From INFORMATION & MANAGEMENT Jacob Chia-An Tsai, James J. Jiang, Gary Klein, Shin-Yuan Hung Presenter ：CHEN,YOU-SHENG (Shane) 2022/05/06

1. Legacy information system
replacement: Pursuing quality design
of operational information systems
From INFORMATION & MANAGEMENT
Jacob Chia-An Tsai, James J. Jiang, Gary Klein, Shin-Yuan Hung
Presenter ：CHEN,YOU-SHENG (Shane) 2022/05/06

2. JCR For INFORMATION & MANAGEMENT
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3. Vocabularies 1/3
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P. English Chinese
1
information elaboration
theory (IET)
資訊精化理論
1 drag 累贅
1 turbulent 動盪
1 amplifies 放大
1 arose 產生
1 lackluster 平凡
1 disparate 不相干
1 referred 首選
2 collective 集體
2 underscores 強調
P. English Chinese
2 commence 開始
2 controversies 爭論
2 obsolete 廢棄
2 resistance 抗拒
2 impedes 阻礙
3 traits 特徵
3 commonality 共性
3 transient 短暫的
3 niche areas 商機
3 know-how 專業知識

4. Vocabularies 2/3
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P. English Chinese
3 scope of authority 權力範圍
3 mobilizes 調動
4 mitigate 減輕
4 advocates 提倡
4 sound decisions 合理的決策
4 cognitive load theory 認知負荷理論
4 consideration of the full
picture
全面考慮
4 extensive
and exhaustive
廣泛且透徹
4 mutually beneficial 互惠的
P. English Chinese
4 rationale 理由
4 synthesize 綜合
4 sophisticated 複雜
4 contingencies 意外事件
4 accommodate 調解
4 acknowledged 承認
4 routines 例行公事
4 incompatible 矛盾
5 surmount 克服
5 tackle 阻截

5. Vocabularies 3/3
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P. English Chinese
5 tacit 默認
5 asymmetry 不對稱
5 reliance 依賴
5 pro-actively 積極主動
5 induce 催生
6 dissenting opinions 反對意見
6 courses of action 行動方針
6 mutual 相互
6 taking account of 考慮到
6 deviations 偏離
6 divergent views 大相徑庭的觀點
6 confidentiality 保密性
P. English Chinese
6 safeguards 保障
6 confounding 混淆
6 maximum likelihood
estimation (MLE)
最大概似估計法
8 social desirability
responding (SDR)
社會期許誤差
9 portray 描繪
12 deserve 應得
12 discrepancies 差異
12 political correctness 合時宜
13 inadequate 不適當
13 disarray 混亂

6. Table of Contents
Introduction
Background
Methodology
Data analysis and results
01
02
03
04
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Discussion
Conclusion
05
06

7. Introduction
01
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8. Legacy information systems
LIS are information systems (IS) based on outdated technologies
but still critical to an organization.
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In 2011, MS-DOS was still used in some enterprises to run legacy applications, such as this
US Navy food service management system. (U.S. Navy photo by John F. Williams)

9. Introduction
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LIS solved only a single business issue
Designing a system during a significant change to the environment
The original functionality must also extend to the new system design in an
expanded scope
LIS replacement projects often result in lackluster outcomes
The literature splits into a focus on
• a preferred development methodology (eg. agile approaches)
• managing interactions of the development team
(mostly ignored by researchers)

10. Introduction
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We propose that a properly constructed team of development partners and
information elaboration processes will effectively pursue a quality design
for LIS replacement
We propose a framework that explicates the creation of the extended team
as knowledge resources and integrates the elaboration processes
Research question
if information elaboration processes with extended knowledge
sources improve the design of LIS replacements

