To pursue a career in accounting or not: a study based on the Theory of Planned Behavior^*

Abstract

This study investigates the intention of 691 students graduating from Accounting courses at public universities in the state of Paraná to pursue a career in the area of accounting, based on the Theory of Planned Behavior. For the analysis, the sample was divided into ten mesoregions according to the criteria of the Paranaense Institute for Economic and Social Development (Ipardes). The data collected were treated using descriptive statistics and structural equations techniques. The research hypotheses were corroborated in most of the mesoregions and the main findings show that attitude, subjective norm, and perceived behavioral control variables affect the students' intention to pursue a career in the area of accounting. The samples for six mesoregions (1. Curitiba Metropolitan Area, 2. East Center, 4. North Central, 5. Northwest, 6. West, and 9. South Center), in which the three hypotheses were corroborated, represent the largest and most developed cities in Paraná. The results in the ten mesoregions studied explain an intention variance of between 27.84% and 64.31%. The findings of this research contribute to understanding the profiles of accounting graduates from public institutions in the state of Paraná, providing elements to support the managers of the institutions in analyzing and elaborating differentiated strategies in relation to course curricula and approaches, according to the particular region. In addition, regulatory agencies can use these findings as a basis for in-depth research on the variables that influence the intentions of future professionals and to develop policies that guide institutions in developing courses with more adequate and consistent content for the market.

Keywords:
Accounting career; Theory of Planned Behavior; behavioral intentions; mesoregions

Resumo

Este estudo investiga, sob o enfoque da Teoria do Comportamento Planejado, a intenção de 691 alunos concluintes dos cursos de Ciências Contábeis das universidades públicas do estado do Paraná em seguir carreira na área contábil. Para análise, a amostra foi seccionada em dez mesorregiões, seguindo o critério do Instituto Paranaense de Desenvolvimento Econômico e Social (Ipardes). Nos dados coletados foram aplicadas as técnicas de estatística descritiva e equações estruturais. As hipóteses de pesquisa foram corroboradas na maioria das mesorregiões e os principais achados evidenciam que as variáveis atitude, norma subjetiva e controle comportamental percebido afetam a intenção dos alunos em seguir uma carreira na área contábil. As amostras de seis mesorregiões (1. Metropolitana de Curitiba; 2. Centro-Oriental; 4. Norte-Central; 5. Noroeste; 6. Oeste; e 9. Centro-Sul), nas quais as três hipóteses foram corroboradas, representam as maiores e mais desenvolvidas cidades paranaenses. Os resultados nas 10 mesorregiões estudadas explicam a variância da intenção entre 27,84% a 64,31%. Os achados desta pesquisa contribuem para a compreensão dos perfis dos concluintes em contabilidade das instituições públicas do estado do Paraná, fornecendo elementos para subsidiar os gestores das instituições na análise e elaboração de estratégias diferenciadas em relação aos currículos e abordagens do curso conforme a região de atuação. Ainda neste sentido, os órgãos reguladores podem utilizar estes achados como base para pesquisas aprofundadas a respeito das variáveis que influenciam a intenção dos futuros profissionais e para elaborarem políticas que orientem as instituições no desenvolvimento de cursos com conteúdos mais adequados e consistentes para o mercado.

Palavras-chave:
carreira contábil; Teoria do Comportamento Planejado; intenção comportamental; mesorregiões

Introduction

In general, students graduating from university courses express different intentions and expectations in relation to their professional future. They exhibit a certain optimism regarding the future, in a situation permeated by doubt and insufficient knowledge about the challenges and specificities of possible careers (Perrone & Vickers, 2003).

The decision regarding which career to pursue, independent of the moment, is an individual competency based on commitment to a given educational or vocational direction (Osipow, Carney & Barak, 1976). Thus, career decisions can be understood as the individual’s ability to identify his/her interests within the profession, to establish his/her professional objectives, and to coherently elaborate a strategy (Teixeira & Gomes, 2005). Deciding on a career is not limited to choosing a specific area within the profession, but also implies the individual’s willingness and ability to implement his/her plans.

Along these lines, throughout the process of deciding which career to pursue, various factors influence the individual, and these can be intrinsic (for example, intellectual interests and job satisfaction), extrinsic (such as job availability and pay), and interpersonal (for example, the influence of other people such as parents, friends, and partners) (Carpenter & Foster, 1977). In addition, from the understanding of Super and Bohn (1980), the causes influencing individuals’ choices are known as career determinants, and include geographical factors understood as the community, the school attended, family, peers, the economy, society, the job market, the social policy that interacts with and affects professional activities, and biological (including psychological) factors that affect development and relate to needs, intelligence, values, attitudes, interests, and special aptitudes, which together represent the individual’s personality and accomplishments. For Emmerling and Cherniss (2003), careers should not be chosen from an isolated viewpoint, but by combining a series of decisions. These decisions can involve questions such as: What activities are interesting? What are your aspirational levels? How will the interrelations between personal and professional life and emotional influences be processed, among others?

In light of these questions, understanding the dynamic involved in the choice or intention to pursue a career and its due commitment, both from an individual and collective view point, is of great importance for developing and consolidating the profession. A profession will only achieve its objectives and its social affirmation if the members that constitute it show dedication and establish bonds, pathways, and objectives, as well as striving towards professional growth (Carvalho, 2007). Accounting professionals, the target population of this study, also form part of this reality.

