!"# %&' " (!))
Human Resource Risk Management affecting Performance of Spa Business in Koh Samui, Surat Thani Province
Tanayu Puwitthayathorn * and Nit Hathaivaseawong Suksri Received: October 2,2018,, Revised: December 10,2018, Accepted : December 26,2018
!"#$%&'()+-.$!%(/3&!-(4)4/5%
)#)5%)%!/-7%9.3)! %3)"#).')4 3/#') /.3!5;;<$%$'()!')(=>3=$')..)."!"(=>3=%$3)! $')
$%?($%.(%.!@%$"/")%>&$ B4+-&..$!%(/3
&!-&.C/&!) =/.!%!'()&B/3&.) =/.!(//3E/3 .$!%(=/3$/%')34 3!$.$!%(=/3
!&) =/.!F/3E/3.$!%(=/3.$)./.
$!%(=/3&G&.$!%(=/3..3)! &.$$!5/.
4/5%=&!) =/.!(/%!'()&B/3&.) =/.!(//3E/3 /3%/3 $3) =/.!/3E/3/3.=/3% 3&G!5/.
.$!%(/3&!-/3..3)! &.$$/3. $).
//3$/%')34 3!$4.)4/5%)#
=)5%)%!/-7)!5$I"
*
: .$!%(/3&!-4/5%#J4 3>$B/!>K-7
J Assistant Professor, Faculty of Management Sciences, Suratthani Rajabhat University
-./ 01+'"$ $
»‚·Õè 11 ©ºÑº·Õè 2 àÁ.Â.-ÁÔ.Â. 62
Abstract
The purpose of this research were to study human resource risk management affecting performance of spa business in Koh Samui, Surat Thani province. The questionnaires were used for collecting data from 114 business owners or spa managers as well as supervisors. The statistics used for data analyzing were mean, standard deviation and multiple regression analysis. The result showed that the overall human resource risk management was at high level. When considering each aspect, it was found that at highest level in two areas, namely recruitment selection and placement risk and labor relation risk. At a high level in three areas, namely compensation and welfare risk, operation management risk, and personal information system risk.
The performance management was at very higher level; when analyzing each aspect, it was found that at highest level in two aspects: financial perspective and customer perspective. At a high level in two areas:
internal process perspective and learning and growth perspective. Furthermore, the study indicated that human resource risk management in the dimensions of personal information system risk, compensation and welfare risk, and recruitment, selection and placement risk positively and significantly affect on performance of spa business in Koh Samui, Surat Tthani province.
Keywords
: Human Resource Risk Management, Performance, Spa Business1+)
#%#9.(%!&[+(%(3).)!)%((!)%I%.C /%9 =#%#%[+(%#94! )/$3). #../5%>)$=#.(!
$!===&#)..#E!%)-B=/3=3.(%/=>3 !#IIE5=3E/3.
$!! >E>>\B)#%@, 2557) / #E+!..5$I)&G )#%=@%#93E/3%3 #%C/! $/)#=#%E!)%.C )%'()8`)# =>#2013-2015 ')$/%#9! $#!B3.5 !'(3./%#9)/.(16 )C )/.(5 =%)%> $/B)Global Wellness Institute (GWI) &.! $/)#(C!
C3!%?(6`)#')! $/%&1.29 3/)@ /.1.69 3/)
@=>#2015-2020 (Economic Intelligence Center (EIC), 2561) +5=3%/3%/E/3)%'() .)!)'((%(3) %! /-7 %#9%(!&=)%(%>&
!$!&3)!=/3#+!"4/=3%!%#9 #\Hub of spa) E/3
\B)#%@, 2557) !3)5/%(./$.$(!$! 3%>(>I).#
5=3%/#I>>.$%&'()=3E/3.$!\B)>, 2555 ; , 2556 ; B)#%@, 2557; 5.C$3!%!$3#%, 2558) !"+%3 #>$!
01+'"$ $ -.-$
%-@)%[[+(!%#/%=!#%!>5=3!C)%')!(+ .$!%(
%#9(($=3$!=!+ %'()((3)$')4). /=.$ 4/5%))!
E!%#9E#/($/%)E3/"+$/B).- !$!%(? !.$!%(=)$
!"3$!!(=E/3=/.+(/5%.%#3!(E3\/.I,
#& -)B>&I, 2554) %'().$!%(%#9$/B(!
