Gap analysis of future employee and employer on soft skills

Abstract

BACKGROUND:

Soft skills have become more necessary than ever in today’s labour market, and their development has become an increasingly key area for companies’ HR departments. Employees with the soft skills required for a given job can perform the tasks assigned to them more efficiently and successfully, therefore all those involved in the process can consider the completion of the task as a positive experience. By strengthening the employees’ soft skills, companies can improve their corporate culture, their market performance and thus their competitiveness.

METHODS:

The authors conducted a multi-year research in Hungary, the first part of which was a quantitative study to analyse the soft skills of young people leaving school, their awareness of employers’ expectations and the opportunities and tools they consider useful for developing these skills. The second part of the research involved the other side, i.e. the employers, to assess their expectations of the prospective employees’ soft skills and to explore the development opportunities that employers provide to strengthen these skills.

RESULTS:

The results of the two questionnaire surveys confirmed that both sides are aware of the soft skills needed in the labour market, although the market participants are not always in agreement about these needs. However, the development of skills, even though they enhance the market competitiveness of the employee and the employer, is not really in line with market expectations.

Keywords

Soft skills hard skills workers labour market

Dr. habil Tímea Juhász, PhD: Budapest Business School, Department of Methodology for Social Studies. Since 2019, she has been working as a senior researcher at Budapest Business School. She is the author of nearly 200 publications, her articles have been published on 4 continents. Her research areas include Knowledge Management, Reconciliation of work and private life, The relationship between sport and management, Generation, Workplace stress and conflicts, Career Planning and Digital competence.

Dr. Gabriella Horváth-Csikós, PhD: Budapest Business School, Department of Languages for International Business. She has been in higher education for two decades. Apart from being a lecturer she supports university students in research competitions, acts as their supervisor, and also she is head of a Mentorship Program of the university. Her research areas include Knowledge Management, Mentoring, Language Mentoring, Developing soft skills, Necessity of soft skills on today’s labour market.

Dr. Tamás Gáspár, PhD: Budapest Business School, Department of International Economics. He participates in the development of talented students by mentoring students’ research papers, participating in the organisation of research competitions and of the College of Advanced Students as well as mentoring PhD students. He is a founding member of the Doctoral School and member of the Doctoral Council. His research areas include: the conceptual and methodological questions of strategic foresight, the strategic issues and methodology of international economics, mainly in terms of global value changes and input-output table and the research and development of the growing up generation by the complex needs of the future.

1 Introduction

To be successful and stay successful in the workplace, one of the most important things is to be able to adapt to change, as you may suddenly have to change your working environment, your company strategy, or work with different people, different age groups, different schedules. Therefore, the key is not just whether we have the skills that are necessary and indispensable in each situation, but whether we will be able to learn new skills and adapt to changing circumstances in the first place [1]. Superior performance in the workplace can be derived from the right combination of soft and hard skills. Soft skills, combined with hard skills, complement each other perfectly and are the only way to achieve the best results and sustainable long-term success in the workplace [2]. Some research [3] has shown that some soft skills are more highly expected than hard skills. Their results are consistent with previous research [3, 4] showing that some soft skills are as important or even more important than hard skills according to employees, and that employees perceive employers to value soft skills as non-systemic, closely related skills.

We all know that the acquisition of soft skills is a process and typically not a short one. According to Robles [5] soft skills encompass traits, attitudes and behaviours and are not a measure of technical aptitude or knowledge. Soft skills are harder to define and more complex to articulate than hard skills, as they are less tangible, non-technical and not personality-specific skills.

The role of soft skills in the competitiveness of employees and thus in the competitiveness of employers is no longer questionable. It is therefore no coincidence that the authors wanted to know to what extent market players are aware of which soft skills are valuable in the labour market, which can be closely related to each other, how they can be developed and in which environments. The present paper seeks to answer these questions, among others, by presenting some of the results of a three-year research study conducted in Hungary, involving participants from both sides of the market, i.e. future employees, and employers of today.

1.1 Background

Defining soft skills is not an easy task. Soft skills are psychological traits that inform how people learn, think and act. Measuring soft skills is important because they are variables that allow individuals, in this case students, to anticipate their professional future and career orientation, but tools to assess soft skills are often lacking in educational settings [6]. Hard skills are easier to define and measure than soft skills [7]. As soft skills are not so easily acquired, soft skills are typically learned over time as individuals gain more knowledge and experience on the job [8]. All industries require specific skills, and none is an exception. In many different sectors, workers need both hard and soft skills.

However, the sources of the skill set are not only the qualifications, diplomas and degrees that can be acquired through formal education, but also the ever-changing and enriching range of knowledge and skills that can be acquired in non-formal and informal learning settings [9]. We all need soft skills to be successful in education, at work and in our personal lives. Young people learn soft skills primarily at home, in their own families, by observing their family members, by observing others, and they continue this process later, entering the education system, from primary school, through to university and beyond, in their workplaces. There is a study [10] that argues that young people acquire soft skills primarily from school during their schooling. The research findings of Rajabzadeh show that undergraduates become more confident in the teamwork during seminars over time in case older, senior students are in the same group with them, as senior students were more likely to take a leadership role in the task and by their own admission, they perform better as a group member as a result [11]. Their study provides further insights into the different group work experiences of university engineering students, describing how their soft skills develop over the course of the semester, how students engage in experiential learning (learning by doing) and work-integrated learning (WIL) opportunities such as different collaborative exercises. In a study regarding another field of industry, the software industry, the authors of the paper state that the software industry needs universities to train IT developers with strong soft skills in addition to technical skills, which enable them to collaborate on international software development projects. The study details the program where an online software development project course was organised to develop soft skills of students, during which teams of 5–8 Scrum students from five universities in Belarus worked on industrial projects for Danish clients [12].

