Bio-based and Applied Economics BAE Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6e172 | DOI: 10.36253/bae-13475 Copyright: © 2023 L. Deißler, K. Mausch, A. Karanja, S. McMullin, U. Grote. Open access, article published by Firenze University Press under CC-BY-4.0 License. Firenze University Press | www.fupress.com/bae Citation: L. Deißler, K. Mausch, A. Karanja, S. McMullin, U. Grote (2023). A complex web of interactions: Personal- ity traits and aspirations in the context of smallholder agriculture. Bio-based and Applied Economics 12(1): 53-67. doi: 10.36253/bae-13475 Received: July 31, 2022 Accepted: March 31, 2023 Published: June 24, 2023 Data Availability Statement: All rel- evant data are within the paper and its Supporting Information files. Competing Interests: The Author(s) declare(s) no conflict of interest. Editor: Davide Menozzi, Linda Arata. ORCID LD: 0000-0002-3646-534X KM: 0000-0002-2962-7646 AK: 0000-0001-9095-4905 SMM: 0000-0002-0976-1880 UG: 0000-0002-9073-6294 A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Luzia Deißler1,*, Kai Mausch2, Alice Karanja3, Stepha McMullin3, Ulrike Grote1 1 Leibniz University Hannover, Institute for Environmental Economics and World Trade, Germany 2 Center for International Forestry Research (CIFOR)-World Agroforestry (ICRAF), Nai- robi, Kenya and Bonn, Germany 3 Center for International Forestry Research (CIFOR)-World Agroforestry (ICRAF), Nai- robi, Kenya *Corresponding author. E-mail: deissler@iuw.uni-hannover.de Abstract. Some recent research began to shift the focus of development efforts away from income and yield to more diverse concepts that consider people’s intrinsic driv- ers and values, such as aspirations and personality traits. We aim to contribute to the literature by exploring the connections between intrinsic drivers. Hence, we analyze if and how the formation of aspirations relates to personality traits against the back- ground of different socio-economic household characteristics. This research will help us provide practical insights for the successful design of development projects specifi- cally tailored to the unique needs and aspirations of individuals and households. Our analyses are based on a primary data set of 272 smallholder farming households in rural and peri-urban Kenya. Structural Equation Modeling (SEM) results show a sig- nificant positive correlation of personality traits with aspirations (openness; extraver- sion; conscientiousness), indicating that personality structures indeed correlate with the formation of aspirations in a rural, agricultural context. Furthermore, we show that household and respondent characteristics are associated with differences in edu- cation, income, and social aspirations. Considering intrinsic factors for the prediction of human behavior has the potential to increase the efficiency of agricultural develop- ment projects and policies. We conclude that a contextualized understanding of aspi- rations can provide useful insights for development practice aiming to support small- holder farmers’ livelihoods. Keywords: Big Five, aspirations, smallholder agriculture, rural livelihoods, Kenya. JEL codes: D91, Q12. 1. INTRODUCTION The agricultural sector in sub-Saharan Africa (SSA) faces numerous pre- sent and urgent challenges that affect current farming systems (FAO, 2018; Horton et al., 2017; Rockström et al., 2009) and require sustainable solutions. http://creativecommons.org/licenses/by/4.0/legalcode 54 Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Luzia Deißler et al. Traditional development efforts often focus on increas- ing income (Frediani, 2010). However, these approaches do not always lead to success as the well-being of indi- viduals and communities is defined differently among different contexts. Income is not a goal in itself for sus- taining the needs of individuals and their families’ basic primary needs, but rather the use of it (Nathan, 2005). Instead of solely focusing on tangible resources or other traditional welfare measures, assessing people’s values and life goals to understand what drives and motivates them can provide practical insights for development research, projects and policies. Farmers’ decisions on land use and sustainable prac- tices play an important role within the current global debate on climate change and sustainability (Giampi- etri et al., 2020; Gios et al., 2022; Menozzi et al., 2015). Moreover, psychosocial constructs are frequently being referred to for the evaluation of farmers behavior and decision-making regarding development projects and policies (Chipfupa & Wale, 2018; Giampietri et al., 2020; Mekonnen & Gerber, 2017; Menozzi et al., 2015). Recently, aspirations have received more attention as an approach to gain nuanced insights into people’s life goals (Bernard & Taffesse, 2014; Horton et al., 2017), and their subsequent decision-making. Since aspirations are theorized to be highly relevant for understanding the complex livelihood decisions of farmers, they can help align project or policy implementation with farmers’ individual life goals in order to improve adoption and success. Aspirations can be viewed as drivers of a par- ticular behavior that is supposed to lead to well-being in the future (Bernard & Taffesse, 2014). They can therefore provide additional details to broaden the understanding of decision-making processes and human behavior. Amongst various external factors that inf luence the formation of aspirations (Ajzen, 1991; Bernard & Taffesse, 2014; Mausch et al., 2021; Ray, 2006), an impor- tant aspect under consideration is the impact of person- ality traits in this process (Roberts & Robins, 2000; Vis- ser & Pozzebon, 2013). Personality traits were found to have significant influence on aspirations and life goals. However, this has so far only been investigated in stud- ies in higher education settings in the global North, for example in Sweden with regard to individuals’ business perceptions (Hansson & Sok, 2021). Furthermore, their impacts on decision-making processes have also only been examined in similar settings (Buelow & Cayton, 2020; Bühler et al., 2020; Zhao & Seibert, 2006) using artificial experimental designs (Byrne et al., 2015). The correlation of aspirations with decision-making behavior in the context of countries of the global South or agri- cultural settings, however, has not been investigated yet. However, there are emerging studies which have found differences in the influence of personality and aspira- tions across different economic decisions (Knapp et al., 2021), indicating the importance of context-specific analyses. The objective of this research is the investigation of connections between the formation of aspirations and personality traits, and to evaluate the impact of socio- economic household and individual characteristics on these mechanisms. We aim to contribute to the literature on intrinsic drivers of decision-making, particularly in the context of agricultural settings in the global South. Towards this aim, we use econometric analyses of pri- mary data of smallholder farming households from rural and peri-urban Kenya. 