1. Introduction
The choice of a major course remains one of the critical decisions business students are confronted within their academic life at the university. Globally, business students mainly have the choice to specialize in a field of interest at a point in time in their academic journey. Although most academic institutes offer a wide variety of alternative career routes (i.e. marketing, finance, management, mostly traditional business disciplines) to their students, prior research work illustrates a continuous decrease in the number of students who pursue accounting as a career choice (Tang & Seng, 2016). The dramatic reduction in students majoring in accounting has been one of the dominant sources of worry for stakeholders in the accounting profession, usually because most of the countries (developed and developing) continue to experience scarcity in the supply of accounting professionals (Rita et al., 2018).
Wen et al. (2018) highlighted that a major cause of shortage in several countries is the difficulty in attracting students to pursue a major in accounting in their educational journey. Though, the career choice is usually believed to be a complex phenomenon that is difficult to comprehend and predict (Krajbich 2019). Young et al. (2018) claimed that the occupational choices of the students are largely associated with their major disciplined. Further, Wen et al. (2018) argued that although accounting professionals played a significant role in facilitating China’s economic transformation and development, accounting majors are not enthusiastic in China. Indeed, the challenge of satisfying the demands of accounting professionals throughout the world could worsen, if urgent steps are not taken to point out the main cause of students not taking accounting majors. In part, low salary, misinformation about workload, and students’ negative perception have been acknowledged to be a significant source of this problem (Suryani, 2018).
Most importantly, Baxter and Kavanagh (2012); Polvillo and Vazquez (2018) point out that usually young people develop their career choice based on inaccurate perceptions, preconceived ideas about careers, and their work environment. Besides, Baxter and Kavanagh (2012); Wen et al. (2018) highlight that students who are generally not attracted to the finance and accounting field consider it to be uninteresting, a major that requires substantial numerical skills, rule of memorizing, and career of boring people who are rarely extrovert and only work. Therefore, the stereotypical image of accounting has been recognized to be an important factor in the decrease in the number of students majoring in accounting.
The students’ choice of careers is likely to be affected by numerous factors, such as interpersonal, cultural, social, careers expectation, financial, family background, etc. In particular, prior studies investigated the several predictors that influence students’ decision regarding an accounting career choice have been conducted in the different cultural contest (Rita et al. 2018; Ticoi & Albu, 2018; Wen et al., 2018). However, existing literature called for studies regarding accounting knowledge and profession (Sandra, 2020), perceptions of students majoring in accounting and the expectations of employers towards skills and knowledge required by accounting students (Aryanti & Adhariani, 2020), to investigate factors influencing the employees’ satisfaction with accounting graduates (Nguyen et al., 2020), and a few of other studies (Le & Bui, 2020; Nguyen, 2020), proposed to assess the intention of universities students towards accounting major and stated that no empirical study has been dedicated from international (multiple countries) perspective in order to comprehend their subjective view about why they choose accounting careers or another nonaccounting career.
The empirical analysis in this study contributes to the existing literature in two ways. First, this research provides insights into the students’ major decision regarding an accounting career choice from an international perspective, unlike the prior studies aforementioned that usually focused on a single country, while this study includes international students (Cameroon, Canada, China, Ethiopia, Ghana, India, Ivorian, Jamaica, Kenya, Morocco, Malawi, Nigeria Pakistan, and many other). Thus, this study provides a comprehensive understanding of what factors influence them to an accounting career choice, against the backdrop that the predictors that impacts the choice of major decision believed to be contextual (Young et al., 2018), there is a need for the further exploration into career choice from multiple countries perspective, which has not received required attention. Second, given that students’ academic discipline has significant effects on their career choices, an understanding of the predictors that influence them or impede them to pursue a major in accounting is critical to stakeholders interested in addressing the skill-shortage of professional accountants in many countries.
The remaining part of the paper is organized as follows: the upcoming section we discuss the literature review which is separated into theoretical support and hypotheses development; the third section looks at the research methodology; the fourth section contains the analysis of the results; the fifth section includes the discussion and the conclusion of the study.