However, many young people find it difficult to make the transition from the classroom to the workplace. It is also especially important to look at and know who comes from what background. For young people with disabilities or disadvantaged young people, social skills are particularly important and need more attention to master them, as some have difficulty controlling their emotions or even having a good relationship with others. Regardless of their disadvantaged situation, many young people also need to learn the importance of, for example, turning up at work on time, calling in when they are ill, or opening to others as a new colleague.

This is also where the role of schools comes in, and for the reasons mentioned above, it is vital that educational institutions (primary schools, secondary schools, and universities) help students to develop their soft skills. Secondary school, and later university, is the bridge between the world of learning and the world of work, and it is therefore essential that there is a close link between these two important pillars.

In his study, Schulz [13] encourages educators to put more emphasis on developing the soft skills of their students. Seetha [14] also suggests in his paper that employers are more likely to hire and support individuals who are resourceful, able to work well independently and have soft skills. He also stresses the need to integrate soft skills into training programmes and curricula, highlighting the different teaching methods to be used in the development of soft skills [14].

What are the soft skills required from young people entering the current labour market? The study by Kyrousi and colleagues examines the issue of employability from the perspective of Generation Z students. The topic is timely as Generation Z is the newest generation to enter the business workforce. The results of their research support the two key dimensions of employability, job readiness and employability skills, on which students and educators share similar perceptions. Both stakeholders distinguish between hard and soft skills, but their relative importance is filtered through a generational lens [15].

LinkedIn has tracked the skills that companies need most on an annual basis and published the results for 2019 [16]. LinkedIn staff narrowed down the list of 50,000 skills to a list of 30 skills, resulting in a list of the skills that are currently in greatest demand (5 soft and 25 hard skills).

The most in-demand soft skills on the list were 1. creativity (despite the fact that computers and artificial intelligence can do so much now, creativity remains an infinitely valuable and essential human trait), 2. persuasion (since few products sell themselves; therefore companies still need to find and hire employees who can persuade consumers to buy a product or service), 3. collaboration (since teamwork is at the heart of all good business, newer and newer projects require companies to hire more and more skilled team players), 4. adaptability (our modern world is changing rapidly and those who can adapt effectively to new circumstances and technologies; who can make decisions quickly and react quickly to situations will prevail), 5. time management (the ability to manage time effectively is a skill that will prove useful throughout our careers). The top three of the 25 hard skills on the list are: 1. cloud computing, 2. artificial intelligence and 3. analytical reasoning.

Google’s Oxygen [17] project began in the early 2000s with a fundamental question posed by managers: do managers matter? The topic generated a multi-year research project that eventually led to a comprehensive program built around eight key leadership attributes, with the goal of making Google employees better leaders. By November 2012, the program had been in place for several years and the company had seen statistically significant improvements in leadership effectiveness and performance. Research from Google’s Oxygen project showed that soft skills were more important than STEM (science, technology, engineering, and maths) skills for Google’s top employees. The top performers had the following soft skills: effective communication skills, the ability to coach, understanding others, empathy and supportiveness towards colleagues, critical thinking and problem-solving skills, and the ability to identify the links between complex tasks.

Another study, Project Aristotle [18], looked at how resourceful and productive teams are at Google. They found that the top performing employee characteristics were primarily: pro-equality, generosity, openness to team members’ ideas, empathy, and emotional intelligence, with the most important characteristic being emotional safety (confidence, ability to speak up and acknowledge mistakes).

The perception of soft skills is growing not only on the employees’ side but also on the employers’ side [19]. According to a national study focusing on vocational training in economics [20], companies primarily look for career starters with reliability, precision and practical application of their skills, moreover the entrants should be able to work independently, should have good problem-solving skills, should be able to endure workload and should gave great work capacity, i.e. they are looking for employees with up-to-date competences who can be a driving force for the company with their creativity and problem-solving skills. The results of the research show that there is a gap between the competences that students perceive as necessary and those expected by employers in terms of problem-solving skills, practical application of skills, communication skills, foreign language skills, organisational skills, stress tolerance, analytical skills, analytical approach, flexibility, and the ability to motivate others. In such a way that students perceive these competences as more important to employers than they are relevant to them.

While professional knowledge is seen as a solid requirement, flexibility, communication, and active participation in teamwork are even more strongly desired by employers [21]. Studies also show that graduates perceive skills that support the functioning of leadership, communication, and organisational knowledge assets as significantly stronger criteria than graduates. However, when evaluating the results, it can be said that in most cases gender, age and educational attainment influence soft and hard skills [21].

According to a study by Harvard University [22] eighty-five percent of success in the workplace is due to soft skills, while only fifteen percent is due to hard skills. According to LinkedIn’s Global Talent Trends (LinkedIn 2019) 2019 report, 92 percent of experts believe that soft skills are as important or more important than hard skills, and 89 percent of experts said that if a new hire does not live up to expectations, it is because they lack or are not adequately equipped with the necessary and critical soft skills [23].