>/')#3)$!%=5 )E33C/.$!%((/%#9 /$!!"/5%).$=)$\#B>&-.)/!, 2557)
!.$!%((/ 4/5%))!%#9E#!"#$%#3!(5/E3 )!#&3$!!"==3.E/3/(+ \&B!, &-C
&&&-, 2557 ; !&., /#!B &-%&, 2558)
#.)$=#%EE!E/3=3$!5$I=%'().$!%(/3&!- [+(.$!%(/3&!- %#9#(!")=3%/$!%()$!5%9))$
%>%/.#/3)'(\#(, 2555) C/$!%(/3&!-()%/+ ).
$!%(=/3.$)./)%/E/3E!!#%!$%&'()//.
5(" 3)!$)=5E!!C$3%%/')(>/%" 3).$!%(=
/3&G&%>)$/..$3!"$!!"=5(>/%.
.$!%(=/3!&%>)$))%..3).$./.7!5II(%)
%#.&C/$/&!=II 3.-!"=>3.$.E/3B\%>&!), 2556 ; !&., /#!B &-%&, 2558 ; B.!, &B)+B )4$, 2559)
/(E/3!33$!%(/3&!-% 4%)/5%/.)$
/..$$5=3E!!"."#$!()$E/35/E3)$E!=3$!5$I=
.$!%(/3&!-(%/+ 4 3+=+-%'().$!%(/3&
!-)#)5%)%!/-7%&'()3=3#"+#I/3&!-
!(!%&(!!+ )%3 )%[
2. " -'/% "
=$ 5/=3.$!%(/3&!-%#9#)4)4 /5%)#)5%)%!/-7"#$33!"#).$/
=E/3/
-.8 01+'"$ $
#9$--$:$8$;;<;;$=8
0#&#'
3 -' !"#
ǰ
2.1 )(Human Resource Risk Management)
.#$.$!!./5%%(...$$%&'()=3 /.)$!%%(.&.$$(%/+ =)$)!.E/3#%!E/3$.$!).E/3 )!..[+(!"5=3)$.45%9!%#3!))$E/3)!#& (/.I,
#& -)B>&I, 2554 ; /BE>%I, ) !
%, 2554)
2.1.1 .$!%(=/3$/%')34 3!$(Recruitment Selection and Placement Risk) !"+$!%(/3.$ =)%3!
#K./3/4 3(53(!-B(!-#.B!"+=>3..$B!).#
%&'()./5(E/3%[+(E!!"5E/3)=3%/4.%/$!%=3 )$
2.1.2 .$!%(=/3.$)./(Compensation and welfare Risk) !"+$!%(/35/$).(%!!$! 3$!!"!5/C$3%%/') (>/%!#.#/!"+5$!%3=.$"+..3 ==$).(/
%&'()3=3.$#K.)!#&[+(E!!"5E/3)=3%/4.%/$!%
=3)$
2.1.3 .$!%(=/3&G&(Personal Development Risk) !"+$!%(
/3/.#!B&G.$(%&&).%3+).!!$!=)&C/(
).!%3#K.!#%!4/!4=&G+).!.$[+(E!!"5E/3 )=3%/4.%/$!%=3)$
2.1.4.$!%(=/3!&(Labor Relation Risk) !"+$!%(/35/
%..3).$.IIC/)/$3).7!!"+!5$!&+&)==5
1. .$!%(=/3$/%') 34 3!$
2. .$!%(=/3.$)./
3. .$!%(=/3&G&
4. .$!%(=/3!&
5. .$!%(=/3..3)! &.$$
1. /3%
2. /3 $3
3. /3.=
4. /3% 3&G
-.>$
01+'"$ $
%!=3.$3/$!$/%9) !/!!&= #..[+(E!!"5E/3 )=3%/4.%/$!%=3)$
2.1.5 .$!%(=/3..3)! &.$$(Personal Information System Risk)
!"+$!%(/3..#!B=&G#.#))....3)! &!-(!
$!#)/%&'()=>3'.$3/5/3&!-[+(E!!"5E/3)=3%/
4.%/$!%=3)$
2.2 )(Performance)
> /%#95/%B')!@')%#.%.5.> /%&'()=3.