11. Background
02
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12. Legacy information systems (LIS)
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2019 L. Kappelman et al. Legacy systems often fail on responsive to change
and integrative organizational functions.
2018 PWC
2010
B. Furneaux, M.
Wade
An increasing number of legacy components become
obsolete for reasons of reliability, suitability, and
supportability.
2019 H.A. Bakar et al.
The legacy process model continuation often causes
resistance to use, impedes the organization from achieving
IT transformation and fails to deliver the expected results
2012 A. Alexandrova
Technical motivation and advancement are not
sufficient to ensure the quality design of LIS

13. Core team
Responsible
for taking top
management guidance
and transforming
Accountable
for the achievement
of business goals
Decision authority
on how the system
should be designed
and implemented
Resolving differences
is central to resolving
differences among
functional units
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D. Gerster et al. (2018), M. Hoegl (2005), O. Ibert (2004)

14. Extended team (End-users)
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2001
C.V. Brown and
I. Vessey
End-users on the extended team provide feedback on
the system functionality and usability to avoid possible
pitfalls in system design and further ensure the
renewal systems will be accepted by the user
community.
2001 Gartner
2020 P. Vitharana, A. Basu
Awareness of business operations and internal
changes
2012 J.S.C. Hsu et al.
Support operational objectives and enhance business
processes
2001 Gartner End-users can provide informational links

15. Extended team (External experts)
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2008 V. Dewangan External experts may include specialists on hardware,
quality assurance, and software engineers to address
technical niche areas
1998 L. Dube
2020
S.M. Nuwangi and D.
Sedera
Provides the know-how to understand the technical
limitations
2015 A. Alexandrova et al.
Add further information about new technology and
business climate changes presenting alternative views
2017 M. Ali, L. Miller
2019
R. Linden and C.
Rosenkranz

16. Team actors
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Actors Designations
Technical
leaders
Those in the core team holding positions of authority over
technical design issues.
Functional
leaders
The primary representatives of each functional area, holding
knowledge, and authority to decide the features and operations
of the LIS system for the functional unit they represent.
Table 1
Teams and actors in the system design phase.
Core team members serve for the duration of the project

17. Team actors
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Actors Designations
End-
users
End-users from the functional areas who will interact with the LIS
as a consumer or producer of information. They own specific
operational knowledge of day-to-day operations.
External
experts
External experts of outside organizations steeped in industry best
practices about technical solutions, business process
standardization, and the external environment.
Table 1
Teams and actors in the system design phase.
Extended team members serve during limited time
frames and hold no responsibility in the decision process

18. • Information elaboration utilizes and mobilizes
knowledge resources between diverse actors to
improve processes reliant on the information.
(S. Uitdewilligen, 2004)
• To achieve an expected team performance,
members must exchange, discuss, project, and
integrate the dispersed task-relevant information.
(D. Van Knippenberg, 2007)
Information elaboration theory (IET)
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19. Information elaboration theory (IET)
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2007
D. Van Knippenberg
and M.C. Schippers
Provide group members with a larger pool of
knowledge resources relevant to the group’s task.
The implications for their area of expertise and integrate
different perspectives into an optimal solution
2004
D. Van Knippenberg
et al.
The differences inherent among perspectives and
opinions can lead the core team to understand the task
and develop a quality decision
2014 C.J. Resick et al.
The core team leverages diverse knowledge to develop
adaptive solutions to meet complexity

20. Information elaboration theory (IET)
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21. Information elaboration theory (IET)
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22. Hypotheses- Research model
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Fig. 1. Research model.

23. Hypotheses- H1a
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H1a
2003
K.A. Jehn
and C.
Bendersky
Constructive debate helps group
members to identify alternatives and
make quality decisions
2004
S. Park et al.
To synthesize different perspectives and
evaluate different solutions
2017
M. Ali and L.
Miller
Mutual learning, leading to better
performance
2010
T.P. Liang et
al. Improves development performance
H1a: Constructive debate positively
influences system design quality.