Language and IT skills are still one of the most important recruitment criteria in most fields, but soft skills are also increasingly becoming a recruitment requirement and are identified as a significant need on the employer side. Therefore integrated soft skills courses are seen as an important part of university education and can make a major contribution to the development of soft skills for students entering the labour market. Soft skills help young people to succeed in life, regardless of what they do [24]. By developing these skills, young people can improve their social lives, perform better in post-secondary education, and be more successful in finding and keeping jobs. The authors’ study also confirmed that both employers and employees value effective interpersonal relationships between labour market actors, as soft skills are seen as essential to working in a team.

Lepeley, in his 2021 study [25], argued that interpersonal skills are needed by all employees who work with others, as they need to be able to work effectively in a team to achieve mutual success.

As soft skills are much more challenging to master [26] than hard skills, companies often outsource their acquisition to professionals, trainers and coaches who are aware of current global trends and practices.

LinkedIn’s Global Talent Trends research, which presents a survey of more than 5,000 professionals interviewed in 35 countries, detailed how, after interviewing company leaders and talking to experts, they were able to identify three trends that could influence current labour markets. The three variables were: soft skills, job flexibility and pay transparency.

Typically, workers can excel and move up the job ladder because of their hard skills but are able to fail because of their lack of soft skills [27]. In her study, Fouzia [28] examined the perspectives of professionals working in different engineering disciplines to understand the role of soft skills in their profession. She found that technical competence is not considered sufficient by either employees or employers, as employers are looking for graduates who can complement their technical expertise with various soft skills to succeed in the complex world of engineering. The study also points out that while much of the curriculum in engineering schools focuses on the technical aspects, the training and development of soft skills is essential.

However, developing soft skills is not easy, and in many cases, it is quite costly, time-consuming, and expensive. Laker and Powell [29] look in detail at the differences between the development of soft and hard skills, with a particular focus on the extent of knowledge transfer.

There exists a model, the COACH_ING model, which is an educational framework where engineering skills and soft behavioural skills are integrated into new competencies to prepare students and young engineers for their entry into the labour market, along with strong relational skills and awareness of the career path best suited to their abilities and growth potential [30].

The flipped classroom approach is increasingly being used in higher education institutions, where a new methodology and a new educational structure are proposed to develop engineering students’ soft skills, in particular lifelong learning, critical thinking, curiosity, autonomy, communication, and presentation techniques, to succeed in this digital age and meet the requirements of industry 4.0. Jamila delivered the flipped course to the fourth-year industrial engineering class of the fourth year of engineering studies at the National School of Applied Sciences NSAS in Fez, Morocco. In the study, the essence and importance of the method is described in detail, but he highlights that it was quite challenging and extra work for the instructors to train students with the soft skills needed in Industry 4.0 [31].

If employees’ soft skills are consciously developed and strengthened, they will increase their effectiveness in the workplace and minimise the dropout rate [32]. Trainers and coaches working on the development of soft skills consider self-awareness to be of utmost importance [33] as it is considered the most important foundation for the development of soft skills. Within the category of leadership skills, critical and strategic thinking, understanding diverse cultures, self-awareness, leadership, and developing a sense of accountability are particularly critical areas [34].

Vlachopoulos has explored the perceptions of organisational change management among executive coaches working with UK higher education leaders and the factors that make leaders effective in managing change. The research further emphasised the role of coaching in developing the key soft skills (including honesty, responsibility, flexibility, creativity, proactivity, and empathy) required for effective change management and leadership in higher education [35].

1.2 Objectives

The research, entitled “The importance of soft skills in the labour market”, was conducted in Hungary between 2020 and 2022. The studies were carried out in several stages and the main objective of the researchers was to assess both the employers’ and the future employees’ side of the labour market in terms of how they perceive the supply and demand of soft skills, how well the soft skills of employees match the expectations and what market players are willing to do to reduce these gaps.

2 Methods

The first part of the study took place in 2020-21, when the authors conducted a quantitative questionnaire survey with 500 future employees. The participants were university students from one of Hungary’s largest universities (MATE). The institution currently has five campuses, with around 13 000 students studying in four large rural cities in addition to the country’s capital. The institutions offer students a wide range of subjects, from agricultural sciences to engineering, arts, and economics. This was one of the reasons why the authors conducted their first round of research at this university. The method of sample collection was a snowball method, with email and social networking sites being used to send out the questionnaire to the researchers. The email response rate was low, at 20%. The social media site was not able to measure the willingness to respond by the writers. Students were asked to answer how they perceive their own soft skills, how strong they are, and how well they meet employer expectations.

No problems of interpretability were encountered by those who completed the test questionnaire, so the questions were sent out unchanged. The questionnaire consisted of closed and open questions. Of the 28 questions, one was open, and the rest were closed. The questionnaire was designed by the authors themselves and did not use questionnaires from previous research. The questionnaire consisted of the following groups of questions, which is included in Table 1.

Table 1
The employee’s questionnaire. Source: own research

Specification of the sample Soft skill analysis Soft and hard skills in the labour market

Residence Soft skill term Expectations for soft and hard skills,

Age Assessment of the skills, professional, language and computer knowledge of the candidates Value of soft skills in the labour market

Highest level of education Employer expectations of soft skills Soft skill acquisition tools

Marital status Soft skill development opportunities

Employer expectations of soft skills

Specification of the sample	Soft skill analysis	Soft and hard skills in the labour market
Residence	Soft skill term	Expectations for soft and hard skills,
Age	Assessment of the skills, professional, language and computer knowledge of the candidates	Value of soft skills in the labour market
Highest level of education	Employer expectations of soft skills	Soft skill acquisition tools
Marital status		Soft skill development opportunities
		Employer expectations of soft skills

In the second round of the survey, the authors asked employers, where they conducted a quantitative questionnaire survey. The authors conducted this survey in 2021-2022, with 416 enterprises participating. When contacting the employers’ side, the questionnaire compiled by the authors could be accessed and filled in by the companies via the internet. The enquiries took three forms. In person, email, and through various social media platforms. The sample collection method here was also the snowball method. During the pilot survey, the 10 responding firms did not indicate any problems with interpretability when completing the questionnaire, therefore the authors sent out the questionnaire in its unmodified form. The response rate to the personal and e-mail enquiries was close to 30%. The authors were able to divide the 28 questions into three groups. One was open-ended and the others were closed questions. Table 2 contains the Employer’s questionnaire.

