This is my multi-variate analysis report. paper from:Journal of Business Ethics Mubako, G., Bagchi, K., Udo, G., & Marinovic, M. (2020). And another one - Responsible Artificial Intelligence (AI) for Value Formation and Market Performance in Healthcare from Information Systems Frontiers Pradeep Kumar, Yogesh K. Dwivedi & Ambuj Anand (2021).

1. Multi-Variate Analysis
Final report by 0624011 陳佑昇
Personal Values and Ethical Behavior in Accounting Students
Journal of Business Ethics
Mubako, G., Bagchi, K., Udo, G., & Marinovic, M. (2020).

2. JCR
/25
1
(SSCI)

3. Table of
Contents
Introduction
01
Theory and Hypotheses Development
02
Research Methodology
03
Results and Hypothesis Testing
04
Discussion
05
Another paper - Responsible Artificial Intelligence (AI) for
Value Formation and Market Performance in Healthcare
06
/25
2 Future research direction
07

4. Introduction
Ethical behavior is one of the key requirements of accounting professionals
How personal values affect
ethical behavior of accountants
based on the updated Schwartz
personal value scale.
Provides further evidence on
how gender, religiosity, and
ethics training relate to
personal values.
/25
3

5. Theory and Hypotheses Development
Literature review (1/4)
Relationship between personal values and ethical behavior
Finegan(1994) People with different value hierarchies perceived the targeted behaviors differently.
Roig and Ballew (1994) An individual’s choice to engage in academic dishonesty
depends on his personal value system.
Akaah and Lund (1994) Personal and organizational values significantly influence their ethical behavior.
Fritzsche and Oz (2007) Personal values influence managers’ decisions when faced with ethical dilemmas.
Maclagan (2004) Personal values influence corporate social responsibility practices adopted by
managers.
Rosario et al (2014) Examined how values influenced attitudes towards social initiatives of
organizations using the Schwartz Value Theory.
Schmidt (2015) Explore the impact of personal values on ethical behavior of accounting students
and conclude that values indeed influence ethical decision making.
/25
4

6. Theory and Hypotheses Development
Literature review (2/4)
Gender and Ethical Behavior
Smith and Oakley
III (1997)
Observe significant differences between male and female responses to
questions concerning ethics in social and personal relationships (318 business students).
Glover et al. (1997) Men were 1.5 to 2.3 times more likely than women to engage in economically
unethical behaviors.
Roozen et al. (2001)
and Razzaque and
Hwee (2002)
Do not report gender differences in ethical behavior.
Loe et al. (2000)
and O’Fallon and
Butterfeld (2005)
Either there are no gender differences or that females are more ethical than males, with
more studies pointing to more ethical behavior in females.
Lua and Yuen (2013) Males seem to be involved in riskier online behaviors than females.
Jafarkarimi et al.
(2016)
Identify the factors affecting ethical decision-making of social network users and find
that gender has a significant effect on ethical decision making.
/25
5

7. Theory and Hypotheses Development
Literature review (3/4)
Religiosity and Ethical Behavior
Khavari and Harmon (1982) Religion influences behaviors like use of illicit substances.
Hood et al. (1996) Religion does not influence unethical behaviors such as cheating or dishonesty.
Keller et al. (2007) Accounting students are more likely to make ethical decisions based on religious
standards.
Bloodgood et al. (2008) Religious undergraduate business students are less likely to cheat than the non-
religious ones.
Oumlil and Balloun (2009) Rligiosity does not influence ethical intentions.
Jafarkarimi et al. (2016) Influential factors affecting individuals’ ethical decision-making of social network
users and observe that religion has a positive effect on ethical decision making.
/25
6

8. Theory and Hypotheses Development
Literature review (4/4)
Ethics Training and Ethical Behavior
Geiger and O’Connell (1998)
and Stead et al. (1990)
Ethics training for employees can improve ethical behavior.
Luthar and Karri (2005) Exposure to ethics in the curriculum courses had a positive efect on perceptions
of an ideal ethical climate.
Abdolmohammadi (2005) Using the case-based pedagogy to teach ethics to graduate students can
increase performance in ethical reasoning.
Luthar and Karri (2005), Effect of ethics training on ethical behavior
Cagle and Baucus (2006) Ethics scandals positively impacts finance students’ ethical decision-making.
/25
7

9. H1a：Openness to Change influences ethical behavior.
H1b：Self-Enhancement influences ethical behavior.
H1c：Conservation influences ethical behavior.
H1d：Self-Transcendence influences ethical behavior
Theory and Hypotheses Development
Hypotheses Development (1/2)
Schwartz’s model.
Adapted from Schwartz (2017)
/25
8

