THE INFLUENCE OF CONTEXTS IN THE PROCESS OF CHOOSING A UNIVERSITY PRODUCT

Abstract

In the current global context, organisations are compelled to reposition themselves in the distribution chain due to changes in consumer behaviour. Consumers no longer simply seek products and services; instead, they are pursuing the maximisation of satisfaction promised by their providers. The authors of this article have focused their analytical efforts on highlighting specific aspects of the diverse challenges that consumers must find optimal solutions to at the time of purchase decision. Within this dynamic framework, intellectual capital plays an increasingly important role, its core components being human capital, relational capital, and structural capital. Addressing the human capital component, the authors of this study have directed their analytical approach toward the key determinants of young people's decisions to opt for specific study programmes, aiming to explain how educational offerings can be personalised and adapted. Methodologically, an econometric model is employed, allowing universities to conduct a stakeholder analysis to gather information to determine a matrix of the expressed interest and influence power of various categories of interests in societal terms. The paper presents the results of testing the foundations of students' choices for a particular university-level study programme. Furthermore, the research sought to establish the desirable level of econometric robustness of the basic vectors in the decision-making process regarding the selection of a specific set of competencies and cognitive skills promised by the study programmes. Based on the operationalisation of the specific methodological tools, a panel of tools has been constructed for universities to attempt to meet the expectations of future students. Candidates and students can also use these tools to find ways to optimise resources related to the creation, modification, and promotion of study programmes through the planning of competitive strategies and simultaneous action as promoters of social responsibility.

Headnote

Abstract

In the current global context, organisations are compelled to reposition themselves in the distribution chain due to changes in consumer behaviour. Consumers no longer simply seek products and services; instead, they are pursuing the maximisation of satisfaction promised by their providers. The authors of this article have focused their analytical efforts on highlighting specific aspects of the diverse challenges that consumers must find optimal solutions to at the time of purchase decision. Within this dynamic framework, intellectual capital plays an increasingly important role, its core components being human capital, relational capital, and structural capital. Addressing the human capital component, the authors of this study have directed their analytical approach toward the key determinants of young people's decisions to opt for specific study programmes, aiming to explain how educational offerings can be personalised and adapted. Methodologically, an econometric model is employed, allowing universities to conduct a stakeholder analysis to gather information to determine a matrix of the expressed interest and influence power of various categories of interests in societal terms. The paper presents the results of testing the foundations of students' choices for a particular university-level study programme. Furthermore, the research sought to establish the desirable level of econometric robustness of the basic vectors in the decision-making process regarding the selection of a specific set of competencies and cognitive skills promised by the study programmes. Based on the operationalisation of the specific methodological tools, a panel of tools has been constructed for universities to attempt to meet the expectations of future students. Candidates and students can also use these tools to find ways to optimise resources related to the creation, modification, and promotion of study programmes through the planning of competitive strategies and simultaneous action as promoters of social responsibility.

Keywords: intellectual capital, context, informed decision-making process, study programme, sustainable education.

JEL Classification: A13, 121, 123, 125, M31, P46.

(ProQuest: ... denotes formulae omitted.)

Introduction

The educational landscape has always been one of contrasts, encompassing both immobility and resistance to change, as well as modernity and positioning at the forefront of societal transformations. Managing change requires fundamental revisions of curriculum content, educator preparation, ethical and methodological-didactic reconfigurations, and pedagogical practice. The aspects that influence the decision of young people to opt for specific study programmes must be identified and understood, as only in this way can universities adapt their curriculum design and equip themselves with highly qualified human resources to assist students in the learning process.

