Transformation of skills in the accounting field: the expectation–performance gap perceived by accounting students

ABSTRACT

Addressing the discussion about accounting students’ readiness for future accounting work, this study aims to explore their perceptions of what kinds of gaps possibly exist between their expectations about the importance of various skills in professional practice and the level of skill development attained during accounting studies. The data for the study were collected using a survey of Finnish accounting students. The findings highlight the expected importance of several professional skills for future accounting work and emphasise the need for further development of technological skills in accounting education. The study’s results also show that students do experience gaps between their expectations and actual performance in various skill areas. The study extends the literature on such gaps by presenting accounting students’ perspectives concerning a comprehensive list of technical and professional skills, including skills related to emerging technologies, and offers suggestions about skill areas probably needing further emphasis in accounting education.

KEYWORDS:

• Accounting education
• expectation–performance gap
• professional skills
• student perceptions
• technical skills
• technological skills

Introduction

Following the debate about accounting students’ preparedness for future work, our study examines the extent to which their own expectations about the future importance of various skills in the practice of the profession match their perceived skill development in accounting education. As the accounting practice and skill requirements are transformed, during their education, it is essential that they be equipped with the skills that they will actually need in their future accounting careers. To help accounting education institutions develop and better align their programmes with changing expectations, it is important to understand possible skill gaps experienced in accounting education. With changes in the accounting environment and profession, skill gaps and potential deficiencies in accounting education are international issues and vital for all educators and educational institutions to understand. Our study shows that students perceive multiple key skills as underdeveloped in accounting education in relation to the expected importance of such competencies, which seems alarming and calls for prompt action.

The accounting practice and profession are undergoing a transformation as a result of developments and changes in the global business environment. The transformation is especially due to digitalisation and the advances of information technology, as well as the globalisation of economies (Carvalho & Almeida, 2022; Tan & Laswad, 2018). Recently, the COVID-19 pandemic has even accelerated digital transformation by rapidly driving or even forcing organisations and people to extensively adopt and utilise technology (Ng & Harrison, 2021; Tsiligiris & Bowyer, 2021). Advancement in digital technologies can be regarded as a revolution in the accounting profession, particularly when emerging technologies, such as artificial intelligence (AI), are considered (Polimeni & Burke, 2021). Bakarich and O’Brien (2021) argue that emerging data analysis tools and technologies will change the way of doing a substantial part of (public) accounting work. Thus, it seems that the nature of accounting work will be quite different from what accounting professionals are used to.

Following the overall transformation in the accounting practice and the nature of its work, the skills required in accounting work are also affected. Traditional accounting tasks change, leading to a shift in the needed skill sets of accounting employees and graduates (Chaplin, 2017; De Lange et al., 2006). Kavanagh and Drennan (2008) refer to the expectations about additional competencies due to the competitive pressure and technological developments. Technical knowledge of accounting or subject-specific knowledge alone is no longer sufficient, so accounting employees’ competencies and skills should be expanded to knowledge and skills in multiple areas in order to succeed in their accounting careers (Bolt-Lee & Foster, 2003; Conway, 2018, p. 194; De Lange et al., 2006; Gammie et al., 2002; Jackling & De Lange, 2009). A widespread perception is that accounting graduates need to have a range of both technical and professional skills¹, with an increasing emphasis on or demand for the latter (e.g. Bressler & Pence, 2019; De Lange et al., 2006; Dolce et al., 2020; Tsiligiris & Bowyer, 2021; Wilkin, 2022). Following the growing digital transformation, the technological skill set is also expected to be a crucial part of the accountant’s skill portfolio (Banasik & Jubb, 2021). In general, technical skills (or hard skills) refer to skills or knowledge related to a specific job, discipline or profession and skills that can rather easily be learned or taught (Robles, 2012). Professional skills are regarded as transferable qualities and skills that are neither industry- or subject-specific nor easy to acquire or teach (Crawford et al., 2011; De Lange et al., 2006; Robles, 2012).

Over the years, there have been debates about accounting students’ professional adequacy or preparedness for accounting work (e.g. Bayerlein & Timpson, 2017; Bui & Porter, 2010; Jackling & De Lange, 2009; Towers-Clark, 2015), and those debates are becoming even more relevant, considering the changing requirements for work. Bayerlein and Timpson (2017) suggest that entering accounting work successfully may be difficult for graduates if accounting programmes are not aligned with the profession’s expectations. However, fully aligning them may be challenging for higher education institutions as the needs change at a rapid pace and might be difficult to predict and address in advance in accounting courses. The issue of the perceived inadequate response of educational institutions to the skill requirements may be called the expectation–performance gap. The idea of the expectation–performance gap is grounded on the framework by Bui and Porter (2010), who define it as the gap between the skills that employers desire or expect accounting graduates to possess and the latter’s actual skills that employers perceive. The development of Bui and Porter’s (2010) framework was motivated by the debate on accounting education’s failure to adequately equip accounting graduates with the skills expected in the accounting profession.

Following this debate about accounting students’ preparedness for future accounting work, the purpose of our study is to explore what kinds of expectation–performance gaps related to accounting skills and education are experienced by students. Thus, our aim is to learn about these issues directly from the students’ perspectives. In this setting, the expectation part comes from the students’ expectations about the importance of different skills in their future accounting work. The performance part comes from the students’ self-assessed academic performance, measured by their perceptions of the level of development of such skills during their accounting studies. The aim is to identify possible gaps to see if there are skill areas needing further development or attention in education to ensure accounting students’ readiness for accounting work. To determine whether such gaps exist, the main research question (RQ) is formulated as follows:

RQ. To what extent do accounting students’ expectations about the future importance of various skills in the practice of the profession match their perceptions of the development of those skills in accounting studies?

Bui and Porter’s (2010) framework, with all of its components (expectation gap, constraints gap and performance gap), is not tested as such in this study. Instead, we concentrate on accounting students’ perspectives, measuring potential gaps between their expectations of the importance of various skills in actual professional practice and perceptions of the development of those skills during their accounting studies (i.e. academic performance). According to Kavanagh and Drennan (2008), students should be regarded as comprising a key stakeholder group when examining the views on skill development for an accounting career. Al Mallak et al. (2020) and Gioiosa and Kinkela (2019) also regard students as key stakeholders in accounting education as they are the participants of accounting courses; therefore, their perceptions are relevant. The issue of changing requirements particularly affects current students since they should gain skills that will enhance their employment possibilities (Gammie et al., 2002). They have up-to-date knowledge and understanding of the curriculum content that is currently learned in university programmes. They are also the future professionals who will be affected by the ongoing transformation in the long term and are often the youngest stakeholders who face the longest time horizon when considering their future work. According to Ng et al. (2010), students have a realistic expectation of their first job. Examining students’ expectations about the future importance of various skills is also crucial because their motivation to learn or acquire skills may be driven by their perceptions of the importance of those skills (Kavanagh & Drennan, 2008). Likewise, Bui and Porter (2010) argue that students’ perceptions of accountants, accounting work and accounting courses contribute to the expectation–performance gap.

Nevertheless, accounting students’ perspectives have not gained much attention in prior research. The studies about expectation–performance gaps or skill gaps in the accounting field have largely concentrated on the views of employers and/or educators (e.g. Abayadeera & Watty, 2014; Anis, 2017; Howcroft, 2017). Only a few studies related to skill gaps have focused on accounting students or graduates. Those studies have mainly concentrated on professional skills instead of technical skills or both technical and professional skills. The studies’ researchers conclude that students regard several professional skills as very important and would therefore benefit from further development of those skills during their degree programmes because all the skills that are considered essential are currently not well developed (e.g. Dolce et al., 2020; Smith et al., 2018; Towers-Clark, 2015). Dolce et al. (2020) also conclude that students’ perceptions concerning professional skills (described as soft skills in their study) only partially match employers’ expectations. Kavanagh and Drennan (2008) have studied both professional and technical skills from accounting students’ perspectives alongside employers’ expectations. They argue that students focus on developing multiple vital professional skills in addition to routine technical skills, but many of the skills that are regarded as important by both students and employers are not sufficiently addressed in accounting programmes (Kavanagh & Drennan, 2008). Considering the ongoing – especially technological – transformation of the field, newer studies are needed.

For this study, the data were collected from a survey of Finnish accounting students. The data collection resulted in a total of 108 valid observations, representing a response rate of approximately 15.5%. Statistical analyses were conducted to determine whether accounting students experience significant gaps between their expectations about the importance of multiple skills and perceptions of their actual skill development (i.e. performance). This study’s findings highlight the expected importance of several professional skills besides technical skills, as well as stress the development of technological skills during accounting studies. By noting that students do experience gaps between their expectations and actual performance in various skills, our study contributes to the debate about accounting students’ preparedness for accounting work and indicates areas that are possibly worth developing in higher education institutions’ accounting programmes.

Contribution

The study makes several contributions to accounting literature. First, this study extends the literature on skill gaps (see, e.g. Dolce et al., 2020; Gunarathne et al., 2021; Kavanagh & Drennan, 2008; Smith et al., 2018) between expectations and performance by presenting more recent perspectives of accounting students and providing their insights concerning a comprehensive list of both technical and professional skills. Second, along with many other technological skills, this study addresses skills related to emerging technologies that have not gained attention in previous studies concerning skill gaps. Many prior studies have largely concentrated on professional skills (e.g. Abayadeera & Watty, 2014; Dolce et al., 2020; Howcroft, 2017; Webb & Chaffer, 2016) or professional and technical accounting skills (e.g. Anis, 2017; Kavanagh & Drennan, 2008), but considering the ongoing digitalisation and technological evolution, the studies highlighting technological skills, let alone skills related to emerging technologies, have been surprisingly scarce. Third, the Finnish context of the study is unique compared with prior research contexts since skill gaps in the accounting profession have not been studied in the Nordic countries. Finland is a relevant and interesting context for gathering newer insights on the discussion related to the transformation of accounting work since the country can be considered a pioneer in digital transformation. In fact, in the International Digital Economy and Society Index (I-DESI) 2020, Finland was the leading country among 27 European Union (EU)-member states and 18 non-EU countries when their digital performance was assessed and compared using five dimensions (EU, 2021).