2. THEORETICAL AND EMPIRICAL APPROACH 2.1 Aspirations Smallholder farmers face continuous and often urgent challenges (i.a. increasing pressure on food pro- duction systems, extreme weather events, land degrada- tion). Changes in livelihood strategies are not uncom- mon and contribute to risk management and increasing living standards (Ellis & Freeman, 2004). The frequently used sustainable livelihoods framework suggests numer- ous aspects that influence livelihood choices and strate- gies (Scoones, 1998). However, decisions and choices are not always the result of purely rational behavior (World Bank, 2007). Hence, not all decisions can be evaluated using standard indicators. Besides the typically con- sidered factors such as those in the livelihood frame- work, intrinsic factors have recently gained attention in explaining decision-making (Mausch et al., 2018). In the pursuit of strategies and goals, it is not only ‘hard’ external factors that determine the outcome, but also the intrinsic drivers that shape people’s goals and actions (Ajzen, 1991; Verkaart et al., 2018) as well as the effort they exert (Lybbert & Wydick, 2018). Thus, in the devel- opment context, many studies highlight the need to address aspirations and desires of farming households in the global South (Chipfupa & Wale, 2018; Lybbert & Wydick, 2018; Mausch et al., 2018; Mekonnen & Gerber, 2017; Roberts & Robins, 2000). Aspirations can be interpreted as visions for the future and include diverse, individually defined, aspects and dimensions of well-being (Bernard & Taffesse, 2014). In the broader sense, aspirations are determined and shaped by other intrinsic factors, such as mindset, per- sonal interests and skills (Mausch et al., 2018; Roberts & Robins, 2000), beliefs about the environment (Dolan 55A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 et al., 2012), and extrinsic factors such as farmer char- acteristics, household factors, access to resources, social or political conditions (Mausch et al., 2018; Mekonnen & Gerber, 2017), as well as community peers (Chipfupa & Wale, 2018). Th ese infl uences aff ect aspirations indi- rectly by shaping the aspirations window, within which individual aspirations are formed. Th e aspiration win- dow is a space of imaginable goals (Mausch et al., 2021; Ray, 2006). Bennike et al. (2020) stress the importance of imaginative horizons for the formation of the aspiration window. Th ose are aff ected by real and perceived limita- tions of specifi c outcomes in addition to the infl uence of social dynamics emerging from communities and gen- eral surroundings. Finally, the gap between a desired level and the cur- rent status of a specific welfare dimension has been defi ned as the aspiration gap which, to some degree, determines a person’s level of eff ort. Ray (2006) argues that the aspiration gap can lead to investments in the future to achieve the aspired level. If the gap is too small, it can limit motivation and investment, and progress is bound to be slower than optimal (Janzen et al., 2017). Neither should the gap be too wide, as this could induce frustration and stagnation (Janzen et al., 2017; Ray, 2006). Cognizant of this complex web of interactions that infl uence aspirations and subsequent choices and actions we conclude that aspirations shape decisions and the eff ort put in livelihood choices and thereby, are quite important for the agricultural development context. 2.2 Th eoretical framework Various theories of human behavior focus on the inf luence of numerous intercorrelated intrinsic and extrinsic factors on choices and decisions (Ajzen, 1991; Lybbert & Wydick, 2018; Ray, 2006; Sen, 1999). However, as stated by Ajzen (1991), a critical factor for someone’s actual behavior is one’s intention to act in a specifi c way. Th e ‘Th eory of Planned Behavior’ provides a wide- ly used model for explaining people’s behavior (Ajzen, 1991). Behavior, or decision making, is infl uenced by diff erent factors. Firstly, perceived behavioral control, which describes the perceived power and opportunity for someone to make a particular decision and take a corresponding action (Ajzen, 1991; Lybbert & Wydick, 2018). Secondly, subjective norms and attitudes, includ- ing societal structures and opinions on a particular topic, shape decisions. Th ese aspects have a combined impact on an individual’s intention to make a specifi c choice or whether to take or not to take a specifi c action to achieve well-being. It is notable that the drivers of intention described by Ajzen (1991) are similar to the factors shaping aspirations. Moreover, aspirations can be highly relevant for understanding the individual valua- tion of well-being, hence, the way people decide to use their resources. Since aspirations are signifi cantly associ- ated with livelihood choices (Ajzen, 1991; Mausch et al., 2018; Verkaart et al., 2018), they should be included in a framework describing individual decision-making. To shed light on the specifi c formation of choices and the interlinkage between extrinsic and intrinsic factors and their impact on well-being, aspirations and their role in livelihood strategies and decision-making play an important role. Th e fi rst step in understanding that process is refi n- ing the understanding of aspirations and their forma- tion. Figure 1 shows our conceptual framework for the formation of aspirations in the context of smallholder agriculture. External factors, such as resources and subjective norms provide the frame of the theoretically feasible, whereas individual preferences and personal- ity traits account for the intrinsic attributes. Both parts infl uence the aspiration window and subsequent forma- tion of aspirations. Additionally, besides the stated factors, there is evi- dence for a correlation between personality traits, major life goals and aspirations (Roberts & Robins, 2000; Vis- ser & Pozzebon, 2013). It was shown that personality traits can be directly linked to specifi c economic deci- sions (Zhao & Seibert, 2006). Gutman and Akerman (2008) suggest that individual self-perception infl uences aspirations, indicating a relationship between personal- ity traits and aspirations. Yet, most fi ndings are based on samples within higher education settings in the global North. Th us, examining the transferability of these fi nd- ings to agricultural households’ decision-making could provide useful insights for the application in develop- ment projects. Exploring the correlation of personality Figure 1. Conceptual framework of the formation of aspirations (Ajzen, 1991; Bernard & Taff esse, 2014; Mausch et al., 2021). 56 Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Luzia Deißler et al. traits with aspirations is a first step towards this direc- tion. Most studies rely on the Five-Factor Model or Big Five (Table 1), which is a commonly used concept for measuring personality traits (i.a. Buelow and Cayton, 2020; Bühler et al., 2020; Byrne et al., 2015; Nishimura and Suzuki, 2016; Xu, 2020). It includes aspects that capture a person’s extraversion, agreeableness, conscien- tiousness, neuroticism, and openness (McCrae & John, 1992). Although these traits are more commonly used in the global North, it was found that it can also be applied in studies in the global South such as Thailand and Viet- nam (Bühler et al., 2019, 2020). 