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The Influence of Trainees' Characteristics on the Transfer of Entrepreneurship Training: Evidence from Microfinance Institutions in Tanzania

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Title: The Influence of Trainees' Characteristics on the Transfer of Entrepreneurship Training: Evidence from Microfinance Institutions in Tanzania
Language: English
Authors: Minja, Joyce J. (ORCID 0000-0002-7974-9182), Mbura, Omari K. (ORCID 0000-0002-5755-5889), Charles, Goodluck (ORCID 0000-0003-0227-9933)
Source: International Journal of Training and Development. Sep 2022 26(3):448-471.
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: 24
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Adult Education
Descriptors: Foreign Countries, Teaching Methods, Entrepreneurship, Transfer of Training, Barriers, Business Administration Education, Creativity, Community Organizations, Financial Support, Age Groups, Higher Education, Educational Attainment, Andragogy, Cultural Context, Context Effect, Adult Education, Finance Occupations
Geographic Terms: Tanzania
DOI: 10.1111/ijtd.12266
ISSN: 1360-3736
1468-2419
Abstract: While entrepreneurship training is essential for the growth and sustainability of enterprises, the literature identifies several challenges which contribute to insufficient transfer (application) of trained materials to enterprises. Yet, the extant literature on training transfer is inconclusive, with minimal focus on trainee personal characteristics and scarce visualization of transfer as a dimensional concept. The study addressed this gap by examining the influence of selected trainee demographics on dimensions of near, far and creative transfer of entrepreneurship training. Based on a survey of 418 trainees in Tanzanian community-based microfinance institutions, findings reveal that, each dimension of training transfer tested was influenced by a different set of demographic determinants. It was evident that elders were less enthusiastic about near and far application of entrepreneurship training. Males perceived slightly more training transfer in far and creative domains while those with higher education levels were more likely to apply training in all transfer dimensions. Those with exposure to entrepreneurship were more convinced of the value of applying the trained skills to near and creative domains. Consequently, the study advances Andragogy by showing the contextual nature of applicability of its principles, as well as the dependence of training transfer on contextual factors surrounding trainees.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1344931
Database: ERIC
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  Value: <anid>AN0158528514;bpu01sep.22;2022Aug17.08:15;v2.2.500</anid> <title id="AN0158528514-1">The influence of trainees' characteristics on the transfer of entrepreneurship training: Evidence from microfinance institutions in Tanzania </title> <sbt id="AN0158528514-2">INTRODUCTION</sbt> <p>While entrepreneurship training is essential for the growth and sustainability of enterprises, the literature identifies several challenges which contribute to insufficient transfer (application) of trained materials to enterprises. Yet, the extant literature on training transfer is inconclusive, with minimal focus on trainee personal characteristics and scarce visualization of transfer as a dimensional concept. The study addressed this gap by examining the influence of selected trainee demographics on dimensions of near, far and creative transfer of entrepreneurship training. Based on a survey of 418 trainees in Tanzanian community‐based microfinance institutions, findings reveal that, each dimension of training transfer tested was influenced by a different set of demographic determinants. It was evident that elders were less enthusiastic about near and far application of entrepreneurship training. Males perceived slightly more training transfer in far and creative domains while those with higher education levels were more likely to apply training in all transfer dimensions. Those with exposure to entrepreneurship were more convinced of the value of applying the trained skills to near and creative domains. Consequently, the study advances Andragogy by showing the contextual nature of applicability of its principles, as well as the dependence of training transfer on contextual factors surrounding trainees.</p> <p>There is a growing consensus that entrepreneurship training offered to microentrepreneurs enables them to acquire knowledge, skills and attitudes (KSAs) that can be applied to improve clients' enterprise growth and sustainability (Gegenfurtner et al., 2020; Prediger & Gut, 2014). It is often argued that effective entrepreneurship training contributes considerably toward eliminating poverty by transforming the poor into successful microentrepreneurs (Abeysekera et al., 2017; Mihret Dessie & Shumetie Ademe, 2017). However, training initiatives face criticism of failure to enhance entrepreneurship in developing economies which exhibit enormous skill gaps (Awais Bhatti et al., 2013; Oware, 2020). These gaps cause the majority of micro, small and medium enterprises (MSMEs) to be plagued with a lack of creativity and innovation (Mihret Dessie & Shumetie Ademe, 2017) and a low graduation rate to the next level (Henrekson & Johansson, 2010). Consequently, several scholars (e.g., Brown et al., 2015; Lensink et al., 2018) question the compatibility of entrepreneurship training with trainees' specific needs and characteristics. A myriad of issues relating to their characteristics are considered to account for the failure to transfer skills or use of the imparted skills on the job. In view of this, a growing amount of literature argues that inadequate transfer of training affects its effectiveness (Baldwin et al., 2017; Grossman & Salas, 2011). This is partly due to the complex nature of training as a process with inputs, throughputs and outputs (Hughes et al., 2018). Meanwhile, there is increasing demand for training to be evaluated in terms of an improvement in the performance of human resources rather than in fiscal‐related outcomes alone (Baldwin et al., 2017; Frese et al., 2016).</p> <p>Despite this demand, the majority of training evaluations focus on market performance and entrepreneurship as outcomes of training (Hutchins et al., 2013; Minja & Mbura, 2019). Related to this, a meta‐analysis by Honorati and Cho (2013) found that almost 28 per cent of evaluations of the impact of entrepreneurship training in developing countries were based on performance in the labour market and the impact on incomes and profits. Further complexity arises over the multi‐dimensionality of the concept of the transfer of training, leading to few studies focusing on more than one dimension (Cowman & McCarthy, 2016). However, Haskell (2001) identified six levels of training transfer, the most relevant being 'near transfer' which deals with applying what has been learnt in similar situations, 'far transfer' which focuses on applying what has been learnt in dissimilar contexts and 'creative or displacement transfer' whereby what has been learnt is used in new or unique situations.