The remainder of this paper is structured as follows. In the following section, we review the literature on the changing nature of accounting work and skill requirements as well as the gaps related to skills. We then present the data and methods used in the study and the results of the study, followed by the discussion of our findings and the conclusions of the study. Finally, we acknowledge the limitations of the study and provide suggestions for future research.

Literature review

The transformation of accounting work

An accountant’s role and tasks have been transformed over time. Particularly over the past few decades, an accountant’s role has changed significantly, shifting from the traditional role of a score keeper to the more complex role of a professional with in-depth financial knowledge in order to respond to the changing needs of the business environment (De Lange et al., 2006; Towers-Clark, 2015). De Lange et al. (2006) refer to the emergence of the so-called knowledge professional in terms of the new role of an accounting employee, which is supported by Howieson (2003), who views knowledge management as the core function of accounting practitioners. However, there are reasons to believe that the profession will further change in the future. Yigitbasioglu et al. (2023) suggest that following technological development, accountants will play an increasing number of non-traditional roles, providing different kinds of advisory services in addition to traditional accounting services and roles.

Accounting work is affected by several trends and developments, such as technological progress and globalisation (Albrecht & Sack, 2000; Pincus et al., 2017). According to Qasim and Kharbat (2020), the emergence and adoption of digital technologies such as blockchain technology, Big Data and AI, have begun to affect and change accounting and auditing work. Considering further advances in technology, Kroon et al. (2021) conclude that the emerging technologies affect the accounting profession by changing tasks and the ways that these are performed. Indeed, Bakarich and O’Brien (2021) argue that emerging data analysis tools and technologies will change the way of doing a lot of work, at least in public accounting. Emerging technologies, such as robotic process automation (RPA), machine learning and AI, enable and facilitate automation. In accounting work, automation leads to an extensive transformation because accounting and auditing tasks traditionally include many structured, repetitive tasks, which are likely to be automated (Kokina & Davenport, 2017). Some technologies, such as RPA, have already been employed in accounting, and their use has increased in recent years (Cooper et al., 2019; Kokina & Blanchette, 2019). Especially, AI capability is expected to continue its rapid expansion, with a remarkable impact on the accounting profession, and AI applications will likely continue to attract the interest of accounting researchers and practitioners (Bakarich & O’Brien, 2021; Sutton et al., 2016). In addition to technological development, other drivers of change, such as offshoring and increased demand for and interest in transparency and responsibility issues and sustainability reporting, have already transformed and will probably further affect the accounting profession and revise an accountant’s role and tasks, even though automation has started to displace offshoring (Conway, 2018, p. 189; Pincus et al., 2017).

Skill requirements and demands

As accounting work continues to evolve, the skills required to perform accounting tasks in order to succeed in an accounting career become increasingly complex (Chaplin, 2017; De Lange et al., 2006). The requirement for developing new or broader sets of skills to perform well in accounting work has been largely recognised (e.g. Banasik & Jubb, 2021; Burns et al., 2004; De Lange et al., 2006). Jackling and De Lange (2009) argue that the digital age and global business models have modified the expectations about the work of accountants, while Kavanagh and Drennan (2008) suggest that graduates are expected to demonstrate additional competencies due to the competitive pressure and technological developments. Instead of possessing technical knowledge alone, accounting employees should acquire or possess skills and knowledge in several areas, including a range of professional skills (see Bolt-Lee & Foster, 2003; Bressler & Pence, 2019; Carvalho & Almeida, 2022; De Lange et al., 2006; Dolce et al., 2020; Gammie et al., 2002; Jackling & De Lange, 2009). Professional skills have also been referred to as generic, key, soft, transferable, transversal, vocational or employability skills (e.g. Crawford et al., 2011; De Lange et al., 2006; Howcroft, 2017; Ng & Harrison, 2021; Succi & Canovi, 2020; Tan & Laswad, 2018; Towers-Clark, 2015). The term chosen in this study – ‘professional skills’ – is based on International Education Standard (IES) 3 (International Federation of Accountants [IFAC], 2014) and has also been adopted in recent accounting literature (e.g. Kirstein et al., 2019; Tan & Laswad, 2018; Wilkin, 2022). According to IES 3, professional skills cover many kinds of skills – classified as intellectual, interpersonal and communication, personal and organisational – that professional accountants need, along with technical skills and personal values and attitudes (IFAC, 2014).

The roles of technical skills versus professional skills have been debated and studied by multiple researchers (e.g. Crawford et al., 2011; Kavanagh & Drennan, 2008; Smith et al., 2018; Usoff & Feldmann, 1998), with conflicting views concerning their importance. For instance, Usoff and Feldmann (1998) suggest that many students rank non-technical skills lower in importance than technical accounting skills, while Kavanagh and Drennan’s (2008) findings suggest that students regard many professional skills as more important than technical ones. In turn, Jackling and De Lange (2009) note that employers rate the importance of non-technical skills above technical ones. Although professional skills have gained much attention in recent research, Rebele and St. Pierre (2019) argue that the development of such skills during students’ accounting education should never take priority over the development of their technical accounting competence.

A range of the most common skills and abilities studied in prior accounting-related literature is summarised in Table 1. Those studies have examined different stakeholders’ expectations concerning the importance of such skills in accounting work, their perceptions on the extent of the development of those skills during accounting education, or the emphasis placed on specific skills in accounting education. These have been classified into five skill categories, which are used in the empirical analysis of this study. The classification is partly based on and adapted from some studies (Arquero Montaño et al., 2001; De Lange et al., 2006; Hassall et al., 2003; Jackling & De Lange, 2009; Kavanagh & Drennan, 2008; Klibi & Oussii, 2013; Smith et al., 2018; Towers-Clark, 2015), as well as IES 3 (IFAC, 2014). In the absence of a single exclusive and commonly accepted skill classification framework covering both technical and professional skills, subjective judgement has also been applied in the classification.

Table 1. Skills examined in prior research.

Skill group	Prior literature
Technical skills and knowledge Examples: key accounting skills, financial administration skills, research skills, accounting knowledge, knowledge of interaction of disciplines, juridical knowledge, knowledge of statistics	De Lange et al., 2006; Edeigba, 2022; Jackling & De Lange, 2009; Kavanagh & Drennan, 2008; Klibi & Oussii, 2013; Towers-Clark, 2015; Usoff & Feldmann, 1998
Computer, information technology (IT), data processing skills Examples: computer technology, computing and IT, IT software and accounting software skills	Arquero Montaño et al., 2001; De Lange et al., 2006; Dolce et al., 2020; Hassall et al., 2003; Howcroft, 2017; Jackling & De Lange, 2009; Kavanagh & Drennan, 2008; Spraakman et al., 2015; Towers-Clark, 2015; Usoff & Feldmann, 1998
Interpersonal, social and communication skills Examples: written and oral communication, teamwork, effective listening, customer service	Al Mallak et al., 2020; Arquero Montaño et al., 2001; Crawford et al., 2011; De Lange et al., 2006; Dolce et al., 2020; Douglas & Gammie, 2019; Hassall et al., 2003; Howcroft, 2017; Jackling & De Lange, 2009; Kavanagh & Drennan, 2008; Paguio & Jackling, 2016; Towers-Clark, 2015; Usoff & Feldmann, 1998; Zaid & Abraham, 1994
Intellectual skills Examples: decision-making, problem-solving, critical evaluation, analytical and logical skills	Al Mallak et al., 2020; Arquero Montaño et al., 2001; Dolce et al., 2020; Douglas & Gammie, 2019; Hassall et al., 2003; Howcroft, 2017; Jackling & De Lange, 2009; Kavanagh & Drennan, 2008; Klibi & Oussii, 2013; Towers-Clark, 2015; Usoff & Feldmann, 1998
Other professional skills Examples: leadership, negotiation, continuous learning, flexibility and adaptability, critical reading, time management, organising workloads	Al Mallak et al., 2020; Arquero Montaño et al., 2001; Crawford et al., 2011; Douglas & Gammie, 2019; Hassall et al., 2003; Howcroft, 2017; Jackling & De Lange, 2009; Kavanagh & Drennan, 2008; Klibi & Oussii, 2013; Smith et al., 2018; Usoff & Feldmann, 1998

The importance of technical skills, especially accounting-specific skills, is evident when thinking about succeeding in accounting work. The results of Jackling and De Lange’s (2009) study show that both graduates and employers acknowledge the importance of technical accounting skills although professional skills are highlighted. Berry and Routon’s (2020) findings suggest that accounting students are technically prepared but could benefit from improvements in their professional skills. However, according to the results reported by De Lange et al. (2006), technical skills could be even more emphasised or developed during accounting courses. Thus, the perceptions of stakeholders seem to vary.

