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The Effects of Voluntary and Mandatory Training Participation on the Dynamics of Transfer of Training for Different Training Types

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Title: The Effects of Voluntary and Mandatory Training Participation on the Dynamics of Transfer of Training for Different Training Types
Language: English
Authors: Bastian de Jong (ORCID 0000-0001-7848-1527), Joost Jansen in de Wal, Frank Cornelissen
Source: International Journal of Training and Development. 2025 29(4):419-432.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 14
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Adult Education
Descriptors: Training, Transfer of Training, Training Methods, Job Training, Employees, Job Skills, Soft Skills, Online Courses, In Person Learning, Mandatory Continuing Education, Guidelines
DOI: 10.1111/ijtd.12371
ISSN: 1360-3736
1468-2419
Abstract: Should participation in employee trainings be mandatory or voluntary? This remains an important matter for organizations aiming at fostering employee development. Previous studies have provided mixed evidence about the merits of mandatory or voluntary training participation for transfer of training. One explanation for this is that these studies did not take differences in training characteristics (i.e., soft- or hard-skills, online or in-person) into account. It also remains unclear how personal and contextual antecedents of transfer of training and transfer motivation differ between mandatory versus voluntary trainings. Departing from the Unified Model of Task-specific Motivation (UMTM), the aim of this study is to investigate the effects of mandatory or voluntary training participation on antecedents of transfer motivation, transfer motivation and transfer of training for different training characteristics. A total of 1122 trainees filled in a questionnaire covering the UMTM components directly after attending a training and 728 trainees indicated transfer of training after 6 weeks. Data were analyzed by means of multi-group structural equation modelling. The outcomes indicate that the effects of mandatory versus voluntary training participation on personal and contextual antecedents and transfer of training depend on whether trainings cover soft- or hard-skills, whereas voluntary training participation is more beneficial for transfer motivation, irrespective of other training characteristics. The findings underline that training content matters for the effects of mandatory and voluntary training participation on transfer of training. This provides guidelines towards trainers and policy makers in which cases mandatory or voluntary training participation is more beneficial.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1488353
Database: ERIC
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  Value: <anid>AN0189133091;bpu01dec.25;2025Nov10.01:24;v2.2.500</anid> <title id="AN0189133091-1">The Effects of Voluntary and Mandatory Training Participation on the Dynamics of Transfer of Training for Different Training Types </title> <p>Should participation in employee trainings be mandatory or voluntary? This remains an important matter for organizations aiming at fostering employee development. Previous studies have provided mixed evidence about the merits of mandatory or voluntary training participation for transfer of training. One explanation for this is that these studies did not take differences in training characteristics (i.e., soft‐ or hard‐skills, online or in‐person) into account. It also remains unclear how personal and contextual antecedents of transfer of training and transfer motivation differ between mandatory versus voluntary trainings. Departing from the Unified Model of Task‐specific Motivation (UMTM), the aim of this study is to investigate the effects of mandatory or voluntary training participation on antecedents of transfer motivation, transfer motivation and transfer of training for different training characteristics. A total of 1122 trainees filled in a questionnaire covering the UMTM components directly after attending a training and 728 trainees indicated transfer of training after 6 weeks. Data were analyzed by means of multi‐group structural equation modelling. The outcomes indicate that the effects of mandatory versus voluntary training participation on personal and contextual antecedents and transfer of training depend on whether trainings cover soft‐ or hard‐skills, whereas voluntary training participation is more beneficial for transfer motivation, irrespective of other training characteristics. The findings underline that training content matters for the effects of mandatory and voluntary training participation on transfer of training. This provides guidelines towards trainers and policy makers in which cases mandatory or voluntary training participation is more beneficial.</p> <p>Keywords: mandatory trainings; training characteristics; transfer motivation; transfer of training; voluntary trainings</p> <hd id="AN0189133091-2">Introduction</hd> <p>Every year, organizations invest heavily in employee trainings as they believe that employee development can aid their organizational development (Ford et al. [<reflink idref="bib21" id="ref1">21</reflink>]). An important open question for organizations is whether employees should participate in trainings mandatorily or voluntarily (Gegenfurtner et al. [<reflink idref="bib22" id="ref2">22</reflink>]). Organizations often struggle with this matter as voluntary participation often leads to less training attendance by employees than desirable (Lacerenza et al. [<reflink idref="bib39" id="ref3">39</reflink>]). An important consideration for deciding whether trainings should be mandatory or voluntary is the extent to which training content is being applied in practice (i.e., transfer of training, Curado et al. [<reflink idref="bib16" id="ref4">16</reflink>]). Sufficient transfer of training is crucial to ensure that trainings make their intended impact on practice (Curado et al. [<reflink idref="bib16" id="ref5">16</reflink>]; Ford et al. [<reflink idref="bib21" id="ref6">21</reflink>]). To date, however, there is mixed evidence for whether mandatory or voluntary training participation is more beneficial for transfer of training. There are studies indicating greater transfer of mandatory trainings (e.g., Cotterchio et al. [<reflink idref="bib14" id="ref7">14</reflink>]; Rynes and Rosen [<reflink idref="bib50" id="ref8">50</reflink>]), voluntary trainings (e.g., Gegenfurtner et al. [<reflink idref="bib22" id="ref9">22</reflink>]; Salamon et al. [<reflink idref="bib51" id="ref10">51</reflink>]; Yardley [<reflink idref="bib60" id="ref11">60</reflink>]) or no differences (Dysvik and Kuvaas [<reflink idref="bib19" id="ref12">19</reflink>]; Van Dongen et al. [<reflink idref="bib18" id="ref13">18</reflink>]).</p> <p>One explanation for these inconclusive findings is that other training characteristics were not considered in these studies. An important training characteristic for transfer of training identified in previous studies (e.g., Laker and Powell [<reflink idref="bib40" id="ref14">40</reflink>]; Massenberg et al. [<reflink idref="bib42" id="ref15">42</reflink>]; Mishra and Sahoo [<reflink idref="bib45" id="ref16">45</reflink>]) is the type of training content (i.e., whether trainings cover soft‐ or hard‐skills). Soft‐skill trainings (often open‐skills) focus on acquiring skills related to personal development and communication capabilities, whereas hard‐skill trainings (often closed‐skills) focus on acquiring knowledge and mastering specific procedures (Laker and Powell [<reflink idref="bib40" id="ref17">40</reflink>]). The type of training content might moderate the effects of voluntary or mandatory training participation on transfer of training. This is because trainees are expected to experience differences in resistance to attending trainings depending on whether trainings focus on hard‐ or soft‐skills (Laker and Powell [<reflink idref="bib40" id="ref18">40</reflink>]). Trainees often see more value in acquiring hard‐skills as they are often necessary to perform a specific job. For soft‐skills, on the other hand, trainees less often see the utility of acquiring them as they already possess specific knowledge about soft‐skills (Laker and Powell [<reflink idref="bib40" id="ref19">40</reflink>]). In addition, application of soft‐skill trainings is considered more difficult than hard‐skill trainings (Laker and Powell [<reflink idref="bib40" id="ref20">40</reflink>]), and if soft‐skills are applied in practice, its application might be less obvious than of hard‐skills. As such, trainees might be held less accountable by supervisors when they do not apply soft‐skill trainings which might impede the perceived utility of such trainings (Botke et al. [<reflink idref="bib7" id="ref21">7</reflink>]). These differences in perceived resistance and utility might be larger among soft‐skill trainings that are mandated, as organizations often fail to explain sufficiently why participation in mandatory trainings could be of added value for trainees themselves (Salamon et al. [<reflink idref="bib51" id="ref22">51</reflink>]).</p> <p>Another training characteristic that more recently emerged as relevant for transfer of training due to the rise ICT is whether trainings are provided online or in‐person (Martins et al. [<reflink idref="bib41" id="ref23">41</reflink>]). Online or in‐person trainings could also moderate the effects of voluntary versus mandatory training participation. Trainees need to invest more effort to participate in in‐person trainings (e.g., travel time, more active participation) compared to online trainings (Martins et al. [<reflink idref="bib41" id="ref24">41</reflink>]). When trainings are mandated, these efforts might be experienced as an additional burden for attendance in comparison to when trainings are attended voluntarily. However, these effects are yet to be empirically explored.