This factor has been tested on the Global Fortune 100
companies (G100) for the period of 2011–2015; representing
a sample of 500 reports while applying Quantitative
methodological techniques. Having an ordered, categorical
dependent variable of the research made the logistic
regression the best quantitative choice for the analysis process. Thus, an Ordinal, Logistic Regression Analysis is
chosen to statistically analyze the collected data, using SPSS
statistical software package. As a result of the empirical
findings, it is concluded that the Assurance of the Sustainability Report (ASR) can explain 15.2–16.6% of the variability occurring in the Quality of Sustainability Reporting
(QSR), which is a significant percentage. Of which, the
inferential results concluded that there is an Extremely Significant relationship between the Assurance of the Sustainability Report and the Quality of Sustainability Reporting.
This significant relationship is found to be a Positive relationship, in which the statistical results reach that as the
assurance of report increases by one unit, it is more likely to
be in a higher level of the quality of sustainability reporting
by 8.482456 units. Based on that, a conclusive decision is
taken regarding the research hypothesis that is the hypothesis
is Accepted stating that Assurance of the Sustainability
Report (ASR) has a significant impact on the Quality of the
Sustainability Reporting (QSR).
9 Research Limitations and Future Research
As it is the usual case in any research of social sciences,
some limitations have been evolved from the insights provided in this research. There are two main research limitations derived from the empirical results. The first limitation
to be highlighted is deducted from the value of Pseudo
R-Square of 15.2–16.6%. This means that the Assurance of
the Sustainability Report (ASR) can explain only from 15.2
to 16.6% of the change in the Quality of Sustainability
Reporting (QSR). Although this is considered as a significant percent; however there is still a more significant percent, which is 83.4 to 84.8%, of the variability/change in the
quality of sustainability reporting that needs to be scientifically explained. Based on that, it is recommended for future
research to fill in this gap through testing other factors that
are affecting around 80% of unexplained change in the
quality level of sustainability reporting. The second limitation in relation to one of the controlling variables is that of
the company size (measured by the Total Assets (TOA)).
Because of this, the empirical results show that it has a
negative significant relationship with the quality of sustainability reporting. Although it is not the main research independent variable, its result is contradicting with a
considerable literature arguing a positive relationship
between these variables. It is recommended for future
research to retest the relationship between those variables,
perhaps using different measurement technique that may
lead to different results.
Acknowledgements As this paper is extracted from my Ph.D. thesis, I
would like to express my sincere gratitude to my supervisors, Prof.
Kenneth D’Silva (LSBU) and Dr. Mohamed H. Rashwan (BUE). Prof.
Kenneth D’Silva, thank you for your continuous support, guidance and
valuable comments that greatly contributed in improving this manuscript, as well as, enriching my scientific knowledge. Dr. Mohamed H.
Rashwan, thank you for all the support that you have been providing
me since the early stage of my career, and without which I would not
have reached this point. I would like to thank you for being my great
career coach.
References
Adams, J., Khan, R., & White, D. (2007). Research methods for
graduate business and social science students. Response Books.
ISBN: 978-0-7619-3589-6 (PB).
Ahmed, M. D., & Sundaram, D. (2012). Sustainability modelling and
reporting: From roadmap to implementation. Decision Support
Systems, 611–624.
Ane, P. (2012). An assessment of the quality of environmental
information disclosure of corporation in China. Systems Engineering Procedia, 420–426.
Arens, A. A., Elder, R. J., Beasley, M. S., & Hogan, E. C. (2017).
Auditing and assurance services an integrated approach (sixteenth
(Edition ed.). Boston: Pearson Education.
Arnold, M. (2017). Fostering sustainability by linking co-creation and
relationship management concepts. Journal of Cleaner Production,
140, 179–188.
Baumgartner, R. J., & Rauter, R. (2017). Strategic perspectives of
corporate sustainability management to develop a sustainable
organization. Journal of Cleaner Production, 140, 81–92.
Bebbington, J. (2009). Measuring sustainable development performance: Possibilities and issues. Accounting Forum, 189–193.
Bebbington, J., Gonzalez, C. L., & Abadıa, J. M. (2008). Legitimating
reputation/the reputation of legitimacy theory. Accounting, Auditing
& Accountability Journal, 21(3), 371–374.
Brown, S., & Hillegeist, S. A. (2007). How disclosure quality affects
the level of information asymmetry. Review of Accounting Studies,
443–477.
Comyns, B., Figge, F., Hahn, T., & Barkemeyer. (2013). Sustainability
reporting: The role of “Search”, “Experience” and “Credence”
information. Accounting Forum, 13.
Daub, C.H. (2007). Asessing the quality of sustainability reporting: An
alternative methodological approach. Journal of Cleaner Production, 75–85.
de Villiers, C., & van Staden, C. (2006). Can less environmental
disclosure have a legitimising effect? Evidence from Africa.
Accounting, Organizations and Society, 31, 763–781.
Denham, B. E. (2017). Categorical statistics for communication
research (1st ed.). New Jersey: Wiley, Inc.
Dougherty, C. (2002). Introduction to econometrics (2nd ed.). Oxford:
Oxford University Press. ISBN: 0-19-877643-8.
Eugenio, T. P., Lourenco, I. C., & Morais, A. I. (2013). Sustainability
strategies of the company TimorL: Extending the applicability of
legitimacy theory. Management of Environmental Quality: An
International Journal, 24(5), 570–582.
