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Communication

Triggers and Halts of Professional Mobility in Public Companies: A Case Study of the Romanian Forest Administration

by
Vasile Iosifescu
and
Marian Drăgoi
*
Faculty of Forestry, University of Suceava, 13, Uniersității Str., 720229 Suceava, Romania
*
Author to whom correspondence should be addressed.
Soc. Sci. 2023, 12(9), 468; https://doi.org/10.3390/socsci12090468
Submission received: 29 May 2023 / Revised: 16 July 2023 / Accepted: 28 July 2023 / Published: 22 August 2023
(This article belongs to the Topic Employee Quality of Life, Well-Being and Wellness: A Pathway to Organizational Performance, Efficiency, and Sustainability)
Review Reports Versions Notes

Abstract

:
This research tried to identify the most important factors that motivate or hinder forest engineers in commuting between their household and the regional office of the National Forest Administration, or prompt them to relocate their entire family to Bucharest, where the headquarters of the NFA is located, in seeking promotion in the professional hierarchy. A survey, administered as a Google form, was designed to carry out analysis of independent benefits, opportunities, costs, and risks. The decision process was designed as an analytic hierarchy process, and each one of these factors was a separate analytic hierarchy process. We found that forest engineers tend to be very conservative when it comes to changing their professional position from the forest district to the NFA regional office or NFA top management. On the one hand, the professional opportunities to promote upwards do not compensate for the fringe benefits gained at the forest district level, while the costs of living in a larger city outweigh the benefits, even though the house rent is paid by the employer.