</p> <p>A further unresolved question is whether effects of attending trainings mandatorily or voluntarily can be explained by how trainees perceive antecedents of transfer of training after attending trainings. Multiple antecedents have been identified, of which especially transfer motivation (i.e., the desire to use skills and insights acquired during the training in practice, Noe and Schmitt [<reflink idref="bib47" id="ref25">47</reflink>]) seems to play a pivotal role in predicting transfer of training (Gegenfurtner et al. [<reflink idref="bib23" id="ref26">23</reflink>]; Grohmann et al. [<reflink idref="bib27" id="ref27">27</reflink>]). If individuals are more motivated to transfer, the likelihood that transfer occurs increases (Gegenfurtner et al. [<reflink idref="bib23" id="ref28">23</reflink>]). Transfer motivation, in turn, is predicted by personal antecedents (e.g., self‐efficacy, feelings of autonomy), and contextual antecedents (e.g., organizational norms, organizational support; Blume et al. [<reflink idref="bib5" id="ref29">5</reflink>]; Gegenfurtner et al. [<reflink idref="bib23" id="ref30">23</reflink>]; Massenberg et al. [<reflink idref="bib42" id="ref31">42</reflink>]). Examining effects of participation type on these antecedents can provide more insight into which antecedents of transfer of training are affected by voluntary or mandatory training participation. It can also provide insight for policy makers and trainers into which antecedents warrant additional attention to optimize transfer of training of content offered in both voluntary and mandatory trainings.</p> <p>Previous research has provided evidence that trainees are more motivated for voluntary than mandatory trainings (Curado et al. [<reflink idref="bib16" id="ref32">16</reflink>]; Gegenfurtner et al. [<reflink idref="bib22" id="ref33">22</reflink>]; Salamon et al. [<reflink idref="bib51" id="ref34">51</reflink>]). Studies also showed that trainees of voluntary trainings tend to experience more involvement in their own learning process (Könings et al. [<reflink idref="bib37" id="ref35">37</reflink>]). As a result, these trainees are assumed to experience more satisfaction with their learning environment (Könings et al. [<reflink idref="bib37" id="ref36">37</reflink>]), whereas trainees of mandatory trainings are expected to experience less autonomy and less motivation to learn (Gegenfurtner et al. [<reflink idref="bib22" id="ref37">22</reflink>]). To date, it remains an open question whether these effects translate towards differences in experienced autonomy to apply training content and whether such effects also exist for other antecedents.</p> <p>This study examines the aforementioned gaps in the literature by investigating the effects of voluntary versus mandatory training participation for (antecedents of) transfer of training and their interrelationships for different training characteristics (i.e., soft‐ and hard‐skill trainings and online and in‐person trainings). This study does so through the lens of the Unified Model of Task‐specific Motivation (UMTM, De Brabander and Martens [<reflink idref="bib9" id="ref38">9</reflink>]). This leads to the following research questions:</p> <p></p> <ulist> <item> 1. To what extent does mandatory or voluntary training participation affect personal and contextual antecedents of transfer motivation?</item> <p></p> <item> 2. To what extent does mandatory or voluntary training participation affect transfer motivation?</item> <p></p> <item> 3. To what extent does mandatory or voluntary training participation affect transfer of training?</item> <p></p> <item> 4. To what extent do training characteristics (i.e., soft‐ and hard‐skill and online and in‐person) moderate the effects of mandatory versus voluntary training participation?</item> </ulist> <hd id="AN0189133091-3">The Unified Model of Task‐Specific Motivation</hd> <p>The UMTM aims to predict task‐specific motivation of individuals at a given moment in time. The UMTM forms an integration of six theories of motivation, namely: the self‐determination theory (Deci and Ryan [<reflink idref="bib17" id="ref39">17</reflink>]), expectancy‐value theory (Eccles and Wigfield [<reflink idref="bib20" id="ref40">20</reflink>]) theory of planned behaviour (Ajzen [<reflink idref="bib1" id="ref41">1</reflink>]), flow theory (Csikszentmihalyi [<reflink idref="bib15" id="ref42">15</reflink>]), social cognitive theory (Schunk and DiBenedetto [<reflink idref="bib55" id="ref43">55</reflink>]) and the person‐object theory of interest (Krapp [<reflink idref="bib38" id="ref44">38</reflink>]). Based on this integration, the UMTM aims to overcome the challenge of navigating through multiple theories that conceptualize motivation differently. The UMTM includes personal antecedents (e.g., self‐efficacy and perceived utility of a training) and contextual antecedents (e.g., supervisor support and social norms) of task‐specific motivation that are also described by existing transfer of training models (e.g., Grossman and Salas [<reflink idref="bib28" id="ref45">28</reflink>]; Holton [<reflink idref="bib29" id="ref46">29</reflink>]; Massenberg et al. [<reflink idref="bib42" id="ref47">42</reflink>]). However, in contrast to transfer of training models, the UMTM also takes the complex interrelationships of these factors into account and how they relate to different types of motivation. Based on this, the UMTM can inform other transfer of training models about how these factors together predict transfer of training. Previous empirical research has provided evidence that the UMTM can provide insight into which factors explain the extent to which both self‐ and externally reported transfer of training occurs and that it can be used to investigate differences in training characteristics (Boere et al. [<reflink idref="bib6" id="ref48">6</reflink>]; De Jong et al. [<reflink idref="bib32" id="ref49">32</reflink>]; Jansen in de Wal et al. [<reflink idref="bib30" id="ref50">30</reflink>]). As such, the UMTM is used as theoretical lens in this study (see Figure 1 for an overview).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01dec25/ijtd12371-fig-0001.jpg?ephost1=dGJyMMvl7ESepq84yOvsOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12371-fig-0001.jpg" title="1 The unified model of task‐specific motivation (De Brabander and Martens [9]), adapted to the transfer of training context (De Jong et al. [33])." /> </p> <p></p> <p>The UMTM conceptualizes affective and cognitive motivation types as affective and cognitive valences. <emph>Affective valences</emph> are defined as feelings individuals anticipate to experience when they would perform an activity (e.g., feeling happy about using a new skill in practice, De Brabander and Martens [<reflink idref="bib9" id="ref51">9</reflink>]). <emph>Cognitive valences</emph> are values ascribed to the results of performing an action (e.g., experiencing the utility of trainings as its application can increase the quality of work), which can be considered valuable for individuals themselves, but also for others (e.g., colleagues, supervisors). Cognitive values can therefore be personal and nonpersonal (De Brabander and Glastra [<reflink idref="bib8" id="ref52">8</reflink>]). Both valences can be positive and negative. If they are positive, individuals experience positive feelings and consequences due to the prospect of performing behaviour, whereas the opposite is the case when the valences are negative (De Brabander and Martens [<reflink idref="bib9" id="ref53">9</reflink>]).</p> <p>Positive affective and cognitive valences are expected to positively predict readiness for action (De Brabander and Glastra [<reflink idref="bib8" id="ref54">8</reflink>]), whereas the opposite is expected when the valences are negative. <emph>Readiness for action</emph> (e.g., transfer intention) is defined as the intention of individuals to perform task‐specific behaviour (De Brabander and Glastra [<reflink idref="bib8" id="ref55">8</reflink>]). Readiness for action, in turn, positively predicts <emph>action</emph> (e.g., transfer of training). Action is conceptualized as enacting task‐specific behaviour (De Brabander and Glastra [<reflink idref="bib8" id="ref56">8</reflink>]).</p> <hd id="AN0189133091-5">Task‐Specific Antecedents</hd> <p>The UMTM also includes personal‐ and contextual antecedents predicting affective and cognitive valences (De Brabander and Martens [<reflink idref="bib9" id="ref57">9</reflink>]). These antecedents can be translated to personal and contextual factors which in previous research were found to be predictors of transfer motivation and/or transfer of training (Blume et al. [<reflink idref="bib5" id="ref58">5</reflink>]; Gegenfurtner et al. [<reflink idref="bib23" id="ref59">23</reflink>]; Massenberg et al. [<reflink idref="bib42" id="ref60">42</reflink>]). The personal UMTM antecedents are (<reflink idref="bib1" id="ref61">1</reflink>) <emph>sense of personal relatedness</emph> (i.e., the extent to which individuals experience a sense of belonging and connection with individuals participating in the context of the task‐specific behaviour), (<reflink idref="bib2" id="ref62">2</reflink>) <emph>sense of personal competence</emph> (i.e., the judgement of individuals about whether they themselves are capable to enact behaviour successfully), and (<reflink idref="bib3" id="ref63">3</reflink>) <emph>sense of personal autonomy</emph> (i.e., the extent to which individuals consider themselves as a cause of choosing and performing behaviour) (De Brabander and Martens [<reflink idref="bib9" id="ref64">9</reflink>]). The contextual UMTM antecedents are (<reflink idref="bib1" id="ref65">1</reflink>) <emph>subjective norm</emph> (i.e., the propensity of individuals to abide by the (dis)agreement of significant others for enacting specific behaviour), (<reflink idref="bib2" id="ref66">2</reflink>) <emph>perceived external support</emph> (i.e., the extent to which individuals experience support from their environment, such as sufficient application time and supervisory support, to perform specific behaviour) and (<reflink idref="bib3" id="ref67">3</reflink>) <emph>perceived freedom of action</emph> (i.e., the extent to which individuals experience freedom in making choices for selecting and performing task‐specific behaviour) (De Brabander and Martens [<reflink idref="bib9" id="ref68">9</reflink>]).