24. Hypotheses- H1b
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H1b
2020
A. Alexiev et
al.
Uncovers new insights to enhance the
quality of new products
2006
R.V. Bradley
et al.
Draw from diverse functional knowledge
to generate sophisticated plans
2001
B.H. Wixom
and H.J.
Watson
System quality is achieved through
searching alternatives and considering
contingencies
H1b: Comprehensiveness positively
influences system design quality.

25. Hypotheses- H1c
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H1c
2019
Bruccoleri et
al.
Positively associated with higher
performance
2001
S.Mohammed
and E.
Ringseis
Better understanding of the group
product
2014
J.J. Jiang et
al.
Can improve the identification of
problems during IS development
H1c: An integrative solution positively
influences system design quality.

26. Hypotheses- H2a
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H2a
2012
A. Tiwana
End-users usually have knowledge of
the particular routines and practices
2004
M.L. Markus
and J.Y. Mao,
Introduce incompatible and new
views that draw on differences in their
interests and experiences
2004
D. Van
Knippenberg
et al.
Facilitate an open and informed
debate to the core team because end-
users bring their differing assumptions
to the surface
H2a: End-user input positively
influences constructive debate

27. Hypotheses- H2b
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H2b
2006
E.T.G. Wang
and J.H.F.
Chen,
The core team can know where they
stand concerning desired features and
functionalities
2012
A. Tiwana
To formulate alternatives and identify
major concerns
2018
I.J.J.
However et al.
Can conduct more information
searching, evaluate various options
Manage hidden information more
carefully
H2b: End-user input positively
influences comprehensiveness

28. Hypotheses- H2c
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H2c
2006
E.T.G. Wang
and J.H.F.
Chen,
Reaching an integrative design
requires a shared agreement on
design issues
2012
A. Tiwana
Can clarify local needs and provide a
rationale for requirements
2018
I.J.J.
However et al.
Can understand different
perspectives by developing an
integrative solution
H2c: End-user input positively
influences integrative solutions

29. Hypotheses- H3a
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H3a
1999
T.
Ravichandran
and A. Ra
Is useful in design as it helps the design
team to develop a mutual understanding
of ideals and constraints through
controversy
2012
D.G. Ko et al.
Provides guidelines for migrating data
and manipulating system configurations
and induces potential conflicts with
legacy knowledge
2019
R. Linden and
C. Rosenkranz
2006
E.T.G. Wang
and J.H.F.
Chen
H3a: End-user input positively
influences integrative solutions

30. Hypotheses- H3b
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H3b
2010
G.S. Dawson
et al.
The tacit knowledge from outside the
core team that further improves
design specification (helps the core
team to design a complete system)
2019
R. Linden and
C. Rosenkranz
They analyze the business needs and
processes, recommend technical
solutions, and suggest replacements
(increase the core team’s
comprehensive analysis and technical
understanding)
H3b: External expert input positively
influences comprehensiveness

31. Hypotheses- H3c
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H3c
2019
R. Linden and
C. Rosenkranz
Creates closer interaction and
communication, facilitating knowledge
transfer and reducing information
asymmetry
1999
T.
Ravichandran
and A. Rai
Encourage the core team to reduce
reliance on legacy knowledge pools,
consider best management practices,
and integrate industry perspectives
of certain problems into the final
decision
H3c: External expert input positively
influences integrative solutions

32. Hypotheses- H4a
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H4a
2009
M. Dayan et al.
Intensive debate have difficulties
detecting cause-effect relationships
2011
S. Elbanna et
al.
Cannot make effective decisions in
highly turbulent conditions
2009
L.M.
Marupinget al.
Increases the risks of dissenting
opinions that distract from the original
objectives
H4a: Change complexity negatively
moderates the effect of constructive
debate on system design quality