1. Introduction

Social mobility increases are based on many dimensions and are an important feature of our modern society. As Fields (2019) writes, occupational, income, education, and even class mobility exist; indeed, Lal (1981) noted as much decades earlier in modern Indian society. Labor mobility has been studied mainly in sectors depending on highly developed technologies, such as health care (Glinos 2015) or ICT (Gonzalez Ramos and Vergas Bosch 2011).
Xu (2018) deployed a dynamic discrete choice model to analyze the decreasing rate of job switching, based on two public databases, i.e., a current population survey and survey of income and program participation. The study spanned more than 20 years and the author concluded that information technology contributed to a greater extent to better matching the appropriate job, especially for young people, whose switching rate decreased gradually, from decade to decade.
Despite intragenerational occupational mobility being limited, the occupational mobility of immigrants is high, as revealed in Italy, based on two identical surveys, one for natives and one for immigrants (Avola and Piccitto 2020). Within the European Union (EU), occupational mobility interferes with migration. Teague (1991) considered that non-recognition of training qualifications was an important halt of migration, while Groes et al. (2013), based on a large quantity of panel data, concluded that Danish people are more likely to change their occupation if their wages are either low or high.
Intergenerational social mobility is another large area of study in social sciences, where welfare economics mingles with sociology. As a matter of fact, this is the type of mobility which really matters in the long run, because greater social mobility offsets income inequality. Trying to demonstrate the relationship between inequality and social mobility, Andrews and Leigh (2009) overcame the lack of suitable data and carried out a cross-country study, encompassing more than three decades. For 16 countries where data about fathers’ occupation were available, the authors developed a multiple regression with hourly wages as a regressand, which allowed calculation of intergenerational elasticity as a percentage change of a son’s earning when a father’s income doubles. They concluded that the greater the social inequality, the less social mobility there is.
Kearney and Levine (2014) noted the contradiction between inequality and social mobility: across space, there is a negative correlation between them, but this correlation disappears when the study is carried out across time. Instead of studying that paradoxical problem, they developed an econometric model able to assess the likelihood of staying in school and, of course, the causes of dropping out. The two authors studied the cause of perpetual inequality of youth, linked with low socioeconomic status.
Heckman and Landersø (2021) found that, in Denmark at least, families and neighbors influence income mobility to a great extent, while intergenerational elasticity of income is greater when it is computed over a lifetime and not small intervals of wages.
Intergenerational mobility behaves in different ways, depending on many factors, the most important one being the father’s and the offspring’s incomes. Derived from a multiplicative model, the intergenerational elasticity of income is a good proxy for social mobility (Ichino et al. 2011).
Regressing the childhood inequality against intergenerational elasticity on income, one may produce the Great Gatsby Curve (GGC). Durlauf and Seshadri (2018) summarized a great deal of the literature focused on parametrizing the GGC, which can be linear, nonlinear, or represented as a Markov chain. Brandén (2019) decomposed the integrational mobility into four orthogonal components: educational attainment, cognitive skills, non-cognitive skills, and a residual effect, which captures socioeconomic status across generations.
Using the same methodologies to parametrize the GGC, Jerrim and Macmillan (2015) concluded that there is a strong correlation between income inequality, parental education, and offspring’s earnings. Therefore, high-inequality countries invest more in private education and less in public schools, at the expense of intergenerational mobility.
In Romanian forestry, occupational mobility interferes with geographical mobility because the organization the forest engineers most desire to join is the forest district administration. Given the nature of forests, working in this organization requires a well-defined and quite limited set of knowledge related to local ecological conditions, some tree species, some statistics, and the few pests jeopardizing those forest species. In addition to this basic knowledge, a forest engineer must know legislation, a few logging technologies, some protected species and habitats, and the main silvicultural systems applied in order to reduce the number of trees per hectare and regenerate the forest at maturity.
The manner in which decisions are made under these particularities makes the difference between a good and a bad professional; these are the so-called “hard” skills. Social and communication abilities (soft skills) are also important in preventing (or managing, if preventive measures fail) conflicts with various stakeholders. Despite being good professionals, some forest engineers are “missing the point” in their multilevel dialogue with the general public and media (Withrow-Robinson et al. 2002). Therefore, the real motive behind the decision to promote a forest engineer to a higher professional level could indeed be “soft” skills. Nudin et al. (2022) deployed random forest algorithms to predict graduates’ entrance to the labor market, while Reddy et al. (2022) identified the following soft skills as important: entrepreneurship, leadership, time management, and personality development. Apparently, in a hierarchical system like the Romanian National Forest Administration (NFA), these soft skills have little to do with forestry technicalities except for leadership and time management.
Therefore, given the narrow, localized hard skills and the ambiguous soft skills required, the higher the rank in a professional hierarchy, the more likely it validates the Peter principle (Martinez et al. 2011; Benson et al. 2019), according to which in a stiff hierarchy, each person attains a level where she/he is no longer competent. Abbot (2019) highlighted this risk in the UN structure, while Artz et al. (2020) estimated that 13% of European workers are complaining of bad bosses.
After the collapse of the communist regimes in Eastern Europe, a long process of restoring the property rights on private forests was initiated (Knorn et al. 2012; Abrudan et al. 2015; Mihai et al. 2017; Scriban et al. 2019). Currently, NFA is responsible for the sustainable forest management of public forests; moreover, it shoulders the responsibility of managing the majority of Romanian national and natural parks, which overlap significantly with Natura 2000 sites. The success of these two endeavors is a contentious issue, since NFA is seen as a controversial, highly politicized, and corrupt institution (Vasile 2009; Bouriaud and Marzano 2016; Vincent 2004). Nevertheless, no benchmark organization better than NFA has been identified so far. Regardless of these claims, many public forests have been certified to meet FSC standards, attesting to a positive FSC endorsement (Halalisan et al. 2016; Popa et al. 2019).

2. Materials and Methods

2.1. Snapshot on Romanian Forest Administration and How It Works

From an organizational viewpoint, the NFA operates like a rigid and highly centralized hierarchy. Regrettably, political coalitions that have led the Romanian Government have appointed their own general managers of NFA, while middle management positions were occupied by forest engineers who could readily commute by car or train to and from counties around Bucharest. This has severely biased the NFA’s professionalism and hindered the resolution of regional issues such as low accessibility of public forests, windthrow management, a positive relationship with associations of forest owners, and, last but not least, pest control in Norway spruce forests. Given these circumstances, exploring occupational mobility within the NFA is a worthwhile challenge, especially as it could facilitate a comprehensive reform of the entire forest administration under the broad umbrella of National Recovery and Resilience Plans (Bekker 2021; Natea 2021; Nicolescu 2022).
The public forests stretch over three million hectares, the rest of the forestland being managed by private forest districts. Some private forests are effectively managed by the NFA, if no other option is cost-effective. The NFA personnel has gradually shrunk, as the forestland restitution unfolded, from about 40,000 employees before the year of 2000 to 15,164 employees nowadays, of which 15,034 work in 41 county-level subsidiaries, summarizing 306 forest districts, which is the entry level in a professional career (data provided by www.rosilva.ro, accessed on 12 May 2023).
The NFA personnel are still envied by the rest of the forest engineers and technicians for higher wages and fringe benefits like different bonuses in kind, cheap housing, gratifications at the end of the year, a final gratification before retirement, and many others. Unfortunately, illegal logging, much more reported by media than analyzed to the root causes (Vasile and Iordăchescu 2022; Niţă 2015), paved the way to corruption (Koyuncu and Yilmaz 2013; Gisladottir et al. 2020) and overshadowed other social and professional peculiarities of forest management.