Table 2

The employer questionnaire. Source: own research

Specification of the sample	Employer soft skills and employer expectations	Soft skills development opportunities
Location of the organisation Organisation size	Characteristics of the soft skills of young people	The arenas for the development of soft skills
Organizational industry	Employers’ expectations of soft skills	Factors affecting the development of soft skills
Ownership structure	Perceptions of the importance of soft skills	The role of trainers/coaches in the development of soft skills
Knowledge priority in the organisation	Employers’ expectations of soft skills	The financial benefits of soft skills development

For both questionnaires, the questions were based on nominal and metric variables. The metric variables were 5-point Likert scales, where one was for uncharacteristic and five was for completely characteristic. Except for open-ended questions, respondents were required to answer, so there were no missing variables in the evaluation. In both surveys, there were no unevaluable questionnaires. The split-half reliability was used to test the reliability of the questionnaires. For both questionnaires, the Spearman-Brown coefficient was above 0.8 for the scale questions that were analyzed by the authors.

Several research questions were formulated by the researchers. These were:

Is it possible to differentiate between the expectations of young people in terms of soft skills on the future employee side according to distinctive characteristics (gender, age, education)?

How do company size and ownership structure differentiate between what soft skills employers expect young people to have?

In what contexts and in what forms can employees’ soft skills be developed?

What soft skills can coaches/trainers develop?

Are future employees and employers willing to invest financially in the development of soft skills?

Based on the research questions and the empirical results of the literature, the following hypotheses were evaluated:

H1: There is a difference in the perception of young people’s soft skills between employers and future employees.

H2: Future employees and employers consider it important to strengthen the necessary soft skills and are willing to invest financially in this.

To evaluate the questionnaires, the authors used SPSS version 28 and Amos version 28. Univariate and multivariate statistical methods were used to analyse the variables: frequency, mean, analysis of variance, correlation, factor analysis, cluster analysis, SEM model. The study involved 500 students with an average age of 28.48 years. On the employer side, 416 enterprises were included. The minimum sample size for both samples is determined by Yamane’s formula [36] at the 95% confidence level and p = 0.5 as follows in Fig. 1:

Fig. 1

Yamane’s formula. Source: Prasad & Vaida, (2020).

N is the population size, so N = 13000 students for students and N = 495549 enterprises for employers in Hungary at the time of the survey (KSH, 2021). For students, 13000/ (1+ 13000*0.05*0.05) = 388, for enterprises: 495549/ (1 + 495549*0.05*0.05) = 399. Thus, in both cases, the authors have worked with a sufficient sample size based on the formula. The specifications of the young people and companies included in the survey are summarised in Table 3:

Table 3

Specification of the student and employer sample. Source: own research

Students		Companies
Residence	21.6% Northern Hungary	Location	18.8% Northern Hungary
	2.8% Northern Great Plain		4.1% Northern Great Plain
	7.8% Southern Great Plain		1.9% Southern Great Plain
	44.4% Central Hungary		5.3% Central Hungary
	7.0% Central Transdanubia		63.2% Central Transdanubia
	6.2% Western Transdanubia		3.8% Western Transdanubia
	10.2% South Transdanubia		2.9% South Transdanubia
Highest level of education	49% Graduated from high school	Size	8.7% Micro (2–8 persons)
	50.6% University Diploma		22.4% Small (9–49 persons)
	0.4% PhD		27.6% Medium (50–249 persons)
			41.3% Large (250 and over persons)
Gender	31.4% Male	Ownership structure	61.1% Hungarian only
	68.6% Female		20.9% Mixed
	18.% Foreign

3 Results

3.1 Soft skills: Perspective of employers and employees

The authors first analysed students’ perceptions of the soft skills expected of them and the soft skills that employers expect from employees. In both cases, the researchers listed the same qualities. On a five-point Likert scale, respondents were asked to rate how typical they thought it was for companies to expect this from employees. A score of one was not at all typical, and a score of five was completely typical. Table 4 shows the standard deviation and mean of opinions on the skills expected:

Table 4
What are the expectations of young people’s skills from the perspective of students and employers. Source: own research

Skills Employee Employer

Valid N Mean Std. Devi. Valid N Mean Std. Devi.