2. Literature Review
2.1. Theoretical Background
According to Agarwala (2008), choice means selecting one from the more which is preferred. Likewise, career choice includes choosing/selecting one occupation over others. Furthermore, there are two conditions of career choice. (1) Availability of other career options; and (2) an individual preference between such career alternatives.
The number of career alternatives available to individuals is affected by several factors (external and individual); external factors include the state of the economy, government regulation, labor market, etc. Whereas, individual factor includes attitude, self-confidence, competencies, family background, education, etc. Thus, career choice is not unbridled, rather, are often impeded by socio-cultural factors (Jamali, 2009), personal and cultural values, individual factors, and structural factors are constraints normally faced by women in choosing careers in India and the Middle East (Singh & Pattanaik, 2020; Afiouni, 2014). Most of the studies directed to career choice focused on intrinsic (interest in the job, personally satisfying work); extrinsic (availability of jobs, well-paying professions); and interpersonal (influence of family, peers, and significant others) motivational factors (Matthew et al., 2019; Auyeung & Sands, 1997; Wen et al., 2018)
Wen et al. (2018) for instance, investigated Chinese university students’ motivation to pursue an accounting major and found the compensation, varieties of professional experience, career advancement, challenging career, and less traveling to be significant predictors. Auyeung and Sands (1997) also examined that factors are motivating accounting career choice in Taiwanese and Hong Kong students and conclude that parents’, peers’, and teachers’ influence and association with others in the accounting field have greater effects on career choice among. Agarwala (2008) finds competencies, parents were the most important factor for students to choose an accounting career among Indian students. Ticoi and Albu (2018) found that intellectual motivation, relational and financial incentives as important factors for Romanian students to choose an accounting majors. Rita et al. (2018) used logistic regression on 457 Ghanaian students and found that intrinsic motivation, prior exposure, and desire to pursue professional accounting in the future are good determinants of students’ intention to major in accounting. Similarly, students’ confidence, self-interest, and extrinsic interest are positively associated with major selection decisions among Ghanaian students (Matthew et al., 2019).
The theory of reasoned action and theory of planned behavior has been largely used in prior studies (Tang & Seng, 2016; Rita et al., 2018) to examine the student’s career choice. The theory of reasoned action developed by Fishbein and Ajzen (1975) stated that an individual’s outcome is mainly led by intentions. Intentions represent significant factors that influence an outcome or desired behavior. Further, the stronger the extent of intention, the stronger will be the likelihood of an individual practicing the behavior (Ajzen 1991). According to the theory of reasoned action, intentions are determined by two significant factors (attitude and subjective norms). An attitude describes the disposition of an individual in evaluating a behavior (positive or negative). Further, it is normally defined by an individual’s belief about the results of performing the behavior. Subjective norm refers to the pressure from family, friends, and peers to whether to perform or not a particular behavior (Yuan et al., 2019). Ajzen and Fishbein (1988) extend the theory of reasoned action to the theory of planned behavior and argued that the outcome of an action is grounded on their intentions and Perceived Behavioral Control (PBC). It refers to one’s ability to control a particular, (Shneor & Munim, 2019) used the theory of planned behavior in crowdfunding rewards, and argued that rewards are within an individual’s control. Thus, based on the above theoretical support we construct the following model (refer to Figure 1)
Figure 1: Comceptual framework
2.2. Hypotheses Development
2.2.1. Financial Rewards (FR)
Socio-cultural and financial factors produce significant variation in students’ careers choice, like those in market economies, enabling money and power when deciding career choice (Agarwala, 2008). Low salary is one of the demotivating factors among Indonesian students to choose an accounting career (Suryani, 2018). Similarly, Omar et al. (2015) investigated undergraduate students and found that salary is the most important influencing factor for a student to pursue an accounting career. Most importantly, financial factors not only contribute to an individual’s decision to relocate but also contribute to the development of an intention to build an expatriate career (Presbitero & Quita, 2017). Recently, Wen et al. (2018) surveyed 163 undergraduate and graduate-level Chinese students and found that compensation is one of the dominant factors influencing students’ career choice. Based on the above literature, we proposed the following hypothesis:
H1. Financial factors have a significant influence on students’ accounting career choice.