The topic related to the main factors influencing the decision-making process for certain study programmes has been of interest to analysts since 2014 (Narang and Mishra, 2014), with the authors identifying and grouping the main variables influencing decisions to choose specific study programmes. Gradually, it has become increasingly clear that such analyses can provide high added value for organisations seeking a better understanding of their customers' buying behaviour. In an article addressing the influence of various factors on purchase decisions (Karnreungsiri and Praditsuwan, 2017), the importance of understanding the key foundations of a decision regarding the choice of study programmes is highlighted, whether they are conducted online (Al Kurdi et al., 2020) or in their physical form (Wahyuni, 2022). One of the dilemmas related to this thematic area concerns the intensity with which young people's decision to choose a study programme is influenced by the speed and depth of such a change.

Based on the analysis conducted, our aim is to gain a deeper understanding of the factors that influence purchase decisions in the field of education. Using the proposed model, universities can better tailor their educational offerings to candidates' requirements, offering more attractive and relevant study programmes.

1. Marketing Toolkit - the Resilience Boost Provided to the Educational Act

1.1. The Modern University's Need to Experiment with Modern Elements of the Marketing Mix

In the specific context of the new economy and a knowledge-based and creative society, an increasing number of social actors participate in the educational act, playing roles that are becoming more complex, and their influence needs to be increasingly known and considered. In Figure 1, the synergistic interferences between these societal vectors of quality are presented schematically.

To build and optimise a modern educational landscape, one in which the transition from teaching to learning has been recognised, and the importance of proactivity and participative leadership becomes increasingly necessary, the internalisation of specific marketing tools is essential. The unique role of marketing in the university landscape is to establish a favourable relationship between different interest groups using the most appropriate tools and to modify individuals' reactions to external stimuli. Internationally, at the European and national levels, we observe a provocative mix whose basic components include the massification and marketisation of higher education. Under the influence of these two complementary but contradictory trends, one of the challenging aspects becomes the growth in the number of students, as their participation in social progress and their own development become increasingly pressing. Adopting this concept once again aligns with the application of marketing practices in universities, with the most suitable range of tools being social marketing, designed to help disseminate behaviours, with the main objective of modifying one of the four states: accepting a new behaviour, rejecting a potentially undesirable behaviour, changing current behaviour, or giving up an old inappropriate habit (Cheng, Kotler and Lee, 2011).

Because today's consumers have increasingly complex consumption behaviours that are harder to satisfy, a significant paradigm shift in marketing and consumer attraction methods becomes necessary. In the case of social marketing, there is an imperative focus on behavioural learning, defined as "the process of developing automatic responses to a constructed situation through repeated exposure to it" (Kerin and Hartley, 2017).

1.2. Implications of the Paradigm Shift in Marketing on the Buying Decision

In higher education, we have been witnessing a reconfiguration of the context in which significant decisions are made. The modern university, aspiring to be both effective and efficient, must firmly and irreversibly align itself with the coordinates of entrepreneurship, with the vectors of this process being people, opportunities, context, and relational diagram (Osterwalder, Pigneur and Tucci, 2005). Recent developments have reinforced the idea that context prevails compared to other vectors, with attitudes toward certain categories of goods and services becoming increasingly important. Considering that choice involves the existence of alternatives, Menon and Kahn (1995) practically presented a situation where changes in the context of choice may not significantly reduce the desire for variety but could only to some extent decrease the inclination towards seeking diversity. In other words, beyond a certain threshold, the repetition of choices can only be surpassed by diversifying products within the same category, indicating a positive relationship, albeit with a lower degree of statistical robustness, between context and alternative evaluation (decision-making), and competition can play an extremely significant role.

Traditional economic models usually exclude context when explaining consumer behaviour, but a series of research studies in psychology and neuroeconomics show that the type of consumer behaviour significantly depends on context (Louie and De Martino, 2014). This is particularly evident, especially in cases where assets subject to choosing are frequently used and have moderate costs. On the other hand, both the theory and practice of behavioural economics have highlighted numerous situations where consumers make irrational choices. Some analysts (Stankevich, 2017) have argued about the high value of indicators related to consumer behaviour, emphasising the importance of the decision-making context.

