Introduction to organisational research and case studies

ESRC Scottish Doctoral Training Centre
Information Science Pathway
Training day 25th June 2014

Introduction to organisational
research and case studies
Professor Hazel Hall
Institute for Informatics and Digital Innovation/School
of Computing

This session
 Theme is organisational research
 Context is Information Science
 Mix of lecture material and short exercises
 Session begins with consideration of the distinctiveness of
organisational research, then moves on to case studies
 But first…

Organisational research and case studies
at doctoral level within the Centre for
Social Informatics
Organisational
case study
Organisational
case study
Case study
Organisational
research
Organisational
research

Research cited in this session
Title Organisational
research
Business
research
Case study
as output
Setting
Intranet implementation in
a corporate environment
X X X Professional
services firm
Blogs in the classroom X X Edinburgh Napier
E-information roles X IM/KM
Outsourcing research &
information services
X Business
information
services
Research in Librarianship
Impact Evaluation Study
(RiLIES)
X Information
science research

Organisational research
 What makes organisational research
“different/distinctive”?
 Practical difficulties in accessing sites for data collection
 Information sharing practice of drug dealers
 Strategies for dealing with information security breaches in Company X
 Legal and ethical issues when setting up studies
 Power of the context in sites of data collection
 Real-life organisations staffed by humans whose behaviours are influenced by
range of factors – culture, politics, power struggles
 Intangibility of phenomena under investigation
 Knowledge, value, social capital, goodwill
 Expectation of the organisation to derive value from the study

Information Science and organisational
research
 Borrows from other disciplines
 because Information Science is concerned with range of
organisational perspectives
 technology, culture, functions…
 Requirement to read widely
 Sociology, anthropology, management science… even physics?
 Intranet implementation: Galison, P. (Ed), (1997). Image and logic: a material
culture of microphysics. Chicago: University of Chicago Press.
 As an applied science, organisational partners may expect
return on participation

Understanding of the term “case study”
 Case study is an approach to research
 Empirical enquiry that investigates a contemporary phenomenon
within a bounded, real-life context
 especially when boundaries between phenomenon and context are not clearly
evident
• Intranet implementation: “The reasons why they don’t use the intranet to
knowledge share [phenomenon] may be due to cultural issues [context]”
 uses multiple methods including, but not exclusively, qualitative techniques,
e.g. participant observation, interviews, document analysis
• Intranet implementation: interviews; document analysis
• RiLIES: interviews; citation “sketching”

Alternative understandings
 The case study is the output of research
 “Story/ies” of the case(s) investigated
 The knowledge trap: an intranet implementation in a corporate environment
(http://hazelhall.org/publications/phd-the-knowledge-trap-an-intranet-
implementation-in-a-corporate-environment/)
 Hall, H. & Davison, B. (2007). Social software as support in hybrid learning
environments: the value of the blog as a tool for reflective learning and peer
support. Library and Information Science Research, 29(2), 163-187. (DOI
10.1016/j.lisr.2007.04.007.)
 Enhancing the impact of LIS Research projects
 (Text book exercise)

Case study approach for real-life,
contemporary research
 Describe - explore – explain – illustrate – provide
examples
 Intranet implementation
 “Here’s a real information-intensive distributed organisation that hoped an
intranet would support knowledge sharing in the firm. I established that it did
not to the extent anticipated, and propose reasons why with illustrations and
examples.”
 Blogs in the classroom
 “We wondered if claims that blogs can encourage student reflection were
exaggerated. We tested this by analysing the content of recent student blog
postings in an educational setting, and demonstrated with examples that
reflection is often limited.”
 RiLIES
 “These five case studies of real LIS research projects show how a range of
factors can increase the impact of the research output on the practice of
librarians.”

Case study approach for investigating
“how” and “why” questions
 RiLIES
 How can LIS research projects be conceived, designed and
implemented to increases the chances that their findings will
influence the practice of librarians?
 Intranet implementation
 Why don’t staff in this corporate environment use the intranet for
knowledge sharing?