</p> <p>These antecedents are associated with each other and the valences in multiple ways. First, perceived freedom of action is hypothesized to predict sense of personal autonomy, in line with the self‐determination theory, as experiencing more freedom to make choices granted by your environment (i.e. perceived freedom of action) is expected to influence the extent to which an individual experiences volition to display specific behaviour (i.e., sense of personal autonomy, De Brabander and Martens [<reflink idref="bib9" id="ref69">9</reflink>]). Second, whereas sense of personal relatedness is expected to predict subjective norm (De Brabander and Martens [<reflink idref="bib9" id="ref70">9</reflink>]). Thirdly, perceived external support and sense of personal competence together form <emph>feasibility appraisal</emph>, which is defined as expectations of individuals regarding the feasibility of performing behaviour successfully (De Brabander and Martens [<reflink idref="bib9" id="ref71">9</reflink>]). Fourthly, subjective norm, sense of personal relatedness and feasibility appraisal are hypothesized to negatively predict negative valences and positively predict positive valences, in line with the self‐determination theory, social cognitive theory and expectancy‐value theory (Ajzen [<reflink idref="bib1" id="ref72">1</reflink>]; Bandura [<reflink idref="bib3" id="ref73">3</reflink>]; Eccles and Wigfield [<reflink idref="bib20" id="ref74">20</reflink>]; Deci and Ryan [<reflink idref="bib17" id="ref75">17</reflink>]). Sense of personal autonomy is expected to have reciprocal associations with affective valences (De Brabander and Martens [<reflink idref="bib9" id="ref76">9</reflink>]), whereas it is hypothesized to positively predict positive cognitive valences and negatively negative cognitive valences, in line with the self‐determination theory (Deci and Ryan [<reflink idref="bib17" id="ref77">17</reflink>]). Finally, based on previous research it is also possible that antecedents have direct effects on readiness for action (Boere et al. [<reflink idref="bib6" id="ref78">6</reflink>]; Jansen in de Wal et al. [<reflink idref="bib30" id="ref79">30</reflink>]; De Brabander and Glastra [<reflink idref="bib8" id="ref80">8</reflink>]), in line with the theory of planned behaviour (Ajzen [<reflink idref="bib1" id="ref81">1</reflink>]).</p> <hd id="AN0189133091-6">Hypothesized Effects of Voluntary Versus Mandatory Training Participation</hd> <p>It can be expected that whether training participation is mandatory or voluntary affects the UMTM components. This is because, according to the Hierarchical Model of Intrinsic and Extrinsic Motivation (HMIEM) (Vallerand [<reflink idref="bib58" id="ref82">58</reflink>]), situational motivation is influenced by motivation on a broader, contextual level. When we translate the dynamics of the HMIEM to the transfer of training context, whether training participation is voluntary or mandatory resides at the contextual level, whereas transfer (motivation) and its antecedents concern particular, task‐specific behaviour and therefore reside at the situational level.</p> <p>We expect effects of mandatory or voluntary training participation on perceived freedom of action, sense of personal autonomy and negative valences. The reason organizations often mandate trainings is because they are considered important for organizational development (Baldwin et al. [<reflink idref="bib2" id="ref83">2</reflink>]; Salas et al. [<reflink idref="bib53" id="ref84">53</reflink>]). Yet, trainees of mandated might feel less ownership over their own learning processes (Deci and Ryan [<reflink idref="bib17" id="ref85">17</reflink>]) and less freedom to make choices with regard to their learning opportunities (Gegenfurtner et al. [<reflink idref="bib22" id="ref86">22</reflink>]). Furthermore, organizations often communicate that trainings that are mandated are important for organizational development (Baldwin et al. [<reflink idref="bib2" id="ref87">2</reflink>]; Curado et al. [<reflink idref="bib16" id="ref88">16</reflink>]). This could be interpreted as external pressure for trainees to apply training content, which can lead to increased feelings of alienation and powerlessness (Könings et al. [<reflink idref="bib37" id="ref89">37</reflink>]), affecting negative affective valence. These effects can also affect negative cognitive valences. For instance, Gegenfurtner et al. ([<reflink idref="bib22" id="ref90">22</reflink>]) found that trainees of mandatory trainings more often expect negative consequences as a result of applying training than trainees of voluntary trainings. Summarizing, we expect that trainees of mandatory trainings experience less perceived freedom of action (H1) and sense of personal autonomy (H2) and more negative affective (H3) and cognitive valences (H4) in comparison to trainees of voluntary trainings.</p> <p>Effects on feasibility appraisal are also expected. As organizations are expected to consider mandatory trainings as more important, they could invest effort to support employees in applying training content (Curado et al. [<reflink idref="bib16" id="ref91">16</reflink>]; Gegenfurtner et al. [<reflink idref="bib22" id="ref92">22</reflink>]), whereas they would not do that to such an extent for voluntary trainings (Gegenfurtner et al. [<reflink idref="bib22" id="ref93">22</reflink>]). For example, organizations could grant more time towards trainees to apply training content of mandatory trainings and provide sufficient supervisory support. Furthermore, receiving more supervisory support can also be beneficial for self‐efficacy (i.e., sense of personal competence, Chiaburu et al. [<reflink idref="bib13" id="ref94">13</reflink>]). As such, we expect that trainees of mandatory trainings experience more feasibility appraisal than trainees of voluntary trainings (H5).</p> <p>As we have expectations for personal and contextual antecedents, we expect effects for positive valences as well. Trainees of voluntary trainings might see more utility for applying training content because they themselves chose to participate in specific trainings (Baldwin et al. [<reflink idref="bib2" id="ref95">2</reflink>]; Mathieu et al. [<reflink idref="bib44" id="ref96">44</reflink>]). As a result, they could also experience more enjoyment in applying training content (Salamon et al. [<reflink idref="bib51" id="ref97">51</reflink>]). Empirical evidence underlines this by indicating that trainees of voluntary trainings experience more enjoyment and see more utility in applying training content in comparison to trainees of mandatory trainings (Curado et al. [<reflink idref="bib16" id="ref98">16</reflink>]; Gegenfurtner et al. [<reflink idref="bib22" id="ref99">22</reflink>]). Based on these findings, we expect that trainees of voluntary trainings experience more positive affective (H6) and cognitive valences (H7) in comparison to trainees of mandatory trainings.</p> <p>As a result of our expectations for the valences, we also expect trainees of voluntary trainings to experience a higher transfer intention and transfer of training (H8) in comparison to trainees of mandatory trainings. This would be in line with the dynamics of the UMTM components found in previous studies (e.g., De Jong et al. [<reflink idref="bib32" id="ref100">32</reflink>]; Jansen in de Wal et al. [<reflink idref="bib30" id="ref101">30</reflink>]) and with empirical findings between mandatory versus voluntary trainings for transfer intention (De Jong et al. [<reflink idref="bib32" id="ref102">32</reflink>]) and transfer of training (Gegenfurtner et al. [<reflink idref="bib22" id="ref103">22</reflink>]; Salamon et al. [<reflink idref="bib51" id="ref104">51</reflink>]; Yardley [<reflink idref="bib60" id="ref105">60</reflink>]).</p> <p>Finally, we expect that effects of mandatory or voluntary training participation are moderated by training characteristics. As explained above, trainees often see less added value of using content of soft‐skill trainings in practice in comparison to hard‐skill trainings (Laker and Powell [<reflink idref="bib40" id="ref106">40</reflink>]). Trainees also need to invest more effort to engage in in‐person trainings than online trainings (Martins et al. [<reflink idref="bib41" id="ref107">41</reflink>]). This might especially have negative effects when trainings are attended mandatorily. As such, we expect that the negative effects of mandatory participation on UMTM components are more pronounced in trainees who participate in in‐person and/or soft‐skill trainings (H9).</p> <p>There are also components for which we do not expect effects of mandatory or voluntary training participation. We expect no effects for sense of personal relatedness and subjective norm as such components are more related to the work environment and not so much to the training context (Gilpin‐Jackson and Bushe [<reflink idref="bib25" id="ref108">25</reflink>]; Laker and Powell [<reflink idref="bib40" id="ref109">40</reflink>]).</p> <hd id="AN0189133091-7">Methods</hd> <p></p> <hd id="AN0189133091-8">Sample and Procedure</hd> <p>The study was performed at the Dutch police academy (PA) and the Dutch judicial training institute (SSR) who provide trainings towards employees working for the police or judiciary. We collected data among trainees who attended to one of the 264 included trainings. Of these trainings, 135 (51.5%) were provided by PA, whereas 129 (48.9%) trainings were offered by SSR. We selected trainings if using its content in practice was not compulsory. Transfer of training would otherwise be the result of obliging to transfer training content instead of transfer motivation. It was also required that trainings covered one specific topic (e.g., learning how to communicate more efficiently) as the UMTM aims to predict task‐specific behaviour.