Accounting for sustainable
societies
Topics
- Accounting theory & philosophy of science
Lecture 1
- Formulating research questions & hypothesis (propositions)
Lecture 2
- Methodical challenges (quantitative & qualitative)
Lecture 3&4
- Earnings smoothing
Lecture 4
- Tax, tax planning & reporting.
Lecture 5-7
- Sustainability reporting & CSR
Lecture 8
- Materiality Lecture 10
Inhoudsopgave
Lecture 1- Introduction...................................................................................2
Lecture 2 – Formulating a research question and transitioning to hypotheses (or
propositions)................................................................................................. 3
Lecture 3 – Methodological and theoretical challenges: qualitative research.....7
Lecture 4 – Methodological and theoretical challenges: quantitative research. 13
Lecture 5 – Societal challenges in Business Economics I.................................16
Lecture 6 & 7 – Societal challenges in Business Economics II & III...................23
Lecture 8 – Voluntary and mandatory sustainability reporting........................29
Lecture 9 – Can accounting save the world?...................................................34
Lecture 10 – The concept of (single vs. double) materiality in non-financial
reporting..................................................................................................... 37
,Lecture 1- Introduction
Theory: a formal set of ideas that is intended to explain why something
happens or exists.
Hypothesis: an idea or explanation of something that is based on a few
known facts but has not yet been proven to be true or correct.
Proposition: like a hypothesis but the link cannot be verified by
experiment.
Theorem: a rule, especially in mathematics, that can be proven to be
true.
Law: a generalised, especially in natural sciences, in the form of a
mathematical statement.
There are four basic levels of research:
- Description: collection and reporting data (observations) and basic
statistics
- Classification: grouping (or clustering) of data based on similarities
or differences
- Explanation: makes sense of the data by attempting to explain
relationships (or casualty); generally concerned with the “Why?”.
- Prediction: provide models that allow testable predictions for
(future) events.
There are two further distinctions within types of research:
- Deductive reasoning (theory observation) vs. Inductive
reasoning (observation theory).
1. Deductive reasoning: idea observations conclusions
2. Inductive reasoning: observations analysis theory
- Confirmatory research vs. exploratory research
1. Confirmatory: test a priori hypothesis, normally based on existing
study, stringent research restrictions, seals with knowns and
unknowns
2. Exploratory: generates a posteriori hypothesis, discovers new
knowledge, less stringent research restrictions, deals with
unknowns.
,Lecture 2 – Formulating a research question
and transitioning to hypotheses (or
propositions)
The Kinny three paragraphs:
- What?
What is the problem?
What are you trying to find out?
- Why?
Why is it an important problem?
To Whom?
- How?
How will it be solved?
How will it be done?
Examples:
What: there are different ways for management to react to criticism on
social media. How do investors react to remaining silent, providing an
explanation, or redirecting attention?
Why: we already know much about traditional communication channels,
but communication to stakeholders increasingly takes place on social
media. Important to know for companies’ reputation how to react to
criticism.
How: Experiment in which participants receive scenario (manipulating the
variable) and answer questions about their perceptions of the firm and
their decisions.
What: research question. Research questions are clear, focused, and
concise. You should minimize room for misinterpretation (clear), be specific
enough to be covered on paper (focused and concise), and it is not about
personal opinions, and you know the possible answers (falsification is
important) (arguable).
Be aware of the following trade-off:
Link your research question to what others have done make your
research question offer something new.
Research questions are often (not always) motivated both form theory and
practice.
, Why: what could be some good
reasons to pursue a research
question? What could be a good
‘why’?
- Advancement of knowledge,
solving real-world problems,
personal and professional development, innovation and creativity,
and contribution to policy and decision making.
How: types of research. Gaining knowledge by means of direct and
indirect observation or experience.
- Empirical:
Archival (any structures or unstructured naturally occurring or
human-managed data not generated by researchers themselves),
field experiment, survey, controlled experiment, case study.
- Theoretical:
Conceptual, analytical modelling.
Collected variables vs. generated variables.
Collected: originating from naturally occurring or human-managed data.
Generated: data created by researchers.
Uncontrolled setting vs. controlled setting
Uncontrolled: setting has other potentially influential variables besides the
ones being studied.
Controlled: setting restricts itself to the study of the variables of interest
and not others.