Skill-related studies in the accounting field, especially those conducted in the twenty-first century, have largely focused on professional skills. Abayadeera and Watty (2014) argue that in general, the development of professional skills is vital for success in an accounting career in the global work environment. Specific professional skills have been suggested as essential for accounting professionals. For instance, the importance of communication skills in accounting work or education has been highlighted by many researchers (e.g. Borzi & Mills, 2001; Carvalho & Almeida, 2022; De Lange et al., 2006; Plant et al., 2019; Smith et al., 2018; Zaid & Abraham, 1994). Along with communication skills, analytical, critical-thinking and problem-solving skills have come up in multiple studies when considering the most important skills for an accounting career (e.g. Carvalho & Almeida, 2022; De Lange et al., 2006; Towers-Clark, 2015). In turn, teamworking or interpersonal skills have been highlighted in studies that have explored the importance or the desirability of multiple skills (e.g. Jackling & De Lange, 2009). However, Paguio and Jackling (2016) have delved even deeper into the dimensions of teamwork, providing evidence that employers expect accounting graduates to possess various teamworking skills. Similarly, Dolce et al. (2020) suggest that employers look for graduates with good interpersonal and communication skills and that they seem to prioritise professional over technical skills. Carvalho and Almeida (2022) conclude that along with communication skills, many other professional and personal skills, such as the ability to adapt to new contexts and to work under stress, and being proactive and showing initiative, are needed in the accounting profession. In turn, Plant et al. (2019) emphasise the importance of self-management and time management skills, while Daff et al. (2012) accentuate the importance of a broader skill set for accountants, including emotional intelligence, along with other professional skills. As can be observed, many types of professional skills are considered significant for accountants. Overall, versatile professional skill sets have been investigated in skill-related research (e.g. Al Mallak et al., 2020; Crawford et al., 2011; Dolce et al., 2020; Douglas & Gammie, 2019; Howcroft, 2017; Webb & Chaffer, 2016).

In prior research, various approaches have been adopted regarding the classification of skills related to information technology (IT), data processing and computers. For instance, Crawford et al. (2011) and Towers-Clark (2015) have included basic computer use, data/information-collecting skills or IT skills in professional skills, while in other studies (e.g. Dolce et al., 2020; Jackling & De Lange, 2009; Usoff & Feldmann, 1998), technical skills have covered computer knowledge/skills or the ability to use IT. Thus, those skills may have both technical and professional skill features. Therefore, especially when studying digital and technological changes, we consider it reasonable to classify those skills into their own group. Overall, it seems logical that following the digitalisation and the widespread technology adoption, accounting professionals also need digital and technological skills. Tsiligiris and Bowyer (2021) highlight the increasing importance of various digital skills and the understanding of digital technologies in the business context, while Spraakman et al. (2015) suggest that the IT skills of (management) accountants should evolve along with the evolution of IT. According to Qasim and Kharbat (2020), teaching in accounting programmes should be updated, and the increasing adoption of new technologies should shape the practices related to the design, development or implementation of accounting curricula. Jackson et al. (2022) also recommend paying more attention and devoting more resources to the preparation of future accountants for future technology demands.

Accounting education and students’ readiness for accounting work

The extent to which different technical and professional skills are emphasised and developed in higher education programmes seems to vary. Some accounting graduates perceive that the focus of their education has been directed towards technical skills instead of professional skills (Jackling & De Lange, 2009). As professional skills are largely expected and demanded from accounting graduates when starting their work (Dolce et al., 2020), accounting programmes will fail to meet such expectations if the development of professional skills is not considered (De Lange et al., 2006). This would signify the need to refocus the accounting curricula to enable further professional skill development during the programmes (Jackling & De Lange, 2009). Kavanagh and Drennan (2008) suggest that in accounting programmes, more attention should be paid to training students in those skills that would help graduates succeed in the changing environment, and it seems that these comprise professional skills. Gunarathne et al. (2021) state that to fulfil the demands of the profession, accounting educators are responsible for maintaining the balance between teaching the core subjects and integrating emerging issues related to the accounting discipline into the lessons, while paying attention to the development of professional skills.

Related to accounting education, the debate about accounting students’ professional adequacy or readiness for accounting work has continued for years (e.g. Bayerlein & Timpson, 2017; Bui & Porter, 2010; Edeigba, 2022; Jackling & De Lange, 2009; Towers-Clark, 2015). Bayerlein and Timpson (2017) argue that starting accounting work successfully might be difficult for graduates if accounting programmes are not aligned with the expectations in the profession. According to Bui and Porter (2010), over the last decades, accounting education has been criticised for not equipping students with the knowledge, skills and attributes required or expected in the accounting profession in the changing environment. Motivated by the criticism, Bui and Porter (2010) have proposed a framework for the expectation–performance gap, which is defined as the gap between the skills desired by employers and the actual skills that they perceive among the accounting graduates. Their framework consists of three components. The expectation gap refers to the gap between accounting employers’ and educators’ expectations on the competencies desired from accounting graduates. The constraints gap signifies the gap between what is desired and what is reasonably expected by educators due to the constraints affecting the effectiveness of accounting education. The performance gap denotes the gap between the competencies that are reasonably expected by educators and graduates’ actual competencies that are perceived by employers (Bui & Porter, 2010). For example, Abayadeera and Watty (2014) have adapted the framework to study the professional skills of accounting students, suggesting that an expectation–performance gap exists in the development of such skills in accounting education. Likewise, Howcroft (2017) has adapted and used the framework to study graduates’ vocational skills in management accountancy, finding expectation gaps and disagreements among three stakeholder groups.

The concepts of the expectation gap or the expectation–performance gap are neither new nor only tied to skills. Liggio (1974) already introduced the concept of the expectation gap, defining it as the difference between the expectation levels of independent accountants and users of financial statements regarding the performance of the accountants or the accounting profession. Porter (1993) has suggested a framework for the expectation–performance gap in the auditing context, defined as the gap between society’s expectations of auditors and its perceived performance of auditors, consisting of two major components: the reasonableness gap and the performance gap. A skill gap is also a widely used concept when analysing or discussing the differences between the required skills or the expected importance of skills and the emphasis on skills in education or demonstrated skill levels (e.g. De Lange et al., 2006; Pincus et al., 2017). The studies about expectation–performance gaps or skill gaps are restricted to neither the accounting nor the auditing context. For instance, Llorens et al. (2013) and Llorens Garcia et al. (2019) have examined the skill gaps in the information and communication technology (ICT) field, and Duke (2002) has investigated the differences between students’ perceived importance of skills in marketing and other business disciplines and perceived levels of their skills in these fields.

In the accounting field, gaps or deficiencies related to skills have indeed been recognised. Towers-Clark (2015) has found that some professional skills, such as interpersonal, decision-making, oral communication and management skills, are deficient and not strongly developed in accounting programmes, while other skills, such as practical research and written communication, are perceived to be well developed in the programmes but are not regarded as very important by students. In their study of possible deficiencies in the emphasis on professional skills in undergraduate accounting courses, De Lange et al. (2006) conclude that graduates perceive deficiencies in multiple skills in those courses, especially in interpersonal, oral expression and computing skills. Additionally, they have found skill gaps in multiple, typically technical, accounting skills. The results indicate that both professional and technical types of skills should be accorded a greater emphasis in undergraduate accounting courses (De Lange et al., 2006). Similarly, Kavanagh and Drennan (2008) argue that multiple skills are not sufficiently taught or focused on in accounting programmes compared with their assessed importance, and they find statistically relevant gaps in all of the studied skills, except research and technical or bookkeeping skills. Jackling and De Lange (2009) have also found that employers expect and require a range of professional skills that are not adequately developed in the degree programmes, according to accounting graduates. Similar types of gaps have been reported in other studies (e.g. Al Mallak et al., 2020; Dolce et al., 2020; Krikorian et al., 2020).

Motivated not only by the ongoing transformation and the gaps found in previous studies but also by the lack or scarcity of recent studies examining skill gaps from accounting students’ perspective, we define the research objectives as follows. First, we seek to find out how well accounting students’ expectations about the future importance of skills match their perceptions of the development of those skills in accounting studies (RQ), that is, whether they experience expectation–performance gaps related to different types of skills. Second, our aims are to analyse and compare the features of different skill groups regarding expectations of their importance and perceived development from students’ perspective, as well as find out whether there are some individual student characteristics associated with the gaps that they experience.

Methodology

Sample selection and data collection

In this paper, we present part of the results of a broader survey conducted in the winter of 2019/2020 (late November to early February). The broader study focused on students’ expectations of future work and forces of change in the accounting field, their perceptions of future skill requirements in the field, as well as their assessments of the extent of learning different skills during their higher education. The parts relevant to this study are those relating to skill requirements and skill development.

The study sample was drawn from three higher education institutions (two universities and one university of applied sciences [UAS]) operating in eastern and south-eastern Finland and offering a degree programme in accounting or financial administration. In Finland, the students who are admitted to universities basically obtain the right to pursue both bachelor’s and master’s degrees, and it usually takes a total of approximately 5 years to complete those degrees in economics and business administration. In the UASs, the target duration of a bachelor’s degree in business administration is usually 3.5 years, and the students are not automatically given the right to pursue master-level studies, but they can apply for admission to master’s programmes in UASs or universities after completing a bachelor’s degree. The data were collected from responses to an online questionnaire since it enabled reaching a large number of students and allowed the respondents to answer the survey questions easily and relatively quickly. The resulting data were quantitative in nature.

The survey’s target group included students pursuing bachelor’s or master’s degrees in accounting or financial administration. Both bachelor’s and master’s students were targeted in order to reach a broader group of participants and to allow us to analyse possible differences among the expectations of students with different study backgrounds. To ensure that the respondents already had an impression or understanding of the accounting field, first-year students were excluded from the target group. Background questions concerning the higher education institution, each student’s year level and field of specialisation (major) were asked to ensure that each respondent belonged to the target group.

The survey link was distributed by a contact person in each target institution by using mailing lists, accounting lectures or online learning platforms of accounting courses. The survey was also promoted on social media, particularly in a closed student group, with the specification of the target group. As the questionnaire was disseminated using multiple channels and student e-mail lists were unavailable from all three institutions, it is difficult to accurately determine the total population of accounting students in the selected institutions. However, approximate numbers of the target students were obtained from contact persons or student services of each higher education institution; thus, a fairly accurate size of the total population was calculated. The approximate size of the target group comprised 696 students.