</p> <p>Trainers of the included trainings indicated whether attending their trainings was voluntary or mandatory. A total of 112 trainings (42.4%) were attended voluntarily, whereas 152 trainings (57.6%) were attended mandatorily. Moreover, two researchers coded each training as either hard‐ or soft‐skill. This was done based on training descriptions provided by the PA and SSR regarding the content covered in trainings and the learning goals. Both researchers coded independently of each other whether trainings were more focused on hard‐ or soft‐skills. We used the definition of hard‐ and soft‐skill trainings as described by Laker and Powell ([<reflink idref="bib40" id="ref110">40</reflink>]) as guideline for coding the trainings. We found a substantial interrater reliability between both researchers (<emph>κ</emph> = 0.71; Warrens [<reflink idref="bib59" id="ref111">59</reflink>]). Cases in which we did not agree with one another we discussed why we thought a training would cover mostly soft‐ or hard‐skills to reach an agreement. In rare cases, we contacted trainers of the trainings to ask their opinion regarding whether they thought their training covered soft‐ or hard‐skills. Eventually, a total of 160 trainings (60.6%) covered soft‐skills and 104 trainings (39.4%) covered hard‐skills. A total of 27.6% of the participants participated mandatorily in soft‐skill trainings, whereas 72.4% participated voluntarily. Among hard‐skill trainings, 35.9% of the participants participated mandatorily and 64.1% voluntarily. The number of trainings provided online was 136 (51.5%) and these trainings were synchronously provided via Teams, Zoom or Skype. The remaining 128 trainings (48.5%) were provided in‐person. Of the online trainings, 39.9% of the participants participated mandatorily and 60.1% voluntarily. For in‐person trainings, 35,9% of the participants participated mandatorily and 64.1% voluntarily. The number of training days ranged between half a day and 36 days, but the duration of most trainings was one or 3 days.</p> <p>The included trainings covered a mix of exercises and lectures. The lectures were focused on explaining specific content, whereas the exercises were a mix of individual and group assignments with the aim of letting participants practice with training content. At the end of each training, participants were informed about the research and invited to fill in a questionnaire. Participation was voluntary and without incentives (see Table 1 for sample characteristics). After 6 weeks, participants indicated their transfer of training. This time period was based on the likelihood that participants would have had sufficient opportunities to transfer training content.</p> <p>1 Table Characteristics of the sample.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Demographic characteristic</th><th>Judicial training institute</th><th>Police academy</th><th>Total sample</th></tr></thead><tbody valign="top"><tr><td>Number of participants T1 (response rate)</td><td>595 (45.5%)</td><td>527 (55.1%)</td><td>1122 (49.5%)</td></tr><tr><td>Indicated transfer at T2 (response rate)</td><td>458 (35.0%)</td><td>270 (28.2%)</td><td>728 (32.1%)</td></tr><tr><td>Filled in questionnaire at T1 and indicated transfer at T2 (response rate)</td><td>345 (26.4%)</td><td>188 (19.6%)</td><td>533 (23.5%)</td></tr><tr><td>Total number of unique participants (response rate)</td><td>706 (54.0%)</td><td>611 (63.8%)</td><td>1317 (58.1%)</td></tr><tr><td>Range in number of participants per training</td><td>1–12</td><td>1–18</td><td>1–18</td></tr><tr><td>Mean age in years (SD)</td><td>40.71 (11.50)</td><td>38.75 (10.36)</td><td>39.89 (11.03)</td></tr><tr><td>Percentage women</td><td>81.4%</td><td>30.4%</td><td>57.52%</td></tr><tr><td>Mean experience in years (SD)</td><td>7.00 (8.41)</td><td>5.05 (5.49)</td><td>6.12 (7.29)</td></tr><tr><td>Type of work (percentage of the whole sample)</td><td>Executing (59.5%)</td><td>Executing (88.5%)</td><td>Executing (73.8%)</td></tr><tr><td /><td>Supporting (37.0%)</td><td>Supporting (9.2%)</td><td>Supporting (23.3%)</td></tr><tr><td /><td>Governing (3.5%)</td><td>Governing (2.3%)</td><td>Governing (2.9%)</td></tr><tr><td>Profession (percentage of the whole sample)</td><td>Legal assistant (42.3%)</td><td>Police officer (32.8%)</td><td>Legal assistant (22.4%</td></tr><tr><td /><td>Administrative assistant 28.8%)</td><td>Investigator (26.1%)</td><td>Police officer (15.4%)</td></tr><tr><td /><td>Judge (6.2%)Administrative judicial assistant (5.2%)Manager (3.0%)</td><td>Manager (11.2%)Apprentice (9.5%)Security (2.1%)Intelligence (1.3%)</td><td>Administrative assistant (15.2%)Investigator (12.3%)Manager (7.3%)Apprentice (4.5%)Judge (3.3%)</td></tr><tr><td /><td>Other (14.5%)</td><td>Other (17%)</td><td>Other (22.9%)</td></tr></tbody></table> </ephtml> </p> <hd id="AN0189133091-9">Materials</hd> <p>For T1, we used a questionnaire representing the UMTM components (see De Jong et al. [<reflink idref="bib33" id="ref112">33</reflink>] for the whole questionnaire) adapted from the questionnaire of De Brabander and Glastra ([<reflink idref="bib8" id="ref113">8</reflink>]). All components except for nonpersonal positive and negative cognitive valence were measured with one item and answered on a bipolar seven‐point Likert scale. An example item is: <emph>I find the facilities in our court to apply what I have learned successfully [...]</emph>, which was answered from 1 (very obstructive) to 7 (very conducive). At T2, we measured self‐reported transfer of training with one item: <emph>To what extent did you put the learned content into practice?</emph>, which was answered from 1 (not at all) to 7 (very much). Nonpersonal cognitive valences were measured for every relevant stakeholder, which differed per context. For the police, these were the team, sector, police task and civilian. For the judiciary these were the team, court, judiciary and litigant. We matched actors that were not similar, leading to the following combinations: court/sector, judiciary/police task and litigant/civilian.</p> <p>For constructs measured with one item, reliability cannot be assessed with contemporary reliability indicators (e.g., Cronbach's α or McDonald's ω). Instead, reliability can be examined indirectly with Structural Equation Modelling (SEM) model‐fit indices as they were originally initiated as indices to evaluate the reliability of latent structural equated scores (Tucker and Lewis [<reflink idref="bib57" id="ref114">57</reflink>]). In addition, they were used 'to avoid models with superfluous parameters that assume meaningless values' (Browne and Cudeck [<reflink idref="bib10" id="ref115">10</reflink>], p. 136). Since unreliable item response patterns cannot predict or correlate with responses on other items, model‐fit indices provide indirect insight into the unreliability of item responses. Moreover, we aim to evaluate the predictive value of the latent structurally equated scores. Model‐fit coefficients provide indirect insight into reliability of these latent scores. That is, when there is support for the predictive validity of the questionnaire, there is also evidence for its reliability as validity is not possible without reliability. Previous studies already provided indirect evidence for the reliability of the one item per construct UMTM questionnaire (De Jong et al. [<reflink idref="bib32" id="ref116">32</reflink>], [<reflink idref="bib33" id="ref117">33</reflink>]; Jansen in de Wal et al. [<reflink idref="bib30" id="ref118">30</reflink>]; De Jong et al. [<reflink idref="bib31" id="ref119">31</reflink>]).</p> <hd id="AN0189133091-10">Data‐analysis</hd> <p></p> <hd id="AN0189133091-11">Assumption Checking</hd> <p>As a first step, we examined assumptions of linearity, multicollinearity, absence of univariate and multivariate outliers, homoscedasticity, normality of distributed data (Kline [<reflink idref="bib35" id="ref120">35</reflink>]) and independence of residuals (Barker and Shaw [<reflink idref="bib4" id="ref121">4</reflink>]). The analysis showed four outliers that we excluded from further analyses. All other assumptions were met.</p> <hd id="AN0189133091-12">Measurement Quality</hd> <p>To investigate the factor structure of nonpersonal positive and negative cognitive valences and feasibility appraisal (consisting of sense of personal competence and perceived external support), we performed a confirmatory factor analysis (CFA) in Mplus (Muthén and Muthén [<reflink idref="bib46" id="ref122">46</reflink>]). In addition, since our sample consisted of a voluntary and mandatory group, we examined measurement invariance for the latent variables. To be able to compare latent group means, at least partial scalar invariance should hold (Van de Schoot et al. [<reflink idref="bib54" id="ref123">54</reflink>]). To test model‐fit, we used multiple goodness‐of fit indices. For RMSEA and SRMR, a value below 0.08 was sufficient and below 0.05 good. For TLI and CFI, a value above 0.90 was sufficient and above 0.95 good (Geiser [<reflink idref="bib24" id="ref124">24</reflink>]). We employed a chi‐square difference test to compare different models. Model‐fit indices provided a good fit for the configural (<emph>χ</emph><sups>2</sups>(<reflink idref="bib60" id="ref125">60</reflink>) = 92.794, <emph>p</emph> < 0.001; RMSEA = 0.03; CFI = 0.99, TLI = 0.98, SRMR = 0.03), metric (<emph>χ</emph><sups>2</sups>(<reflink idref="bib67" id="ref126">67</reflink>) = 96.231, <emph>p</emph> = 0.01; RMSEA = 0.03; CFI = 0.99, TLI = 0.99, SRMR = 0.04) and scalar models (<emph>χ</emph><sups>2</sups>(<reflink idref="bib74" id="ref127">74</reflink>) = 113.920, <emph>p</emph> < 0.001; RMSEA = 0.03; CFI = 0.99, TLI = 0.99, SRMR = 0.04). Yet, the scalar model fitted significantly worse than the metric model ( <ephtml> <math altimg="urn:x-wiley:13603736:media:ijtd12371:ijtd12371-math-0001" display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><msup><mrow><mo>∆</mo></mrow><mn>2</mn></msup></mrow></mrow></semantics></math> </ephtml> (<reflink idref="bib7" id="ref128">7</reflink>) = 18.70, <emph>p</emph> = 0.01). In such cases, a model containing more constraints can be considered tenable if the CFI does not decrease with more than 0.01, the BIC decreases, and the RMSEA does not increase with more than 0.015 (Chen [<reflink idref="bib11" id="ref129">11</reflink>]; Cheung and Rensvold [<reflink idref="bib12" id="ref130">12</reflink>]; Van de Schoot et al. [<reflink idref="bib54" id="ref131">54</reflink>]). Since this was the case, we assumed measurement invariance between both groups. We also assessed measurement invariance for each training characteristic. We created subgroups for (<reflink idref="bib1" id="ref132">1</reflink>) soft‐skill trainings, (<reflink idref="bib2" id="ref133">2</reflink>) hard‐skill trainings, (<reflink idref="bib3" id="ref134">3</reflink>) online trainings and (<reflink idref="bib4" id="ref135">4</reflink>) in‐person trainings and compared the factor structure within each subgroup between voluntary and mandatory trainees. Outcomes of these analyses provided support for measurement invariance within each subgroup as well.