/5%%#9E#!!@5/')E!=3.%#3!!()$E/35/E3! %#9 /4/5%).$.$=)$!&!3)%&=//45%9))$%&'()=3 .3)!#.#)$) ))%'()(Kaplan Norton, 1993; &B!, &-C
&&&-, 2557; !&., /#!B &-%&, 2558; @&>, 2558;
!%>, )))"$&GE>3)!, 2558; B.!&B)+B )4$, 2559)
2.2.1 /3%(Financial Perspective) !"+)$!5E%&(!+ (%/)/5$3 .!"+./%&(!+ [+(5=34/5%/)!5(%!)
2.2.2 /3 $3(Customer Perspective)!"+)$E/35$55>!) $3!#.#
$B&))..$3.%&'()).)$!3)) $3$!.$ ) !
#.# $3=!%)== $3%
2.2.3 /3.=(Internal Process Perspective) !"+)$!#.#
..=3!.5=3>/%!"+!#.#!=3!$!!"=
=3. $3#.#!%&'()3=3.$!$!!$$
2.2.4 /3% 3&G(Learning and Growth Perspective) !"+)$!#.#
C$3)$=3%!!..=#K.=3.$!$!>5I%?&/3!"+5
%$CC%=!3)$/%9%)).$!%#93)! %&'()#.#$3.#.#
)$
3+) ! "
3.1)' -' !7
$ %#9%>&B\Descriptive Research)
#>566\B/-7, 2559) !)=!5//
)!)!)Krejcie Morgan (1970557C/=>3!)..\Simple Random Sampling) C/.?C/E!=$'[+(!)$ $')%3)"#).')4 3/
-.? 01+'"$ $
»‚·Õè 11 ©ºÑº·Õè 2 àÁ.Â.-ÁÔ.Â. 62
#')/.3 2$!5114$%9..!3)! C/..)."!=3!
)/3%)E#-B[+(..)."!(E/3.$'!))..$/%#9100%#)%[9%#9 ..)."!(!$!!. B
3.2 88' -#
.$!%(/3&!-5))%#95/3/ 1) .$!%(=
/3$/%')34 3!$553)C/$).$!.$ = )%&'()%3!#K.=5(/4 353(!-B(!-#.B$).$!
=5).#$B!.4 3!$()/$3).5($/%')&
/3=>3..$B!%&'()=3E/3.$(!$! 3$!!"%!!../5E/3
%2) .$!%(=/3.$)./553)C/$).$!5/
$).=3..$!$! 3$!!"#.B)%#9!5/C$3%%/') (>/%%!!.%3$!33).$=>3..3 ==$).(/%&'()3
=3.$#K.)!#&#.#/C/=>33)! $!3)).$!!
&B3..$).(%!!()=3%/#C>.$)$3) .$!%(
=/3&G&553)C/$).$!&G.$C//=3!%3+).!) 5).!C/#K.%&'()=3.$!$!%3==(5!+ #%!4/!
4=&G+).!.$/.#!B&G.$)%&&)+).!%&'()&G .$!3)$!=).$4) .$!%(=/3!&553)C/
$).$!/$!$/%93)%3)5/%..3).$.C/)/$3).7!/5 II(!$!%#9!.$5$!&+&)==5).$/.) %!)/
!!&= #..5) .$!%(=/3..3)! &.$$553) C/$).$!))....3)! &!-(/.=3.&!-#.$!5%9 ..#3)$!#)/%(..3)! &!-=>3%$CC%3!#.#/3)!
/3&!-=>3..'.$3/5%&'().=%(5/.#!B=3!
&G..3)! &!-
4/5%5))%#95/3/ 1) /3%543)C/$).$!45E )/5$3../4/5%(/ 2) /3 $3543)C/
$).$!5$55>!) $3!+-%&'()%$#.#$3.#.#$3 .=3!$B&%&'())).$!3)) $3= $3=!%)== $3%
))..$3.%&'()3$!.$ )'(3) /3.=543) C/$).$!..=3!) )/%..=3!) )/%.