2.2. The Survey

In our approach, we referred to professional mobility as the capacity (and willingness, at the same time) to change the current job from a forest district (status quo—SQ) to a regional subsidiary of NFA (commute—CM), from a subsidiary to the headquarters of NFA, or, the shortest path, from a forest district to NFA headquarters (displacement—DP).
The decision to give up working for a forest district, with its picturesque lifestyle, for the multiple consequences a forest engineer may encounter in a higher hierarchical position is difficult. For the employer, another alternative, which is actually a Hobson’s choice, is to delegate the technical staff from the forest district to the NFA subsidiary, or from subsidiary to headquarters, whenever it is necessary. We did not consider this option in our study simply because it is just a cost-saving solution for the employer, not for the employee.
Based on these assumptions, we designed a survey to tell the benefits, opportunities, costs, and risks of taking or not taking advantage of the opportunity of one of the two options an employee of NFA may go for: a middle management level at county subsidiary of NFA, or the headquarters of NFA. The main office of NFA is located in Bucharest, a city where the cost of living is comparable with other European capitals, despite chaotic urbanization (Rufat and Marcińczak 2020). According to a recent study (Sdino et al. 2020), living in Bucharest brings more disadvantages than advantages, except for healthcare and education systems.
The survey was designed to enable a quadruple analytic hierarchy process (AHP) of benefits, opportunities, costs, and risk (BOCR) of the decisions already made by some forest engineers who decided or refused to make the leap to a higher professional position. The first stage of this analysis was to set up some relevant criteria, not necessarily professional but economic, social, and motivational. The decision-making criteria we concluded as relevant are presented in Table 1.
The first array of benefits refers to salary, terrain car and, quite importantly, the fringe benefits, which may include social and professional aspects like enough spare time for gardening or farming and different payoffs for transactions with wood (in money, or in kind). Gratifications are also paid on a costumery basis, two times a year, and could be quite substantial for middle and top management.
Spouse’s salary is important because, in many cases, at forest district level, the wives of the technical staff have jobs difficult to find in larger cities. Quite often the marginal salary earned by the ‘promoted’ husband is smaller than the salary his wife shall receive, in case of full-family displacement. Choosing to commute to a regional NFA subsidiary rather than keeping the current position at the forest district may trigger peers’ envy (Eissa and Wyland 2016); moreover, a commuter’s spouse may turn a regular employee into an insider for the forest district, where some closets are not quite clean; obviously, a potential spy is never ever welcome.
The inbound transportation matters for those who want to live and work in Bucharest, while the outbound transportation is important for commuters, especially for the ones who have to take care of their parents. This could be seen as a special case, and it is beyond the scope of this analysis; anyway, these are important criteria for making the decision to stay in the current position, if the risks outweigh the benefits.