33. Hypotheses- H4b
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H4b
2007
A.C. Homan
et al.
Comprehensiveness involves a
more objective and rational
process to efficiently use the
information cues
2004
B.A. Walters
and S.N.
Bhuian
Decision-makers give more
precise estimates
1993
K. Sengupta
and T.K
Abdel-Hamid
They have access to multiple
knowledge bases to evaluate
and verify alternative courses
of action
H4b: Change complexity positively
moderates the effect of comprehensiveness
on system design quality

34. Hypotheses- H4c
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H4c
2005
S. Gosain et
al.
Better decisions reflect the
diverse organizational and
environmental needs
2014
A. Barua and
D. Mani
Change complexity creates an
increased number of
deviations and requires
integrating divergent views
H4c: Change complexity will positively
moderate the effect of an integrative solution
on system design quality.

35. Hypotheses- Control variables
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2001
L.A.
DeChur
ch and
M.A.
Marks
Groups low on active conflict
management prefer to accommodate
others and normally avoid open
discussion of disagreements
CS
AS
2000
S.
Alper et
al.
Interdependent goals positively
affect controversy as they lead to an
open-minded discussion of
differences for mutual benefit
GI
2017
C.I.
Farh et
al.
Teams with higher cognitive
ability possess a more accurate
understanding of team tasks
TCA

36. Methodology
03
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37. Random sampling
method on
companies in China
Members
Target population Sampling
Technical leaders from the IT department,
functional leaders are lower managers
from operational departments
LIS replacements in
medium to
large companies
Methodology
Survey target
Two surveys went to each
organization (IT & functional
& same project)
Mail and return
■ Introductory letter
■ Return envelope
■ Follow-up phone calls
Confidentiality
Only the research team had the means
to match the two surveys to the single
LIS replacement
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38. CVR and CVI of all items are
>the cut-off value of 0.8
Amount of target sample
Total survey pairs Content translation
ensures that our target sample (N = 500)
represents the wide range of LIS
replacements at medium &large companies
132 pairs (-6 with
omitted items after)
Methodology
Data validation
CMV is not an issue
SDR is not an issue
Data analysis
■ PLS-SEM
■ bootstrap resampling of
2000 instances
■ CR > 0.7 [85]
■ AVE > 0.5 [33]
■ HTMT < 0.9 [45]
■ Correlation < 0.8 [33]
■ CMB [86]
■ SDR[66]
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39. Measurement items (1/4)
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40. Measurement items (2/4)
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41. Measurement items (3/4)
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42. Measurement items (4/4)
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43. Sample characteristics
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44. Data analysis and results
04
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45. Measurement model
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>0.7 >0.7 >0.5

46. Measurement model
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Correlation <0.8
(HTML) <0.9

47. Structural model
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Control variables
Goal
interdepe-
ndence
CD 0.26*
COM 0.21*
IS 0.17*
Team
cognitive
ability
CD 0.13
COM 0.04
IS 0.23*
Comprising
strategy
SDQ 0.11
Avoiding
strategy
SDQ (0.06)

48. Meditation tests
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49. Meditation tests
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Estimate 90% CI 95% CI
Direct effect
End-user→SDQ 0.18 [-0.002, 0.276] [-0.037, 0.322]
External Expert→SDQ 0.25 [0.132, 0.368] [0.093, 0.403]
Total effect
End-user→SDQ -0.21 [0.160, 0.305] [0.142, 0.325]
External Expert→SDQ 0.11 [0.046, 0.146] [0.032, 0.159]
• The significant total effects provided evidence to support the set of IET variables
can transmit the indirect effect of knowledge input from the extended team

50. Moderation- CC
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X: Constructive debate
Y: SDQ
High change complexity
X: Comprehensiveness
Y: SDQ
High change complexity

51. Discussion
05
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52. Discussion (result 1/4)
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• Comprehensiveness is a critical
underlying mechanism that
can translate greater
information richness into
better decisions.
[46,72,101]

53. Discussion (result 2/4)
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• The three processes are
positively influenced by the
knowledge provided by end-
users and external experts
• The extended team inputs
provide informational value
and promote the discovery
of deeper perspectives
• Knowledge inputs ↑
the chances of better design
quality increase
[91,101]