2.2.2. Parents’ and Peers’ Influence Factors (PPIF)
Most of the Korean college students believe that career choice is based on family needs; they usually choose a career that satisfies their family, rather than themselves (Yang et al., 2002). Indeed, family pressure to gain a job to satisfy the basic needs of the family and meet the caring responsibility may influence students’ career decisions (Jackson & Wilton, 2017). Duffy et al. (2011) argued that the effect of external predictors is marginally investigated, usually for those who are employed and balance work and family. Agarwala (2008) argued that studies dedicated to investigating the role of peers, mentors, managers, and colleagues in a career choice are limited and found a significant relationship between family and career decision making. Recently, Rita et al. (2018) surveyed 457 University students and found that family members, peers, and course trainers play a key role in students’ decision to pursue an accounting career. Therefore, we proposed the following hypothesis
H2. Parents’ and peers’ influence factors have a significant influence on students accounting career choice.
2.2.3. Benefits and Cost Factors (BCE)
It is defined as an “analysis of the cost-effectiveness of different alternatives in order to see whether the benefits outweigh the costs”. A few of the research from an accounting perspective focused on the investigation of benefits and costs and considered it one of the dominant factors in developing a model of career choice (Chen et al., 2008; Felton et al., 1994). Felton et al. (1994) investigated the association between the university students of whether to select chartered accountant as a career, and the significance students attached to intrinsic rewards, prior exposure of accounting in high school. Further, they found that benefits and cost ratio was one of the dominant factors of career choice among university students. Chen et al. (2005) highlight that students already having accounting exposure played a key role in the process of choosing a major and found that the students having accounting exposure related to differential influence on the evaluation of benefits and cost. Thus, we proposed the following hypothesis
H3. Benefits and cost effect factor has a significant influence on students accounting career choice.
3. Methodology
3.1. Study Design, Population and Data Collection
This study used a quantitative and convenient random sampling approach. A closed-ended questionnaire was used to record the response; a questionnaire was divided into two main parts. The first part includes the demographical (gender, age, country, education, work experience, marital status) information as well as general questions asked related to their academic major, interest, what accounting is, and exposure of accounting in high school. The second part is subdivided into four sections (financial rewards (FR), parents and peers influence (PPIF) factors, benefits and cost (BCE) factors, and accounting career choice), each section directed to one variable.
This study used an online cross-sectional questionnaire for international students as participants of the study; due to the pandemic, it was not feasible to conduct a community survey (Shi et al., 2020). Past studies show that online questionnaire is one of the finest approaches of cutting-down the costs of a research study and in the parallel, it helps in getting authentic information from the online population (Demuyakor, 2020; Fricker. 2016). Further, online survey is generally used to accumulate more information and to reach a scattered population (Kuila et al., 2019). An online survey was conducted and shared via WeChat, WhatsApp, and other social media applications. Students were invited to respond to the questionnaire via an online link. The data was collected in a month during June-July, 2020. We sent one reminder every week to remind students to respond to the 20 minutes’ questionnaire. This study targeted to collect at least 400 responses, and 311 students responded to the questionnaire (see Table 1). This yields an 77.75% response rate, and scholars suggest that a study with 50% and above response rate is suitable to carry out further data analysis (Creswell & Poth, 2016; Babchuk, 2017).
Table 1: Descriptive statistics of respondents’ information (N = 311)
3.2. Measures of the Study
In order to measure the constructs, a well-established scale was used. The financial rewards were measured using five items adapted from (Sugahara et al., 2009; Omar et al., 2015). PPIF was assessed using five items adapted from (Myburgh, 2005; Agarwala, 2008). The BCE effect factor was assessed using three items adapted from (Sugahara & Boland, 2006; Chen et al., 2008). The accounting career choice was assessed using five items adapted from (Rottinghaus et al., 2005; Sugahara & Boland, 2006). All the items were rated on a five-point Likert scale (1= strongly disagree; 2= disagree; 3= neutral; 4= agree; and 5= strongly agree). The items adapted were modified as per the objective of the study.