Another study on the same theme (Trueblood et al., 2013) demonstrated through three experiments that decision-making is positively influenced by the context in which the decision maker is situated and docs not specifically rely on perception, even though information can be accumulated sequentially. This suggests that the consumer's state directly influences the buying decision.

Therefore, the context refers more to the moment when the beneficiary of a particular societal activity recognises its need. Additionally, Otto et al. (2022) highlight that the options available to consumers are influenced by their perception or expectations, which, in turn, depend on the context in which the consumer finds themselves at the time of decision-making. They argue that the value of an option is calculated in relation to its context.

Consumers gain social approval from those around them by adhering to social norms related to their consumption choices, ensuring that they arc visible, distinct, and align with what the community desires (Fisher and Price, 1992). If this concept applies when the consumer decides to make a purchase, it is understood that social perceptions are closely linked to the decision-making process and are influenced by social trends.

A possible model for contextual decision-making by consumers is conceptually presented (Suomala, 2020) in Figure 2. The model shows how a consumer makes decisions in the market based on mental models of different contexts (Cml, Cm2,... Cmn), where each represents a specific contextual model, and at that moment, their previous beliefs PB2 are activated.

Suomala (2020) constructed the model based on models of contextual and rational resources of human behaviour and decision-making (Griffiths, Lieder and Goodman, 2015; Tymula and Plassmann, 2016; McKenzie, 2018).

1.3. Methodological Considerations Regarding the Specifics of Study Programs and the Behavioural Elements of their Beneficiaries

Specialised personnel involved in educational marketing activities must possess, above all, a comprehensive understanding of the product/service offered and demonstrate an understanding of consumer behavioural patterns. The evolution towards a global learning ecosystem increasingly based on digital resilience, characterised by almost unlimited access to information and extended learning opportunities, completely redefines how we interact in the academic environment, offering the increasingly digital generation a diverse spectrum of resources and educational communities through virtual communication (Dolence, 2015). The curriculum design planning of an education provider must focus on the general academic plan for the future, considering the fundamental changes brought by the new paradigm and global learning ecosystem, and act as a central guide, orienting the organisation, and supporting other institutional strategic plans (Dolence, 2015).

An interesting approach to the university's product (Kraehenberg, 1972; Dominici and Seaf, 2009; Nedbalova, Greenacre and Schulz, 2014; Mahajan and Golahit, 2019) is the study programme chosen by students. Practically, all participants in the university-level educational act attribute increasing importance to the dynamic correlation between specialised and transversal skills and cognitive abilities offered by study programmes and the current requirements of the labour market (Psacharopoulos and Velez, 1993; Hartman and Schmidt, 1995). It has been observed that the alignment between educational objectives and the real needs of employers has been established as the most important factor contributing to maximising the satisfaction of postgraduate students (Harvey and Green, 1993). As employers expect students to be prepared for the business environment, they also value this aspect (Bruce, 2009).

One of the concepts with the highest frequency both in position papers from various organisations and in academic research is sustainability, which is defined as a combination of economic efficiency, social responsibility, and ecological resilience. In the field of higher education, there is a need to maximise the degree of sustainability, this process involving obtaining a level of knowledge that corresponds to a sustainable world and promoting skills for success in an unpredictable future (Cini et al., 2023). Although universities are vital in addressing these challenges and preparing students for future demands, these organisations must undergo significant transformation, demonstrating that they internalise new opportunities, are prepared to face threats, and set the tone for future directions in advanced knowledge.

Starting from a series of grounded hypotheses, we focused on the most relevant correlations between the aspirations nurtured by the interest groups that matter at the societal level (United Nations, 2023). We also started from the hypothesis that to align with the goals contributing to sustainable development, universities must make changes in the curriculum, promote research development and the generation of innovative practices, continuously modernise their infrastructure and infostructure, and involve students and members of the communities to which they belong in their own activities, not just to develop skills for sustainable development (Wang, Sommier and Vasques, 2022). A university should align its strategies and operational programmes with social norms and context to ensure that its educational offering remains relevant and its efforts take into account the dynamic needs of the community. Adapting strategies to fit social norms equips students with real success skills and contributes to societal progress, improving the institution's relevance, sustainability, and community support. The digital revolution in education confirms the direction toward sustainable management of this field. Universities must quickly adapt to macro-environmental changes and integrate key trends in their digital transformation, where artificial intelligence stands as a crucial part of this change (Mohamed Hashim, Tlemsani and Matthews, 2022). Therefore, we decided to observe how much the context of alterable factors could influence the decision-making process.