2.3. AHP Structure

The method developed by Professor Thomas Saaty (Saaty 1990) is used worldwide for solving a large variety of problems encountered by decision makers (Ho 2008; Seyhan and Mehpare 2010; Yu et al. 2021).
Based on a template provided by www.superdecisions.com, we developed an AHP/BOCR model, which envelops four separated AHP analyses, whose results are merged into the final score, taking into account the weights of benefits, costs, opportunities, and risks. The template produces four different subnets, each subnet being processed as a single AHP problem.
The other two candidate ranking methods, contemplated before designing the survey, were Simple Additive Weighting (Afshari et al. 2010; Sahir et al. 2017; Setiawan et al. 2018), and TOPSIS (Zavadskas et al. 2016; Zulqarnain et al. 2020). We opted for AHP for three main reasons: (1) the easiness of using superdecision® software, which provides a template for BOCR, (2) the need to avoid numbers as input into the google form developed to collect input data, given the complexity of handling 20 criteria, and (3) consistent pairwise assessments between the three alternatives, thanks to a simplified mode to collect input data (see the next section).
The main advantage of AHP over all other Multicriteria Decision Methods (MCDM) is its flexibility in conveying not only the importance of an alternative against others, but also the likelihood or desirability of that specific alternative. This flexibility is very important when it comes to opportunities and risks, where things can be rather more desirable or more likely than more important.
When the criteria cannot be measured in physical units or currency, AHP is probably the most suitable MCDM for it is based on comparative and superlative adjectives: 1—equally important/likely/desirable; 3—quite important/likely/desirable; 5—more important/likely/desirable than; 7—very important/ important/likely/desirable, compared to…, and 9) extremely important/likely/desirable, compared to the other one. The even marks (2,4,6,8) can be used for fine-tuning the consistency index, addressed in the next paragraph.
The final weights of alternatives are given by the eigen vector corresponding to the highest eigen value of the pairwise assessment matrix procedure, which is common to the Markov chain model too (Stavrovsky et al. 2013). The greatest eigen value (λmax) is used to calculate the inconsistency coefficient (IC), which is given by formula
IC = (λmax − n)/(n − 1)
where n is the number of alternatives.
Put in simple words, consistency means that if A is three times more important than B, and B is two times more important than C, then A shall be about six times more important than C; if not, it is a situation of inconsistency. The inconsistency ratio (IR) is the proportion between the calculated IC and ‘another’ IC averaged across 50,000 simulations of an input square matrix, with the same number of lines, but populated with randomly generated values. These randomly generated inconsistencies vary between 0.58 for three alternatives and 1.51 for 10 alternatives. IR shall be smaller than 10%.

2.4. A Better Way to Collect Input for AHP

Both AHP and ANP are based on pairwise comparisons between criteria against goal (i.e., the decision to be made), and alternatives against criteria. The literature related to AHP/ANP is tremendous; by far, AHP is the most frequently used method for MCDM but little has been done to improve the way in which the pairwise evaluations are carried out, not only by decision makers but by laypeople unfamiliar with this technicality.
Apparently, the main merit of this method is the easiness of making pairwise comparison between criteria and the goal, and between alternatives against criteria. In recent years, some attempts have been carried out in order reduce the number of pairwise comparisons, from (n2 − n)/2 to n − 1 (Leal 2020; Nunes and Leal 2020); for three alternatives, this reduction is not significant (from 3 to 2 comparisons, in our case), but for large numbers a simplified approach is welcome. In our study, before comparing each pair of alternatives against criteria, we proceeded to prioritize the four clusters of benefits, opportunities, costs, and risks.
Unfortunately, a set of consistent evaluations is hard to achieve without using an excel file to test different scores; and pairwise comparisons on large data sets cannot be plugged into online surveys. Even so, the data shall be processed shortly afterwards and for this reason, we deployed google forms to collect data, Excel® spread-sheet to prepare input data, and the superdecisions® package to solve the problem for each respondent.
Because BOCR analysis implies six different AHPs for benefits, opportunities, costs, and risks (B vs. O, B vs. C, B vs. R, O vs. C, O vs. R, and C vs. R), we split this initial analysis into three simpler steps, dealt with on a 5-point Likert scale. Firstly, we compare the bunch of benefits and opportunities against the bunch of costs and risks, and secondly, we compare benefits with opportunities, and costs with risks, respectively. In so doing, instead of analyzing simultaneously six pairs of criteria, we used just three 5-point Likert scales. This simplification does not challenge the method itself, since each branch of BOCR is a different decision process.
Based on the experience gained with AHP/ANP (Drăgoi 2018; Drăgoi et al. 2015), we scaled down the evaluation process to selecting one of the four sets of ranks: A > B > C (with two options), A > B = C, and A = B > C. In Table 2, we exemplified the following sequence of preferences: status quo and commuting are equally important (A for both), while displacement is less preferred (B). An all-even situation does not alter the outcome of the rest of evaluations and it is considered the default option whenever the questionee came across a criterion that makes no difference between the three alternatives.
As a matter of fact, we split the pairwise evaluations into two different steps: Firstly, the questionee maps the three alternatives according to the lexicographic order (A, B, and C), by checking three boxes on different lines, but never two boxes on the same column. The next step is to choose one of the four pre-defined combinations of scores (Table 3), all of them being mathematically consistent. Suggestive bar charts produced by superdecision® software were embodied into the google form to facilitate quick answers.
The first five questionnaires were distributed by WhatsApp and e-mail in order to test whether or not the surveyees are able to fill in the form, without any concern for consistency. The outcome was disappointing because all evaluations carried out on crisp ranks (A > B > C) were not consistent at all. Realizing how difficult it is to obtain consistent analyses, we simplified the evaluation process as explained, but not at the expense of interviewee’s freedom to evaluate the most suitable combination of scores.
After the testing phase, we improved the AHP methodology as described above, and we distributed via e-mail a cover letter explaining our study, its aims, and the guidelines of using the AHP two-step evaluation. We also included the link to the google form, stored on a google drive.
Because some criteria may not be applicable to all respondents (like those related to spouses, parents, or children) the corresponding questions can be simply skipped by respondents. For these situations we had two options for final calculations: (1) to completely neglect those questions or (2) to assign equal scores (0.33) to all three alternatives. The first option shortens the list of multipliers considered for the final evaluation, without altering the final rank, while the latter option may flatten the final scores to zero due to numerous weights equal to 0.333. For instance, 0.71·0.4·0.75 = 0.213 (1st option) while 0.71·0.33·0.4·0.75 = 0.070 (2nd option). The first approach was chosen despite the risk of rank reversal, which is often discussed in the literature (Wang and Elhag 2006; Aires and Luciano 2018; Kizielewicz et al. 2021).
We distributed the survey using snowball sampling, trying to contact as many as possible professionals who have had some opportunities (taken or not) to move up the professional ladder. The data were extracted from the Google Drive as a simple spreadsheet, which was later transformed into a workbook. Afterwards, the data referring to each participant was copied into a separate sheet.