</p> <p>Our literature search did not locate any research with a clear focus on the influence of entrepreneurship training on near, far or creative transfer, which is a gap that needed to be filled, as the training needs to be evaluated in terms of whether it fulfils the purpose of ensuring the growth and sustainability of a venture (Eijdenberg et al., 2019; NEEC, 2013). In addition, a review of the Baldwin and Ford Model of the Transfer Process points to the need to focus on personal characteristics and adaptive or displacement transfer, which entails the creative application of training (Baldwin et al., 2017). The original model of 1988 incorporates trainees' characteristics as inputs and generalized transfer as the output, but it does not separate transfer into dimensions. Meanwhile, the entrepreneurship training literature indicates that personal characteristics, such as age and being a woman, reduces trainees' chances of performing well in entrepreneurship training courses, while their level of knowledge and skills has a positive impact on their performance (Zamfir et al., 2018). For instance, research has found that in developing countries the cultural environment that constitutes traditional reproductive roles, male‐dominated power relations, and meagre entrepreneurial skills leads to the development of mindsets that entrepreneurship is unsuitable for female entrepreneurial activity (Hunter & Lean, 2018; Raza et al., 2019). However, few studies in the field have examined these characteristics in connection with the transfer of training (Cowman & McCarthy, 2016; Matricano & Formica, 2017), leading to scarce evidence from emerging economies.</p> <p>One such economy is Tanzania in East Africa. In a bid to boost sustainable entrepreneurship, the country instituted the Tanzania National Inclusive Entrepreneurship Strategy (INES) in 2018. This strategy contains a with an action plan to strengthen nonformal training and skill development systems by promoting learning‐by‐doing methodologies (URT, 2017). Consequently, public and private firms; including microfinance institutions (MFIs); are tasked with provision of entrepreneurial skills. MFIs are key providers of entrepreneurship training in emerging economies through the microfinance‐plus model. Current data shows that 59 per cent MFIs adopt this model globally, which supplements finance with nonfinancial services to maximize social impact (Convergences, 2019). In Tanzania's 2012 MSME baseline survey, MFIs accounted for 68 per cent of entrepreneurship training providers (FSDT, 2012). Most of it is in community microfinance groups (CMGs) which were developed for women empowerment through credit and training. Actually, training is offered mostly to women who also own 54 per cent of MSMEs in Tanzania (Mori, 2014) and face the sociocultural challenges as other emerging economies, but are also subjected to generally negative attitude towards entrepreneurship instilled during the 1961–1984 socialist era (Hunter & Lean, 2018). This invites rigorous research, especially in the frontline entrepreneurship training providers such as CMGs, to provide the evidence necessary to advance theory and to reveal which training programmes for entrepreneurs work best in such contexts (Prediger & Gut, 2014).</p> <p>In this study, we extend current research on microfinance‐plus services by examining how trainees' application of KSAs after entrepreneurship training influences a change in their behaviour (training transfer). Specifically, the study drew from Andragogy to examine the direct influence of age, gender, education level and exposure to entrepreneurship on near, far and creative transfer dimensions. The study findings inform policy makers on the systematic promotion of entrepreneurship training and the training of out‐of‐school populations in emerging economies, which will be better placed to contribute to the attainment of Sustainable Development Goal 4 on the provision of quality education for all.</p> <p>The rest of the paper is organized as follows. Section Literature Review and Analytical Framework contains the literature review and analytical framework, Section Methodology provides the methodological framework, Section Results and Discussion presents the results and discussion, and the last section draws conclusions and provides implications, limitations and areas for further study.</p> <hd id="AN0158528514-3">LITERATURE REVIEW AND ANALYTICAL FRAMEWORK</hd> <p>The study begins with an analytical model relating to Andragogy, followed by an empirical review and resultant hypotheses, based on adult trainees in a context in which they were expected to transfer training. It drew on the assumptions of Andragogy (Knowles, 1978) that an adult learner possesses self‐concept and autonomy, is capable of self‐directed learning, has accumulated a reservoir of experience that informs learning, and is intrinsically motivated (Watkins, 2015). Basing our analysis on the theory was both to challenge and reinforce its applicability to the transfer of entrepreneurship training in a developing economy because the theory assumes that the self‐directedness and autonomy of trainees will result in the automatic absorption of training. We also sought to verify the criticism of Andragogy by Lejano and Shankar (2013) that it fails to acknowledge the effects of environment (culture, society, history, etc.) on adult learning. This view emphasizes that social structures largely define the learning transaction, irrespective of learners' characteristics, through their constraining or enabling effects on decisions. The study also sought to reinforce the assumption that a pool of knowledge and experience possessed by adult trainees informed learning and subsequent transfer by focusing on education level and exposure to entrepreneurship and the selected transfer dimensions.</p> <p>Notwithstanding the fact that numerous factors influencing training transfer have been established by previous research (Deckers et al., 2021), the literature that focuses on the direct effects of trainees' characteristics on the transfer of training use age, gender, education and background as control variables (Chiaburu et al., 2010; Heuer & Kolvereid, 2014; Paulsen & Kauffeld, 2017). It is also inconsistent and mainly focusing on Western and Asian contexts. For instance, a global analysis by Shirokova et al. (2018) revealed that older trainees tended to partake more in start‐up activities after entrepreneurship education, whereas Matricano and Formica (2017) found that youth in Italy were more likely to start a business after training. Chiaburu et al. (2010) revealed that age was not significantly related to the transfer of training in the United States of America, while Cowman and McCarthy (2016) found that respondents' age was significantly associated with positive transfer in the health sector in Ireland, whereby adults aged 40–49 were involved in this regard. In view of this, they concluded that age was not a barrier to transferring training. Due to this contrasting literature, we linked the andragogical principle of learners' possession of self‐concept to their ability to appraise themselves and direct their learning, depending on their view of age in relation to the proximity to death (Watkins, 2015), whereby it was expected that older trainees will be less inclined to transfer training. Furthermore, no comparable studies were found in Tanzania, leading to geographical under‐representation and limited contextual scope. To contribute the findings from the study's context, we hypothesized that:</p> <hd id="AN0158528514-4">H1:</hd> <p>Seniority has a negative influence on the near, far and creative transfer of entrepreneurship training.