TY - JOUR
T1 - Measuring annual report narratives disclosure
T2 - Empirical evidence from forward-looking information in the UK prior the financial crisis
AU - Abed, Suzan
AU - Al-Najjar, Basil
AU - Roberts, Clare
N1 - Funding information: The authors are grateful to the Applied Science Private University, Amman, Jordan, for the financial support granted to this research project (Gran No. DRGS-2015-2016-36).
PY - 2016/4/4
Y1 - 2016/4/4
N2 - Purpose – This paper aims to investigate empirically the common alternative methods of measuring annual report narratives. Five alternative methods are employed, a weighted and un-weighted disclosure index and three textual coding systems, measuring the amount of space devoted to relevant disclosures. Design/methodology/approach – The authors investigate the forward-looking voluntary disclosures of 30 UK non-financial companies. They employ descriptive analysis, correlation matrix, mean comparison t-test, rankings and multiple regression analysis of disclosure measures against determinants of corporate voluntary reporting. Findings – The results reveal that while the alternative methods of forward-looking voluntary disclosure are highly correlated, important significant differences do nevertheless emerge. In particular, it appears important to measure volume rather than simply the existence or non-existence of each type of disclosure. Overall, we detect that the optimal method is content analysis by text-unit rather than by sentence. Originality/value – This paper contributes to the extant literature in forward-looking disclosure by reporting important differences among alternative content analyses. However, the decision regarding whether this should be a computerised or a manual content analysis appears not to be driven by differences in the resulting measures. Rather, the choice is the outcome of a trade-off between the time involved in setting up coding rules for computerised analysis versus the time saved undertaking the analysis itself.
AB - Purpose – This paper aims to investigate empirically the common alternative methods of measuring annual report narratives. Five alternative methods are employed, a weighted and un-weighted disclosure index and three textual coding systems, measuring the amount of space devoted to relevant disclosures. Design/methodology/approach – The authors investigate the forward-looking voluntary disclosures of 30 UK non-financial companies. They employ descriptive analysis, correlation matrix, mean comparison t-test, rankings and multiple regression analysis of disclosure measures against determinants of corporate voluntary reporting. Findings – The results reveal that while the alternative methods of forward-looking voluntary disclosure are highly correlated, important significant differences do nevertheless emerge. In particular, it appears important to measure volume rather than simply the existence or non-existence of each type of disclosure. Overall, we detect that the optimal method is content analysis by text-unit rather than by sentence. Originality/value – This paper contributes to the extant literature in forward-looking disclosure by reporting important differences among alternative content analyses. However, the decision regarding whether this should be a computerised or a manual content analysis appears not to be driven by differences in the resulting measures. Rather, the choice is the outcome of a trade-off between the time involved in setting up coding rules for computerised analysis versus the time saved undertaking the analysis itself.
KW - Content analysis methods
KW - Forward-looking information
KW - Narrative disclosure
UR - http://www.scopus.com/inward/record.url?scp=84973647611&partnerID=8YFLogxK
U2 - 10.1108/MAJ-09-2014-1101
DO - 10.1108/MAJ-09-2014-1101
M3 - Article
AN - SCOPUS:84973647611
SN - 0268-6902
VL - 31
SP - 338
EP - 361
JO - Managerial Auditing Journal
JF - Managerial Auditing Journal
IS - 4-5
ER -