個體差異（Individual Differences）在相關工作壓力的組織研究中最常 被設為調節變項（Moderator）。其以各種不同的類型影響壓力結果，主要 談及的人格構面有：A 型行為模式（Type A Behavioral Pattern）、內外控
（Locus of Control）、自尊（Self-esteem）及負向情感（Negative Affectivity）
（Ganster & Schaubroeck, 1991）。本研究未將其列進研究架構之因在於，
文獻上並無直接探討承諾對工作壓力之關係，已偏探索性研究，若再加入 個體差異做為調節變數，恐混淆了本研究驗證型的重點，未來可將此部分 獨立，純以探索性的觀點深入瞭解承諾與工作壓力之關係，並帶入個體差 異，因為人格的養成是壓力宣洩方式的關鍵因素，期使讓整體研究更臻於 完善。
本論文是以員工「變革後」的相關文獻來建立「變革中」的研究架構，
時間點上有比變革後的施測更為精確，雖然實證結果發現兩者大同小異，
但不能就此保證員工在這兩個不同時期的感受程度是相仿的；另一方面，
變革前，組織呈現混沌未明的狀態，下一步組織會往哪裡走，哪些人會是 變革後的倖存者，沒人能保證；這些議題促成了變革前、中、後一連慣性 變革心理學，而組織變革需要時間來消化，檢測前中後期是一個長期的觀 察，若能掌握這方面完整的資訊，相信對個人及組織在面臨變革勢在必行 的當下，有更踏實的安定感。以上提供未來研究一個參考的方向。
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附錄一 問卷設計
第一部份：檢測同仁對於轉型過程的公平認知與轉型本身的喜好程度。
1. 提供足夠的資訊給受轉型（再造）影響的員工（同仁）。
2. 受轉型（再造）影響的員工（同仁）有充足的機會參與決策與制訂。
3. 這次轉型（再造）破壞了所屬單位的工作效率。
4. 這次轉型（再造）的結果會提昇工作的趣味性。
5. 轉型（在造）後，留任的員工（同仁的表現）多數是理想的。
6. 轉型中，公司（單位）保持讓每位員工都有完全的訊息告知。
7. 這次的轉型（再造）增加了所屬單位的困擾。
8. 這次轉型（再造）擾亂了原有的工作模式，例如：工作地點的轉換、
出差的增加等（公文的傳遞方式、訊息溝通管道）。
9. 轉型（再造）的時程、方向、目標與願景不明確。
10. 轉型（再造）後，與上下游廠商（與各單位間）的聯繫會有問題。
第二部分：檢測同仁對於組織與轉型（再造）兩者的承諾。
1. 能大方的跟朋友說 M 公司（自己所屬的單位）是一個優質的公司
（單位）。
2. 我相當在意 M 公司（自己所屬單位）未來的發展。
3. 願意盡心盡力，來協助公司（本單位）一切順利。
4. 在工作表現的方式上，公司（本單位）能給予我最大的鼓舞。
5. 我很高興在 M 公司（本單位）這段時間，為我所重視的人事工作。
6. 能自豪的對他人說，我是 M 公司（這個單位）的一份子。
7. 對我來說，在所有可能的企業（單位）裡，M 公司（這裡）是我工 作最好的選擇。
8. 認同公司轉型為設計發展中心的策略（我認同政府的再造計畫）。
9. 這次的轉型（再造）對於我們公司（所屬單位）來說是好的策略。
10. 我相信這次轉型（再造）的價值。
11. 我會盡可能的協助這次轉型（再造）的成功。
12. 我已經做好這次轉型（再造）的準備，例如：調整心態、學習額外 技能等。
13. 我相信自己可以應付這次的轉變（再造計畫）。
第三部分：檢測同仁在轉型期間的心理健康狀態。
1. 在平常的工作中，我不只一次感到煩躁但卻不知原因為何。
2. 有幾次在工作時，覺得生活實在是付出太多心力了。
3. 我曾在工作的同時懷疑過自己的能力與判斷。
4. 假使交付的任務在一開始就出錯，我會因此缺乏信心且容易驚慌。
5. 回想平常的工作與生活，我覺得自己是一個憂愁的人。
第四部分：基本資料
1. 性別： □男 □女
2. 年齡： □ 30 歲以下 □ 31 歲~40 歲 □ 41 歲~50 歲 □ 51 歲~60 歲 □ 61 歲以上
3. 年資：□未滿 1 年 □ 1 年以上~3 年未滿
□ 3 年以上~6 年未滿 □ 6 年以上~10 年未滿 □ 10 年以上
4. 教育程度：□專科學院 □學士 □碩士 □博士 5. 婚姻狀況：□未婚 □已婚 □鰥寡 □離婚 □分居
附錄二 SAS 指令-信效度檢測
OPTIONS nodate linesize=85 pagesize=60;
DATA THESIS;
INFILE 'D:result\ALL1.prn';
INPUT X1-X28 sex$ age$ service$ edu$ marriage$ Atype$;
X3=6-X3; X7='problem' X8='disruptfun' X9='indefinte'
X10='connecting' X11='greatorg' X12='careorg' X13='helporg' X14='inspire' X15='considerpeo'
X16='proudorg' X17='bestorg' X18='indentify' X19='goodstrategy' X20='changevalue' X21='helpchange'