</p> <p>The andragogical principle of autonomy prescribes that adult trainees are free to choose what to do regardless of gender. Nonetheless, the literature reveals that female trainees are disadvantaged in terms of entrepreneurship training and subsequent performance (Zamfir et al., 2018). Heuer and Kolvereid (2014) found some significant correlations between entrepreneurial intentions and gender in Belgium and Norway. Global figures also indicate that gender appears to matter, as being a female student is negatively associated with start‐up activities after entrepreneurship education (Shirokova et al., 2018). A controlled trial by Gine and Mansuri (2014) found that men benefited more from training than women in rural Pakistan, while being a woman reduced the chances of becoming an entrepreneur (Zamfir et al., 2018). In Tanzania, Hunter and Lean (2018) and Nchimbi (2003) revealed that female entrepreneurs generally had a heavier workload than males and a lower level of entrepreneurial skills. Mori (2014) also found that traditional reproductive roles and power relations make it more difficult for women to participate in entrepreneurship thus reducing their autonomy. Contrary findings include a study on a large organization in the mid‐west, United States of America, which showed that gender was not significantly related to the transfer of training (Chiaburu et al., 2010). Paulsen and Kauffeld (2017) found no significant relationship between gender, positive affect and motivation to transfer training in Germany. In the Czech Republic, Kozubíková et al. (2016) found that there was no differentiation between the genders as regards autonomy. Although the limited theoretical literature suggests gender homogeneity in the application of training, the bulk of the empirical literature reveals contradictory findings. In particular, the evidence from emerging economies points out that being a woman has a bearing on the training of female entrepreneurs, as they face cognitive, time and material constraints that cause them to doubt their ability to transfer training, as they perceive that their environment is challenging and unsuitable for entrepreneurial activity (Field et al., 2010; Raza et al., 2019). To contribute to this subject, we hypothesized that:</p> <hd id="AN0158528514-5">H2:</hd> <p>Males are more likely to transfer near, far and creative entrepreneurship training than females.</p> <p>We also sought to verify the assumption of andragogy that reserves of knowledge from education are a rich resource of great benefit to trainees. The bulk of studies on education level and training show its positive influence, although there is some inconsistency in the results. Qualitative research conducted by Abeysekera et al. (2017) found that the education of owner managers influenced their ability to follow the training. In Europe, the level of trainees' knowledge and skills was found to have a positive impact on entrepreneurship (Zamfir et al., 2018). In Britain, Westhead et al. (2009) found that entrepreneurs with a higher level of education identified more business opportunities. Heuer and Kolvereid (2014) found that entrepreneurship education directly influenced entrepreneurial intentions in Belgium and Norway. Nchimbi (2003) found that it contributed to the higher performance of female enterprises in Tanzania. However, a global study found that nonbusiness bachelor's degree holders exposed to entrepreneurship education started up fewer businesses than business bachelor's degree holders (Shirokova et al., 2018). Meanwhile, Jiménez et al. (2015) found that having a high‐level education was beneficial to formal entrepreneurship but not to informal entrepreneurship because it raised ethical awareness. In the United States of America, Chiaburu et al. (2010) found that education level was not significantly related to the transfer of training. Basing on Andragogy, which maintains that knowledge reservoirs are relevant for improved performance in trainees, led us to hypothesize that:</p> <hd id="AN0158528514-6">H3:</hd> <p>Education level has a positive influence on the near, far and creative transfer of entrepreneurship training.</p> <p>Exposure to entrepreneurship falls under the andragogical principle that a pool of prior knowledge is a rich resource for trainees and the trainer. However, the literature is not in complete agreement about the influence of trainees' background. A global multilevel study found that trainees' previous business‐related experience had a significant and positive effect on the application of entrepreneurship education (Shirokova et al., 2018). McKenzie and Woodruff (2014) found that business training increased the short‐term profitability of experienced entrepreneurs. Heuer and Kolvereid (2014) found a significant correlation between having close ties to entrepreneurs and entrepreneurial intentions in Belgium. Cowman and McCarthy (2016) found that respondents' background was significantly associated with the positive transfer. However, some research reveals the disadvantages of experience, such as less ability to think 'outside the box' (Gielnik et al., 2012; Westhead et al., 2009). This indicates that experienced individuals may be constrained by the familiar, their experience, pride or denial, making them unable to notice and react to new factors. This can be a barrier to new perspectives which is bound to influence the transfer of training. In line with the study's theoretical basis, we hypothesized that:</p> <hd id="AN0158528514-7">H4:</hd> <p>Exposure to entrepreneurship has a positive influence on the near, far and creative transfer of entrepreneurship training.</p> <hd id="AN0158528514-8">METHODOLOGY</hd> <p></p> <hd id="AN0158528514-9">Study design, sample selection and data collection</hd> <p>The study used the cross‐sectional quantitative evaluation design, as the area of study was well established theoretically and empirically. It was therefore possible to predetermine all the possible responses in an objective and structured manner. A structured survey was used to collect primary data through a Computer Assisted Personal Interview (CAPI) questionnaire to ensure accuracy and validity.</p> <p>It is estimated that 1 million CMGs, with an average of 23 members, exist in Tanzania, around 4960 of which are in Dar es Salaam, tallying approximately 114,080 members (VICOBA‐FETA, 2018). Another criterion included in the sampling frame was a lapse of at least 3 months after training to gain a better perception of the transfer of training (Smidt et al., 2009). Complexity in getting aggregated data on training activities compelled the use of multistage sampling. The sampling unit was CMG clients who had been trained.</p> <p>In Stage 1, three CMG umbrella organizations and an independent promoter most actively involved in training were purposively selected. In Stage 2, promoter organizations subscribing to umbrella organizations coordinating 2106 CMGs were purposively sampled. In Stage 3, quota sampling was used to select 80 CMGs to participate in the survey based on their attendance at meetings during the pilot study. In Stage 4, the sampling frame was calculated based on the 80 CMGs multiplied by an average group size of 23 to get 1840. Calculations based on Cochran's formula for infinite populations with a confidence interval of 5 at 99 per cent confidence level produced a required sample of 489 individuals as units of observation. In Stage 5, Krejcie's and Morgan's (1970) formula for proportionality: <ephtml> <math altimg="urn:x-wiley:13603736:media:ijtd12266:ijtd12266-math-0001" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mfrac><msub><mi>N</mi><mn>0</mn></msub><mi>N</mi></mfrac><mspace width="0.1em" /><mo>*</mo><mspace width="0.1em" /><mi>n</mi><mo>=</mo><msub><mi>n</mi><mi>o</mi></msub></mrow><annotation encoding="application/x-tex"> $\frac{{N}_{0}}{N}\,* \,n={n}_{o}$</annotation></semantics></math> </ephtml> was used to get proportions and strata of the final CMG and respondent samples. Stratified listing was done to create the actual sampling frame from which the respondents were randomly selected. Table 1 presents the sampling process.</p> <p>1 TableSample Phases and Final Survey</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th align="left">S/n</th><th align="left">Sampling Stage 1</th><th align="left">Stage 2</th><th align="left">Stage 3</th><th align="left">Stage 4</th><th align="left">Stage 5</th><th align="left">Final survey</th></tr><tr valign="bottom"><th align="left">Promoter</th><th align="left">No. of subscribers/partners</th><th align="left">Selected subscribers/partners (purposive)</th><th align="left">No. of CMGs</th><th align="left">quota</th><th align="left">CMGs proportions</th><th align="left">Frame</th><th align="left">Required sample per strata</th><th align="left">CMGs actually surveyed</th><th align="left">%</th><th align="left">Respondents actually surveyed</th><th align="left">%</th></tr></thead><tbody valign="top"><tr><td align="left">1.