It is known that for Accounting graduates there are ample career opportunities, especially those that specify an exclusive niche for professional practice, due to the regulations for the profession and their corporate bias. These opportunities include the careers of accountant, auditor, accounts inspector, controller etc. However, although professional practice in the area involves a market protected by laws and regulations, it is an illusion to think that all students embarking on or graduating from the course want to build a professional career in this area. Thus, the findings of this study can support discussions regarding the desired profile of new students and/or changes in course programs, so that graduates can compete with students and graduates from other areas in professional activities that requires accounting knowledge, instead of only focusing on the career of accountant. Moreover, studies of this type have the potential to place Brazil within the international discussion regarding the profile of accounting professionals, their stereotypes, and intentions, thus contributing towards widening the range of studies on the subject.

In light of this context, the aim of this research is to investigate the intention of students graduating from Accounting courses at public higher education institutions (HEIs) in the state of Paraná to pursue a professional career in the area of accounting. In order to achieve this objective, the precepts of the Theory of Planned Behavior will be applied.

Theoretical-empirical framework and research hypotheses

2.1 Concepts of Profession and Career

The terms “profession” and “career” are, in general, used as if they were synonyms; when they are not used as synonyms, the conceptual confusion regarding their understanding is common. Carvalho (2007, p. 23) argues that “career is characterized from an organizational and work viewpoint, presenting conceptual similarities and differences in relation to concepts such as profession and occupation”. However, the understanding and characterization of profession and career need to be preceded by an understanding of occupation and vocation. Both form some sort of mastery and amount to the set of knowledge and abilities related to the production of a good or the providing of a service.

For Wilensky (1970), a person’s mastery of a particular area of knowledge is one of the determining factors in differentiating a profession from an occupation. The author argues (1970, p. 494) that “the knowledge base or doctrine for a profession is the result of a combination of practical and intellectual knowledge, part of which is explicit, part implicit”. Thus, “professional knowledge, just like all knowledge, is something that is relatively tacit, giving the established professions their ‘air of mystery’” (Wilensky, 1970, p. 494).

Along these lines, the understanding and characterization of what a profession is for Kast and Rosenzweig (1970) leads to some criteria being considered, such as: (i) the existence of a systematic body of (intellectual and practical) knowledge; (ii) a degree of authority granted by “clients” because of specialized technical knowledge; (iii) widespread social recognition as the basis for exercising authority; (iv) an ethical code that regulates the relationships between peers and between the professionals and their clients; and (v) the professional culture maintained by organizations.

In this context, a profession has the power of creating, transmitting, and organizing its own knowledge and thus the people that seek to achieve a particular professional status should undergo good training, guided by a standardized curriculum (Wilensky, 1970). Therefore, the institutional establishment of knowledge in a particular area is an essential requirement for configuring a profession, in that it constitutes the basis for claiming exclusive jurisdiction over a particular ability.

In relation to the term “career”, based on the compilation of various dictionaries the researchers Arthur and Lawrence (1984, p. 1-2) developed a structure formed of four basic points to support its definition: (i) people find themselves consistently engaged in an occupational activity that results in personal consequences for them, such as significant experiences, progress, and development; (ii) these activities present a particular meaning for the individual’s life, something related to the notion of an expressed identity, for example in sentences such as: “I am what I do”; (iii) the term can be applied to any person that works and to any succession of roles performed by the individual, [and there is a component of] social evaluation suggesting that individuals’ careers are subject to measures of success by society; and (iv) the term implies a dynamic and prospectively developmentalist relationship between the individual and organizations, incorporating a temporal dimension.

Faced with the ambiguous interpretations of the concept of career, Adamson, Doherty, and Viney (1998) argue that it cannot be considered as a theoretical construct. For the authors, the interpretation of what career is undergoes alterations according to its respective social context. In everyday life, when individuals comment on their careers, they tend to perceive it as their job itself. The idea of “career” for them refers to what they do, who they work for, and what they describe in their professional resumes.

The position of Adamson, Doherty, and Viney (1998) is aligned with that of Super (1957, 1980), and Van Maane and Schein (1979), for whom the concept of career originally corresponded to the positions reached within an organizational hierarchy. However, influenced by organizational and technological changes, this understanding has undergone reformulations and currently covers professional trajectory as well as other roles carried out by the individual during his/her life. In this modern conception, “career” can be interpreted as the combination of roles carried out by the individual over the course of his/her professional trajectory and is not restricted to the specific set of tasks of a work post, but rather involves different jobs over a long-term perspective (Chanlat, 1995).

These understandings are related to the two models generally found in the literature and explained by Chanlat (1995): the traditional one and the modern one. The former is characterized by stability, progress, and the sexual and social division of work (only men worked), with a linear and vertical progression. The second model, suggested in the 1970s, is the result of the socioeconomic changes that occurred in the previous years, such as women joining the workplace, the increase in individuals’ educational level, the cosmopolitization of society, the globalization of economy, and the flexibilization of work. In the modern model, there are opportunities for both male and female workers and for those belonging to various social groups; career progression is discontinuous and there is greater instability (Chanlat, 1995).

Covered in the traditional and modern models, Chanlat (1995) also defines four types of career: (i) bureaucratic, characterized by the ordered division of work; (ii) entrepreneurial, with independent activities developed by an individual; (iii) sociopolitical, understood by social abilities; and (iv) professional, characterized by the individual that has some specific knowledge. And it is based on this type of career that this study is built.

2.2. Influences on the Choice of Profession and Career

Regarding career choice, it is noted that individuals take into consideration various intrinsic and extrinsic aspects. The choice is directly related with the level of knowledge that the individual has of his/herself, the world of work, and especially, his/her personal and professional motives. The decisions in this process involve personal aspects related to the level of aspiration, the importance of each individual’s values, and his/her interests in the activities (Emmerling & Cherniss, 2003).