2.3 Data Our analysis uses primary data collected as part of the Fruit Tree Portfolio (FTP) project carried out by World Agroforestry (McMullin et al., 2019). The project aimed to close seasonal dietary gaps in rural households by providing location-specific portfolios of a diversity of selected fruit trees and annual crops (McMullin et al., 2019). The data for this study was collected in 2021 across three Kenyan counties (Laikipia, Tharaka Nithi, Kitui) covering semi-arid agro-ecological zones. The total sample consisted of 272 households. The survey included general socio-economic characteristics, per- sonality traits and aspirations. Socio-economic house- hold characteristics captured the extrinsic factors stated in the theoretical framework (Chapter 2.2), covering financial-, physical-, social- and human capital (Table 2). Data on personality traits (Big Five) were collected fol- lowing the German Socio-Economic Panel (SOEP) (Cali- endo et al., 2011).1 Aspirations were captured following 1 Table A (Appendix) shows the two questions per personality trait asked within the questionnaire, following a five point Likert scale. The the methodology of (Bernard & Taffesse, 2014).2 The use of Likert scales to capture current and aspirational lev- els of income, education, and social status worked quite well in the smallholder context based on the quality of Big Five traits are then computed by adding up the Likert scale points and calculating the average score per trait. 2 The questionnaire included two questions for capturing aspirations per each welfare dimension (income, education, social status), followed by one question regarding the importance of each dimension (Table A, Appendix). First, respondents are asked to establish a scale of 1-10, 1 representing the person in their community with the lowest score and 10 representing the person with the highest score. On this scale, respondents rank themselves according to their current status. Second, respondents state the status they would like to achieve in the future (can be higher than 10). Finally, respondents rank the welfare dimensions according to their personal importance. Table 1. Description of the Big Five (Costa & McCrae, 2017; Xu, 2020). Personality traits – Big Five Openness open to new information; fantasy, feelings, actions, ideas, values Conscientiousness efficient, hardworking, organized; competence, dutifulness, achievement striving, self-discipline Extraversion outgoing and social; assertiveness, activity, excitement seeking, positive emotions Agreeableness kind, empathic, cooperative; straightforwardness, altruism, compliance, modesty Neuroticism anxiety, further negative emotions (e.g. depression, vulnerability) Table 2. Description of the variables used in the correlation analy- ses. Variable Explanation Aspirations Level of education, income and social status wanted to achieve Household characteristics total income Total monthly HH income (KW) access to credit Access to credit services farm size Size of the entire farm (acres) number of extension visits Number of extension visits during the last 12 months shocks Number of shocks experienced in the last three years (climatic, biological, economic, other) HH size Number of household nucleus members gender HH Gender of the HH head, binary (0=female, 1=male) education HH head Highest level of education achieved by the household’s head food security Number of months without enough food during the last year (using Months of Adequate Household Food Provisioning – MAHFP) Respondent characteristics gender Gender of the respondent, binary (0=female, 1=male) age Age of the respondent (in years) education Highest level of education achieved by the respondent membership Number of different groups/ organizations the respondent is a member of travel Number of travels outside of one’s own village for one month media use per week Number of times media was used during one week (television, radio, internet) 57A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 data collected. This was enabled by thorough enumerator training, which capacitated the team to facilitate a com- prehensive understanding of the scales by the smallhold- er farming respondents. The general sample characteristics are presented in Table B (Appendix). Of all households, 21% are headed by women, with the highest proportion of female-head- ed households in Laikipia at 39%. The main source of household income is wages (43%), while the usual occu- pation of the household head is casual labor, and farm- ing for the spouse. While households located in Kitui farm the biggest areas (2.35 acres), their average monthly household income is lowest with 5,648 Kenyan Shilling3. General aspirations are lowest in Kitui as well, and high- est in in Tharaka Nithi, mainly based on comparatively high educational aspirations. 2.4 Methodology Previous studies used correlation models to exam- ine the relationship between the Big Five and aspirations (Buelow & Cayton, 2020; Byrne et al., 2015; Roberts & Robins, 2000; Xu, 2020). To detangle the complex rela- tionships and to account for the intangibility of the vari- ables we performed descriptive analyses and Structural Equation Modelling (SEM) in STATA 14. 3 51.51 US Dollar based on exchange rate for time of data collection (2021) derived from World Bank 2022 (109.64). SEM allows us to treat personality traits and aspira- tions as latent variables when analyzing their relation- ship. Thus, SEM takes into account that these variables cannot be observed directly, which can lead to meas- urement errors. SEM compiles these latent variables according to their observed indicator variables (Bollen & Noble, 2011; Fan et al., 2016; Gallagher & Brown, 2013). It consists of two parts, the measurement model that contains the measurement of the latent variables (con- structs) based on their indicators (items), and the struc- tural model that describes the relationship between the latent variables (Hair et al., 2017). Each personality trait (ξa) consists of two respective indicators (xi, xj), where- as the aspirations construct consists of three indicators (xi, xj, xk). We specified the SEM model according to the literature and proxy general aspirations by education (xi), income (xj) and social aspirations (xk) (Bernard & Taffesse, 2014), while each personality trait (ξa) consists of two respective indicators (xi, xj), as described in the data section (Caliendo et al., 2011) (Figure 2). Information on the respective questions is shown in the Appendix, Table A. We used the aspirations gap as the indicator for aspirations, based on the assumption by Ray (2006) that the aspirations gap is the immediate driver of actions and decisions. We further hypothesized that the personality traits are intercorrelated with each other (indicated by the dotted line arrows). The first step is the confirmatory factor analysis (CFA) as part of the measurement model (shown exem- Aspirations artistic imagination considerate forgiving efficient thorough outgoing talkative Openness Agreeableness Conscientiousness Extraversion nervous worrying education aspirations income aspirations social aspirations Neuroticism Figure 2. Model specification of the SEM measurement and structural model. 