</p> <p>As a next step we examined reliability of the questionnaire measuring the UMTM components. We specified a path model that contained the scalar invariance model for the latent variables and the other UMTM constructs represented by single items. These components were modelled in line with the dynamics of the UMTM and within this model we constrained relationships in the direction proposed by De Brabander and Martens ([<reflink idref="bib9" id="ref136">9</reflink>]). When items consistently did not relate or correlate with to each other in accordance with the expected UMTM dynamics (De Brabander and Martens [<reflink idref="bib9" id="ref137">9</reflink>]) then this would indirectly indicate unreliability. This turned out to be the case for sense of personal relatedness. After excluding this item, we found a sufficient to good model‐fit for most model‐fit indices (<emph>χ</emph><sups>2</sups>(<reflink idref="bib230" id="ref138">230</reflink>) = 619.565, <emph>p</emph> < 0.001; RMSEA = 0.06; CFI = 0.94, TLI = 0.92, SRMR = 0.10). In this model, the personal and contextual antecedents predicted the valences, and the valences predicted transfer intention which, in turn, predicted transfer of training. Together, this provided support for the predictive validity of the questionnaire. As such, we found indirect support for the reliability of the questionnaire.</p> <hd id="AN0189133091-13">Hypothesis Testing</hd> <p>To test our hypotheses, we performed a multi‐group SEM. We examined differences between voluntary and mandatory trainings for the general group and for each training characteristic (i.e., (<reflink idref="bib1" id="ref139">1</reflink>) soft‐skill trainings, (<reflink idref="bib2" id="ref140">2</reflink>) hard‐skill trainings, (<reflink idref="bib3" id="ref141">3</reflink>) online trainings and (<reflink idref="bib4" id="ref142">4</reflink>) in‐person trainings). To do so, we employed the model resulting from the reliability analysis. To be able to interpret mean differences between mandatory versus voluntary trainings, we constrained regression coefficients between the components to be equal between both groups.</p> <p>To compare intercepts and factor means (i.e., nonpersonal positive and negative cognitive valences and feasibility appraisal) between the mandatory and voluntary group, we first made a model in which the indicator intercepts and factor means were constrained to be equal between both groups and compared model‐fit of this model to a model in which intercepts and factor means were estimated freely. This was done with a chi‐square difference test. We only investigated differences between individual intercepts and factor means if the freely estimated model fitted significantly better than the constrained model. Differences in indicator intercepts were examined with Wald tests (Klopp [<reflink idref="bib36" id="ref143">36</reflink>]). A significant Wald test (<emph>p</emph> < 0.05) would indicate a significant intercept difference between mandatory and voluntary trainings. Moreover, we set factor means at zero for mandatory trainings (i.e., the reference group) and estimated factor means freely in voluntary trainings. As participants took part in trainings consisting of other participants, they were clustered in groups. Since we did not have group‐level hypotheses, we controlled for the clustered structure of the data by employing cluster‐robust fit statistics and standard errors (using option '<emph>type = complex</emph>' in Mplus 8.0) while using the maximum likelihood ratio estimator.</p> <hd id="AN0189133091-14">Results</hd> <p></p> <hd id="AN0189133091-15">Descriptive Statistics</hd> <p>Table 2 provides an overview of correlations between the UMTM components for the voluntary and mandatory groups. Most components correlate with each other in line with expectations of the UMTM. However, we did find some correlational differences between the voluntary and mandatory groups. In the mandatory group we found no correlations between negative cognitive valences and subjective norm and between positive cognitive valences and transfer intention. Sense of personal autonomy and perceived freedom of action also do not correlate with transfer of training. In the voluntary group we found no correlation between nonpersonal positive cognitive valence and sense of personal autonomy and perceived freedom of action. Also, perceived freedom of action does not correlate with transfer intention and nonpersonal negative cognitive valence does not correlate with transfer of training.</p> <p>2 Table Correlation matrix of mandatory and voluntary group.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Variable</th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th></tr></thead><tbody valign="top"><tr><td>1. Feasibility appraisal</td><td /><td>0.70<ext-link href="***" /></td><td>0.52<ext-link href="***" /></td><td>0.45<ext-link href="***" /></td><td>0.74<ext-link href="***" /></td><td>−0.51<ext-link href="***" /></td><td>‐.75<ext-link href="***" /></td><td>‐0.38<ext-link href="***" /></td><td>0.77<ext-link href="***" /></td><td>‐0.35<ext-link href="***" /></td><td>0.60<ext-link href="***" /></td><td>0.38<ext-link href="***" /></td></tr><tr><td>2. Subjective norm</td><td>0.70<ext-link href="***" /></td><td /><td>0.25<ext-link href="***" /></td><td>0.17<ext-link href="***" /></td><td>0.35<ext-link href="***" /></td><td>–0.21<ext-link href="***" /></td><td>0.33<ext-link href="***" /></td><td>–0.22<ext-link href="***" /></td><td>0.30<ext-link href="***" /></td><td>–0.22<ext-link href="***" /></td><td>0.26<ext-link href="***" /></td><td>0.21<ext-link href="***" /></td></tr><tr><td>3. Sense of personal autonomy</td><td>0.65<ext-link href="***" /></td><td>0.39<ext-link href="***" /></td><td /><td>0.31<ext-link href="***" /></td><td>0.33<ext-link href="***" /></td><td>–0.20<ext-link href="***" /></td><td>0.23<ext-link href="***" /></td><td>–0.18<ext-link href="***" /></td><td>0.05</td><td>–0.18<ext-link href="***" /></td><td>0.08<ext-link href="*" /></td><td>0.20<ext-link href="***" /></td></tr><tr><td>4. Perceived freedom of action</td><td>0.67<ext-link href="***" /></td><td>0.30<ext-link href="***" /></td><td>0.42<ext-link href="***" /></td><td /><td>0.26<ext-link href="***" /></td><td>–0.18<ext-link href="***" /></td><td>0.17<ext-link href="***" /></td><td>–0.15<ext-link href="***" /></td><td>0.05</td><td>–0.13<ext-link href="**" /></td><td>0.04</td><td>0.11<ext-link href="*" /></td></tr><tr><td>5. Positive affective valence</td><td>0.74<ext-link href="***" /></td><td>0.40<ext-link href="***" /></td><td>0.49<ext-link href="***" /></td><td>0.46<ext-link href="***" /></td><td /><td>–0.31<ext-link href="***" /></td><td>0.43<ext-link href="***" /></td><td>–0.16<ext-link href="***" /></td><td>0.36<ext-link href="***" /></td><td>–0.15<ext-link href="***" /></td><td>0.26<ext-link href="***" /></td><td>0.20<ext-link href="***" /></td></tr><tr><td>6. Negative affective valence</td><td>–0.58<ext-link href="***" /></td><td>–0.20<ext-link href="***" /></td><td>–0.40<ext-link href="***" /></td><td>–0.32<ext-link href="***" /></td><td>–0.42<ext-link href="***" /></td><td /><td>–0.18<ext-link href="***" /></td><td>0.22<ext-link href="***" /></td><td>–0.18<ext-link href="***" /></td><td>0.19<ext-link href="***" /></td><td>–0.18<ext-link href="***" /></td><td>–0.18<ext-link href="***" /></td></tr><tr><td>7. Pers. positive cognitive valence</td><td>0.59<ext-link href="***" /></td><td>0.35<ext-link href="***" /></td><td>0.26<ext-link href="***" /></td><td>0.15<ext-link href="**" /></td><td>0.43<ext-link href="***" /></td><td>–0.22<ext-link href="***" /></td><td /><td /><td>0.62<ext-link href="***" /></td><td>–0.17<ext-link href="***" /></td><td>0.33<ext-link href="***" /></td><td>0.23<ext-link href="***" /></td></tr><tr><td>8. Pers. negative cognitive valence</td><td>–0.30<ext-link href="**" /></td><td>–0.07</td><td>–0.22<ext-link href="***" /></td><td>–0.29<ext-link href="***" /></td><td>–0.13<ext-link href="*" /></td><td>0.20<ext-link href="**" /></td><td>0.03</td><td /><td>–0.11<ext-link href="**" /></td><td>0.86<ext-link href="***" /></td><td>–0.11<ext-link href="**" /></td><td>–0.13<ext-link href="*" /></td></tr><tr><td>9. NP. positive cognitive valence</td><td>0.60<ext-link href="***" /></td><td>0.32<ext-link href="***" /></td><td>0.22<ext-link href="***" /></td><td>0.11<ext-link href="*" /></td><td>0.41<ext-link href="***" /></td><td>–0.24<ext-link href="***" /></td><td>0.80<ext-link href="***" /></td><td>0.08</td><td /><td>–0.11<ext-link href="*" /></td><td>0.33<ext-link href="***" /></td><td>0.16<ext-link href="**" /></td></tr><tr><td>10. NP. negative cognitive valence</td><td>–0.27<ext-link href="**" /></td><td>–0.04</td><td>–0.20<ext-link href="**" /></td><td>–0.27<ext-link href="***" /></td><td>–0.14<ext-link href="*" /></td><td>0.25<ext-link href="***" /></td><td>0.01</td><td>0.88<ext-link href="***" /></td><td>0.05</td><td /><td>–0.11<ext-link href="**" /></td><td>–0.09</td></tr><tr><td>11. Transfer intention</td><td>0.56<ext-link href="***" /></td><td>0.33<ext-link href="***" /></td><td>0.24<ext-link href="***" /></td><td>0.19<ext-link href="***" /></td><td>0.36<ext-link href="***" /></td><td>–0.13<ext-link href="*" /></td><td>0.39<ext-link href="***" /></td><td>–0.01</td><td>0.37<ext-link href="***" /></td><td>–0.01</td><td /><td>0.11<ext-link href="*" /></td></tr><tr><td>12. Transfer of training</td><td>0.53<ext-link href="***" /></td><td>0.32<ext-link href="***" /></td><td>0.15</td><td>0.09</td><td>0.30<ext-link href="***" /></td><td>–0.15<ext-link href="*" /></td><td>0.45<ext-link href="***" /></td><td>0.22<ext-link href="**" /></td><td>0.46<ext-link href="***" /></td><td>0.26<ext-link href="**" /></td><td>0.26<ext-link href="***" /></td><td /></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note:</emph> Correlations of the mandatory group can be found below the diagonal. Correlations of the voluntary group can be found above the diagonal.