3. Results

The first set of respondents consisted of five forest engineers, who graduated from Batchelor’s and Master’s programs in forestry: one of them has been employed by the headquarters of NFA (priorly having a top-management position at the Sibiu regional subsidiary of NFA), one is a retired forest inspector, who worked with NFA and the Forest Guard, and three of them are forest engineers who had started their careers at forest districts. Nowadays they work with two large and complex regional subsidiaries of NFA, being in charge of preventing illegal logging, timber cruising, and pest control. All interviewees started their career at forest districts and only two of them had professional foresters (rangers, technicians, or engineers) as ancestors. These five questionnaires were filled in between January 2023 and March 2023, and resumed online, when an appropriate google form was re-designed, in order to provide consistent evaluations.
Between March, 4 and April, 12, as many as 15 respondents filled in the online survey, the one simplified as explained in the prior section. After May, 30, the survey was formally endorsed by a NFA frontpage and the response rate increased to 148 surveyees, who provided 124 valid answers. Regarding the gender representation, only four women responded to the survey.
We typified three behavioral patterns: the conservative, who simplifies the decision-making process to a simple benefits and cost analysis, the commuter, willing to seize the opportunity mainly to have a broader professional perspective from a regional office of NFA, and the relocatee, in quest of benefits and opportunities.
The average priorities shown in the first three lines of Table 4 (highlighted with bold figures) tell us that all respondents were quite consistent with themselves, in the sense that conservatives’ second option was commuting, not displacement, and the second option of commuters was, on average, the status quo, but not displacement.
Individuals who preferred to relocate their families were somehow inconsistent as their second choice was the status quo, not commuting to the county office of NFA. This is the first hint of the reluctance in moving upward on the professional hierarchy. The reason is straightforward: the benefits of living in a large city do not compensate for the cost of leaving a small city, where social links are stronger.
We also tried to find a correlation between the willingness to promote (indicated by the final score) and the average length of service on the current position, for the three types of respondents. Assuming no normal distribution for both variables (the final score and the average length of service on the latest position), we conducted an analysis of non-parametric correlation, using both Kendal and Spearman’s rank correlation. Both analyses failed for the same reason: the variation of the final score is too small compared to the variation of length of service. The hypothesis that the average length of service influences the decision to accept a promotion was not confirmed.
Table 5 shows the average scores of the three types of respondents against the four clusters of benefits, opportunities, cost, and risks. It is obvious that benefits and costs matter for conservatives, opportunities for commuters while relocatees are equally focused on benefits and opportunities (significant scores are highlighted with bold figures in the same table).
Presumably, the relocatees took advantage of external support provided by their families and/or their social webs if the costs and risks matter so little.
In Table 6, we summarized the criteria considered to be the most important for more than 50% of respondents from each class. These data convey deeper insights into what actually mattered when the decision was made, because the weights averaged in the previous table refer to clusters of criteria, not to any particular criterion.
If the earnings expressed in monetary terms (salaries and gratifications) are so important for all three types of employees, a simple way to facilitate professional mobility is to reduce the fringe benefits for those who work at the forest district, and increase the earnings of those who work at the NFA subsidiary.