58 Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Luzia Deißler et al. plary for a latent construct with two items): xi=λiaξa+δi, Eq. 1 xj=λjaξa+δj Eq. 2 With ξ1 as the latent variable or factor, xi/xj as the observed variable or item, λi/λj is the factor loading that represents the respective difference in the item per one unit change in the factor and δi/δj as the respective error terms of the items (Bollen & Noble, 2011). In a second step, SEM calculates the covariance between the latent variables (Bollen & Noble, 2011; Jeon, 2015), represent- ing their respective intercorrelation. The estimated coef- ficients provide information on the correlation of our variables of interest. To find and confirm external determinants of aspi- rations for contextualizing the formation of aspira- tions, we analyzed differences in variables of interest (Table 2) to examine the relationship between factors derived from previous literature and aspirations. The variables include socio-economic household character- istics such as income, access to credit, farm size, exten- sion visits, shocks, food security and household head characteristics. Further, we included variables regard- ing the respondent and account for gender, age, educa- tion, memberships in groups or organizations, travel frequency and media use. For the aspiration measure, we normalized each dimension (income, education and social status) and computed an aggregate index (Ber- nard & Taffesse, 2014). The aggregated index of the aspi- rations gap allows an assessment of the overall ambi- tions, or drive, towards achieving more in life (Bernard & Taffesse, 2014; Ray, 2006). By using the following equation (3), the values for each dimension were nor- malized to make them comparable across communities and dimensions (Bernard & Taffesse, 2014; LaRue et al., 2021): Eq. 3 With k as the respective dimension, as the value for the aspirations regarding dimension k for individual i, σk and μk as the standard deviation and the communi- ty sample mean of the values for the aspirations and as the specific weight (ranking) the respondents assigned to the respective dimension. However, we did not only use the aspiration index (Bernard & Taffesse, 2014), but also looked at income, educational and social aspirations separately (LaRue et al., 2021). This allowed us to identi- fy the importance that is placed on each dimension and shows what welfare aspects might be more important than others. We conducted Welch’s T-tests to identify significant differences between those variables regarding high or low aspirations. Aspirations were classified high or low if the values are above or below average: Low/high: Aindex<0.04 / Aindex≥0.04 Eq. 4 Aeducation≤0.01 / Aeducation>0.01 Eq. 5 Aincome≤0.01 / Aincome>0.01 Eq. 6 Asocial≤0.01 / Asocial>0.01 Eq. 7 3. RESULTS 3.1 Connection between personality, aspirations and adop- tion We investigated the correlation between personality traits and aspirations. In the following chapter we dis- cuss the association between these two intrinsic factors and its implication for the decision-making behavior of smallholder farmers in Kenya. The results from the Con- firmatory Factor Analysis (CFA) on the latent variables are presented in Table 3. They show a good fit of the measurement model for the Big Five personality traits and aspirations. The observed variables for each latent construct are statistically significant with standardized factor loadings above 0.3 (Kang & Ahn, 2021). However, the indicator questions for neuroticism did not result in a valid latent variable. Subsequently, we used the respec- tive indicator questions themselves in the following path analysis. Table 4 and Figure 3 show the estimates from the structural model which analyzed the covariance between the latent variables. Table 4 includes all theoretically possible relationships and their respective standardized correlation coefficients. Except for neuroticism, all per- sonality traits are intercorrelated. The lack of correlation here might be a result of the non-significant factor load- ings (Table 3) that indicate that the construct of neu- roticism is not identified correctly. The strongest posi- tive correlation exists between agreeableness and con- scientiousness, extraversion and conscientiousness and openness and agreeableness. The results show that three of the five personality traits significantly correlate with aspirations. Openness (0.41), conscientiousness (0.35) and extraversion (0.31) show a positive correlation coef- ficient. Furthermore, the neuroticism indicator nervous- ness, also significantly correlates with aspirations (-0.13), indicating that individuals that are prone to nervousness or anxiety are less likely to have higher aspirations. This confirms our hypothesis that intrinsic factors such as personality traits do in fact, significantly cor- relate with the formation of aspirations. Conscientious- ness is usually associated with efficient and hardwork- 59A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 ing individuals (Costa & McCrae, 2017; Xu, 2020). In relation to aspirations, the literature is inconsistent, reporting positive or insignificant correlations of con- scientiousness with (including economic) aspirations (Nishimura & Suzuki, 2016; Roberts & Robins, 2000; Visser & Pozzebon, 2013). Considering education and income aspirations as achievement-oriented goals, our results are consistent with Roberts and Robins (2000), who found high values for conscientiousness resulting in a significant effect on economic and achievement-orient- ed life goals. Moreover, the results suggest that individuals that are open to new experiences and ideas, seeking excite- ment and socially outgoing also have a higher aspira- tions gap (Costa & McCrae, 1997; Xu, 2020; Zhao & Seibert, 2006). These are characteristics that can expand a person’s aspiration window by providing information and ideas that might be passing by more close-minded individuals. Information and social networks play an important role for aspirations and in turn for livelihood choices and strategies of smallholder farming house- holds. Agreeableness and the indicators of neuroticism did not have a significant effect on farmers’ aspiration gap in our study. As described earlier, SEM offers several advantages in dealing with theoretical constructs and hypothetical relationships. On the one hand, due to the limitations of the model, only correlations could be analyzed, not causality. On the other hand, however, considering that the data were collected after the actual intervention, it is reasonable to examine only correlations, as it would have been difficult to prove causality ex post. 3.2 Correlation analysis Aspirations are not only determined by personal- ity, but also shaped by current context. We examined specific contextual variables and their correlation with educational-, income related-, and social aspirations to form a comprehensive idea of aspirations in a smallhold- er context. To this end, we examined the mean differ- ence between individuals with above-average (high) and below-average (low) aspirations. Table 5 presents the results from the correlation analyses. Educational aspirations are significantly cor- related with a higher number of extension visits, more frequent travels outside of one’s home village, smaller households, higher food security in terms of Months Table 3. Factor Loadings of Measurement Model. A. Estimates of factor loadings Factors Items Standardized factor loadings SE p-value SMC Agreeableness forgiving 0.49 0.07 <0.01 0.24 considerate 0.50 0.07 <0.01 0.25 Openness artistic 0.52 0.06 <0.01 0.27 imagination 0.80 0.07 <0.01 0.64 Conscientiousness thorough 0.40 0.07 <0.01 0.16 efficient 0.60 0.09 <0.01 0.35 Extraversion talkative 0.43 0.07 <0.01 0.18 outgoing 0.74 0.08 <0.01 0.55 Neuroticism worrying 0.48 0.55 0.38 0.23 nervous 0.80 0.89 0.37 0.63 Aspirations educ. aspirations 0.72 0.09 <0.01 0.51 inc. aspirations 0.33 0.09 <0.01 0.11 soc. aspirations 0.33 0.08 <0.01 0.11 B. Covariances of measurement error Item 1 Item 2 Standardized correlation coefficient SE p-value forgiving talkative -0.22 0.08 <0.01 imagination efficient 0.55 0.13 <0.01 worrying nervous 0.38 0.05 <0.01 Note: SMC = squared multiple correlations. Table 4. Estimates of the Structural Model. Relationship Standardized correlation coefficient SE p-value Big Five personality traits Openness ←→ Agreeableness 0.74 0.12 <0.01 Agreeableness←→ Conscientiousness 0.82 0.16 <0.01 Conscientiousness ←→ Extraversion 0.81 0.13 <0.01 Extraversion ←→ Openness 0.59 0.09 <0.01 Openness ←→ Conscientiousness 0.47 0.12 <0.01 Agreeableness ←→ Extraversion 0.95 0.16 <0.01 Personality Traits - Aspirations Openness ←→ Aspirations 0.41 0.10 <0.01 Agreeableness ←→ Aspirations 0.04 0.13 0.74 Conscientiousness ←→ Aspirations 0.35 0.13 <0.05 Extraversion ←→ Aspirations 0.31 0.11 <0.01 worrying ←→ Aspirations -0.07 0.08 0.40 nervous ←→ Aspirations -0.16 0.08 <0.10 Fit indices: c2 (p-value) = 0.1129; RMSEA = 0.031; CFI = 0.0.970; TLI = 0.947 Note: RMSEA = root mean squared error of approximation; CFI = comparative normed fit index; TLI = Tucker-Lewis index. 