</p> <ulist> <item>2 Abbreviations: NP. = nonpersonal, Pers. = personal.</item> <item>3 * <emph>p</emph> < 0.05</item> <item>4 ** <emph>p</emph> < 0.01</item> <item>5 *** <emph>p</emph> < 0.001.</item> </ulist> <hd id="AN0189133091-16">Mean Differences Between Mandatory and Voluntary Trainings</hd> <p>Table 3 provides an overview of model‐fit of the different (sub)samples. Outcomes show that SRMR was somewhat too high for all (sub)samples, whereas TLI was somewhat too low for the soft‐skill and in‐person subsamples. However, since other model‐fit indices were sufficient to good and no model modifications made sense from a theoretical perspective, we considered these models as tenable.</p> <p>3 Table Model‐fit of training characteristic subsamples.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th /><th><p><math altimg="urn:x-wiley:13603736:media:ijtd12371:ijtd12371-math-0002" display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics xmlns=""><mrow><mrow><msup><mo>∆</mo><mn>2</mn></msup></mrow></mrow></semantics></math></p></th><th>DF</th><th><italic>p</italic></th><th>CFI</th><th>TLI</th><th>SRMR</th><th>RMSEA</th></tr></thead><tbody valign="top"><tr><td>General sample</td><td>711.527</td><td>262</td><td>< 0.001</td><td>0.94</td><td>0.92</td><td>0.10</td><td>0.05</td></tr><tr><td>Soft‐skill sample</td><td>539.393</td><td>262</td><td>< 0.001</td><td>0.91</td><td>0.89</td><td>0.10</td><td>0.06</td></tr><tr><td>Hard‐skill sample</td><td>565.419</td><td>262</td><td>< 0.001</td><td>0.93</td><td>0.91</td><td>0.12</td><td>0.06</td></tr><tr><td>Online sample</td><td>607.390</td><td>262</td><td>< 0.001</td><td>0.92</td><td>0.90</td><td>0.10</td><td>0.06</td></tr><tr><td>In‐person sample</td><td>517.791</td><td>262</td><td>< 0.001</td><td>0.92</td><td>0.89</td><td>0.10</td><td>0.06</td></tr></tbody></table> </ephtml> </p> <p>Table 4 provides an overview of intercept and factor mean differences between voluntary and mandatory trainings for each (sub)sample. In all cases, model‐fit was significantly better when intercepts and factor means were estimated freely between the mandatory and voluntary group than when intercept and factor means were constrained to be equal. We therefore examined individual intercept and factor mean differences between mandatory and voluntary trainings for each subsample. Our results show that there are multiple differences between participants of mandatory and voluntary trainings for personal and contextual antecedents. Subjective norm was significantly higher among trainees of voluntarily trainings than among trainees of mandatory trainings in the general, soft‐skill and online subgroup, whereas sense of personal autonomy was significantly higher for trainees of voluntary trainings in the soft‐skill group. Feasibility appraisal was significantly lower among trainees of mandatory trainings in comparison to trainees of voluntary trainings in the soft‐skill subgroup, whereas the opposite was found in the hard‐skill subgroup.</p> <p>4 Table Intercept differences between voluntary and mandatory trainings per (sub)group. intercepts of the mandatory trainings are fixed at zero.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th /><th>General</th><th>Soft‐skill</th><th>Hard‐skill</th><th>Online</th><th>In‐person</th></tr><tr valign="bottom"><th>Variable</th><th>Mean diff</th><th>SE</th><th>Mean diff</th><th>SE</th><th>Mean diff</th><th>SE</th><th>Mean diff</th><th>SE</th><th>Mean diff</th><th>SE</th></tr></thead><tbody valign="top"><tr><td>Sense of personal autonomy</td><td>0.07</td><td>0.08</td><td>0.37</td><td>0.15</td><td>−0.14</td><td>0.10</td><td>0.16</td><td>0.11</td><td>0.02</td><td>0.12</td></tr><tr><td>Perceived freedom of action</td><td>0.12</td><td>0.10</td><td>0.21</td><td>0.16</td><td>‐0.02</td><td>0.12</td><td>0.10</td><td>0.12</td><td>0.30</td><td>0.19</td></tr><tr><td>Feasibility appraisal</td><td>0.03</td><td>0.12</td><td>0.67<ext-link href="*" /></td><td>0.22</td><td>−0.34</td><td>0.15</td><td>0.11</td><td>0.13</td><td>−0.24</td><td>0.28</td></tr><tr><td>Subjective norm</td><td>0.19</td><td>0.08</td><td>0.43<ext-link href="*" /></td><td>0.15</td><td>0.05</td><td>0.10</td><td>0.29<ext-link href="*" /></td><td>0.11</td><td>0.05</td><td>0.15</td></tr><tr><td>Positive affective valence</td><td>0.19<ext-link href="*" /></td><td>0.07</td><td>0.21</td><td>0.12</td><td>0.26</td><td>0.10</td><td>0.11</td><td>0.08</td><td>−0.34<ext-link href="*" /></td><td>0.12</td></tr><tr><td>Negative affective valence</td><td>0.08</td><td>0.08</td><td>0.12</td><td>0.14</td><td>0.02</td><td>0.12</td><td>0.21</td><td>0.10</td><td>0.08</td><td>0.15</td></tr><tr><td>Positive cognitive valence (p)</td><td>0.21</td><td>0.09</td><td>0.29</td><td>0.14</td><td>0.13</td><td>0.12</td><td>0.27</td><td>0.11</td><td>0.07</td><td>0.15</td></tr><tr><td>Positive cognitive valence (np)</td><td>0.18</td><td>0.10</td><td>0.16</td><td>0.20</td><td>0.20</td><td>0.14</td><td>0.10</td><td>0.11</td><td>−0.07</td><td>0.21</td></tr><tr><td>Negative cognitive valence (p)</td><td>−0.23</td><td>0.14</td><td>0.04</td><td>0.18</td><td>0.28</td><td>0.13</td><td>0.22</td><td>0.14</td><td>−1.12<ext-link href="**" /></td><td>0.27</td></tr><tr><td>Negative cognitive valence (np)</td><td>−0.22</td><td>0.09</td><td>0.04</td><td>0.14</td><td>−0.27</td><td>0.12</td><td>0.03</td><td>0.10</td><td>−0.75<ext-link href="**" /></td><td>0.18</td></tr><tr><td>Transfer intention</td><td>0.21</td><td>0.12</td><td>0.51</td><td>0.23</td><td>0.02</td><td>0.14</td><td>0.26</td><td>0.15</td><td>0.09</td><td>0.15</td></tr><tr><td>Transfer of training</td><td>0.16</td><td>0.14</td><td>0.90<ext-link href="**" /></td><td>0.22</td><td>‐0.36</td><td>0.17</td><td>0.27</td><td>0.18</td><td>0.21</td><td>0.25</td></tr></tbody></table> </ephtml> </p> <ulist> <item>6 Abbreviations: np = nonpersonal; p = personal.</item> <item>7 * <emph>p</emph> < 0.01</item> <item>8 ** <emph>p</emph> < 0.001.</item> </ulist> <p>Concerning the valences, transfer intention and transfer of training, we found that trainees of voluntary trainings scored significantly lower on personal negative cognitive valence than trainees of mandatory trainings among the in‐person group, whereas we found similar effects for nonpersonal negative cognitive valence for the general, hard‐skill and in‐person group. In addition, trainees of voluntary trainings scored significantly higher on negative affective valence in the online group in comparison to trainees of mandatory trainings. For positive affective valence, we found that trainees of voluntary trainings scored significantly higher than trainees of mandatory trainings among the general and soft‐skill subgroup, whereas the opposite was the case for the in‐person subgroup. For positive cognitive valences, we found that trainees of voluntary trainings experienced a higher positive personal cognitive valence in comparison to trainees of mandatory trainings, whereas no differences were found for nonpersonal positive cognitive valence. Finally, our results show that transfer intention and transfer of training are significantly higher among trainees of voluntary trainings in the soft‐skill group in comparison to trainees of mandatory trainings, whereas the opposite is the case for transfer of training in the hard‐skill group.</p> <hd id="AN0189133091-17">Discussion</hd> <p>Previous research provided mixed results between mandatory versus voluntary training participation on transfer of training (Cotterchio et al. [<reflink idref="bib14" id="ref144">14</reflink>]; Dysvik and Kuvaas [<reflink idref="bib19" id="ref145">19</reflink>]; Gegenfurtner et al. [<reflink idref="bib22" id="ref146">22</reflink>]). One explanation for these mixed outcomes could be that previous trainings did not consider whether trainings are provided online or in‐person and whether trainings cover soft‐ or hard‐skills. In addition, it remains unclear to what extent trainees perceive personal‐ and contextual antecedents of (motivation to) transfer differently for mandatory or voluntary trainings. Using the UMTM, the aim of this study was to examine effects of mandatory or voluntary training participation on personal and contextual antecedents of transfer motivation, transfer motivation and transfer of training for different training characteristics.</p> <hd id="AN0189133091-18">Mixed Effects for Personal and Contextual Antecedents</hd> <p>We found mixed effects among participants of voluntary versus mandatory trainings for personal and contextual antecedents. In line with H2, we found that sense of personal autonomy was higher among soft‐skill trainees of voluntary trainings than among soft‐skill trainees of mandatory trainings, whereas we did not find differences for perceived freedom of action (H1). These outcomes underline that experiencing more freedom to make choices is not a necessity to experience more volition to enact specific behaviour (Katz and Assor [<reflink idref="bib34" id="ref147">34</reflink>]). The differences between mandatory and voluntary soft‐skill trainees could be the result of the perceived utility of trainings. The added value of trainings in which trainees participate voluntarily could be clearer than for mandatory participating trainees (Salamon et al. [<reflink idref="bib51" id="ref148">51</reflink>]), and without understanding the relevance of the training, trainees might experience less autonomy to apply what they have learned in their work (Gegenfurtner et al. [<reflink idref="bib23" id="ref149">23</reflink>]). This could especially play a role in soft‐skill trainings as the utility of participating in those trainings is often less clear for trainees than among hard‐skill trainings (Laker and Powell [<reflink idref="bib40" id="ref150">40</reflink>]).