The data collection resulted in a total of 108 valid observations after four observations were filtered out because the respondents did not belong to the target group. Thus, the response rate was roughly 15.5%, in line with those of some similar studies using online questionnaires and also targeting accounting students or graduates (e.g. Dolce et al., 2020; Towers-Clark, 2015). Similar response rates in Finnish student web-based questionnaires have been obtained, for example, by Sakurai et al. (2016) (15.9%) and Halme et al. (2021) (20.9% of business students and 18.3% of social science students). The demographic characteristics of the sample are presented in Table 2.

Table 2. Demographic composition of the sample.

	Age group				Work experience (years)
Degree level	19–25	26–30	> 30	Total	None	< 1	1–2	≥ 3	Total
Bachelor	48	5	4	57 (52.8%)	29	22	6	0	57 (52.8%)
Master	21	19	11	51 (47.2%)	7	13	16	15	51 (47.2%)
Total	69 (63.9%)	24 (22.2%)	15 (13.9%)	108 (100%)	36 (33.3%)	35 (32.4%)	22 (20.4%)	15 (13.9%)	108 (100%)

As shown in Table 2, the sample was almost evenly distributed between bachelor’s degree students (53%) and master’s degree students (47%). The majority of the respondents belonged to the 19–25 age group (64%); only 15% were over 30 years old. About one-third of the respondents (33%) had no work experience in the field of accounting or financial administration, whereas another third (32%) had less than one year of work experience. The rest had been working in the field for 1–2 years (20%) or three or more years (14%). Approximately 44% of the respondents were women and 54% were men, while the rest chose the option ‘Other / I don’t want to answer’ for the gender question. As expected, master’s degree students were, on average, older than bachelor’s degree students, with average ages of 28.45 and 23.68 years, respectively. As also expected, master’s degree students had more work experience in the field, with almost 61% having more than one year of employment, while only 11% of bachelor’s degree students had the same amount of experience. The significance of these associations was verified by chi-square tests of independence, which were conducted to determine whether those categorical variables were statistically related. As expected, a significant association was observed between degree level and age group (χ² (2) = 21.73, p = .000) and between degree level and work experience (χ² (3) = 35.08, p = .000).

Notably, the response rate was higher in the UAS (50%) than in the universities (12%), which was probably a result of different distribution and promotion methods for the questionnaire. Among all respondents, 32% were students from the UAS. In Finland, UASs have traditionally been regarded as slightly more practice oriented than universities, while the latter have been viewed as more research oriented. Moreover, all respondents from the UAS were bachelor-level students. Thus, in addition to the main data analysis, potential differences among these student groups’ perceptions are analysed as well.

Survey instrument

A self-administered questionnaire was used as the instrument for data collection. The questionnaire included socio-demographic background questions (e.g. age, degree level of studies, major and amount of work experience in the field), questions regarding expectations of the importance of 31 different skills in future accounting work and questions regarding perceptions of the extent of developing those skills during accounting studies. The original questionnaire was in Finnish, and it was delivered with a promise of anonymity and a data protection declaration.

The expectations of the importance of different skills were measured by asking students to rate how likely they believe that each skill will be needed in future work in the field – on a 5-point Likert scale, from 1 = ‘not likely at all’ to 5 = ‘very likely’. This variable is referred to as ‘expectation of importance’ or ‘expected importance’. In turn, the perceptions of skill development were measured by asking the respondents to rate how comprehensively they perceive learning each skill in their current studies – on a 5-point Likert scale, from 1 = ‘not comprehensively at all’ to 5 = ‘very comprehensively’. In this setting, the perceptions of skill development are regarded as academic performance. This variable is further referred to as ‘perception of development’ or ‘perceived development’.

There is no definite list of attributes or competencies required from graduates (Towers-Clark, 2015). The skills and competencies defined in the questionnaire were mainly based on prior research. The skills used in the questionnaire are listed in Appendix 1, with references to prior studies in which they were addressed or studied in the accounting context. Most of the skills were addressed in one or more earlier studies, although the wordings of the prior studies might differ slightly from those presented on the list (used in this study) because they were first adapted from English to be comprehensible in Finnish and then translated back from Finnish to English as precisely as possible. However, some skills were also not directly studied previously, but the idea for them was obtained from specific studies. A few skills (knowledge related to robotics and AI, and innovation skills and innovativeness) were added to complement the skill set of the questionnaire because they were predicted to be relevant skills in the future. The prediction of the relevance of robotics and AI was based on the development of emerging technologies (Polimeni & Burke, 2021), while the relevance of innovativeness was presumed because of the contemporary business environment, in which creativity and innovation are vital for both organisational and individual performance (Westwood & Low, 2003).

Data analysis

The data were analysed with Stata SE software (versions 16.1 and 17). Quantitative data analysis was conducted by first calculating the arithmetic mean values of the expected importance and the perceived development of the skills, as well as the absolute differences between those mean scores. The difference was calculated by subtracting the mean score of the perceived development from the mean score of the expected importance. Based on the mean scores, it was possible to analyse which skills were expected to be the most and the least important in future accounting work and which skills were perceived as the most and the least developed during accounting education by the accounting students, as well as to evaluate the students’ expectations of the skills’ importance in relation to perceived skill development.

The statistical significance of the differences between the expectations of importance and perceptions of the development of the skills (i.e. the skill gaps) was also tested. The significance was tested primarily by using a paired sample t-test, which is a parametric test. The results were verified by non-parametric Wilcoxon signed-rank tests (later referred to as ‘verification tests’). Conflicting views exist concerning the use of parametric tests with non-normally distributed and/or Likert-scale data. The use of parametric tests with Likert data has been discussed for decades (e.g. Clason & Dormody, 1994; Harpe, 2015), and the traditional view is that if the assumption of normal distribution is not met, parametric methods should be avoided, and non-parametric ones should be employed (Vickers, 2005). However, Norman (2010) concludes that parametric tests and statistics can be used with Likert-scale data, as well as non-normal distributions, arguing that the assumption of normality is not necessarily required when examining differences between means because the parametric tests result in nearly correct answers, even for non-normal or asymmetric distributions. Various approaches have been adopted for analyses and scales similar to this study. For example, Jackling and De Lange (2009), Kavanagh and Drennan (2008) and Towers-Clark (2015) conducted parametric t-tests to test the significance of differences in mean values, while Dolce et al. (2020) conducted non-parametric tests (Wilcoxon). In this study, parametric tests (paired t-tests) were chosen as primary statistical tests, but as the normality assumption was not verified for each skill variable, the results were verified by non-parametric tests to determine whether their results would support the conclusions on the statistical significance. Based on the statistical tests, it was possible to analyse whether the expected importance and perceived development of the skills differed from each other, that is, whether there were gaps between expectations and performance, according to the accounting students.

Results

For the analysis, we classified the skills defined in the questionnaire into five groups: technical, technological and data processing, intellectual, social and communication, and other professional skills. We present the results of each skill group separately. For each skill, we calculated the mean score of expected importance and the mean score of perceived development, as well as the absolute difference between those mean scores (gap analysis). Then, we tested the statistical significance of the absolute difference. The statistical tests only analysed pairs in the data, so the presented results include only the observations with responses to both questions, which means that the number of observations (n) varies in different skills.

In the result Tables 3–7, we present the mean scores, standard deviations and ranks of expected importance and perceived development. The ranks reflect the position of the mean score (expected importance or perceived development) relative to the mean scores of all skills in the questionnaire. The overall rankings are concluded in Appendix 2. We also report the absolute differences between those mean scores and t-statistics with their statistical significance, as well as the number of responses analysed (n) for each skill. The reported statistical significance levels are based on the results of the paired t-tests. Finally, we report the Cronbach’s alpha values for each skill group, calculated separately for expected importance and perceived development. All the values are reported as rounded values, even though the analyses and the ranks are based on precise values.

Table 3. Mean scores and their differences in technical skills.

Skill	Expected importance			Perceived development			Absolute difference	t-value	n
	Mean score	SD	Rank	Mean score	SD	Rank
Knowledge of different fields, understanding the big picture	4.31	0.75	16	3.12	1.00	22	1.19	10.82***	106
Juridical knowledge	4.10	0.81	24	3.44	1.05	17	0.66	5.97***	107
Foreign languages	3.88	0.92	27	3.39	0.97	19	0.49	4.24***	107
Financial administration/ accounting skills and theoretical understanding	4.52	0.68	10	4.10	0.83	1	0.42	4.31***	108
Research methodology and statistics	3.35	1.08	31	3.44	0.93	17	−0.09	−0.71	107
Cronbach’s alpha	0.63			0.64

***represents significance at the 1% level (p < .01); SD = standard deviation

Table 4. Mean scores and their differences in technological and data processing skills.

Skill	Expected importance			Perceived development			Absolute difference	t-value	n
	Mean score	SD	Rank	Mean score	SD	Rank
Knowledge related to robotics and artificial intelligence	3.73	1.01	28	2.12	1.15	31	1.61	13.73***	107
Different IT systems	4.53	0.63	8	3.00	1.04	25	1.53	13.37***	108
General technological skills and understanding	4.61	0.56	4	3.26	1.11	20	1.35	12.17***	108
Data processing	4.29	0.81	19	2.98	1.21	26	1.31	10.55***	108
Programming	3.47	1.08	30	2.25	1.22	30	1.21	9.86***	107
Cronbach’s alpha	0.79			0.89

***represents significance at the 1% level (p < .01); SD = standard deviation

Table 5. Mean scores and their differences in intellectual skills.

