The emergence of the digital era has significantly changed various aspects of professional and educational contexts, notably due to the widespread use of e-learning platforms. These platforms offer various benefits, including flexible study schedules, access to a vast collection of resources, and the ability for personalized learning experiences. Nonetheless, the advent of online learning has resulted in an increase in misconduct and dishonesty, particularly among individuals who engage in e-learning programs for professional development. The purpose of this article is to look into the numerous aspects that contribute to employee dishonesty in e-learning in a healthcare setting. This study will use the Fraud Triangle Model Factor to investigate the incentives that drive such activity. Although there were various study conducted in this topic, the current study focusses on nurses in healthcare company in Jakarta, Indonesia. As far as this study concern, there are very limited study conducted in this field.

Nurses are required to engage in continuous professional development throughout their careers (Beckett, 2023). This involves actively participating in ongoing education and training opportunities (1). In order to maintain their annual registration and licensing, nurses are obligated to participate in ongoing professional education, gain new skills, and ensure that their practices align with international best practices. Traditional in-person education can present challenges owing to demanding workloads, time constraints, geographical limitations, financial burdens, restricted learning options in the area, and a lack of adequate supervision. Nevertheless, electronic learning (e-learning) overcomes certain obstacles that arise when in-person training is not feasible (2). E-learning encompasses all educational activities that take place through the utilization of information and computer technologies (3). Individuals can utilize digital devices, such as laptops or computers, in conjunction with self-directed and self-regulated learning. Hence, e-learning serves as a flexible, easily accessible, and convenient medium for nurses to pursue further education (7)

The use of e-learning in healthcare firms raises substantial concerns around academic dishonesty and misconduct. These problems can significantly erode the trustworthiness and efficiency of online training programs, ultimately affecting the calibre of healthcare services. In this article, we explore the particular difficulties presented by dishonesty and misbehaviour in the e-learning setting. The act of cheating in e-learning environments is widespread because of the perceived anonymity and absence of direct monitoring (9). In conventional educational environments, teachers have the ability to directly supervise students, which creates a greater challenge for them to engage in deceitful actions (36). Nevertheless, the online nature of e-learning eliminates this level of supervision, hence intensifying the inclination to engage in dishonest behaviour (37). Hence, the main objectives of the study is to examine the relationship between pressure, opportunities, rationalization and the intention to engage in dishonest activity in e-learning. The following section will provide literature review and discusses the research variables in details.

This study used the fraud triangle model, a theoretical framework used to understand the primary causes of dishonest behaviour. This model has been used as explanatory framework for fraud in a company. Based on this model, the determinants of dishonesty in e-learning among employees at healthcare companies can be classified as ‘pressures’, ‘opportunities’, and ‘rationalisation’. Pressures encompass a range of external and internal obligations, such as substantial workloads, personal challenges, and peer influence (48). The e-learning system's absence of rigorous monitoring methods, easy access to answer keys, and existing gaps create opportunities for exploitation. Rationalisations encompass the arguments that employees adopt to validate their conduct, such as the belief that "everyone does it" or the rationalisation of it as a small transgression resulting from time limitations (17). These factors jointly impact the behavioural intention to engage in dishonest activities during e-learning sessions, which evaluates the likelihood of employees behaving dishonestly. It is essential to consider these considerations when creating measures to reduce dishonest behaviours and improve the integrity of e-learning programmes within the firm.

Literature Review

The widespread adoption of e-learning platforms in corporate settings has yielded several benefits, such as the ability to customize learning schedules, implement scalable training programs, and access a wide range of materials. Nevertheless, the shift to digital learning has also brought other obstacles, specifically with dishonesty and misconduct. This section of the thesis examines the various aspects of dishonesty behaviour in online learning specifically in corporate environments. An analysis of both theoretical ideas and empirical investigations is conducted in order to have a thorough comprehension of the subject at hand.