Professional knowledge 500 3.95 0.83 416 4.13 0.91

Language skills 500 4.21 0.777 416 4 1.082

IT skills 500 4.15 0.729 416 4.19 0.882

Effective communication skills 500 4.22 0.776 416 4.27 0.795

Critical thinking 500 3.4 0.999 416 3.76 0.983

Leadership skills 500 2.83 0.972 416 3.46 1.007

Entrepreneurial skills 500 2.91 1.111 416 3.15 1.17

Ability to work in a team 500 4.45 0.69 416 4.37 0.829

Ethical and moral skills 500 3.59 1.137 416 4.17 0.841

Strategic thinking 500 3.59 1.051 416 3.85 1.001

Time management skills 500 4.01 0.913 416 4.05 0.919

Planning and organisation skills 500 3.79 0.915 416 3.97 0.946

Presentation skills 500 3.74 1.06 416 3.69 1.081

Self-awareness 500 3.07 1.183 416 3.73 0.938

Problem-solving skills 500 4.32 0.806 416 4.35 0.762

Empathy 500 3.15 1.162 416 3.83 0.898

Creativity 500 3.63 1.09 416 3.91 0.951

Flexibility 500 4.46 0.757 416 4.21 0.822

Ability to deal with stress situations and conflicts 500 4.12 0.923 416 4.23 0.817

Emotional intelligence 500 3.04 1.148 416 3.83 0.95

Skills	Employee	Employer
Professional knowledge	500	3.95	0.83	416	4.13	0.91
Language skills	500	4.21	0.777	416	4	1.082
IT skills	500	4.15	0.729	416	4.19	0.882
Effective communication skills	500	4.22	0.776	416	4.27	0.795
Critical thinking	500	3.4	0.999	416	3.76	0.983
Leadership skills	500	2.83	0.972	416	3.46	1.007
Entrepreneurial skills	500	2.91	1.111	416	3.15	1.17
Ability to work in a team	500	4.45	0.69	416	4.37	0.829
Ethical and moral skills	500	3.59	1.137	416	4.17	0.841
Strategic thinking	500	3.59	1.051	416	3.85	1.001
Time management skills	500	4.01	0.913	416	4.05	0.919
Planning and organisation skills	500	3.79	0.915	416	3.97	0.946
Presentation skills	500	3.74	1.06	416	3.69	1.081
Self-awareness	500	3.07	1.183	416	3.73	0.938
Problem-solving skills	500	4.32	0.806	416	4.35	0.762
Empathy	500	3.15	1.162	416	3.83	0.898
Creativity	500	3.63	1.09	416	3.91	0.951
Flexibility	500	4.46	0.757	416	4.21	0.822
Ability to deal with stress situations and conflicts	500	4.12	0.923	416	4.23	0.817
Emotional intelligence	500	3.04	1.148	416	3.83	0.95

Two groups of skills could be distinguished: hard and soft skills. In both cases, the hard skills were professional knowledge, language skills and IT skills. For both groups of respondents, these skills were strongly expected on the labour market. Our observations support the literature: the importance of soft skills is equal to hard skills, and some even exceed them: for example, effective communication skills, flexibility, problem-solving skills, willingness to work in a team.

However, the importance of soft skills is not self-evident, but is more evident in the world of work. Most of the skills surveyed were identified as more important expectations by employers than by students. Only the following were considered by students to be more important than employers in the labour market: flexibility, teamwork, and presentation skills.

Table 5 summarises the soft skills most valued by students and companies (in order of importance), compared with the results of the LinkedIn survey presented in the literature review and the experiences of Google Oxygen and Project Aristotel, furthermore it summarizes the expected and successful soft skills examined by Kárpátiné. Table 5 represents the expected and successful soft skills by different surveys in the order of the skills.

Table 5

Expected and successful soft skills by different surveys in the order of the skills. Source: own compilation

Students	Companies	LinkedIn	Kárpátiné (comp.)	Google Oxygen	Project Aristotel
Flexibility	Teamwork	Creativity	Reliability	Communication	Equality
Teamwork	Problem solving	Persuasion	Precision	Coaching	Generosity
Problem-solving	Communication	Teamwork	Expertise Application	Understanding	Openness
Communication	Conflict resolution	Adaptability	Autonomy	Empathy	Empathy
Conflict resolution	Flexibility	Time management	Problem solving	Critical thinking	Emotional intelligence
			Loadability	Problem-solving
			Working capacity	Complex viewpoint

There is a basic consistency between the students and companies in the study regarding the definition of the soft skills required, both in terms of content and order, with teamwork –problem-solving - communication skills playing a key role. Flexibility is the only exception, ranked by students as the absolute most needed skill, while it is ranked last in the top five skills for companies. It is noteworthy that while the Hungarian survey emphasises problem-solving - which is reactive - the LinkedIn survey [37]. emphasises creativity - which is proactive, but only ranked in the middle of the pack in the Hungarian survey. This is particularly significant in the light of the fact that the LinkedIn survey points to a broader context of the importance of soft skills, both in space - persuading customers, adaptability on the input and output side - and in time - time management.

When comparing the soft skills identified as necessary with those identified as success factors by Google Oxygen and Project Aristotel case studies, cognitive soft skills are outpaced by social and affective skills. All of these were either ranked in the middle of the Hungarian sample - ethical skills, empathy - or were marked as least (!) important: emotional intelligence and self-awareness. The significance of this result is that self-awareness was identified by the literature review as the most crucial factor in the development of soft skills.

If we also consider Kárpátiné’s research, the soft skills under investigation are embedded in expected skills such as reliability, precision, expertise, workload, which are soft skills, but represent a completely different corporate need and approach.

The authors investigated which skill expectations are significantly positively related to each other in the understanding of students and employers. The authors focused on those expectations where the Pearson correlation value was higher than 0.5. Figure 2 shows the co-movements in student and company perceptions.

Fig. 2

Significant associations between soft skills in student and company opinions. Source: Own research and compilation.