Skill	Expected importance			Perceived development			Absolute difference	t-value	n
	Mean score	SD	Rank	Mean score	SD	Rank
Analytical reasoning	4.60	0.58	5	3.65	1.03	12	0.94	8.90***	107
Decision making	4.53	0.65	8	3.63	0.98	13	0.90	9.47***	108
Critical thinking	4.64	0.59	3	3.91	0.92	4	0.73	8.22***	107
Problem solving	4.59	0.56	6	3.90	0.93	5	0.69	7.51***	108
Logical and mathematical reasoning	4.31	0.79	18	3.69	0.89	11	0.61	5.73***	108
Cronbach’s alpha	0.73			0.81

***represents significance at the 1% level (p < .01); SD = standard deviation

Table 6. Mean scores and their differences in social and communication skills.

Skill	Expected importance			Perceived development			Absolute difference	t-value	n
	Mean score	SD	Rank	Mean score	SD	Rank
Customer service	4.24	0.83	20	2.66	1.19	29	1.58	13.31***	106
Oral communication and interaction	4.41	0.68	12	3.61	0.95	14	0.80	7.35***	108
Active listening	4.23	0.82	22	3.44	1.06	16	0.79	7.48***	108
Networking	4.24	0.75	20	3.46	1.10	15	0.77	7.62***	106
Emotional intelligence	3.67	0.99	29	2.95	1.15	28	0.72	5.90***	98
Written communication	4.31	0.79	17	3.78	0.89	8	0.53	5.35***	107
Teamworking and interaction skills	4.47	0.65	11	4.00	0.85	3	0.47	5.23***	107
Cronbach’s alpha	0.80			0.85

***represents significance at the 1% level (p < .01); SD = standard deviation

Table 7. Mean scores and their differences in other professional skills.

Skill	Expected importance			Perceived development			Absolute difference	t-value	n
	Mean score	SD	Rank	Mean score	SD	Rank
Negotiating	4.35	0.67	15	3.05	1.14	24	1.31	10.93***	108
Innovation skills and innovativeness	4.22	0.78	23	3.16	1.11	21	1.06	10.01***	104
General leadership skills	4.01	0.80	25	2.98	1.00	27	1.03	10.49***	106
Media literacy and criticism	3.96	1.13	26	3.10	1.09	23	0.86	7.39***	105
Self-improvement and learning	4.69	0.54	1	3.88	0.87	6	0.81	9.75***	108
Self-management (organising, managing time and workload)	4.65	0.54	2	3.84	1.04	7	0.81	7.75***	108
Working under pressure	4.39	0.68	13	3.77	0.99	9	0.63	6.39***	107
Adaptability and flexibility	4.36	0.71	14	3.76	0.91	10	0.61	6.42***	107
Initiative skills	4.55	0.68	7	4.07	0.85	2	0.49	5.62***	107
Cronbach’s alpha	0.85			0.86

***represents significance at the 1% level (p < .01); SD = standard deviation

Technical skills

The group of technical skills included all the skills that were regarded as specific to the accounting field or as (theoretical) knowledge taught in university courses. Especially, financial administration and/or accounting skills and theoretical understanding were regarded as field-specific skills, while juridical knowledge, knowledge of different fields, research methodology and statistics, and foreign languages were viewed as knowledge, for which specific courses are offered in accounting education. The results concerning technical skills are presented in Table 3, arranged by the absolute difference (gap).

Among the technical skills, all mean scores of expected importance and perceived development were above 3. Among the technical skills, financial administration or accounting skills and theoretical understanding was rated highest in expected importance, while research methodology and statistics had the lowest mean score among both the technical skills and all skills in the questionnaire (ranked 31st). Regarding the perceived level of development during the studies, the mean score of financial administration or accounting skills and theoretical understanding was the highest, also the highest of all skills in the questionnaire (ranked 1st), and the knowledge of different fields and understanding the big picture had the lowest mean score among the technical skills.

The absolute differences between the mean scores were mainly positive and statistically significant. Verification tests fully supported the t-test results regarding the statistical significance. A positive difference means that the expected importance of a skill area is, on average, higher than the perceived level of development during studies. As the difference was statistically significant, a gap was detected between the expected importance and the perceived level of development in the skill areas of financial administration or accounting skills and theoretical understanding, knowledge of different fields and understanding the big picture, juridical knowledge and foreign languages. The only exception in the technical skills was research methodology and statistics, where the absolute difference was slightly positive but not statistically significant, so there was no gap between the expected importance and the perceived development relating to this skill.

The ranks of technical skills were quite low in terms of both expected importance and perceived development, except financial administration and accounting skills and theoretical understanding, ranked as the most comprehensively developed skills in accounting education. It means that in relation to other skills in the questionnaire, technical skills overall were not perceived as especially important in the future or particularly comprehensively developed during accounting studies. Cronbach’s alpha values for technical skills were 0.63 and 0.64, based on the variables of expected importance and of perceived development, respectively, and those values were interpreted as moderate but acceptable levels of internal consistency (Biggs et al., 2001; Tuan et al., 2005).

Technological and data processing skills

The group of technological and data processing skills included all skills related to technology, data and IT systems. For the purpose of this study and for highlighting the digital transformation occurring in the field, we preferred to examine technology-related skills as a separate group. The results are presented in Table 4, arranged by the absolute difference.

The mean scores of expected importance in all technological and data skills were above 3, but those of perceived development were mainly below 3. General technological skills and understanding were rated, on average, as the most important and the most comprehensively developed skills among the technological and data skills. However, relative to all skills in the questionnaire, the mean score of perceived development of ‘General technological skills and understanding’ was not remarkably high (ranked 20th). Different IT systems were also rated as highly important. Programming skills were rated as the least important of the technological and data skills and almost the least important of all skills (ranked 30th). Those skills were also rated as almost the least comprehensively developed of all skills (ranked 30th). The only skill with a lower rank in perceived development was knowledge related to robotics and AI (ranked 31st). The ranks of different IT systems and general technological skills and understanding were quite high in expected importance, but all other ranks were quite low. Thus, in relation to all skills in the questionnaire, many technological and data skills were, surprisingly, not deemed especially important in the future, and all technological and data skills were not perceived as particularly comprehensively developed in accounting education.

The absolute differences between the mean scores were all positive and statistically significant, so expectation–performance gaps were found in all technological and data processing skills. Verification tests fully supported the t-test results regarding the statistical significance. The largest absolute difference between expected importance and perceived development was found in knowledge related to robotics and AI. Cronbach’s alpha values for technological and data processing skills were 0.79 and 0.89, based on the variables of expected importance and of perceived development, respectively, and both values were regarded as indicators of rather high internal consistency.

Intellectual skills

According to IES 3, intellectual skills include those related to problem solving, professional judgement, reasoning and critical analysis, among others (IFAC, 2014). Thus, all skills related to problem solving, decision making and reasoning were classified under the group of intellectual skills, which are professional skills by nature. The results for this skill group are presented in Table 5, arranged by the absolute difference.

All skills in this group were regarded as very important in the future as all mean scores were above 4, most of them even above 4.50. Critical thinking was rated as the most important skill in the future compared with other reasoning and decision-making skills. Their ranks in expected importance were among the top 10 of all skills, except logical and mathematical reasoning (ranked 18th). The mean scores of perceived development were slightly lower, above 3.50 but below 4 in all skills in this group. Critical thinking was rated as the most comprehensively developed skill, while decision making was rated as the least comprehensively developed in this skill group. Critical thinking and problem-solving skills were ranked among the top five most comprehensively developed skills, while the rest were ranked slightly lower among all skills in the questionnaire.

All absolute differences were positive and statistically significant in this skill group, too. Verification tests fully supported the t-test results. Thus, there seems to be an expectation–performance gap related to each intellectual skill defined in the questionnaire. For this group, Cronbach’s alpha values were 0.73 and 0.81, based on the variables of expected importance and of perceived development, respectively, and both values were interpreted as acceptable levels of internal consistency.

Social and communication skills

The group of social and communication skills included all skills related to interactions with other people. These are also professional skills by nature. The results concerning this skill group are presented in Table 6, arranged by the absolute difference.

Almost all skills were rated at least quite important by future importance (mean scores above 4), except emotional intelligence, whose mean score was rated lower (3.67) and ranked 29th among all skills. Although the mean scores of expected importance were quite high in almost all skills, their positions (ranks) relative to all other skills in the questionnaire were not remarkably high in this group. In this group, teamworking and interaction were rated as the most important skills for the future, ranked 11th among all skills.

The mean scores of perceived development varied to some extent in this group, with teamworking and interaction rated (mean score of 4.00) and ranked (3rd) as the most comprehensively developed skills, and customer service rated (2.66) and ranked (29th) as the least comprehensively developed skill in this group. The overall rankings concerning perceived development were not remarkably high, except for teamworking and interaction and written communication skills, which were ranked among the top 10 most comprehensively developed out of all skills in the questionnaire.

The absolute differences of social and communication skills were all positive and statistically significant, so expectation–performance gaps were identified in this group, too. Verification tests fully supported the t-test results concerning the statistical significance. The absolute difference was the most extensive in customer service skills since they were rated as quite important in the future but not so comprehensively developed during accounting studies. Cronbach’s alpha values for social and communication skills were 0.80 and 0.85, based on the variables of expected importance and of perceived development, respectively, with both values indicating rather high internal consistency.

Other professional skills

The rest of the professional skills were classified under the group of other professional skills. The skills in this group highly varied but shared a professional nature. Some can also be regarded as personal attributes or traits. The results for this group are presented in Table 7, arranged by absolute difference.