3.3. Analytical Tool
This study collected data via an online survey, after screening out of invalid respondents analyzed by utilizing Partial Least Square Structural Equation Modeling (PLSSEM). Both the approaches, that is, the Confirmatory Factor Analysis (CFA) and the Structural Equation Modeling (SEM) were used to test the appropriated model. The approach of CFA was utilized to test convergent validity and reliability of the construct, in that, items having a value less than 0.5 were eliminated from the construct (Hair et al., 2019). PLS-SEM is used in several disciplines, for instance, social science (Hair et al., 2017; Ahmed et al., 2020), psychology (Willaby et al., 2015). The main reason behind the PLS-SEM includes the wide popularity and acceptability of its application (Hair et al., 2012; Li et al., 2020).
4. Results and Discussion
4.1. Descriptive Statistics
Table 1 demonstrates that out of the 311 respondents, 175 (56.3%) were male and 136 (43.7%) were female. Most of the respondents, that is, 194 (62.4%) respondents were aged between 25 and 33 years, and nearly half, that is, 155 (47.9%) respondents had a master’s degree. One-third of the respondents, that is, 104 (33.4%) respondents have 3 to 4 years’ experience. A vast majority of them, that is, 279 (89.7%) respondents were single. Nearly half, that is, 137 (44.1%) respondents had a major in other subjects other than accounting, and 125 (40.2%) respondents had shown interest in a business career. Furthermore, 182 (58.5%) respondents did not know about accounting, and 58.2%, that is, 181 respondents have been not exposed to accounting in high schools (refer to Table 1).
Before moving towards the analysis of the results, Kaiser-Meyer-Olkin (KMO) was used to check the adequacy of data. Table 2 reveals that the KMO test value was 0.944, which is greater than the acceptable threshold 0.50; therefore, the sampling data is considered suitable for the explanatory factor analysis (Chan et al., 2011). Besides, Bartlett’s test illustrated the level of significance to be 0.000, which is considered good as it is far below the 0.05 level of significance (refer to Table 2).
Table 2: KMO and Bartlett’s Test
4.2. Analysis of the Models
An analysis of the results involves several tests mainly related to reliability, validity, and path coefficients, and to ensure the data is free from multicollinearity and other data related bias (Tian et al., 2020). According to Li et al. (2020), the analysis section used a two-way approach to assess the results. (1) An assessment of the measurement model; and (2) the structural model.
4.2.1. Assessment of Measurement Model
Individual item reliability. Measured by the outer loadings of items related to particular constructs. According to Hair et al. (2017), the proposition should be greater than 0.7 (refer Table 3). The value of Cronbach’s alpha (CA) should be greater than 0.7 (Hair et al. 2017). As displayed in Table 3, the values of CA falls between 0.737 and 0.884; therefore, it is concluded that the present study adequately meets the standard of reliability of the measures (Min et al., 2020).
Table 3: Measurement model
Internal consistency reliability. Bagozzi and Yi (1988) recommended that the value of composite reliability (CR) should be equivalent to or greater than 0.7 (refer to Table 3).
Convergent validity. According to Fornell and Larcker (1981); Chin (1998), the proposition value of Average Variance Extraction (AVE), should be equivalent to 0.5 or above. The AVE of the present study falls between 0.646 and 0.685; hence, it is concluded that this study demonstrated a satisfactory level of convergent validity (refer to Table 3).
Discriminant validity. According to Fornell and Larcker (1981), the square root of AVE for each construct should exceed the inter-correlations of the construct with other model constructs (refer Table 4).