Case study approach for triangulation
 Collect data on specific cases to triangulate with other
data collected
 Case study (or studies) are just part of the project, e.g. RiLIES
 Practitioner poll
 Focus groups
 Validation survey
 and case studies

Single/multiple case studies as output
 A study can include single or multiple cases
 Intranet implementation: 1 (big) case study
 Blogs in the classroom: 1 case study
 RiLIES: 5 case studies
 In case of multiple case studies, each should stand on its
own

Rationale for single case study
 A critical case – likely to have strategic importance for the
general population
 Intranet implementation: focus on culture
 ‘If it is valid for this case, it is valid for all (or many) cases’.
 See http://heim.ifi.uio.no/~in166/h00/criticalcase.pdf
 An extreme or unique case
 RiLIES: 5 case studies chosen were amongst the most frequently
cited in the practitioner poll as having influenced practice
 A new/revelatory case
 Blogs in the classroom: no empirical studies conducted previously
(although plenty of claims made!)
 A prelude to further study, to test ideas
 For example, a pilot case

Case study research design process
 Five elements
1. Identify research questions to be explored
2. Determine propositions or hypotheses
 Bearing in mind that case studies themselves often generate hypotheses and
models to be tested in the future – by you, by other researchers
3. Select clear units of analysis
4. Analyse data in a logical fashion so that it can be tied back to
propositions
5. Interpret findings

Case study research design process
 Five elements: Intranet implementation
1. What is the role of an intranet in knowledge sharing?
2. External and internal organisational factors determine role
 This proposition was based on an analysis of sociotechnical literature that dated
back to the 1970s
3. Interviews and document analysis
4. Data analysed and reframed using actor-network theory (more on
this later…)
5. Findings interpreted to uncover underlying explanations of practice

Case study research and “rigour”
 Accusations of bias and lack of rigour in case study
research because data from which findings derive belong
to a specific context
 Poor reliability
 Can you be certain that you would report the same findings if you ran the same
study at another time or location?
• Intranet implementation: Perhaps not, but research protocol is such that
the process could be repeated in another large information-intensive
professional services firm (i.e. method is reliable)
 Doubtful validity
 How can this/these case(s) be generalisable to the wider context? To what
extent is your case study “representative” of the population as a whole?
• Intranet implementation: It can’t, but it does not seek to “generalise”
• RiLIES: Multiple case studies can address this to an extent

Other “weaknesses” of case study research
 Causal inferences cannot be made, and it’s not possible to
“test” in a “traditional” sense
 Chemistry would give you Na2O + 2HCl = H2O + 2NaCl
 In case studies only associations and correlations can be made
 Processes can be time-consuming and cumbersome
 Organising access, non-disclosure agreements
 Requirement to be on-site
 Willingness of “participants” to participate
 Labour in transcribing interviews…

 Events cannot be controlled
Intranet implementation: access agreed
first week of September 2001 for
interviews to start 1st October 2001…

Value of case studies
 In-depth studies
 “Power of good example” derives from “rich” data
 Intranet implementation
 Particularly useful for new areas of research, where
 there is little/no extant literature and previous empirical evidence
is lacking
 Blogging in the classroom
 Generate new hypotheses for future testing
 Blogging in the classroom
 Often inexpensive
 Depends on depth of study (and how you transcribe interviews)

Resources
 Research methods textbooks in business and
management are useful for organisational research in
general
 Most general research methods textbooks include
chapters on case study research
 Three particularly useful texts
 Eisenhardt, K. (1989). Building theories from case studies.
Academy of Management Review, 14, 532-550.
 Flyvbjerg, B. (2001). Making social science matter. Cambridge:
Cambridge University Press.
 Yin, R.K. (2013). Case study research (5th ed.). London: Sage.

Flyvbjerg, B. (2001). Making social science matter.
Cambridge: Cambridge University Press.

Yin, R.K. (2013). Case study research (5th ed.). London:
Sage.