Most of the mean scores in this group were quite high (above 4), except the mean score for media literacy and criticism (3.69), so they were perceived as quite important skills in the future. Self-improvement and learning skills were rated as the most important in this group and ranked as the most important among all skills in the questionnaire. This group included both the top two skills: self-improvement and learning, and self-management skills, ranked as the most important in the future among all skills defined in the questionnaire. Initiative was also among the top 10 skills by expected importance.

The mean scores of perceived development were mainly below 4, except in initiative skills. It was the highest rated (4.07) and ranked (2nd) among the other professional skills. General leadership was rated the lowest among the other professional skills in terms of perceived development (2.98) and was ranked 27th among all skills. The other professional skills’ rankings in perceived development varied to some extent; five skills were among the top 10 most comprehensively developed skills (initiative, self-improvement and learning, self-management, working under pressure, and adaptability and flexibility), but others were ranked quite low.

The absolute differences of the other professional skills were all positive and statistically significant, so expectation–performance gaps were identified in this group as well. Verification tests fully supported the t-test results. The largest absolute difference was found in negotiating skills, which were rated as rather important for the future but not very comprehensively developed during accounting studies. Cronbach’s alpha values for these other skills were 0.85 and 0.86, based on the variables of expected importance and of perceived development, respectively, and both values were regarded as indicators of high internal consistency.

Additional analyses

In addition to the main analysis, we examined whether accounting students in different demographic subgroups experienced expectation–performance gaps differently. First, Mann–Whitney tests were conducted to find whether the subgroups had similar expectation and perception distributions in each skill (i.e. whether they came from populations with the same distribution). Next, if there were some differences in the distributions, gap analyses were conducted for each student subgroup separately to determine whether the student groups experienced different expectation–performance gaps. We used the significance level of 0.05 (5%) for all additional analyses. The main results of our additional analyses are summarised in Appendix 3.

University and UAS students

To address the sample characteristics (a higher response rate in the UAS than in the other two universities), we first conducted additional analyses for subgroups of university students (n = 73) and UAS students (n = 35). The results showed statistically significant differences between those groups in the distributions of seven skills, considering the expected importance, and six skills, considering the perceived development. The results of the gap analyses suggest that university students experience significant gaps between expected importance and perceived development in all defined skill areas (all p-values of paired t-tests and verification tests were < .05), and UAS students experience significant gaps in almost all skills. In the subgroup of UAS students, there were minor differences between the results of paired t-tests and non-parametric verification tests regarding the significance levels. According to the results of the paired t-tests, active listening was the only skill in which significant gaps were not detected (paired t-test t(34) = 1.31, p = .199; signed-rank z = 1.12, p = .262), but verification tests indicated that the gap was also not significant in emotional intelligence (paired t-test t(30) = 2.08, p = .046; signed-rank z = 1.83, p = .068).

Regarding the university and UAS students, the differences between the main analysis and the additional analyses concerned the skills related to research methodology and statistics, active listening and emotional intelligence. In the whole sample, it seemed that the students did not experience a gap between expectations and performance in the skills related to research methodology and statistics. However, for the subgroup of university students, the results showed a significant gap, but this was the only case where the absolute difference was negative (absolute difference = −0.36; paired t-test t(72) = −2.18, p = .033; signed-rank z = −2.13, p = .033), which meant that the university students seemed to think that they learned research methodology and statistical skills more comprehensively than they expected those skills to be important. Since UAS students experienced the gap the other way around (importance higher than performance), in the whole sample, it seemed that a gap did not exist. In turn, UAS students did not experience an expectation–performance gap in active listening skills, even though a gap was detected in the whole sample. According to the mean scores, UAS students rated the perceived development higher (mean score = 4.03, n = 35) than university students did (mean score = 3.16, n = 73), which would explain the smaller absolute difference in the subgroup of UAS students. In emotional intelligence, non-parametric tests showed no significant gaps in the subgroup of UAS students, even though a gap was detected in the whole sample. Based on the mean scores, UAS students rated the expected importance of emotional intelligence lower (mean score = 3.35, n = 31) than university students did (mean score = 3.82, n = 67), making the absolute difference narrower in this subgroup. Apart from these three skills, these additional analyses supported the results of the main analysis well and showed that despite some differences in expectations or perceptions, university and UAS students experienced most gaps similarly.

Degree levels

We then conducted an additional analysis for subgroups according to their degree levels: bachelor-level students (n = 57) and master-level students (n = 51). According to Mann–Whitney tests, there were significant differences in the expected importance of six skills and the perceived development of four skills between bachelor’s and master’s degree students. However, the gap analysis was mostly in line with that of the whole sample (gaps experienced in all other skills except research methodology and statistics). The exception was in foreign language skills, where (according to the verification test) master-level students did not experience a significant gap between expected importance and perceived development (signed-rank z = 1.80, p = .072; paired t-test t(49) = 2.02, p = .049). The mean score of expected importance was slightly lower in the master-level subgroup (3.76, n = 50) than in the bachelor-level subgroup (3.98, n = 57), which made the absolute difference (gap) narrower and not statistically significant. Apart from this skill, the additional analysis supported the main analysis very well and showed that despite slight differences in expectations and perceptions between the two subgroups of students by degree level, they still experienced the gaps rather similarly.

Gender

Possible gender differences between men (n = 58) and women (n = 48) were also analysed. According to Mann–Whitney tests, there were significant differences in the distributions of the expected importance of 15 skills and the perceived development of five skills between women and men. For many skills, women seemed to rate the expected importance, on average, higher than men did. However, the gap analysis was fully in line with that of the whole sample – both men and women experienced statistically significant gaps in all other skills except research methodology and statistics. In research methodology and statistics, the absolute difference (of the mean scores) of the subgroup of women was only 0.09 (paired t-test t(46) = 0.44, p = .660; signed-rank z = 0.72, p = .471), while that of the subgroup of men was −0.28 (paired t-test t(57) = −1.50, p = .139; signed-rank z = −1.31, p = .190).

Work experience

Finally, we conducted additional tests for student subgroups, divided into those with no work experience (n = 36) and with some work experience (n = 72) of accounting or financial administration-related tasks. Mann–Whitney tests showed significant differences in the expected importance of two skills and the perceived development of two skills between the students with accounting work experience and those without such experience. In the subgroup of students with some work experience, the results of the gap analysis were fully consistent with those of the whole sample (gaps experienced in all other skills except research methodology and statistics), but in the subgroup of students with no work experience, the tests showed significant gaps in all other skills except research methodology and statistics, financial administration or accounting skills and theoretical understanding, and emotional intelligence. However, there were minor differences between the results of paired t-tests and of non-parametric verification tests regarding the significance levels. Based on both tests, similar to the results of the gap analysis of the whole sample and of the subgroup of students with some experience, there were no significant gaps between expectations and performance in research methodology and statistics (absolute difference = 0.17; paired t-test t(34) = 0.88, p = .384; signed-rank z = 1.11, p = .269). In the subgroup of students with no experience, the paired t-tests also showed no significant gap in financial administration or accounting skills and theoretical understanding (absolute difference = 0.31; paired t-test t(35) = 1.82, p = .078; signed-rank z = 2.32, p = .021), and the non-parametric verification tests showed no significant gap in emotional intelligence (absolute difference = 0.50; signed-rank z = 1.78, p = .076; paired t-test t(33) = 2.31, p = .027).

Regarding the students with and without accounting work experience, the differences between the main analysis and the additional analyses concerned skills related to financial administration or accounting skills and theoretical understanding, and emotional intelligence. In financial administration or accounting skills and theoretical understanding, the students with no experience rated expected importance very slightly lower (mean score = 4.47, n = 36) and rated perceived development slightly higher (mean score = 4.17, n = 36) than the students with some work experience did (mean scores of 4.54 and 4.07, respectively, n = 72), which would explain the narrower and not statistically significant gap in the subgroup of students with no work experience. In emotional intelligence, the students with no work experience rated expected importance (mean score = 3.41, n = 34) lower than their counterparts with experience did (mean score = 3.81, n = 64), which would explain the smaller, non-significant gap in this subgroup. Despite these differences, additional analyses once again supported the results of the main analysis well and showed only minor differences in the experienced expectation–performance gaps between the students with accounting work experience and those without such experience.

Discussion

In this study, we addressed accounting students’ expectations and perceptions concerning an extensive range of skills and examined possible gaps between their expectations of the skills’ importance and perceptions of skill development in accounting programmes. The data for this study were collected via a survey that targeted Finnish accounting students from three higher education institutions. Overall, in the main analysis, we found that the students experienced expectation–performance gaps related to 30 out of the 31 skills defined in the survey – both technical and professional skills. However, additional analyses also revealed gaps in the 31st skill – research methodology and statistics. The existence of such gaps is similar to the findings of Dolce et al. (2020), Kavanagh and Drennan (2008) and Towers-Clark (2015), who all conclude that many skills that are considered important are not well developed or paid enough attention in accounting programmes.

The accounting students expected all defined skills, on average, to be somewhat important in their future work, but multiple professional skills and a few technological skills were ranked among the most important ones. Self-improvement and learning, self-management (time management included) and critical thinking, all belonging to professional skills, were rated as the most important skills, consistent with the findings of Kavanagh and Drennan (2008) and Towers-Clark (2015), who also conclude that skills in areas such as continuous learning, analysis and critical evaluation or time management are regarded as the most important ones by students. The results suggest that students expect most professional skills to be highly important for the accounting profession besides technical skills, supporting the research results reported by Kavanagh and Drennan (2008). General technological skills were ranked very high among all skills, but skills related to emerging technologies (robotics and AI) were ranked rather low; however, the mean score of the expected importance of those skills was still above 3.70. Thus, the results suggest that students expect emerging technology skills to be rather important in the future but not (at least, not yet) as important as many other technical, technological and professional skills.