1.4. Influences of the Context on the Offering of Study Programmes

To successfully implement these activities, the successful reshaping of study programmes requires continuous involvement from all actors participating in the educational process. Each of these stakeholders contributes, in its specific way, to the creation and dissemination of university-level educational products. Moreover, each of them operates in a certain context that can be favourable or not and has direct implications not only on the configuration of this activity. In Figure 3, the contextual implications arc presented for the four entities involved in the educational process, resulting in a combination of contexts or states of entities that lead to consequences for the product.

Starting from the identifiable relational diagram for the educational landscape, we proceeded to determine the various types of architectures in which the four most important interest groups can participate using the formula:

... (1)

Where:

* R = the number of different combinations of contexts/states

* S = the total number of contexts (not less than 2)

* O = the total number of organisms

In Figure 3, it is relevant that, depending on the types of context that can be identified (favourable or unfavourable), 16 different combinations of contextual elements can be outlined, each having a noticeable influence. The diversity of correlations is very high, with each interest group being in favourable or unfavourable situations. Interesting are the ways to minimise negative effects and those in which training effects can be maximised. Therefore, it becomes extremely necessary for the educational product to be designed considering the intersection of favourable states, the complexity of the process to be acknowledged, and, as some analysts have emphasised (Kotler and Armstrong, 2008), the stages presented in Figure 4 should be followed.

Another interesting approach can be observed in Belch and Belch (2009), who transpose the stages into a psychological process of adaptation and learning (Figure 5). Each of these phases is interconnected and unfolds in a continuous sequence when a person is in the decision-making process. They arc influenced by personal and situational factors, and the progression of these stages can vary from person to person.

Understanding the complexity of these stages and their interactions can contribute to improving the quality of the decision-making process and achieving the envisaged objectives. Therefore, it is imperative to understand to what extent the context, as defined earlier for the four entities contributing to the smooth running of the educational process in the university environment, can influence these stages and how universities can be assisted in understanding this context and adapting their strategies accordingly. To empirically test analytical hypotheses, we subjected the multi-parametric educational landscape to a comprehensive examination, faced with increasingly numerous challenges.

2. Research Methodology

2.1. Identification of the Decision-Making Issue and Research Purpose

According to the National Institute of Statistics, in the academic year 2022-2023, 3.472 million young individuals were enrolled in a study programme in Romania (regardless of the educational level), which was a decrease of 23,000 compared to the previous year. Of these, in the academic year 2022-2023, 538.7 thousand students were enrolled, with 55.3% being female (INSSE.RO, 2023). At the European level of education, the number of people enrolled in higher education (university) in all programmes and sex was 19,969,131 in 2019, indicating a downward trend (Tradingeconomics, 2023).

As a result of developments within the Bologna process, whose main vector is internationalisation, according to relevant statistics (Eurostat, 2023), 1.52 million students from member countries of the European Union are studying abroad, both within and outside the continent.

Taking into account the growing interest of young people in studying programmes in countries other than Romania, decision makers in Romanian universities must correctly understand the factors on which the decision of young people to opt for a particular tertiary education institution depends. Universities have a greater chance of establishing effective and personalised marketing strategies based on student desires and expectations if they understand the defining contextual elements they find themselves at the moment of deciding on a specific university study programme. Therefore, in a world of fierce competition where all higher education entities strive to attract the most valuable young people, promising them a remarkable educational experience, this deep understanding could provide a considerable advantage.