Intranet implementation: Flyvbjerg (2001) helpful
to justify case study approach.

 What are the main “questions” you would need to ask?
 Which methods could you use to collect data?
 Who would you collect data from?
 How will you organise and analyse the data that you have
collected?
An investigation into the impact of UK
information science research
Exercise

Analysis of data for organisational
research
of Computing

In this section
 Data analysis as part of the research process
 Data, evidence and findings
 Role of coding data in data analysis
 Coding exercise

Data analysis as a process
 Design methods  gather evidence  present case
 Move from description of elements, e.g. object, people,
phenomena “observed” to explanation, i.e. analysis.
 Output is tied to purpose of the research and related
research questions, with scope for extension
 discover what the research is really about
 new research questions may emerge
 example: intranets and information sharing  power issues and
knowledge management

Refine & develop concepts – critical
treatment
Research Established “theory”
Intranet
implementation
Poor understanding of
knowledge sharing with
technologies
Blogs in the
classroom
Blogs promote
reflective learning
Contribution (Action)
Knowledge sharing
practice is local.
Efforts to
knowledge share is
influenced by
power bases
(Adopt communities
approach to KM in
case study
organisation)
Blogs do not
promote reflective
learning to the
extent reported
(Pay attention to
weekly blog hints to
engineer reflection)

Refine & develop concepts – critical
treatment
Research Established “theory”
Intranet
implementation
Poor understanding of
knowledge sharing with
technologies
Blogs in the
classroom
Blogs promote
reflective learning
Contribution (Action)
Knowledge sharing
practice is local.
Efforts to
knowledge share is
influenced by
power bases
(Adopt communities
approach to KM in
case study
organisation)
Blogs do not
promote reflective
learning to the
extent reported
(Pay attention to
weekly blog hints to
engineer reflection)
Data analysis
Data analysis

Belief in your research results
 Research findings are expected
 to be grounded in evidence
 not to be based on speculation, nor on weak inference
 Therefore decisions on data analysis are important
 Example from e-information roles study: apparently more
opportunity in the public and voluntary than the corporate sector.
However:
 less obligation in corporate sector to advertise posts
 public and voluntary sector organisations could be playing “catch up” with the
corporate sector
We could not be confident that this finding was grounded in evidence
because our data collection was not extensive enough

Inevitability of “too much” data
 Assume it’s murder
 safety net
 Not all data collected will be analysed - data collectively
“emphasised”
 to serve as evidence
 to build a case
 Tension
 present a set of understandable findings
 yet acknowledge the complexities of the social world under
investigation

Data, evidence and findings
 Data + interpretation = evidence
 Evidence = social product/artefact of work completed
 Evidence  findings
 Data cannot (normally) speak for itself, so
 data ≠ evidence
 evidence ≠ mere illustration
 evidence is built from multiple data sets
 research design should permit multiple collection of “same” data for
triangulation purposes
 obligation falls on the researcher to check alternative claims for the
evidence collected

Links between findings & research design
 Outcome of data analysis (findings) must be understood in
the context of the methods adopted
 Example from e-information roles study: globalisation the strongest
driver in the creation of new job roles in the corporate sector.
However:
 Research design determined sample selection focused on large, multinational
companies
So we were confident that the finding was grounded in evidence,
within the context of our sample
 Obligation to provide detailed and comprehensive account
of both findings and basis on which they were obtained

Data analysis: some examples
Research Format of data Coding & analysis
Intranet
implementation
Recorded interviews;
interview notes; archive
of company documents
Interviews transcribed; interview data
coded using Ethnograph; archive details
organised into historical sequence &
coded manually – “content analysis”
Blogs in the
classroom
Students’ blog entries;
survey
Content analysis of blog entries; survey
results not incorporated
e-information roles Focus group notes; job
adverts; job descriptions;
survey; telephone
interview notes
Combined mind-mapping of focus group
notes & job data; survey & telephone data
analysed using Excel
Outsourcing
research &
information services
Interview notes; provider
web sites
Interview data coded & analysed
manually – total of 11 data sets