As the gap analyses indicated, the students mainly perceived the skills as underdeveloped or inadequately taught in accounting studies compared with their expected importance. This finding is in line with the conclusions of Kavanagh and Drennan (2008), as well as of De Lange et al. (2006), who suggest that both technical and professional skills should be given greater emphasis in accounting programmes. The results might raise concerns, especially about the development of technological skills, since they were all ranked low among all skills, and the deficiencies (gaps) were rather extensive. The students perceived knowledge related to robotics and AI (i.e. emerging technologies) as the least comprehensively developed area among all skills. Thus, we point out that skills related to data processing, digital systems and (emerging) technologies are underdeveloped in accounting studies and should receive more attention as the accounting profession and work continue to evolve. Although an investigation of the content of the current accounting curricula is beyond the scope of this study, we believe that it is safe to state that all higher education institutions offer courses that cover some software or other technological solutions. Thus, we believe that all accounting students become acquainted with at least some basic software or IT systems during their studies, but gaining more in-depth knowledge might – at least for now – require increased personal interest and optional advanced courses, also across disciplines.

The perceptions about the development of technical and professional skills varied, with financial administration or accounting skills and theoretical understanding being the most comprehensively developed among all skills, but with some technical and professional skills being developed rather poorly (e.g. customer service, general leadership skills). Traditionally, these least developed skills have not been at the core of accounting programmes, and in general, some professional skills might be difficult to teach. Traditional university teaching and studying modes, such as lecturing, might even be unsuitable or insufficient for professional skill development (Virtanen & Tynjälä, 2019). Thus, it should be carefully analysed how these skills could be incorporated into the curricula so that they would foster the advancement of future accounting professionals in their careers but not at the expense of diminishing technical skills.

Additional analyses showed that some student characteristics might be associated with the gaps experienced by the students. Analysing the overall dataset seemed to reveal no significant gap related to research methodology and statistics, but further analysis indicated that student subgroups (UAS/university students) experienced the gap differently and significantly. The skill area of research methodology and statistics was exceptional; it was the only skill that was perceived as even overdeveloped – but only by university students. Prior research also suggested that university students or graduates regarded teaching or training in research or statistical skills as aligned with their expectations or even overdeveloped compared with their importance and that a substantial increase in the emphasis on such skills would not be required in university-level accounting education (De Lange et al., 2006; Kavanagh & Drennan, 2008; Towers-Clark, 2015). However, our findings indicated that research methodology and statistics might warrant a broader focus in study programmes of UASs. Our additional analyses also suggested that UAS students did not experience gaps in active listening skills or emotional intelligence, while university students did. When considering the varying degrees of emphasis at the university and the UAS levels (i.e. universities typically highlight theoretical knowledge more than UASs, which typically focus more on practical knowledge), these different views among the studied subgroups can be considered expected findings. In turn, bachelor-level students and master-level students seemed to experience the gaps similarly; however, additional analyses provided some evidence that master-level students did not experience a significant gap in foreign language skills. Both subgroups also perceived no significant gap in research methodology and statistics. Finally, there were a few differences in the experienced gaps between students who had some accounting work experience and those who lacked it. The latter subgroup did not perceive significant gaps in financial administration or accounting skills and theoretical understanding, as well as in emotional intelligence, while the former subgroup did. However, both subgroups perceived no significant gap in research methodology and statistics. Overall, the differences between subgroups were minor, but it seemed reasonable that some small differences might occur due to varying backgrounds and levels of experience.

The transformation and changing skill requirements are important issues to be considered in higher education institutions as they aim to prepare students for accounting work. The future of accounting education has been critically discussed (e.g. Albrecht & Sack, 2000; Rebele, 2002), and it has been argued that accounting education needs updating if it aims to meet the needs of the changing profession (Deppe et al., 1991). Thus, accounting education must address the shift in skill requirements, and the accounting curricula should be revised to ensure that they meet the needs of the accounting practice and environment (Chaplin, 2017; Tan & Laswad, 2018). As technology develops and emerging technologies are likely to transform accounting work, accounting education providers ought to keep up with digitalisation and technological development and equip students with the necessary knowledge and qualifications for future accounting work, especially since it seems that students currently perceive that they do not learn those skills comprehensively enough. Co-operation between accounting education and technological education or programmes could be one way to fulfil this need.

Although higher education aims to prepare students for work, and incorporating important skills in accounting programmes’ agenda is essential, learning must continue after formal education. Howieson (2003) suggests that continuing professional development becomes more significant, in parallel with the changes in knowledge and technology. Accounting students seemed to recognise this need for continuous learning and improvement since self-improvement and learning skills were rated as the most important of all in this study. These skills, along with self-management skills, are most probably improved to some extent in all university programmes as the courses include different kinds of learning activities and assignments, and as students are required to follow the timetables and manage their own workloads throughout their studies. Universities might also offer support services or support groups for students to foster the development of these skills. Furthermore, the COVID-19 pandemic has developed or at least increased the importance of this kind of self-management among students as they have been compelled to study remotely. Thus, peer-to-peer support and interaction with the teachers as well have changed a great deal. However, it might be difficult to emphasise these skills in accounting courses more than just by incorporating them into learning activities and assignments, at least without taking time from teaching the requisite technical accounting skills and knowledge. It could also be noted that these are the kinds of skills that are most probably developed as well outside the universities and throughout anyone’s lifetime.

Conclusion

Changes in the global business environment and the technological evolution are likely to transform accounting work and modify the requirements of the profession. In this study, we aimed to find out the extent to which accounting students’ expectations about the future importance of various skills in the practice of the profession match their perceived development of those skills in accounting studies. We also intended to analyse their perceptions regarding different types of skills and possible individual characteristics associated with their perceptions. The results confirmed the presence of gaps between students’ expectations and performance in multiple skill groups. Slight differences in the expected importance and perceived development were identified among various groups of skills (technical, technological and professional skills), but expectation–performance gaps were found in all skill groups. Some individual characteristics (university, degree level and work experience) were found to be associated with the gaps experienced by the students – however, differences between the subgroups with varying characteristics were found only in a few skill areas.

In sum, the key contributions of this study are as follows. First, theoretically, this study extends the research literature concerning the expectations about the future of accounting work and the expectation–performance gaps related to various skills. The study offers an up-to-date understanding of accounting students’ perceptions, providing further evidence of the existence of expectation–performance gaps, meaning that students perceive multiple key skills as underdeveloped in accounting education in relation to their expected importance. In terms of methodological contributions, this study covers a comprehensive list of both technical and professional skills, as well as multiple technological skills, even one related to emerging technologies. The understanding of the gaps related to such a wide range of skills could help accounting education providers around the world design accounting curricula to respond to changing requirements of the profession. Moreover, Finland represents a new context for studying these issues, and the insights gathered in this setting might also reflect the situations in other countries, especially in the Nordic countries. At least, the Nordic countries share the reputation of being pioneers in digital performance; Finland, Denmark and Sweden have been ranked the top three countries in the 2020 and the 2021 European DESI studies (European Commission, 2020, 2021), and Iceland and Norway were the top non-EU countries in I-DESI 2020 (EU, 2021). In this light, our finding that students experience wide gaps in skills related to data processing, digital systems and (emerging) technologies is especially interesting. One possible explanation for this is that the reputation of Finland among the pioneering countries stems from Finnish companies and their early adoption of digital technologies, not from universities or from academia in general. In the field of accounting, especially in cost accounting, the companies historically have had a major impact on accounting practices (see, e.g. Kaplan, 1984), whereas research – and thereby higher education – may slightly lag behind.

Finally, the study contributes to the practice by suggesting skill areas that probably need further emphasis in accounting education. These recommendations can help higher education institutions design their accounting curricula accordingly. However, it must be kept in mind that in this study, we examined this issue from the students’ perspective, and further research from multiple angles is needed. For example, the skills related to research methodology and statistics were perceived as even overdeveloped by the university students, but accounting educators should not jump to conclusions and diminish the scope of these skills in the curricula based on this finding. Overall, as the transformation can be regarded as universal, the understanding of skill gaps and potential deficiencies in accounting education is crucial for educators internationally.

Limitations and recommendations for future research

We acknowledge some limitations regarding this study. First, the sample size and the response rate were relatively low. The relative response rate was much higher among the UAS students than among the other university students, which might cause the overall results to be somewhat biased. However, according to Nulty (2008), an occurrence of some sampling error or sample bias can be reasonably expected in any survey that uses a sample of a population. Our additional analyses indicated some differences in expectations and perceptions between university and UAS students, even though they were all pursuing accounting or financial administration degrees. As the results also suggest, accounting education programmes might not be identical in different universities. These issues may limit the generalisability of the results. It must also be noted that all our conclusions are drawn from students’ perspectives and based on their perceptions, so the expectations might not represent the actual future importance of different skills, and the perceptions of development might not fully represent the content and extent of the skills included in accounting curricula. Furthermore, there might be a non-response bias of lower achieving or less motivated students. Motivational factors (e.g. the respondents’ interest in the survey topic) are generally considered typical functions of non-response bias in surveys (Fricker & Tourangeau, 2010). At the same time, prior research also shows that higher quality responses are received from the more motivated respondents and from respondents with intrinsic motivation (see, e.g. Medway & Tourangeau, 2015). Nevertheless, due to these limitations, the results should be interpreted with caution.