54. Discussion (result 3/4)
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• End-user knowledge inputs are
more strongly associated with
the elaboration processes than
knowledge inputs from external
experts
• The total impact of external
experts on system design quality
is greater than that of end-
users so external expertise
should be incorporated into the
elaboration techniques to gain
their full benefit.
Direct effect
End-
user→SDQ
0.18
External
Expert→SDQ
0.25
Total effect
End-
user→SDQ
-0.21
External
Expert→SDQ
0.11
[30,43,93]

55. Discussion (result 4/4)
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• Comprehensiveness is the more
critical mechanism in coping with
change complexity
• Having teams openly debate the
task-related issues to stimulate new
ideas is more appropriate when the
environment is relatively stable
because they can more easily build
X: Constructive debate
Y: SDQ
High change complexity
X: Comprehensiveness
Y: SDQ
High change complexity
[5,63,117]

56. Discussion (managerial)
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A diverse team composition provides an important basis for information
diversity for the core team
• Result in a better-quality decision
• Enhancing teams with end-users who have high levels of operational knowledge
The core team should consider ways to mobilize informational resources
and create engagement in information elaboration
• In changing conditions → develop a consensus and perform a comprehensive analysis
• Should be cautious of debate that may lead to overwhelming information disarray
• External experts, it is important to create an atmosphere of trust and mutual
understanding

57. Discussion (managerial & limitations)
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The core team should be sensitive to the distinction between end-user
and external expert inputs to the system design
• The greater the need for knowledge appropriation from the external experts
• The more the core team needs to focus on and invest in constructive debate
and comprehensive analysis.
Limitations
• Data collection is a cross-sectional design→ further studies would be
strengthened by objective data
• This study focuses on the quality aspects of system design
• Our sample restricts replacement systems as operational LIS

58. Conclusion
06
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59. Conclusion
The primary
question V
We develop
and test a model
Make a good decision in
a turbulent environment
“if information elaboration processes
with extended knowledge sources
improve the design of LIS
replacements” is shown on be true
• Constructive debate,
comprehensiveness, and
solution integration
• Expanding the core team’s
knowledge
Comprehensiveness +
Constructive debate –
Integrated solution
not impacted
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60. Thank You

61. Jacob Chia-An Tsai, James J. Jiang, Gary Klein, Shin-Yuan Hung,
Legacy information system replacement: Pursuing quality design of operational
information systems,
Information & Management,
Volume 59, Issue 2, 2022, 103592, ISSN 0378-7206,
https://doi.org/10.1016/j.im.2022.103592.
(https://www.sciencedirect.com/science/article/pii/S0378720622000040)
PPT template- Technology Consulting from https://slidesgo.com/theme/technology-
consulting
P1 Legacy system pic download from https://en.wikipedia.org/wiki/Legacy_system
P18 Microsoft Stock images (royalty-free images)
Resources

62. ● 何謂自變數、應變數、干擾變數、中介變數、控制變數
https://aitmr1234567890.medium.com/%E4%BD%95%E8%AC%82%E8%87%AA%E8%
AE%8A%E6%95%B8-%E6%87%89%E8%AE%8A%E6%95%B8-
%E5%B9%B2%E6%93%BE%E8%AE%8A%E6%95%B8-
%E4%B8%AD%E4%BB%8B%E8%AE%8A%E6%95%B8-
%E6%8E%A7%E5%88%B6%E8%AE%8A%E6%95%B8-1cd7aa3218f7
● 评估区分效度的三大方法 https://zhuanlan.zhihu.com/p/72966699
● 什么是社会期望偏差 https://www.iiiff.com/article/339392
● SEM Amos 範例12-3：多重中介效果檢定(Bootstrap法)
https://www.youtube.com/watch?v=xYl0u5byz9k
Extended learning