4. Discussions

Not surprisingly, the risks do not matter too much because the NFA is a public entity, self-financed by wood sales, having a key position on the timber market (Niţă 2015).
The sample was biased by a greater number of conservatives and commuters (see Table 4, first column) who were content with their good salaries, fringe benefits, terrain cars, and relatively low cost of living. The respondents relied predominantly on hard skills and showed little interest in lifelong learning: the eight respondents who chose relocation had graduated a master’s program, which is a prerequisite for being promoted to a higher professional position. They were lured by the opportunity to leave the forestry system if needed, given the significant priority given to the chance to leave the sought-after position for another one, maybe with a multinational company, which would be impossible otherwise. As a matter of fact, one of the surveyees, initially employed by the NFA as head of the IT department, had left the organization for a multinational company shortly after being dismissed by a new general manager of the NFA.
All four interviewees who reached the NFA headquarters have grown-up children or do not have children at all; hence, costs and risks related to youngsters’ education and health care in Bucharest did not account for much. In other words, a ‘full-family’ relocation to Bucharest can be a risky endeavor; it is affordable only for small families or individuals; otherwise, it could be a logistical nightmare. Although there is an accommodation facility nearby the office building of NFA (which pops up whenever someone hits the NFA website (http://www.rosilva.ro, accessed on 12 May 2023), that facility was designed as a hotel, not as an apartment building.
According to the labor collective contract, the NFA pays employees who choose to relocate themselves to Bucharest the full rent for housing, and this criterion should not have been important at all, irrespective of the reference position of the respondent. Most likely, this ‘revenue’ does not compensate other costs, like heating, housekeeping, inbound transport, or parking services (some of them being overlooked by the survey).
Even though the NFA is a reliable institution for forest engineers, in the event of family relocation, both the spouse and grown-up children may be faced with precarious employment. Despite the fact that forestry trade unions are very proactive in European Union when it comes to labor legislation (Keune and Pedaci 2020), foresters’ spouses are not protected at all against labor precarization, especially in large cities. And this could be a serious reason for a good professional to be so reluctant to change their current position.
Another hypothesis is the Golden Cage Syndrome (Schabracq 2020), which is more likely to occur in small organizations (like a forest district) where full families (husband, wife, and even children) are employed. This syndrome was acknowledged by two respondents, who highly ranked the risk of having their wives fired from their existing position, if they would have left the forest district for a better position. The same syndrome applies to those whose old parents need support on a daily basis.
A solid terrain car, which is an important asset for being cost-effective in fieldwork, is less important at the forest district level, but very important for two-hour commuters and pretty important for those who chose relocation. There are two reasons that explain these preferences. The first one is the simple fact that fieldwork in forestry is time-consuming and the average millage at the forest district level is higher than the average millage at an NFA subsidiary (except the ones located in plain regions, where the situation is vice versa, due to small patches of forests spread out between large farmlands). The latter is the fuel-tracking system implemented by the NFA headquarter, where all cars must be fueled from a single fuel provider, and any extra millage needs additional explanations.
This study can be criticized for the relatively small number of respondents but, having in mind the complexity of multiple evaluations that the algorithm relies on, such a claim does not hold: Sivilevičius and Maskeliūnaite (2010), in order to make a better decision related to the quality of railway transport used only 11 surveys, based on an extensive Analytic Network Process. Apart from other studies based on AHP, we considered that experts’ opinions are not suitable for this analysis: an expert always comes up with an objective judgement, while we were interested exclusively in each person’s subjectivity.
Ishizaka and Labib (2009), also came up with a fair evaluation of AHP used to support multiple decisions, as it is implemented in Expert Choice®, the first commercial software of this kind. Asadabadi et al. (2019) effectively opened Pandora’s box in this issue, explaining why the whole bundle of MCDMs is not so appealing for managers, who intuitively can figure out the ranking errors that may occur when complex problems are to be solved. However, the simplified procedure we came up with in this study is a good premise for enlarging the number of respondents, since the inconsistency will not be a serious problem for online surveys.
Another problem with MCDMs, including AHP, is the aforementioned rank reversal issue, which occurs whenever a new alternative could turn the initial array of alternatives upside down (Maleki and Zahir 2013). However, one should be aware that rank reversal occurs when the number of alternatives changes. Whenever we add or eliminate one or more criteria, we are actually faced with a different problem; each respondent had her or his own decision to make, according to more or less criteria.
For the NFA, a consistent and cost-effective HR strategy is required more than ever due to the multiple challenges the forest management has to face in the new context of the EU programs related to climate change (Sandström et al. 2022), biodiversity conservation (Kokkoris et al. 2023), and the new regulation on deforestation free product (Hedemann-Robinson 2022).
The latest study on HR strategies for the forestry sector was carried out in 2014 (Vele et al. 2014) in Maramures County, and the main professional motivations were found to be labor productivity, remuneration, and competencies. Unfortunately, that study referred to all forest-related companies located in Maramures (from the NFA to logging companies), and the authors included the NFA among large employers, without addressing any specific organizational problems.
In order to promote high quality professionals to top-level management, the NFA should come up with two new facilities, at least, for the newcomers: attractive medical services (like the ones already provided by multinational companies (see Teodorescu et al. 2021)) and appropriate training programs, meant to diversify the employment opportunities forest engineers’ spouses may have in a large city.