</td><td align="left">Tanzania Informal Microfinance Association of Practitioners (TIMAP)</td><td align="char" char=".">25</td><td align="left">Jumuiya ya Kukuza Uchumi Ilala (JUKUILA)</td><td align="char" char=".">531</td><td align="char" char=".">80</td><td align="char" char=".">20</td><td align="char" char=".">297</td><td align="char" char=".">79</td><td align="char" char=".">15</td><td align="char" char=".">75</td><td align="char" char=".">43</td><td char="." align="char">54.4</td></tr><tr><td align="left">Jumuiya ya Wanavikoba Kinondoni (JUWAKI)</td><td align="char" char=".">83</td><td align="char" char="." /><td align="char" char=".">3.2</td><td align="char" char=".">91</td><td align="char" char=".">24</td><td align="char" char=".">4</td><td align="char" char=".">125</td><td align="char" char=".">19</td><td char="." align="char">79.2</td></tr><tr><td align="left">2.</td><td align="left">Village Community Bank‐Federation of Tanzania (VICOBA‐FETA)</td><td align="char" char=".">30</td><td align="left">Social and Economic Development Initiatives of Tanzania (SEDIT)</td><td align="char" char=".">312</td><td align="char" char="." /><td align="char" char=".">12</td><td align="char" char=".">289</td><td align="char" char=".">77</td><td align="char" char=".">11</td><td align="char" char=".">91.6</td><td align="char" char=".">75</td><td char="." align="char">97.4</td></tr><tr><td align="left">Umoja Youth AIDS and Community Development (UYACODE)</td><td align="char" char=".">614</td><td align="char" char="." /><td align="char" char=".">23.2</td><td align="char" char=".">704</td><td align="char" char=".">187</td><td align="char" char=".">18</td><td align="char" char=".">77.5</td><td align="char" char=".">176</td><td char="." align="char">94.1</td></tr><tr><td align="left">3.</td><td align="left">Interreligious‐Village Community Banks (IR‐VICOBA)</td><td align="char" char=".">2</td><td align="left">Evangelical Lutheran Church in Tanzania—Eastern and Coastal Diocese of (ELCT‐ECD) Ilala</td><td align="char" char=".">187</td><td align="char" char="." /><td align="char" char=".">7.2</td><td align="char" char=".">141</td><td align="char" char=".">37</td><td align="char" char=".">3</td><td align="char" char=".">41.6</td><td align="char" char=".">27</td><td char="." align="char">73.0</td></tr><tr><td align="left">Tanzania Episcopal Conference (TEC‐ Temeke)</td><td align="char" char=".">283</td><td align="char" char="." /><td align="char" char=".">10.4</td><td align="char" char=".">263</td><td align="char" char=".">70</td><td align="char" char=".">8</td><td align="char" char=".">76.9</td><td align="char" char=".">68</td><td char="." align="char">97.1</td></tr><tr><td align="left">4.</td><td align="left">Centre for VICOBA Entrepreneurship Development (CeVEDe)</td><td align="char" char=".">0</td><td align="left">N/A</td><td align="char" char=".">97</td><td align="char" char="." /><td align="char" char=".">4</td><td align="char" char=".">58</td><td align="char" char=".">15</td><td align="char" char=".">4</td><td align="char" char=".">100</td><td align="char" char=".">13</td><td char="." align="char">86.7</td></tr><tr><td align="left">Total</td><td align="left">2106</td><td /><td align="char" char=".">80</td><td align="char" char=".">1843</td><td align="char" char=".">489</td><td align="char" char=".">63</td><td align="char" char=".">78.8</td><td align="char" char=".">421</td><td char="." align="char">86.1</td></tr></tbody></table> </ephtml> </p> <p>1 Abbreviation: CMG, community microfinance group.</p> <p>A questionnaire was developed in English and translated into Swahili. Data were collected from January to March 2020 through Survey Solutions CAPI software. Respondents were surveyed during CMG meetings. The response rate was 63 (79 per cent) CMGs and 421 (86 per cent) trainees, from whom 418 useful questionnaires were obtained. Despite the lack of fixed rules on an acceptable response rate, business surveys targeting customers and employees record an average of 35 per cent (Mellahi & Harris, 2016). As trainees can also be regarded as customers, our response rate was adequate.</p> <hd id="AN0158528514-10">Operational definitions of variables</hd> <p>Likert scale ranking of 1 = <emph>strongly disagree</emph> to 5 = <emph>strongly agree</emph> was used to capture transfer dimensions in nine items. Items for near transfer were adopted from the Learning Transfer System Inventory version IV, while those for far and creative transfer were adopted from Campos et al. (2017). Measures of transfer (Cronbach's <emph>α</emph> 0.911 for near transfer, 0.758 for far transfer and 0.820 for creative transfer) were then created by aggregating the median scores of the items on the Likert scale to obtain the perception of transfer. Operational definitions of variables are presented in Table 2.</p> <p>2 TableOperational definitions of variables</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th align="left">Definition</th><th align="left">Source</th></tr></thead><tbody valign="top"><tr><td>Age: Completed years</td><td>Bates et al. (2012)</td></tr><tr><td>Gender: 01 = male, 02 = female</td></tr><tr><td>Exposure: Months practising entrepreneurship</td></tr><tr><td>Education level: 01 = preprimary, 02 = primary, 03 = O‐level, 04 = A‐level, 05 = vocational training, 06 = College</td><td>NBS Tanzania (2015)</td></tr><tr><td>Near transfer: Perceived application of learned concepts in similar situations;</td><td /></tr><tr><td>Far transfer: Perceived application of learned concepts in dissimilar situations</td><td>Campos et al. (2017)</td></tr><tr><td>Creative transfer: Perceived application of learned concepts in new or unique situations</td></tr></tbody></table> </ephtml> </p> <hd id="AN0158528514-11">Model estimation, analysis and interpretation</hd> <p>Generalized Ordinal Logistic Regression (GOLOGIT2) by Williams (2006) was used due to its ability to preserve the ordered nature of the measures and parsimony compared with non‐ordinal models. Wald Statistics were calculated at (<emph>p</emph> < 0.01). Figure 1 presents the analysis model.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0001.jpg" title="1 GOLOGIT2 equation. Source: Williams (2006)" /> </p> <p></p> <p>The Akaike and Bayesian Information Criterion presented in Table 3 provided further justification for the choice of model.</p> <p>3 TableAIC and BICs</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th align="left">Model parameters</th><th>Near transfer</th><th>Far transfer</th><th>Creative transfer</th></tr><tr valign="bottom"><th align="left">Constrained</th><th align="left">Unconstrained</th><th align="left">Diff.</th><th align="left">Constrained</th><th align="left">Unconstrained</th><th align="left">Diff.</th><th align="left">Constrained</th><th align="left">Unconstrained</th><th align="left">Diff.</th></tr></thead><tbody valign="top"><tr><td>AIC</td><td char="." align="char">799.34</td><td char="." align="char">816.36</td><td char="." align="char">−17.02</td><td char="." align="char">748.72</td><td char="." align="char">752.45</td><td char="." align="char">−3.73</td><td char="." align="char">991.87</td><td char="." align="char">1007.21</td><td char="." align="char">−15.34</td></tr><tr><td>AIC divided by N</td><td char="." align="char">1.91</td><td char="." align="char">1.95</td><td char="." align="char">−0.04</td><td char="." align="char">1.79</td><td char="." align="char">1.80</td><td char="." align="char">−0.01</td><td char="." align="char">2.37</td><td char="." align="char">2.41</td><td char="." align="char">−0.04</td></tr><tr><td>BIC (df = 27/48/−21)</td><td char="." align="char">908.29</td><td char="." align="char">1010.06</td><td char="." align="char">−101.76</td><td char="." align="char">865.75</td><td char="." align="char">909.84</td><td char="." align="char">−44.09</td><td char="." align="char">1116.97</td><td char="." align="char">1217.06</td><td char="." align="char">−100.08</td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 <emph>Note</emph>: The bold values are the difference between constrained and the unconstrained model Bayesian information criteria.