acct 660

profileAskabul
isys-51265.pdf

See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/281326114

Accounting Information Systems and Ethics Research: Review, Synthesis, and

the Future

Article  in  Journal of Information Systems · August 2015

DOI: 10.2308/isys-51265

CITATIONS

12 READS

2,067

4 authors, including:

Some of the authors of this publication are also working on these related projects:

Whistleblowing on Occupational Fraud: A review of the literature (2000-2015) View project

Accounting Information Systems and Ethics Research: Review, Synthesis, and the Future View project

Nicholas Hunt

University of Nevada, Reno

7 PUBLICATIONS   30 CITATIONS   

SEE PROFILE

Marc Neri

Texas Christian University

3 PUBLICATIONS   14 CITATIONS   

SEE PROFILE

Eileen Z. Taylor

North Carolina State University

40 PUBLICATIONS   569 CITATIONS   

SEE PROFILE

All content following this page was uploaded by Eileen Z. Taylor on 06 August 2019.

The user has requested enhancement of the downloaded file.

Online Early — Preprint of Accepted Manuscript This is a PDF file of a manuscript that has been accepted for publication in an American Accounting Association journal. It is the final version that was uploaded and approved by the author(s). While the paper has been through the usual rigorous peer review process for AAA journals, it has not been copyedited, nor have the graphics and tables been modified for final publication. Also note that the paper may refer to online Appendices and/or Supplements that are not yet available. The manuscript will undergo copyediting, typesetting and review of page proofs before it is published in its final form, therefore the published version will look different from this version and may also have some differences in content.

We have posted this preliminary version of the manuscript as a service to our members and subscribers in the interest of making the information available for distribution and citation as quickly as possible following acceptance.

The DOI for this manuscript and the correct format for citing the paper are given at the top of the online (html) abstract.

Once the final published version of this paper is posted online, it will replace this preliminary version at the specified DOI.

The Accounting Review • Issues in Accounting Education • Accounting Horizons Accounting and the Public Interest • Auditing: A Journal of Practice & Theory

Behavioral Research in Accounting • Current Issues in Auditing Journal of Emerging Technologies in Accounting • Journal of Information Systems

Journal of International Accounting Research Journal of Management Accounting Research • The ATA Journal of Legal Tax Research

The Journal of the American Taxation Association

preprint

accepted manuscript

Accounting Information Systems and Ethics Research: Review, Synthesis, and the Future

Binod Guragai Nicholas Hunt Marc P. Neri

University of North Texas

and

Eileen Z. Taylor * North Carolina State University

[email protected]

*Corresponding author

We thank Roger Debreceny, Mary Curtis, anonymous reviewers, and participants at the 2015 Mid-year meeting of the Accounting Information Systems Section of the AAA for their helpful suggestions and comments.

preprint

accepted manuscript

Accounting Information Systems and Ethics Research: Review, Synthesis, and the Future Abstract: The rapid evolution of technology and the increasingly integrated nature of Accounting information systems (AIS) in business provide opportunities for those who interact with these systems to act unethically. Accountants, as the managers of accounting information systems and gatekeepers of assets, records, and reporting, have a responsibility to understand and address ethical dilemmas related to these responsibilities in their organizations. A summary of AIS and ethics research calls attention to gaps in the literature and provides directions for future research. The ETHOs framework, which categorizes factors as environmental, technological, human, and organizational, provides a model for researchers to examine ethical issues related to the AIS functions of recordkeeping, reporting, and control. Keywords: Accounting information systems; ethics; data management; judgment and decision- making; outsourcing; privacy; security; information technology.

preprint

accepted manuscript

Accounting Information Systems and Ethics Research: Review, Synthesis, and the Future

I. INTRODUCTION

This paper examines the intersection of accounting information systems (AIS) and ethics

by reviewing existing literature, proposing a research framework, and suggesting future research

ideas. AIS, a critical component of business operations, comprise many interrelated elements

(i.e. people, procedures, data, software, hardware, and controls) that identify, collect, store,

manage, and communicate accounting data. These recordkeeping functions enable organizations

to report data and information to internal and external parties, and to control activities (e.g.,

safeguard assets, limit individuals’ actions). The foundation of ethics is the understanding of how

our behavior affects the well-being of others (Paul and Elder 2013). Because people are key

elements in AIS, and because managers, regulators, investors, and others use information from

AIS to make decisions that affect others (e.g. contracting, hiring, investing, purchasing, and

selling), virtually every aspect of AIS has ethical implications.

Although many think of AIS primarily as automated, whenever people interact with a

system, from development through use, unethical decisions and behavior are a risk. There are

several links between AIS and unethical behavior. First, accountants may use systems to engage

in (i.e., commit, convert, and conceal) occupational fraud.1 Second, accountants may use systems

to violate individuals’ privacy by collecting, storing, selling, and using this data for

unauthorized, self-serving, or unethical purposes. Third, technology-based systems may enable

individuals to engage in unethical practices over others, such as unauthorized monitoring. Last,

systems themselves, even the mere existence of a system (Hannan, Rankin, and Towry 2006),

1 According to the Association of Certified Fraud Examiners (ACFE), occupational fraud includes asset misappropriation (e.g., fraudulent billing, payroll fraud, and expense reimbursement fraud), corruption, and fraudulent financial reporting (i.e., intentional manipulation of reported information, either its content or its form, or both).

preprint

accepted manuscript

2

can lead to deskilling or may bias an accountant’s moral judgment, by either clouding their

awareness of wrongdoing or altering their evaluation of what is right or wrong. Systems,

especially computer-based systems, may precipitate unethical outcomes by allowing individuals

to distance themselves from their actions, obfuscating ethical aspects and enabling unjust

rationalizations for unethical actions. The more technology evolves, the farther the actor is

removed “from the consequences of organizationally sanctioned” actions (Dillard 2003, 13),

reducing personal responsibility and enabling neutralizations. In other words, systems legitimize

individual wrongdoing by allowing people to focus on their duties within the system, without

consideration of the moral impact of their actions (Adams and Balfour, 1998). A striking

example of this occurred when a German subsidiary of IBM helped Hitler’s Third Reich carry

out the Holocaust by providing technology that allowed the Germans to catalog Jewish and other

citizens through people counting and registration technologies (Black and Wallace 2001, Dillard

2003). By treating people as inventory, the Third Reich dehumanized them, allowing Nazis to

distance themselves from their actions of mass extermination.

More recently, individuals acting for themselves and individuals acting as organizational

agents have used AIS to violate individual privacy, misappropriate business assets, and falsify

accounting data to meet organizational goals and market expectations. In the late 1990’s and

early 2000s, executives at WorldCom pressured accounting staff to use their AIS to perpetrate

financial statement fraud, misclassifying expenses as assets, and hiding hundreds of entries from

the internal and external auditors (Cooper 2009). Satyam Computer Services used its AIS to

create ghost employees and falsify sales orders, in order to conceal massive accounting fraud

perpetrated by its executives (Rai 2014). Last, United States (US) government employees (i.e.,

Veteran’s Administration managers) entered false data within their systems, altering waiting

preprint

accepted manuscript

3

times for military veterans’ healthcare appointments to portray more favorable statistics and earn

performance-based bonuses (Bronstein, Griffin, and Black 2014). These examples demonstrate

the harm enabled by modern AIS.

The link between AIS and ethics, in which AIS enable individuals to act unethically, is

heightened by two aspects. They are the increasingly integrated role of AIS in organizations, and

society’s expectations that professional accountants will act in the public interest (Copeland

2005). AIS have grown from simple bookkeeping tools to integrated enterprise resource

planning (ERP) systems. The focus of AIS has gone from making existing processes more

efficient, to designing systems to take strategic advantage of IS/IT capabilities, to addressing

risks associated with managing, retaining, and securing the data that organizations collect and

report (Brancheau and Wetherbe 1987; Brancheau, Janz, and Wetherbe 1996; Beard and Wen

2007; AICPA 2013b). While earlier systems were relatively limited recorders and reporters of

data, due to rapid technological advances, AIS are now powerful systems that integrate myriad

functions within a business (e.g., accounting, human resources, production, and supply chain).

Early ERP systems focused on resource optimization and transaction processing. ERP II expands

these functions to leverage information from business-to-business (B2B) and business-to-

consumer (B2C) electronic commerce (Bond, Genovese, Miklovic, Wood, Zrimsek, and Rayner

2000).2 Because ERP II systems increase the touchpoints where individuals interact with them,

they enable new opportunities for individuals who design, implement, and interact with them to

intentionally and to unintentionally cause harm. In short, the integration and reach of modern

AIS enable unethical behavior.

