ed R2 o 0.601, wi h he same a iables signi ican ly ela ed o he pe cei ed alue, ha is, ca ego y ( − 0.4075) and Sus ainabili y 2018,10, 78 7 o 20 cleanliness (0.3357). The des ina ion o Agadi yields di e en esul s, whe e p ices a e an essen ial aspec o pe cei ed alue. The adjus ed R2 ob ained was he highes , a 0.761 bu he ou p ice le els we e he only a iables signi ican ly ela ed o pe cei ed alue. The maximum p ice in high season ( − 0.0342) and he minimum p ice in low season ( − 0.0565) main ain an in e se ela ionship. Tha is, he highe he p ice, he lowe he alue pe cei ed by cus ome s. By con as , he minimum p ice in high season (0.0388) and he maximum p ice in low season (0.0425) a e di ec ly ela ed o he pe cei ed alue. These esul s e lec a e y impo an p ice adjus men by lodgings in o de o main ain compe i i eness and he equi ed occupancy le els. In his compe i i e en i onmen , highe ca ego y lodgings ha e o adjus hei minimum p ices in high season and hei maximum p ices in low season o a ac cus ome s. Howe e , du ing he bes momen s o he high season, hey ha e o aise hei p ices o ea n income. On he minimum p ices in he low season, highe ca ego y lodgings canno unde cu hei p ices o he le el o lowe ca ego ies. Table 3. Reg ession analysis wi h alue as dependen a iable. All Sec o Coe icien T Signi icance Cons an 3.2265 8.0382 0.0000 Ca ego y −0.2041 −4.72127 0.0000 Minimum p ice in low season 0.0002 0.4974 0.6194 Maximum p ice in low season −0.0007 −0.8092 0.4193 Minimum p ice in high season 0.0007 0.5199 0.6037 Maximum p ice in high season −0.0008 −0.6082 0.5437 Cleanliness 0.2791 4.0120 0.0000 Com o 0.1518 2.0417 0.0425 Loca ion −0.0584 −1.2739 0.2041 Se ice/ acili ies 0.1216 1.6965 0.0913 S a 0.1625 2.0998 0.0370 F alue = 33.235 (sig. 0.000) Adjus ed R2 = 0.629 G an Cana ia Coe icien T Signi icance Cons an 3.5133 6.6895 0.0000 Ca ego y −0.1346 −2.1288 0.0355 Minimum p ice in low season 0.0004 0.7344 0.4642 Maximum p ice in low season −0.0003 −0.3161 0.7524 Minimum p ice in high season 0.0022 1.2394 0.2178 Maximum p ice in high season −0.0023 −1.2411 0.2171 Cleanliness 0.2206 2.3669 0.0197 Com o 0.1452 1.5148 0.1327 Loca ion −0.0638 −0.9360 0.3513 Se ice/ acili ies 0.1085 1.2026 0.2317 S a 0.1768 1.7044 0.0911 F alue = 11.124 (sig. 0.000) Adjus ed R2 = 0.505 Tene i e Coe icien T Signi icance Cons an 2.7814 2.8299 0.0071 Ca ego y −0.4075 −3.8837 0.0003 Minimum p ice in low season 0.0014 0.2308 0.8185 Maximum p ice in low season −0.0013 −0.2347 0.8156 Minimum p ice in high season −0.0025 −0.4302 0.6693 Maximum p ice in high season 0.0013 0.2306 0.8187 Cleanliness 0.3357 2.5994 0.0129 Com o 0.1352 0.8979 0.3744 Loca ion 0.0488 0.5694 0.5721 Se ice/ acili ies 0.2324 1.4084 0.1665 S a 0.0699 0.4933 0.6244 F alue = 8.690 (sig. 0.000) Adjus ed R2 = 0.601 Sus ainabili y 2018,10, 78 8 o 20 Table 3. Con . Agadi Coe icien T Signi icance Cons an 1.1516 0.9785 0.3375 Ca ego y −0.2127 −1.4493 0.1601 Minimum p ice in low season −0.0565 −3.0844 0.0050 Maximum p ice in low season 0.0425 2.8297 0.0092 Minimum p ice in high season 0.0388 2.3561 0.0269 Maximum p ice in high season −0.0342 −2.4429 0.0223 Cleanliness 0.3477 1.9588 0.0618 Com o 0.1157 0.5571 0.5825 Loca ion 0.1878 1.5103 0.1440 Se ice/ acili ies −0.0059 −0.0323 0.9744 S a 0.3336 1.5658 0.1304 F alue = 11.854 (sig. 0.000) Adjus ed