</p> <p>For feasibility appraisal, we found that mandatory training participation is more beneficial among hard‐skill trainings, whereas the opposite is the case for soft‐skill trainings, providing partial support for H5. An explanation for the latter finding could be that soft‐skill trainings often involve personal development which could be perceived as relevant by individuals themselves (Boere et al. [<reflink idref="bib6" id="ref151">6</reflink>]), especially if trainees participate voluntarily (Baldwin et al. [<reflink idref="bib2" id="ref152">2</reflink>]). These trainees might therefore aim more at seeking support from their work environment by for example approaching colleagues as aid in applying training content, which can also raise feelings of competence (i.e., self‐efficacy, Chiaburu et al. [<reflink idref="bib13" id="ref153">13</reflink>]). Trainees of mandatory soft‐skill trainings, on the other hand, could experience less motivation to seek such support. As a result, trainees of voluntary soft‐skill trainings could also expect to experience more feasibility appraisal than trainees participating mandatorily.</p> <hd id="AN0189133091-19">Effects on Transfer Motivation and Transfer of Training</hd> <p>We also found differences between mandatory and voluntary training participation on transfer motivation. In general, the findings indicate that trainees of voluntary trainings seem to experience a higher quality transfer motivation than trainees of mandatory trainings, in line with previous studies (Curado et al. [<reflink idref="bib16" id="ref154">16</reflink>]; Gegenfurtner et al. [<reflink idref="bib22" id="ref155">22</reflink>]; Salamon et al. [<reflink idref="bib51" id="ref156">51</reflink>]) and our expectations (H3, H4, H6, H7). Interestingly, the results show that trainees of voluntary trainings experienced higher personal positive cognitive valences but not nonpersonal positive cognitive valences. This might indicate that voluntary participating trainees do so mostly because of individual reasons (e.g., personal development), and not necessarily because of nonpersonal gains (i.e., for colleagues). For negative cognitive valences, on the other hand, most effects were found for nonpersonal negative cognitive valences, which were often higher among mandatory participating trainees. This might be because of organizations that communicate towards trainees that applying content of such trainings is important for organizational development (Baldwin et al. [<reflink idref="bib2" id="ref157">2</reflink>]; Curado et al. [<reflink idref="bib16" id="ref158">16</reflink>]). As a result, trainees could feel more pressured to apply the training content in their work, while they might not see the relevancy of this for themselves. Instead, they might experience this as conflicting with the quality of their regular work. For example, organizations might communicate the necessity towards their employees of writing verdicts in line with the guidelines explained in the training, which might take more time than the old way of working. Eventually, they might think this slows the productivity of writing verdicts as a whole for the organization. Consequently, employees might experience this as problematic for reaching organizational goals and hence see this as a negative consequence as a result of applying training content.</p> <p>Finally, the results indicate that transfer intention and transfer of training are higher among trainees participating voluntarily in soft‐skill trainings in comparison to trainees of mandatory trainings. This is in line with previous research (e.g., De Jong et al. [<reflink idref="bib32" id="ref159">32</reflink>]; Gegenfurtner et al. [<reflink idref="bib22" id="ref160">22</reflink>]; Salamon et al. [<reflink idref="bib51" id="ref161">51</reflink>]; Yardley [<reflink idref="bib60" id="ref162">60</reflink>]). For hard‐skill trainings, however, mandatory training participation is more beneficial for transfer of training than voluntary training participation, in line with the studies of Cotterchio et al. ([<reflink idref="bib14" id="ref163">14</reflink>]) and Rynes and Rosen ([<reflink idref="bib50" id="ref164">50</reflink>]). As such, we found partial support for H8 and support for H9. The findings among hard‐skill trainings might be the result of higher experiences in feasibility appraisal among mandatory hard‐skill trainees and the indirect effect of feasibility appraisal on transfer of training. It seems that feeling sufficiently competent and perceiving to receive sufficient organizational support play a key role for transfer of training among hard‐skill trainings. This corroborates previous studies showing the predictive value of organizational support and feelings of competence (e.g., Grossman and Salas [<reflink idref="bib28" id="ref165">28</reflink>]; Tonhäuser and Büker [<reflink idref="bib56" id="ref166">56</reflink>]) for transfer of training. Furthermore, these outcomes are also in line with the study of Salamon et al. ([<reflink idref="bib51" id="ref167">51</reflink>]), who showed that sufficient organizational support can alleviate the adverse effects for mandatory training participation on transfer of training.</p> <hd id="AN0189133091-20">Theoretical Implications and Directions for Future Research</hd> <p>Taken together, the results underline that effects of mandatory or voluntary training participation depend on whether trainings cover hard‐ or soft‐skills, whereas whether they are provided online or in‐person has limited effects. These outcomes highlight the importance of including type of training content as a factor that influences the effects of voluntary versus mandatory training participation, and that differences in training resistance between soft‐ and hard‐skills as presumed by Laker and Powell ([<reflink idref="bib40" id="ref168">40</reflink>]) could explain differential effects between mandatory and voluntary trainings for soft‐ and hard‐skill trainings. Together, these results provide an explanation for mixed findings on mandatory or voluntary training participation in previous research (e.g., Cotterchio et al. [<reflink idref="bib14" id="ref169">14</reflink>]; Dysvik and Kuvaas [<reflink idref="bib19" id="ref170">19</reflink>]; Gegenfurtner et al. [<reflink idref="bib22" id="ref171">22</reflink>]).</p> <p>We recommend future studies to take training characteristics into account as an additional factor that might explain mixed findings across different studies. For example, previous studies indicated mixed effects for interventions aimed at raising transfer of training (e.g., relapse prevention, goal‐setting, Blume et al. [<reflink idref="bib5" id="ref172">5</reflink>]; Rahyuda et al. [<reflink idref="bib49" id="ref173">49</reflink>]). Training characteristics, such as the type of training content, might provide an explanation for these mixed findings, which can increase our understanding as to for which type of trainings specific interventions are of added value, and for which types not.</p> <p>Results of our study also provide insight which antecedents of transfer of training are affected by attendance type and show that contextual components (i.e., mandatory or voluntary training participation) seem to affect situational components (i.e., personal and contextual antecedents, transfer motivation and transfer of training). As perceptions of antecedents were examined directly after trainees attended a training, future studies could examine to what extent differences in how these antecedents are perceived between trainees participating voluntarily or mandatorily sustain over time or whether differences increase or decrease. For example, future studies could examine antecedents of transfer once a month over a longer period of time. This would provide further insights into which antecedents are affected by voluntary or mandatory training participation.</p> <hd id="AN0189133091-21">Limitations</hd> <p>This study also has a number of limitations that should be acknowledged. Firstly, an external source (i.e., the trainer of the training) rated trainings as voluntary or mandatory. However, trainees might not perceive participation in a mandatory training necessarily as mandatory, and trainees of voluntary trainings might not always experience their participation as voluntary. We therefore recommend future studies to include a measure in which trainees themselves rate to what extent they attended a training mandatorily or voluntarily. In doing so, we recommend using a similar measure that was used by Salamon et al. ([<reflink idref="bib51" id="ref174">51</reflink>]) based on which participants were classified as experiencing a low, moderate or high level of voluntary training participation.</p> <p>Secondly, due to limitations in sample size it was not possible to examine the effects of combinations of training characteristics (e.g., soft‐skill training provided online vs<emph>.</emph> a hard‐skill training provided in‐person) for mandatory or voluntary training participation. Yet, this would provide finer grained insights into the effects of mandatory or voluntary training participation for different training characteristics, and might shed more light on the limited effects found of mandatory or voluntary training participation for online and in‐person trainings. We therefore recommend future studies to examine effects of combinations of online or in‐person and training content for mandatory or voluntary training participation.</p> <p>Thirdly, we employed a self‐report measure to examine the variables related to our research questions and most components were measured at one point in time. This can increase the likelihood of common method bias, leading to inflated relationships between constructs (Podsakoff et al. [<reflink idref="bib48" id="ref175">48</reflink>]) and self‐reports tend to differ from ratings from thirds (Blume et al. [<reflink idref="bib5" id="ref176">5</reflink>]). We therefore recommend adding the assessment of thirds regarding measuring transfer motivation and transfer of training (cf. De Jong et al. [<reflink idref="bib32" id="ref177">32</reflink>]) along with self‐reports.</p> <p>Fourthly, we were unable to directly assess the reliability of the one‐item questionnaire used in this study. Even though previous studies provided evidence that one‐item questionnaires can yield a satisfactory reliability (e.g., Gogol et al. [<reflink idref="bib26" id="ref178">26</reflink>]), its reliability can be lower than of measures containing multiple items per construct (Gogol et al. [<reflink idref="bib26" id="ref179">26</reflink>]). We therefore recommend future studies to use multiple items per construct and employing a traditional reliability analysis (e.g., Cronbach's α) to assess its reliability.