2 All major ERP vendors (e.g. SAP, Oracle, PeopleSoft) have adopted the concept of ERP II to help customers meet today’s business challenges (Mølller 2006).

preprint

accepted manuscript

4

Understanding the link between AIS and ethics is particularly important for accountants,

as they have a role as protectors of the public interest. Accountants of all types have a long

history of being the designated record-keepers and asset guardians for businesses and

governments alike (Soll 2014). Per the Institute of Internal Auditors Code of Ethics (IIA),

internal auditors have an obligation to maintain integrity, abide by the laws, act in an ethical

manner, and exercise objectivity in reporting. External auditors abide by a Code of Professional

Conduct that places the public interest at the forefront (AICPA 2013a). Audit committees, which

typically comprise accountants, are responsible for enterprise risk management, for reporting to

external parties, for the control environment and control activities, as well as for monitoring

activities (COSO 2013). Further, audit committees now, more than ever, are overseeing controls

related to compliance and operational matters (Deloitte 2014) as well as matters of risk oversight

(Rapoport and Lublin 2015). The designated role of accountants as controllers necessitates our

involvement, as AIS researchers and professionals, in understanding and addressing these issues.

After a brief history punctuated by rapid change, AIS are at an unavoidable crossroads

with ethics. Given AIS’s ubiquity and power, and accountants’ roles as recordkeepers, reporters,

and asset protectors, academics, as creators of knowledge and investigators of social phenomena

in the accounting and information systems’ space, have an obligation to examine and work to

understand these issues. Further, using technology to perform tasks has been found to influence

peoples’ ethical decisions in both positive and negative ways (Hunt and Iyer 2015). We cannot

afford to ignore their potential for harm, both intentional and unintentional. This paper aids in

our understanding of the implications of AIS on ethical issues by cataloging the existing research

on AIS and ethics, identifying gaps in the literature, creating a framework for the study of AIS

preprint

accepted manuscript

5

and ethics based on a four-factor categorization, and posing relevant questions for future

research.

II. DEFINING THE BOUNDARIES OF THE PAPER

Ethics

Ethics encompass an individual’s values, integrity, and courage. Values guide a person’s

moral decisions, integrity is the consistency with which they apply their values (i.e., relative to

time, place), and courage is the ability to convert values to actions, notably in the presence of

threats, both physical and intellectual (Gentile 2012, Kidder 2005). We define ethics using a

universal approach. Unethical actions are those judgments and behaviors enacted by humans

(individuals or groups) that “...inherently deny another person or creature some inalienable

right.” (Paul and Elder 2013, 14). Human rights include life, freedom, and security (among

others), to all, without distinction of any kinds (e.g., race, color, sex, religion, status, etc.)

(United Nations 1948).

The purpose of ethics, and of making ethical decisions, is to help, rather than harm

others, making it a social construct (Paul and Elder 2013). As part of their express duties toward

citizens, governments typical regulate acts that are unethical in and of themselves (such as

murder, fraud, and intimidation). However, social norms, which may vary between communities,

also play a part in communicating ethical standards. For example, professional accounting

societies and regulatory bodies enact differing codes of conduct governing the duties of a

professional, such as the duty of accountants to serve the public interest, and the general

expectation (in the US) of accountants to maintain client confidentiality (AICPA 2014). More

recently, governments have been called to respond to technological developments that enable

companies to infringe on the rights of private citizens. For example, the Court of Justice of the

preprint

accepted manuscript

6

European Union upheld the complaint of a Spanish citizen’s objection to Google including

sensitive information about this person in its search results. The court affirmed European Union

citizens’ “right to be forgotten” (i.e. the ability to remove their digital footprint from the Internet)

over the objections of Internet companies’ worries of extra costs (Chee 2014).

This paper broadens the concept of ethics in two ways. First, it considers not only

individual decisions and actions, but also includes organizational decisions and actions because

AIS’ development, implementation, and use are often the result of a group effort, and are

dependent on the institution’s existing structure. Thus, individuals at times act unethically for

their own direct personal benefit; at other times, they act on behalf of their organizations, or as

part of a group, indirectly for their own personal benefit (Cohen, Manzon, and Zamora 2015).

Second, it categorizes violations of generally accepted social norms as unethical, recognizing

that professional standards may go beyond basic human rights, but are legitimately valid

considerations within the profession. For example, there is an expectation that a professional

accountant has a higher standard to protect the public interest than does any individual citizen.

Accounting Information Systems

We organize the paper using Romney and Steinbart’s (2015) textbook definition:

accounting information systems (AIS) are systems that identify, collect, store, manage, and

communicate accounting data and information for the purposes of reporting and control.

Recordkeeping encompasses the first four activities, while reporting is the communication of

data and information to internal and external stakeholders. These reports, generated by AIS,

include financial information (e.g., balance sheet and income statement, C-suite compensation,

and cost per unit) and non-financial information (e.g., number of employees, patents awarded,

hours worked). Organizations also use AIS and the processes embedded within them to control

preprint

accepted manuscript

7

both people and assets. Accounting, through its recording function, enables management to

identify and hold individuals accountable for their actions. AIS also enable and limit who can

engage in certain transactions (e.g., access controls to physical assets and to electronic data and

approvals). These controls allow organizations to safeguard assets, produce valid information,

and carry out activities efficiently and effectively.

Factor Categories: ETHOs

We classified the existing AIS-Ethics research using a framework, (see Figure 1) that

includes four types of factors: environmental, technological, human, and organizational

(ETHOs).3 Environmental factors include standards, rules, expectations and norms imposed by

governments, professional organizations, industry groups, self-regulatory bodies, and

communities. For example, regulatory factors refer to governments enacting laws influencing the

design, use, and governance of AIS, overseeing the implementation of these laws, enforcing

these laws, and educating the public about these laws (Boritz and No 2011). Technological

factors refer to AIS inputs, systems and tool design, and outputs (Neely and Cook 2011). These

include hardware, software, and communication tools and their features and capabilities. Human

factors include people’s attitudes, perceptions, culture, group membership, and other individual

characteristics that influence their behavior (Pavlou 2011). Human factors are influential in

ethical decisions regarding privacy, equity, personal responsibility, and identity issues

encountered when interacting with AIS (e.g. Clarke 1999, Glass and Wood 1996, Harrington

1996, Sipior, Ward, and Rongione 2004). Last, organizational factors “include organizational

strategy, structure, and the internal and external business environment,” as well as how

organizations interact with their environment (Mauldin and Ruchala 1999, 324). They also

3 We develop and use the acronym ETHOs (environmental, technological, human, and organizational) throughout the paper when referring to these factor types.

preprint

accepted manuscript

8

include decentralization, ethical climate, culture, and approach to self-regulation. Researchers

may use the ETHOs framework to both understand existing literature, and to identify, develop,

and examine relevant research questions related to AIS and ethics.4

[Insert Figure 1 here]

The ETHOs factors influence judgment, decision-making, and actions (JDMA)

individuals make when carrying out the AIS functions of recordkeeping, reporting, or control.

Recall that these individuals may make these JDMA with the goal of personal, direct benefit (as

in asset misappropriation through false billing), or to gain an indirect benefit through the

organization, (as in fraudulent financial reporting to meet analyst expectations, eventually

resulting in individual benefits including bonuses, stock options, and promotions). We go beyond

judgment and decision-making, which academics typically use as their dependent variable, to

include actions as well.

Ethical outcomes are the measured dependent variables resulting from individuals’

JDMA. Note that this is a subjective measure, depending on one’s own determination of what is

ethical and what is unethical. While there will be general agreement about the ethicality of some

outcomes (asset misappropriation (theft) resulting in loss of cash from an organization is

unethical), there are other areas which may stimulate valid disagreement. Some could consider

income-smoothing ethical, as it reduces market volatility, thus lowering transaction costs, and

improving efficiency. Others may seriously object to all forms of income smoothing, deeming it

unethical and a violation of generally accepted accounting principles. One contribution

academics can make is to evaluate outcomes from multiple perspectives, which should lead to a

better understanding of their ethical implications.

4 Thank you to Andrea Kelton for proposing this graphical representation in her discussion of this paper at the mid- year meeting of the 2015 Accounting Information Systems Section of the American Accounting Association.

preprint

accepted manuscript

9

To show how the ETHOs framework applies to a particular paper, Figure 2 includes an

interpretation of Tuttle, Harrell, and Harrison (1997). This study examines the effects of

incentives and system design on system implementation. System design is a technological factor.

Company-provided extrinsic incentives (in this study, bonuses for on time and within budget

delivery) are an organizational factor, which create a moral hazard for the decision-maker.

Judgment surrounding the implementation of a new system is affected, resulting in an ethical

dilemma: implementation of a sub-optimal system. This study does not examine environmental

and human factors that may mitigate the effect of incentives on system implementation

decisions. Therefore, professional standards, experience, and level in the organization are among

a number of factors that might be included in future research.

[Insert Figure 2 here]

The review proceeds as follows. The next section details our methodology. The

following sections address recordkeeping, reporting, and control. In each subsection, we define

the area, review relevant ethics-related AIS research and its connection to ETHOs factors, and

provide suggestions for future research to fill existing gaps in the literature. Existing research,

with variables categorized by ETHOs factor, is available in the online supplemental material.

preprint

accepted manuscript

10

III. METHODOLOGY

All literature reviews are constrained by limits of space and the qualitative preferences

of their authors; this review is intended to be as comprehensive as is possible. We began by

reviewing all Journal of Information Systems (JIS) articles from January 2000 to December 2013

and categorizing these into general areas of AIS research. We then used these areas to develop a

list of keywords to categorize the research streams, and searched each of these terms in

conjunction with the keyword “ethics.”