E-learning Dishonesty and Misconduct in Corporate Environment

The literature on cheating in online contexts has categorized cheating tactics into various distinct groups. According to (59), there are five categories of academic dishonesty: collusion (organized cheating with others), deception (deceptive action alone), plagiarism (copying material from a source and claiming it as one's own work), technology manipulation (using technology to manipulate opportunities), and misrepresentation (falsifying information by using materials from another individual or service). Meanwhile, (53) categorized academic misconduct into five distinct categories. These include plagiarism, which involves using someone else's words or ideas without giving proper credit; fabrication, which entails inventing data, results, information, or numbers; falsification, which involves manipulating research, data, or results to inaccurately represent information; misrepresentation, which involves falsely portraying oneself, efforts, or abilities; and misbehaviour, which refers to actions that do not explicitly constitute misconduct but go against prevailing behavioural expectations. Recent research however, indicates that current cheating tactics are more sophisticated.

Unauthorized participation with others is one of methods of cheating in virtual proctored tests. Collaboration, in this context, refers to the act of seeking assistance from someone else during an examination, despite it being prohibited (Alessio & Messinger, 2021). Instances of interacting with others encompass sharing information during an evaluation using methods such as whispering, using signs or code languages, sending text messages with replies, and utilizing computerized chat platforms. Additional instances encompass observing or replicating from someone else's test and permitting others to observe or replicate from one's own test (D’Souza & Siegfeldt, 2017). 

Impersonation is another form of cheating. It refers to the act of having someone else take a test on one's behalf. Various writers have extensively documented impersonation, including (7,23). Impersonation in virtual proctored examinations is connected to wider concerns over the identity and ownership of the learner (11). Addressing impersonation might provide challenges. An important challenge faced by examiners is the verification of e-learning participant’s identities and the confirmation of their claimed completion of the assigned work (11). Resolving these issues can pose a particular challenge when a student procures a service to register on their behalf and complete the entire online course.

The Fraud Triangle Model Factor

Developed in the 1950s by criminologist Donald Cressey, the Fraud Triangle has long been regarded as a key model for comprehending the elements that lead to fraudulent behaviour (22). The Fraud Triangle is made up of three elements: opportunity, pressure, and rationalization (29). Every component is essential to the incidence of fraud, and research on these components in the context of modern financial and organizational systems is still ongoing.

Researchers have seen a rise in fraud cases, which they ascribe to the pandemic's negative economic effects (K. Smith et al., 2023). For example, a growing number of people are turning to fraudulent operations as a method of surviving due to employment insecurity and the necessity to fulfil financial responsibilities.

Recent empirical investigations highlight the changing characteristics of pressure. (32) did an extensive investigation into the effects of the COVID-19 pandemic on the occurrence of fraudulent activities. Their research reveals a significant surge in fraudulent actions, closely linked to heightened financial and emotional stressors caused by the pandemic. The survey also uncovers a significant increase in instances of fraud across the healthcare and retail sectors, which can be related to the increased pressures experienced in these businesses. A notable investigation conducted by (12) explores the impact of pressure on instances of corporate fraud in Asia. The study cites cultural and societal influences, such as the fear of damaging one's reputation and meeting family expectations, as powerful motivators of dishonest behaviour in this particular situation. The study highlights the necessity of implementing fraud prevention techniques that take into account cultural sensitivities. Improving transparency and promoting a positive business culture can help reduce the effects of external pressures (5).

The term "opportunity" refers to the conditions that make it possible for fraudulent activity to take place. Opportunity, in contrast to pressure and rationalization, is mostly determined by an organization's internal controls and processes. Vulnerabilities in these controls create an ideal environment for fraudulent activity. Fraudulent opportunities might occur due to insufficient division of responsibilities, lack of supervision, inadequate internal audits, and ineffective implementation of organizational policies (40). In addition, the digital era has brought forth new aspects to the concept of opportunities. The widespread adoption of digital transactions and online platforms has increased the opportunities for fraudulent activities. Cybersecurity flaws, such as weak passwords, insufficient encryption, and software that has not been updated with necessary fixes, create substantial opportunity for those engaging in fraudulent activities (21). Therefore, modern company must allocate resources to implement sophisticated security measures and ongoing surveillance in order to protect against digital fraud.  Weak internal controls, a lack of supervision, or intricate organizational structures that make identification challenging are frequently the causes of it. The transition to remote employment and technological improvements have opened up new fraud opportunities. For example, the fast digital change and the vulnerabilities it brought forth are to blame for the rise in cybercrime (49). This change has increased the likelihood of fraudulent activity by making it simpler for people to take advantage of security system flaws.