60 Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Luzia Deißler et al. of Adequate Household Food Provisioning (MAHFP), higher education attainment by the household head or respondent, as well as a younger respondent and a larg- er number of memberships (to groups/ organizations). In households with high educational aspirations of the respondents, human capital, proxied by information (extension visits; travels outside of the village), educa- tion, age and social networks (memberships), is signifi- cantly higher. By providing positive examples, new ideas, different experiences, or new ways of looking at things, these aspects can have an increasing impact on the for- mation of aspirations (Chipfupa & Wale, 2018). It was shown that present resources function as restraining or enhancing factors to what is achievable (Elias et al., 2018). Moreover, higher food security also seems to pro- vide a base for higher aspirations. Based on the ‘Hierar- chy of Needs’, people are more likely to aspire complex future goals if their basic primary needs are fulfilled first (Maslow, 1943). The fulfillment of immediate needs is one of the primary drivers of decisions in rural Ken- yan households (Mausch et al., 2021). Differing effects of household and respondent characteristics could there- fore be due to differences in the ability to satisfy basic needs. Not having to spend the imaginative or cogni- tive capacity on worrying about the availability of food allows individuals to aspire for more than the satisfac- tion of basic needs (Nathan, 2005). High aspirations regarding future income is associ- ated with smaller farms, higher food security (MAHFP), and younger age of respondents. However, our results suggest that the determinants of aspirations are com- plex. On the one hand, food secure farmers might have the capacity to aspire more diverse life goals (includ- ing income and education) (Nathan, 2005). On the oth- er hand, households with significantly smaller farms might rely more heavily on other income sources to cover immediate needs such as food, and with that, have higher aspirations for future income. Mausch et al. (2021) found a similar effect for households from Tur- kana (Kenya) that is characterized by difficult agricul- tural and economic conditions, where decision-making is based on the satisfaction of immediate needs rather than on the fulfillment of specific aspirations. Similar to educational aspirations, younger respondents also have higher income aspirations, in line with a previous study on aspirations in rural Kenya (LaRue et al., 2021). People at an older age may already have reached a considerable level of education and income. Therefore, aspirations for further increases may be lower than for people who have not yet reached a certain level of relative prosperity. Social aspirations appear to depend mostly on resources and household characteristics. They are posi- tively associated with agricultural training, travelling outside of the village and more frequent media use. Social aspirations can be linked with a broader infor- mation network and higher exposure to peers (Chipfu- pa & Wale, 2018). Furthermore, respondents in house- holds that are worse off regarding the education level of the household head, food security (MAHFP), farm size and have experienced a higher number of shocks, Figure 3. Path diagram presenting the estimated covariance coefficients from the structural model. Aspirations Openness Agreeableness Conscientiousness Extraversion nervous worrying 0.41*** 0.31*** 0.04 0.35*** -0.07 -0.16* 0.59*** 0.74*** 0.82*** 0.81*** 0.95*** 0.47*** 61A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 have higher social aspirations than their counterparts. In fact, one would expect that households that are more disadvantaged would also be more likely to focus on their immediate needs than on the pursuit of social status. Nonetheless, the complexity of the formation of aspirations suggests that greater exposure to peers and information may also override the focus on immedi- ate needs. Additionally, households within which the respondent stated high social aspirations are more likely to be female headed. It is notable that the three dimensions show differ- ent combinations of their determining factors. Some of these factors might not directly determine or con- trol aspirations, they do however, limit them (Nathan, 2005). The aggregate aspiration index (Table 6) shows consistent negative association of farm size and consist- ent positive effects of agricultural training and experi- ences of shocks with above average aspirations. Moreo- ver, respondents from female headed households in gen- eral, show higher aspirations. Nevertheless, the effects differ across the factors and dimensions of aspirations under consideration. Our results suggest that aggregating diverse direc- tions of aspirations may mask individual differences in the importance of aspects of well-being based on dif- fering backgrounds and preferences. Effects and prefer- ences can overlap and influence each other at the indi- vidual level, but also interact within the household and the wider community. While income aspirations may be seen as part of basic human needs, social aspirations can be considered a human need higher up the “Hierarchy of Needs”, which only comes into focus once the first basic needs have been satisfactorily fulfilled. Thus, the aggre- gate aspiration index could be a useful tool for assess- ing the general attitude towards the future, as well as the individual’s agency and proactivity. However, when it comes to identifying specific socioeconomic charac- teristics that play a role in the formation of aspirations, looking at the individual aspiration dimensions is more likely to lead to a clearer picture. 4. CONCLUSION We identified the role that personality traits as intrinsic factors play for the formation of aspirations and examined the influence of socio-economic house- hold characteristics as control variables in this process. Table 5. T-Test/Mann-Whitney results on household and individual characteristics of respondents with below or above average aspirations. Variables Education Aspirations Income Aspirations Social Aspirations low high mean diff. low high mean diff. low high mean diff. Extrinsic factors monthly HH income (KSh) 5898 5897 -0.10 5739 6023 284.1 6066 5738 -328.0 access to credit 0.62 0.66 0.04 0.67 0.62 -0.06 0.67 0.62 -0.05 farm size (ac) 1.96 1.83 -0.13 2.16 1.69 -0.46*** 2.07 1.73 -0.34** agric. training 0.57 0.65 0.08 0.60 0.61 0.01 0.52 0.70 0.18*** extension visits 0.68 1.06 0.38* 0.79 0.94 0.15 0.85 0.90 0.05 travel 5.55 7.56 2.01** 5.85 7.16 1.31 5.86 7.25 1.39* shocks 1.11 1.18 0.07 1.08 1.20 0.12 1.04 1.25 0.21** Household characteristics HH size 6.17 5.33 -0.84*** 5.76 5.72 -0.03 5.65 5.82 0.17 gender head 0.79 0.78 -0.01 0.76 0.82 0.06 0.83 0.75 -0.08* education head 3.24 3.54 0.30* 3.46 3.35 -0.11 3.60 3.20 -0.39** MAHFP 9.45 9.94 0.50* 9.36 9.98 0.62** 10.0 9.39 -0.65** Respondent characteristics gender resp. 0.26 0.23 -0.03 0.26 0.23 -0.03 0.25 0.23 -0.02 age resp. 47.4 43.5 -3.96** 47.0 44.2 -2.75* 44.8 46.1 1.28 education resp. 3.16 3.46 0.30* 3.29 3.33 0.03 3.27 3.35 0.08 membership 1.01 1.16 0.14* 1.12 1.06 -0.06 1.11 1.07 -0.03 media use 9.54 9.62 0.09 9.33 9.78 0.44 9.04 10.1 1.05* Note: Low and high refer to below and above average aspirations. T-test/Welch mean differences are displayed. *** p<0.01, ** p<0.05, * p<0.1. HH = household, KSh = Kenya Shilling, MAHFP = Months of Adequate Household Food Provisioning. 