One limitation of this approach is that not all ethics-related research explicitly uses the

word “ethics.” In fact, throughout our search, ethics is often an implicit, rather than explicit

motivation for AIS research. That is, researchers state that they have identified a process,

decision, policy, or behavior that is unfair, unjust, biased, obfuscates results, and/or manipulates

or takes advantage of individuals, but they do not use the word “ethics.” While not all research is

ethics-related, (some identifies ways to improve efficiency or effectiveness), much research has

some underlying motive to reduce harm to others. One early recommendation of this project is

that researchers explicitly identify and explain how their research relates to ethics. This action

(uncovering and explicating the ethics connection) will make ethics a more salient aspect in AIS

research, and like Dorothy’s red shoes reminded her of home, will remind us of something that

was there the whole time.5

Since AIS research is often interdisciplinary, we expanded the literature search beyond

JIS, and following Webster and Watson (2002), used online search tools (including Google

Scholar and university library search engines) to capture relevant studies. We comprehensively

searched the last 14 years of literature from specific journals expected to include a large amount

5 We acknowledge the above limitation of using the term “ethics” in our search, and include any research identified that investigates ethics and AIS even if the study does not specifically use “ethics” in the text.

preprint

accepted manuscript

11

of AIS-related research (e.g., JIS, MIS Quarterly, Information Systems Research, and

International Journal of Accounting Information Systems) and ethics-related research (e.g.,

Journal of Business Ethics, Ethics and Information Technology).

We then developed an understanding (see Figure 3) of what AIS are and do, using the

elements of AIS described by Romney and Steinbart (2015), set under the ethics umbrella. Using

this understanding, we established an overall structure for the review, created sub-headings

related to the major concepts or themes identified within each element of AIS. We then grouped

each article based on AIS functional area, identified ETHOs factors, and presented them in the

online supplemental material.6 This listing includes findings and highlights gaps by factor

category. We continued our search process throughout the writing stage, discovering new

streams of research, using reference lists and citation cross-referencing tools to find additional

sources, per Webster and Watson (2002).

[Insert Figure 3 here]

IV RECORDKEEPING

Recordkeeping, as shown in Figure 3, includes identifying, collecting, storing, and

managing data. While recordkeeping has always been at the heart of accounting, computer

technology has fundamentally broadened and deepened its reach. Our review finds sparse

research explicitly investigating the ethical implications of recordkeeping, although Desai and

Embse (2008) identify six key ethical issues regarding electronic information. These issues

include what data to collect, how it is collected, processed, and presented, what purpose it is used

for, and the extent of its impact on individuals and organizations.

6 Articles appear in the online supplemental material only if they test or propose theory directly related to AIS and Ethics. Not all articles are discussed within the text. Other citations appear throughout the text that are not included in the online supplemental material because they are not AIS-Ethics papers, or because they refer to current events or reports.

preprint

accepted manuscript

12

Identify and Collect Data

Organizations identify and collect data as part of recording normal accounting

transactions, making decisions about these actions an accounting issue. Firms may also internally

generate or purchase external data. Addressing ethical issues related to data acquisition is

important because once collected, data is no longer in the control of those who provided it. Thus,

it is a gatekeeper decision for all future decisions regarding collected data.

The increased reach and virtually infinite capacity of AIS bring the issue of data

identification and collection to the forefront. Integrated systems provide “organizational-wide

access and analysis capabilities by standardizing data capture and providing seamless interfaces

across functions, responsibility centers, and locations” (Dillard and Yuthas 2006, 203). This

integration led to the rise of big data7 and results in firms acquiring more data from more sources

than ever before. The accompanying ethical issues primarily focus on personal privacy issues, a

human factor. Exposure and misuse of personally identifiable information (PII) is a real threat.

For example, it takes only four credit card transactions to identify 90% of individuals, despite

using data scrubbed of all personal identifying information (de Montjoye, Radaelli, Singh, and

Pentland 2015). Individual identification through big data analytics exposes people to identity

theft, unwanted targeted marketing, location tracking, and other invasions of personal privacy.

While research in this area is sparse in the AIS literature, one approach put forth by

Kauffman, Lee, Prosch, and Steinbart (2011) explores the relationships among stakeholders and

each groups’ involvement, to understand related ethical issues. Their review suggests that

stakeholders’ concerns can differ based on which ethical issues associated with data collection

and identification are the most important. For example, businesses may perceive the sale of

personal data as part of daily operations and try to assuage privacy fears by securing the data and 7 Big data refers to the 2.5 quintillion bytes of data that are created and stored every day (IBM 2014).

preprint

accepted manuscript

13

creating protocols to govern the transfer of information. Individuals may view the same sale of

data as a privacy infringement and be more concerned with whether or not they consented to

their information being used for purposes other than their transaction with that business.

Governments may believe that they need to regulate the sale of personal data in order to

safeguard the privacy of their constituents. Understanding these relationships seems especially

important consider the pace at which technology is advancing.

Mason (1986) argues that using IT (technological factors such as facial recognition or

GPS locators) to collect personal attributes, enables the invasion of privacy of one stakeholder by

another. For example, Murphy (2011) discusses how mobile advertising can pinpoint users’

locations at any given moment in time. Ethical issues regarding data collection, such as tracking,

abound when dealing with devices that are “always on”. Stone and Stone-Romero (1998) argue

that information collection poses moral dilemmas for organizations: how do they protect the

interests of consumers and employees while collecting enough information to facilitate decision-

making. Additionally, consumers are often unable to acquire goods or services without providing

personal information the firm considers necessary (Shapiro and Baker 2002). Relevant

organizational factors include industry and products offered. Levin and Nicholson (2005)

contend that privacy laws, an environmental factor, should reflect concerns about private sector

abuse of personal information and enable individuals to set limits upon both public and private

use of their information. Different stakeholders likely have diverse concerns over the

appropriateness of what data is collected and for what purposes.

Generally Accepted Privacy Principles8 (GAPP; AICPA/CICA 2009) lists many negative

outcomes to organizations from misjudging individuals’ (and regulators’) perceptions and

8 This framework was created in 2009 by the AICPA (American Institute of Public Accountants) and CICA (Canadian Institute of Chartered Accountants), in response to privacy concerns associated with PII (personally identifiable information).

preprint

accepted manuscript

14

expectations about data identified and collected. Many of these, such as reputational damage,

legal liability, and loss of customer trust and business, come from the perceived harm resulting

from these misjudgments. A possible mitigating factor is whether the firm transparently

communicated a valid reason for collecting the data.

Based on a review of the literature, there is relatively little research investigating the

identification and collection aspect of AIS. Much of the literature is theoretical in nature and

focuses on privacy issues surrounding data capture. This literature provides directions for future

research investigating how ETHOs factors influence data collection. For example, Kauffman et

al. (2011) discuss privacy rights, policies and procedures. Researchers may investigate how

environmental factors such as regulation and industry standards, and technological factors, such

as automated collection, miniaturization of data collection tools, and connectedness (e.g., the

Internet of everything) enable or limit unethical collection practices. Further, research may

examine whether human factors influence user acceptance, consent, and/or attitudes toward

different types of notices contained within privacy policies.

Data Management: Storage and Security, Quality, and Use

Data management includes storage and security, quality maintenance (including data

accuracy and reliability), and proper use. Integrated applications such as ERP and ERP II allow

organizations to store and use data from various, disparate business units. Furthermore,

organizations, through their AIS, build and maintain extensive centralized databases housing

huge quantities of data, including personally identifiable information (PII). Because PII has been

used to identify, discriminate, persecute, punish, and silence people in the past (Parson 1966;

Lwin, Wirtz, and Williams 2007; Bansal, Zahedi, and Gefen 2010), the right to privacy appears

preprint

accepted manuscript

15

to be a basic human right, and thus control over PII is an ethical issue. The determination of PII

ownership is an area ripe for analysis, as it poses serious ethical concerns.

Organizations are morally and legally responsible for managing the data they collect.

GAPP (AICPA/CICA 2009) recommends entities only use data for the purposes identified in the

notice and for which individuals have provided explicit or implicit consent. COBIT asserts that

privacy issues are a growing concern and that organizations need to manage them if people are to

trust IT systems. The Health Insurance Portability and Accountability Act of 1996 (HIPAA)

provides guidance on maintaining the privacy and security of personally identifiable health

information (HHS 2003). HIPAA ensures patients’ rights to examine and obtain a copy of their

health records and to request corrections. Organizations also collect personal information from

employees through the human resources function. Federal and state privacy laws, as well as

organizations’ own policies govern the storage, security, quality, and use of employee

information.

Data Management (Storage and Security)

Because individuals and organizations can use data for unethical purposes (e.g., identity

theft, unfair competitive advantage, unwanted targeted advertising), its security is paramount.