In relation to the factors that can affect the individual’s decision, Soares (2002) highlights six, namely: (i) political, (ii) economic, (iii) psychological, (iv) social, (v) family-related, and (vi) educational. The first ones refer to government and political actions related to education. The economic factors concern the job market, the level of employment, computerization, and the competencies of the profession, among others. As for the psychological factors, these are intrinsic to the individual, while the social ones relate to the division of society into social classes, the person’s influence in the family context, and the search for social ascension via study. The family-related factor corresponds to the process of seeking to achieve family plans instead of personal ones, as well as their influence on the decisions and construction of different professional roles. Finally, the educational factors belong to the spheres of public and private teaching and issues regarding the educational system (Carvalho, 2007).

These influences extend to all existing areas of activity and in accounting it is no different. For example, the stereotypes related to the profession and its actors has a significant weight on individuals’ decisions throughout the process. In this context, the students’ or future professionals’ choice of the profession and one of the careers within the area of accounting is strongly influenced by the stereotyped perception, especially the “figure” of accountant.

Regarding the stereotypes of the accounting profession, Carnegie and Naiper (2009) argue that there are two types: the stereotype of the traditional accountant or beancounter, and that of the business professional or colorful accountant. This refers to a business professional, a creative and proactive manager, and it emerged to combat the traditional negative stereotype of the beancounter, with the aim of arousing interest and respect for the accounting profession. Yet, Carnegie and Naiper (2009) highlight that this attempt to establish a positive image of the accountant has undergone various criticisms, as it is considered to be something that is impossible for the accounting profession.

Besides the stereotypes, there is a range of factors that are considered influential in choosing the accounting profession/career, such as the lack of information and sometimes the disinformation regarding relevant points about the profession, such as: what really makes a professional from this area or what are the career alternatives, the degree course curriculum as well as access to it, the culture, the financial reward; the job security, market considerations, prestige, work experiences, and family history, among others.

2.3 Theory of Planned Behavior

The Theory of Planned Behavior (TPB) proposed by Ajzen (1991) has been widely published. It results from the evolution of the Theory of Rational Action (TRA), which posits that behavior is a function of intention and this is conditioned by attitudes regarding specific actions and subjective norms (Fishbein & Ajzen, 1975). TRA is based on individuals’ rational use of available information in the behavioral decision-making process, and that this plays the role of mediator in the relationships between Attitude, Subjective Norms, and Behavior.

With the spread of research concerning behavioral intention - and, consequently, behavior -, it was found that TRA was limited to acknowledging people’s willingness and did not consider the resources for carrying it out. As a result of this limitation, Ajzen (1991) elaborated TPB by adding the Behavioral Control variable to TRA, perceived as the objective of capturing the intensity with which the individual believes he/she has the ability to assume a particular behavior and his/her beliefs regarding the existence of factors that can enable this or make it more difficult.

According to TPB, the first conditioner of someone’s intention is the attitude characterized as “an individual’s positive or negative feelings regarding a particular behavior” (Fishbein & Ajzen, 1975, p. 216). Thus, the individual’s attitude in relation to a behavior depends on his/her beliefs and behavioral evaluations; that is, on what the person believes will happen as a result of the behavior and on evaluating these consequences.

In light of the above, it is noted that in this investigation the Attitude construct is applied to predict the Intention of the student graduating from the Accounting course to pursue a career in the area of accounting. Thus, the premise is that the attitudes regarding a career are determined by the student’s belief that it will lead to a particular result. In light of this and understanding that intrinsic and extrinsic factors form graduating students’ attitudes, we suggest the following:

• H ₁  Attitude positively influences the behavioral intention of graduating students to pursue a career in the area of accounting
• H ₂  The subjective norm positively influences the intention of graduating students to pursue a career in the area of accounting
• H ₃  Perceived Behavioral Control positively influences the intention of graduating students to pursue a career in the area of accounting

3. Methodology

The population of this investigation is formed of 1,022 students of degree courses in Accounting, duly matriculated and considered as graduating in 2015, at public universities in the state of Paraná. The final, non-probabilistic, and intentional sample resulted in 691 valid respondents (709 questionnaires were gathered and 18 of them discarded because they presented incomplete data) distributed as according to Table 1.

Table 1
Population and Sample

Mesoregion	Institution	City	Population	Sample
Curitiba Metropolitan Area	Federal University of Paraná - UFPR	Curitiba	109	71
	Federal Institute for Education, Sciences, and Technology of Paraná - IFPR	Curitiba	34	34
	State University of Paraná - Unespar	Paranaguá	23	17
East Center	State University of Ponta Grossa - UEPG	Ponta Grossa	64	42
Pioneer North	State University of North Paraná - UENP	Cornélio Procópio	69	45
North Central	State University of Londrina - UEL	Londrina	85	67
	State University of Maringá - UEM	Maringá	166	46
	State University of Paraná - Unespar	Apucarana	56	52
Northwest	State University of Maringá - UEM	Cianorte	50	20
State University of Paraná- Unespar	Paranavaí	65	58
West	State University of West Paraná - Unioeste	Cascavel	25	13
	State University of West Paraná - Unioeste	Foz do Iguaçu	23	12
	State University of West Paraná - Unioeste	Marechal Cândido Rondon	31	31
West Center	State University of Paraná - Unespar	Campo Mourão	43	43
Southwest	State University of the Center West - Unicentro	Chopinzinho	31	26
	Federal Technological University of Paraná - UTFPR	Pato Branco	24	23
South Center	Federal Institute for Education, Science, and Technology of Paraná - IFPR	Palmas	21	13
State University of the Center West - Unicentro	Guarapuava	44	31
Southeast	State University of Ponta Grossa - UEPG	São Mateus do Sul	24	17
	State University of the Center West - Unicentro	Irati	19	17
	State University of the Center West - Unicentro	Prudentópolis	16	13

• Source: Data from the research (2016).