R2 = 0.761 4.2. Posi ioning Analysis by Des ina ions To analyze he compe i i e posi ioning, i is necessa y o de ine he a iables ha will de e mine how cus ome s assess lodgings and ou is des ina ions. The a iables used in his esea ch a e he quali y a e age (Q) and added alue (AV), which ha e been analyzed in ela ion o he p ice le el o lodgings. Al hough ou ypes o p ices we e a ailable, he maximum high season p ice has been used, which is when he lodgings a e in hei op imum posi ion. Linea and quad a ic eg ession analyses we e ca ied ou o ind he compe i i e posi ioning o he des ina ions and hei lodging o e , in o de o de e mine he unc ion ha bes i s he a iables s udied. The dependen a iables a e he quali y a e age (Q) and added alue (AV), whe eas he independen a iable is he highes p ice in high season. S a is ical analyses we e conduc ed, i s , conside ing all he ou ism companies oge he . Subsequen ly, eg ession analyses we e pe o med indi idually o each o he des ina ions. 4.2.1. Analysis o All Des ina ions Table 4shows he eg ession analysis esul s o all he des ina ions included in he s udy. The pu pose o linea eg ession was o de e mine he end o he o e in he des ina ions, whe eas he quad a ic unc ion was ca ied ou o ob ain a be e i . Table 2shows he esul s ob ained, whe e he adjus ed R2 o he linea unc ion o quali y a e age was 0.188, he quad a ic unc ion ob ained a much highe esul o 0.233 and he F es s we e signi ican . Figu e 1shows he plo s whe e he linea and quad a ic unc ions a e ep esen ed. The end o he quali y a e age a iable is upwa d, demons a ing ha , as p ices ise, lodgings imp o e he se ice o e ed o hei cus ome s. Table 4. Model Summa y and Pa ame e Es ima es o Reg ession S a is ic Analysis: All des ina ions. Dependen Va iable: Quali y A e age (Q) Independen Va iable: Maximum P ice in High Season Equa ion Model Summa y Pa ame e Es ima es R Squa e F d 1 d 2 Sig. Cons an b1 b2 Linea 0.188 62.983 1 271 0.000 7.310 0.003 Quad a ic 0.233 41.015 2 270 0.000 6.940 0.008 −9.537 ×10−6 Dependen Va iable: Added Value (AV) Independen Va iable: Maximum P ice in High Season Equa ion Model Summa y Pa ame e Es ima es R Squa e F d 1 d 2 Sig. Cons an b1 b2 Linea 0.180 59.696 1 271 0.000 0.111 −0.003 Quad a ic 0.310 60.739 2 270 0.000 0.542 −0.008 1.1099 ×10−5 Sus ainabili y 2018,10, 78 9 o 20 Sus ainabili y 2018, 10, 0078 10.3390/su10010078 9 o 19 Figu e 1. Plo s o eg ession analyses o all des ina ions. 4.2.2. Analysis o G an Cana ia Des ina ion Table 5 shows he esul s o he eg ession analysis o he des ina ion o G an Cana ia. Wi h ega d o he quali y a e age (Q), he adjus ed R2 o he linea unc ion was 0.115, he quad a ic was 0.193 and he F es was signi ican (0.000) in he wo eg essions. Pa ame e s b1 a e posi i e, which de e mines a endency o inc ease as lodging p ices ise. This esul can be seen in Figu e 2, whe e he linea eg ession is cons an ly inc easing, whe eas he quad a ic eaches i s maximum a abou 400€ pe nigh and oom and hen declines. I should be cla i ied ha he unc ions o quali y a e age in ela ion o p ice a he G an Cana ia des ina ion a e below he a e age o he h ee des ina ions analyzed oge he . S udying he alue-added a iable e eals ha he linea unc ion ob ained an adjus ed R2 o 0.148 and a quad a ic unc ion o 0.304, wi h he F es demons a ing ha he esul s a e signi ican a 