Yet within the AIS domain, there is little published research in this area. In an interview with

103 IT managers, Dhillon and Torkzadeh (2006) identify specific organizational factors (e.g.,

employer trust, and authority structure) and human factors (e.g., individual lifestyle, personal

financial situation) affecting data security effectiveness. Biot-Paquerot and Hasnaoui (2009)

emphasize organizational factors, noting that strong corporate governance with clear codes of

ethics ensures clarification of fundamental values and reinforces self-regulation within

organization.

preprint

accepted manuscript

16

Sykes and Matza (1957) argue that people psychologically enable themselves to commit

rule-breaking or any anti-social actions by applying the techniques of neutralization.9 Siponen

and Vance (2010) find that neutralization is a major predictor of employees’ intention to violate

IS security policies. Similarly, Harrington (1996) shows that individuals with denial of

responsibility attitude are less likely to judge computer abuse as wrong and are more strongly

influenced by ethical codes. These findings suggest that the human factor, rationalization, holds

in IT cases as well as in other occupational fraud.

While protecting data from unauthorized access is necessary, certain security measures,

such as authentication,10 pose ethical dilemmas of their own. Sutrop and Laas-Mikko (2012)

compare the ethical issues raised by first and second-generation biometrics, both authentication

systems. Ethical issues related to first generation biometrics are privacy, autonomy, bodily

integrity, dignity, equity, and personal liberty. The difference between first and second-

generation biometrics lies in the individuals’ awareness that a third party is collecting data from

them. Second-generation biometrics therefore, raises new ethical issues because it devalues the

principle of informed consent, which may lead to less respect for individual moral autonomy and

to the loss of public trust.

Data Management (Quality)

Companies collect, store, and analyze information from multiple sources using less

structured and informal data processing systems (O’Leary 2013). However, these approaches

may pose major security and privacy breaches if the data involved is sensitive for reasons of

privacy, enterprise security, or regulatory requirements (Villars, Olofson, and Eastwood 2011).

Additionally, since big data allows for information inputs from multiple sources, there is a higher

9 In accounting, this falls into the same category of rationalization. 10 Authentication is the process of confirming that an individual accessing the system is, in fact, who he says he is.

preprint

accepted manuscript

17

likelihood of collecting data with potential errors, incompleteness, or differential precision

(O’Leary 2013). Nunan and Domenico (2013) point to the memory power of big data, passive

data collection, and ownership of the data as major ethical issues associated with big data.

Database quality begins with a high quality implementation. Many organizations

implement information systems (IS) when there are clear signs that quality problems exist and

that the system will not perform up to its expectations (Tuttle, et al. 1997). Using IS

professionals as participants, Tuttle et al. (1997) document that incentives to shirk and privately

held information motivate IS professionals to place their own interests over their organizations’

interests.

Data Management (Use)

Increasing use of electronic databases poses a major threat to data privacy, as the data

within them is searchable, downloadable (possibly undetected), and at risk for illegitimate and

unethical uses. In order to reduce the risks associated with misuse, organizations must address

privacy issues throughout the database design process and teach designers to treat privacy as an

integral database issue (Appel 2006). Culnan and Williams (2009) note that stakeholders are

vulnerable in their dealings with businesses due to their inability to control subsequent use of

their personal information. The authors suggest that organizations create a culture of privacy

through tone at the top. Organizational factors such as ethical climate and strategy and

environmental factors such as industry standards are likely influential here and motivate further

study.

Moris, Kleist, Dull, and Tanner (2014) note that inter-organizational information

sharing may help organizations (e.g., solve complex problems, reduce uncertainty, and improve

decision-making). To address privacy and security concerns in information sharing, Moris et al.

preprint

accepted manuscript

18

(2014) propose a Secure Information Market (SIM) model where organizations contribute data to

the electronic market and the market makes the information available to organizations or to pre-

approved information buyers. Industry and availability of certain technologies likely influence

SIM adoption and may be fruitful areas of investigation.

As companies are increasingly networked via outsourcing and other joint venture

agreements, data sharing becomes more common and ethical concerns more prevalent. Major

public and private organizations such as General Electric, Ford, American Express, Citibank,

British Petroleum, and Hewlett-Packard have outsourced parts of their accounting function to

third-party providers (Elharidy, Nicholson, and Scapens, 2013). Although AIS outsourcing is

common, very limited research exists on its related ethical issues. Elharidy et al. (2013) find that

legal and professional bodies enforce the ethical duties of outsourcing suppliers, whereas religion

and traditional customs and values influence the importance of integrity and ethical dealings. In a

related study, Cullinan and Zheng (2015) find that mutual funds consider potential cost savings

as an important factor in their AIS outsourcing decisions. The authors also document that funds

using more complex valuation processes and older fund families are less likely to outsource their

AIS functions.

Based on the review of articles related to data management and ethics, technological and

environmental factors appear infrequently. Prior literature does not examine how technological

factors (e.g. technological complexity, integrated information system, and emergence of big

data) and environmental factors (e.g. industry standards, regulations, and competitive pressure)

affect the ethical generation and use of information. Also missing in this literature are the

interactive effects of ETHOs factors. Further research to investigate how human factors such as

preprint

accepted manuscript

19

fear-based persuasive communication and cross-cultural differences interact with technological

factors (Crossler et al. 2013) to enable security breaches is appropriate.

Researchers may also investigate whether models such as SIM, proposed by Moris et al.

(2014), effectively address privacy and ethical concerns. Although organizations continue to

implement information systems with known quality problems, little is known about the ethics-

related factors that affect these choices. Future research may focus on whether organizational

factors, such as ethical climate, time pressure, risk preference or system complexity influence the

implementation of faulty systems.

V. REPORTING

As Figure 3 indicates, reporting involves communicating information to stakeholders.

The chief outputs of AIS are financial and non-financial reports, which assist internal and

external users in evaluating performance and in making decisions. Reporting represents a critical

and everyday intersection of AIS and human judgment as both the form and presence of reports

potentially bias user judgment. This intersection has moral implications and exposes two types of

biases, those that arise by design or those that occur accidentally, ex machina.

Commonly cited characteristics of information related to its usefulness include

accessibility, relevance, and understandability, timeliness, and reliability, completeness and

verifiability (Romney and Steinbart 2015). These characteristics provide a framework for

discussing AIS reporting and ethics.

Access (Accessibility)

Access concerns the availability, transparency, and disclosure of information from AIS

to users (Turilli and Floridi 2009). Ethical issues include considerations of how and when

organizations make AIS output available to users. Although information asymmetry is often seen

preprint

accepted manuscript

20

as a negative, Turilli and Floridi (2009) include a valuable discussion of organizations’ duties to

secure certain confidential information from disclosure.

In addition to shareholders of listed entities, there is a host of potential internal and

external users of accounting information (Young 2006). One method for examining access issues

is to consider the distinct information needs of different stakeholders (Dillard and Yuthas 2002).

ETHOs factors likely influence decisions about when and to whom information from AIS is

available. Both individuals and organizations make access decisions. This is an ethical judgment,

because these disclosures (or lack of them) can unfairly advantage (or harm) certain

stakeholders. Technology can deliver better information to all stakeholders, yet evidence

suggests that technology may also exacerbate information asymmetry. Although the SEC

established Regulation FD11 to level the playing field for all investors by regulating corporate

disclosures, Patterson (2014) finds that high frequency traders purchase market reports ahead of

public release in order to gain a competitive advantage in stock trading. While in this case, a

third party acts as a conduit for information, this situation draws attention to the role that

information intermediaries play as an interface with the organization’s AIS, and how their

involvement has ethical implications.

Human and organizational factors may inhibit sharing of financial information with

external stakeholders, despite the promise of transparency enabled by advances in technology.

Accessibility to information involves an interaction of human judgment and technology, and thus

is subject to human and technological factors. In field research, Gowthorpe (2004) reports that

senior corporate offices intend to use Internet reporting to address extant information

11 Regulation FD provides that when an issuer discloses material nonpublic information to certain individuals or entities—generally, securities market professionals, such as stock analysts, or holders of the issuer's securities who may well trade on the basis of the information—the issuer must make public disclosure of that information (SEC 2014).

preprint

accepted manuscript

21

inequalities, but haphazard implementation can result in a failure to identify stakeholder needs

adequately, leading to unintended negative consequences. In experimental research, Hassink,

Bollen, and Steggink (2007) find many firms are reluctant to respond to investor-initiated

requests for financial information over the Internet, even though there are positive consequences

from greater access (e.g., lower cost of capital, greater liquidity and a larger analyst following

Kirk and Vincent, 2013). Therefore, management may view communication through new

technology as inherently different from traditional forms of communication, which may be due

to concerns over misuse or to how technology removes the actors from the actions taken (Dillard,

2003). Researchers have not yet exhaustively examined the uses of AIS in stakeholder relations.