Table 4: Discriminant validity
Common method bias (CMB). The full collinearity approach was used to measure the common method bias. According to Tian et al. (2020), most importantly, in PLSSEM inner variance inflation factor, VIF is used to detect the evidence of CMB. The results revealed that CMB was not a concern since the VIFs were less than 3 (Hair et al., 2011) (refer Table 3).
4.2.2. Assessment of Structural Model
This article used PLS bootstrapping with 5000 bootstraps and 311 cases to describe the path coefficients, their significance, and variance explained (R2 ) (Henseler et al., 2009). Table 6 and Figure 1 demonstrate the comprehensive exhibition of evaluations of the structural model. The most common measure used to examine the validity of the structural equation model is the coefficient of determination. According to Cohen (1998), the value of R2 0.60, 0.33, and 0.19 respectively are set as a rule of thumb and these values are described as substantial, moderate, and weak. This study reveals that 70% variation in accounting career choice occurred due to (FR, PPIF, and BCF) (see Table 7).
Table 6: Path coefficient and hypotheses testing
Note: critical value * t-value > 1.96 (p-value < 0.05).
Figure 2: Structural equation modelling
Table 7: Strength of the model
Furthermore, in the structural equation model, the cross-validated redundancy measure Q2 values should be greater than zero for a specific reflective endogenous latent variable indicating the path model’s predictive relevance for a particular dependent construct. Moreover, as a relative measure of the predictive relevance, q2 values of 0.02, 0.15, and 0.35 respectively, indicate that an exogenous construct has a small, medium, or large predictive relevance for a certain endogenous construct (see Table 7). According to Hair et al. (2011), suggestion SRMR is used to assess the goodness of fit. SRMR is an absolute measure of fit: a value of zero indicates perfect fit and a value less than 0.08 is considered a good fit (Hu & Bentler, 1999) (see Table 7)
This cross-sectional survey-based study aimed to describe the influence of financial rewards (FR), parents’ and peers’ influence (PPIF), and benefits and cost (BCE) on international students’ accounting career choice. The outcomes of the study found interesting (refer Table 6) that all of the hypotheses supported based on the criterion (t-value>1.96, and p-value<0.05). FR was found to be associated with students accounting career choice (p=0.01); hence, H1 supported. These findings are consistent with Omar et al. (2015) who argue that the starting salary is a significant factor for university students to choose an accounting career. This study implies that FR (compensation, bonus, salary, and other economic motivators) are one of the dominant factors (β=0.479) and significantly influence students across the world to choose an accounting career.
PPIF factors were found significant (p=0.001); hence, H2 supported. This result implies that across the globe, parents and peers have a greater influence on students to choose accounting. Further, it reveals the family and peers are the second most important factor (β=0.216) of the study, who have a greater influence on students. These findings are consistent with Rita et al. (2018) who found that family members play a key role in motivating students’ intention to pursue a career in accounting. The BCE construct was also statistically significant (p=0.001), and a positive association was evidenced between the benefits and cost factor and accounting career choice; hence, H3 supported. These findings are consistent with Chen et al. (2005), who found that when students realize the benefits of pursuing accounting as a career are greater than the cost, they will prefer accounting.
5. Conclusion
In conclusion, this paper investigated the effect of FR, PPIF, and BCF on the intention of students to pursue a career in accounting. The outcomes of the study illustrate that students already having exposure to accounting in high school and having a major in accounting, desire to pursue a career in accounting. The findings further proposed that FR PPIF, and BCF are the key factors of students’ intention towards accounting as a career choice.
The study provides significant implications for universities and accounting education across the globe. Given that the epidemic situation across the globe has worsened the state of the economy and normal indicators are largely disturbed, in these scenarios, in the future, businesses’ demand for a professional accountant will increase as they are responsible for the evaluation of the investments and their impacts. Since in the future, demand for professional accountants will increase, universities have to offer and promote accounting as a major discipline. Furthermore, this study is not free from limitations. This study used convenient sampling and distributed the questionnaire online through WeChat and WhatsApp, which worked for only those students having Internet access and using these social media apps in their countries. This limits the potential respondents to record their responses.
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