In order to analyze the data collected, the final sample was divided by the geographical mesoregions in which the public state higher education institutions are located (Table 1). The division by mesoregion followed the criterion adopted by the Paranaense Institute for Economic and Social Development (Ipardes), which subdivides the state - composed of 399 municipalities - into ten geographical regions: 1) Curitiba Metropolitan Area, 2) East Center, 3) Pioneer North, 4) North Central, 5) Northwest, 6) West, 7) West Center, 8) Southwest, 9) South Center, and 10) Southeast.

Table 2
Territorial areas, inhabitants, and economy of the Paraná mesoregions

Mesoregion	Territorial area	Number of inhabitants*	Dominant economy
Curitiba Metropolitan Area	23,147,132 km2	3,794,174	Industry, Commerce, and Agriculture, with production of corn, potato, wheat, and cattle and sheep rearing.
East Center	21,812,024 km2	739,907	Agriculture, with production of soy, corn, beans, and cattle, horse, chicken, sheep, and pig rearing.
Pioneer North	15,718,917 km2	563,980	Agriculture, with production of soy, corn, sugarcane, and cattle, horse, chicken, sheep, and pig rearing.
North Central	24,553,976 km2	2,192,285	Agriculture, with production of soy, corn, sugarcane, and cattle, horse, chicken, sheep, and pig rearing.
Northwest	24,750,384 km2	716,740	Agriculture, with production of sugarcane, cassava, soy, and cattle, horse, chicken, sheep, and pig rearing.
West	22,864,702 km2	1,294,417	Agriculture, with production of soy, corn, wheat, and cattle, horse, chicken, sheep, and pig rearing.
West Center	11,937,564 km2	340,320	Agriculture, with production of soy, corn, sugarcane, and cattle, horse, chicken, sheep, and pig rearing.
Southwest	11,546,792 km2	524,137	Agriculture, with production of soy, corn, beans, and cattle, horse, chicken, sheep, and pig rearing.
South Center	21,093,588 km2	471,339	Agriculture, with production of soy, corn, beans, and cattle, horse, chicken, sheep, and pig rearing.
Southeast	22,356,121 km2	525,719	Agriculture, with production of soy, tobacco, corn, and cattle, horse, chicken, sheep, and pig rearing.

• Note: * Population Estimated (inhabitants) by the Brazilian Institute for Geography and Statistics (IBGE) in 2015.
• Source: Elaborated based on the data from Ipardes (2015).

The mesoregions are subdivisions of the state that group various municipalities with economic and social similarities, as shown in Table 2. Given the data presented in the table, the students’ intentions were analyzed considering the economic and social influences of the region, the opportunities for joining the market, and the real possibilities of pursuing a career in the area of interest. Analyzing the mesoregions in terms of location and territorial extension, the largest is the Northwest, with an area of 24,750,384 km², while the smallest is the Southeast, with an area of 11,546,792 km². The Curitiba Metropolitan Area mesoregion is the most populated, with 3,794,174 inhabitants in 2015, according to the estimate from the Brazilian Institute for Geography and Statistics (IBGE).

3.1. Research Instrument

The applied research instrument is constructed from two blocks based on some studies, as Table 3 shows.

Table 3
Research Instrument

Block	Constructs	Indicators	References
I	Attitude	8	Gul et al., 1989; Ahmed, Alam, and Alam, 1997; Byrne and Willis, 2005; Tan and Laswad, 2006, 2009; Mbawuni and Nimako, 2015
	Subjective Norm	7	Paolillo and Estes, 1982; Tan and Laswad, 2006, 2009; Byrne, Willis, and Burke, 2012; Mbawuni and Nimako, 2015
	Perceived Behav. Control	6	Sugahara and Boland, 2006; Karakaya, Quigley, and Bingham, 2011; Mbawuni and Nimako, 2015
	Intention	4	Ajzen, 1991; Azevedo and Sugahara, 2012; Mbawuni and Nimako, 2015
II	General Profile	15	Own elaboration

• Source: Data from the research (2016).

A Likert-type 7 point scale was used (I Totally Disagree to I Totally Agree). It bears mentioning that the indicators were presented randomly, and three of them were portrayed on a reverse scale to test the respondents’ attention.

To collect the data, the research instrument was given in person by the author at some institutions and by the course coordinators and professors at others to students graduating between October 23^rd and November 25^th of 2015. It should be noted that before the collection two pre-tests of the instrument were carried out: (i) with three professors and ten stricto sensu post-graduates in Accounting at a public university in the state of Paraná, in order to align the content, wording, and presentational layout of the questionnaire; and (ii) with 63 students graduating from the Accounting course at two private HEIs in the city of Curitiba. This contributed to improving the test and its final configuration.

For the data treatment, the descriptive statistics and Structural Equations Modeling techniques were used, with the help of the Statistical Package for the Social Sciences - SPSS version 22 and the SmartPLS3.0® software programs. When applying the Structural Equations Modeling technique, some recommendations were considered regarding the size of the sample. The sample was divided into mesoregion and resulted in one region with the smallest number of respondents (n = 42). However, according to Hair Jr., Hult, Ringle, and Sarstedt (2014, p. 21), for a model with 8 structural pathways, considering a 10% level of significance and a minimum R² of 0.50, the size of the sample should be 38 elements, therefore the criteria was totally met.

4. Results and Discussion

4.1. Profile of Respondents

Table 4 presents the demographic data concerning of the respondents.