Future research should focus on how new technologies influence access to reports, and

whether they mitigate or exacerbate information asymmetry and/or information processing. As

evident from the article list in the online supplemental material, there are few studies, if any,

considering the ethical implications tied to technological factors. While an increasing amount of

research investigates human factors in financial reporting, there are significant research gaps

around possible interactions between human factors and new technology, such as XBRL, social

media, and real-time analysis. For instance, do the frequent updates of the XBRL taxonomy

enable managers to obfuscate financial disclosures? How might managers might seek to use

social media to exploit human factors and exacerbate information asymmetry in spite of a

general assumption that the Internet improves access. Snow’s (2015) analysis of retail investors’

perceptions of financial disclosures on Twitter versus the World Wide Web is just one example.

With regard to environmental factors, whether and how accounting and financial

regulation can keep up with innovation in the integration of reporting with new technology, such

as social media, is an area ripe for investigation. Researchers may also explore environmental

preprint

accepted manuscript

22

factors (e.g., regulation) across different countries, and investigate whether there are significant

interactions with human factors such as culture.

Judgment bias (Timeliness, Understandability, and Relevance)

AIS provide input for individual judgment and decision making (JDM) (O’Donnell and

David 2000). Technology can greatly enhance the timeliness, understandability, and relevance of

reports; however, it also enables organizations to exploit individual judgment biases, an ethical

concern. Heuristics and biases influence moral judgment just as they influence other forms of

accounting judgments (Jones, Massey and Thorne 2003; Bailey, Scott and Thoma 2010; Neri,

2015). AIS research into general judgment biases suggest two areas that merit further

investigation in relation to moral judgment: the effect that the existence of AIS have on JDM and

the effect that presentation format of reports has on JDM.

Effects of the Presence of AIS

Researchers find that the mere existence of an information system can affect moral

judgments, such as manager intentions to be honest (Hannan et al. 2006). The existence of

computer-mediated reporting technology may increase manager perceptions of scrutiny, which

results in more honest reporting. On an individual level, AIS can help improve JDM; however,

AIS might also create dysfunctional behavior, such as over-reliance on systems, reduced

accountability, and acceptance of authority, even malicious obedience (Dillard and Yuthas

2002). These behaviors reduce users’ perceived need for and exercise of professional judgment.

Some researchers express concern that the advent of risk management and related systems

actually supplants managerial moral judgment (Power 2009); moral questions may become

subject to a question of “risk appetite” rather than to adherence to a universal human value.

preprint

accepted manuscript

23

Researchers raise concerns that an auditor’s inadequate understanding of system

limitations when using expert auditing systems, may result in reduced audit quality (Sutton,

Arnold, and Arnold 1995; Sutton and Byington 1993). Longer exposure to decision aids may

actually result in deskilling that could affect an auditor’s professional judgment, resulting in

diminished fraud detection and reduced audit quality.

Effects of Presentation Format

Organizations can present financial information in verbal, numerical, or graphical

formats. Vohs, Meade, and Goode (2008) suggest presenting information in a “money” context

changes behavior. Kelton, Pennington and Tuttle (2010) and O’Donnell and David (2000)

review experimental research which demonstrates that presentation style affects individual JDM.

Dilla and Stone (1997) find that presentation of financial information in numerical rather than

verbal form affects auditors’ inherent risk judgments. In a field study, Dull, Graham and Baldwin

(2003) find that investors’ JDM differs depending on whether organizations present financial

disclosures in interactive, drill-down menus or in conventional, static web pages.

Our review suggests this area of research is already quite mature; however, future

research can combine existing ETHOs factors in new ways to identify important interactions.

There are also many judgment biases that have not yet been considered with regard to ethical

judgment. O’Donnell and David (2000) provide a framework to help researchers identify the

ways in which AIS bias JDM in general. Ethics researchers could then layer the ETHOs

framework to identify ways in which AIS might bias moral judgment specifically.

Environmental factors include the decision-making environment, technological factors include

features of the AIS, and human factors include the individual’s problem-solving skills or their

processing strategy. To date, researchers have studied only three factors in depth: presentation

preprint

accepted manuscript

24

format, decision support system use, and the level of information load involved in particular

judgments (O’Donnell and David 2000).

Financial Reporting Quality (Reliability, Completeness, and Verifiability)

Preventing and detecting fraudulent financial reporting and errors

At the organizational level, control over financial reporting is a clear purpose of

legislation (e.g., SOX) and profession-sponsored frameworks (e.g., COSO) Drennan (2004).

However, legislation alone does not prevent major fraudulent practices (Rockness and Rockness

2005). Rather, strong ethical corporate culture, internal controls, laws, rewards, and penalties

must work together to provide ethical and transparent financial reporting. Thus, environmental

factors, in conjunction with technology, organization, and human factors, influence control

effectiveness.

The automation inherent in modern AIS enables management to adopt continuous

monitoring and auditing to reduce fraudulent financial reporting. Organizations can use

continuous monitoring to help make specific components of AIS, such as the purchasing system,

compliant with SOX regulations (Chang, Wu, and Chang 2008). Continuous auditing also has

the potential to yield better testing and online communication, and less expensive and timelier

audits (Kogan, Sudit, and Vasarhelyi 1999). However, the introduction of these tools raises

ethical concerns, including auditor over-reliance and negative effects on auditor knowledge and

skills development (Daigle, Daigle, and Lampe 2008, Dillard and Yuthas 2001).

XBRL, a technology-based standard, promises more reliable, standardized financial

reporting, yet also introduces ethical concerns. While XBRL is a computer-readable format, the

SEC requires auditors to provide assurance on a manual version of the financial reports

preprint

accepted manuscript

25

generated from it.12 However, Boritz and No (2009) and Bartley, Chen and Taylor (2011) point

out serious shortcomings in XBRL’s early regulation and implementation. XBRL’s complexity

along with the individuals’ inexperience auditing and interpreting XBRL filings provides

managers an opportunity to misrepresent these disclosures with a lower chance of detection. On

the other hand, investors may be able to use XBRL disclosure analysis tools to locate specific

information more easily, improving detection of accounting irregularities by making it more

difficult to “hide information in plain sight” (Cohen, Schiavina, and Servais 2005). Whether

XBRL enables more or less misstatement is a question for future research.

AIS technology enables management to conduct sensitivity analyses to gauge the effect

of transactions on quarterly and annual earnings quickly and easily, increasing the opportunity

for earnings management. Malenko and Grundfest (2014) provide evidence of firms managing

EPS numbers reported by US listed corporations.13 While there is evidence that accruals-based

earnings management (EM) is on the decline post-SOX, it remains prevalent (Dichev, Graham,

Harvey and Rajgopal 2013) and real activities EM14 may be on the rise (Cohen, Dey, and Lys

2008). Arguably, advances in AIS facilitate EM. Using computer programs and digital data,

managers can run virtually unlimited simulations to identify the accounting strategy with the best

(or most desired) financial statement outcome making EM faster and easier than ever before.

Much of the existing research into new reporting technologies considers their impact on

capital markets. Future research should examine how technological factors, such as advances in

12 The SEC and PCAOB developed XBRL guidelines (Plumlee and Plumlee 2008) to address adoption and assurance issues. 13 Quadrophobia, “a fear of four,” is the phenomenon that the number four occurs statistically less frequently than other numerals in the first post-decimal digit of EPS data. The claim is that this occurs because firms manage reported EPS so that it is rounded up more often than it is rounded down. For instance, Dell is cited as rounding up EPS for 48 straight quarters, which is statistically improbable. 14 Real activities earnings management involves manipulating the operations of the business, such as inventory levels or sales through “channel stuffing” (Roychowdhury 2006).

preprint

accepted manuscript

26

audit software, continuous monitoring, and XBRL interact with human factors, such as age,

experience and functional area, or with organizational factors such as ethical climate (Martin and

Cullen 2006) or industry to enable or discourage fraud or deception. Environmental factors, such

as new regulation, seem particularly relevant since present research has primarily considered

regulation of conventional, paper-based media.

VI. CONTROL

AIS encompass controls over the activities of both people and systems to enhance

organizational efficiency and effectiveness and safeguard assets (see Figure 3). Ethical issues

arise when people, like other business assets, are monitored and controlled (Romney and

Steinbart 2015).

Control implies managers, including accountants, have moral obligations when

allocating resources and prioritizing stakeholder claims.15 Yet, controls designed to manage

organizational efficiency and effectiveness can have a detrimental effect on moral judgment at

the human level (Abernathy and Brownell 1997). Research outside AIS finds that formal control

systems16 may be positively associated with employee moral awareness and behavior (Rottig,

Koufteros, and Umphress 2011), but that over-reliance on rules-based systems may also be

detrimental (Stansbury and Barry 2007), as when individuals blindly follow rules despite

15 Otley (1999, 355-356) suggests that management control includes identifying organizational goals leading to an organization’s overall future success; adopting strategies, processes, and activities that enable an organization to achieve its goals; defining levels of performance in each strategy area that allow an organization to set performance targets to assess the achievement of its goals; defining the rewards (penalties) that managers will receive for achieving (failing to achieve) organizational performance targets; and creating information flows (feedback and feed-forward loops) that allow the organization to learn from its experience and adapt its current behavior to reflect what it has learned. 16 Consistent with Weaver, Trevino, and Cochran’s (1999) conception of formal ethics programs, Rottig (2011, 163) defines a multifaceted formal ethical infrastructure as one “consisting of formal communication, recurrent communication, formal surveillance, and formal sanctions.”

preprint

accepted manuscript

27

changes in context. These discoveries are highly relevant to AIS research related to internal

control, management accounting, and audit.