62 Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Luzia Deißler et al. The aim of our research was to gain insights into the intrinsic influences of smallholder farmers’ aspirations towards an improved understanding of their decision- making. We provide insights for agricultural develop- ment projects and policies to understand the under- lying mechanisms of decision-making. Ensuring the alignment of project goals with individual goals could significantly change adoption dynamics and the iden- tification of clusters that could best utilize specific sup- port mechanisms such as sustainable agricultural prac- tices (integrating trees in farming systems, crop rotation and irrigation schemes). We found that three of the five investigated personality traits indeed significantly corre- late with aspirations. These traits paint a picture of per- sonality structures that might be conducive to high aspi- rations while facilitating the basis for proactive behavior. Open-minded, socially outgoing and conscientious indi- viduals will most likely have higher aspirations, which in turn can lead to higher susceptibility to novel technolo- gies and approaches. Nevertheless, extrinsic factors also play an impor- tant role in this system. Our results suggest that dif- ferent types of aspirations (e.g. education, income) are connected to different factors (e.g. food security, household size, age, group membership), indicating that understanding these differences with regard to the direction of aspirations is crucial. Moreover, most of the determining factors derived from the literature are rather inconsistent across settings. Therefore, it is nec- essary to contextualize methods and results in order to understand the process, which we aimed to contrib- ute to by focusing on an agricultural setting within the global South. While social and human capital interact positively with educational and social aspirations, pov- erty is an essential factor that was found to shift the focus from complex future aspirations towards the sat- isfaction of immediate needs. This may warrant future research as it relates to different target groups for agri- cultural development efforts and could add to a more differentiated approach for the poorest segments as compared to those slightly better off. Analyzing aspirations and different livelihood strat- egies prior to the design of agricultural development projects and policies can improve the suitability of these interventions for the target group. Research and projects must acknowledge that there is no ‘one size fits all’ solu- tion for development. Individuals interact differently with opportunities and propositions based on their individual aspirations. For example, more introverted people, who may also have lower aspirations, might not only be more difficult to reach, but also need tailored interaction and support to realize and seize opportuni- ties. Whereas achievement-oriented, outgoing individu- als are more likely to need less support to adopt new approaches. Future research needs to explore these complex connections in more detail, using quantitative meth- ods to examine context specific correlations. This pro- cess could also be extended towards actual behavior, by assessing real life responses to interventions. By doing so, the role of personality traits and aspirations in a concrete context could be identified, further deepening the understanding of behavior in the agricultural devel- opment context, for achieving positive and sustainable livelihoods and well-being outcomes for smallholder farmers in the global South. REFERENCES Ajzen, I. (1991). The Theory of Planned Behavior. Organi- zational Behavior and Human Decision Processes, 50, 179–211. https://doi.org/10.1080/10410236.2018.1493 416 Table 6. T-Test/Mann-Whitney results on household and individual characteristics of respondents with below or above average aspira- tions. Variables Aspiration index < average > average mean diff. Extrinsic factors monthly HH income (KSh) 5899 5896 -3.539 access to credit 0.66 0.62 -0.04 farm size (ac) 2.05 1.68 -0.37** agric. training 0.58 0.65 0.07* number of extension visits 0.75 1.03 0.28 travel 6.52 6.67 0.15 shocks 1.05 1.28 0.23** Household characteristics HH size 5.74 5.74 0.00 gender HH head 0.82 0.75 -0.07* education HH head 3.51 3.24 -0.27 MAHFP 9.69 9.72 0.03 Respondent characteristics gender respondent 0.26 0.21 -0.05 age respondent 46.0 44.6 -1.34 education respondent 3.30 3.33 0.03 membership 1.10 1.08 -0.02 media use 9.23 10.06 0.83 Note: T-test/Welch mean differences are displayed. *** p<0.01, ** p<0.05, * p<0.1. HH = household, KSh = Kenya Shilling, MAHFP = Months of Adequate Household Food Provisioning. 63A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Bennike, R. B., Rasmussen, M. B., & Nielsen, K. B. (2020). Agrarian crossroads: rural aspirations and capitalist transformation. Canadian Journal of Devel- opment Studies, 41(1), 40–56. https://doi.org/https:// doi.org/10.1080/02255189.2020.1710116 Bernard, T., & Taffesse, A. S. (2014). Aspirations: An Approach to Measurement with Validation Using Ethiopian Data. Journal of African Economies, 23(2), 189–224. https://doi.org/https://doi.org/10.1093/jae/ ejt030 Bollen, K. A., & Noble, M. D. (2011). Structural equation models and the quantification of behavior. Proceed- ings of the National Academy of Sciences of the United States of America, 108(SUPPL. 3), 15639–15646. htt- ps://doi.org/10.1073/pnas.1010661108 Buelow, M. T., & Cayton, C. (2020). Relationships between the big five personality characteristics and performance on behavioral decision making tasks. Personality and Individual Differences, 160, 109931. https://doi.org/10.1016/J.PAID.2020.109931 Bühler, D., Sharma, R., & Stein, W. (2019). Personality traits in Southeast Asia: Evidence from rural Thailand and Vietnam (WP-014; TVSEP Working Paper). Bühler, D., Sharma, R., & Stein, W. (2020). Validation of the Big Five model in rural developing economies – Evidence from Thailand and Vietnam (WP-021; TVS- EP Working Paper). Byrne, K. A., Silasi-Mansat, C. D., & Worthy, D. A. (2015). Who chokes under pressure? The Big Five personality traits and decision-making under pres- sure. Personality and Individual Differences, 74, 22–28. https://doi.org/10.1016/J.PAID.2014.10.009 Caliendo, M., Fossen, F. M., & Kritikos, A. S. (2011). Per- sonality Characteristics and the Decision to Become and Stay Self-Employed (No. 369; SOEPpapers on Multidisciplinary Panel Data Research). www.diw.de Chipfupa, U., & Wale, E. (2018). Explaining smallholder aspirations to expand irrigation crop production in Makhathini and Ndumo-B, KwaZulu-Natal, South Africa. Agrekon, 57(3–4), 284–299. https://doi.org/ https://doi.org/10.1080/03031853.2018.1531773 Costa, P. T., & McCrae, R. (1997). Personality Trait Struc- ture as a Human Universal. American Psychologist, 52, 587–596. Costa, P. T., & McCrae, R. (2017). The NEO Inven- tories as Instruments of Psychological Theory. In T. A. Widiger (Ed.), The Oxford Handbook of the Five Factor Model (pp. 11–38). Oxford Uni- versity