198
N. A. El-Rahman
companies (G100) for the period of 2011–2015; representing
a sample of 500 reports while applying Quantitative
methodological techniques. Having an ordered, categorical
dependent variable of the research made the logistic
regression the best quantitative choice for the analysis process. Thus, an Ordinal, Logistic Regression Analysis is
chosen to statistically analyze the collected data, using SPSS
statistical software package. As a result of the empirical
findings, it is concluded that the Assurance of the Sustainability Report (ASR) can explain 15.2–16.6% of the variability occurring in the Quality of Sustainability Reporting
(QSR), which is a significant percentage. Of which, the
inferential results concluded that there is an Extremely Significant relationship between the Assurance of the Sustainability Report and the Quality of Sustainability Reporting.
This significant relationship is found to be a Positive relationship, in which the statistical results reach that as the
assurance of report increases by one unit, it is more likely to
be in a higher level of the quality of sustainability reporting
by 8.482456 units. Based on that, a conclusive decision is
taken regarding the research hypothesis that is the hypothesis
is Accepted stating that Assurance of the Sustainability
Report (ASR) has a significant impact on the Quality of the
Sustainability Reporting (QSR).
9 Research Limitations and Future Research
As it is the usual case in any research of social sciences,
some limitations have been evolved from the insights provided in this research. There are two main research limitations derived from the empirical results. The first limitation
to be highlighted is deducted from the value of Pseudo
R-Square of 15.2–16.6%. This means that the Assurance of
the Sustainability Report (ASR) can explain only from 15.2
to 16.6% of the change in the Quality of Sustainability
Reporting (QSR). Although this is considered as a significant percent; however there is still a more significant percent, which is 83.4 to 84.8%, of the variability/change in the
quality of sustainability reporting that needs to be scientifically explained. Based on that, it is recommended for future
research to fill in this gap through testing other factors that
are affecting around 80% of unexplained change in the
quality level of sustainability reporting. The second limitation in relation to one of the controlling variables is that of
the company size (measured by the Total Assets (TOA)).
Because of this, the empirical results show that it has a
negative significant relationship with the quality of sustainability reporting. Although it is not the main research independent variable, its result is contradicting with a
considerable literature arguing a positive relationship
between these variables. It is recommended for future
research to retest the relationship between those variables,
perhaps using different measurement technique that may
lead to different results.
Acknowledgements As this paper is extracted from my Ph.D. thesis, I
would like to express my sincere gratitude to my supervisors, Prof.
Kenneth D’Silva (LSBU) and Dr. Mohamed H. Rashwan (BUE). Prof.
Kenneth D’Silva, thank you for your continuous support, guidance and
valuable comments that greatly contributed in improving this manuscript, as well as, enriching my scientific knowledge. Dr. Mohamed H.
Rashwan, thank you for all the support that you have been providing
me since the early stage of my career, and without which I would not
have reached this point. I would like to thank you for being my great
career coach.
References
Adams, J., Khan, R., & White, D. (2007). Research methods for
graduate business and social science students. Response Books.
ISBN: 978-0-7619-3589-6 (PB).
Ahmed, M. D., & Sundaram, D. (2012). Sustainability modelling and
reporting: From roadmap to implementation. Decision Support
Systems, 611–624.
Ane, P. (2012). An assessment of the quality of environmental
information disclosure of corporation in China. Systems Engineering Procedia, 420–426.
Arens, A. A., Elder, R. J., Beasley, M. S., & Hogan, E. C. (2017).
Auditing and assurance services an integrated approach (sixteenth
(Edition ed.). Boston: Pearson Education.
Arnold, M. (2017). Fostering sustainability by linking co-creation and
relationship management concepts. Journal of Cleaner Production,
140, 179–188.
Baumgartner, R. J., & Rauter, R. (2017). Strategic perspectives of
corporate sustainability management to develop a sustainable
organization. Journal of Cleaner Production, 140, 81–92.
Bebbington, J. (2009). Measuring sustainable development performance: Possibilities and issues. Accounting Forum, 189–193.
Bebbington, J., Gonzalez, C. L., & Abadıa, J. M. (2008). Legitimating
reputation/the reputation of legitimacy theory. Accounting, Auditing
& Accountability Journal, 21(3), 371–374.
Brown, S., & Hillegeist, S. A. (2007). How disclosure quality affects
the level of information asymmetry. Review of Accounting Studies,
443–477.
Comyns, B., Figge, F., Hahn, T., & Barkemeyer. (2013). Sustainability
reporting: The role of “Search”, “Experience” and “Credence”
information. Accounting Forum, 13.
Daub, C.H. (2007). Asessing the quality of sustainability reporting: An
alternative methodological approach. Journal of Cleaner Production, 75–85.
de Villiers, C., & van Staden, C. (2006). Can less environmental
disclosure have a legitimising effect? Evidence from Africa.
Accounting, Organizations and Society, 31, 763–781.
Denham, B. E. (2017). Categorical statistics for communication
research (1st ed.). New Jersey: Wiley, Inc.
Dougherty, C. (2002). Introduction to econometrics (2nd ed.). Oxford:
Oxford University Press. ISBN: 0-19-877643-8.
Eugenio, T. P., Lourenco, I. C., & Morais, A. I. (2013). Sustainability
strategies of the company TimorL: Extending the applicability of
legitimacy theory. Management of Environmental Quality: An
International Journal, 24(5), 570–582.
198
N. A. El-Rahman