X22='myselfready' X23='copechange' X24='unsettlt' X25='mucheffort' X26='quesability' X27='lackconfidence' X28='worrier'
F1='changefairness' F2='changefavorableness' F3='obcommetiment' F4='changecommetiment'
FY='jobstress';
RUN;
PROC PRINT label;
TITLE1 'OBG data';
RUN;
PROC CORR DATA=THESIS out=OBGCORR nomiss alpha plots;
VAR X1-X28;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X1 X2 X6;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X3-X5 X7-X10;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X11-X17;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X18-X23;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X24-X28;
RUN;
PROC PRINT DATA=OBGCORR;
TITLE 'Correlation matrix for X1-X45';
RUN;
PROC CALIS CORR modification;
LINEQS
X1=LX1F1 F1+E1, X2=LX2F1 F1+E2, X3=LX3F2 F2+E3, X4=LX4F2 F2+E4, X5=LX5F2 F2+E5, X6=LX6F1 F1+E6, X7=LX7F2 F2+E7, X8=LX8F2 F2+E8, X9=LX9F2 F2+E9, X10=LX10F2 F2+E10, X11=LX11F3 F3+E11, X12=LX12F3 F3+E12, X13=LX13F3 F3+E13, X14=LX14F3 F3+E14, X15=LX15F3 F3+E15, X16=LX16F3 F3+E16, X17=LX17F3 F3+E17, X18=LX18F4 F4+E18, X19=LX19F4 F4+E19, X20=LX20F4 F4+E20, X21=LX21F4 F4+E21, X22=LX22F4 F4+E22, X23=LX23F4 F4+E23, X24=LX24FY FY+E24, X25=LX25FY FY+E25, X26=LX26FY FY+E26, X27=LX27FY FY+E27, X28=LX28FY FY+E28;
F4=1,
F1 F2=CF1F2, F1 F3 =CF1F3, F1 F4=CF1F4, F1 FY=CF1FY, F2 F3 =CF2F3, F2 F4=CF2F4, F2 FY=CF2FY, F3 F4=CF3F4, F3 FY=CF3FY, F4 FY=CF4FY;
VAR X1-X28;
TITLE 'CFA for F1-FY';
RUN;
附錄三 SAS 指令-CFA 與迴歸分析
OPTIONS nodate linesize=85 pagesize=60;
DATA THESIS;
INFILE 'D:result\OBC1.prn'; X7='problem' X8='disruptfun' X9='indefinte'
X10='connecting' X11='greatorg' X12='careorg' X13='helporg' X14='inspire' X15='considerpeo'
X16='proudorg' X17='bestorg' X18='indentify' X19='goodstrategy' X20='changevalue' X21='helpchange'
X22='myselfready' X23='copechange' X24='unsettlt' X25='mucheffort' X26='quesability' X27='lackconfidence' X28='worrier'
F1='changefairness' F2='changefavorableness' F3='obcommetiment' F4='changecommetiment' FY='jobstress';
RUN;
PROC PRINT label;
TITLE1 'OBG data';
RUN;
PROC CORR DATA=THESIS out=OBGCORR nomiss alpha plots;
VAR X1-X28;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X1 X2 X6;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X11-X17;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X18-X23;
RUN;
PROC CORR DATA=THESIS nomiss alpha plots;
