Using CPA Firms and Understanding Their Functions

Keyword(s):  
2015 ◽  
Vol 229 (1) ◽  
pp. 253-264 ◽  
Author(s):  
Hsihui Chang ◽  
Hiu Lam Choy ◽  
Iny Hwang

2015 ◽  
Vol 03 (11) ◽  
pp. 128-133
Author(s):  
Jiexiao Shan
Keyword(s):  

2003 ◽  
Vol 17 (2) ◽  
pp. 87-110 ◽  
Author(s):  
Marilyn M. Greenstein ◽  
James E. Hunton

The primary purposes of this study are to identify and validate a list of necessary skills required to ensure good data privacy protection for organizations, recognize potential privacy service providers, compare the perceived skill levels of potential providers, and test the impact of an educational brochure developed by the AICPA designed to communicate how and why members of the accounting profession are qualified to conduct privacy engagements. A total of 82 corporate managers representing 27 companies participated in a randomized between-subjects experiment where they responded to skill-related items either before or after reading the privacy brochure. Factor analysis of 17 skill items revealed four factors: technical, legal, control/assurance, and strategic. The following potential service providers were identified: law firms, CPA firms (both Big 5 and non-Big 5), security consultants, and e-business consultants. Study findings suggest that all four of the skill constructs are necessary in providing good data privacy protection. Before reading the brochure, the highest construct index means (potential providers) were as follows: technical (e-business consultants), legal (law firms), control/assurance (CPA firms and security consultants), and strategic (security consultants). After reading the brochure, CPA firms moved significantly higher on technical, legal, and strategic skills; additionally, CPA firms were ranked among the highest service providers in all areas except legal skills, where law firms continued to predominate.


1986 ◽  
Vol 61 (6) ◽  
pp. 252-255 ◽  
Author(s):  
Gregory M. Thibadoux ◽  
Ira S. Greenberg

2001 ◽  
Vol 17 (4) ◽  
pp. 421-436 ◽  
Author(s):  
Philip H. Siegel ◽  
Alan Reinstein

2020 ◽  
Vol 0 (0) ◽  
pp. 1-34
Author(s):  
Kuang-Hua Hu ◽  
Fu-Hsiang Chen ◽  
Ming-Fu Hsu ◽  
Gwo-Hshiung Tzeng

In today’s big-data era, enterprises are able to generate complex and non-structured information that could cause considerable challenges for CPA firms in data analysis and to issue improper audited reports within the required period. Artificial intelligence (AI)-enabled auditing technology not only facilitates accurate and comprehensive auditing for CPA firms, but is also a major breakthrough in auditing’s new environment. Applications of an AI-enabled auditing technique in external auditing can add to auditing efficiency, increase financial reporting accountability, ensure audit quality, and assist decision-makers in making reliable decisions. Strategies related to the adoption of an AI-enabled auditing technique by CPA firms cover the classical multiple criteria decision-making (MCDM) task (i.e., several perspectives/criteria must be considered). To address this critical task, the present study proposes a fusion multiple rule-based decision making (MRDM) model that integrates rule-based technique (i.e., the fuzzy rough set theory (FRST) with ant colony optimization (ACO)) into MCDM techniques that can assist decision makers in selecting the best methods necessary to achieve the aspired goals of audit success. We also consider potential implications for articulating suitable strategies that can improve the adoption of AI-enabled auditing techniques and that target continuous improvement and sustainable development.


Author(s):  
Gary Kleinman ◽  
Philip Siegel ◽  
Claire Eckstein

The pace of organizational and environmental change seems to demand that such professional organizations as CPA firms become learning organizations in order to compete with other firms. The flattening or thinning out of traditional hierarchical structures within organizations argues that traditional mentoring and supervisory structures may be inadequate for fostering needed individual learning about (a) organizational goals and politics, and (b) personal learning about job context and skill development, thus the ability of individuals within CPA firms to master new skills may be impaired. One effect of the lack of such learning may be increased role stress, job burnout, loss of commitment to the organization, intention to leave, and diminished job satisfaction. Using a sample of 440 accounting professionals from major CPA firms in the southeastern, southwestern, and northeastern regions of the United States, this research studies the ability of peer developmental relationship functions foster the requisite personal and organizational learning, and also to directly and indirectly influence attitudinal outcomes. We further examine whether the impact of developmental peer relationships on attitudinal outcomes is mediated by personal and organizational learning.A hierarchical regression-based test was used to evaluate our hypotheses. The results partially supported our expectations that such peer developmental relationship functions were significantly related to attitudinal outcomes, to elements of organizational learning, and to the skill development aspect of personal learning. Elements of organizational socialization, personal learning, and team-source learning were significantly related to attitudinal outcomes as well.


Author(s):  
David P. Franz ◽  
Scott I. Jerris

<p class="MsoNormal" style="text-align: justify; margin: 0in 0in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">CPA firms are continuously being ranked and compared to each other. Most rankings are based on total revenue or total clients and convey a measure of prestige. But is ranking by total revenue the best way to compare firms, and benchmark and judge performance? Linking revenues to the resources used to generate them would give a more meaningful basis for evaluating firm performance regardless of size.</span></span></p>


2019 ◽  
Author(s):  
Yossef Tobol ◽  
Ronen Bar-El ◽  
Yuval Arbel ◽  
Ofer H. Azar
Keyword(s):  

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