It must also be taken into account that the data were collected before the COVID-19 pandemic caused restrictions and affected daily life in Finland, so the pandemic was not considered in the responses. The pandemic may have affected students’ expectations of the importance of some skills, most likely technological skills, as it seems that the digital transformation has accelerated due to the pandemic (Tsiligiris & Bowyer, 2021). However, students may have learned some basic technological skills more comprehensively during the pandemic as the rapid shift to online courses has forced them to use digital technology (Ng & Harrison, 2021). Nevertheless, we believe that the responses and our study’s results are still valid since the pandemic has most likely, at most, widened the skill gap as technological skills are expected to be even more important in the future and the more comprehensive development most likely applies only to basic technological skills, not the skills related to emerging technologies or various software. Overall, accounting graduates are expected to face changes in the business environment due to various circumstances, which also include the effects of pandemics (Edeigba, 2022).

As the transformation will probably further change the accounting field and profession, we suggest some areas for future research. It would be interesting to study the perceptions and experiences of graduates who currently work in accounting to determine whether they experience expectation–performance gaps differently than when they were studying accounting. Comparisons among the expectations or perceptions of different stakeholder groups are of further interest as well, especially if current technological developments and skills related to emerging technologies are taken into account. Considering various stakeholder groups, such as students, practitioners or educators, it would be valuable to investigate what kinds of attributes or characteristics possibly affect their expectations. Additionally, future studies using lists of skills could specify at least technical accounting or financial administration-related skills or technological skills in more detail to gather more precise data. For instance, bookkeeping and financial statement skills, cost accounting skills, budgeting skills or skills related to taxation could be separated from the overall accounting and financial administration skills, and in technological skills, different IT systems could be specified. Lastly, examining the actual or intended skill contents of accounting courses and matching them to stakeholders’ expectations and perceptions could be one more area of interest for future research.

Acknowledgements

The authors are grateful to the university contact persons for their assistance in the data collection, Jan Pfister for the insightful discussion and feedback at the Accounting Tutorial 2022 (Oulu, Finland), as well as Pasi Syrjä and Terhi Chakhovich for their help in designing and developing this paper. The authors also thank the Associate Editor and the anonymous reviewers for their constructive and valuable comments that helped improve the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 These skills have also been called ‘generic’, ‘key’, ‘soft’, ‘transferable’ or ‘employability skills’. For further information, see the Literature review section.

Appendix 1.

Skill list of the questionnaire

Table

Skill	Examples of references
Skills studied in prior research
Financial administration/accounting skills and theoretical understanding	Jackling and De Lange (2009)Kavanagh and Drennan (2008)Usoff and Feldmann (1998)(also referred to as ‘key accounting skills’ and ‘accounting knowledge’)
Juridical knowledge	Usoff and Feldmann (1998)(referred to as ‘law’)
Research methodology and statistics	Kavanagh and Drennan (2008)Klibi and Oussii (2013)Towers-Clark (2015)(also referred to as ‘research’, ‘practical research’ and ‘the use of quantitative methods & statistics’)
Different IT systems	Arquero Montaño et al. (2001)Hassall et al. (2003)Howcroft (2017)Spraakman et al. (2015)(also referred to as ‘relevant/IT software’)
General technological skills and understanding	De Lange et al. (2006)Jackling and De Lange (2009)Usoff and Feldmann (1998)Spraakman et al. (2015)Towers-Clark (2015)(also referred to as ‘computer skills’, ‘computing and IT’, ‘IT skills’, etc.)
Analytical reasoning	Crawford et al. (2011)Kavanagh and Drennan (2008)Towers-Clark (2015)(referred to as ‘analytical/analysis & critical evaluation’ and ‘analytical skills’)
Critical thinking	Arquero Montaño et al. (2001)Crawford et al. (2011)Hassall et al. (2003)Howcroft (2017)Kavanagh and Drennan (2008)Klibi and Oussii (2013)(referred to as ‘critical analysis/thinking’ and ‘critical reasoning skills’)
Logical and mathematical reasoning	Usoff and Feldmann (1998)(referred to as ‘logical reasoning’)
Teamworking and interaction	Arquero Montaño et al. (2001)De Lange et al. (2006)Hassall et al. (2003)Howcroft (2017)Jackling and De Lange (2009)Kavanagh and Drennan (2008)Klibi and Oussii (2013)Towers-Clark (2015)
Emotional intelligence	Daff et al. (2012)
Networking	Gammie et al. (2002)
Customer service	Kavanagh and Drennan (2008)
Negotiating	Kavanagh and Drennan (2008)
Oral communication and interaction	Arquero Montaño et al. (2001)De Lange et al. (2006)Hassall et al. (2003)Howcroft (2017)Jackling and De Lange (2009)Kavanagh and Drennan (2008)Towers-Clark (2015)Usoff and Feldmann (1998)(also referred to as ‘oral/verbal expression’)
Written communication	Arquero Montaño et al. (2001)De Lange et al. (2006)Hassall et al. (2003)Howcroft (2017)Jackling and De Lange (2009)Kavanagh and Drennan (2008)Towers-Clark (2015)Usoff and Feldmann (1998)
Active listening	Arquero Montaño et al. (2001)Crawford et al. (2011)Hassall et al. (2003)Howcroft (2017)Kavanagh and Drennan (2008)Klibi and Oussii (2013)(also referred to as ‘effective listening’ and ‘listening skills’)
Foreign languages	Kavanagh and Drennan (2008)Klibi and Oussii (2013)
General leadership	Kavanagh and Drennan (2008)Klibi and Oussii (2013)Usoff and Feldmann (1998)
Problem solving	Arquero Montaño et al. (2001)Hassall et al. (2003)Howcroft (2017)Klibi and Oussii (2013)Jackling and De Lange (2009)Kavanagh and Drennan (2008)Towers-Clark (2015)Usoff and Feldmann (1998)
Decision making	Kavanagh and Drennan (2008)
Adaptability and flexibility	Jackling and De Lange (2009)Kavanagh and Drennan (2008)
Skills not directly studied but the idea obtained from prior research
Knowledge of different fields, understanding the big picture	De Lange et al. (2006) using ‘interaction between accounting and other disciplines’
Programming	Spraakman et al. (2015) mentioning programming in the literature review
Data processing	Spraakman et al. (2015) mentioning word processing in the literature review
Media literacy and criticism	Klibi and Oussii (2013) using ‘critical reading’
Self-management (e.g. organising and managing time and workload)	Arquero Montaño et al. (2001) using ‘organising workloads', Crawford et al. (2011) using ‘time management', Dolce et al. (2020) using ‘emotional self-regulation’
Self-improvement and learning	Arquero Montaño et al. (2001), Kavanagh and Drennan (2008) and Klibi and Oussii (2013) using ‘effective/active learning’
Working under pressure	‘Work under pressure’ mentioned in the qualitative comments of Towers-Clark (2015)
Initiative skills	Crawford et al. (2011) mentioning initiative as a personal skill in the literature review
New skills
Knowledge related to robotics and artificial intelligence
Innovation skills and innovativeness

Appendix 2.

Skill rankings

Table

Rank	Expected importance	Rank	Perceived development
1	Self-improvement and learning	1	Financial administration/accounting skills and theoretical understanding
2	Self-management (organising, managing time and workload)	2	Initiative skills
3	Critical thinking	3	Teamworking and interaction skills
4	General technological skills and understanding	4	Critical thinking
5	Analytical reasoning	5	Problem solving
6	Problem solving	6	Self-improvement and learning
7	Initiative skills	7	Self-management (organising, managing time and workload)
8	Decision making	8	Written communication
8	Different IT systems	9	Working under pressure
10	Financial administration/accounting skills and theoretical understanding	10	Adaptability and flexibility
11	Teamworking and interaction skills	11	Logical and mathematical reasoning
12	Oral communication and interaction	12	Analytical reasoning
13	Working under pressure	13	Decision making
14	Adaptability and flexibility	14	Oral communication and interaction
15	Negotiating	15	Networking
16	Knowledge of different fields, understanding the big picture	16	Active listening
17	Written communication	17	Juridical knowledge
18	Logical and mathematical reasoning	17	Research methodology and statistics
19	Data processing	19	Foreign languages
20	Networking	20	General technological skills and understanding
20	Customer service	21	Innovation skills and innovativeness
22	Active listening	22	Knowledge of different fields, understanding the big picture
23	Innovation skills and innovativeness	23	Media literacy and criticism
24	Juridical knowledge	24	Negotiating
25	General leadership skills	25	Different IT systems
26	Media literacy and criticism	26	Data processing
27	Foreign languages	27	General leadership skills
28	Knowledge related to robotics and artificial intelligence	28	Emotional intelligence
29	Emotional intelligence	29	Customer service
30	Programming	30	Programming
31	Research methodology and statistics	31	Knowledge related to robotics and artificial intelligence

Appendix 3.

Summary of expectation–performance gaps related to skills

Table

		University		Degree level		Gender		Work experience
Skill	Whole sample	UAS students	University students	Bachelor-level students	Master-level students	Women	Men	Students with work experience	Students without work experience
Financial administration /accounting skills and theoretical understanding									X
Juridical knowledge
Research methodology and statistics	X			X	X	X	X	X	X
Knowledge of different fields, understanding the big picture
Different IT systems
General technological skills and understanding
Programming
Data processing
Knowledge related to robotics and artificial intelligence
Analytical reasoning
Critical thinking
Logical and mathematical reasoning
Teamworking and interaction
Emotional intelligence		X							X
Networking
Customer service
Negotiating
Oral communication and interaction
Written communication
Active listening		X
Foreign languages					X
Media literacy and criticism
General leadership skills
Self-management (organising, managing time and workload)
Working under pressure
Problem solving
Decision making
Adaptability and flexibility
Self-improvement and learning
Innovation skills and innovativeness
Initiative skills

Note: X = no significant gaps experienced according to either paired t-test or verification test, at a significance level of 0.05 (5%)