Data analysis options
 Analysis using software
 Standard packages
 Word
 Excel
 Access
 Dedicated software
 SPSS - http://www.spss.com/
 Ethnograph - http://www.qualisresearch.com/
 Nvivo http://www.qsrinternational.com/products_nvivo.aspx
 Atlas.ti - http://www.atlasti.com/
 Manual analysis

Use of Excel to analyse survey &
interview data for the e-information
roles project
Relative ranking of the importance of employee
backgrounds: computing, business, librarianship
Column M records
comments

Date Data Source
8 November 2001
History – investment
Budget changes
Named meeting minutes
Use of Word to
analyse document
data for intranet
implementation
Source of information
Date of activity/development
Activity/development

H: Who controls 422
the Intranet content, is it 423
controlled by you in XX … rather than 424
from the centre, from the KM group …? 425
#-CONTROL $-RELS KMG
P: Well, in terms of what tools and what 427 -#-$
facilities are made available to us, 428 | |
that's obviously controlled by the 429 | |
central group. But in terms of the XX 430 |-$
content and the XX presence, that's 431 |
entirely controlled by me … simply 432 |
because it wouldn't be relevant to go 433 |
through a central group. 434 -#
H: Yeh, OK. You've told me about 436
#-INT BUY-IN
ownership. How … it sounds as if 437 -#
you've got really good buy-in from 438 |
your own set of people … 439 |
|
P: Absolutely. 441 -#
#-INT BUY-IN
H: What about the Intranet as a whole in 443 -#
the UK? What are your perceptions of 444 |
buy-in there? 445 |
|
$-KM SPONS
P: I think it varies. I mean, I'm very 447 -#-$
fortunate in that I report into the 448 |
KM partner, who's also one of the 449 |
senior partners … 450 -$
H: Which, who …? 452
Use of Ethnograph to analyse
interview data for intranet
implementation

“Translating” data for analysis - coding
 Coding
 records instances of occurrence
 organises data into categories
 comprises part of the analysis stage in qualitative research

Attention to coding in research design
 Design of research tool has determined predefined
codes
Indicate the best day of the week for team leader
meetings:
A. Monday
B. Tuesday
C. Wednesday
D. Thursday
E. Friday
F. Don’t know
G. No preference
H. Not applicable
Note also the importance of the last
three options: there is a difference
between not having a preference and not
knowing; if this forms part of a survey of
staff who have nothing to do with team
leader meetings, there needs to be an
option for their response. Attention to
coding at the design stage can help with
asking the “right” questions.

Coding down
 Data is coded according to predefined categories
 identified in range of work brought together in literature review
 identified in a single piece of work
 commonly deployed, e.g. age breakdowns used in national
statistics

Dimension Code Interpretation Evidence
Reflection C Content-free Comment makes no reference to points in the original entry.
U Non-reflective
(U=’unreflective’)
Comment makes reference to the original blog entry, the module content or the
general context in order to state an opinion, emotion or a point of fact or theory.
R Reflective Comment addresses points from the main blog entry and demonstrates a
consideration of the validity of the content, the process or the underlying premise.
Propositional stance A Agree Comment actively supports the point made in the original entry.
I Indifferent Comment neither supports nor challenges original entry.
D Disagree Comment takes up a contradictory position to the original entry.
Affective P Positive Comment is encouraging, approving, accepting, etc.
E Even Comment appears affectively neutral.
N Negative Comment is hostile, discouraging, dismissive, etc.
Scheme based on Kember, D., Jones, A., Loke, A., McKay, J., Sinclair, K., Tse, H., Webb, C., Wong, F., Wong, M. &
Yeung, E. (1999). Determining the level of reflective thinking from students’ written journals using a coding scheme
based on the work of Mezirow. International Journal of Lifelong Education, 18(1), 18–30.
Example coding down: blog posting data
coding scheme