0.000. Again, hese esul s show ha he quad a ic unc ion bes explains he lodging o e o his des ina ion. Figu e 2 shows ha he linea unc ion o added alue in he des ina ion o G an Cana ia dec eases less han in all he des ina ions oge he , as i has a sligh ly lowe b1 pa ame e (−0.002). Table 5. Model Summa y and Pa ame e Es ima es o Reg ession S a is ic Analysis: Sou h o G an Cana ia des ina ion. Dependen Va iable: Quali y A e age (Q) Independen Va iable: Maximum P ice in High Season Equa ion Model Summa y Pa ame e Es ima es R Squa e F d 1 d 2 Sig. Cons an b1 b2 Linea 0.115 21.851 1 168 0.000 7.482 0.002 Quad a ic 0.193 20.017 2 167 0.000 6.993 0.009 −1.209 × 10−5 Dependen Va iable: Added Value (AV) Independen Va iable: Maximum P ice in High Season Equa ion Model Summa y Pa ame e Es ima es R Squa e F d 1 d 2 Sig. Cons an b1 b2 Linea 0.148 29.277 1 168 0.000 0.113 −0.002 Quad a ic 0.304 36.478 2 167 0.000 0.569 −0.008 1.1283 × 10−5 Figu e 1. Plo s o eg ession analyses o all des ina ions. The o he eg ession analysis was pe o med using he added alue as a dependen a iable and he maximum p ice in high season as an independen a iable. In his case, he adjus ed R2 o he linea unc ion (0.180) was sligh ly lowe han he eg ession o he quali y a e age, whe eas he adjus ed R2 o he quad a ic unc ion was 0.310, which is a good i in he social sciences, wi h a signi ican F es in bo h eg essions (0.000). As Table 4shows, b1 pa ame e s we e nega i e, con i ming a downwa d end in bo h unc ions. These esul s con i m wha has been s a ed in he academic li e a u e [ 69 , 71 ], ha is, ha pe cei ed alue is a subjec i e concep . Likewise, i is in e sely ela ed o he p ice le el, gi en ha he se ice pe cei ed by cus ome s exceeds hei e alua ion o he pe cei ed alue when lodgings inc ease hei ca ego y. 4.2.2. Analysis o G an Cana ia Des ina ion Table 5shows he esul s o he eg ession analysis o he des ina ion o G an Cana ia. Wi h ega d o he quali y a e age (Q), he adjus ed R2 o he linea unc ion was 0.115, he quad a ic was 0.193 and he F es was signi ican (0.000) in he wo eg essions. Pa ame e s b1 a e posi i e, which de e mines a endency o inc ease as lodging p ices ise. This esul can be seen in Figu e 2, whe e he linea eg ession is cons an ly inc easing, whe eas he quad a ic eaches i s maximum a abou 400 € pe nigh and oom and hen declines. I should be cla i ied ha he unc ions o quali y a e age in ela ion o p ice a he G an Cana ia des ina ion a e below he a e age o he h ee des ina ions analyzed oge he . S udying he alue-added a iable e eals ha he linea unc ion ob ained an adjus ed R2 o 0.148 and a quad a ic unc ion o 0.304, wi h he F es demons a ing ha he esul s a e signi ican a 0.000. Again, hese esul s show ha he quad a ic unc ion bes explains he lodging o e o his des ina ion. Figu e 2shows ha he linea unc ion o added alue in he des ina ion o G an Cana ia dec eases less han in all he des ina ions oge he , as i has a sligh ly lowe b1 pa ame e (−0.002). Sus ainabili y 2018,10, 78 16 o 20 maximum p ices in high season. The esul s show ha quad a ic unc ions ha e a be e i han linea unc ions. The g aphs made o each des ina ion e eal ha he des ina ion o Tene i e has a s eepe slope, inc easing un il eaching he maximum alues o quali y o se ice. By con as , Agadi is he des ina ion whe e he lodgings ha e lowe alue, in addi ion