Understanding the fundamental elements of the behaviour of a prospective student in a university study programme becomes crucial for the survival of that study programme and the university offering it. Therefore, we conducted research aimed at developing and testing a model that focusses on the influence of contexts on the choice of university study programmes.

2.2. Objectives and Research Hypotheses

We aim to achieve the following analytical and methodological objectives throughout the investigation:

01. Evaluate the causality relationships between the specific contextual design for each of the main interest groups;

02. Measure the impact of perception on contexts in the decision-making process;

03. Identify and argue possible changes in the acquisition decision-making process;

04. Establish the most relevant context for the decision to opt for a particular university-level study programme.

Research hypotheses:

Building on the concept of Otto et al. (2022), stating that perception fluctuates based on the available options for the consumer, we empirically tested the following hypotheses regarding students' perception of contexts:

H1: The perception of the consumer's (student's) context positively impacts the organism's own context (Trueblood et al., 2013);

H2: The perception of the university's competitive context positively impacts the organism's own context (Menon and Kahn, 1995);

H3: The perception of the university's context positively impacts the organism's own context (Menon and Kahn, 1995);

H4: The perception of society's context positively impacts the organism's own context (Fisher and Price, 1992);

H5A: The perception of the personal context positively impacts the decision-making process;

H5B: The perception of the university's competitive context positively impacts the decision-making process;

H5C: The perception of the university's context positively impacts the decision-making process;

H5D: The perception of the context of the society positively impacts the decision-making process.

Considering the possible combinations of contexts for the actors involved in the educational process, the following hypotheses arise:

H6: The university's context positively impacts students' context.

H7: The student's context positively impacts the competitor's context.

H8: Competitors' context positively impacts society's context.

H9: The society's context positively impacts the university's context.

H10: Competitors' context positively impacts the university's context.

H11: The society's context positively impacts the students' context.

H12: The decision-making process undergoes changes.

H13: The context in which students find themselves is more relevant compared to those of other interest groups in society (Belch and Belch, 2009), mentioning personal factors as the basis of the decision-making process.

2.3. Determining the Sampling Method and Research Coordinates

Considering the research resources and its primary purpose, the sampling scheme was exhaustive, with respondents being first-year students at the Bucharest University of Economic Studies enrolled in the undergraduate cycle. In this phase of the research (Cochran, 1977), we opted for a sample consisting of first-year students, starting from the premise that 50% of students possess the characteristics necessary for our study, offering the greatest variability. This 50% figure is chosen because it represents a median value that provides the greatest possible variability in the absence of specific data and is a way to estimate the possible distribution of student behaviour in the absence of other information, providing a starting point for further analysis. We considered a confidence level of 95% (which leads to a=0.05) and a precision of ±5%. From the z-table, the value for z is 1.96.

... (2)

Where:

* e is the margin of error

* p is the estimated proportion in the population with the attribute in question,

* q is 1 - p

* Z is the number of standard deviations.

We managed to obtain responses from 3T1 randomly and voluntarily selected students, operationalising a questionnaire comprising six sections and 29 observable elements (questions) outlined in the Annex. The questionnaire was completed over a period of 6 days (October 2, 3, 4, 9, 10, 11, 2023) and was distributed using Google Forms. The collected data underwent analysis and interpretation processes using software such as MO Excel, SPSS, and WarpPLS to comprehensively extract relevant information and obtain the necessary results for our research purposes. Annex 1 presents the definition of the variables used throughout the study.

To operationalise 01 and 02, a correlation analysis between variables was performed using WarpPLS software, based on the structure of 9 blocks of variables composed of the 8 mentioned in the Annex plus a variable presenting the steps of the acquisition process recorded by respondents. Thus, we considered that the 8 blocks of variables, as seen in Figure 6, have direct connections to the decision. According to the analysis, the connections between them are diverse, and they are synthetically represented in the figure below.