Coding up
Data is coded according to categories suggested by the data
 Revise codes as new insight is developed through the process of coding - further
discovery of what the research is really about
 Example from intranet implementation project: seven broad categories related the
intranet under investigation
 Content
 Functionality
 History
 KWorld
 Policy
 Staffing
 Uptake

Some data in this spreadsheet fits
with predefined codes, i.e. in
columns D-L. However comments
need to be coded up.
Relative ranking of the importance of employee
backgrounds: computing, business, librarianship
Column M records
comments

H: Who controls 422
the Intranet content, is it 423
controlled by you in XX … rather than 424
from the centre, from the KM group …? 425
#-CONTROL $-RELS KMG
P: Well, in terms of what tools and what 427 -#-$
facilities are made available to us, 428 | |
that's obviously controlled by the 429 | |
central group. But in terms of the XX 430 |-$
content and the XX presence, that's 431 |
entirely controlled by me … simply 432 |
because it wouldn't be relevant to go 433 |
through a central group. 434 -#
H: Yeh, OK. You've told me about 436
#-INT BUY-IN
ownership. How … it sounds as if 437 -#
you've got really good buy-in from 438 |
your own set of people … 439 |
|
P: Absolutely. 441 -#
#-INT BUY-IN
H: What about the Intranet as a whole in 443 -#
the UK? What are your perceptions of 444 |
buy-in there? 445 |
|
$-KM SPONS
P: I think it varies. I mean, I'm very 447 -#-$
fortunate in that I report into the 448 |
KM partner, who's also one of the 449 |
senior partners … 450 -$
H: Which, who …? 452
Value of software packages for
coding and generating reports for
analysis
Speaker
Code
Line numbers
Data coded

Advice pointers
 Be disciplined and systematic when analysing data
 especially important to keep records of what you do if you dip in
and out of your research work
 Be prepared to account for what you have done in the
report of your work
 another reason to keep good records
 When designing data collection tools, look forward to data
analysis
 good decisions at this stage may save a lot of work at data
analysis stage – as will be demonstrated in the class exercise!

The class exercise
is based on the
responses to
questions 3.1, 3.2
and 3.3 in the e-
information roles
survey

Ability to align work activities to
business strategy
Ability to connect with
developments
Ability to cope with change
Ability to see the big picture
Ability to translate the needs of
the business at all levels
Abstracting
Adaptability
Analytic mind
Business acumen
Business awareness
Business development
Business focus
Cataloguing
Change management
Classification
Collaboration – non-technical
Collaboration – technical
Commercial awareness
Communication
Computer literacy
Confidence
Contract/supplier management
Creativity
Diplomacy
E-learning facilitation
Empathy
Engaging audiences
Enterprise content management
Enthusiasm
Evaluation of information sources
Facilitation
Flexibility
Grammar
Imagination
Indexing
Influencing
Information analysis
Information delivery
Information governance
Information literacy
Information retrieval
Innovation
Integrity
Intellectual property knowledge
Intelligence
Interviewing
IT savvy
Knowledge harvesting
Knowledge of e-information
arena, new technologies
Knowledge of government policy
Knowledge of information
sources
Knowledge of law
Knowledge of public sector
vocabulary
Languages
Leadership
Literacy
Management
Management of individuals
Management of teams
Marketing
Multi-tasking
Negotiation
Networking
Numeracy
Organisation
Outgoing personality
Political awareness
Presentation skills
Prince 2
Problem solving
Professionalism
Project management
Records management
Relationship building
Relationship management
Repackaging information
Research
Self-management
Small business knowledge
Social computing
Spelling
Stakeholder management
Strategic thinking
Synthesising information
Taxonomy development
Technical ability
Time management
Training
Understanding of
technical tools
Validation of information
sources
Web authoring
Web development
Web usability testing
Working under pressure
Writing
How would you
group these
responses for
coding?