o ha ing he lowes p ices. Wi h ega d o added alue, he quad a ic unc ions ob ain a highe adjus ed R2 alue han he linea unc ions. The g aphs show ha he Agadi des ina ion has a highe p opo ion o posi i e added alue o lodgings because he lodgings o e a le el o se ice quali y a lowe p ices. Finally, a join s udy has been ca ied ou on accommoda ions in des ina ions di e en ia ed by ca ego y. The g aph o he a e age quali y o 4 and 5-s a accommoda ions shows ha he des ina ions in G an Cana ia and Tene i e each sligh ly highe alues as he p ice ises. Howe e , o lodgings wi h 3-s a s o less, he alues ob ained by he h ee des ina ions a e qui e simila . In ela ion o he added alue a iable, he 4- and 5-s a lodging g aph shows ha Agadi ’s lodgings ha e he lowes p ices and he highes added alue. The analysis o accommoda ions wi h 3 s a s o less shows ha he e is a g ea e balance in his ype o o e . This s udy has p ac ical and esea ch implica ions o ou ism des ina ions. Des ina ion leade s and DMOs need compe i i e ools o make decisions and de ine s a egies wi h economic and sus ainabili y esul s. The p oposed me hodology de e mines he posi ioning o he lodging o e is-à- is o he compe ing des ina ions, which acili a es s a egic analysis and he s udy o he main a iables ha in luence cus ome s. I is also a dynamic p ocedu e ha can cons an ly be upda ed based on he in o ma ion a ailable on specialized websi es. Achie ing a compe i i e accommoda ion o e means ob aining quali y s anda ds o se ice and added alue based on he p ice paid by cus ome s. To he ex en ha signi ican di e ences a e ound compa ed o o he des ina ions, he ac ions o DMOs should ocus on aising lodging manage s’ awa eness o he need o modi y hei compe i i e s a egies. F om a esea ch pe spec i e, his s udy p oposes a iables and unc ions o de ine he compe i i e posi ioning o he lodging o e o des ina ions. In his con ex , a line o s udy is de eloped ha can be expanded h ough he in oduc ion o o he a iables and s a is ical p ocedu es. The main limi a ion o his s udy lies in he a iables wi h in o ma ion a ailable on he In e ne . Al hough quan i a i e measu emen scales consis o ew a iables, hey ha e been shown o p o ide ele an in o ma ion abou he basic a ibu es ha in eg a e pe cei ed se ice and pe cei ed alue. Fu u e esea ch should pe o m compa a i e analyses o he compe i i e posi ioning o des ina ions, aking in o accoun o he lodging da abases such as T ipAd iso and HolidayCheck. These esul s should be compa ed wi h hose ob ained wi h he in o ma ion a ailable on Booking.com in o de o de e mine whe he simila esul s a e eached. Ano he aspec o highligh is ha he me hodology has been es ed in h ee ou is des ina ions o g ea impo ance in he sun and beach segmen . Howe e , u u e esea ch should es his me hodology in o he ypes o des ina ions wi h di e en s a egic o ien a ions. Finally, he a iables used in he analysis a e able o measu e he pe o mance o des ina ions’ lodging o e s om he pe spec i e o cus ome s. Fu u e esea ch should examine he ela ionship be ween cus ome pe o mance and he economic and inancial pe o mance o hospi ali y i ms and ou is des ina ions. Au ho Con ibu ions: The au ho s ha e con ibu ed equally in he esea ch design and de elopmen , he da a analysis and he w i ing o he pape . 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