In each case, three sets of “factors” emerge from the results: those related to entrepreneurship, strategic planning, and emotional maturity. However, while among student’s entrepreneurship and strategic thinking are two separate skills, in the corporate world the two are more closely related. On the other hand, working strategically as a skill is more equated with planning among students, while in the corporate world it is seen as time management. It is also noteworthy that while in corporate practice morality is associated with clearly communicated teamwork, in the students’ perceptions morality comes from the individual, an inherent part of empathy moving with self-awareness.

To further analysis, the authors grouped the soft skills as judged by students and employers into factors, i.e. professional knowledge, language skills and IT skills were not included in the factor training.

For future employees, the results of the KMO Bartlett test are KMO: 0.832, Approx. Chi-Square: 1824.17, df: 45, sig.:.000, explained variance ratio: 73.763 %, and Varimax rotation was used by the authors to construct the factors. Not all variables were suitable for factorization. Thus, effective communication skills, critical thinking, strategic thinking, time management, planning and organizational skills, creativity, among others, were not included.

On the employer side, the results of the KMO Bartlett test are KMO: 0.893, Approx. Chi-Square: 2832.123, df:78, sig.:.000, explained coefficient of variance: 73.076 %. Effective communication skills, critical thinking, strategic thinking, presentation skills, creativity were not suitable for factor training. Table 6 summarises the factors from the perspective of employers and students, i.e. future employees:

Table 6

Rotated component values. Source: own research

	Students
			Component
		1	2	3	4
Emotional maturity (EM)	Empathy (EM1)	0.858
	Self-awareness (EM2)	0.805
	Emotional intelligence (EM3)	0.789
	Ethical and moral skills (EM4)	0.738
	Cronbach Alpha	0.853

Leadership Maturity (LM)	Leadership skills (LM1)		0.870
	Entrepreneurship skills (LM2)		0.867
	Cronbach Alpha	0.812

Flexibility (FL)	Stressful situations (FL1)			0.816
	Resilience (FL2)			0.767
	Cronbach Alpha	0.584

Cooperation (C)	Teamwork skills (C1)				0.857
	Presentation skills (C2)				0.583
	Cronbach Alpha	0.509
	Companies
		Component
		1	2	3	4
Cooperation (CO)	Flexibility (CO1)	0.829
	Ability to cope with stress and conflict (CO2)	0.775
	Problem-solving ability (CO3)	0.706
	Teamwork skills (CO4)	0.610
	Cronbach Alpha	0.836

Emotional maturity (EM)	Empathy (EM1)		0.761
	Emotional intelligence (EM2)		0.752
	Self-awareness (EM3)		0.705
	Ethical and moral skills (EM4)		0.660
	Cronbach Alpha	0.834

Operational Activity (OA)	Planning and organisation skills (OA1)			0.772
	Time management skills (OA2)			0.702
	Presentation skills (OA3)			0.651
	Cronbach Alpha	0.738

Leadership Maturity (LM)	Entrepreneurship skills (LM1)				0.864
	Leadership skills (LM2)				0.814
	Cronbach Alpha	0.807

In the first column of the tables, the researchers present the names of the factors defined by the factor weights. For each factor, the authors have highlighted the Cronbach’s alpha values and colour-coded which variables were included in a factor. Based on the data in the Table, 4 factors were developed by the authors. These were named by the future employees as: emotional maturity, leadership maturity, flexibility, cooperation. On the employer side, the following factors were created: cooperation, emotional maturity, operational activity, managerial maturity. The nature and content of the factors suggest that both prospective employees and companies will identify similar key areas: the ability to collaborate, based on emotional maturity/intelligence, and the willingness and ability to manage groups strategically and operationally. At the same time, while the students believe that this should be complemented by flexible thinking and adaptability, companies believe that it should be complemented by the ability to work: the willingness to work and the ability to organise.

The authors have examined how the clustering of the two samples can be achieved using the factors on both the employer and the employee side. The authors used the K-means procedure to create homogeneous clusters, with 20 iterations for students and 18 for employees. The authors created 3 clusters in both cases, with cluster centres as follows in Table 7:

Table 7

Final cluster centres. Source: own research

Students				Employer
	Cluster				Cluster
	1	2	3		1	2	3
Emotional development	–0.46149	–0.12085	0.55741	Cooperation skills	–1.15711	0.57767	0.01159
Leadership skills	0.77577	–0.10504	–0.71180	Emotional maturity	0.57830	0.34354	–1.10536
Flexible thinking	0.38926	–1.13404	0.43305	Operational activity	0.09967	–0.32592	0.47929
Collaboration	0.25517	–0.44379	0.06494	Leadership maturity	0.29111	–0.29645	0.25990

On the student side, the cluster meanings allowed the following homogeneous groups to be formed based on the characteristics that they believe employers expect from their employees:

emotionally intelligent individuals with leadership skills

they have no expectations in terms of these factors

young people who are emotionally open and flexible

The authors analysed whether there is a difference in clustering by gender, age, and education. There were no differences by age (Chi-square: 8.212, df: 10, p:.608 p > 0.05) or when examining educational attainment (Chi-square: 5.760, df: 4, p:.218 p > 0.05). By age, those in their twenties are in the third cluster (38.8%), while those in their thirties are in the first (43.5%). Those with a high school diploma are in the third cluster (37.6%), while those with a university degree are in the first (37.5%). Significant differences were identified by gender (Chi-square: 8.428, df: 2 p:.015 p < 0.05), with men being the most likely to be in the first cluster (36.3%) and women in the third (39.7%).

On the employer side, the following clusters could be identified:

Young people with strong emotional and leadership maturity

Employees should be open-minded in cooperation, emotion, and operational activities.