Table 4
Data for Respondents

Data		MESOREGION
		1	2	3	4	5	6	7	8	9	10
Gender	Female	71	20	18	98	42	32	26	32	24	33
	Male	51	22	27	67	36	24	17	17	20	14
	Total	122	42	45	165	78	56	43	49	44	47
Age group	From 1961 to 1970	-	2	-	1	1	-	1	-	-	1
	From 1971 to 1980	10	1	2	5	2	-	2	1	5	1
	From 1981 to 1990	50	9	14	51	14	18	18	16	13	21
	From 1991 to 1995	62	30	29	108	61	38	22	32	26	24
	Total	122	42	45	165	78	56	43	49	44	47
Maritial status	Single	85	32	37	135	66	45	29	41	28	33
	Married	33	10	7	29	11	11	13	8	16	13
	Divorced	4	-	1	1	1	-	1	-	-	1
	Total	122	42	45	165	78	56	43	49	44	47
Course satisfaction	Totally unsatisfied	2	1	-	1	1	-	1	1	-	-
	Unsatisfied	8	6	3	8	2	2	3	1	2	3
	Neither unsatisfied nor satisfied	31	16	15	48	19	11	7	15	6	7
	Satisfied	76	23	22	98	48	36	29	29	35	35
	Totally satisfied	5	-	1	10	8	7	3	3	1	2
	Total	122	42	45	165	78	56	43	49	44	47
Family Income	Up to 3 minimum wages	19	8	14	30	19	16	15	16	8	21
	Up to 4 minimum wages	20	8	10	34	21	9	8	6	16	11
	Up to 5 minimum wages	15	8	5	23	8	10	3	7	7	7
	Up to 6 minimum wages	16	8	5	28	15	7	7	1	5	6
	More than 6 minimum wages	52	10	11	50	15	14	10	19	8	2
	Total	122	42	45	165	78	56	43	49	44	47

• Note: 1. Curitiba Metropolitan Area; 2. East Center; 3. Pioneer North; 4. North Central; 5. Northwest; 6. West; 7. West Center; 8. Southeast; 9. South Center; 10. Southeast.
• Source: Elaborated by the authors.

By observing the data in Table 4, it was found that the respondents presented the following profile: 396 of them are female and 295 are male. Most questioned were between 20 and 24 on the date the data was gathered. Regarding marital status, it is noted that 531 answered that they were single: that is, 76.75% of the sample.

The 691 respondents were also questioned regarding their satisfaction with the Accounting course and it was observed that 431 claimed to be satisfied, while 175 said they were neither satisfied nor dissatisfied. Finally, 7 of them claimed to be totally dissatisfied. In addition, the students were asked whether the Accounting course was their first degree, and it was found that 587 of them were taking it as their first degree; for 88 students, the course was their second degree, and one of them was completing their third degree (having previously studied Geography and Mathematics).

In relation to the students’ family income, it was shown that in five mesoregions the predominant income is up to 3 minimum wages; in two mesoregions it is up to 4 minimum wages. In mesoregions 1, 2, and 4, the preponderant family income is more than 6 minimum wages, which may be explained by the fact that mesoregions 1 and 4 in particular include the most economically developed cities in the state, such as Curitiba and region, and Londrina and Maringá, respectively (Ipardes, 2015).

The students were also questioned regarding their professional life, whether they are currently working, and if they are, whether this is in the accounting area or not. Of the total respondents, 48 were not working, 364 of them had positions in the accounting area, and 278 carried out roles belonging to other areas of knowledge.

4.2. Evaluation of the Measurement Model

In order to evaluate the measurement model, the convergent validity, discriminant validity, and internal consistency criteria were observed for reflexive indicators. When these tests were first applied, the need to exclude some indicators was verified and those that met all of the criteria were left, as shown in the summary presented in Table 5:

Table 5
Summary of the indicators

Mesoregion	Attitude	Subjective Norm	Perceived Behavioral Control	Intention
Curitiba Metropolitan Area	1, 2, 3, 8	4, 5, 6	1, 2, 4	1, 2 , 3, 4
East Center	1, 2, 6, 8	2, 3, 4, 6, 7	1, 2, 4, 5	1, 2, 3, 4
Pioneer North	1, 2, 3	1, 2, 4, 6	1, 3, 4, 6	1, 2, 4
North Central	1, 2, 3, 8	3, 4, 5, 6	1, 2, 4, 5	1, 2, 3, 4
Northwest	2, 3, 8	4, 5, 6	1, 4, 5	1, 2, 3, 4
West	2, 3, 8	3, 4, 5, 6	1, 2, 4	1, 2, 3, 4
West Center	2, 3, 4	1, 3, 7	1, 2, 4, 5	1, 2, 3, 4
Southwest	1, 2, 3, 8	2, 4, 6	1, 2, 4, 5	1, 2, 3, 4
South Center	1, 2, 3, 8	2, 5, 6	1, 2, 4	1, 2, 4
Southeast	1, 2, 8	1, 3, 4, 5, 6	1, 2, 4, 6	1, 2, 3, 4

• Note: Data from the research (2016).
• Source: Elaborated by the authors.

As detailed, all of the constructs had indicator exclusions, the majority in Attitude (ATT), Subjective Norm (SN), and Perceived Behavioral Control (PBC). It is noted that for the Intention construct, the only excluded variable was “Inten3”, which corresponds to the option I intend to get a good job in the area of accounting after concluding the course, in the Pioneer North and South-Center mesoregions. These findings suggest that in these regions seeking work in the area of accounting is not a priority for the graduates, which is possibly explained by the lack of options in the market.