A major aspect of organizational control is the control over employees through electronic

monitoring. Electronic monitoring of employees in the workplace has deep ethical implications

with respect to workplace outcomes such as employee perceptions of privacy and fairness,

quality of work life, and stress-related illness (Tabak and Smith 2005). Using the concepts of

formalism and utilitarianism, Alder, Schminke, Noel, and Kuenzi (2008) argue that an

employee’s prior beliefs and ethical orientation, both human factors, affect his or her reaction

towards electronic monitoring. Similarly, continuous monitoring introduces the ethical question

of whether greater surveillance of workers and their work is at all times and in all places

acceptable and desirable. Monitoring may have unintended consequences through its effects on

individual judgment and behavior.

In addition to control over people and their activities, AIS include controls over assets.

While information technology may positively affect organizational development and growth, its

widespread use also increases opportunities for occupational fraud (Kesar 2006), which costs

about 5% of an organization’s total revenue (ACFE 2014). Although employee dishonesty and

fraud are clearly not new issues, use of integrated information technology creates fruitful ground

for new forms of employee dishonesty (Todd 2004). Further, considering Ariely’s (2008) finding

that cheating is easier when the actor is a step removed from the cash, technology may have the

unintended consequence of increasing unethical behavior by creating illusory distance between

individuals and the cash they misappropriate.

Lynch and Gomaa (2003) suggest that information technology enables fraud. Based on

Ajzen’s (1991) theory of planned behavior, they posit a framework for considering the likelihood

preprint

accepted manuscript

28

of fraud in an environment that includes integrated information systems, a technological factor.

In a survey of IT managers, Behling, Floyd, Smith, Koohang, and Behling (2009) find that even

when employee fraud detection controls are in place, they are not fully effective due to

organizational factors such as limited staff, shrinking budgets, and time constraints. Wells

(2007) posits that technology controls are not always enough to prevent employee fraud because

they are designed to provide reasonable, but not absolute assurance. Furthermore, employees

with sufficient motivation can override most controls since employees are usually more aware

than are outsiders of flaws in the system (Wells 2007; Kesar 2006). Human factors such as the

ability to rationalize and financial pressures are relevant here.

Based on our review of articles related to the control function of AIS, technological and

environmental factors are under-researched. Prior literature does not examine how environmental

factors (e.g. local laws and industry standards) affect the acceptance of employee monitoring and

employee satisfaction. Although limited research indicates that AIS technology facilitates fraud,

more research is needed to validate this argument. Understanding whether and how technological

complexity and certain AIS features facilitate (or mitigate) occupational fraud is a fruitful path to

explore. Also important is to investigate whether and how organizational and technological

factors (e.g. decision aids, AIS features, tracking tools, remote access, formal ethical

infrastructure, and continuous monitoring practices) negatively influence critical thinking, induce

employees towards checklist mentality in ethical decisions, and contribute to increased

occupational fraud.

VIII. CONCLUSION

This review outlines major areas of interest related to AIS and ethics, based on the

primary AIS functions of recordkeeping, reporting, and control. We define ethics as issues that

preprint

accepted manuscript

29

infringe upon universal human rights, and expand the definition to include issues related to the

public’s expectations of accounting and other business professionals. AIS affect peoples’ lives;

these effects are magnified by systems’ ubiquitous integration into all areas of organizations and

by their expanding technological capabilities (i.e., ability to collect, store, disseminate, and

process data faster and further, with minimal cost). It is imperative that individuals and groups

acknowledge the harm and risk of harm that inevitably come with AIS. This review suggests that

overreliance on AIS potentially provides individuals a convenient source of rationalization for

unethical behavior.

We discuss the current state of research in each of the AIS functional areas, summarizing

findings, and linking them to ETHOs factor categories and suggest future research within each

category. Within recordkeeping are privacy issues associated with data collected, stored, and

used by organizations. The discussion expands beyond consideration of customer data to include

other stakeholders’ data such as that belonging to employees, vendors, and other third parties. A

central concern is the determination of who owns data, and how organizations may use this data

to harm others.

The next area is reporting, a key function of AIS. As AIS are the primary source of

financial disclosures, it is important to understand their technological capabilities, and how these

may lead to unethical acts. One example is the ease with which managers can use scenario

analysis to manage earnings faster and more precisely than ever before. Another example is the

ability to alter presentation format to influence moral judgments (e.g., minimizing effects of

employees’ layoffs by scaling graphs to overstate benefits or to obscure costs to individuals).

Control issues, namely, how managers use AIS as a tool to control people and assets, is

the final area explored. Employee monitoring, decision automation, and dehumanization of

preprint

accepted manuscript

30

processes all affect human rights. Monitoring, both with and without consent, evokes fears of

“Big Brother” and may impede productivity and innovation. Systems enable individuals to

distance themselves both physically and psychologically from their actions, facilitating

occupational fraud by enabling rationalizations. Control issues are inextricably linked with AIS

and ethics.

In the process of preparing this review, we were encouraged by the attention a small

contingent of AIS researchers has paid to ethics. However, there are significant gaps in the

literature. While much AIS research has ethical implications, researchers rarely explicitly tie

their research questions and motivations underlying ethical goals. Preventing harm to others is a

noble endeavor, and we recommend researchers acknowledge this as a purpose of their research

when appropriate.

Accounting is a moral discipline; people designed, developed, and control it, for the

benefit of themselves and others. There are no scientific laws of accounting, thus we are

ultimately responsible for its development and for its effects on society. Universal ethics demand

that professionals and academics alike, take on the responsibility of understanding how AIS not

only help, but also potentially harm others. It is a challenge we are fully capable of meeting.

preprint

accepted manuscript

31

References Abernathy, M. A., and P. Brownell. 1997. Management control systems in research and

development organizations: the role of accounting, behavior and personnel controls. Accounting, Organizations and Society 22(3): 233-248.

Adams, G.B., and D.L. Balfour. 1998. Unmasking Administrative Evil. Thousand Oaks, CA.

Sage Publications. Ajzen, I. 1991. The theory of planned behavior. Organizational Behavior and Human Decision

Processes 50(2): 179-211. Alder, G. S., M. Schminke, T. W. Noel, and M. Kuenzi. 2008. Employee reactions to Internet

monitoring: The moderating role of ethical orientation. Journal of Business Ethics 80(3): 481-498.

American Institute of Certified Public Accounts (AICPA). 2013a. Code of professional conduct

and bylaws. Available at: http://www.aicpa.org/research/standards/codeofconduct/downloadabledocuments/2013june1c odeofprofessionalconduct.pdf

American Institute of Certified Public Accountants (AICPA). 2013b. 2013 North America Top

Technology Initiatives Survey Results. Available at: http://www.aicpa.org/InterestAreas/InformationTechnology/ Resources/TopTechnologyI nitiatives/Pages/2013TTI.aspx.

American Institute of Certified Public Accountants (AICPA). 2014. Code of Professional

Conduct. Available at: http://pub.aicpa.org/codeofconduct/Ethics.aspx. American Institute of Certified Public Accountants and the Canadian Institute of Chartered

Accountants (AICPA/CICA). 2009. Generally Accepted Privacy Principles: CPA and CA Practitioner Version. New York, NY: AICPA/CICA.

Appel, F. 2006. The study of database design must address privacy concerns. Journal of

Information, Communication and Ethics in Society 4(3): 155-161. Ariely, D. (2008). How honest people cheat. Harvard Business Review, 86(2): 24-24. Association of Certified Fraud Examiners (ACFE). 2014. Report to the Nation: Occupational

Fraud and Abuse. Association of Certified Fraud Examiners.

preprint

accepted manuscript

32

Bailey, C. D., I. Scott, and S. J. Thoma. 2010. Revitalizing accounting ethics research in the neo- Kohlbergian framework: Putting the DIT into perspective. Behavioral Research in Accounting 22(2): 1-26.

Bansal, G., F. Zahedi, and D. Gefen. 2010. The impact of personal dispositions on information

sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems 49(2): 138-150.

Bartley, J., A. Y. S. Chen, and E. Z. Taylor. 2011. A comparison of XBRL filings to corporate

10-Ks: Evidence from the voluntary filing program. Accounting Horizons 25(2): 227-245. Beard, D., and H. J. Wen. 2007. Reducing the threat level for accounting information systems.

CPA Journal 77(5): 34. Behling, S., K. Floyd, T. Smith, A. Koohang, and R. Behling. 2009. Managers’ perspectives on

employee information technology fraud issues within companies/organizations. Issues in Information Systems 10(2): 76-81.