The mental process known as rationalization is what enables people to defend their dishonest behaviour. It entails coming up with defences or explanations for immoral actions. After 2020, the pandemic's psychological and societal effects have shaped people's rationalization strategies. People may use the economic slump or the need to safeguard their family's welfare as justifications for their behaviour (18). Furthermore, rationalization may be strengthened by the normality of immoral action in some business environments, which makes it simpler for people to perpetrate fraud without facing serious moral dilemmas.

Hypotheses development

This study argue that Pressure is a pivotal element that contributes to employees engaging in cheating in e-learning settings, and it is due to several factors. An employer's high-performance expectations are a significant source of pressure. Employees in ABC Company are required to consistently enhance their skills and knowledge in order to maintain competitiveness. This anticipation frequently accompanies stringent time limits and challenging tasks. When confronted with the simultaneous task of fulfilling work obligations and finishing e-learning courses, employees may utilize deceitful methods to manage the pressure and time limitations. Therefore, the following hypothesis is proposed:

H1: There is a positive relationship between pressures and employees' behavioural intention to engage in dishonest practices in e-learning.

The second element in the fraud triangle model is the opportunities (51). Prior empirical studies have demonstrated that the presence of an opportunity to engage in fraudulent activities without facing any consequences or the likelihood of being detected increases the propensity of fraudsters to commit fraud (29). The absence of monitoring and enforcement procedures in e-learning systems in ABC Company can create many chances for dishonest behaviour. In the context of this study, when employees are aware that their actions are not being thoroughly observed, they may feel empowered to engage in dishonest behaviour. For instance, in the absence of proctoring tools or other methods to monitor employee activity, they may perceive an opportunity to engage in dishonest conduct, such as exchanging answers, utilizing unauthorized resources, or enlisting someone else to complete their assessments, without facing consequences. Therefore, the following hypothesis is proposed:

H2: There is a positive relationship between opportunities and employees' behavioural intention to engage in dishonest practices in e-learning.

Rationalisation is the third element in the fraud triangle model. (33) provided a definition of rationalisation as the process of justifying or legitimising a manner or concept that contradicts one's own beliefs. The perpetrator of fraud will exhibit greater motivation to engage in dishonest activity whenever they are able to rationalise their misconduct (33). According to research conducted by (45), the existence of rationalisation has a substantial impact on the escalation of cheating during online exams. 

In Healthcare company, some employees may rationalise engaging in dishonest behaviour as a result of perceived pressure or unjust expectations imposed by their managers. Within a demanding work environment characterised by intense pressure, employees may justify the necessity of engaging in cheating as a means to fulfil the numerous demands of their heavy workloads and ongoing learning obligations. They could contend, "I am already overwhelmed with tasks; engaging in academic dishonesty on this examination is the sole means to efficiently handle my time." Another prevalent justification is the conviction that "everybody is engaging in the same behaviour." If employees observe their colleagues participating in dishonest behaviours without facing any repercussions, they may feel morally justified in adopting similar practices in order to achieve fairness. The social rationale for cheating can be particularly compelling in settings where there is lax oversight or lenient punishment for such behaviour. The cognitive reasoning behind this can be, "If my peers are engaging in dishonest practices and achieving success, why should I not do the same?" Therefore, the following hypothesis is proposed:

H3: There is a positive relationship between rationalization and employees' behavioural intention to engage in dishonest practices in e-learning

The research design of this study is methodically designed to examine the impact of pressures, opportunities, and rationalisation on employees' desire to engage in dishonest acts in e-learning environments. This section provides an overview of the selected study design, encompassing the research kind, the methodological approach, and the justification for these decisions. This study utilises a quantitative research methodology, which is suitable for analysing the connections between many variables and for evaluating hypotheses based on established theories (16). The quantitative method enables the gathering and examination of numerical data, which aids in the detection of patterns and the assessment of correlations between variables (41). This approach is well-suited for the study's objectives, which involve analysing the impact of certain elements (pressures, opportunities, rationalisation) on intentions to engage in dishonest behaviour and establishing the collective predictive ability of these aspects. Moreover, this study utilises a survey-based research Surveys are a highly efficient method of gathering data from a sizable sample, offering a comprehensive comprehension of the phenomena being studied (44). This method enables the effective collection of data on employees' perceptions and intentions regarding dishonest behaviours in e-learning.