</p> <hd id="AN0189133091-22">Practical Implications</hd> <p>Based on our outcomes, we also have multiple recommendations for policy makers and trainers. We recommend practitioners to take into consideration whether the training content is focused on soft‐ or hard‐skills in their policy on mandatory or voluntary training participation. If trainings are focused on soft‐skills, we recommend voluntary participation in trainings. For hard‐skill trainings, mandatory participation seems to be more beneficial.</p> <p>If soft‐skill trainings cannot be provided voluntarily or if there is resistance against mandating hard‐skill trainings, we recommend trainers and practitioners to aim at supporting personal‐ and contextual antecedents. This can be done on the situational and contextual level as conceptualized by the aforementioned Hierarchical Model of Intrinsic and Extrinsic Motivation (HMIEM) (Vallerand [<reflink idref="bib58" id="ref180">58</reflink>]). On the situational level (i.e., within trainings) is seems to be important to raise sense of personal competence for both soft‐ and hard‐skill trainings. This could be done by adding a relapse prevention element at the end of trainings in which trainees acquire strategies that prevent them from falling back in their old work habits (Rahyuda et al. [<reflink idref="bib49" id="ref181">49</reflink>]).</p> <p>On the contextual level (i.e., within the work context), it seems to be important for both soft‐ and hard‐skill trainings that trainees experience sufficient support from the work environment (i.e., perceived external support). This can be done by informing supervisors about the content and objectives of the training and what kind of support trainees might need to apply the training content in practice (Massenberg et al. [<reflink idref="bib42" id="ref182">42</reflink>]). For mandatory soft‐skill trainings, we also recommend stimulating subjective norm and sense of personal autonomy. Subjective norm could be fostered by letting multiple employees and supervisors of the same team take part in trainings. This can increase the likelihood that the training content aligns with the organizational norms (Gilpin‐Jackson and Bushe [<reflink idref="bib25" id="ref183">25</reflink>]) or that the norms among employees within the organization are more aligned when employees participate in trainings as a group (Salamon et al. [<reflink idref="bib52" id="ref184">52</reflink>]). As a result, this could elicit positive responses among employees when training content would be used (Salamon et al. [<reflink idref="bib51" id="ref185">51</reflink>]). Finally, sense of personal autonomy could be raised by letting supervisors foster a shared interest between employees within the organization regarding the perceived utility of employing the training content in practice (Massenberg et al. [<reflink idref="bib43" id="ref186">43</reflink>]). This could increase the likelihood that employees use the training content out of their own volition.</p> <hd id="AN0189133091-23">Conclusion</hd> <p>This study has shed more light on the effects of mandatory versus voluntary training participation on (antecedents of) transfer. Based on the results of our study, organizations can make a better informed decision as to in which cases they should let their employees attend trainings mandatorily, in which cases voluntary participation would be a better decision and what they could do to diminish the negative effects of mandatory versus voluntary training participation. Eventually, this can aid organizations in ensuring that the content of trainings make their intended impact on practice to enable organizational development.</p> <hd id="AN0189133091-24">Acknowledgements</hd> <p>We would like to thank all employees of the training and study centre for the judiciary and the police academy for their approval of using their trainings in this study.</p> <hd id="AN0189133091-25">Ethics Statement</hd> <p>This study was approved by the Ethics Review Board of the University of Amsterdam.</p> <hd id="AN0189133091-26">Conflicts of Interest</hd> <p>The authors declare no conflicts of interest.</p> <hd id="AN0189133091-27">Data Availability Statement</hd> <p>The data set analyzed during the current study is not publicly available due to privacy regulations at both the police academy and judicial training institute. 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  Data: The Effects of Voluntary and Mandatory Training Participation on the Dynamics of Transfer of Training for Different Training Types
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Bastian+de+Jong%22">Bastian de Jong</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-7848-1527">0000-0001-7848-1527</externalLink>)<br /><searchLink fieldCode="AR" term="%22Joost+Jansen+in+de+Wal%22">Joost Jansen in de Wal</searchLink><br /><searchLink fieldCode="AR" term="%22Frank+Cornelissen%22">Frank Cornelissen</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Training+and+Development%22"><i>International Journal of Training and Development</i></searchLink>. 2025 29(4):419-432.
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: 14
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  Data: 2025
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  Data: Journal Articles<br />Reports - Research
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  Label: Education Level
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  Data: <searchLink fieldCode="EL" term="%22Adult+Education%22">Adult Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Training%22">Training</searchLink><br /><searchLink fieldCode="DE" term="%22Transfer+of+Training%22">Transfer of Training</searchLink><br /><searchLink fieldCode="DE" term="%22Training+Methods%22">Training Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Job+Training%22">Job Training</searchLink><br /><searchLink fieldCode="DE" term="%22Employees%22">Employees</searchLink><br /><searchLink fieldCode="DE" term="%22Job+Skills%22">Job Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Soft+Skills%22">Soft Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Online+Courses%22">Online Courses</searchLink><br /><searchLink fieldCode="DE" term="%22In+Person+Learning%22">In Person Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Mandatory+Continuing+Education%22">Mandatory Continuing Education</searchLink><br /><searchLink fieldCode="DE" term="%22Guidelines%22">Guidelines</searchLink>
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  Label: DOI
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  Data: 10.1111/ijtd.12371
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  Label: ISSN
  Group: ISSN
  Data: 1360-3736<br />1468-2419
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Should participation in employee trainings be mandatory or voluntary? This remains an important matter for organizations aiming at fostering employee development. Previous studies have provided mixed evidence about the merits of mandatory or voluntary training participation for transfer of training. One explanation for this is that these studies did not take differences in training characteristics (i.e., soft- or hard-skills, online or in-person) into account. It also remains unclear how personal and contextual antecedents of transfer of training and transfer motivation differ between mandatory versus voluntary trainings. Departing from the Unified Model of Task-specific Motivation (UMTM), the aim of this study is to investigate the effects of mandatory or voluntary training participation on antecedents of transfer motivation, transfer motivation and transfer of training for different training characteristics. A total of 1122 trainees filled in a questionnaire covering the UMTM components directly after attending a training and 728 trainees indicated transfer of training after 6 weeks. Data were analyzed by means of multi-group structural equation modelling. The outcomes indicate that the effects of mandatory versus voluntary training participation on personal and contextual antecedents and transfer of training depend on whether trainings cover soft- or hard-skills, whereas voluntary training participation is more beneficial for transfer motivation, irrespective of other training characteristics. The findings underline that training content matters for the effects of mandatory and voluntary training participation on transfer of training. This provides guidelines towards trainers and policy makers in which cases mandatory or voluntary training participation is more beneficial.
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  Data: 2025
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        Value: 10.1111/ijtd.12371
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 419
    Subjects:
      – SubjectFull: Training
        Type: general
      – SubjectFull: Transfer of Training
        Type: general
      – SubjectFull: Training Methods
        Type: general
      – SubjectFull: Job Training
        Type: general
      – SubjectFull: Employees
        Type: general
      – SubjectFull: Job Skills
        Type: general
      – SubjectFull: Soft Skills
        Type: general
      – SubjectFull: Online Courses
        Type: general
      – SubjectFull: In Person Learning
        Type: general
      – SubjectFull: Mandatory Continuing Education
        Type: general
      – SubjectFull: Guidelines
        Type: general
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      – TitleFull: The Effects of Voluntary and Mandatory Training Participation on the Dynamics of Transfer of Training for Different Training Types
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          Identifiers:
            – Type: issn-print
              Value: 1360-3736
            – Type: issn-electronic
              Value: 1468-2419
          Numbering:
            – Type: volume
              Value: 29
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: International Journal of Training and Development
              Type: main
ResultId 1