5. Conclusions

In this study, based on more than 100 surveyees, we demonstrated how complex the promotion to a higher position in the NFA could be, when all aspects of social and family wellbeing are taken into account. Splitting the array of 20 exclusively non-professional criteria into benefits, opportunities costs, and risks we gave the surveyees an opportunity to take into account their propensity to be conservative or risk-takers, according to their family, cultural, and psychological profile.
Based on their preferences to remain in their current position, to commune on short distances, or to relocate their entire family to the Capital, where the headquarter of the NFA is located, we typified three categories of respondents: conservatives, commuters, and relocatees.
The way in which opportunities and benefits were combined by respondents showed that conservative people ground their decisions on sizable benefits and costs, the commuters put their hopes on opportunities (even though these opportunities are not explicitly professional), while the relocatees rely more on benefits and opportunities.
Most respondents preferred not to change their actual position in the NFA. The survey did not show explicitly how important the educational opportunities for children are simply because those four respondents who came to the NFA headquarters either do not have small children, or their children had already graduated high school. Instead, those who chose staying in the same position acknowledged the high cost of having their children educated in a large city like Bucharest. Hence, they prefer the current situation instead of being faced with new challenges and time-consuming solutions to problems that would not have occurred otherwise.
All in all, the risks any newcomer has to face within a large city seem to be not so important for forest engineers, who implicitly considered that the NFA is a very stable and solid institution: the risk of being fired is negligible for most respondents. However, without any protection for their spouses against labor precarization, most of the forest engineers will refuse a new job offered by the NFA in a large city.
As a first recommendation for the NFA human resource strategy, we suggest to tighten up or to better clarify the fringe benefits attainable at the forest district level. If forest engineers were not enjoying so many fringe benefits, or the benefits were dependent on some new key performance indicators, they probably would prefer a higher position in the NFA.
As we demonstrated, extensive studies based on AHP can now be easily carried out online, providing that no more than three alternatives can be chosen, and each respondent select one of the four predefined arrays of ranks. In so doing, the consistency of all assessments is ensured; moreover, by involving more experts in making the same decisions, the biases across experts can be better explained.