</item> <item>3 Abbreviations: AIC, Akaike Information Criterion; BIC, Bayesian Information Criterion.</item> </ulist> <p>A magnitude of difference greater than 10 provides adequate evidence for using the model with smaller information criterias (Kass & Raftery, 1995).</p> <hd id="AN0158528514-13">Estimation of marginal effects</hd> <p>Coefficient and odds ratio estimates seldom provide a straightforward summary of the effects of interest (Mize, 2019; Williams, 2016). To make the results more tangible and meaningful, postestimation was done to obtain marginal effects at representative values (MERs) the visualization of which is presented in Figure 2.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0002.jpg" title="2 Equation for calculation of marginal effects at representative values (MERs). Source: Mize (2019)" /> </p> <p></p> <hd id="AN0158528514-15">RESULTS AND DISCUSSION</hd> <p></p> <hd id="AN0158528514-16">Descriptive statistics</hd> <p>The study was conducted in all municipal councils of the commercial hub of Tanzania, Dar‐es‐salaam City, namely Ilala, Temeke, Kinondoni, Ubungo and Kigamboni. The data revealed that Ilala and Temeke municipalities had the most respondents (60.8 per cent), with 35.5 per cent from Ilala and 25.1 per cent from Temeke. This is because CMGs were first established in Ilala District and they spread elsewhere unequally over time (NEEC, 2019). The respondents' ages ranged from 21 to 77 with a mean age of 43. The age group of 36–40 comprised the largest number of respondents. Furthermore, 16.5 per cent of the respondents were males and 83.5 per cent were females, simply because CMGs are primarily aimed at women's empowerment. The mean years of schooling was 9, and 54 per cent of the sampled respondents had completed primary education or less. Exposure ranged from 1 to 492 months while 92 per cent of respondents reported that their exposure came from their own enterprises, the majority (81 per cent) had been in business between 0 and 15 years. This indicates the youthful nature of Tanzania's microenterprise sector, due partly to the delayed involvement in private enterprise in Tanzania as a result of the delay in moving from a socialist regime to market liberalization, which delayed the adoption of an entrepreneurial culture (Hunter & Lean, 2018).</p> <hd id="AN0158528514-17">GOLOGIT2 output</hd> <p>Table 4 presents the summary of GOLOGIT2 coefficients and odds ratios. Outcomes equate to measures on the Likert scale administered to trainees aggregated as median scores for each predictor and outcome. Only creative transfer recorded medians for 'strongly disagree'.</p> <p>4 TableSummary of trainees' characteristics on transfer of entrepreneurship training</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th /><th><italic>β</italic></th><th>Gamma 1</th><th>Gamma 2</th><th>Gamma 3</th></tr><tr valign="bottom"><th align="left"><sub>Coef.</sub></th><th align="left"><sub>Odds ratio</sub></th><th align="left"><sub><italic>P</italic> > <italic>z</italic></sub></th><th align="left"><sub>95% Conf.</sub></th><th align="left"><sub>Interval</sub></th><th align="left"><sub>Coef.</sub></th><th align="left"><sub>Odds ratio</sub></th><th align="left"><sub><italic>P</italic> > <italic>z</italic></sub></th><th align="left"><sub>95% Conf.</sub></th><th align="left"><sub>Interval</sub></th><th align="left"><sub>Coef.</sub></th><th align="left"><sub>Odds ratio</sub></th><th align="left"><sub><italic>P</italic> > <italic>z</italic></sub></th><th align="left"><sub>95% Conf.</sub></th><th align="left"><sub>Interval</sub></th><th align="left"><sub>Coef.</sub></th><th align="left"><sub>Odds ratio</sub></th><th align="left"><sub><italic>P</italic> > <italic>z</italic></sub></th><th align="left"><sub>95% Conf.</sub></th><th align="left"><sub>Interval</sub></th></tr></thead><tbody valign="top"><tr><td>Near transfer</td></tr><tr><td>Age</td><td char="." align="char">−0.02</td><td char="." align="char">0.98</td><td align="left">**</td><td char="." align="char">0.96</td><td char="." align="char">1.00</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Gender (F)</td><td char="." align="char">0.02</td><td char="." align="char">1.02</td><td align="left">ns</td><td char="." align="char">0.58</td><td char="." align="char">1.80</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Edu. lev</td><td char="." align="char">0.06</td><td char="." align="char">1.07</td><td align="left">*</td><td char="." align="char">1.00</td><td char="." align="char">1.14</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Exp.</td><td char="." align="char">0.00</td><td char="." align="char">1.00</td><td align="left">**</td><td char="." align="char">1.00</td><td char="." align="char">1.01</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Far transfer</td></tr><tr><td>Age</td><td char="." align="char">0.06</td><td char="." align="char">1.06</td><td align="left">**</td><td char="." align="char">1.01</td><td char="." align="char">1.11</td><td char="." align="char">−0.01</td><td char="." align="char">0.99</td><td align="left">ns</td><td char="." align="char">0.95</td><td char="." align="char">1.02</td><td char="." align="char">−0.08</td><td char="." align="char">0.93</td><td align="left">***</td><td char="." align="char">0.88</td><td char="." align="char">0.97</td><td /><td /><td /><td /><td /></tr><tr><td>Gender</td><td char="." align="char">−1.78</td><td char="." align="char">0.17</td><td align="left">*</td><td char="." align="char">0.02</td><td char="." align="char">1.33</td><td char="." align="char">1.43</td><td char="." align="char">4.17</td><td align="left">ns</td><td char="." align="char">0.59</td><td char="." align="char">29.57</td><td char="." align="char">1.44</td><td char="." align="char">4.21</td><td align="left">ns</td><td char="." align="char">0.52</td><td char="." align="char">33.84</td><td /><td /><td /><td /><td /></tr><tr><td>Edu. lev</td><td char="." align="char">0.11</td><td char="." align="char">1.11</td><td align="left">***</td><td char="." align="char">1.04</td><td char="." align="char">1.19</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Exp.</td><td char="." align="char">0.00</td><td char="." align="char">1.00</td><td align="left">ns</td><td char="." align="char">1.00</td><td char="." align="char">1.00</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Creative transfer</td></tr><tr><td>Age</td><td char="." align="char">−0.01</td><td char="." align="char">0.99</td><td align="left">ns</td><td char="." align="char">0.97</td><td char="." align="char">1.01</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Gender</td><td char="." align="char">−0.51</td><td char="." align="char">0.60</td><td align="left">**</td><td char="." align="char">0.36</td><td char="." align="char">1.01</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Edu. lev</td><td char="." align="char">−0.10</td><td char="." align="char">0.90</td><td align="left">*</td><td char="." align="char">−0.23</td><td char="." align="char">0.02</td><td char="." align="char">0.11</td><td char="." align="char">1.11</td><td align="left">**</td><td char="." align="char">1.00</td><td char="." align="char">1.23</td><td char="." align="char">0.23</td><td char="." align="char">1.25</td><td align="left">***</td><td char="." align="char">1.10</td><td char="." align="char">1.42</td><td char="." align="char">0.23</td><td char="." align="char">1.26</td><td align="left">***</td><td char="." align="char">1.09</td><td char="." align="char">1.45</td></tr><tr><td>Exp.