Analytical tools and frameworks for
organisational analysis
of Computing

In this section
 Focus on tools and techniques for organisational and case
study analyses through a consideration of:
 Purpose and output of frameworks
 Actor-network theory as a framework – with example of its
application in the research into the intranet implementation
 NB there is a wide range of tools and techniques for research in
general. Some (or elements of some) are more applicable to
organisational and case study research than others. Actor-network
theory is just one example for illustration purposes here.

Purpose of frameworks
 Frameworks
 help make sense of data collected, and thus of phenomena (e.g.
organisational dynamics) observed
 act as a tool for diagnosis
 and thus aid the processes of:
 acquiring knowledge
 reflection
 action for change (if appropriate, for example in an action research setting)

Output of frameworks
 Frameworks provide you with a means of formatting your
findings
 e.g. as a graphical representation of the organisation under
investigation
 In using a framework you are encouraged to
 (re)organise your data
 understand what it is that your data represent
 present your findings in a format that is understandable to others –
the representation can be used as a short-cut to shared
understanding

Actor-network theory as a framework -
example
 Background
 Optimism associated with the development of systems to promote
knowledge sharing is misguided.
 Examples in the literature go back to 1980s.
 “Culture” often takes the blame.
 Case study organisation wanted explanations as to why the efforts
of its knowledge management staff to promote information
systems for knowledge sharing were sub-optimal.

Actor-network theory as a tool of analysis
 History
 Developed in 1980s
 Michel Callon and Bruno Latour
 Key concepts
 Non-humans, as well as humans, are actors
 Relationships between actors shift as they compete for
organisational resources, from tangible, e.g. office space, to
intangible, e.g. corporate attention
 Actor-networks grow through successful “translation”
 Actor-networks diminish/disintegrate when ties in the network
loosen

Relevance of actor-network theory to this
case
 The organisation was understood as a mesh of competing
actor-networks.
 The success/failure of corporate initiatives was suspected
to be related to the degree to which particular groups
enhanced or diminished their organisational power-base.
 Service delivery could be examined with reference to
historical and social context of the organisation.
 The approach provided opportunities to reflect, learn, act.

Actors in the organisation
External consultants
Senior staff with KM
responsibilities (not KM
specialists)
Knowledge
sharing as a
concept
Intranet
Repositories
Shared
collaboration
space
Mission
statements
Specialist KM staff
members in
centralised unit
Specialist KM staff
members in business
units
Senior sponsors of
KM (not KM
specialists)
External
systems
vendors
Intranet
usage
statistics
“Ordinary” staff
(not KM
specialists)
KM strategy
KM as a
concept

Analysis phase 1
Mission
statements
KM as a
concept
Senior sponsor of
KM (not a KM
specialist)
Intranet
Specialist IT/KM staff
member in
centralised unit
Senior specialist
IM/KM staff member
in centralised unit

Analysis phase 2
Mission
statements
KM as a
concept
Senior sponsor of KM (not
a KM specialist)
Intranet
Specialist IT/KM staff
member in centralised unit
Senior specialist
IM/KM staff member
in centralised unit
Senior specialist
IM/KM staff member
in centralised unit
Specialist IM/KM
staff members in
centralised unit
Some specialist
IM/KM staff members
in business units
“Ordinary” staff (not
KM specialists)

Analysis phase 3
Mission
statements
KM as a
concept
Senior sponsor of KM (not
a KM specialist)
Intranet
Senior specialist
IM/KM staff member
in centralised unit
Senior specialist
IM/KM staff member
in centralised unit
Specialist IM/KM
staff members in
centralised unit
Specialist IM/KM staff
members in business
units
“Ordinary” staff (not
KM specialists)

Some findings
 Central position of intranet, and its proximity to KM as a
concept, account for confusion over what KM represented
in the organisation.
 Distance between policy documentation and “ordinary”
staff explained lack of engagement with KM, and what it
implied in terms of behaviours.
 Ties between KM staff in business units and “ordinary”
staff strengthened over time at the expense of their
relationship with the central KM team and the main tool of
the KM implementation. As a result their commitment to
KM weakened, as did that of their “ordinary” colleagues.

Introduction to organisational research and case studies

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