VAR X24-X28;
RUN;
PROC PRINT DATA=OBGCORR;
TITLE 'Correlation matrix for X1-X45';
RUN;
PROC CALIS CORR modification;
LINEQS
X1=LX1F1 F1+E1, X2=LX2F1 F1+E2, X3=LX3F2 F2+E3, X4=LX4F2 F2+E4, X5=LX5F2 F2+E5, X6=LX6F1 F1+E6, X7=LX7F2 F2+E7, X8=LX8F2 F2+E8, X9=LX9F2 F2+E9, X10=LX10F2 F2+E10, X11=LX11F3 F3+E11, X12=LX12F3 F3+E12, X13=LX13F3 F3+E13, X14=LX14F3 F3+E14, X15=LX15F3 F3+E15, X16=LX16F3 F3+E16, X17=LX17F3 F3+E17, X18=LX18F4 F4+E18, X19=LX19F4 F4+E19, X20=LX20F4 F4+E20, X21=LX21F4 F4+E21, X22=LX22F4 F4+E22, X23=LX23F4 F4+E23, X24=LX24FY FY+E24, X25=LX25FY FY+E25, X26=LX26FY FY+E26, X27=LX27FY FY+E27, X28=LX28FY FY+E28;
STD F1=1, F2=1, F3=1,
F4=1,
F1 F2=CF1F2, F1 F3 =CF1F3, F1 F4=CF1F4, F1 FY=CF1FY, F2 F3 =CF2F3, F2 F4=CF2F4, F2 FY=CF2FY, F3 F4=CF3F4, F3 FY=CF3FY, F4 FY=CF4FY;
VAR X1-X28;
DATA THESIS;
PROC CALIS DATA=THESIS CORR RESIDUAL MODIFICATION;
LINEQS
X18=1.0 F4 + E18,
F3=PF3F1 F1+PF3F2 F2+PF3H1 H1+PF3I1 I1+PF3I2 I2+PF3I3 I3+
PF3J1 J1+PF3J2 J2+PF3J3 J3+PF3J4 J4+PF3K1 K1+PF3K2 K2+
PF3L1 L1+PF3L2 L2+D1,
F4=PF4F1 F1+PF4F2 F2+PF4H1 H1+PF4I1 I1+PF4I2 I2+PF4I3 I3+
PF4J1 J1+PF4J2 J2+PF4J3 J3+PF4J4 J4+PF4K1 K1+PF4K2 K2+
PF4L1 L1+PF4L2 L2+D2,
FY=PFYF1 F1+PFYF2 F2+PFYF3 F3+PFYF4 F4+PFYH1 H1+PFYI1 I1+
PFYI2 I2+PFYI3 I3+PFYJ1 J1+PFYJ2 J2+PFYJ3 J3+PFYJ4 J4+
PFYK1 K1+PFYK2 K2+PFYL1 L1+PFYL2 L2+D3;
STD
F1 F2=VARF1 VARF2, E1-E28=VARE1-VARE28,
D1 D2 D3=VARD1 VARD2 VARD3, H1=VARH1,
F1 F2=CF1F2, F1 H1=CF1H1, F1 I1=CF1I1, F1 I2=CF1I2, F1 I3=CF1I3, F1 J1=CF1J1, F1 J2=CF1J2, F1 J3=CF1J3, F1 J4=CF1J4, F1 K1=CF1K1, F1 K2=CF1K2, F1 L1=CF1L1,
F2 I3=CF2I3, F2 J1=CF2J1, F2 J2=CF2J2, F2 J3=CF2J3, F2 J4=CF2J4, F2 K1=CF2K1, F2 K2=CF2K2, F2 L1=CF2L1, F2 L2=CF2L2, H1 I1=CH1I1, H1 I2=CH1I2, H1 I3=CH1I3, H1 J1=CH1J1, H1 J2=CH1J2, H1 J3=CH1J3, H1 J4=CH1J4, H1 K1=CH1K1, H1 K2=CH1K2, H1 L1=CH1L1, H1 L2=CH1L2, I1 I2=CI1I2, I1 I3=CI1I3, I1 J1=CI1J1, I1 J2=CI1J2, I1 J3=CI1J3, I1 J4=CI1J4, I1 K1=CI1K1, I1 K2=CI1K2, I1 L1=CI1L1, I1 L2=CI1L2, I2 I3=CI2I3, I2 J1=CI2J1, I2 J2=CI2J2, I2 J3=CI2J3, I2 J4=CI2J4, I2 K1=CI2K1, I2 K2=CI2K2, I2 L1=CI2L1, I2 L2=CI2L2, I3 J1=CI3J1, I3 J2=CI3J2, I3 J3=CI3J3, I3 J4=CI3J4, I3 K1=CI3K1, I3 K2=CI3K2, I3 L1=CI3L1,