The employee should be competent in operational work.

A comparison of the two groupings reveals that there are distinctly like-minded groups: in emotionally mature, managerially skilled workers on the one hand, and in cooperative, emotionally open workers on the other. Here again, the difference between student resilience and the operational needs of the company emerges. The biggest difference is between the groups where students do not have a specific expectation, but where the company has an unclouded vision of the quantity and quality of work. The greatest friction in the future labour market may be between these two groups. The authors have analysed whether differences in organisational size and ownership structure can be identified when examining clusters. No differences could be detected by organisational size (Chi squared: 2.729 df: 6 p:0.842 p > 0.05), but differences could be detected by ownership structure (Chi squared: 10.239 df: 4 p:0.037 p < 0.05). For all organisational sizes and ownership structures, the second cluster had the largest number of organisations.

Overall, it can be concluded that prospective employees and employers have similar perceptions of the soft skills of young people in the labour market. There are some soft skills that respondents attached more importance to than hard skills. However, both sides have similar views on the perception of the most important soft skills, although employers tend to have stronger expectations than young people would like to think. The authors therefore accept their first hypothesis.

3.2 Soft skills and development

In the second part of the survey, respondents were asked to say where they think young people’s soft skills could be developed the most. Respondents were given a choice of several pre-selected options. 40.8% of respondents thought it would be at school, 44.8% thought it would be with friends, 77.4% thought it would be with strangers and 58% thought it would be with an employer. 47.1% of those in employment said they thought it was at school, 63% thought it was with friends, 61.3% thought it was with strangers, and 81% thought it was at work. For the latter, there is a large gap between the opinions of students and employers. The question arises: if employers see opportunities for development and improvement in the workplace, how will they be partners in this process?

The survey therefore also analysed which skills respondents thought might need external help, i.e. the involvement of a trainer/coach, to develop them. The five skills most frequently mentioned by students were: communication, conflict management, decision-making, self-assertion, and motivation.

Employers most frequently mentioned the following: communication, conflict management, time management, organisational skills, decision-making. The skills that coaches can develop overlap to some extent.

It was asked whether the respondents were willing to invest financially in the development of these skills and whether they preferred group or individual training. In the question on payment, the respondents could choose between three variables: yes, no, or don’t know if they would pay for the development. As to the type of training solution, they had to select one of the options: individual, group or both. The researchers analysed these questions for both students and employers.

The authors used SPSS AMOS 28. They therefore investigated whether, in the light of the skill expectations shown in Table 6, the respondents were willing to pay for skills development and what form they envisaged development should take. The authors examined the relationships in the SEM model they created. SEM (Structural Equation Modelling) can show the relationship between one or more exogenous (independent) variables and one or more endogenous (dependent) variables. Endogenous variables can be affected directly and indirectly by exogenous variables. In the diagrams, arrows indicate the effect of one variable on another, and back and forth arrows indicate the covariance or correlation between variables.

The authors have modelled separately the views of young people and employers.

For future workers, the “absolute model fit: the Chi-square was significant (109.790 df: 42 p: 0.000). After a sample size of 500, the significance of the Chi-square is stronger at 0. The RMSEA (Root Mean Square Error Approximation) value is 0.057, which should typically be below 0.08. The GFI (Goodness of Fit Index), which is acceptable for a value higher than 0.9, was.964 for this model, so it was adequate. In terms of Incremental Model Fit, the indices tested were AGFI, CFI, NFI, TLI, all of which were considered good at values above 0.9. In the model, the AGFI:.932, CFI:.962, NFI:.941, TLI:.941, were excellent. For the Parsimony Fit, the Chi-squared/df- value was 2.614, which was considered good because it did not exceed the threshold of 5. Thus, the model -shown in Fig. 3- was considered adequate.

Fig. 3

Form of expected skills development and possible financial support for development based on the views of future employees. Source: own research.

Table 8 shows the regression values.

Table 8

Regression values (p = 0.05). Source: own research

Non-Standardized							Standardized
			Estimate	S.E.	C.R.	P	Estimate
Support	< —	Emotional m.	0.023	0.082	0.275	0.783	0.020
Support	< —	Leadership m.	0.041	0.106	0.388	0.698	0.043
Support	< —	Flexibility	–0.320	0.279	–1.149	0.250	–0.164
Support	< —	Cooperation	0.095	0.241	0.393	0.694	0.073
Training f	< —	Emotional m.	0.066	0.080	0.828	0.408	0.061

Training f.	< —	Leadership m.	0.243	0.109	2.234	0.025	0.262
Training f.	< —	Flexibility	0.004	0.275	0.014	0.988	0.002
Training f.	< —	Cooperation	–0.301	0.249	–1.208	0.227	–0.238

The regression values of the model showed that students’ fundamental belief in different forms of development in leadership maturity training (marked in grey) was 55% of students believed that group and individual development together can be successful, while one in four students believed in individual reinforcement. The data also show that there is no meaningful relationship between skill expectations and financial gain for students. 40% of the students in the sample would have paid for opportunities to improve their skills.

When examining the employer model, the “absolute model fit: the Chi-square was significant (317.121 df: 78 p:.000). The RMSEA (Root Mean Square Error Approximation) was 0.086, which was slightly above the cut-off. The GFI (Goodness of Fit Index for the model was.907, which was good. The Incremental Model Fit Indexes are AGFI, CFI, NFI, TLI, which are considered good with values above.9. In the model, AGFI:.856, CFI:.915, NFI:.854, TLI:.886, i.e., they met or were close to the threshold. For Parsimony Fit, the Chi-squared/df value was 4.066, which was good. The model was accepted by the authors based on the above. Figure 4 shows the employers’ views on the form of skills development expected and possible financial support for development.