5=3>/%%!!$! 3$!!"%&'()=3. $3 )4) /3% 3
&G543)C/$).$!5%$CC%=!%3!=>3=#.#.4$3
01+'"$ $ -.@$
.#.C$3)$=3%!!..=#K.%&(!$!>5I%?&/3 53)$/%9%)).$!%#93)! %&'()#.#)$
3.3 8& 77
4 3E/35/).$!%(C/4&B%' )3)$5"!4 3%>(>I
$!%>'()!()%$'()!')(Reliability) C/=>3$!#)(Alpha Coefficient) !)Cronbach [+(!$!#))$).$ ?..0.968 /3.$!%(/3&!-!$!#
)%.0.957 /34/5%$!#)%.0.923 [+() =/.!0.7
!"5!=>3%9.3)! )E/3\>.I>, 2555) ) 4 3E/35%$$)5 5..)."!3)\Discriminant Power) C/=>3%$$Item-total Correlation [+(.$!%(
/3&!-!$)55\r) ) 0.290 - 0.852 4/5%!$)55
\r) ) 0.325 - 0.797 [+()/$3).$!")!%\2550) E/3%)%B&B$)55 )..)."!0.20 + E#"')3)$5"!!$!%!!
3.4 ;%<% "
.$ 4 3E/3=>3%$"/")..&$ B..
Enter [+(%!E/3/
!HRR = E0 + E1 RR + E2 CR + E3 PR + E4 LR + E5 IR + İ
C/ E $') $!#"/") ǰ 庥 $') $$!$/%$'()
HRR $') .$!%(/3&!-C/!
RR $') .$!%(=/3$/%')34 3!$
CR $') .$!%(=/3.$)./
PR $') .$!%(=/3&G&
LR $') .$!%(=/3!&
IR
$') .$!%(=/3..3)! &.$$4. ! "-'&#
.$!%(/3&!-)#)5%)%!/-7
!4&)#4&.
0 =# 0-;
4+-3)! (E#%(.4 3)...)."!&. #..)#=I%#9.-5/
587 $/%#93)76.30 .$$!/514 $/%#93)12.30 335/
513 $/%#93)11.40 %(%#//5%)#=I%10 #+ E#558
$/%#93)50.90 %5 #–E!"+10 #546 $/%#93)40.30 5(5 #510
$/%#93)8.80 -B)#=I.))C/%3)I>E576
-.= 01+'"$ $
»‚·Õè 11 ©ºÑº·Õè 2 àÁ.Â.-ÁÔ.Â. 62
$/%#93)66.60 %$')=#%E515 $/%#93)13.20 %$')#%515
$/%#93)13.20 .))C/%3)>>58 $/%#93)7.00
)1)$!$/%9.$!%(/3&!-#=)5%)%!/-7 C/!
)(HRR) S.D. ' >
.$!%(=/3$/%')
34 3!$(RR) 4.28 0.61 !(/**
.$!%(=/3.$)./
(CR)
4.20 0.72 !*
.$!%(=/3&G&(PR) 4.14 0.68 !*
.$!%(=/3!&(LR) 4.21 0.69 !(/**
.$!%(=/3..3)! &.$$ (IR) 4.09 0.66 !*
3 4.19 0.57 *
* 3.41-4.20 !"+!/.$!$/%9=/.!
** 4.21-5.00 !"+!/.$!$/%9=/.!(/
1&..$!%(/3&!-!$!$/%9C/&!) =/.!
)/$3))/.I, #& -)B>&I\2554+-%'() 4.).$!%(/3&!-(!4)/5%)%$'()!=#%E 4+-&.4 3#).!$!$/%9/3%(..$!%(/3&!-C/!)
=/.!%!'()&B/3&.) =/.!(/2/3$').$!%(=/3
$/%')34 3!$.$!%(=/3!&) =/.!3/3E/3 .$!%(=/3.$)./.$!%(=/3&G&
.$!%(=/3..3)! &.$$%'()#=)5%)%! !$!!!(=
$/%')&/3=>3..$B!%&'()=3E/3.$(!$! 3$!!"%!!. =3
$!5$I.).$B!.4 3!$=3)/$3).5) #!5/%..
3).$.()/$3).7!/5II(!$!%#9!.$5/$).=3.
.$!$! 3$!!"!"+=3$!5$I.#%!4/!4=&G+).!
.$!..#3)$!#)/%(..3)! &!-)/$3).)&%
&/ )/\2556) +-%'()/$!%(/3..$$))$.5.
C&E)5%)&. !/).>4+-&../$!%(/3..$$
$/5%!..$B!=3%#9E#!$! 3$!!"E!$=3!4#C>%3![
01+'"$ $ -..$
=>3#%!4!=>3=%'() 5/').%%/')=3%#9E#!$! 3 $!!"