Press. https://doi.org/10.1093/OXFORD- HB/9780199352487.013.10 Dolan, P., Hallsworth, M., Halpern, D., King, D., Met- calfe, R., & Vlaev, I. (2012). Influencing behaviour: The mindspace way. Journal of Economic Psychol- ogy, 33(1), 264–277. https://doi.org/https://doi. org/10.1016/j.joep.2011.10.009 Elias, M., Mudege, N., Lopez, D. E., Najjar, D., Kandiwa, V., Luis, J., Yila, J., Tegbaru, A., Ibrahim, G., Bad- stue, L., & Njuguna-mungai, E. (2018). Gendered aspirations and occupations among rural youth, in agriculture and beyond: A cross-regional prescrip- tive. Journal of Gender, Agriculture and Food Security, 3(1), 82–107. https://doi.org/https://doi.org/10.19268/ JGAFS.312018.4 Ellis, F., & Freeman, H. A. (2004). Rural Livelihoods and Poverty Reduction Strategies in Four African Coun- tries. Journal of Development Studies, 40(4), 1–30. htt- ps://doi.org/10.1080/00220380410001673175 Fan, Y., Chen, J., Shirkey, G., John, R., Wu, S. R., Park, H., & Shao, C. (2016). Applications of structural equation modeling (SEM) in ecological studies: an updated review. In Ecological Processes (Vol. 5, Issue 1). Springer Verlag. https://doi.org/10.1186/s13717- 016-0063-3 FAO. (2018). The future of food and agriculture – Alterna- tive pathways to 2050. Food and Agriculture Organi- zation. Frediani, A. A. (2010). Sen’s capability approach as a framework to the practice of development. Devel- opment in Practice, 20(2), 173–187. https://doi. org/10.1080/09614520903564181 Gallagher, M. W., & Brown, T. A. (2013). Introduction to Confi rmatory Factor Analysis and Structural Equa- tion Modeling. In T. Teo (Ed.), Handbook of Quan- titative Methods for Educational Research (pp. 289– 314). Sense Publishers. Giampietri, E., Yu, X., & Trestini, S. (2020). The role of trust and perceived barriers on farmer’s intention to adopt risk management tools. Bio-Based and Applied Economics, 9(1), 1–24. https://doi.org/10.13128/bae- 8416 Gios, G., Farinelli, S., Kheiraoui, F., Martini, F., & Orlan- do, J. G. (2022). Pesticides, crop choices and changes in wellbeing. Bio-Based and Applied Economics, 11(2), 171–184. https://doi.org/10.36253/bae-10310 Gutman, L. M., & Akerman, R. (2008). Determinants of aspirations. In Centre for Research on the Wider Ben- efits of Learning Research Report (Issue June). http:// eprints.ioe.ac.uk/2052/ Hair, J. F. 1944-, Hult, G. T. M. 1967-, Ringle, C. M. 1974-, Sarstedt, M. 1979-, Richter, N. F., Hauff, S., & Verlag Franz Vahlen GmbH. (2017). Partial Least Squares Strukturgleichungsmodellierung (PLS-SEM). Eine anwendungsorientierte Einführung. Verlag Franz Vahlen . 64 Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Luzia Deißler et al. Hansson, H., & Sok, J. (2021). Perceived obstacles for business development: Construct development and the impact of farmers’ personal values and personal- ity profile in the Swedish agricultural context. Journal of Rural Studies, 81, 17–26. https://doi.org/10.1016/j. jrurstud.2020.12.004 Horton, P., Banwart, S. A., Brockington, D., Brown, G. W., Bruce, R., Cameron, D., Holdsworth, M., Lenny Koh, S. C., Ton, J., & Jackson, P. (2017). An agenda for integrated system-wide interdisciplinary agri-food research. Food Security, 9(2), 195–210. https://doi. org/https://doi.org/10.1007/s12571-017-0648-4 Janzen, S. A., Magnan, N. P., Sharma, S., & Thompson, W. M. (2017). Aspirations failure and formation in rural Nepal. Journal of Economic Behavior and Organization, 139, 1–25. https://doi.org/10.1016/j. jebo.2017.04.003 Jeon, J. (2015). The Strengths and Limitations of the Sta- tistical Modeling of Complex Social Phenomenon: Focusing on SEM, Path Analysis, or Multiple Regres- sion Models. International Journal of Economics and Management Engineering, 9(5), 1634–1642. https:// doi.org/https://doi.org/10.5281/zenodo.1105869 Kang, H., & Ahn, J. W. (2021). Model Setting and Inter- pretation of Results in Research Using Structural Equation Modeling: A Checklist with Guiding Ques- tions for Reporting. In Asian Nursing Research (Vol. 15, Issue 3, pp. 157–162). Korean Society of Nursing Science. https://doi.org/10.1016/j.anr.2021.06.001 Knapp, L., Wuepper, D., & Finger, R. (2021). Preferences, personality, aspirations, and farmer behavior. Agricul- tural Economics (United Kingdom), 52(6), 901–913. https://doi.org/10.1111/agec.12669 LaRue, K., Daum, T., Mausch, K., & Harris, D. (2021). Who Wants to Farm? Answers Depend on How You Ask: A Case Study on Youth Aspirations in Kenya. European Journal of Development Research, 0123456789. https:// doi.org/10.1057/s41287-020-00352-2 Lybbert, T. J., & Wydick, B. (2018). Poverty, aspirations, and the economics of hope. Economic Development and Cultural Change, 66(4), 709–753. https://doi. org/10.1086/696968 Maslow, A. H. (1943). Motivation and personality. Harper and Row. Mausch, K., Harris, D., Dilley, L., Crossland, M., Pagella, T., Yim, J., & Jones, E. (2021). Not all about farm- ing: capturing aspirations can be a challenge to rural development assumptions. European Journal of Development Research, 0123456789. https://doi. org/10.1057/s41287-021-00398-w Mausch, K., Harris, D., Heather, E., Jones, E., Yim, J., & Hauser, M. (2018). Households’ aspirations for rural development through agriculture. Outlook on Agri- culture, 47(2), 108–115. https://doi.org/https://doi. org/10.1177/0030727018766940 McCrae, R., & John, O. P. (1992). An Introduction to the Five‐ Factor Model and Its Applications. Journal of Personality, 60(2), 175–215. https://doi.org/10.1111/J.1467-6494.1992. TB00970.X/FORMAT/PDF McMullin, S., Njogu, K., Wekesa, B., Gachuiri, A., Ngethe, E., Stadlmayr, B., Jamnadass, R., & Kehlen- beck, K. (2019). Developing fruit tree portfolios that link agriculture more effectively with nutrition and health: a new approach for providing year-round micronutrients to smallholder farmers. Food Secu- rity, 11(6), 1355–1372. https://doi.org/https://doi. org/10.1007/s12571-019-00970-7 Mekonnen, D. A., & Gerber, N. (2017). Aspirations and food security in rural Ethiopia. Food Security, 9(2), 371–385. https://doi.org/https://doi.org/10.1007/ s12571-017-0654-6 Menozzi, D., Fioravanzi, M., & Donati, M. (2015). Farm- er’s motivation to adopt sustainable agricultural prac- tices. Bio-Based and Applied Economics, 4(2), 125– 147. https://doi.org/10.13128/BAE-14776 Nathan, D. (2005). Capabilities and Aspirations. Econom- ic and Political Weekly, 40(1), 36–40. http://www.jstor. org/stable/4416008 Nishimura, T., & Suzuki, T. (2016). Aspirations and life satisfaction in Japan: The big five personality makes clear. Personality and Individual Differences, 97, 300– 305. https://doi.org/10.1016/j.paid.2016.02.070 Ray, D. (2006). Aspirations, Poverty and Economic Change. In A. V. Banerjee, R. Benabou, & D. Mookherjee (Eds.), Understanding Poverty. Oxford University Press. https:// doi.org/https://doi.org/10.1093/0195305191.003.0028 Roberts, B. W., & Robins, R. W. (2000). Broad disposi- tions, broad aspirations: The intersection of personal- ity traits and major life goals. Personality and Social Psychology Bulletin, 26(10), 1284–1296. https://doi. org/10.1177/0146167200262009 Rockström, J., W. Steffen, K. Noone, Å. Persson, F. S. Chap- in, E. F. Lambin, T. M. Lenton, M. Scheffer, C. Folke, H. J. Schellnhuber, B. Nykvist, C. A. de Wit, T. Hughes, S. van der Leeuw, H. Rodhe, S. Sörlin, P. K. Snyder, R. Costanza, U. Svedin, … J. A. Foley. (2009). A safe oper- ation space for humanity. Nature, 461(September), 472– 475. https://doi.org/https://doi.org/10.1038/461472a Scoones, I. (1998). Sustainable Rural Livelihoods: A Framework for Analysis (No. 72; IDS