For the ATT construct, it is perceived that indicators 5 (I think that the work in accounting area careers does not provide significant results - pay, benefits) and 7 (I think that the work in accounting area careers requires aptitude - vocation) were not validated in any of the regions. One possible reason for this fact is that indicator 5 was elaborated inversely, with the aim of testing the students’ attention. As for “Att7”, it seeks to infer that the students understand that to be an accounting professional there is no need of aptitude.

For the SN construct, all the indicators were validated in at least one of the regions. It is observed that the relevant professionals from the area, as well as friends, partners, relatives, teacher(s), and parents, did not influence the respondents in all of the mesoregions in the same way, since some were significant in some regions and not so in others.

Regarding the PBC construct, the validation in all of the mesoregions of indicators 1 and 4 (I have the sufficient education/preparation to pursue a career in the area of accounting and I have a strong belief in my accounting knowledge in order to pursue a career in the area of accounting) is accentuated. The indicators validated in the fewest regions were 6 and 3 (I am not confident in my ability to carry out the work in an accounting area career and I believe that my knowledge in accounting is not sufficient to pursue one of the careers), observed in two regions and one mesoregion. It bears mentioning that these last two indicators may have been compromised since they were presented inversely to the respondents in order to test their attention.

After the exclusion of the indicators reported, the convergent validity, internal consistency, and discriminant validity indices were analyzed with the aim of evaluating the reliability and validity of the measures. The convergent validity evaluation was carried out using the average variance extracted (AVE) and the values of each latent variable were greater than the threshold value of 0.50 (Hair Jr. et al., 2014).

Table 6
Measurement criteria

1. Curitiba Metropolitan Area					2. East Center
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
AVE	0.6423	0.7681	0.8192	0.6358	AVE	0.5990	0.6833	0.8532	0.5143
CR	0.8774	0.9085	0.9476	0.8375	CR	0.8557	0.8955	0.9587	0.8386
CA	0.8167	0.8497	0.9255	0.7186	CA	0.7766	0.854	0.9423	0.7742
3. Pioneer North					4. North Central
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
AVE	0.6068	0.6763	0.8055	0.5887	AVE	0.6663	0.7312	0.8465	0.5291
CR	0.8127	0.8928	0.9254	0.8500	CR	0.8887	0.9157	0.9566	0.8155
CA	0.7834	0.8389	0.8796	0.7662	CA	0.8345	0.8773	0.9393	0.7166
5. Northwest					6. West
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
AVE	0.6581	0.7397	0.8944	0.6573	AVE	0.7775	0.7323	0.7952	0.7377
CR	0.8521	0.8948	0.9713	0.8516	CR	0.9128	0.8912	0.9391	0.9183
CA	0.7714	0.8289	0.9607	0.7422	CA	0.8556	0.8216	0.9133	0.8827
7. West Center					8. Southwest
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
AVE	0.6860	0.7320	0.8194	0.4911	AVE	0.6304	0.6322	0.8427	0.6194
CR	0.8647	0.9161	0.9475	0.7007	CR	0.8716	0.8724	0.9553	0.829
CA	0.7903	0.8799	0.9248	0.7398	CA	0.8098	0.8101	0.9371	0.7112
9. South Center					10. Southeast
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
AVE	0.6168	0.6631	0.8702	0.506	AVE	0.7540	0.6792	0.7074	0.596
CR	0.8642	0.855	0.9526	0.7235	CR	0.9019	0.8941	0.9052	0.8785
CA	0.7998	0.7493	0.926	0.7048	CA	0.837	0.8436	0.8599	0.8548

• Note AVE: Average Variance Extracted; CR: Composite Reliability; AC: Cronbach’s Alpha. ATT: Attitude; PBC: Perceived Behavioral Control; INTEN: Intention; SN: Subjective Norm.
• Source: Elaborated by the Authors.

The convergent validity evaluation was based on the AVE and the results reveal that the only construct that did not meet the recommended values (AVE > 0.5) was Subjective Norm in the West Center mesoregion. However, this construct only had 3 indicators, which made the removal of any other to try to increase this criterion unviable. Nonetheless, the evaluation of the model proceeded, given that all of the other evaluation criteria for the model were met.

The Composite Reliability (CR) analysis, whose index should be equal to or greater than 0.7, as well as the Cronbach’s Alpha (CA), which plays the role of evaluating whether the indicator has adequately measured the constructs (Hair Jr. et al., 2014), was validated for all of the constructs in all of the mesoregions.

The discriminant validity (DV), a measure that evaluates whether only one construct is capturing a particular phenomenon and that this is not represented by other constructs of the model (Hair Jr. et al., 2014), was analyzed using the Fornell and Larcker (1981) criterion. This criterion is measured by comparing the square root of the AVE with the correlations of the latent variables. The square root of the AVE of each construct should be higher than its greatest correlation with another construct, and if this criterion is not met, the indicator for a specific construct can be removed in an attempt to fulfill what is recommended (Hair Jr. et al., 2014).

Table 7
Discriminant validity -Fornell and Larcker Criterion (1981)