Biot-Paquerot, G., and A. Hasnaoui. 2009. Stakeholders perspective and ethics in financial

information systems. Journal of Electronic Commerce in Organizations 7(1): 59-70. Black, E., and B. Wallace. 2001. IBM and the Holocaust: The strategic alliance between Nazi

Germany and America's most powerful corporation. NY: Crown Publishers. Bond, B., Y. Genovese, D. Miklovic, N. Wood, B. Zrimsek, and N. Rayner. 2000. ERP is dead–

Long live ERP II. Gartner Group, New York. Boritz, J. E., and W. G. No. 2009. Assurance on XBRL-related documents: The case of United

Technologies Corporation. Journal of Information Systems 23(2): 49-78. Boritz, J. E., and W. G. No. 2011. E-commerce and privacy: Exploring what we know and

opportunities for future discovery. Journal of Information Systems 25(2): 11-45. Brancheau, J. C., B. D. Janz, and J. C. Wetherbe. 1996. Key issues in information systems

management: 1994-95 SIM Delphi results. MIS Quarterly, 225-242. Brancheau, J. C., and J. C. Wetherbe. 1987. Key issues in information systems management.

MIS Quarterly, 23-45.

preprint

accepted manuscript

33

Bronstein, S., D. Griffin, and N. Black. 2014. VA deaths covered up to make statistics look better, whistle-blower says. Available at: http://www.cnn.com/2014/06/23/us/phoenix-va- deaths-new-allegations/.

Chang, S. I., C. C. Wu, and I. C. Chang. 2008. The development of a computer auditing system

sufficient for Sarbanes-Oxley Section 404—A study on the purchasing and expenditure cycle of the ERP system. Information Systems Management 25(3): 211-229.

Chee, F. Y. 2014. European court says Google must respect ‘right to be forgotten’. Reuters (May

13). Available at: http://www.reuters.com/article/2014/05/13/us-eu-google-dataprotection- idUSBREA4C07120140513

Clarke, R. 1999. Internet privacy concerns confirm the case for intervention. Communications of

the ACM 42(2): 60-67. Cohen, D. A., A. Dey, and T.Z. Lys. 2008. Real and accrual-based earnings management in the

pre-and post-Sarbanes-Oxley periods. The Accounting Review 83(3): 757-787. Cohen, J., G. B. Manzon Jr, and V. L. Zamora. 2015. Contextual and Individual Dimensions of

Taxpayer Decision Making. Journal of Business Ethics 126(4): 631-647. Cohen, E. E., T. Schiavina and O. Servais. 2005. XBRL: The standardised business language for

21st century reporting and governance. International Journal of Disclosure and Governance 2(4): 368-394.

Committee of Sponsoring Organizations of the Treadwway Commission (COSO). 2013. Internal

control integrated framework. New York, NY: AICPA. Cooper, C. 2009. Extraordinary circumstances: The journey of a corporate whistleblower. John

Wiley & Sons. Copeland, J. 2005. Ethics as an imperative. Accounting Horizons 19(1): 35-43. Crossler, R. E., A. C. Johnston, P. B. Lowry, Q. Hu, M. Warkentin, and R. Baskerville. 2013.

Future directions for behavioral information security research. Computers and Security 32: 90-101.

Cullinan, C.P., and X. Zheng. 2015. Outsourcing accounting information systems: Evidence

from closed-ended mutual fund families. International Journal of Accounting Information Systems 17: 65-83.

preprint

accepted manuscript

34

Culnan, M. J., and C. C. Williams. 2009. How ethics can enhance organizational privacy: Lessons from the ChoicePoint and TJX data breaches. Management Information Systems Quarterly 33(4): 6.

Daigle, J. J., R. J. Daigle, and J. C. Lampe. 2008. Auditor ethics for continuous auditing and

continuous monitoring. Information Systems Control Journal 3: 1-4. de Montjoye, Y. A., L. Radaelli, V. K. Singh, and A. S. Pentland. 2014. Unique in the shopping

mall: On the re-identifiability of credit card metadata. Science 347(6221): 453-580. Deloitte. 2014. The 2013 COSO framework and the audit committee. Audit Committee Brief.

Available at: http://www2.deloitte.com/content/dam/Deloitte/us/Documents/risk/us-aers- acbrief-march-2014.pdf.

Desai, M. S., and T. J. Embse. 2008. Managing electronic information: An ethics perspective.

Information Management and Computer Security 16(1): 20-27. Dhillon, G. 2001. Violation of safeguards by trusted personnel and understanding related

information security concerns. Computers and Security 20(2): 165-172. Dhillon, G., and G. Torkzadeh. 2006. Value‐focused assessment of information system security

in organizations. Information Systems Journal 16(3): 293-314. Dichev, I., J. Graham, C. R. Harvey, and S. Rajgopal. 2013. Earnings quality: Evidence from

the field. Journal of Accounting and Economics 56(2-3): 1-33. Dilla, W. N., and D. N. Stone. 1997. Representations as decision aids: The asymmetric effects of

words and numbers on auditors' inherent risk judgments. Decision Sciences 28(3): 709-743. Dillard, J. F. 2003. Professional services, IBM, and the Holocaust. Journal of Information

Systems 17(2): 1-16. Dillard, J. F., and K. Yuthas. 2001. A responsibility ethics for audit expert systems. Journal of

Business Ethics 30(4): 337-359. Dillard, J. F., and K. Yuthas. 2002. Ethics research in AIS. In Researching Accounting as an

Information Systems Discipline, edited by Arnold, V., and S. Sutton, 181-206. Sarasota, FL: American Accounting Association.

preprint

accepted manuscript

35

Dillard, J. F., and K. Yuthas. 2006. Enterprise resource planning systems and communicative action. Critical Perspectives on Accounting 17(2): 202-223.

Drennan, L. T. 2004. Ethics, governance and risk management: Lessons from Mirror Group

Newspapers and Barings Bank. Journal of Business Ethics 52(3): 257-266. Dull, R. B., A. W. Graham, and A. A. Baldwin. 2003. Web-based financial statements:

Hypertext links to footnotes and their effect on decisions. International Journal of Accounting Information Systems 4(3): 185-203.

Elharidy, A. M., B. Nicholson, and R. Scapens. 2013. The embeddedness of accounting

outsourcing relationships. Qualitative Research in Accounting and Management 10(1): 60-77.

Espinosa-Pike, M. 1999. Business ethics and accounting information. An analysis of the Spanish

code of best practice. Journal of Business Ethics 22(3): 249-259. Glass, R. S., and W. A. Wood. 1996. Situational determinants of software piracy: An equity

theory perspective. Journal of Business Ethics 15(11): 1189-1198. Gentile, M.C. 2012. Giving Voice to Values: How to Speak Your Mind When You Know What’s

Right. Yale University Press. Gowthorpe, C. 2004. Asymmetrical dialogue? Corporate financial reporting via the Internet.

Corporate Communications: An International Journal 9(4): 283-293. Hannan, R. L., F. W. Rankin, and K. L. Towry. 2006. The effect of information systems on

honesty in managerial reporting: A behavioral perspective. Contemporary Accounting Research 23(4): 885-918.

Harrington, S. J. 1996. The effect of codes of ethics and personal denial of responsibility on

computer abuse judgments and intentions. MIS Quarterly 257-278. Hassink, H., L. Bollen, and M. Steggink. 2007. Symmetrical versus asymmetrical company-

investor communications via the internet. Corporate Communications: An International Journal 12(2): 145-160.

preprint

accepted manuscript

36

Hunt, N. and G. Iyer. 2015. The effect of tax domain, income class, and personal norms: An analysis of taxpayer compliance decisions using paper and software. Working paper, University of North Texas. International Business Machines IBM. 2014. What is big data? Big data at the speed of business.

Available at: http://www-01.ibm.com/software/data/bigdata/what-is-big-data.html Jones, J., D. W. Massey, and L. Thorne. 2003. Auditors’ ethical reasoning: Insights from past

research and implications for the future. Journal of Accounting Literature 22: 45–103. Kauffman, R. J., Y. J. Lee, M. Prosch, and P. J. Steinbart. 2011. A survey of consumer

information privacy from the accounting information systems perspective. Journal of Information Systems 25(2): 47-79.

Kelton, A. S., R. R. Pennington, and B. M. Tuttle. 2010. The effects of information presentation

format on judgment and decision making: A review of the information systems research. Journal of Information Systems 24(2): 79-105.

Kesar, S. 2006. Legal issues alone are not enough to manage computer fraud committed by

employees. Journal of International Commercial Law and Technology 1(1): 25-40. Kidder, R.M. 2005. Moral Courage. Harper Collins. Kirk, M. P., and J. Vincent. 2014. Professional investor relations within the firm. The Accounting

Review. 89(4):1421-1452. Kogan, A., E. F. Sudit, and M. A. Vasarhelyi. 1999. Continuous online auditing: A program of

research. Journal of Information Systems 13(2): 87-103. Levin, A., and M. J. Nicholson. 2005. Privacy law in the United States, the EU and Canada: the

allure of the middle ground. University of Ottawa Law and technology Journal 2: 357. Lynch, A., and M. Gomaa. 2003. Understanding the potential impact of information technology

on the susceptibility of organizations to fraudulent employee behavior. International Journal of Accounting Information Systems 4(4): 295-308.