Author Contributions

Conceptualization, MCDM design, and English translation: M.D.; formal analysis, defining criteria, data processing in Excel and superdecisions®, and writing the Romanian version: V.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable. The Commission of Research Ethics of University of Suceava has competencies over research projects involving experiments on animals or clinical studies on human health.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Neither personal data (name, surname, or personal ID) nor e-mail addresses have been required from surveyees. Upon request, the final scores of each record are available. We explained the aim of the study in a cover letter, which was provided both in English and Romanian language to the editor. The cover letter (including the link to google forms) was cascaded by a small number of respondents to all surveyees without any obligation to report to the two authors the names or email addresses of the new respondents.

Data Availability Statement

The online survey is available (in Romanian language) at https://docs.google.com/forms/d/e/1FAIpQLScskWX76h6N1JkuSJW-hQIYQ9BrA0djBUwQa7GLmfr1kADXmg/viewform?usp=sf_link.

Conflicts of Interest

There are no conflict of interest.

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Table 1. The four clusters with decision-making criteria assessed by interviewees.
Table 1. The four clusters with decision-making criteria assessed by interviewees.
BenefitsOpportunitiesCostsRisks
Terrain car
Salary
Fringe benefits
Gratifications
Spouse’s salary		Better conditions to borrow money
Easier professional change
Better social status
Better health service
Better education for children		Higher rents
Costly health care
Cost of living
Parents health care
Household expenses
Outbound transportation
Inbound transportation		Relegation
Spouse’s relegation
Stress and professional diseases
Table 2. An example of the mapping matrix of the three alternatives (A = B > C).
Table 2. An example of the mapping matrix of the three alternatives (A = B > C).
Effective RankSQ (Status Quo)WC (Weekly Commute)DP (Displacement)
AXX
B X
C
Table 3. Pre-defined arrays of weights assignable to alternatives.
Table 3. Pre-defined arrays of weights assignable to alternatives.
Alternatives RanksABC
AB > C (1)0.75140.17820.0704
A > B > C (2)0.71660.20510.0667
A = B > C0.46670.46670.0667
A > B = C0.7500 0.12500.1250
Table 4. Average priorities of the three alternatives against the three types of surveyees.
Table 4. Average priorities of the three alternatives against the three types of surveyees.
Type of Employee (Number of Respondents in Each Class)Type of Respondent
Conservative (74)Commuter (46)Relocatee (4)
Status Quo 0.7610.173 0.281
Commuter0.1310.6830.051
Displacement0.1080.1440.668
Average length of service (years)131012
Average length of service on the latest position (years)768
Spearman’s rank correlation between main priority and average length of service0.0550.0730.213
Education and training for more than 50% respondentsBatchelor’s and high school Batchelor’sMaster’s
Table 5. Priorities of BOCR against type of employee.
Table 5. Priorities of BOCR against type of employee.
Decision Made byPriorities of Clusters (Normalized Values on Line)
BenefitsOpportunitiesCostsRisks
Conservative0.4630.0800.3900.067
Commuter0.1040.6970.1040.095
Relocatee 0.4260.4350.0870.052
Table 6. The criteria considered most important by more than 50% of respondents.
Table 6. The criteria considered most important by more than 50% of respondents.
Decision Made byMain Criterion of Each Cluster
BenefitsOpportunitiesCostsRisks
ConservativeFringe benefitsBetter educationCost of livingRelegation
CommuterSalary Cheap credit HousingStress
Relocatee Gratifications Children educationHousingSpouse’s relegation
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Iosifescu, V.; Drăgoi, M. Triggers and Halts of Professional Mobility in Public Companies: A Case Study of the Romanian Forest Administration. Soc. Sci. 2023, 12, 468. https://doi.org/10.3390/socsci12090468

AMA Style

Iosifescu V, Drăgoi M. Triggers and Halts of Professional Mobility in Public Companies: A Case Study of the Romanian Forest Administration. Social Sciences. 2023; 12(9):468. https://doi.org/10.3390/socsci12090468

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Iosifescu, Vasile, and Marian Drăgoi. 2023. "Triggers and Halts of Professional Mobility in Public Companies: A Case Study of the Romanian Forest Administration" Social Sciences 12, no. 9: 468. https://doi.org/10.3390/socsci12090468

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