The predictive validity framework (Libby et al. 2002)
Deepening the ‘what’ and ‘how’.
societies
Topics
- Accounting theory & philosophy of science
Lecture 1
- Formulating research questions & hypothesis (propositions)
Lecture 2
- Methodical challenges (quantitative & qualitative)
Lecture 3&4
- Earnings smoothing
Lecture 4
- Tax, tax planning & reporting.
Lecture 5-7
- Sustainability reporting & CSR
Lecture 8
- Materiality Lecture 10
Inhoudsopgave
Lecture 1- Introduction...................................................................................2
Lecture 2 – Formulating a research question and transitioning to hypotheses (or
propositions)................................................................................................. 3
Lecture 3 – Methodological and theoretical challenges: qualitative research.....7
Lecture 4 – Methodological and theoretical challenges: quantitative research. 13
Lecture 5 – Societal challenges in Business Economics I.................................16
Lecture 6 & 7 – Societal challenges in Business Economics II & III...................23
Lecture 8 – Voluntary and mandatory sustainability reporting........................29
Lecture 9 – Can accounting save the world?...................................................34
Lecture 10 – The concept of (single vs. double) materiality in non-financial
reporting..................................................................................................... 37
,Lecture 1- Introduction
Theory: a formal set of ideas that is intended to explain why something
happens or exists.
Hypothesis: an idea or explanation of something that is based on a few
known facts but has not yet been proven to be true or correct.
Proposition: like a hypothesis but the link cannot be verified by
experiment.
Theorem: a rule, especially in mathematics, that can be proven to be
true.
Law: a generalised, especially in natural sciences, in the form of a
mathematical statement.
There are four basic levels of research:
- Description: collection and reporting data (observations) and basic
statistics
- Classification: grouping (or clustering) of data based on similarities
or differences
- Explanation: makes sense of the data by attempting to explain
relationships (or casualty); generally concerned with the “Why?”.
- Prediction: provide models that allow testable predictions for
(future) events.
There are two further distinctions within types of research:
- Deductive reasoning (theory observation) vs. Inductive
reasoning (observation theory).
1. Deductive reasoning: idea observations conclusions
2. Inductive reasoning: observations analysis theory
- Confirmatory research vs. exploratory research
1. Confirmatory: test a priori hypothesis, normally based on existing
study, stringent research restrictions, seals with knowns and
unknowns
2. Exploratory: generates a posteriori hypothesis, discovers new
knowledge, less stringent research restrictions, deals with
unknowns.
,Lecture 2 – Formulating a research question
and transitioning to hypotheses (or
propositions)
The Kinny three paragraphs:
- What?
What is the problem?
What are you trying to find out?
- Why?
Why is it an important problem?
To Whom?
- How?
How will it be solved?
How will it be done?
Examples:
What: there are different ways for management to react to criticism on
social media. How do investors react to remaining silent, providing an
explanation, or redirecting attention?
Why: we already know much about traditional communication channels,
but communication to stakeholders increasingly takes place on social
media. Important to know for companies’ reputation how to react to
criticism.
How: Experiment in which participants receive scenario (manipulating the
variable) and answer questions about their perceptions of the firm and
their decisions.
What: research question. Research questions are clear, focused, and
concise. You should minimize room for misinterpretation (clear), be specific
enough to be covered on paper (focused and concise), and it is not about
personal opinions, and you know the possible answers (falsification is
important) (arguable).
Be aware of the following trade-off:
Link your research question to what others have done make your
research question offer something new.
Research questions are often (not always) motivated both form theory and
practice.
, Why: what could be some good
reasons to pursue a research
question? What could be a good
‘why’?
- Advancement of knowledge,
solving real-world problems,
personal and professional development, innovation and creativity,
and contribution to policy and decision making.
How: types of research. Gaining knowledge by means of direct and
indirect observation or experience.
- Empirical:
Archival (any structures or unstructured naturally occurring or
human-managed data not generated by researchers themselves),
field experiment, survey, controlled experiment, case study.
- Theoretical:
Conceptual, analytical modelling.
Collected variables vs. generated variables.
Collected: originating from naturally occurring or human-managed data.
Generated: data created by researchers.
Uncontrolled setting vs. controlled setting
Uncontrolled: setting has other potentially influential variables besides the
ones being studied.
Controlled: setting restricts itself to the study of the variables of interest
and not others.
The predictive validity framework (Libby et al. 2002)
Deepening the ‘what’ and ‘how’.