#.B).$/54#K.%&'()&G+).!.$
ǰ
)2)$%?(%.(%.!@)4/5%#=)5%)%!/-7C/!
)) S.D. ' >
/3% 4.58 0.63 !(/**
/3 $3 4.31 0.72 !(/**
/3.= 4.17 0.72 !*
/3% 3&G 4.02 0.70 !*
4.27 0.60 **
* 3.41-4.20 !"+!/.$!$/%9=/.!
** 4.21-5.00 !"+!/.$!$/%9=/.!(/
2 &.4/5%#=)5%)%!/-7=&!) =/.
!(/%!'()&B/3&.) =/.!(/2 /3E/3/3%/3 $3) =/.!2 /3 E/3/3.=/3% 3&G[+(#=)5%)%!/-7 E/3=3
$!5$I.4/5%/3%/3 $3C/!45E(%&(!+ ))$ %'()!
./(%&(!+ ))%'()C/#5$55>!) $3!+-%$#.#$3 .=3!$B&%&'())).$!3)) $3=3/(+ )/$3).)!&., /#!B &-%&\2558(+-%'()4.)/.%>(!)4 /5%)#=#%E4+-&.#E/353)5$5>!) $3!%$
#.#.=3!$B&))%'() &G$B&$3').=3!$!//%9!
#&!.=/5%%!!!$!3)) $3 #=)5%)
%! !#.#= $3=!%)== $3%..(!$!
!) )/% C/#.#&=3!$! 3$!!"%&'()=3. $3 ) !"+%!
&=3!$!>5I%?&/3 )/$3).)B.!, &B )+B) 4$
\2559+-%'()4.)!@.(/(!)4/5%)#=#%E 4 +-&.5=#.! )$3)!$/=&G./5%%&'()=3
!").)$!3)) $3 #.#&=3!$! 3$!!"%&'()=3. $3E/3#.#
)$/3% 3&GC/!+).!&G!') -$!>5I)&%!)
-.A 01+'"$ $
»‚·Õè 11 ©ºÑº·Õè 2 àÁ.Â.-ÁÔ.Â. 62
3 %$!&).$!%(/3&!-# =)5%)%!
/-7
-# RR CR PR LR IR VIF
9
4.28 4.20 4.14 4.21 4.09 S.D. 0.61 0.72 0.68 0.69 0.66RR - .73** .74** .60** .56** 2.74
CR - .75** .58** .52** 2.81
PR - .60** .66** 3.37
LR - .76** 2.74
IR - 2.83
**p < 0.01
3 &.#)/3!$!!&)!5$I"(/.0.01 [+() 5=3%/$!!&#) (Multicollinearity) + E/3/ 4 3+E/35/).$VIF )#
.$!%(/3&!-)#!$!&E!%0.80 $VIF ) 2.74 – 3.37 [+(!$3)10 /$!!&)#)E!"+ ()=3%/#I$!!&#) ')Multicollinearity (Black, 2006)
)4 /)..$!%(/3&!-(4)/5%C/!)#
)5%)%!/-7 (HRR)
3
t p-value
#'!O
;;
7 /
$$( 0.66 0.24 2.75 0.00*
1. .$!%(=/3$/%')
34 3!$(CR) 0.21 0.09 2.41 0.02*
2. .$!%(=/3.$).
/(RR) 0.28 0.07 3.82 0.00*
3. .$!%(=/3&G& (PR) 0.14 0.09 1.64 0.10
4. .$!%(=/3!&(LR) -0.08 0.08 -0.99 0.32 5. .$!%(=/3..3)! &
.$$ (IR)
0.32 0.08 3.98 0.00*
F = 51.2, p= 0.000, AdiR2= 0.690
*!5$I"(/.0.05
01+'"$ $ -.B$
4&..$!%(/3&!-=/3..3)! &.$$
/3.$).//3$!%(=$/%')34 3!$
4.)4/5%)#)5%)%!/-7)/$3))/
.I, #& -)B>&I\25544+-&..$!%(
/3&!-/3$!%(=$/%')34 3!$/3.$).