Working Paper). IDS. https://opendocs.ids.ac.uk/opendocs/han- dle/20.500.12413/3390 Sen, A. (1999). Development as Freedom. In J. T. Roberts, Am. B. Hite, & N. Chorev (Eds.), The Globalization 65A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 and Development Reader. Perspectives on Development and Global Change (2nd ed., pp. 525–548). Wiley Blackwell. Verkaart, S., Mausch, K., & Harris, D. (2018). Who are those people we call farmers? Rural Kenyan aspira- tions and realities. Development in Practice, 28(4), 468–479. https://doi.org/https://doi.org/10.1080/0961 4524.2018.1446909 Visser, B. A., & Pozzebon, J. A. (2013). Who are you and what do you want? Life aspirations, personal- ity, and well-being. Personality and Individual Dif- ferences, 54(2), 266–271. https://doi.org/10.1016/j. paid.2012.09.010 World Bank. (2007). World Development Report 2008: Agriculture for Development. https://openknowledge. worldbank.org/handle/10986/5990 License: CC BY 3.0 IGO Xu, H. (2020). Big Five Personality Traits and Ambigu- ity Management in Career Decision-Making. Career Development Quarterly, 68(2), 158–172. https://doi. org/10.1002/cdq.12220 Zhao, H., & Seibert, S. E. (2006). The big five personality dimensions and entrepreneurial status: A meta-ana- lytical review. Journal of Applied Psychology, 91(2), 259–271. https://doi.org/10.1037/0021-9010.91.2.259 66 Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Luzia Deißler et al. APPENDIX Table A. Questionnaire sections on personality traits and aspirations. Variable Question Scale Aspirations social status present Imagine the person with the highest level of social status in your community, this represents a 10. The one with the lowest level of social status in the community is represented with a 1. What is the level of social status that you have at present? (on the scale from 1-10) self-set scale (1-10) social aspirations What is the level of social status that you would like to achieve? (could be higher than 10) self-set scale (starting with 1) income present Imagine the person with the highest level of income in your community, this represents a 10. The one with the lowest income in the community is represented with a 1. What is the level of income that you have at present? (on the scale from 1-10) self-set scale (1-10) income aspirations What is the level of income that you would like to achieve? (could be higher than 10) self-set scale (starting with 1) education present Imagine the person with the highest level of education in your community, this represents a 10. The one with the lowest education in the community is represented with a 1. What is the level of education that you have at present? (on the scale from 1-10) self-set scale (1-10) education aspirations What is the level of education that you would like to achieve? (could be higher than 10) self-set scale (starting with 1) Ranking of the three dimensions We have asked you about three dimensions - income, social status and education. Now I would like you to tell me which of these three dimensions are the most important for you. Please assort 20 beans to the three dimensions, according to their importance for you. No beans assorted to a dimension means this dimension is of no importance for you. The more beans you assort to one dimension, the more important. rank_in How many beans would you allot for annual income? number (0-20) rank_soc How many beans would you allot for social status? number (0-20) rank_ed How many beans would you allot for education? number (0-20) Big Five Do you see yourself as someone who… bf1 … works thoroughly? Likert scale (1-5) bf2 … is talkative? Likert scale (1-5) bf3 … worries a lot? Likert scale (1-5) bf4 … has a forgiving nature? Likert scale (1-5) bf5 … is outgoing, sociable? Likert scale (1-5) bf6 … gets nervous easily? Likert scale (1-5) bf7 … values artistic, aesthetic experiences? Likert scale (1-5) bf8 … is considerate and kind to almost everyone? Likert scale (1-5) bf9 … does tasks efficiently? Likert scale (1-5) bf10 … has an active imagination? Likert scale (1-5) Note: Own Source. Survey 2021. 67A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Bio-based and Applied Economics 12(1): 53-67, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13475 Table B. Characteristics of the 272 sample households. VARIABLE LAIKIPIA (N=93) THARAKA NITHI (N=89) KITUI (N=90) Total (N=272) Mean SD Mean SD Mean SD Mean SD Household head and respondent characteristics gender HH head (% female) 0.39 0.49 0.12 0.33 0.11 0.32 0.21 0.41 age HH head 51.3 14.0 47.0 13.7 50.8 13.2 49.7 13.7 main occupation HH head farming casual labor casual labor casual labor education HH head 3.24 1.47 3.62 1.60 3.29 1.67 3.40 1.59 gender resp. (% female) 0.75 0.43 0.77 0.42 0.74 0.44 0.24 0.43 age respondent 46.5 13.5 42.5 13.4 47.3 13.6 45.4 13.6 occupation respondent farming farming farming farming education respondent 3.17 1.53 3.42 1.60 3.31 1.57 3.31 1.56 Household characteristics HH size 5.88 2.96 5.21 2.23 6.18 2.56 5.74 2.65 number of children 3.19 2.15 2.31 1.27 2.86 1.59 2.79 1.75 farm size (ac) 1.78 1.28 1.56 1.26 2.35 1.76 1.90 1.48 monthly HH income (KSh) 5950 3407 6093 3556 5648 3770 5898 3580 main income source wage (43.2 %) wage (32.9%) wage (51.8%) wage (42.6%) MAHFP 8.84 3.72 10.50 2.92 9.79 2.62 9.71 3.02 number of extension visits 0.97 2.25 1.17 2.45 0.49 1.02 0.87 2.02 number of shocks (last 3 yrs) 1.16 1.03 1.06 0.97 1.23 0.82 1.15 0.94 Decision-making agricultural head joint joint head market head joint joint joint livestock head joint head head income off farm business head head joint head income employment head joint joint joint major expenditures head joint joint head minor expenditures head spouse spouse spouse loans head joint joint joint Respondent characteristics access to credit 0.61 0.49 0.67 0.47 0.65 0.48 0.64 0.48 number of days travelled outside of the village (for one month) 3.89 4.91 8.06 9.91 7.91 10.1 6.58 8.81 number of memberships 0.96 0.84 1.03 0.74 1.28 0.78 1.09 0.80 Aspirations education aspirations -0.01 0.29 0.04 0.27 0.01 0.23 0.01 0.26 income aspirations 0.00 0.34 0.02 0.34 0.01 0.33 0.01 0.34 social aspirations 0.03 0.36 0.02 0.20 -0.01 0.23 0.01 0.23 aspiration index 0.02 0.61 0.08 0.56 0.01 0.51 0.03 0.56 Personality Traits (Big Five) agreeableness 4.42 0.77 4.34 0.63 4.71 0.64 4.41 0.76 openness 3.70 0.98 3.70 0.92 4.29 0.89 3.88 0.99 conscientiousness 4.23 0.73 4.49 0.61 4.59 0.66 4.42 0.73 extraversion 3.83 1.02 4.00 0.89 4.24 0.96 4.01 1.00 neuroticism 2.54 1.04 2.63 1.00 2.42 1.05 2.52 1.04 Note: Own source. Farmers’ motivations and behaviour regarding the adoption of more sustainable agricultural practices and activities Linda Arata1, Davide Menozzi2 How do farmers’ pluriactivity projects evolve? How do farmers’ pluriactivity project evolve? Clarisse Ceriani*, Amar Djouak, Marine Chaillard Heterogeneity of adaptation strategies to climate shocks: Evidence from the Niger Delta region of Nigeria Chinasa Sylvia Onyenekwe1, Patience Ifeyinwa Opata1, Chukwuma Otum Ume1,*, Daniel Bruce Sarpong2, Irene Susana Egyir2 Organic cocoa farmer’s strategies and sustainability Ibrahim Prazeres1,*, Maria Raquel Lucas1, Ana Marta-Costa2, Pedro Damião Henriques3 A complex web of interactions: Personality traits and aspirations in the context of smallholder agriculture Luzia Deißler1,*, Kai Mausch2, Alice Karanja3, Stepha McMullin3, Ulrike Grote1 Exploring the effectiveness of serious games in strengthening smallholders’ motivation to plant different trees on farms: evidence from rural Rwanda Ronja Seegers*, Etti Winter, Ulrike Grote