</td><td char="." align="char">0.00</td><td char="." align="char">1.00</td><td align="left">**</td><td char="." align="char">1.00</td><td char="." align="char">1.00</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr></tbody></table> </ephtml> </p> <ulist> <item>4 <emph>Note</emph>: Obs.: 418, LR <emph>χ</emph><sups>2</sups> (<reflink idref="bib16" id="ref1">16</reflink>) = 320.17, <emph>p</emph> < 0.001, for near transfer LR <emph>χ</emph><sups>2</sups> (<reflink idref="bib16" id="ref2">16</reflink>) = 211.57, <emph>p</emph> < 0.001, for far transfer, and LR <emph>χ</emph><sups>2</sups> (<reflink idref="bib16" id="ref3">16</reflink>) = 177.38, <emph>p</emph> < 0.001, for creative transfer.</item> <item>5 ***, ** and * denote statistically significant at 1 per cent, 5 per cent and 10 per cent, respectively.</item> </ulist> <p>Predictors that met the assumption of proportional odds were analyzed by the beta parameter, while those in violation were analyzed at the indicated gamma levels. The results show that age, education level and exposure to entrepreneurship had a statistically significant (<emph>p</emph> < <emph>0.05 and p</emph> < <emph>0.10 and p</emph> < <emph>0.05, respectively</emph>) influence on the application of training to similar situations that is, near transfer. For the application of training to dissimilar situations, that is, far transfer, age, gender and education level attained statistically significant results (<emph>p</emph> < <emph>0.05 and p</emph> < <emph>0.10 and p</emph> < <emph>0.01, respectively</emph>). Results on the application of training to novel situations, that is, creative transfer, revealed that gender, education level and exposure to entrepreneurship had a significant influence (<emph>p</emph> < <emph>0.05 and p</emph> < <emph>0.10 and p</emph> < <emph>0.05, respectively</emph>). Table 5 summarises the results on influence of each characteristic per dimension.</p> <p>5 TableInfluence of trainee characteristics on transfer dimensions</p> <p> <ephtml> <table><tbody valign="top"><tr><td><graphic href="" /></td></tr></tbody></table> </ephtml> </p> <p>6 Abbreviation: NS, not significant.</p> <p>Further visualization was done to assist hypothesis testing. The results are presented in Figure 3–11. Only transfer dimensions with statistically significant results in the GOLOGIT2 analysis were subjected to postestimation to maintain rigour in the results. Hypothesis 1 on the negative influence of seniority was verified for near and far transfer in terms of the strength of trainee agreement to having applied training as shown in Figures 3 and 4.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0003.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0003.jpg" title="3 Marginal effects for age and near transfer. CI, confidence interval" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0004.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0004.jpg" title="4 Marginal effects for age and far transfer. CI, confidence interval" /> </p> <p></p> <p>As an example, 44.6 per cent of respondents aged 20 strongly perceived that they had applied near transfer, compared to 28.5 per cent of those aged 50 and 20.9 per cent of those aged 70. The effect of the perception of age as being linked to proximity of death may be the reason for the reduced enthusiasm of seniors to use the training. Findings for creative transfer were not significant. This points to the existence of age‐specific effects on training transfer dimensions. The visualization, has provided empirical clarification in that older trainees felt strongly that their age decreased their likelihood of application of the training they had received in similar and dissimilar situations. These results for near and far transfer support the findings that age affects the effectiveness of entrepreneurship training, (Matricano & Formica, 2017) and that older trainees find it more difficult to apply the content of training to their work (Chen & Klimoski, 2007). This contrasts Cowman and McCarthy (2016), who found that those aged 40–49 were more positive about transferring training than younger employees. Our study thus underscores the importance of concerted age‐sensitive design of training initiatives similar to (Rhebergen & Wognum, 1997). This is especially vital for MFIs' entrepreneurship training in this context, since the average age of trainees was found to be 43, which further clarifies the reduction in enthusiasm to applying the training in the two dimensions. An interesting finding is the fact that the influence of seniority did not hold for creative transfer. Although the literature on effects of age on creativity is quite mixed, with negative (Zhang & Niu, 2013), and positive effects (Palmiero et al., 2015), our results suggest that creativity oriented training may be suitable for older trainees than that which requires doing the same thing that was trained or using training for different purposes than intended.</p> <p>MERs for Hypothesis 2 revealed that males strongly perceived that they had used the training for far and creative transfer but not near transfer as per Figures 5 and 6.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0005.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0005.jpg" title="5 Marginal effects for gender and far transfer. CI, confidence interval" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0006.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0006.jpg" title="6 Marginal effects for gender and creative transfer. CI, confidence interval" /> </p> <p></p> <p>Analysis revealed that males were more likely to agree with the transfer of training, whereby the marginal probability was 42.9 per cent for males and decreased to 36.2 per cent for females' perceptions of far transfer, whereas 29.3 per cent of males agreed on the likelihood of creative transfer compared to 20.9 per cent likelihood for females. <emph>S</emph>imilar findings on females' lower entrepreneurial performance have been provided by Field et al. (2010); Gine and Mansuri (2021); Hunter and Lean (2018); and Nchimbi (2003), who cited several constraints that include gender‐stereotypic norms and beliefs as the culprits. Our study adds knowledge that females are also less likely to apply entrepreneurship training in dissimilar or creative situations, thereby constraining their entrepreneurial pursuits. In Tanzania, the cultural environment has been cited as a key barrier to female entrepreneurial pursuits, due to constraining environment, which impedes their capacity to realize their full entrepreneurial potential (Mori, 2014). The andragogical principle of autonomy has failed to take account of the gender differences in terms of applying the training received, as it anticipates that adult trainees, regardless of gender, will behave similarly in training situations.</p> <p>Therefore, akin to the maxim 'All men are equal but some are more equal than others', this study sheds light on this principle by showing that although adults are autonomous, some (<emph>males</emph>) are more autonomous than others (<emph>females</emph>) in transferring creative entrepreneurship training in settings where norms and cognitions and favour certain groups and discriminate against others as per the liberalist feminist view (Solesvik et al., 2019) Therefore, whereas Andragogy might fit the training context in which Kozubíková et al. (2016) found that gender had no effect on entrepreneurial autonomy, it cannot be said for contexts with characteristics similar to those of the present study, that is, a developing economy with a patriarchal basis. Our study hereby extends theoretical frontiers by providing evidence of the contextual nature of theories and the fact that the suitability of a particular theory, in our case Andragogy, depends on the socioeconomic and culturally shared mindsets engrained in a particular society. From a social theorist standpoint, these findings may also be a result of the naturally inherent differences between women and men which may cause females to adopt approaches that may or may not be as effective as those of men (Solesvik et al., 2019). However, it is largely accepted that discriminative practices that lead to resource constraints are the main culprits for women in emerging economies (ibid).