H1: Perception of the context in which the consumer (student) finds himself has a positive impact on the organism's own context - (ß= 0.17, p-value < 0.01) - accepted;

H2: The perception of the university's competitive context has a positive impact on the organism's own context - (ß= 0.06, p-value = 0.14) - rejected;

H3: Perception of the university context has a positive impact on the context - (ß= 0.10, p-value = 0.03) - accepted;

H4: Perception of society's context has a positive impact on the organism's own context - (ß= 0.19, p-value < 0.01) - accepted;

H5a: Perception of personal context has a positive impact on the decision-making process - (ß= 0.08, p-value < 0.06) - rejected;

H5b: The perception of the university's competitive context has a positive impact on the decision-making process - (ß= 0.13, p-value < 0.01) - accepted;

H5c: Perception of the university context has a positive impact on the decision-making process - (ß= 0.07, p-value = 0.09) - rejected;

H5d: Perception of society's context has a positive impact on the decision-making process - (ß= -0.03, p-value = 0.27) - rejected;

H6: The university context has a positive impact on students' context - (ß= 0.33, p-value < 0.01) - accepted;

H7: Students' context has a positive impact on competitors' context - (ß= 0.35, p-value < 0.01) - accepted;

H8: Competitors' context has a positive impact on society's context - (ß= 0.50, p-value < 0.01) - accepted;

H9: The society context has a positive impact on the university context - (ß= 0.14, p-value < 0.01) - accepted;

H10: Competitors' context has a positive impact on the university's context - (ß= 0.45, p-value < 0.01) - accepted;

H11: The society context has a positive impact on students' context - (ß= 0.12, p-value = 0.01) - accepted;

Based on the analysis, it was found that the coefficient ß registers a negative value for the SocPerc and DecSteps variables (-0.03), while positive values were obtained for the other blocks. Regarding the variables with a negative ß coefficient, it can be seen that for an increase of one unit in the SocPerc variable, the DecSteps variable will vary by -0.03 units.

Another coefficient, the p-value, indicates a very good probability of establishing connections between variables for all blocks, except those identified between CompPerc -> ComCntxt, PersPerc -> DecSteps, UnivPerc -> DccSteps, and SocPerc -> DecSteps, where the values exceed the acceptable limit.

However, based on the statistical data presented in Table 1, we can consider the model valid. The APC index with a value of 0.195 and its significance with a p-value of <0.001, as well as other values (AARS, AVIT, AFVIF, GoF, SPR, RSCR, SSR, and NLBCDR) within ideal limits, lead us to believe that the model is efficient in terms of causality relationships.

To fulfil 03, we descriptively analysed responses to the question "Thinking about the steps you went through when deciding to pursue university studies, please rank (step 1 -step 5) the following actions:" asking respondents to place the five actions of the decision-making process in their preferred order (Kotler and Armstrong, 2008).

In Figure 7, we observe the order of importance in deciding to pursue university studies. Recognising the need takes the first place among the 255 respondents, followed by searching for alternatives, with 206 respondents ranking it second. The third step is represented by an information search (191 respondents), mentioning that only after this step do they decide to commit (152 respondents mentioning this action in the fourth step), and finally, they contemplate whether the acquisition is satisfactory or not (134 respondents mentioning this action as the last step). Based on this information, we can accept hypothesis Hl2, suggesting that the decision-making process undergoes modifications.

According to the results, evaluating alternatives is a step high school graduates take before processing information about a specific university study programme. This may happen because they arc not sure about their career before choosing a particular college and could believe, influenced by society and the university, that it offers employment opportunities and development directions in this regard. This deduction is based on the extracted information presented in Tables 2 and 3.

04. To determine the relevance of contexts for new respondents, we subjected a suggestive factor panel analysis using SPSS. Therefore, we subjected the variables SocCntxt, ComCntxt, UniCntxt and PrsCntxt to the analysis. A key coefficient indicating the importance of the relationship between the studied variables is the Kaiser-Meyer-Olkin coefficient, with a value of 0.806. Correlated with the significance of Bartlett's sphericity test with a value of 0, this demonstrates a significant relationship between the data, encouraging a factor reduction analysis, as presented in Table 4.