//3..3)! &.$$4.)4/5%)%$'()!=#%E [+(.$!%(=/3..3)! &.$$)#)5%)%!/-7
!..#3)$!#)/%(..3)! &!-!))....3)! &!-(/
C/=>3%$CC%3!#.#/3)! /3&!- '.$3/5=3/%9!
#&(+ )/$3).$/)&>%&B\2555E/3"+=>3%$CC%#9%$'()!')%3!>
=35!$!/.!..#3)(/$)+ 5=3#&=.3)! &' @ /3&!-!$!" 3))/$3).)Berber, orĜeviđ Milanoviđ (2018)+-
%'()/&!-/3..)%9)\Electronic Human Resource Management :e-HRM) :
$/=!5.$/) 4+-&.)$=#.=3$!5$I.5..%$CC!
%!#.=>3./&!-=)$%&'())5$!//%9=3%/#& / ./3)! /3&!-=/3.$!%(=/3.$)./
#=3$!5$I=5/$).=3..$!$! 3$!!"#.B )%#9!)/$3). -K$!%%!\Equity Theory) .$$&B%#.%.)
$!&!=#K..4&(E/3)%)..$$)'(!$!%%!%#9!')E!"3.$$)'(
E/3)4).( 9)()=3%/$!E!.=+ .$))=3%/#I=
#K.+ E/3/ 5/$).)!3$!&)==3.$#3)#I(
4.)#&=/5%))$E/3\@#?(E&, 2559).$!%(=
/3$/%')34 3!$)#E/3=3$!5$I.$/%')&
/3=>3..$B!%&'()=3E/3.$(!$! 3$!!"%!!.=3$!5$I.).
$B!.4 3!$()/$3).5 )/$3)./$!%(/3.
.$$))$.5.C&E)5%)&. !/).>))&%&/
)/ (2556(/5%&3)#K.!..$B!=3%#9E#!$! 3
$!!"E!$=3!4#C>%3![)/$3).$/)BK@&%\ǰ ("+/&!-\HRM)/33$/%').$$E3(5$I#
+(()$3)$/%')$').$$(!$! 3$!!"!$B!.%!!.5(/
/ .$!%(/3&!-=/3..3)! &.$$/3.$).
//3$!%(=$/%')34 3!$+4=3#)5%)%!
/-7!4/5%(/)!5(%!)!45E(%&(!+
-A/ 01+'"$ $
»‚·Õè 11 ©ºÑº·Õè 2 àÁ.Â.-ÁÔ.Â. 62
5. -' "%-'#'3< "
5.1 -' "%
5.1.1 $+-=%&' (/)'(%&'()53)! %#.%.%#9&G.$!
%(/3&!-(!$!$).$!!+
5.1.2 $+-#')4.)'((4).$!%(/3&!-4 /5%+-=!)
5.1.3 $+- #..%$!C$3\Structural Equation Model: SME) =/3 .$!%(/3&!-4/5%
5.2 #'3< "
5.2.1 )$$..#!B=3!&G..3)! &!-%'()..3)!
&!- >=3%&(!/$!!"/34&!-/.$$=3%!!.
.$E/3.&G%)5E/3%9!&!#&
5.2.2 )$$!.=$/%')34 3!$(!#&
C/#>!&.!$4>)=33)$/%').$(!$! 3$!!"
%>(>I=5 %>!!-B')/).-$!%>(>I=
5.2.3 )$$5#=>3%$CC%=!%3!=>3../3)! /3
&!-%&'()/.%3 HR Tech%>)%)%9=(')./3)! Big Data & AI C/4%$CC%/=3!+ %&=#.E/33%3 $)$/!. 33)!
))E!+
6. # "
!"#$%&'()+-/..$!%(/3&!-/.4/5%
+-.$!%(/3&!-(4)4/5%)#)5%)%!
/-7&. .$!%(/3&!-&.C/&!) =/.!/3 ) =/.!(/2/3E/3.$!%(=/3$/%')34 3!$
.$!%(=/3!&) =/.!3/3E/3.$!%(=/3&G
&.$!%(=/3..3)! &.$$/34/5%#=)5%)%!
/-7&.=&!) =/.!(//3) =/.!(/2/3E/3/3%
/3 $3) =/.!2/3E/3/3.=/3% 3&G.$!%(
/3&!-/3$!%(=..3)! &.$$/3$!%(=.$).