Data Collection

Data was gathered through the utilization of a survey questionnaire, which was disseminated to the research participants via Google Forms. The selection of this online survey platform was based on its user-friendly interface, wide availability, and capability to produce individualized links for every participant (31). Google Forms streamlined the process of managing and analysing the gathered data. Furthermore, to contact the research participants, the authors used a research assistant to hand out the surveys and ensure they reached their intended audience. The distribution of the questionnaire involved generating a link using Google Forms and then sending it to participants through the WhatsApp application. The selection of this method was based on its extensive adoption and ease of use, ensuring a high rate of response (42). The study will apply multiple regression analysis to further examine the direct impact of pressures, opportunities, and rationalisation on employees' behavioural intention.

Descriptive Analysis

In this study, data was obtained from employees who work at ABC Company. Survey questionnaire was established using Google Form and distributed through WhatsApp application. The questionnaire was distributed on June 2024. There were 287 respondents completed the questionnaire and all the data were considered to be valid without missing data. The following below are the descriptive analysis in details.

The sample demonstrates a notable disparity in gender representation, with females comprising a substantial majority of 88% (253 out of 287 respondents), while males constitute a mere 12% (34 respondents). The age distribution shows a notable clustering in the 25-34 age group, which accounts for 53% of all respondents (152 out of 287). The age group of 35-44 years, comprising 38% (108 respondents), is the second largest demographic. The age cohorts of 18-24 years and 45-54 years represent 3% (11 respondents) and 6% (16 respondents), respectively. The high occurrence of individuals aged 25-34 and 35-44 suggests that the workforce is predominantly composed of individuals who are relatively youthful to middle-aged. Out of the total of 287 respondents, 64% or 185 individuals have a bachelor's degree as part of their educational background. Among the respondents, 32% (93 persons) have a diploma, whereas only 3% (9 individuals) hold a master's degree.

Data Analysis

This study investigates several variables to comprehend the aspects that impact employees' behavioural intentions to participate in cheating behaviours in e-learning settings. In conducting the multiple regression analysis, several key assumptions were verified to ensure the validity of the results. First, the assumption of linearity was confirmed by examining scatterplots, which showed a linear relationship between the independent and dependent variables. The assumption of independence was checked using the Durbin-Watson statistic, which indicated no significant autocorrelation in the residuals. Homoscedasticity was assessed through a plot of standardized residuals versus predicted values, confirming that the variance of the residuals was constant across all levels of the independent variables. Additionally, normality of the residuals was verified using a normal probability plot (P-P plot) and the Shapiro-Wilk test, both of which indicated that the residuals were approximately normally distributed. Multicollinearity was assessed using Variance Inflation Factors (VIF), with all VIF values being well below the threshold of 10, suggesting no significant multicollinearity among the predictors. Lastly, the questionnaire's scales and items had strong reliability, as indicated by Cronbach's alpha values surpassing the widely acknowledged criterion of 0.70 By meeting these assumptions, the multiple regression analysis is deemed robust and reliable for drawing conclusions from the data.

Table 1. Pearson Correlations

According to the Pearson Correlation table above, the study of variables shows that there are important connections between employees' intention to engage in dishonest behaviour in an e-learning scenario. The correlation coefficients between the variables offer valuable information about the intensity and orientation of these interactions. The association between gender and the intention to participate in dishonest conduct is negative and statistically significant (r = -0.142, p < 0.05), indicating that male individuals are slightly less intention to engage in dishonest behaviours compared to their female counterparts. Also, the study found a strong negative relationship (r = -0.250, p < 0.001) between having a vocational diploma and the desire to engage in dishonest behaviour. This suggests that those with vocational education are less likely to be involved in dishonest actions. In contrast, there is a strong and positive relationship between having a bachelor's degree and having intentions to engage in dishonest behaviour (r = 0.258, p < 0.001). This suggests that individuals with greater levels of education may be more likely to engage in dishonest activities in e-learning. The correlation between work experience and intentions to engage in dishonest behaviour yielded mixed results. Employees who have worked for less than one year show a weak positive relationship with intentions to engage in dishonest behaviour (r = 0.092), although this relationship is not statistically significant. 