10. H3 Religiosity influences ethical behavior.
H4 Ethics training influences ethical behavior.
H5 The proposed research models will not be the same when gender is used as a divider.
H6 The proposed research models will not be the same when religiosity is used as a divider.
Theory and Hypotheses Development
Hypotheses Development (2/2)
/25
9

11. Theory and Hypotheses Development
Research model
/25
10

12. Research
Methodology
This Photo by Unknown Author is licensed under CC BY-SA-NC
/25
11
Online
Survey
• Four-year university in US
• Total：318
Respond • Total：
262 (82%)
Invalid
• Total：
252
(79%)

13. Research Methodology
/25
12
Dependent Variable—Ethical Behavior
• 17 Questions ( base on Akaah
and Lund[1994] )
• 7 point Likert scale where 1
represented ‘extremely
unlikely’ and 7 represented
‘extremely likely’.
(more high mean more
unethical)
• Calculating a mean response
score
Personal
use
Passing
blame
Bribery
Falsifcation
Padding
expenses
Deception

14. Research Methodology
/25
13
Independent Variables—Personal value
• 19 LOVs, 57 Statements
• 6 point Likert scale where 1
represented ‘not like me at all’
and 6 represented ‘very much
like me’.
• Calculating a mean from each
statement of LOVs
Schwartz’s model.
Adapted from Schwartz (2017)

15. Research Methodology
/25
14
Independent Variables—Gender/Religiosity/Ethics training
What is your gender?
• 1(Male), 2(Female)
Are you religious?
• 1(Yes), 2(No)
Number of courses done with
an ethics component.
• (Positive integer)

16. Research Methodology
/25
15
Model Validation
Using factor-based partial least squares structural equation modeling (SEM)
techniques using WARP PLS software.
Table 3 Reliability and validity tests

17. Research Methodology
/25
16
Model Validation
• Discriminant validity (AVE v.s. correlation)

18. Results and Hypothesis Testing
/25
17
PSL-based structural equation modeling

19. Results and Hypothesis Testing
/25
18
Multi-group analysis (Gender/Religiosity)
Table 8 Religiosity
multi-group
analysis
Table 7 Gender
multi-group
analysis

20. Discussion
/25
19
Conclusion
 This is the first attempt to apply Schwartz’s recently redefined values to the
study of ethical behavior.
 The positive effect of ethics training is seen despite the general lack of
consensus on what should be the best approach.
 Self-Enhancement since the results seem to suggest that this personal value is
positively associated with unethical behavior.

21. Another paper
Responsible Artificial Intelligence (AI)
for Value Formation and Market
Performance in Healthcare: the
Mediating Role of Patient’s Cognitive
Engagement
/25
20

22. Another paper
Research design
/25
21
Fig. 3 Research design
進行一項混和研究，調查醫療保
健反饋式AI的組成部分，驗證其
價值形成與市場中的作用表現
第一階段訪談，解釋構面相關
第二階段隨機抽樣問卷調查，了
解反饋式AI重要因子構面關係
第三階段滾雪球問卷調查，了解
此模型的強度與市場表現

23. Another paper
Part1. Interviews
/25
22
共12人(專業醫療保健人員)
每次40-60分鐘
發現構面
• 資料(公平收集性)
• 演算法(通知解釋清楚)
• 個人道德(尊重自主權)
• 服務倫理(避免侵犯隱私)
• 適應性(能快速配置)
• 合作(提供協助)
• 顯現度(對利害關係人透明)

24. Another paper
Part2. SEM
-隨機抽樣問卷調查
/25
23
回覆共290(專業醫療保健人員)
五點量表、共7構面/26題
結論
• 通過模型驗證 (CR均
>=0.764、AVE>=0.504、
Factor loading >= 0672、
區別效度AVE法通過)
• 支持上頁提到的中介構面(技
術技能、道德關切及風險緩
解)，全部具顯著差異

25. Another paper
Part3. SEM
-滾雪球問卷調查
/25
24
回覆174對(保健人員推薦2-3位)
五點量表、共4構面/16題
結論
• 通過模型驗證 (CR均>=0.81、
AVE>=0.525、Factor
loading >= 0662、區別效
度AVE法通過)
• 沿用Part2組成新的模型，
發現最終結果與訪談一致，
降低風險是最重要因素
Fig. 6 Bootstrapping – validated conceptual model. *path coefficient and p-values
Table 8 Hypothesis testing
市場表現
認知參考
(安全)
終值
工具價值

26. Future research direction
/25
25
Edge
computing
因應硬體發展，預計實作
一些AI 應用在終端裝置
(如微晶片控制器、手機)
AIOT
(AI、IoT)
市場分
析(應用
SEM)
前後測問卷分
析，調查應用
的市場需求

27. Thank you