Lwin, M., J. Wirtz, and J. D. Williams. 2007. Consumer online privacy concerns and responses:

A power–responsibility equilibrium perspective. Journal of the Academy of Marketing Science 35(4): 572-585.

preprint

accepted manuscript

37

Malenko, N., and J. Grundfest. 2014. Quadrophobia: Strategic rounding of EPS data. Rock Center for Corporate Governance at Stanford University Working Paper No. 65; Stanford Law and Economics Online Working Paper No. 388. Available at: http://ssrn.com/abstract=1474668 or http://dx.doi.org/10.2139/ssrn.1474668.

Mason, R. O. 1986. Four ethical issues of the information age. MIS Quarterly 5-12. Martin, K. D., and J. B. Cullen. 2006. Continuities and extensions of ethical climate theory: A

meta-analytic review. Journal of Business Ethics 69 (2):175-194. Mauldin, E. G., and L. V. Ruchala. 1999. Towards a meta-theory of accounting information

systems. Accounting, Organizations and Society 24(4): 317-331. Møller, C. (2005). ERP II: A conceptual framework for next-generation enterprise systems?.

Journal of Enterprise Information Management, 18(4), 483-497. Moris, B. W., V. F. Kleist, R. B. Dull, and C. D. Tanner. 2014. Secure information market: A

model to support information sharing, data fusion, privacy, and decisions. Journal of Information Systems 28(1): 269-285.

Murphy, D. 2011. The geo-targeting revolution (March 4). Available at:

http://mobilemarketingmagazine.com/geo-targeting-revolution/ Neely, M. P. and J. S. Cook. 2011. Fifteen years of data and information quality literature:

Developing a research agenda for accounting. Journal of Information Systems 25(1): 79-108. Neri, M. P. 2015. Moral intuition: A review for accounting research. Presented at the 20th

Annual Ethics Research Symposium of the American Accounting Association, Chicago, IL, August 9.

Nunan, D., and M. D. Domenico. 2013. Market research and the ethics of big data. International

Journal of Market Research 55(4): 41-56. O'Donnell, E., and J. S. David. 2000. How information systems influence user decisions: a

research framework and literature review. International Journal of Accounting Information Systems 1(3): 178-203.

O'Leary, D. E. 2013. Artificial intelligence and big data. IEEE Intelligent Systems 28(2): 96-99.

preprint

accepted manuscript

38

Otley, D. 1999. Performance management: a framework for management control systems research. Management Accounting Research 10(4): 363-382.

Parson, D. P. 1966. Individual right of petition: A study of methods used by international

organizations to utilize the individual as a source of information on the violations of human rights. The Wayne Law Review 13: 678.

Patterson, S. 2014. Speed traders get an edge (February 6). Available at:

http://online.wsj.com/news/articles/SB10001424052702304450904579367050946606562 Paul, R., and L. Elder. 2013. The Thinker's Guide to Ethical Reasoning. Tomales, CA:

Foundation for Critical Thinking Press. Pavlou, P. A. 2011. State of the information privacy literature: where are we now and where

should we go. MIS Quarterly 35(4): 977-988. Pennington, R., and B. Tuttle. 2009. Managing impressions using distorted graphs of income and

earnings per share: The role of memory. International Journal of Accounting Information Systems 10(1): 25-45.

Plumlee, R. D., and M.A. Plumlee. 2008. Assurance on XBRL for financial reporting.

Accounting Horizons 22(3): 353-368. Power, M. 2009. The risk management of nothing. Accounting, Organizations and Society 34(6):

849-855.

Rai, S. 2014. Despite dramatic half-billion-dollar award in Satyam scandal, ‘India’s Enron,’ It may be years before investors see a dime. Forbes (July 21). Available at: http://www.forbes.com/sites/saritharai/2014/07/21/despite-dramatic-half-billion-dollar- award-in-satyam-scandal-indias-enron-it-may-be-years-before-investors-see-a-dime/.

Rapoport, M., and J. S. Lublin. 2015. Meet the corporate board's 'kitchen junk drawer'; workload of the audit committee has expanded well beyond oversight of financial reporting. Wall Street Journal (February 3). Available at: http://blogs.wsj.com/cfo/2015/02/03/meet-the- corporate-boards-kitchen-junk-drawer/

Rockness, H., and J. Rockness. 2005. Legislated ethics: From Enron to Sarbanes-Oxley, the

impact on corporate America. Journal of Business Ethics 57(1): 31-54. Romney, M. B., and P. J. Steinbart. 2015. Accounting Information Systems. Upper Saddle River,

NJ: Prentice Hall.

preprint

accepted manuscript

39

Rottig, D., X. Koufteros, and E. Umphress. 2011. Formal infrastructure and ethical decision-

making: An empirical investigation and implications for supply management. Decision Sciences 42(1): 163-204.

Roychowdhury, S. 2006. Earnings management through real activities manipulation. Journal of

accounting and economics 42(3): 335-370. United States Securities and Exchange Commission (SEC). 2014. Fair Disclosure, Regulation

FD. Available at: http://www.sec.gov/answers/regfd.htm Shapiro, B., and C. R. Baker. 2002. Information technology and the social construction of

information privacy. Journal of Accounting and Public Policy 20(4): 295-322. Sipior, J. C., B. T. Ward, and N. M. Rongione. 2004. Ethics of collecting and using consumer

Internet data. Information Systems Management 21(1): 58-66. Siponen, M., and A. Vance. 2010. Neutralization: new insights into the problem of employee

information systems security policy violations. MIS Quarterly 34(3): 487. Snow, N. M. 2015. Retail investors' perceptions of financial disclosures on social media: An

experimental investigation using twitter. Working Paper. University of South Florida. Soll, J. The reckoning: Financial accountability and the rise and fall of nations: Basic Books. Stansbury, J., and B. Barry. 2007. Ethics programs and the paradox of control. Business Ethics

Quarterly 239-261. Stone, D. L., and E. F. Stone-Romero. 1998. A multiple stakeholder model of privacy in

organizations. Managerial ethics: Moral Management of People and Processes 35-59. Sutrop, M., and K. Laas‐Mikko. 2012. From identity verification to behavior prediction: Ethical

implications of second generation biometrics. Review of Policy Research 29(1): 21-36. Sutton, S., V. Arnold, and T. Arnold. 1995. Toward an understanding of the philosophical

foundations for ethical development of audit expert systems. Research on Accounting Ethics 1: 61-74.

preprint

accepted manuscript

40

Sutton, S. G., and J. R. Byington. 1993. An analysis of ethical and epistemological issues in the development and implementation of audit expert systems. Advances in Public Interest Accounting 5: 231-243.

Sykes, G. M., and D. Matza. 1957. Techniques of neutralization: A theory of delinquency.

American Sociological Review 664-670. Tabak, F., and W. P. Smith. 2005. Privacy and electronic monitoring in the workplace: A model

of managerial cognition and relational trust development. Employee Responsibilities and Rights Journal 17(3): 173-189.

Todd, K. J. 2004. Using digital evidence to ferret out the dishonest employee. Employee

Relations Law Journal 30(2): 13-22. Turilli, M., and L. Floridi. 2009. The ethics of information transparency. Ethics and Information

Technology 11(2): 105-112. Tuttle, B., A. Harrell, and P. Harrison. 1997. Moral hazard, ethical considerations, and the

decision to implement an information system. Journal of Management Information Systems 7-27.

United Nations, Universal Declaration of Human Rights, December 10, 1948. Unites States Department of Health and Human Services (HHS). 2003. Summary of the HIPAA

privacy rule. Available at: http://www.hhs.gov/ocr/privacy/hipaa/understanding/summary/privacysummary.pdf

Villars, R. L., C. W. Olofson, and M. Eastwood. 2011. Big data: What it is and why you should

care. White Paper, IDC. Vohs, K.D., N.L. Meade, and M.R. Goode. 2008. Merely activating the concept of money

changes personal and interpersonal behavior. Current Directions in Psychological Science 17(3): 208-212.

Weaver, G. R., L. K. Trevino, and P. L. Cochran. 1999. Integrated and decoupled corporate

social performance: Management commitments, external pressures, and corporate ethics practices. Academy of Management Journal 42(5): 539-552.

Webster, J., and R. T. Watson. 2002. Analyzing the past to prepare for the future: Writing a

literature review. Management Information Systems Quarterly 26(2): 3.

preprint

accepted manuscript

41

Wells, J. T. 2007. What is your fraud IQ? Journal of Accountancy 204(6): 56-57. Young, J. J. 2006. Making up users. Accounting, Organizations and Society 31(6): 579-600.

preprint

accepted manuscript

42

preprint

accepted manuscript

43

preprint

accepted manuscript

44

Recordkeeping Identify Collect Store Manage

Reporting Communicate Data and Information

Control People Activities Assets

ETHICS Environmental

Technological

Human

Organizational

Figure 3 Relationship of AIS Functions, Ethics, and ETHOs Factors

V ie

w p

u b lica

tio n sta

ts V

ie w

p u b lica

tio n sta

ts

  • Title Page
  • Article