Fig. 4

Employers’ views on the form of skills development expected and possible financial support for development. Source: own research.

Table 9 shows the regression values.

Table 9

Regression values (p = 0.05). Source: own research

Non-Standardized							Standardized
			Estimate	S.E.	C.R.	P	Estimate
Support	< —	Cooperation	–0.452	0.205	–2.210	0.027	–0.290
Support	< —	Emotional m.	0.140	0.180	0.776	0.438	0.088
Support	< —	Operational act.	0.023	0.163	0.141	0.888	0.017
Support	< —	Leadership m	–0.060	0.104	–0.581	0.561	–0.058
Training f	< —	Cooperation	0.042	0.172	0.246	0.806	0.032
Training f.	< —	Emotional m.	0.249	0.153	1.628	0.103	0.187
Training f.	< —	Operational act.	–0.194	0.139	–1.396	0.163	–0.171
Training f.	< —	Leadership m	0.026	0.088	0.296	0.767	0.030

The data show that there is only a meaningful relationship (marked in grey) with the need for cooperation in terms of subsidies. 53% of firms would also provide financial support for the development of soft skills. For the different forms of training, there was no meaningful relationship with expectations. Typically, 55% of companies relied on the combined effect of group and individual development.

Overall, it was found that both the forms of training and the willingness to support it were perceived as similar by future employees and employers and were considered important. At the same time, the results show that these initiatives are not yet really induced and conducted in line with labour market expectations of soft skills, so the authors do not accept the second hypothesis.

4 Conclusions

Our research supports the literature that soft skills are at least as important as hard skills. In some areas, the importance of soft skills exceeded the role of hard skills in the student and company contexts studied. These are teamwork, flexibility, problem-solving and communication skills. Students’ perceptions of the soft skills needed to supply the workforce of the future are broadly in line with the needs expressed by companies. All of this can be considered a good sign for the labour market of the future, as well as the development direction and potential of soft skills in educational institutions.

The main differences were found, first, in the fact that corporate needs are stronger than the students’ perception and, secondly, in terms of content, students consider adaptability as one of the main success factors, while companies emphasise work skills with good workload and good organisational skills. All these findings support the hypothesis of a difference in perceptions of soft skills.

Direct contacts (friends and workplace) were identified by companies as the most important environment for the development of soft skills, while the influence of indirect (non-direct acquaintances) was much greater for students.

Both parties recognised the importance of soft skills. It is therefore no coincidence that the studies show that research participants are willing to make financial sacrifices for its development. But even so, employers value these skills as non-systemic, closely related skills [21].

Research results contribute to the field at least in two ways. First, methodologically they infer a wider perspective to investigate the role of soft skills in the labour market. Enriching the empirical surveys and linking them highlight that the results of the different approaches overlap as well as complement each other. It is good to realise that the proactive openness to the changes (creativity, flexibility, etc.) go together with the need of reliability. In addition, the increasing number of data enables us to cluster the great number of soft skills and shrink the relevant information of the core areas.

This leads to the other area of contribution: implications for managers. Soft skills are part of corporate culture, and hence steep the overall market performance of companies. The literature review has also supported that soft skills have an emerging importance as driving forces of competitiveness.

More specifically, our research results raise that there seems to be an emerging generational shift that challenges management, while the soft skills highlighted by the employers and future employees complement each other at the same time. Companies express stronger need for soft skills than what students perceive; however, students articulate party different directions or clasters of soft skills. Employers more stress entrepreneurial, leadership and strategic thinking skills, while cooperation or emotional maturity has more importance in terms of future employees. In addition, students express the importance and influential power of outdoor environment regarding learning and developing soft skills. All in all, not only the adaptation power of the companies is increasing in our volatile and uncertain world, but also their social responsibility. Cooperation, emotional maturity etc. enhance the sensitivity of companies to produce in a socially responsible way; leadership, strategic and operational skills make responsibility active in the everyday life; and teamwork, the mutually preferred soft skill bridge the conceptual and practical sides of responsibility.

In terms of further research directions, it was noteworthy that strategic thinking was found to be of low importance in both the student and company surveys. However, in today’s uncertain, complex, and ambiguous world, a growing body of literature highlights the importance and impact of foresight skills. Within soft skills, we will soon start to examine futures skills in a separate project.

Footnotes

Acknowledgments

The authors have no acknowledgments.

Author contributions

CONCEPTION: Gabriella Horváth-Csikós, Tímea Juhász and Tamás Gáspár.

METHODOLOGY: Gabriella Horváth-Csikós, Tímea Juhász and Tamás Gáspár.

DATA COLLECTION: Gabriella Horváth-Csikós, Tímea Juhász and Tamás Gáspár.

INTERPRETATION OR ANALYSIS OF DATA: Gabriella Horváth-Csikós, Tímea Juhász and Tamás Gáspár.

PREPARATION OF THE MANUSCRIPT: Gabriella Horváth-Csikós, Tímea Juhász and Tamás Gáspár.

REVISION FOR IMPORTANT INTELLECTUAL CONTENT: Gabriella Horváth-Csikós, Tímea Juhász and Tamás Gáspár.

SUPERVISION: Gabriella Horváth-Csikós, Tímea Juhász and Tamás Gáspár.

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