</p> <p>The MERs for Hypothesis 3 revealed those with more than 7 years of schooling as more likely to agree that they had transferred entrepreneurship training for all transfer dimensions as presented in Figures 7–9.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0007.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0007.jpg" title="7 Marginal effects for education level and near transfer. CI, confidence interval" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0008.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0008.jpg" title="8 Marginal effects for education level and far transfer. CI, confidence interval" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0009.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0009.jpg" title="9 Marginal effects for education level and creative transfer. CI, confidence interval" /> </p> <p></p> <p>The illustrations show that, between 7 and 16 years of schooling, the perceptions of near transfer rose from 17.5 per cent to 36.8 per cent. For far transfer, perceptions rose from 32.4 per cent to 51.3 per cent while for creative transfer the rise was also from 17.5 per cent to 36.8 per cent, respectively. A key difference is that for creative transfer, the probability of strong disagreement at having transferred training also rose from 8.9 per cent with 7 years and 17.9 per cent with 16 years of schooling. This contrast in the findings is in line with (Jiménez et al., 2015), who also found that tertiary education had a negative influence on informal entrepreneurship by raising awareness of the potential negative repercussions of informal activities. More importantly, these findings concur with the literature on the importance of entrepreneurship education in stimulating entrepreneurship and innovativeness (Hunter & Lean, 2018; Jiménez et al., 2015; McKenzie & Woodruff, 2014). Our study extends the literature by revealing that near, far and creative transfer all have a better chance of occurring as the trainees' education level increases, emphasizing that education and entrepreneurship are intertwined.</p> <p>As regards Hypothesis 4 on influence of exposure, only near and creative transfer dimensions had significant results in the main model thus qualified for visualization in Figures 10 and 11.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0010.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0010.jpg" title="10 Marginal effects for exposure and near transfer. CI, confidence interval" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BPU/01sep22/ijtd12266-fig-0011.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ijtd12266-fig-0011.jpg" title="11 Marginal effects for exposure and creative transfer. CI, confidence interval" /> </p> <p></p> <p>The visuals show that those with more than 3 months exposure to entrepreneurship were more likely to strongly agree with the concept of transfer. For instance, 25.6 per cent of trainees with 3 months exposure agreed with near transfer versus 48.4 per cent of trainees with 421 months exposure, while 18.9 per cent of trainees with 3 months exposure versus 36.6 per cent of trainees with 421 months exposure agreed at having done creative transfer. This means that the more months entrepreneurs spent on running a business, the more strongly they agreed with undertaking near and creative transfer of entrepreneurship training. These findings support the literature on the importance of entrepreneurs' background regarding the performance they realize after entrepreneurship training, such as the work of Heuer and Kolvereid (2014), González Restrepo et al. (2019) and Honorati and Cho (2013). We have added that not all dimensions of the transfer of training are affected by exposure to entrepreneurship, and the lack of influence of trainee background on far transfer is probably because this dimension does not necessarily entail the use of entrepreneurship training to enhance entrepreneurship, rather far transfer can occur in nonentrepreneurial contexts. This adds to the soundness of our results.</p> <hd id="AN0158528514-27">Conclusions and implications</hd> <p>This study examined the direct influence of trainees' characteristics on near, far and creative transfer dimensions, prompted by assertions of the lacklustre performance of micro‐entrepreneurs even after training. Our study has provided empirical evidence of creative transfer as part of the generalized transfer of training, and verified several trainee characteristics that influence it. Accordingly, it has contributed to the concept of the adaptive or displacement transfer of training as proposed in the 2017 review of the Baldwin and Ford Model of the Transfer Process. Particularly important is that, it has identified that, gender, education level and exposure to entrepreneurship are key antecedents to the creative use of training in microenterprise. This implies that strategies aiming to boost enterprise growth through training in similar contexts should consider these factors since creativity is closely linked to innovation which in turn drives enterprise growth. We also provide empirical evidence that contests the andragogical principle of the autonomy of adult trainees, which shows that the transfer of training depends on a particular antecedent like age or gender and that trainees' interplay with the environment influences their readiness to learn and subsequently apply entrepreneurship training. We have provided empirical evidence that the principles of adult learning applied to the transfer of entrepreneurship provided by MFIs, the majority of whose clients are women, can be overridden by socioeconomic and cultural cognitions embedded in the training context.</p> <p>Indeed, we have shown that national, and subnational contextual conditions have the power to subvert theory, hence, the importance of recognizing the value of context in social science research. In our case, sociocultural, and cognitive embeddedness of female entrepreneurs in terms of societal understanding and influence on economic behaviour, networks, interpersonal relations and mental models in which individuals analyse the information provided undercurrents on the influence of trainee characteristics on training transfer. Therefore, these results reveals that the use of training in an enterprise in the microcontext depends on the interplay of prevailing conditions in the macrocontext. This means that training policy and strategy ought to be formulated in line with the prevailing macro conditions for maximal transfer that will translate into more training effectiveness and returns on training expectations. Specifically, for the Tanzanian context, transfer of entrepreneurship training in MFIs trainees is influenced by trainees' age, gender, education level and exposure where the majority are primary schooled females aged between 36 and 50 years, and involved in young enterprises. The influence of these characteristics is further tied to the Tanzanian culture and outlook towards entrepreneurship as such near, far, and creative transfer of entrepreneurship training is made unique by context.