//3$!%(=$/%')34 3!$4.)4/5%)
#)5%)%!/-7/ #)5%)%!/-7$!..#3)
$!#)/%(..3)! &!-!))....3)! &!-(/C/=>3
01+'"$ $ -A-$
%$CC%3!#.#/3)! /3&!- &3)! =3$!5$I=5/$).=3.
.$!$! 3$!!"#.B)%#9!!$/%')&/3=>3..
$B!%&'()=3E/3.$(!$! 3$!!"%!!.!(/
&B!, &-C&&&-\2557). 4.)&).) $3
(!)4/5%)C!=$%') ,
7(1), 1-12.
>.I>\2555). =>3SPSS for Windows =%$3)! %&!
B.!&B )+B) 4$ \2559). 4.)!@.(/(!) 4/5%)#=#%E
8(1), 107-120.
@#?(E&\2559). %&>&!&
BK@&%\! %&[%)9/ %$>(ǰ
#(\2555). .&.$$)E=$))#>%#9 "#$%&'(#) *$+'&,-.#$%/-0&1-((02-&/-, 7(1), 60-63.
!&., / #!B &-%&\2558). 4.)/.%>(!)
4/5%)#=#%E!3434
, 34 (3), 255-267 .
&%&/ )/\2556). /$!%(/3..$$))$.
5.C&E )5%)&. ! /).> 56437!!3434, 2 (2), 15-34.
$!")!%\2550). 898:;45<= $3%!'()2 $!2560, http://web.kku.ac.th/nikom/item_relia_validity_2007_u1.pdf
%>&!)\2556). >?@;4A>B8?@
C?<D983E &%-@!.B. !!$!
#B>&-.)/!\2557). ..$!%(/3&.$$)C&.!%9 5#)5%)%!')/5# <FB9, 2 (2), 84 - 96.
&>%&B\2555). !8 @ %&[%)9/ %$>(
!%>, )))"$&GE>3)!\25584.).&-B)$(!
)4/5%)C!=%$%')!3434
, 34 (4), 104-116.
-A8 01+'"$ $
»‚·Õè 11 ©ºÑº·Õè 2 àÁ.Â.-ÁÔ.Â. 62
@&>\2558). >?@DA;4A>B8?@GD983E &.!.B>/%>.!!$!
B)>\2555). !8:;4A8;&!&$ (3. %&
!%-
/BE>%I, ) !%\2554). .$!%(/3&.$$
=C%!!+-)5%)!I$/)37!34H56437!
?A, 5(2), 130-137.
B/-7.( 2559).B9D!I@;EC4J. $3%!'()28 $!
2559 ,http:// http://www.stpho.go.th/rx/down/spa.
\2556). B@34>9F4A8??A?$3%!'()25 2559, http://www.sme.go.th/SiteCollectionDocuments/#.&%20_final.pdf
5.C$3!%!$3#%\2558). @9E.$3%!'()25 2559, http://www.ditp.go.th/contents_attach/143532/143532.pdf
B)#%@\2557). &G!@#=)5%)%!/-7 #>$!%-@
)%[, 1 (1), 125-141.
/.I, #& -)B>&I\2554). 4.).$!%(
/3&!-(!4)/5%)%$'()!=#%E
, 3(1), 96-107.
Berber, N., orĜeviđ, B. & Milanoviđ, S. (2018). Electronic Human Resource Management (e-HRM): A New Concept for Digital Age. K1%'1-20/L'&'2-+-&1, (23) 2, 022-032.
Black, K. (2006). M$.0&-...1'10.10/.N)#%/#&1-+O#%'%PQ-/0.0#&+'R0&2. USA : John wiley and Son.
Economic Intelligence Center (EIC). (2561). *#1-(.O'G@S0&TS0&. $3%!'()12561, https://www.scbeic.com/th/detail/file/product/4383/exu8jbu48o/NOTE_TH_Hotel-
Spa_20180131.pdf
Kaplan, R.S. & Norton, D.P. (1993). Using the balanced scorecard as a strategic management system.
*'%U'%QM$.0&-..,-U0-S, 74 (1), 75-85.
Krejcie, R. V. & Morgan, D. W. (1970). Determining Sample Size for Research Activities. VQ$/'10#&'('&Q W.P/X#(#20/'(L-'.$%-+-&1, 30 (3), 607-610.