In Table 5, the results regarding the total variance expressed of the components of the analysed variable blocks are synthesised, highlighting the influence of six components/items of research, representing 58.801% of the maximum of 20, the first 6 having Eigenvalues coefficients greater than 1. The first component has the highest variation after rotation, representing a percentage of 12.158%, followed by component 2 with 11.226%, component 3 - 10.982%, component 4 - 10.497%, component 5 - 7.072%, and component 6 - 6.867%.

In Table 6, we presented a more detailed perspective on the evolution and adjustment of the components after rotation. This is a crucial step in factor analysis as it helps us to understand how variables (or elements) interact with component factors. These interactions are measured through the Pearson correlation coefficient. Focusing on Component 1, we observe that this component provides us with information about the factors that have the strongest correlations. In this context, we see that the elements PrsCntxtl, PrsCntxt2, UniCntxtl, UniCntxt2, and PrsCntxt4 are significantly positively correlated with this component. Therefore, we can deduce that 3 elements belong to the context in which students find themselves, while 2 elements belong to the university context, allowing us to accept hypothesis H13.

Conclusions

The research carried out allowed us to highlight that each participant in the educational process can influence the perception of study programmes and the choices of the candidates for them. Although perceptions of top universities are important, personal factors, such as aspirations and interests, are crucial in choosing a study programme. Almost all young people attach great importance to career opportunities and university reputations. Despite universities' efforts toward social integration, students focus more on their individual needs. These findings have helped us to recommend an increased focus on educational marketing to dynamically tailor educational offerings to the specific needs of young people. Additionally, we argued for the increased importance of data collection and analysis to generate and apply innovative educational mechanisms and processes. Regarding the decision-making process in choosing a study programme, students transition from evaluating alternatives to obtaining information, and the perception of the competitive university context decisively influences this process. The relationships between the entities involved in the decision are interdependent, relevant, and valid. The study suggests a qualitative approach to better understand the complex process of students choosing a faculty.

The research highlights that perception and personal factors influence students' decisions in choosing a study programme. Universities, faced with a competitive market, must anticipate demand and adjust programmes to remain relevant. The decision-making process of students is not dictated only by society or university requirements, but also by impressions of the competitive environment of the institution. An adaptable and sustainable approach to educational offerings can make education more relevant to student needs, preparing them to make informed choices and contribute to sustainable solutions.

Due to intense competition nationally and internationally, universities must rapidly adapt to meet current requirements. It is crucial for them to adjust marketing strategies and study programmes to meet students' needs and opinions, primarily influenced by personal goals and values. Flexibility becomes essential to maintain competitiveness and adapt to changes in education and the job market.

Higher education needs to reconsider its approaches in the face of increasing digitisation, adopting innovative teaching methods, and ensuring that study programmes are relevant to industry requirements. Universities should highlight the unique and innovative aspects of their programmes, including sustainability concerns and alignment with contemporary needs. Student and community participation, along with the promotion of research and external partnerships, can be key to attracting students and developing effective marketing strategies in the university environment. Understanding the influences on student decisions and the adaptability of educational institutions becomes imperative to maintaining relevance and effectiveness in the ever-changing educational landscape.

Sidebar

Please cite this article as:

Miron, D., Brandabur, R.E., Maitā, D.N., Darie, F.C., Goldbach, D. and Lixandru, I.D., 2024. The Influence of Contexts in the Process of Choosing a University Product. Amfi teatru Economic, 26(66), pp. 648-665.

DOI: https://doi.org/10.24818/EA/2024/66/648

Article History

Received: 29 December 2023

Revised: 9 February 2024

Accepted: 10 April 2024

Footnote

* Autor de contact, Dumitru Miron - e-mail: [email protected]

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(ProQuest: Appendix omitted.)