Shareholder ratification of the auditor and audit market competition

In my dissertation, I examine factors associated with firms’ submission of auditor selection for shareholder ratification and test if shareholder ratification of auditor selection is associated with the extent of price competition in the audit market (as measured by audit fees) and audit quality (as measured by clients’ earnings management). The dissertation is motivated from the recent recommendation of the U.S. Treasury’s Advisory Committee on Auditing Profession (ACAP) regarding the submission of auditor selection for shareholder ratification votes. The ACAP suggests that this practice may improve the competition in the audit market; yet, there is no empirical evidence supporting the ACAP’s recommendation. My dissertation attempts to fill the gap in the literature on an issue of current interest to the auditing profession. I find that firm size, CEO-Chair duality, insider ownership and institutional ownership are associated with the submission of auditor selection for shareholder ratification vote. However, I do not find an association between audit committee variables and the submission of auditor selection for shareholder ratification vote. The second essay investigates the association between auditor ratification and audit fees. Audit fees are higher in firms that submit auditor selection for shareholder ratification. The finding is not consistent with the increased price competition predicted by the ACAP. The third essay of my dissertation examine whether the submission of auditor selection for shareholder ratification is associated with earnings management. I find that firms that submit auditor selection for shareholder ratification are more likely to have lower level of earnings management. Overall, the results suggest that the same factors that are associated with higher quality monitoring also may be associated with the submission of auditor selection for shareholder ratification vote. The results call into question the one-size-fits-all approach recommended by the ACAP.

Shareholder Ratification of The Auditor and Audit Market Competition

In my dissertation, I examine factors associated with firms’ submission of auditor selection for shareholder ratification and test if shareholder ratification of auditor selection is associated with the extent of price competition in the audit market (as measured by audit fees) and audit quality (as measured by clients’ earnings management). The dissertation is motivated from the recent recommendation of the U.S. Treasury’s Advisory Committee on Auditing Profession (ACAP) regarding the submission of auditor selection for shareholder ratification votes. The ACAP suggests that this practice may improve the competition in the audit market; yet, there is no empirical evidence supporting the ACAP’s recommendation. My dissertation attempts to fill the gap in the literature on an issue of current interest to the auditing profession. I find that firm size, CEO-Chair duality, insider ownership and institutional ownership are associated with the submission of auditor selection for shareholder ratification vote. However, I do not find an association between audit committee variables and the submission of auditor selection for shareholder ratification vote. The second essay investigates the association between auditor ratification and audit fees. Audit fees are higher in firms that submit auditor selection for shareholder ratification. The finding is not consistent with the increased price competition predicted by the ACAP. The third essay of my dissertation examine whether the submission of auditor selection for shareholder ratification is associated with earnings management. I find that firms that submit auditor selection for shareholder ratification are more likely to have lower level of earnings management. Overall, the results suggest that the same factors that are associated with higher quality monitoring also may be associated with the submission of auditor selection for shareholder ratification vote. The results call into question the one-size-fits-all approach recommended by the ACAP.

Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.