1. Curitiba Metropolitan Area					2. East Center
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
ATT	0.8014				ATT	0.774
PBC	0.4548	0.8764			PBC	0.7352	0.8266
INTEN	0.6272	0.5831	0.9051		INTEN	0.7192	0.7205	0.9237
SN	0.3543	0.2566	0.442	0.7974	SN	0.5723	0.5087	0.4662	0.7171
3. Pioneer North					4. North Central
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
ATT	0.779				ATT	0.8163
PBC	0.0617	0.8224			PBC	0.4583	0.8551
INTEN	0.0337	0.5734	0.8975		INTEN	0.4282	0.6883	0.9201
SN	0.3456	0.1331	0.1156	0.7673	SN	0.1702	0.2798	0.4223	0.7274
5.Northwest					6. West
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
ATT	0.8112				ATT	0.8818
PBC	0.5534	0.8601			PBC	0.6102	0.8557
INTEN	0.6383	0.7	0.9457		INTEN	0.717	0.6863	0.8917
SN	0.3496	0.3706	0.5092	0.8107	SN	0.3581	0.3475	0.4685	0.8589
7. West Center					8. Southwest
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
ATT	0.8283				ATT	0.794
PBC	0.1303	0.8556			PBC	0.5284	0.7951
INTEN	0.3665	0.3169	0.9052		INTEN	0.6671	0.6313	0.9180
SN	0.0028	-0.0599	-0.2803	0.6333	SN	0.5108	0.4298	0.4221	0.7870
9. South Center					10. Southeast
	ATT	PBC	INTEN	SN		ATT	PBC	INTEN	SN
ATT	0.7854				ATT	0.8683
PBC	0.4863	0.8143			PBC	0.4713	0.8241
INTEN	0.4032	0.6959	0.9328		INTEN	0.6055	0.6729	0.8411
SN	0.1521	0.4417	0.4238	0.7043	SN	0.2688	0.3472	0.2217	0.7720

• Note: ATT: Attitude; PBC: Perceived Behavioral Control; INTEN: Intention; SN: Subjective Norm.
• Source: Data from the research (2016).

According to Table 7, the discriminant validity criterion was duly met since the coefficients of the correlations between the constructs are greater than the value of the square root of the AVE.

4.3. Evaluation of the Structural Model

The next stage, developed in accordance with the guidance from Hair Jr. et al., 2014, was to analyze the R² values since they portray the percentage of variance of a latent variable that is explained by other latent variables. The R² values provide a relative measure of adjustment specifically for each structural equation only for endogenous latent variables. Table 8 details the R² values for all of the mesoregions:

Table 8
R² values for the mesoregions

Mesoregion	1. Curitiba Metropolitan Area	2. East Center	3. Pioneer North	4. North Central	5. Northwest
R2	54.44%	59.77%	33.07%	54.43%	62.76%
Mesoregion	6. West	7. West Center	8. Southwest	9. South Center	10. Southeast
R2	64.31%	27.84%	55.33%	50.83%	56.28%

• Source:Data from the research (2016).

The results calculated for the R² of the 10 mesoregions and also of the sample for the state of Paraná are in an interval between 27.84% and 64.31%, which enables it to be interpreted that the models for the mesoregions are able to explain between approximately 30% and 65% of the students’ intention to pursue a career in the area of accounting. The mesoregion with the lowest coefficient is the West Center, represented by the respondents from the Campo Mourão (Unespar) institution. The highest coefficient is for the West mesoregion, represented by the respondents from Unioeste (Cascavel, Foz do Iguaçu, and Marechal Cândido Rondon campuses). The considerable difference between the regions is possibly due to the students’ perception in relation to the profession, since the number of respondents was very similar (West Center n =43; West n = 56). Another factor may be the job options available, since the West Center is one of the least industrialized mesoregions, it presents the lowest population density, and one of the smallest territorial areas, compared to the others. This same reason can also be extended to the Pioneer North mesoregion, which also obtained an R² coefficient below 50%, and which presents a mainly agricultural economy, which directly influences job options in the area of business, especially accounting.

Before laying out the bootstrapping results, it is important to mention that the predictive validity (Q²) and size of the effects (f²) values were evaluated for the relationships of the models for all of the mesoregions tested. The first test verifies the precision of the model, how much it is adjusted, and whether the values above zero satisfactorily meet the corresponding criterion, as recommended by Hair Jr. et al. (2014). In addition, the f² test enables it to be evaluated how much each construct is useful in the estimate of the examined phenomenon. The values of the f² test covered in the interval from 0.02 to 0.15 and above 0.35 indicate, respectively, a small, medium, and large effect of the constructs in the model (Hair Jr et al., 2014). Thus, it is noted that both tests resulted in the accuracy of the model and in the relevance of the variables for a general adjustment in all of the mesoregions, satisfactorily fulfilling the reference values.

Another evaluation was to analyze the absence of multicollinearity for the exogenous (independent) variables, since they cannot be strongly correlated. In the presence of multicollinearity, at least one of the independent variables is redundant, inflating the estimate of the variances of the parameters, producing standardized coefficients higher than 1 or lower than -1, or also possibly causing negative variance estimates. In light of this understanding, the evaluation using the VIF (Variance Inflation Factor) statistic results in an indicator that measures how much the variance of a coefficient is increased due to collinearity. In our model, the test results indicate the non-presence of multicollinearity in the mesoregions studied.

The structural coefficients and the p values were estimated using bootstrapping, considering the sample for the mesoregions and 2,000 resamplings, so that confidence intervals could be obtained to evaluate the significance of the estimated coefficients. Table 9 was elaborated based on these results:

Tabela 9
Structural relationships

1. Curitiba Metropolitan Area				2. West Center
	β	t-value	p-value		β	t-value	p-value
H1	0.393	16.64	0.000	H1	0.384	14.144	0.000
H2	0.213	13.201	0.000	H2	0.072	5.379	0.000
H3	0.35	16.646	0.000	H3	0.408	18.045	0.000
3. Pioneer North				4. North Central
	β	t-value	p-value		β	t-value	p-value
H1	-0.017	0.662	0.508	H1	0.13	7.206	0.000
H2	0.046	1.7271	0.085	H2	0.243	16.722	0.000
H3	0.568	29.498	0.000	H3	0.561	33.835	0.000
5. Northwest				6. West
	β	t-value	p-value		β	t-value	p-value
H1	0.312	16.741	0.000	H1	0.431	24.741	0.000
H2	0.439	19.882	0.000	H2	0.19	14.415	0.000
H3	0.237	13.878	0.000	H3	0.357	20.553	0.000
7. West Center				8. Southwest
	β	t-value	p-value		β	t-value	p-value
H1	0.334	20.005	0.000	H1	0.452	28.637	0.000
H2	-0.266	10.184	0.000	H2	0.028	1.598	0.110
H3	0.258	14.095	0.000	H3	0.381	23.412	0.000
9. South Cener				10. Southeast
	β	t-value	p-value		β	t-value	p-value
H1	0.097	5.552	0.000	H1	0.379	23.371	0.000
H2	0.152	7.506	0.000	H2	-0.059	3.499	0.000
H3	0.581	36.210	0.000	H3	0.515	36.05	0.000

• Source: Data from the research (2016).

