Corporate environmental social and governance (ESG) reporting is becoming subject to increased scrutiny by regulators, investors and public. This dissertation will contribute to several research streams in the extant literature. This dissertation is the first to show the impact of employee environmental values and attitudes on reporting and whistleblowing decisions, making contributions to accounting, management, whistleblowing and environmental psychology literatures. Next, it is among the first to examine the role of the identity of ESG assurance provider in ESG reporting context. Further, it is among the first to examine the impact of SEC assurance mandate and the value of assurance over ESG information, thus contributing to audit literature. Using experimental methodology, I examine how ESG report assurance, ESG report assurance provider, ESG issue type, and environmentalism as a personality factor influence employee decisions to accede to a supervisory request to misrepresent ESG information, to report management's actions to a corporate hotline, to post information about management wrongdoing on social media, to switch jobs, and to judge ESG misreporting actions as unethical. The results indicate that (1) employee personality factor environmentalism impacts their ESG reporting decisions; (2) pro-environmental employees are more likely to whistleblow when assurance is not mandated, and they judge management actions to be more unethical when assurance is required; (3) under pressure to misreport ESG information, employees are more likely to switch jobs and judge management actions significantly more unethical, when they are dealing with quantitative data (as opposed to qualitative data), and when ESG assurance is provided by a consultant (versus an auditor); (4) pro-environmental employees do not differentiate between the issues impacting financial statements or ESG report only, whereas, employees with low-level environmentalism judge management actions to be more unethical when facing ESG issue with immediate impact to financial statements as opposed to an issue impacting ESG report only; (5) older employees (over 35) with low-level environmentalism are more likely to post information on social media when dealing with an environmental issue as opposed to a social issue; and (6) majority of participants (57%) perceive ESG misreporting to be a widespread phenomenon.

<p>The Swedish Transport Administration has, and manages, a database containing information of the status of road condition on all paved and governmental operated Swedish roads. The purpose of the database is to support the Pavement Management System (PMS). The PMS is used to identify sections of roads where there is a need for treatment, how to allocate resources and to get a general picture of the state of the road network condition. All major treatments should be reported which has not always been done.</p><p>The road condition is measured using a number of indicators on e.g. the roads unevenness. Rut depth is an indicator of the roads transverse unevenness. When a treatment has been done the condition drastically changes, which is also reflected by these indicators.</p><p>The purpose of this master thesis is to; by using existing indicators make predictions to find points in time when a road has been treated.</p><p>We have created a SAS-program based on simple linear regression to analyze rut depth changes over time. The function of the program is to find levels changes in the rut depth trend. A drastic negative change means that a treatment has been made.</p><p>The proportion of roads with an alleged date for the latest treatment earlier than the programs latest detected date was 37 percent. It turned out that there are differences in the proportions of possible treatments found by the software and actually reported roads between different regions. The regions North and Central have the highest proportion of differences. There are also differences between the road groups with various amount of traffic. The differences between the regions do not depend entirely on the fact that the proportion of heavily trafficked roads is greater for some regions.</p>

The Swedish Transport Administration has, and manages, a database containing information of the status of road condition on all paved and governmental operated Swedish roads. The purpose of the database is to support the Pavement Management System (PMS). The PMS is used to identify sections of roads where there is a need for treatment, how to allocate resources and to get a general picture of the state of the road network condition. All major treatments should be reported which has not always been done. The road condition is measured using a number of indicators on e.g. the roads unevenness. Rut depth is an indicator of the roads transverse unevenness. When a treatment has been done the condition drastically changes, which is also reflected by these indicators. The purpose of this master thesis is to; by using existing indicators make predictions to find points in time when a road has been treated. We have created a SAS-program based on simple linear regression to analyze rut depth changes over time. The function of the program is to find levels changes in the rut depth trend. A drastic negative change means that a treatment has been made. The proportion of roads with an alleged date for the latest treatment earlier than the programs latest detected date was 37 percent. It turned out that there are differences in the proportions of possible treatments found by the software and actually reported roads between different regions. The regions North and Central have the highest proportion of differences. There are also differences between the road groups with various amount of traffic. The differences between the regions do not depend entirely on the fact that the proportion of heavily trafficked roads is greater for some regions.