Moreover, strong positive relationships are shown between the variables of pressure (r = 0.603, p < 0.001), opportunity (r = 0.635, p < 0.001), and rationalisation (r = 0.597, p < 0.001). The findings suggest that there is a substantial correlation between increased intents to engage in dishonest practices in e-learning program and higher levels of perceived pressure, more possibilities for dishonest behaviour, and a stronger ability to rationalise dishonest activities. The strong positive association between pressure and the propensity to participate in dishonest behaviours suggests that individuals who face higher levels of pressure in the workplace are more likely to consider or engage in unethical behaviours.

Table 2. Result of Hypotheses Testing

Pressure, Opportunities, and Rationalisation are identified as significant predictor variables, and they have a notable impact on the dependent variable. The variable "pressure" has a considerable positive impact, as indicated by its B coefficient of 0.311, standardised Beta of 0.294, t-value of 5.693, and highly significant p-value of 0.000. This indicates that there is a strong correlation between greater pressure and higher intention to conduct dishonest activities in e-learning. Similarly, the opportunities variable has a positive correlation with a B coefficient of 0.383, a Beta value of 0.350, a t-value of 6.743, and a significance level of 0.000. This suggests that higher perceived opportunities are likewise positively associated with higher intention to conduct dishonest activities in e-learning. The presence of rationalisation, as indicated by a B coefficient of 0.186, a Beta of 0.190, a t-value of 3.430, and a p-value of 0.001, provides additional evidence that rationalising factors have a significant relationship with higher intention to conduct dishonest activities in e-learning, although to a smaller degree than Pressure and Opportunities. Therefore, we can conclude that all of the hypotheses proposed in this study are supported.

This study set out to examine the factors influencing employees' behavioural intentions to engage in dishonest practices in e-learning environments, focusing on the elements of pressure, opportunity, and rationalization. The research findings support all three hypotheses proposed in this study:

• There is a positive relationship between pressures and employees' behavioural intention to engage in dishonest practices in e-learning.

• There is a positive relationship between opportunities and employees' behavioural intention to engage in dishonest practices in e-learning.

• There is a positive relationship between rationalization and employees' behavioural intention to engage in dishonest practices in e-learning.

These results underscore the complex interplay of factors contributing to academic dishonesty in corporate e-learning environments. The study highlights that addressing dishonest practices requires a multifaceted approach that considers psychological, environmental, and situational factors. Based on the findings, several key implications emerge for managers in Healthcare Company. First, pressure Management, Managers should reassess performance expectations and deadlines associated with e-learning programs. Implementing more realistic timelines and providing additional support may help alleviate pressure that could lead to dishonest practices. Second, opportunity reduction: the company should invest in robust technological solutions to minimize opportunities for cheating. This could include advanced proctoring software, randomized question banks, and time-limited assessments. Third, ethical culture development: company should focus on fostering a culture of integrity that discourages rationalization of dishonest behaviours. This could involve regular ethics training, clear communication of academic integrity policies, and consistent enforcement of consequences for violations. Lastly, continuous Monitoring and Adaptation: Regular assessment of the e-learning environment and employee feedback can help identify emerging risks and allow for timely interventions to maintain academic integrity.

This study contributes to the existing body of knowledge in several ways. First, the research extends the application of the Fraud Triangle Theory to the specific context of e-learning in corporate environments, demonstrating its relevance beyond traditional academic settings. By examining the simultaneous effects of pressure, opportunity, and rationalization, this study provides a more comprehensive understanding of the factors influencing dishonest behaviours in e-learning.

While this study offers valuable insights, several limitations should be acknowledged. First, the study focused on employees from a single company (ABC Company), which may limit the generalizability of the findings to other organizational contexts or industries. Second, the reliance on self-reported data may introduce potential biases, as participants might underreport their intentions to engage in dishonest practices due to social desirability concerns. Based on the findings and limitations of this study, several avenues for future research are proposed. Future research can conduct longitudinal research to examine how the influence of pressure, opportunity, and rationalization on dishonest behaviours may change over time and across different stages of employees' careers. Also, researcher can expand the study to include multiple companies across various industries to enhance the generalizability of the findings and identify potential industry-specific factors. Lastly, future research may develop and test specific interventions aimed at reducing pressure, minimizing opportunities, and addressing rationalization to determine their effectiveness in reducing dishonest practices in e-learning.

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