The prediction of the three variables of the TPB model (H₁: Attitude -> Intention; H₂: Subjective Norm -> Intention; and H₃: Perceived Behavioral Control -> Intention) for the respondents’ intention to pursue an accounting career was examined. It was found that in mesoregions 1, 2, 4, 5, 6, and 9 all of the hypotheses were corroborated. It is noted that these mesoregions have the most economically developed cities in the state. With this, it can be deduced that the respondents perceived greater chances of pursuing one of the accounting profession careers due to the fact that they have more options in the job market. This inference contradicts Bardagi et al. (2006), which argues that some students overvalue job market conditions and become demotivated and less interested by the profession itself when they perceive difficulties in joining it. Also in this respect, there are various studies that comment on these influences, such as the availability of work, job security, perceived benefits, and pay packages (Gul et al., 1989; Adams, Pryor & Adams, 1994; Ahmed, Alam & Alam, 1997; Mbawuni & Nimako, 2015).

With relation to the hypotheses that could not be corroborated, H₁ and H₂ stand out, observed via the data for mesoregions 3, 7, 8, and 10. Regarding H₁, which concerns attitude, defined as the individual’s positive or negative feelings with regards to carrying out a particular behavior (Fishbein & Ajzen, 1975), this was not supported in mesoregion 3. As for H₂, this was not corroborated for mesoregions 3, 7, 8, and 10, since in 3 and 8 it presented statistical significance and in 7 and 10 it presented negative path coefficients. These findings enable it to be inferred that the non-significant results of the “SN” construct may indicate that social pressure has little relevance for the respondents in terms of their intention to pursue the career. However, in the mesoregions in which H₂ was corroborated, the confirmation is observed of the ranking that was ordered into professionals from the area, friends, partners, relatives, teacher(s), and parents.

These findings are not consistent with those of the studies by Tan and Laswad (2006, 2009), who found that accounting students in New Zealand were more motivated to consider the opinion of parents in pursuing a career in accounting. However, it is partially consistent with the results of Bebbington, Thomson, and Wall (1997), who concluded that parents, friends, and professional guidance advisors (or teachers) exert very little influence over the intention of Scottish students to become accountants, and with the research from Lowe and Simons (1997), which reveals that parents, friends, and teachers were the least influential factors in the decision of U.S. students to specialize in accounting.

Finally, H₃ was supported in the samples for all of the mesoregions. This concerns the PBC construct, which refers to the individual’s perceived ability to carry out a particular behavior and their perception of enabling factors or difficulties in doing so. Under this definition, it is assumed that the respondents believe in their ability to carry out an accounting career after concluding their course.

5. Conclusions

This study investigated the behavioral intention of students graduating from Accounting courses at public universities in the state of Paraná to pursue a career in the area of accounting. As theoretical support, the Theory of Planned Behavior was used, which has been addressed in various studies and in different areas of knowledge.

Regarding the results obtained, the little influence of the Subjective Norm factor on the students’ intention stands out, giving rise to possible discussions. The main one is the fact that the sample for some mesoregions did not consider this factor by not supporting this hypothesis. Thus, this finding is characterized as a niche for new research in the area of accounting that seeks to show what the main influencers of the behavior of Brazilian students are.

Concerning the implications for professional practice, the findings of this study contribute to understanding the profile of accounting graduates from public HEIs in the state of Paraná. With this information, different strategies can be outlined for the HEIs to rethink their curricula and their approaches to the course, depending on the region in which they are located, given that economic and social characteristics directly influence the perception of job opportunities for the future professionals.

In addition, the competent bodies can use and broaden studies regarding the variables that influence the intention of these future professionals in order to develop more adequate and consistent courses for the market. For HEIs, another possible approach is to develop actions focused on supporting professional practice in order to increase the interest and knowledge of the students in accordance with their local needs. Moreover, this study contributes to advancing the discussion regarding the career choices of higher education students in Brazil, especially for evaluating the most significant aspects of this process and for the use of psychological theories in accounting.

This study, as in any scientific research, presents limitations due to the researchers’ decisions regarding the methodological design. However, these limitations open up opportunities for new studies. One of these is the sample definition, since, for example, the opinion of the students from all years of the course, as well as from private universities, could have been addressed. Another limiting factor may be the simplicity of the questionnaire that marks the validity of the results of a particular point, since there may be other variables that influence the students’ intended career choice that were not considered.

Thus, one suggestion for future studies is to extend the sample to other students from intermediate levels of the course, as well as students from private institutions. Since the Subjective Norm factor showed little significance in some mesoregions, another suggestion is to prioritarily address this construct in the elaboration of other studies with the same theme as this paper.

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• *
  Paper presented at the X ANPCONT Congress, Ribeirão Preto, SP, Brazil, June 2016.

Publication Dates

• Publication in this collection
  Apr 2018

History

• Received
  20 Dec 2016
• Accepted
  26 Sept 2017