</p> <p>Moreover, our study has revealed that transfer dimensions, and not transfer in general, should be specified at the planning stage in relation to trainees' demographics, which has not been clearly captured in the literature. Consequently, entrepreneurship policy makers, MFIs and trainers need to consider the variability in trainees' characteristics in a bid to achieve maximal transfer. These results inform the setting of the strategic policy target of promoting the application of nonformal training. In Tanzania, this would be particularly useful for strengthening the nonformal training and skills development system enshrined in the Inclusive National Strategy for Entrepreneurship (INES) of 2018. Our study shows that training materials need to be customized so that the training provided can be applied by entrepreneurs to their work environment. This would possibly entail generating age‐specific training outcomes for maximal transfer in that youth be subjected to near and far transfer targeted training while senior trainees be subjected to training with outcomes geared more towards creativity as it was observed that the average age was 43. Training for females could entail topics for mindset change to curb the negative mental constructs that limit far and creative transfer. This is crucial for CMGs which cater largely for women as evidenced in the 83.5 per cent female majority of respondents in this study.</p> <p>Our study also provides empirical evidence that a comprehensive education policy is needed in developing economies like Tanzania to ensure that entrepreneurship education is prioritized, so that students are equipped to become entrepreneurs and run successful businesses. Our results imply that an enhanced application of MFI–CMG entrepreneurship training in Tanzania and elsewhere may best be realized by offering training in parallel with formal education, since the majority (81.9 per cent in this study) of clients have received only secondary education or less. The study has also shown positive results of training transfer among entrepreneurs with the highest levels of formal education, which is very useful for the growth and sustainability of businesses. Also, training may target those with exposure to entrepreneurship through employment or ownership of enterprises to increase likelihood of near and creative transfer as the results have shown.</p> <hd id="AN0158528514-28">Study limitations and areas for further studies</hd> <p>Although the study makes sound theoretical and practical contributions, it has some limitations. First, in view of the fact that it was cross‐sectional based on a self‐report survey and the data from a single developing economy, issues of common method and perceptual bias cannot be ruled out. While quantitative research provides a good basis for generalization, may be a follow‐up longitudinal and in‐depth analysis of the variables identified in this study in more countries over a longer period using peer or supervisor reports can expand its scope. Second, much as the unit of analysis was the MFI clients, inclusion of other sectors and sub‐sectors is likely to enhance the results of future studies. In connection to this, further research can focus on the maintenance of transfer training and the effects of personality on the utilization of the skills acquired across various sectors. More theoretical variations could be achieved by applying theories of innovation, creativity or knowledge transfer to obtain a diverse set of results and validation.</p> <hd id="AN0158528514-29">ACKNOWLEDGEMENTS</hd> <p>Special recognition is afforded to the Microfinance stakeholders that participated in one way or another in facilitating this study. It is largely due to the voluntary cooperation of TAMFI, K‐Finance, NEEC, VICOBAFETA, TIMAP, CeVEDe, UYACODE, SEDIT, JUWAKI, JUKUILA, IR‐VICOBA and many others that data for the study was collected.</p> <hd id="AN0158528514-30">CONFLICTS OF INTEREST</hd> <p>The authors declare no conflicts of interest.</p> <hd id="AN0158528514-31">DATA AVAILABILITY STATEMENT</hd> <p>Data used in the study are available on request from the authors.</p> <hd id="AN0158528514-32">ETHICS STATEMENT</hd> <p>Research clearance was provided by the University of Dar‐salaam.</p> <ref id="AN0158528514-33"> <title> REFERENCES </title> <blist> <bibl id="bib1" type="bt">1</bibl> <bibtext> Abeysekera, R., Patton, D., & Mullineux, A. (2017). Co‐production in business training in microfinance institutions: A conceptual approach. 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  Label: Abstract
  Group: Ab
  Data: While entrepreneurship training is essential for the growth and sustainability of enterprises, the literature identifies several challenges which contribute to insufficient transfer (application) of trained materials to enterprises. Yet, the extant literature on training transfer is inconclusive, with minimal focus on trainee personal characteristics and scarce visualization of transfer as a dimensional concept. The study addressed this gap by examining the influence of selected trainee demographics on dimensions of near, far and creative transfer of entrepreneurship training. Based on a survey of 418 trainees in Tanzanian community-based microfinance institutions, findings reveal that, each dimension of training transfer tested was influenced by a different set of demographic determinants. It was evident that elders were less enthusiastic about near and far application of entrepreneurship training. Males perceived slightly more training transfer in far and creative domains while those with higher education levels were more likely to apply training in all transfer dimensions. Those with exposure to entrepreneurship were more convinced of the value of applying the trained skills to near and creative domains. Consequently, the study advances Andragogy by showing the contextual nature of applicability of its principles, as well as the dependence of training transfer on contextual factors surrounding trainees.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2022
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1344931
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1344931
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/ijtd.12266
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 24
        StartPage: 448
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Teaching Methods
        Type: general
      – SubjectFull: Entrepreneurship
        Type: general
      – SubjectFull: Transfer of Training
        Type: general
      – SubjectFull: Barriers
        Type: general
      – SubjectFull: Business Administration Education
        Type: general
      – SubjectFull: Creativity
        Type: general
      – SubjectFull: Community Organizations
        Type: general
      – SubjectFull: Financial Support
        Type: general
      – SubjectFull: Age Groups
        Type: general
      – SubjectFull: Higher Education
        Type: general
      – SubjectFull: Educational Attainment
        Type: general
      – SubjectFull: Andragogy
        Type: general
      – SubjectFull: Cultural Context
        Type: general
      – SubjectFull: Context Effect
        Type: general
      – SubjectFull: Adult Education
        Type: general
      – SubjectFull: Finance Occupations
        Type: general
      – SubjectFull: Tanzania
        Type: general
    Titles:
      – TitleFull: The Influence of Trainees' Characteristics on the Transfer of Entrepreneurship Training: Evidence from Microfinance Institutions in Tanzania
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Minja, Joyce J.
      – PersonEntity:
          Name:
            NameFull: Mbura, Omari K.
      – PersonEntity:
          Name:
            NameFull: Charles, Goodluck
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Type: published
              Y: 2022
          Identifiers:
            – Type: issn-print
              Value: 1360-3736
            – Type: issn-electronic
              Value: 1468-2419
          Numbering:
            – Type: volume
              Value: 26
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: International Journal of Training and Development
              Type: main
ResultId 1