I3 L2=CI3L2, J1 J2=CJ1J2, J1 J3=CJ1J3, J1 J4=CJ1J4, J1 K1=CJ1K1, J1 K2=CJ1K2, J1 L1=CJ1L1, J1 L2=CJ1L2, J2 J3=CJ2J3, J2 J4=CJ2J4, J2 K1=CJ2K1, J2 K2=CJ2K2, J2 L1=CJ2L1, J2 L2=CJ2L2, J3 J4=CJ3J4, J3 K1=CJ3K1, J3 K2=CJ3K2, J3 L1=CJ3L1, J3 L2=CJ3L2, J4 K1=CJ4K1, J4 K2=CJ4K2, J4 L1=CJ4L1, J4 L2=CJ4L2, K1 K2=CK1K2, K1 L1=CK1L1, K1 L2=CK1L2, K2 L1=CK2L1, K2 L2=CK2L2, L1 L2=CL1L2;
VAR X1-X28 H1 I1-I3 J1-J4 K1 K2 L1 L2;
TITLE 'Path analysis for F1-FY';
RUN;
PROC STANDARD M=0 S=1 OUT=NEWTHESIS;
VAR F1-F4 FY;
RUN;
DATA NEWTHESIS;
SET NEWTHESIS;
IF sex='1' THEN H1=1;
ELSE H1=0;
IF age='1' THEN I1=1;
IF service='1' THEN J1=1;
PROC REG DATA=NEWTHESIS;
VAR F1-F4 FY H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
MODEL FY=F3 F4 H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
OUTPUT OUT=A R=RES1;
TITLE 'Multiple regression by PROC REG FY F3';
RUN;
PROC REG DATA=NEWTHESIS;
VAR F1-F4 FY H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
MODEL FY=F3 F4 F1 F2 H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
OUTPUT OUT=B R=RES2;
TITLE 'Multiple regression by PROC REG FY F4';
RUN;
PROC REG DATA=NEWTHESIS;
VAR F1-F4 FY H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
MODEL F3=F1 F2 H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
OUTPUT OUT=C R=RES3;
TITLE 'Multiple regression by PROC REG F1 F2 F3';
RUN;
PROC REG DATA=NEWTHESIS;
VAR F1-F4 FY H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
MODEL F4=F1 F2 H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
OUTPUT OUT=D R=RES4;
TITLE 'Multiple regression by PROC REG F1 F2 F4';
RUN;
PROC REG DATA=NEWTHESIS;
VAR F1-F4 FY H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
MODEL FY=F1 H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
OUTPUT OUT=D R=RES5;
TITLE 'Multiple regression by PROC REG F1 FY';
RUN;
PROC REG DATA=NEWTHESIS;
VAR F1-F4 FY H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
MODEL FY=F2 H1 I1 I2 I3 J1 J2 J3 J4 K1 K2 L1 L2;
OUTPUT OUT=D R=RES6;
TITLE 'Multiple regression by PROC REG F2 FY';
RUN;
PROC UNIVARIATE DATA=A NORMAL PLOT;
VAR RES1;
TITLE 'Test for normal of the error term FY F3';
RUN;
PROC UNIVARIATE DATA=B NORMAL PLOT;
VAR RES2;
TITLE 'Test for normal of the error term FY F4';
RUN;
PROC UNIVARIATE DATA=C NORMAL PLOT;
VAR RES3;
TITLE 'Test for normal of the error term F1 F2 F3';
RUN;
PROC UNIVARIATE DATA=D NORMAL PLOT;
VAR RES4;
TITLE 'Test for normal of the error term F1 F2 F4';
RUN;